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DISCOVERING BIOMARKERS OF PAINFUL INFLAMMATORY
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PATRICIA ELIZA DE ALMEIDA

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DISCOVERING BIOMARKERS OF PAINFUL INFLAMMATORY FOOT LESIONS
IN LAME DAIRY CATTLE

By

Patricia Eliza de Almeida

A DISSERTATION
Submitted to
Michigan State University

in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHYLOSOPHY
Department of Animal Science

2006

ABSTRACT
DISCOVERING BIOMARKERS OF PAINFUL INFLAMMATORY FOOT LESIONS
IN LAME DAIRY CATTLE
By

Patricia Eliza de Almeida

Lameness is a principal health issue and probably the single most common cause
of distress in dairy cattle. Current methods used for screening lameness rely on
qualitative scoring systems that are time-consuming, unreliable, non-sensitive, and
require great skill on the part of the herdsman. This dissertation encompasses a series of
studies aimed to discover biomarkers to assist with diagnosis of painful inﬂammatory
foot lesions in lame dairy cows.

The ﬁrst study investigated the use of a pressure plate for early detection of
lameness. Peak vertical force (PVF) was measured using a pressure plate on 7 Holstein
heifers that were deemed sound, on the basis of a subjective lameness scoring system.
Feet were then inspected during trimming and revealed no lesions in 3 heifers and hairy
heel wart (HHW) lesions in the other 4 heifers. Sound heifers demonstrated signiﬁcantly
higher PVF (5.32 :l: 0.62N.kg"; P = 0.01) and better right-left hindlimb PVF symmetry
(1.04 :I: 0.02; P = 0.03) than those with HHW (3.64 .1: 0.82 N.kg'l and 0.77 :I: 0.16). Thus,
a pressure plate was sensitive to detect gait abnormalities in heifers with HHW lesions
that were undiagnosed by subjective means.

In the second study, blood serum and peripheral blood mononuclear cells (PBMC)

were collected from 8 lame (i.e., inﬂammatory foot lesions and sickness behaviors) and 8

sound Holstein cows. The abundance of IL-lB, MMP-9, L—selectin, GRa and POMC was
investigated in PBMCs via absolute quantitative real-time RT-PCR. Serum cortisol and
dehydroepiandrosterone (DHEA) concentrations were also measured. Lame cows
demonstrated a 23% decrease in serum DHEA (P = 0.01), a 79% increase in cortisol (P =
0.10), and a 65% higher cortisol:DHEA ratio (P = 0.06) compared to sound cows. No
differences in PBMC expression of the candidate genes were found.

In the third study, BOTLS microarrays were interrogated with the PBMCs cDNA
samples from previous study in an 8-array balanced design. Samples from one lame and
one sound cow were directly compared with each other on individual arrays. Statistical
analysis of the resulting ﬂuorescence intensity data revealed 31 putatively differentially
expressed genes in lame versus sound cows (P < 0.05). Validation of 15 of these genes,
whose protein products are known to be important in immune response, inﬂammation,
and pain, was carried out using relative quantitative real-time RT-PCR. Up regulation (P
S 0.05), expressed as fold increase (:t SEM) in lame relative to sound cows, was
conﬁrmed for IL-2 (12.68 i 1.47), IL-10 (2.39 :I: 0.55), MMP-l3 (10.44 :t 1.14), and
CCR5 (5.26 :t: 1.05) gene expression. Similarly, GM-CSF-R-alpha (2.30 :t 0.63) and IL-4
(2.06 :t 0.59) gene expression showed a tendency (P = 0.10) for up regulation in lame
compared to sound cows.

In addition to vertical ground reaction force measured by pressure plate and
circulating levels of DHEA and cortisol:DHEA ratio, PBMC co-expression of the genes
mentioned above appear to be promising potential biomarkers for diagnosis of painful
inﬂammatory foot lesions in lame dairy cattle. Further studies should verify the

universality and clinical utility of these results.

Copyright by
PATRICIA ELIZA DE ALMEIDA
2006

To my parents Maria Eliza and Fernando and my brother Daniel

ACKNOWLEDGEMENTS

First of all, I would like to acknowledge my family for unconditional support and
love which gave me the strength to endure all these years of hard work, loneliness,
sometimes despair and others happiness. Without you I would never be able to achieve
this degree and to learn so much about compassion, honesty, generosity, altruism,
unconditional friendliness and love.

Secondly, I would like to acknowledge the Animal Behavior and Welfare Group,
who opened the doors that led me to this doctorate program and believed in my potential
as a researcher. We went through a ‘roller-coaster’ of events and difﬁculties throughout
the years and, although some events were harsh and painful, they certainly inspired me
with personal and professional growth, and made me value the importance of intellectual
collaboration, leadership, good communication, and organization.

My committee - Drs. Jeanne Burton, Bernadette Earley, Robert Tempelman,
Michael Orth and Deborah Wilson — You were essential to the outcome of my program.
It was a delightful inspiration to work with all of you. I especially would like to thank
Drs. Burton and Barley for the thorough revisions of my manuscripts and for being the
ﬁrst and second readers of this dissertation, and Dr. Orth for agreeing to participate on
my committee at such a crucial stage.

The Immunogenetics laboratory — Drs. Jeanne Burton and Patty Weber, Rachael
Kruska, Kelly Buckam and David Thompson — You not only taught and assisted me with

the laboratory work of my research, but also inspired and showed me the meaning of a

vi

good working environment and its importance for both creation and development of good
quality research.

Sometimes life brings us unexpected surprises, the best surprise of all during my
Ph.D. program was to have met the two most important role models of my professional
career — Drs. Jeanne Burton and Patty Weber. You were not only my intellectual mentors,
but also became my friends. I will never forget what you did for me; it would be literally
impossible to have completed this program without you. You were responsible for a
signiﬁcant transformation in my life because you taught me about the importance of
having self-conﬁdence. Thank you so much for being part of my life!

Finally, I would like to thank my friends who believed and supported me
throughout these years - Denise E. de Almeida, Andrea Polachini de Oliveira, Marcelo
Hemandes, David Mullineaux, and Juan Pedro Steibel. You are and always will be very
special to me because of your generosity, understanding, and compassion.

This program was not about success and prestige but about learning from
mistakes and standing up after falls with the help of the great people that I mentioned

above.

“Out beyond the ideas of right and wrong, there is aﬁeld. I'll meet you there. ” -

Mowlana Jalaluddin Rurni.

vii

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. x
LIST OF FIGURES ........................................................................................................ vii
LIST OF ABBREVIATIONS .................................................................. xv
INTRODUCTION .................................................................................. 1
CHAPTER ONE .................................................................................... 7
A REVIEW OF THE LITERATURE ............................................................. 7
I. LAMENESS IN DAIRY CATTLE ............................................................. 8

A. Pain and welfare .............................................................................. 10

B. Economic impacts ............................................................................ 12

C. Epidemiological considerations ............................................................. 20

D. Treatment .................................................................................... 23

II. LAMENESS ASSESSMENT IN DAIRY CATTLE ....................................... 24
A. Qualitative lameness assessment ......................................................... 24

B. Quantitative lameness assessment ........................................................ 28

i. Kinematics ................................................................................. 28

ii. Kinetics .................................................................................. 30

III. SICKNESS RESPONSE ...................................................................... 36
A. Mediators of the HPA responses to acute immune insults .......................... 38

B. Mechanism f cytokine activation of the HPA axis ................................... 40

C. HPA mediated changes in the immune system ....................................... 41

D. Pro-algesic versus analgesic actions of immune cells ................................ 47

IV. DIAGNOSTIC BIOMARKERS OF DISEASE .......................................... 50

A. Biomarker discovery ...................................................................... 51

B. Biomarker validation ..................................................................... 53

C. Issues with biomarker research .......................................................... 53

V. DISSERTATION’S HYPOTHESES ......................................................... 55
CHAPTER TWO ................................................................................. 56

EARLY DETECTION OF LAMENESS IN HEIFERS WITH HAIRY HEEL WARTS
USING A PRESSURE PLATE

I. ABSTRACT .................................................................................... 56
II. INTRODUCTION ...................................................................................................... 56
III. MATERIALS AND METHODS ............................................................ 58
IV. RESULTS ........................................................................................ 60
V. DISCUSSION .................................................................................. 60
VI. CONCLUSION AND ANIMAL WELFARE IMPLICATIONS ........................ 62
CHAPTER THREE .............................................................................. 64

viii

DEPRESSED DHEA AND INCREASED SICKNESS RESPONSE BEHAVIORS IN
LAME DAIRY COWS WITH INFLAMMATORY FOOT LESIONS.

1. ABSTRACT ..................................................................................... 65
II. INTRODUCTION .............................................................................. 66
III. MATERIALS AND METHODS .............................................................. 69
A. Subjects ................................................................................... 69

B. Blood collections and isolation of serum and PBMCs ............................. 70

C. RNA isolation ............................................................................. 71

D. Real time RT-PCR standard curve preparation ..................................... 72

E. Quantitative real-time RT-PCR analysis of PBMC gene expression .......”.73

F. Cortisol and DHEA assays .............................................................. 74

G. MMP-9 assay ............................................................................ 74

H. Observation of sickness behaviors ..................................................... 75

1. Statistical analysis ....................................................................... 75

IV. RESULTS ....................................................................................... 76
A. Behavioral observations 1n lame versus sound cows ................................ 76

B. Serum steroids in lame versus sound cows ............................................. 76

C. PBMC gene expression in lame versus sound cows ................................ 77

D. MMP-9 activity in serum of lame and sound cows 77

V. DISCUSSION ................................................................................... 78
CHAPTER FOUR ............................................................................... 92

SIGNATURE GENE EXPRESSION OF PERIPHERAL MONONUCLEAR CELLS IN
LAME DAIRY COWS WI I'H INFLAMMATORY FOOT LESIONS.

1. ABSTRACT ................................................................................... 92
II. INTRODUCTION ............................................................................. 93
IH. MATERIALS AND METHODS .......................................................... 96
A. Subjects .................................................................................... 96

B. Blood collections and isolation of PBMCs and RNA .............................. 97

C. Experimental design ..................................................................... 97

D. Preparation of labeled cDNA and hybridization 98

E. Microarray data analysis ................................................................. 99

F. Validation of differential gene expression using quantitative real-time RT—PCR
............................................................................................... 100

IV. RESULTS ..................................................................................... 103
A. Microarray experiment ................................................................ 103

B. Validation of differential expression ................................................ 103

V. DISCUSSION ................................................................................. 104
CHAPTER FIVE ................................................................................. 115
GENERAL DISCUSSION ...................................................................... 115
APPENDIX ....................................................................................... 125
REFERENCES ................................................................................... 127

ix

LIST OF TABLES

Table 1 Changes in various systems as part of the sickness response. ....................... 4
CHAPTER ONE

Table 1.1 Treatment practices for common lameness pathologies (Greenough, 1987).
.......................................................................................................... 22
Table 1.2 Comparison of studies measuring peak vertical forces in sound cows. N =
Newtons; n = number of animals included in the study; BM = body mass ................. 31
Table 1.3 Different approaches for biomarker discovery. Adapted ﬁom Yun-Fu et a1.
(2005) and Crebs (2006) ............................................................................ 52
CHAPTER TWO

Table 2.1 Mean peak vertical force (PVF) and right-left hindlimb PVF symmetry of
heifers (645 :t 60 kg) with (n = 4) and without (11 = 3) ha' heel wart lesions. Values
marked with the same symbol were signiﬁcantly different. (P = 0.04) indicates PVF
differences between RH and LH of heifers with lesions; .. (P = 0.01) indicates PVF mean
differences between hindlimbs heifers with and without lesions; m (P = 0.04) indicates
PVF symmetry mean differences between hindlimbs of heifers with and without lesions.

RH = right hindlimb; LH = left hindlimb ........................................................ 63
CHAPTER THREE

Table 3.] Bovine gene-speciﬁc primers used to develop real time RT-PCR standard
curves. ................................................................................................ 83
Table 3.2 Bovine gene-speciﬁc primers used for quantitative real time RT-PCR. ........ 84
Table 3.3 Behavior categories recorded and their deﬁnitions. ................................ 85

Table 3.4 Behavioral proﬁle of lame (n = 8) and sound (11 = 8) cows. LSMeans (:1: SEM)
are represented as the duration (min) of each behavior over the time period studied (see
Materials and Methods). * P S 0.05 for main effect of lameness group. .................... 86

Table 3.5 Quantitative real time RT-PCR analysis of PBMC mRN A abundance (in log;
fentograms, fg) of the inﬂammation regulating genes pro-opiomelanocortin (POMC),
interleukin-113 (IL-113), L—selectin (CD62L), and stress hormone glucocorticoid receptor
alpha (GRa) gene. B-actin is shown as a control gene. Data represent LSMeans (:1: SEM)
of mRN A abundance for lame (n = 8) versus sound (n = 8) cows. .......................... 87

CHAPTER FOUR

Table 4.1 Genes detected in PBMC by cDN A microarray analysis as putatively altered in
expression by lameness ........................................................................... 109

Table 4.2 Sequence of primers used for real—time RT-PCR measurement of gene
expression and concentration of template PBMC cDNA used in the reactions. F =
forward, R = reverse ............................................................................... 111

APPENDIX

Table A.1 Real-time RT-PCR on PBMC expression of genes with no lameness effect
from Chapter Four. Fold change represents means of expression ratios between lame (n
= 8) and sound (11 = 8) derived using the 2““ method of Livak and Schmittgen (2001),
with B-actin as the control gene and sound cows as a calibrator. The P-values represent
the main effect of lameness. ...................................................................... 126

xi

LIST OF FIGURES

Images in this dissertation are presented in color.
CHAPTER ONE

Figure 1.1 Most common sites of lameness lesions within the claw: white line and sole.
Drawing by RE. Almeida. ........................................................................ 14

Figure 1.2 Hemorrhagic sole ulcer lesion on the lateral claw of a cow’s left hindlimb
(Picture by RE. Almeida at the Kellogg Biological Station Dairy Center - Michigan State
University). .......................................................................................... 16

Figure 1.3 Histological appearance of the laminated region of the anterior hoof wall of
hind lateral claw. Corium (Co) stained red, and horn (Ho) stained yellow, (a) maiden
heifer, (b) two weeks pre—calving, (c) four weeks post-calving, (d) twelve weeks post-
calving. Maiden heifer laminae were straight with narrow corium. A widening and
distortion of the interdigitating laminae at four and twelve weeks can be seen. An
apparent increase in the amount of collagenous matrix of the corium is shown (arrows).
From Tarlton et al. (2002). ........................................................................ 18

Figure 1.4 Transverse section of a cow’s claw (A) without and (B) with distal
displacement of the pedal bone. (1) Vertical displacement of the corium on the inner
surface of the horn capsule. The dark arrow on (B) indicates the force acting on the pedal
bone (2) that causes its sinking. The suspensory apparatus (3) is the main structure
responsible for suspending the pedal bone. Modiﬁed by RE. Almeida from Lischer et a1.
(2002). ................................................................................................ 19

Figure 1.5 Example of a locomotion scoring scale (Sprecher et al., 1997). During
standing and walking, based on back posture, and stride length where appropriate, cows
can be graded from sound (score 1) to severely lame (score 5). Courtesy of Zinpro®
Corporation, Eden Prairie, MN. .................................................................. 27

Figure 1.6 Stride parameter measurements (modiﬁed by RE. Ahneida from Telezhenko
et al., 2002). In addition to the six variables indicated, step asymmetry was measured as
the difference between two consecutive steps. FL = left forelimb; RL = right hindlimb;
FR = right forelimb; RR = right hindlimb. ...................................................... 30

Figure 1.7 Vertical force for fore- and hind-limbs for a sound animal (from Scott, 1988).
Note the modal forelimb, short time difference between limb contacts, bimodal hindlimb,
lower hindlimb values and impact spikes for each limb, all of which might be typical of

xii

sound animals. A = impact spike; B = peak vertical ground reaction force..
................................................................................................................ 32

Figure 1.8 Photograph of (a) an animal standing on a pressure plate system (Tekscan,
Boston, MA; 1.44 sensors per cmz, 34 x 47cm area and 40 Hz sampling rate). Insert
shows the pressure plate proﬁle with colors ranging from low (blue) to high (red)
pressures, and the point of peak pressure is indicated; (b) a RSscan pressure plate
(Footscan Scientiﬁc version, RSscan International, Olen, Belgium; 0.39 sensors per cm2;
100 x 40 cm, 250 Hz). Pictures by RE. Almeida. ............................................. 34

Figure 1.9 Pressure plate image at midstance for a cow’s left forelimb at walk. Image is
orientated with top as anterior and left as lateral. The path of the net force, known as the
center of pressure that is also provided by a force platform, is included (dotted black and
white line). Red areas within the claw indicate the areas receiving more pressure. Red and
pink lines represent force vectors from other feet in simulataneous contact with the
pressure plate. Picture by RE. Almeida .......................................................... 35

Figure 1.10 Phagocytic cells produce pro-inﬂammatory cytokines when activated by
pathogens. The cytokine molecules act in the brain to re-organize the animal’s behavioral
priorities. The resulting sickness behavior syndrome is an adaptive response that
enhances the animal’s immunological defenses (i) and inhibits (-) proliferation of the
pathogen. Thus, sickness behavior enhances disease resistance and promotes recovery.
Adapted by RE. Almeida from Johnson (2002) and Hart (1988) ............................. 38

Figure 1.11 Overview of the HPA axis system. (A) Stress stimulates (+) the
hypothamalus to CRF and AVP that induce (+) the release ACTH by the anterior
pituitary. This culminates with the release of steroid hormones (e.g. glucocorticoids) by
the adrenal gland cortex and a negative feedback (-) to hypothalamic activation.
Furthermore, glucocorticoids also modulate inﬂammatory responses by acting on
immune cells via glucocorticoid receptors. (B) Anatomical location of the hypothalamus
and pituitary gland. Brain picture is from the American Accreditation HealthCare
Commission (A.D.A.M., Inc) website (www.urac.org —
httLJ/z.about.com/d/p/440/e/f/ 19239.jpg). ....................................................................... 40

Figure 1.12 Development of TH] and TH2 type cell subsets. Cytokines produced in the
innate immune response to microbes or early in adaptive immune responses inﬂuence the
differentiation of naive CD4+ T cells into TH] or TH2 cells. IL-12, made by activated
macrophages and dendritic cells, induces TH] cell development through a STAT4-
dependent pathway. IL-4, which may be produced mainly by T cells themselves, favors
induction of TH2 cells through a STAT 6 dependent pathway. The transcription factor
Tbet, produced in response to IFN-y, ampliﬁes TH] responses, and GATA-3 is critical for
TH2 differentiation. Other cytokines that may inﬂuence helper T cell differentiation are
not shown. However, IFN-y and IL-4 are the main differentiating cytokines for THI and
TH2, respectively. Glucocorticoid suppresses IL-12 and consequently, TH2 type immune
response is favored. Adapted by RE. Almeida from Abbas and Litchman (2003) and
Tizzard (2004). ....................................................................................... 45

xiii

CHAPTER THREE

Figure 3.1 General stance and foot lesion proﬁles of lame and sound cows. Lame cow:
(a) arched back posture (courtesy of Zinpro® Corporation, Eden Prairie, MN) and (b)
foot lesion. Sound cow: (c) straight back posture (courtesy of Zinpro® Corporation, Eden
Prairie, MN) and (d) no visible foot lesions. ................................................... 88

Figure 3.2 Standard curves used for absolute quantiﬁcation of the expression of
candidate genes. .................................................................................... 89

Figure 3.3 Cortisol (a), DHEA (b) concentrations, and cortisol:DHEA (0) ratio in sera of
lame (n = 8) and sound (n = 8) cows. The bars represent LSMeans (:1: SEM) of lame (dark
bar) and sound (white bar) cows. * P = 0.01 and T P = 0.06 for the main effect of
lameness group ........................................................................................ 90

Figure 3.4 Representative gelatin zymogram of MMP-9 and MMP-2 activities in serum
of lame and sound cows. Lanes 1, 3 and 5 are sera from lame (L) cows while lanes 2, 4
and 6 are sera for sound (S) cows. Little to no MMP-9 activity was detected in any sera

despite clear and consistent MMP-2 activity in all sera ....................................... 91
CHAPTER FOUR
Figure 4.1 Microarray experimental design. ................................................... 112

Figure 4.2 Real-time RT-PCR of lameness effects on PBMC expression of IL-2, CCR5
and MMP-13. The bars represent means of expression ratios between lame (n = 8) and
sound (11 = 8) cows derived using the 2M0 method of Livak and Schmittgen (2001), with
B-actin as the control gene and sound cows as the calibrator. The asterisks (*) represent
mean differences between lame and sound cows (P S 0.05) ................................. 113

Figure 4.3 Real time RT-PCR of lameness effects on PBMC expression of the anti-
inﬂammatory cytokines IL-10, IL-4, and pro-inﬂammatory GM-CSF—R-alpha. The bars
represent means of expression ratios between lame (n = 8) and sound (11 = 8) derived
using the 2M0 method of Livak and Schmittgen (2001), with B-actin as the control gene
and sound cows as the calibrator. The asterisk (*) represents mean differences (P S 0.05)
and the crosses (T) represent a tendency for means differences (0.05 S P _<_ 0.10) between
lame and sound cows. ............................................................................ 114

CHAPTER FIVE
Figure 5.1 Tentative model to summarize the changes observed in the lame cows of the

studies of this dissertation. Genes in orange and blue boxes are involved in pro- and anti-
inﬂammatory activities, respectively. 121

xiv

°C

“8

ACD

ACTH

AVP

BLASTn

BM

BOTL

CCR5

CD

CD62L

cDNA

CINC-2

cm

CNS

CRF

DGR

DHEA

DNA

dNTP

LIST OF ABBREVIATIONS

Degrees Celsius

Microgram

Acid Citrate Dextrose

Adrenocorticotrophic Hormone

Arginine Vasopressin

Basic Local Alignment Search Tool — nucleotide
Body Mass

Bovine Total Leukocyte

Base Pairs

Chemokine Receptor-5

Cluster of Differentiation (e.g., CD4, CD62L)
L-Selectin

Complementary DNA

Cytokine-induced Neutrophil Chemoattractant-Z
Centimeter

Central Nervous System

Corticotrophin Releasing Factor

Dorsal Root Ganglia

Dehydroepiandrosterone

Deoxyribonucleic acid

Deoxyribonucleoside Triphosphate

XV

DTT
E. coli
ECM
EIA

EST

g
GATA-3

Gi/o
GM-CSF-R-a
GR
GRF
GRa
HHW
HPA
Hz
ICAM- 1
IFN-y
IgG

IL

Dithiothreitol

Escherichia coli

Extracellular Matrix

Enzyme Immuno Assay
Expressed Sequence Tag

False Discovery Rate

Fentogram

Left Forelimb

Right Forelimb

Gram

GATA binding protein 3
Inhibitory G-protein

Granulocyte Macrophage-Colony Stimulator Factor-Receptor—alpha
Glucocorticod Receptor

Ground Reaction Force
Glucocorticoid Receptor-alpha
Hairy Heel Wart
Hypothalamic-Pituitary-Adrenocortical
Hertz

Intracellular Adhesion Molecule-1
Interferon-gamma
Immunoglobulin G

Interleukin (e. g., IL- 113, IL-6)

xvi

KC

KC
kDa

kg

LH
LOESS
log

LPS

MgCh

MIP-2
ml

MMP-l3

N/kg
NCBI
NGF
NSAIDs

OA

Keratinocyte-derived Chemokine
Keratinocyte-derived Chemokine
KiloDaltons

Kilogram

Left Hindlimb

Local-Weighted Regression and Smoothing Scatterplots
Logarithmic

Lipopolysaccharide

Molarity

Meter

Magnesium Chloride

Minutes

Macrophage Inﬂammatory Protein-2
Mililiter

Matrix Metalloproteinase- 13

Matrix Metalloproteinase-9

Messenger Ribonucleic Acid

Newton

Newton per kilogram

National Center for Biotechnology Information
Nerve Growth Factor

Non-Steroidal Anti-Inﬂammatory Drugs

Osteoarthritis

xvii

PBMC
PBS

PCR

pg

POMC
PVF
Q-RT-PCR
RA

RH

SEM
SLE
STAT4
STAT6
TGF-B
THO
TH]
THZ
TIGR
TIMP

TNF-a

Peripheral Blood Mononuclear Cell

Phosphate Buffered Reaction

Polymerase Chain Reaction

Picogram

Pro—opiomelanocortin

Peak Vertical Force

Quantitative real-time Reverse Transcription Polymerase Chain Reaction
Rheumatoid Arthritis

Right Hindlimb

Hind Hindlimb

Ribonucleic Acid

Right Hindlimb

Mean Standard Error

Systemic Lupus Erythematosus

Signal Transducer and Activator of Transcription 4
Signal Transducer and Activator of Transcription 6
Transforming Growth Factor Beta

Naive T helper

T helper type 1

T helper type 2

The Institute for Genomic Research

Tissue Inhibitor of Metalloproteinase

Tumor Necrosis Factor-Alpha

xviii

Treg Regulatory T cell
Tris-HCL Tris-Hydrochloric Acid
US United States

USDA United States Depanment of Agriculture

xix

INTRODUCTION

Lameness in dairy cattle refers to the abnormal gait used by animals as they
attempt to alleviate or avoid pain from lesions and inﬂammation in the affected limb or
back area (Scott, 1989; Hardie, 2000). Lameness not only severely compromises the
welfare of affected animals due to pain and discomfort (Webster, 1986), but also has a
real negative economic impact on the dairy industry. Estimated annual lameness
incidence in adult dairy cows based upon studies conducted in the United States and
Europe ranges from 4 to 56% (Leech et al., 1960; Prentice and Neal, 1972; Eddy and
Scott, 1980; McLennan, 1988; Clarkson et al., 1996; Whitaker et al., 2000; Wells et al.,
1993). This widely differing estimate is suggested to be due to issues with sensitivity of
lameness detection within individual herds: how lameness is deﬁned and by who (Whay
et al., 1997). Lameness is suggested to cost approximately US$350 per clinical episode
(Greenough and Weaver, 1997). This remarkable economic impact is due to direct losses
with treatment and control (Moore et al., 2001), and indirect losses due to impaired
reproductive performance (Sprecher et al., 1997), decreased milk yield (Warnick et al.,
2001), increased involuntary culling rate (Rajala-Shultz and Grohn 1999), and decreased
carcass value of culled cows (Arendonk et al., 1984; Booth et al., 2004). Realizing the
economic importance of lameness, its high incidence, and severe implications to the
welfare of cows, strategies to objectively diagnose, treat, and improve lameness outcomes
are of paramount importance.

Qualitative biomechanical applications in cattle, such as scoring systems, have

been adopted by the dairy industry for lameness screening, whereas the more quantitative

techniques have rarely been used (e.g. Herlin and Drevemo, 1997; Rajkondawar et al.,
2002b; Tasch and Rajkondawar, 2004). Lameness scorings are based on qualitative
assessments of kinematic measures (descriptors of motion) during standing and walking.
This strategy is time-consuming, unreliable, non-sensitive, and requires great skill on the
part of the herdsman (Whay et al., 1997; O’Callaghan et al., 2003; Wells et al., 1993;
Kopcha et al., 2003). Furthermore, deviations in locomotion, the focus of scoring
systems, might be associated with factors other than pain, including damage in locomotor
system (muscles, ligaments, nerves) (Greenough et al., 1981), natural variation among
cows, and physical constraints such as a distended udder (Flower et al., 2006). As a
consequence of inappropriate lameness screening, 30 to 50% of cows are suggested to
remain undiagnosed (O’Callaghan et al., 2003; Kopcha et al., 2003), treatment is often
delayed or neglected, and the pathologies that underlie lameness (e.g., sole ulcer, white
line disease, interdigital dermatitis) are likely to become chronic with unfavorable
prognoses (Logue et a1. 1998). To overcome some of the limitations imposed by the
subjectivity of current lameness screening methods, alternative strategies able to objectify
lameness diagnosis and enhance its accuracy and sensitivity are needed.

Lameness encompasses locomotor changes due to alterations in the limb loading
proﬁle, and in the force distribution within and between the limbs (Goodship et al., 1983;
Morris and Seeherman, 1987; Merkens et al., 1988). These changes are manifested by
asymmetries in temporal and spatial kinematics (geometry of motion), as well as in
kinetics (force distribution variables between the limbs). As a result of technological
innovations in biomechanical research, tools that enable objective measurement of

kinematics and kinetic variables (e.g. joint angle, ground reaction force) are available for

ﬁeld studies. For example, the vertical component of ground reaction forces (GRF),
which is often used to characterize altered locomotion in lame horses (Clayton et al.,
2000) and cows (Scott 1989; Rajkondawar et al., 2002b), can, now, be measured using
pressure plates. This device measures pressure under foot using optoelectrical techniques
such as light reﬂection or pressure sensitive electrodes. Compared to force plates, which
measures the direction and magnitude of the ground reaction forces beneath the foot,
pressure plates offer better portability and lower cost. However, the use of pressure plates
to detect lameness in dairy cattle has never been documented.

In addition to changes in locomotion, lame cows manifest sickness response type
behaviors. These behavioral changes are: increased lying time, altered social behavior,
decreased food-intake (Singh et al., 1993; 1994; Sauter-Louis et al., 2004), and
hyperalgesia (increased sensitivity to noxious stimuli) (Whay et al., 1998). Sickness
response is a phenomenon triggered by the recognition of anything foreign to the host
(Hart, 1988). It is initiated by the immune system but orchestrated and partially created
by the brain (Maier and Watkins, 1998; Hart, 1988; Kent et al., 1992). Sickness response
includes physiological, behavioral, and hormonal responses designed to enhance the

chances of host survival (Table 1).

Table 1 Changes in various systems as part of the sickness response.

 

System Changes

 

Decreased social interaction and exploration
Behavioral Decreased sexual activity

Decreased food and water intake

Fever

Alterations in plasma ions to suppress minerals required by
Physiological bacteria and viruses to replicate

Increase in white blood cell replication

Increased sleep

Increased release of classic hypothalamo-pituitary-adrenal
Hormonal [HPA]

Increase release of sympathetic hormones

 

Although the mechanism underlying sickness behaviors in lame cows is not
characterized, it may be triggered by injury and inﬂammation often present at the claw(s).
Lesions in the claw horn constitute 90% of all lameness cases (Murray et al., 1996) and
involve exposure to microorganisms (e.g., spirochetes and Fusobacterium necrophorum),
loss of horny sole and uncovering of the corium, laminar inﬂammation, and laminar
tissue necrosis. These lesions most likely trigger innate immunity and the release of
proinﬂammatory cytokines by peripheral immune cells (e.g., macrophages). These
cytokines are crucial for the development of sickness response and allow communication

between peripheral tissues and the central nervous system (CNS) (Watkins and Maier,

2005). Consequently, a pronounced increase in the activity of the HPA axis is expected to
occur (Buckingham, 1996; Turnbull and Rivier, 1999) and culminates in the release of
steroid hormones such as cortisol and dehydroepiandrosterone (DHEA) from the adrenal
cortex (Besedovsky et al., 1986; Jessop, 1999). Despite the occurrence of sickness
behaviors in lame cows, physiological changes consistent with sickness response, such as
altered steroid hormones, have not been documented. Therefore, the potential of using
circulating concentrations of HPA axis related hormones as candidates to differentiate
lame from sound cows is worthy of investigation.

In addition to changes in hormones that reﬂect HPA axis activation, immune cells
also are important sources of information about organismal health (Dunnes, 2005). For
example, peripheral blood mononuclear cells (PBMCs) are responsible for a
comprehensive surveillance of the body for signs of infection and disease. PBMCs have
been used as sources of biomarkers to identify ongoing autoimmune diseases such as
rheumatoid arthritis, systemic lupus erythematosus, type I diabetes, and multiple sclerosis
(Maas et al., 2002), and non-autoimmune diseases such as renal cell carcinoma in humans
(Burczynski et al., 2005), Johne’s disease (Coussens et al., 2004a; 2004b),
trypanosomiasis (Hill et al., 2005), and tuberculosis (Meade et al., 2006) in livestock.
Considering the previous use of PBMCs for the diagnosis of a variety of diseases and the
cells’ vital role as triggers of sickness response, these ciculating mononuclear leukocytes
might carry transcriptome-level information regarding the presence of inﬂammatory
events at the cow’s claw and thus aid lameness screening in dairy herds.

Because of limitations imposed by the subjectivity of current methods used for

lameness screening in dairy cows and the consequent negative impact to cattle welfare

and the dairy industry, the main objective of this Ph.D. dissertation research was to
discover candidate biomarkers with potential to assist with objective diagnosis of lame
cows suffering from inﬂammatory and painful foot lesions. This was accomplished by
completing three related studies, which were entitled: 1) Early detection of lameness in
heifers with hairy heel warts using a pressure plate; ii) Depressed DHEA and increased
sickness response behaviors in lame dairy cows with inﬂammatory foot lesions; and iii)
Signature gene expression of peripheral mononuclear cells in lame dairy cows with
inﬂammatory foot lesions. These studies are described in Chapters Two, Three and Four
of this dissertation.

The overall hypothesis explored in this dissertation was that lame cows with
painful inﬂammatory foot lesions have behavioral, biomechanical and physiological
changes that are amenable to objective measurement. This hypothesis was tested under
the following sub-hypotheses:

i) a pressure plate is a sensitive tool for early detection of lameness in heifers
suffering from papillomatous digital dermatitis compared to Sprecher’s
( 1997) lameness scoring system;

ii) circulating concentrations of key inﬂammation regulating steroids (cortisol
and DHEA) and indicators of PBMC activation (gene expression for IL-lB,
CD62L, MMP-9, POMC and GRa) are altered in lame cows showing
sickness behavior and foot lesions compared to healthy sound cows;

iii) cows suffering from inﬂammatory and painful type of lameness derived
from foot lesions have a signature gene expression proﬁle of PBMC that is

distinguishable from that of healthy sound cows.

CHAPTER ONE

A REVIEW OF THE LITERATURE

I.LAMENESS IN DAIRY CATTLE

Today’s dairy cows face different environmental and management challenges
relative to the cows of the past. High energy rations, conﬁnement on concrete, constant
exposure to corrosive conditions, conformation defects, and perhaps even increased body
size are some risk factors that increase the probability of “production diseases”.
Production diseases are traditionally induced by management mistakes made by the
modern dairy industry to maximize proﬁt (Markusfeld, 2003). For example, inappropriate
management of clinical digital diseases in cows increases the risk of metabolic disorders
(Enting et al., 1997); providing cows with inappropriate space for resting and and
improper hygiene (Sogstad et al., 2006) increase the incidence of lesions at the tarsus and
teat injuries which predispose to lameness and subclinical or clinical mastitis (Osteras
and Lund, 1988; Rajala-Schultz and Grohn, 1999). Despite an increased awareness of
such factors, high levels of production diseases in dairy herds have persisted into the 21St
century.

Lameness in cattle is a debilitating condition, which is often associated with tissue
damage, pain, and discomfort, and manifests as an inability to walk normally
(O’Callaghan, 2002). Worldwide, 60% of a herd may become lame at least once a year
(Vermunt, 2005). Consequently, economic losses and cow welfare issues are alarming
concerns for the dairy industry. Problems such as inaccurate lameness diagnosis, the

paucity of licensed veterinary products available for lameness treatment, and producer

desensitization to lameness occurrence in their herd may exacerbate the problem (Wells
et al., 1993; Mill and Ward, 1994; Whay et al., 2003, O’Callaghan, 2002). Hence,
research targeting prevention, diagnosis, and treatment of lameness are timely and

paramount.

A. Pain and welfare

Lame cows do suffer from behavioral-modifying pain and prolonged discomfort,
in spite of the widespread belief amongst the general public that cattle are relatively
insensitive to pain (O’Callaghan, 2002). This belief stems from cattle’s instinctively
stoical nature, a survival strategy used by prey species in the wild to divert the attention
of a predator away from a sick or injured animal. This makes the identiﬁcation of injury
or disease in cattle difﬁcult until a condition is at an advanced stage (O’Callaghan, 2002).
Furthermore, the inattention to cattle’s pain might be due to a general lack of
understanding regarding ethical questions. Ethical questions posed by society and
philosophers are often considered as merely emotional outbursts by the livestock
industry, a means of threatening agricultural jobs, current livestock practices, and thus the
sustainability of animal agriculture. As a consequence, concerned citizens on both sides
of the debate tend to be irrational about animal welfare issues. This is confounded by the
fact that animals are not part of the vocal constituency and are thus unable to press for a
reasonable resolution to the problems surrounding their welfare (Rollin, 1989).

The physiological mechanisms associated with pain perception are complex and
remain poorly understood (Hutchinson et al., 2004). Several biological factors contribute

to a substantial inter-individual variability in nociception (Hardy et al., 1967). However,

despite the difﬁculties in determining if an animal is in pain, lame cows do have an
altered (exacerbated) pain indicative of primary hyperalgesia (increased sensitivity to
noxious stimuli in the vicinity of an injury) for a period up to 28 days following apparent
lameness resolution compared to sound cows (Whay et al., 1998). The hyperalgesia
phenomenon occurs due to a cascade of sensitizing events that follow tissue injury. For
example, damaged cells and primary afferent ﬁbers release a number of chemical
mediators, including substance P, neurokinin A, and calcitonin gene-related peptide
which have direct effects on the excitability of sensory and sympathetic ﬁbers (Siddall
and Cousins, 1997; Woolf, 1989). Moreover, immune cells that migrate to the injury site
have a role in modulating pain (Watkins and Maier, 2000) because they contribute to
sensitization of peripheral nerve system by releasing inﬂammatory mediators such as
proinﬂammatory cytokines, reactive oxygen and nitrogen species (i.e., free radicals),
norepinephrin, bradykinin, histamine, potassium ions, serotonin, and products from the
cyclo-oxygenase and lipoxygenase pathways of arachidonic acid metabolism (Dray,
1995; Levine et al., 1993; Siddall and Cousins, 1995; 1997). These molecules act
synergistically rather than individually, generating what is often referred to as a
‘sensitizing soup’ that effectively lowers the response threshold for nociceptive ﬁbers
(A8 and C) activation which results in hyperalgesia (Treede et al., 1992).

Considering that lame cows do experience pain, welfare issues in dairy systems
must be carefully considered. Lame cows display behavioral changes such as increased
lying time, decreased food-intake, hyperalgesia, and altered social behaviors (Singh et al.,
1993; 1994; Galindo and Broom, 2002; Sauter-Louis et al., 2004; Whay et al., 1998).

These modifications might prevent lame animals from meeting their range of ‘needs’ that

bring equilibrium to functional systems. A ‘need’ is deﬁned as a deﬁciency in an animal
that can be remedied by obtaining a particular resource or responding to a particular
environmental or bodily stimulus (Fraser and Broom, 1990). If an animal is in need, its
motivational state is affected so that behavioral and physiological coping responses that
remedy the need can be made. Coping responses allow the animal to control and maintain
mental and physical stability. It includes normal regulation of body state and emergency
responses, such as high adrenal activity, heart rate, or ﬂight activity, which requires more
energy expenditure and hence is used only when the animal predicts that normal
regulatory actions will be inadequate (Broom, 1991). Owing to the lame animal’s
impaired state and inability to properly cope with its environment, lameness represents a

serious animal welfare concern (Broom, 1986) that must be addressed.

B. Economic impacts

Lameness continues to be one of the largest ﬁnancial drains on the dairy industry.
Lameness in dairy cows is second only to mastitis in terms of its detrimental effect on
herd productivity (Esslemont and Kossaibati, 1996). In the United States, lameness costs
on average between US$300 to $400 per incident (Greenough and Weaver, 1997). The
United States Department of Agriculture (USDA) reports a national incidence rate of
12% (Morrow, 2002), which is equivalent to 9 million dairy cows (Amstutz, 1985;
Greenough and Weaver, 1997), and amounts to an annual ﬁnancial loss of approximately
US$300 million. As a result of its high incidence, prominent economic losses, and the

pain and discomfort that lame animals experience, lameness has been identiﬁed as a

10

principal health issue by the Animal Welfare Information Center of the USDA (Morrow,
2002).

The ultimate cost of a case of lameness is attributable in part to the costs of
treatment and control methods (Britt et al., 1996; Shearer and Hernandez, 2000;
Hernandez et al., 1999). However, numerous indirect costs that substantially increase
losses from lameness also must be considered. For example, lameness causes profound
decreases in milk yield (Rajala-Schultz et al., 1999; Warnick et al., 2001; Hernandez et
al., 2005). In an examination of the impact of clinical lameness (including sole ulcers,
white line disease, interdigital dermatitis and papillomatous digital dermatitis) on the
milk yield of dairy cows, Green et al. (2002) found that milk loss per affected cow
averaged 360 kg with a 95% conﬁdence interval that ranged from 160 to 550 kg.
Similarly, Hernandez et a1. (2002) reported a 10% decrease in milk production in lame
cows with interdigital phlegmon compared to sound cows and also demonstrated a linear
relationship between increasing degree of lameness and decreasing milk yield among
cows in their second or later lactations (Hernandez et al., 2005). Furthermore, lameness
impairs reproductive performance (Lucey et al., 1986; Collick et al., 1989; Lee et al.,
1989; Hernandez et al., 2001) with lame cows having longer calving-to-conception
intervals than sound cows (Hernandez et al., 2005). Lame cows also have an increased
susceptibility to other diseases such as mastitis (Peeler et al., 1994), and increased risk for
involuntary culling (Collick et al., 1989; Esslemont and Kossaibati, 1997). A recent study
by Hadley et a1. (2006) demonstrated that the most common reason for culling across 10
states of the USA. were injury related conditions (26.9%), reproductive problems

(18.9%), low production (12.8%), mastitis (12.1%) and mortality (10.6%). In the

11

National Animal Health Monitoring System Dairy 1996 Study, lameness alone was

reported as the reason for culling 15% of dairy cows sent to slaughter.

C. Epidemiological considerations

There is high variability in reported incidence of bovine lameness and few studies
have been performed on its prevalence in the dairy cow population, especially in high-
producing Holstein cows (Espejo et al., 2006). Lameness incidence estimates of between
12% (Morrow, 2002) to 50% (Kopcha et al., 2003; Espejo et al., 2006) have been made
in the United States. This variability in lameness incidence is reﬂected in worldwide
estimates, such as the 0% to 50% incidence reported by Harris et a1. (1988) in Australia,
9% to 50% in the Netherlands reported by Barkema et a1. (1994), and 5% to 70%
reported in the United Kingdom by Eddy and Scott (1980) and Hedges et a1. (2001).
Difﬁculty in deﬁning clinical lameness in dairy cows may in part explain this high
variability in reported incidence. Parlor workers, farm managers, veterinarians, and
research workers have been used to identify lame cows both within (Barkema et al.,
1994; Clarkson et al., 1996) and between (Lucey et al., 1986; Hedges et al., 2001) farms.
Part of the variation also may be attributed to the different skills of personnel responsible
for identifying lame cows. Large variability also occurs in the incidence and types of
lameness across farms (Barkema et al., 1994; Hedges et al., 2001). The imprecise
deﬁnition of lameness (Martin et al., 1987) and the use of subjective methods for
lameness screening (Thomsen and Baadsgaard, 2006) cause misclassiﬁcation: lame cows
deﬁned as non-lame and vice versa. These factors also may cause downward bias in

identifying whether or when a cow becomes lame (Martin et al., 1987). If true the

12

impacts of lameness on cow welfare, production, and economic loss are likely to be
signiﬁcantly underestimated.

Almost 90% of lameness incidents arise from abnormalities of the claw (Weaver,
2000) with an occurrence of 92% of lesions in the hind feet and 65% in the lateral claw
(Murray et al., 1996). The most common lesions and abnormalities are white line disease,
sole ulcer, toe ulcer, heel erosion, double sole, and sole hemorrhage (Russell et al., 1982;
Murray et al., 1996; Kopcha et al., 2003). Sole ulcers (40%) and white line lesions (29%)
are suggested to be the predominant diseases of horn, and digital dermatitis (40%) is the
most common skin disease (Murray et al., 1996). Lesions of the claw horn (Figure 1.1)
are suggested to be the most intractable cause of lameness, which develop initially as
hemorrhages of the sole and white line and can progress to solar ulceration and white line
separation (Murray et al., 1996; Vermunt and Greenough, 1996). Abnormalities on a claw
can be inter-correlated (Manske et al., 2002). For example, animals with heel horn lesions
are likely to show erosive dermatitis while animals with sole hemorrhages are also likely
to have white-line disease on the same claws (Manske et al., 2002). Furthermore,
ulceration of the sole and toe, white line disease, and heel erosion are usually associated
with a general condition termed laminitis (Greenough et al., 1981), which results from
insult to the vascular tissue of the foot. The correlation between lesions suggests that
factors impairing the structural integrity of the claw are associated with multiple

pathologies.

l3

Figure 1.1 Most common sites of lameness lesions within the claw: white line and sole.
Drawing by RE. Almeida.

I
,.,/’ r;

f a
, .

'.
w
..

 

White Line

Detailed studies of cohorts of animals (Leonard et al., 1996, Leach et al., 1997)
and epidemiological investigations (Clarkson et al., 1996) have identiﬁed several
potential risk factors contributing to lameness. Lameness is likely affected by a complex
array of factors (Vermunt and Greenough, 1994; Manske et al., 2002; Cook, 2003), which
include animal behavior and social interaction among animals (Leonard et al., 1996),
body conformation, contagious agents, diet, genetics, housing systems, hygiene, and
management (Bergsten, 2001). For example, foot and leg disorders that result in lameness
tend to increase with more conﬁned management systems and increased production
(Bergsten, 2001). A number of these factors, either alone or in conjunction with one
another, inﬂuence the severity and the prevalence of lameness (Hirst et al., 2002).
However, the relationships between these factors have not been well studied with regard
to their impact on lameness, and thus the etiology of lameness is poorly understood.

Among all housing systems, solid concrete ﬂoors are associated with an increased
prevalence of hoof lesions when compared with straw yards around ﬁrst calving

(Webster, 2002), straw yards for milking cows (Somers et al., 2003), slatted-concrete

14

L _-

 

ﬂoors (Frankena et al., 1992), and rubber slats (Hultgren and Bergsten, 2001). Increased
hoof lesions are associated with reduced lying times (Leonard et al., 1996), discomfort
lying, and the presence of high steps and slopes in housing (Philipot et al., 1994).
Moreover, freestall barns appears to be more detrimental to hoof health compared with
tie-stall barns or straw yards (Cook, 2003; Sogstad et al., 2005), and there is convincing
evidence that the incidence of claw horn lesions might be greater for cows housed in
cubicles than in straw yards (Livesey et al., 1998; Webster, 2001). Studies in Wisconsin
have shown that cows in sand-based stalls have a lower prevalence of lameness than
cows in mattress-based stalls (Cook, 2003; Cook et al., 2004). This difference may be
attributed in part to the physical surface of the lying and walking areas (Bergsten and
Frank, 1996; Faull et al., 1996) and in part to the fact that cows in straw yards spend
more time lying down (Singh et al., 1993).

Hemorrhagic lesions of the sole (Figure 1.2) and white line typically start to
develop around the time of parturition and tend to be most severe in the early weeks of
lactation (Bergsten and Frank, 1996; Leach et al., 1998; Livesey et al., 1998; Offer et al.,
2000). A typical dairy cow or heifer that develops claw horn lesions during the ﬁrst
weeks of lactation will have experienced marked changes in both housing and feeding.
For example, cows move from pasture or dry-cow accommodations in a straw yard into
cubicle house, and eat more starch and protein through concentrate ration feeding. These
peripartum animals also will have experienced major hormonal changes associated with
physiological processes of parturition and the onset of lactation. Therefore, any resolution

of the problem of claw horn lesions in early lactation requires an analysis of the relative

15

importance of these three risk factors: housing, nutrition, and parturition itself (Webster,
2002).
Figure 1.2 Hemorrhagic sole ulcer lesion on the lateral claw of a cow’s leﬁ hindlimb

(Picture by RE. Almeida at the Kellogg Biological Station Dairy Center — Michigan State
University).

 

The profound physiological changes that occur around calving and lactogenesis,
likely, inﬂuence connective tissue metabolism. In particular, blood concentrations of the
hormones estrogen and relaxin are increased during calving, are these regulate matrix
remodeling (Winn et al., 1994). As the name suggests, relaxin is associated with
increased laxity of connective tissues, particularly those of the birth canal. However, its
inﬂuence is systemic and is known to slacken other structures, such as cruciate ligaments
in humans (Blecher, 1998). Estrogen is considered to have an anabolic inﬂuence on
connective tissue metabolism, via induction of TGF-B (Ashcroﬁ et al., 1997). It has pro-
ﬁbrotic inﬂuence in hormone-replacement therapy, and may increase the risk of ﬁbrotic

diseases such as scleroderma (Beebe et al., 1997). Contrarily, estrogen is also reported to

16

reduce ﬁbroblast proliferation and collagen synthesis in cruciate ligaments (Liu et al.,
1997). Therefore, either or both of these hormones are suggested to contribute to the
pathogenesis of claw horn lesions and that the events associated with calving and the
onset of lactation are primary factors in the etiology of lameness in dairy cattle (Tarlton
et al., 2002).

Also, increased matrix metalloproteinase (MMP) activity in the circulation
(Weber et al., 2006b) and in circulating leukocytes (Burton et al., 2005) occurs with the
onset of labor in association with the need for reproductive tract and pelvic ligament
softening, and may also contribute to lameness susceptibility early postpartum. Indeed,
biochemical, biomechanical, and histological changes in feet of primiparous cows
support this hypothesis (Tarlton et al., 2002). In that study, histological changes were
observed as early as two weeks prepartum (Figure 1.3) and were accompanied by an
increase in laxity of the connective tissue supporting the third phalanx within the hoof
(Figure 1.4). Regional variations in connective tissue strength of the hoof are associated
with metabolic and compositional differences in total protein, collagen, proteoglycan, fat,
and water content, as well as the key regulatory molecules that mediate changes in them
leading to altered structure and composition of the connective tissue, the MMPs and their
natural tissue inhibitors the TIMPs. In turn, reduced suspensory support for the third
phalanx is expected to lead to greater loading of the sole, and may cause bruising and
pain. However, when external forces on the sole are greatest, such as when heavy (e.g.,
pregnant) animals stand for long periods on concrete, these will be most severe, and may

progress to a sole ulcer. The swelling and distortion of the laminae and corium are likely

17

to increase lateral pressure on the hoof wall, and therefore predispose to white line
separation (Tarlton et al., 2002).

Figure 1.3 Histological appearance of the laminated region of the anterior hoof wall of
hind lateral claw. Corium (Co) stained red, and horn (Ho) stained yellow, (a) maiden
heifer, (b) two weeks prepartum, (c) four weeks postpartum, (d) twelve weeks
postpartum. Maiden heifer laminae were straight with narrow corium. A widening and
distortion of the interdigitating laminae at four and twelve weeks can be seen. An
apparent reduction in overall collagenous matrix of the corium with increased matrix
thickening is shown (arrows). From Tarlton et al. (2002)

 

Figure 1.4 Transverse section of a cow’s claw (A) without and (B) with distal
displacement of the pedal bone. (1) Vertical displacement of the corium on the inner
surface of the horn capsule. The dark arrow on (B) indicates the force acting on the pedal
bone (2) that causes its sinking. The suspensory apparatus (3) is the main structure
responsible for suspending the pedal bone. Modiﬁed by RE. Almeida from Lischer et al.
(2002).

 

In addition, supplementation with minerals and vitamins seem to affect the
occurrence of lameness. For instance, supplementation with biotin is associated with a
reduction in lameness, especially white line disease (Hedges et al., 2001; Amory et al.,
2006). In addition to nutrition (e.g., increase period of feeding corn silage) (Faye and
Lescourret, 1989), farms that have foot baths and hoof-trimming apparatus are reported to
have less lameness than farms that do not have these features available (Amory et al.,
2006).

Finally, although much of the feet and leg health is associated with environmental
effects (e.g., management and housing), studies have revealed genetic sources of
variation in diseases of the foot and leg (Distl et al., 1990; Huang and Shanks, 1995). For
examples, traits such as foot angle, hoof diagonal, and rear leg set have shown genetic

associations with certain foot diseases (Distl et al., 1990). Therefore, genetic selection

may represent an important strategy to decrease the incidence of lameness in dairy cows

(Boettcher et al., 1998).

D. Treatment

People who have been trained to trim cows’ feet and treat lame cattle (i.e. foot
trimmers and veterinary surgeons) play an important role in lameness management on
many farms (O’Callaghan et al., 2004). Their perceptions and working practices when
dealing with lame cattle are likely to be inherently related to the welfare of the lame cow
(O’Callaghan, 2002). Treatment of claw horn lesions usually involves physical restraint
of the affected limb while excessive or defective horn is removed. In this scenario, the
sensitive corium is often exposed (Blowey, 1993) so pain is an important consideration.
As foot trimmers do not have the training or authority to administer anesthetics during
treatment of foot lesions they cannot alleviate the acute pain associated with this
procedure. The options available to the foot trimmer when presented with diseased feet
are to advise veterinary attention or to proceed despite legal restrictions. Those who
choose to proceed rely on good trimming technique and unloading of weight bearing by
diseased claws to limit pain (O’Callaghan et al., 2004).

Once lameness occurs, limited treatments are available for dairy cows. Unlike
foot trimmers, veterinary surgeons can prescribe and administer analgesic, anesthetic, or
sedative drugs to alleviate pain or stress. Pharmacological interventions that produce pain
relief mainly by restoring nociceptive sensitivity to its resting state (Dayson and Marks,
2003; Huxley and Whay, 2004; Skarda, 1996) are difﬁcult to use in the dairy industry

because of government food and drug regulations. Only one local anesthetic drug,

20

 

procaine hydrochloride (Willcain; Arnolds Veterinary Products Ltd) and two non-
steroidal anti-inﬂammatory drugs (NSAID), ketoprofen (Ketofen® 10%; Merial Animal
Health Ltd, Essex, UK) and ﬂunixin meglumine (Meﬂosyl 5%; Fort Dodge Animal
Health, or Banamine; Schering-Plough Animal Health, Middlesex, UK) are currently
licensed for use in lactating cattle. However, despite legal requirements to prevent
unnecessary pain, and evidence that administration of NSAID in addition to normal
treatments for lameness in cattle results in signiﬁcant reduction in the level of
hyperalgesia after treatment (Whay et al., 1998), the pain control potentially afforded by
these drugs is not fully utilized by veterinary surgeons when treating lame cattle
(O’Callaghan et al., 2004). Limited use of analgesics in cattle may be due to low client
expectation regarding pain control and reluctance to withhold milk (which is unnecessary

for Ketoprofen). As such, the principal approach to treating lameness is by claw trimming

(Table 1.1).

21

Table 1.1 Treatment practices for common lameness pathologies (Greenough, 1987).

 

 

Pathology Etiology Treatment

Interdigital phlegmon Claw injury and F usobacterium Systemic antibiotics

(foot rot) necrophorum

Interdigital dermititis Dichelobacter nodosum Cleansing and topical

antibiotics

Digital dermititis Unknown Cleansing and topical

(hairy heel wart) oxytetracycline

Pododermititis Claw injury, laxity of suspensory Therapeutic trimming,

circumscripta (sole apparatus due to physiological elevation of the sound

ulcer) changes around parturition claw

White line disease Mechanical injury, foreign body, Cleansing and drainage,
maybe secondary to sole ulcer, high therapeutic trimming
energy feed

 

Trimming for treatment is different than for prevention of lameness. Where
preventative trimming aims to optimize weight distribution within the hoof minimizing
strain injuries (Toussaint-Raven et al., 1985), therapeutic trimming is carried out to clean
the injured area from necrotic tissue and expose the lesion to facilitate healing and
treatment delivery. The importance of trimming as a preventive method for claw horn
lesions was demonstrated by Manske et a1. (2002) where abnormal claw shape was
strongly associated with sole ulcer (r2: 0.41 at cow level)—suggesting the importance of
maintaining a correct claw shape for the prevention of hoof-hem lesions.

Once the lesion has been treated, claw blocks, rubber coatings and bandages have
all been used to aid recovery. For instance, corrective trimming for ulcers involves
creating a steep slope of the horn around the ulcer, taking care not to damage the corium.
This procedure is performed to avoid entrapment of dirt in the ulcer area. Moreover, the

elevation of the sound claw, by application of a claw block to relieve all weight bearing

22

from the affected area and facilitate healing (Greenough, 1987), is also an important

treatment practice.

II. LAMENESS ASSESSMENT IN DAIRY CATTLE

Lameness alters locomotion such that the supporting or swinging limb periods, or
both, are shortened, so that the stride length is reduced. Reduction in the supporting limbs
period is most common with acutely painful lesions such as sole abscess (Phillips, 1998).
When the swinging limb period is shortened increased abduction or adduction often
occurs as the animals attempt to decrease load bearing by a particular part of the hoof.
Some unevenness of gait is evident before and after each lameness incident, and in total
the animal’s gait may be affected for three months, with clinical lameness being apparent
for an average of eight weeks (Phillips, 2002).

There are several methods available for lameness assessment, ranging from the
more qualitative (e.g., lameness scoring scales) to the more quantitative biomechanical
approaches (e.g., automated motion analysis systems), each which detects abnormalities
of locomotion. Qualitative biomechanical applications in cattle have been adopted by the
dairy industry for use in the ﬁeld, whereas the more quantitative techniques have rarely
been used.

The deviations in gait observed in lame cattle are to avoid pain associated with
injuries on the feet and legs (Whay et al., 1998). However, much of the variation reported
for both objective and subjective measures of gait also could be due to factors other than
pain, including damage in locomotor system (muscles, ligaments, nerves) (Greenough et

al., 1981), natural variation in gait among cows, and physical constraints to normal gait

23

such as a distended udder (Flower et al., 2006). The obvious method for determining
which gait attributes are speciﬁcally associated with pain would be to observe the effect
of an analgesic on behavior of an animal with impaired gait (Rutherford, 2002).
Unfortunately, little work on this issue has been published for cattle. Therefore validation
of gait measures that correlate with pain as objective measurement techniques to
diagnosis of lameness associated with tissue injury and pain, are urgently needed.
Similarly, available information derived from studies performed in horses and broilers
employed subjective and objective diagnostic approaches to evaluate the potency of
analgesics (Owens et al., 1995; McGeown et al., 1999) but failed to focus speciﬁcally on
the gait characteristics associated with pain. Objective measures of gait changes with
signiﬁcant correlation to pain could be used for both treatment development and
monitoring. In addition these measures could be able to assist with screening of cows

suffering from lameness type pain and welfare issues.

A. Qualitative lameness assessment

There are several qualitative methods for assessing lameness using locomotion
scoring scales. These scales are based on qualitative assessments of kinematic measures,
which are descriptions of motion during standing and walking that range from a few
measures of back posture and stride length (Sprecher et al., 1997; see Figure 1.5) to a
combination of back posture, leg abduction, limb weight bearing, joint ﬂexion, relative
front to hind foot placement, head carriage and ‘smoothness’ of gait (Welsh et al., 1993).
Other scales use a combination of these measures (e.g. Morrow, 1966a; b; Manson and

Leaver, 1988a; b; Whay et al., 1997; Kestin et al., 1992; Wells et al., 1993; May and

24

 

Wyn-Jones, 1987). The behavioral measures used by the various scoring scales to
establish the severity of lameness may also indicate the painfulness of the condition, such
as a humped back, unwillingness to move, and changed stride length of the lame limb.
Scoring scales often show good correlation to other measures such as activity level
(O’Callaghan et al., 2003). The relationship between lameness scoring and fertility
(Sprecher et al., 1997) suggests that such systems may be useful predictors of the
systemic differences between severities of lameness. However, although lameness
scoring scales beneﬁt from simplicity and ease of use in the ﬁeld, these scales are
subjective in nature and hinder lameness diagnostic accuracy.

Overall, lameness scorings have varied between (inter)- and within (intra)-
observer reproducibility of diagnosis depending on the type of lameness lesion involved
and the lameness score system in question. As with any subjective technique, scoring
systems can vary in reliability. For example, numerical rating scales has been shown to
correctly discriminate healthy cows from those with sole ulcers (R2 = 0.73) in 92% of
cases with reasonable intra— and inter-observer reliabilities (R2 2 0.64) (Flower and
Weary, 2006). However, other studies report correct diagnosis of only 22% (van
Eerdenburg et al., 2003) and 48% (Whay et al., 1997) of lameness cases. As an
aggravating factor, even the same observer may not score the gait of a cow the same on 2
occasions. For example, O’Callaghan et al. (2003) reported that a trained observer
rescoring the gait of 129 cows was consistent for only 56% of observations. In addition, a
lack of agreement between observers also has been reported; O’Callaghan et a1. (2003)
found only 37% agreement in the scores of 2 observers, and Winckler and Willen (2001)

found 68% agreement among scores of 3 observers. Moreover, subjective lameness

25

scoring systems were demonstrated to lack sensitivity to detect subtle changes in posture
and weight bearing (Flecknell and Molony, 1997; Whay et al., 1997; O’Callaghan et al.,
2003).

By using lameness scoring scales, producers misdiagnose lameness in 50 to 55%
of the cases (Wells et al., 1993). Others have found that the probability of observer and
expert agreement on exact estimates of 9 classes of gait scores ranged between 25 and
47% and rose to 80% if one class difference was permitted between observer and expert
(Engel et al., 2003). Observer training inconsistently improved the agreement between
observer and expert estimates, but the probability of agreement on exact score estimates
remained low at 47% (Engel et al., 2003). With these pitfalls in mind, methods of
objective, automated scoring may enable earlier, more accurate detection of lameness
which could lead to more efﬁcacious practices that reduce animal welfare issues in

commercial dairy units.

26

Figure 1.5 Example of a locomotion scoring scale (Sprecher et al., 1997). During
standing and walking, based on back posture, and stride length where appropriate, cows
can be graded from sound (score 1) to severely lame (score 5). Courtesy of Zinpr®
Corporation, Eden Prairie, MN and used with permission from the company.

 

 

l — Standing and walking ﬂat

‘ ' 2 — Standing ﬂat and walking
. arched

 

‘ . 3 — Standing and walking
' arched. Gait is short strided

 

4 — Standing and walking
1 ‘. arched. Cow favors one or more
" l ' legs/feet

’ P 5 - Standing and walking arched.
Cow demonstrates an inability, or
0‘ ‘ extreme reluctance to bear weight
on one or more limbs/feet

 

. 111;: 1 - 9“.

27

B. Quantitative lameness assessment

Quantitative assessment of locomotion is based on the use of biomechanical
techniques. Biomechanics is the study of the causes and description of motion. This is
referred to as gait analysis when the mode of locomotion, principally walking, is used.
Taking a broader deﬁnition, biomechanics can encompass all motions, including eating,
bullying, lying, standing, walking, trotting, cantering, galloping and transitions between
motions. Three ﬁelds of study comprise biomechanics: kinetics is the study of the forces
that cause motion; kinematics is the description of motion caused by forces, and
neuromuscular analysis is the study of the functional anatomy of the animal.

To overcome some of the limitations and subjectiveness of lameness scoring
scales, objective and technologically advanced methods may be used to improve accuracy
of measures for lameness detection (e.g., stride length, stance time, and weight-bearing
forces). These more precise measures, which will be expanded upon below, may provide
means for effective detection of lameness, treatment monitoring, and development of

lameness therapies.

i. Kinematics

Kinematic variables that describe motion principally include linear and angular
measurements of position (e.g. distance from an origin, or joint angle), displacement
(change in position), velocity (rate of change of displacement) and accelerations (rate of
change of velocity). At walk, for example, the position of a cow’s feet (illustrated in
Figure 1.6) enables the measurement of a number of other stride parameters (e.g. step

abduction, overlap, stride length, step length) (Telezhenko et al., 2002). These parameters

28

can be used to objectively measure locomotor changes that occur with lameness and
therefore assist with lameness diagnosis (Herlin an Drevemo, 1997; Flower et al., 2005).
Kinematics also can be useful to objectively evaluate the effect of different types of
ﬂooring on cow’s locomotion. For example, Telezhenko et a1. (2002) identiﬁed kinematic
differences between slatted and solid ﬂoors, where slatted ﬂoors were suggested to
impair locomotion and require more energy.

Additional kinematic variables that can be recorded in such analyses include
timing of events, trajectories of positions, jerk (rate of change of acceleration) and snap
(rate of change of jerk). In fact, an inﬁnite number of potential kinematic variables are
possible, depending on which position is selected on the animal. Typically, positions are
constrained to segment end points, bony landmarks, and centers of rotation of joints,
which together still provide a vast number of potential variables. These variables can be
measured using basic equipment (e.g. ruler and stopwatches to measure distances and
speeds; goniometers to measure joint angles), consumer equipment (e.g. digital cameras
in combination with picture software) or specialized equipment (e.g. automated motion

analysis systems, accelerometers, force platforms).

29

Figure 1.6 Stride parameter measurements (modiﬁed by RE. Almeida from Telezhenko
et al., 2002). In addition to the six variables indicated, step asymmetry was measured as
the difference between two consecutive steps. FL = left forelimb; RL = right hindlimb;
FR = right forelimb; RR = right hindlimb.

Step abduction

)4

    

 

Diagnonal support

Sride

Overlap
length

ii. Kinetics

Several methods of can measure forces both directly and indirectly. Direct
measurements can be made using force platforms, force transducers, pressure plates and
strain gauges. Indirect measurements of forces can be obtained mathematically from
theoretical muscle-force models, or through inverse dynamics of accelerometer or other
kinematic data. The ability to measure forces is important as the stance phase of the limb

has been considered the most susceptible time to injury occurrence rather than during the

30

swing phase of the limb (Peloso, 1994) and also an important indicator of locomotor
abnormalities associated with lameness and pain (Rushen et al., 2006), as cows tend to
remove the weight from the injured leg while walking and standing (Scott, 1989; Neveux
et al., 2006).

The most common device for measuring forces, particularly those exerted
between the hoof and ground, is a force platform. This instrument is embedded ﬂush in
the ground and measures forces in all three orthogonal directions (i.e. vertical, anterior-
posterior, medio-lateral). A force platform collect data on loading forces, including
ground reaction forces, loading rates, location of force (in combination with knowledge
of foot position), and stance times. The peak vertical force is used most frequently. For
adult cows, the ratio of fore- to hindlimb peak vertical forces is similar between studies,
ranging from 4.95 to 5.61 body-mass (BM) in the forelimb and 3.64 to 4.96 BM in the
hindlimb (Table 1.2).

Table 1.2 Comparison of studies measuring peak vertical forces in sound cows. N =
Newton; 11 = number of animals included in the study; BM = body mass.

 

Body 11 Breed Reference
mass

Peak vertical force

 

Fore Hind Fore Hind (k)
(BM) (BM) (N) (N) g

 

van der Tol et a1. (2005)

 

 

 

5.61 4.96 3537 3132 631 9 Holstein-Friesian

5.48 4.57 3301 2753 602 8 Friesian Scott (1989)

4.95 3.64 3324 2444 671 9 Holstein-Friesian van der Tol et a1. (2003)
5.42 4.25 N/A N/A N/A 3 Holstein Rajkondawar et al. (2002)

 

 

 

 

 

 

 

 

 

 

In six sound maiden heifers, force platform readings were recorded monthly for 6
months (Scott, 1988). The vertical force in the front limbs produced a modal pattern and
experienced a peak value of approximately 62% of body weight. In the hindlimbs the

pattern was bimodal and the peak values were approximately 50% of body weight. These

31

fore- and hind-limb patterns are illustrated in Figure 1.7 where, in addition to small
impact spikes, a short time difference between the limbs typical of sound animals can be
seen. In addition, Scott (1989) demonstrated that peak vertical force is linearly increased
with body mass both intra- and inter-cow, which supports the recommendation to account
for different animal masses by normalizing peak vertical forces by dividing by body mass
(Clayton and Schamhardt, 2001).

Figure 1.7 Vertical force for fore- and hind-limbs for a sound animal (from Scott, 1988).
Note the modal forelimb, short time difference between limb contacts, bimodal hindlimb,

lower hindlimb values and impact spikes for each limb, all of which might be typical of
sound animals. A = impact spike; B = peak vertical ground reaction force.

 

 

go: 2000;-
c3
§ 1600 -
§ 1
)6 1200’ B
c:
3 B
El) 8001’
E Fore- A
g 400’ A step Hind
:> -step
0 0.5 "1'.0"7‘1f5""270
Time (sec) .

In another study, ground reaction forces in 4 lame and 8 sound Friesian cattle
were measured (Scott, 1989). Peak vertical force was considered to be a sensitive
measure for detecting lameness, which was often reduced in the lame limb. The potential
of force plate technology to detect lameness has resulted in the commercialization of a
lameness detection system for the dairy industry. This device is called the SoftSeparator
(Tasch and Rajkondawar, 2004). It focuses on one variable (i.e. vertical force) and uses

an algorithm to separate the data for several animals moving over the device at one time.

32

An alternative to a force plate is a pressure plate, which can also be used to
measure vertical force. Typical systems possess 1 or 4 sensors per cmz, cover 20 x 20 to
100 x 200 cm areas and collect data from each sensor at between 40 and 500 observations
per second. A photograph of two systems and the pressure distribution of the four front
claws of a standing cow are illustrated in Figure 1.8. Pressure plates measure the
pressure exerted between the ground and areas under each claw for sound cattle standing,
walking and pre-post trimming (van der Tol et al., 2002; 2003; 2004, respectively — used
in combination with a force platform underneath to provide calibration). Analysis of each
claw could involve weight distribution, peak pressure, and location of peak pressure.
Using the six regions of the claw (Smilie et al., 1999), the pressure within each region
could also be determined. Although high pressure concentrations have been proposed to

cause ulcers (Toussaint-Raven et al., 1985; Greenough and Weaver, 1997), no empirical

studies have been performed that correlate pressure measurements to lesions.

33

Figure 1.8 Photograph of (a) an animal standing on a pressure plate system (Tekscan,
Boston, MA; 1.44 sensors per cm , 34 x 47cm area and 40 Hz sampling rate). Insert
shows the pressure plate proﬁle with colors ranging from low (blue) to high (red)
pressures, and the point of peak pressure is indicated; (b) a RSscan pressure plate
(Footscan Scientiﬁc version, RSscan International, Olen, Belgium; 0.39 sensors per cmz;
100 x 40 cm, 250 Hz). Pictures by RE. Almeida.

  

(a)

(b)

 

In comparison to force plates, pressure plates are less expensive and more
portable. The pressure plate provides a map of vertical pressure whereas a force plate
provides the net force, which is equivalent to the center of pressure proﬁle (Figure 1.9).
A force plate also provides horizontal forces, which in combination with vertical forces
provides an even more sensitive measure to detect lameness (Scott, 1989). A pressure

plate has proven to provide a quick, accurate and sensitive means to identify trimming

34

effects in horses (van Heel et al., 2004), to develop normative data for time-related
changes in humans (de Cock et al., 2002) and to evaluate locomotion in cattle (van der
Tol et al., 2002; 2003; 2004). Further work evaluating its effectiveness in detecting
lameness early in cattle is still required. Placing it across the width of a single-ﬁle alley
may provide valuable information. The device would need to be covered with a thin
rubber mat for disguise, to prevent it from becoming slippery when wet, and to offer
additional protection from damage.

Figure 1.9 Pressure plate image at midstance for a cow’s leﬁ forelimb at walk. Image is
orientated with top as anterior and leﬁ as lateral. The path of the net force, known as the
center of pressure that is also provided by a force platform, is included (dotted black and
white line). Red areas within the claw indicate the areas receiving more pressure. Red and

pink lines represent force vectors from other feet in simultaneous contact with the
pressure plate. Picture by RE. Almeida.

 

The principles of kinetic measurements have been covered above. Variations on
the applications include the use of force shoes (Rollot et al., 2004) and pressure insoles
(Judy et al., 2001). In addition, strain gauges exist that usually consist of a material
whose electrical resistance changes in response to a deformation (Verteramo and

Seedhom, 2004). The feasibility of these techniques on live cattle is limited in

35

comparison to the other kinetic measures, partially owing to the need to attach the

devices to the animals.

11. SICKNESS RESPONSE

In addition to gait changes, lameness can induce a classical sickness response in
cattle that is related to neuroendocrine and immune reactions to infection and
inﬂammation (e. g., fever and profound physiological and behavioral changes). These
changes are adaptive, evolutionarily old, and occur across a wide range of species as an
attempt to decrease body activity and so decrease energy expenditure to save energy for
use in the production of fever which often facilitates recovery (Kent et al., 1992).

Sickness response classically includes body temperature, endocrine (activation of
the hypothalamic-pituitary-adrenal axis and sympathetic nervous system) and behavioral
changes (e. g., decreased social interaction and decreased food and water intake).
Although changes in pain responsiveness have not been considered in the classic view of
sickness, hyperalgesia (increased sensitivity to noxious stimuli) is now considered a
natural part of the sickness response because recuperative behaviors supportive of healing
would be produced by enhanced pain (Watkins et al., 1995a; 1995b).. As well as
behavioral changes (e. g., increased lying, decreased eating, and decreased social
behaviors), cows with lameness present hyperalgesia that lasts up to 28 days after
treatment (Whay et al., 1997; 1998). This hyperalgesic state supports the premise that the
changes in gait, characteristic of lameness, are likely due to enhanced pain sensitivity at

the injury site (i.e., foot).

36

The explanation for the behavioral changes observed as part of sickness response
can be explained simplistically by assuming that infectious pathogens make their way to
the brain where they are detected by neurons. However, many pathogens that elicit
sickness behavior upon infection do not target the brain. Evidence now indicates that
infectious pathogens induce sickness response by stimulating mononuclear phagocytic
cells at the injury site to produce soluble proteins called pro-inﬂammatory cytokines
(Kent et al., 1992). The pro-inﬂammatory cytokines interleukin-1 beta (IL-113),
interleukin—6 (IL-6) and tumor necrosis factor-alpha (TNF-a) are synthesized in both
brain and periphery. Systemic or central injection or recombinant pro-inﬂammatory
cytokines induce a full-blown sickness behavior syndrome similar to that observed in
infected animals. In essence, the immune system uses cytokines to convey information to
the brain and other physiological systems about tissue injury and infection (Hart, 1988)

(Figure 1.10).

37

Figure 1.10 Phagocytic cells produce pro-inﬂammatory cytokines when activated by
pathogens. The cytokine molecules act in the brain to re-organize the animal’s behavioral
priorities. The resulting sickness behavior syndrome is an adaptive response that
enhances the animal’s immunological defenses (:t) and inhibits (-) proliferation of the
pathogen. Thus, sickness behavior enhances disease resistance and promotes recovery.
Adapted by RE. Almeida from Johnson (2002) and Hart (1988).

 

Damaged .

epithelium, Inﬂammatory cytokines:

endothelium, and Interleukin-l

tissue macrophages ’ Interleukin—6 ’
TNF-B

 

 

    

 

 

Sickness response

(e.g., anorexia, lethargia, decreased
social behaviors, fever)

 

Infectious pathogen
Tissue trauma

A. Mediators of the HPA axis responses to acute immune insults

As mentioned above, the proinﬂammatory cytokines released during immune
activation relay information about the events in the periphery to the brain (hypothalamus)
(Tracey, 2002), which then takes measures to re-establish “homeostasis” as quickly as
possible by “adaptive responses”. The central nervous system effector of this response is

the “stress system” with its main components, the corticotrophin-releasing factor

38

(CRF)/arginine-vasopressin (AVP) and locus ceruleus-noradrenaline (LC-NA)/autonomic
(sympathetic) neurons of the hypothalamus and brain stem (Chrousos, 2000). Activation
of the HPA axis and the LC-NA/autonomic system result in systemic elevations of
glucocorticoids and catecholamines (CAs), respectively, which act in concert to maintain
homeostasis. Stress inﬂuences the immune response primarily through the HPA axis
system. Activation of the HPA axis culminates in secretion of glucocorticoids (Figure
1.11), that are recognized by glucocorticoids receptor molecules in cells of numerous
organs, including immune cells. For example, because cytokines can activate
hypothalamic—pituitary release of glucocorticoids, in turn, glucocorticoids suppress
further cytokine synthesis and thus inhibiting inﬂammation (Besedovsky et al., 1986).
The HPA response to acute immune insults is driven primarily by the mediators
released from activated immune/inﬂammatory cells (Buckingham et al., 1996; Turnbull
and Rivier, 1999). The cytokines IL-lB, IL-6 and TNF-a, which are released sequentially
from activated macrophages in response to, for example, endotoxin, are known to be
particularly important in this regard. They amplify the inﬂammatory response locally,
inﬂuence the adaptive immune response, and serve as signals of an inﬂammatory
response to the CNS. The role of T-cell-derived cytokines in activating the HPA axis has
received less attention, although H.-2 triggers ACTH release from the pituitary gland in

vivo (Turnbull and Rivier, 1999).

39

Figure 1.11 Overview of the HPA axis system. (A) Stress stimulates (+) the
hypothamalus to CRF and AVP that induce (+) the release ACTH by the anterior
pituitary. This culminates with the release of steroid hormones (e.g. glucocorticoids) by
the adrenal gland cortex and a negative feedback (-) to hypothalamic activation.
Furthermore, glucocorticoids also modulate inﬂammatory responses by acting on
immune cells via glucocorticoid receptors. (B) Anatomical location of the hypothalamus
and pituitary gland. Brain picture is from the American Accreditation HealthCare
Commission (A.D.A.M., Inc) website (wxx wurucoru -
httpz. :Zaboulcomx(13154401617’19239.jpg).

(A) (+)
Stress ‘

 

Hypothalamus

      
 

        

   

(+)
. . . Pons - (Qt. 1331‘; 1‘ '
Anterior p1tu1tary I) ~ ._. 2;“
H Pituitary Gland
Immuno modulation of
immune cells: anti-

   

. ﬂ
Adrenal Gland 1n ammatory effeCtS

      

Kidneys - '
Leukocytes

Glucocorticoids

  

B. Mechanism of cytokine activation of the HPA axis
The mechanisms by which pro-inﬂammatory cytokines activate the HPA axis and
increase glucocorticoid secretion are complex and varied, including both centrally

mediated actions and actions at the levels of the pituitary gland and the adrenal cortex.

40

Several lines of evidence suggest that IL-1, IL-6 and TNF-a act synergistically in the
neuroendocrine system, as they do in the immune system, and thereby drive the release of
ACTH and glucocorticoids by potentiating each other’s actions in a complex cascade of
events (Buckingham et al., 1996; Turnbull and Rivier, l999).Because there is no arterial
blood supply to the anterior pituitary gland, cytokines released into the circulation only
reach the hypophyseal portal capillaries in the median eminence (MB) of the tuber
cinereum via the anterior hypophyseal arteries (Porter et al., 1983). Cytokines are large
polypeptides (15 kDa) and, therefore, are unlikely to diffuse across the blood-brain
barrier; however, they diffuse into the ME because there is little or no blood-brain barrier
there. While the evidence that cytokines act at the hypothalamic level to increase the
secretion of CRF and AVP is compelling, the ability of cytokines released from
peripheral cells (e.g., macrophages) to gain access to targets in the CNS has been
questioned. It has been argued instead that cytokines may enter the brain via: (a)
fenestrated regions of the capillary endothelium; (b) areas in which the permeability is
increased by e.g. local inﬂammation; or (c) an active transport system (Buckingham et
al., 1996; Turnbull and Rivier, 1999). Another route of communication that must be
mention is that proinﬂammatory cytokines also can be produced by glial cells under
infection or inﬂammatory stimuli, and these brain cytokines can be critical in the

mediation of sickness responses (Wieseler-Frank et al., 2005).

C. HPA mediated changes in the immune system

Stress has been deﬁned as a state in which the organism confronts a novel,

threatening, or challenging situation, or when the metabolic or physical status is

41

compromised (Zinder and Dar, 1999). The activation of a global stress response during
tissue injury and infection (e.g., lameness) can profoundly inﬂuence the function of the
immune system indirectly, through activation of the HPA axis, and directly through local
modulatory cytokine actions on inﬂammatory responses (Chrousos, 2000). The general
immunosuppressive and anti-inﬂammatory effects of stress are well known (Elenkov and
Chrousos, 1999). However, stress does not simply suppress all aspects of immunity, but
rather results in wide changes in acute and chronic irmnunocompetence and even
exaggerated responsiveness of certain components of the innate immune/inﬂammatory
reaction (Yeager et al., 2004).

The stress induced release of hypothalamic CRF leads ultimately to adrenal
secretion of glucocorticoids, epinephrine and norepinephrine into the peripheral
circulation, which in turn inﬂuence local and systemic immune/inﬂammatory reactions in
major ways. Glucocorticoids modulate immune/inﬂammatory reactions through their
cognate receptor (GR) present in the cytoplasm of target immune cells (Weber et al.,
2006a). For example, glucocorticoids prevent the transendothelial migration of
leukocytes from the circulation into extravascular ﬂuid space, reduce the accumulation of
monocytes and granulocytes at inﬂammatory sites, and suppress the transcription and
action of many cytokines and inﬂammatory mediators in immune and immune accessory
cells (as reviewed in Chrousos, 2000). In addition, glucocorticoids inﬂuence the
development, course, and pathology of certain allergic, autoimmune/inﬂammatory
infections, and neoplastic diseases, predominately by stimulating TH2 and limiting THI

based immune responses, which will be expanded below.

42

Naive THO cells can differentiate to at least two functional classes of cells during
an immune response (Mosmann et al., 1986) — T31 cells, which are classiﬁed as such,
based upon their secretion of interferon-gamma (IFN-y) and TH2 cells, which instead
secrete interleukin-4 (IL—4) (Abbas et al., 1996; Ho and Glimcher, 2002). Hereafter, we
refer to IFN-y and IL—4 as effector cytokines. THI cells are responsible for inducing
cytotoxic T cells for cell-mediated immunity, whereas TH2 cells are responsible for
inducing B cells for humoral (antibody-based) immunity. As well as their protective roles
in host defense, both subsets of TH cell have been implicated in pathological responses.
For example, TH] cells can mediate organ-speciﬁc autoimmunity (Murphy and Reiner,
2002) and THZ cells have been implicated in the pathogenesis of asthma and allergy
(Murphy and Reiner, 2002). The ﬁnal composition of the TH-cell response to antigen can,
therefore, determine whether the outcome of infectious, inﬂammatory and autoimmune
responses is favorable or unfavorable.

The process of differentiation from uncommitted THO cell to a mature THI or TH2
cell is highly plastic. Many factors inﬂuence the decision to become a THI or TH2 cell.
The cytokines IL-12 and IL-4, acting through signal transducer and activator of
transcription 4 (STAT4) and STAT6, respectively, are key determinants of this outcome
(Abbas et al., 1996; Ho and Glimcher, 2002). Antigen dose, co-stimulator factors such as
adhesion molecules (e.g., ICAM-l), and other non-cytokine factors also have crucial
roles in deterrrrining the dominance of a particular TH cell type response (Kohlmeier et
al., 2006). How each signal inﬂuences the differentiation process is an area of active

investigation and, often, lively controversy.

43

In situations of stress, glucocorticoid acting through GR in antigen-presenting
cells (APCs) directly suppresses transcription of the main inducer of TH] responses, IL-
12 (Elenkov et al., 1996; Blotta et al., 1997) (Figure 1.12). Since IL-12 is extremely
potent in enhancing IFN-y and inhibiting IL-4 synthesis by T cells, the inhibition of IL-12
production may represent a major mechanism by which glucocorticoids affect the
THl/TH2 balance, that is, by enhancing humoral (T112) and suppressing cell mediated
(THI) immunity (Wilder, 1995; Elenkov et al., 1996; 1998; Ramirez et al., 1996). The
cytokines produced by differentiated effector T cells function to activate macrophages
and B lymphocytes in the effector phases (eliminate antigen and activate other immune

cells) of cell—mediated and humoral immunity.

Figure 1.12 Development of TH] and THZ type cell subsets. Cytokines produced in the
innate immune response to microbes or early in adaptive immune responses inﬂuence the
differentiation of naive CD4+ T cells into THl or T112 cells. lL-12, made by activated
macrophages and dendritic cells, induces THl cell development through a STAT4-
dependent pathway. IL-4, which may be produced mainly by T cells themselves, favors
induction of T112 cells through a STAT 6 dependent pathway. The transcription factor
Tbet, produced in response to IFN-y, ampliﬁes TH] responses, and GATA-3 is critical for
TH2 differentiation. Other cytokines that may inﬂuence helper T cell differentiation are
not shown. However, IFN-y and IL-4 are the main differentiating cytokines for TH] and
TH2, respectively. Glucocorticoid suppresses IL—12 and consequently, TH2 type immune
response is favored. Adapted by RE. Almeida from Abbas and Litchman (2003) and
Tizzard (2004).

Naive CD4”r T cell (THO)

    

Glucocorticoid

~J

 

Activated
macrophages,
dendritic cells

IL-2 <—

1m. // J” _, .i

4'" ‘ A
TNF-ﬁ TNF-a GM-CSF ”'5

45

Other adrenal steroids, such as dehydroepiandrosterone (DHEA) and its sulphate
metabolite (DHEA-S), released in response to ACTH during the stress response, also
have immunomodulatory properties. These include increased mitogen-stimulated IL-2
production by T cells (Daynes et al., 1990; Suzuki et al., 1991), diminished TNF-a and
IL-6 production by macrophages (Di Santo et al., 1996; Straub et al., 1998), inhibition of
natural killer cell differentiation (Risdon et al., 1991), and inhibition of mitogen—induced
lymphocyte proliferation (Padgett and Loria, 1994). DHEA is also considered to possess
anti-glucocorticoid activity (Kalimi et’ al., 1994) though its antagonistic mechanism of
action is unclear (Dillon, 2005) that include production of THl cytokines (Suzuki et al.,
1991; Daynes et al., 1995) and down regulation of TH2 (Daynes et al., 1995 ; Tabata et al.,
1997). There also is evidence that DHEA(S), or closely related steroids, alters the
THIITHZ cytokine balance (Tabata et al., 1997). The speciﬁc alterations in the balance of
THI and TH2 cytokines seem to be model-speciﬁc. Rook et al. (1997) have shown that
DHEA or androstenediol improve survival in a mouse model of Mycobacterium
tuberculosis infection. Delayed hypersensitivity response was improved and IL-2 was
increased, while IL-4 was decreased in the DHEA and androstenediol treated animals
(Rook et a1. 1997). These authors propose that DHEA and androstenediol stimulate TH]
cytokine release, which may be of importance in successful response to disease.

Plasma concentrations of DHEA(S) are lower in chronic inﬂammatory conditions
such as systemic lupus erythematosus (SLE), inﬂammatory bowel disease, rheumatoid
arthritis, and polymyalgia rheumatica (Straub et al., 1998; 2002) than in health humans.
Moreover, circulating concentrations of DHEA(S) correlate inversely with those of

cortisol in the pathological conditions mentioned above (Straub et al., 1998; 2002).

46

Increased circulating levels of cortisol have been demonstrated in sheep (Ley et al., 1994)
and horses with severe lameness (Galey et al., 1991; Clarke et al., 1982), but it is still
uncertain whether these alterations in cortisol concentration are only a result of the
severity of the disease or also plays a role in its etiology. These results have not been
replicated in cows with lameness (Ley et al., 1996). However, in other situations
involving pain and stress, including branding, castration, and dehorning (Lay et al., 1992;
Robertson et al., 1994; Stafford et al., 2002; McMeekan et al., 1998), cows demonstrate
elevated circulating cortisol concentrations. In addition, circulating DHEA concentrations
are altered (decreased) during castration stress in pigs (Carroll et al., 2006). Similar to
cortisol, information regarding serum DHEA concentrations in lame dairy cows is

lacking.

D. Pro-algesic versus analgesic actions of immune cells

Immediately following tissue injury, inﬂammatory and pain mediators are
delivered by the circulation (e.g., bradykinin), and by local tissue macrophages and
dendritic cells that are activated. The inﬂammatory response is then ampliﬁed by
migration of leukocytes into the inﬂamed tissue, by production of inﬂammatory
mediators, including cytokines (TNF-a, IL-1 and IL-6), chemokines (e.g., keratinocyte-
derived chemokine [KC], macrophage inﬂammatory protein-2 [MIP-2] and cytokine-
induced neutrophil chemoattractant-2 [CINC-2]), and nerve growth factor (NGF), as well
as by tissue acidiﬁcation (Rittner et al., 2005). Leukocytes are the source not only of
hyperalgesic agents but also of analgesic mediators. Among the best-characterized and

clinically relevant of these are the endogenous opioid peptides and their receptors. Other

47

analgesic mediators include anti-inﬂammatory cytolcines (IL-4, IL-10 and IL-13) as well
as somatostatin and the endocannabinoids (Rittner et al., 2005).

In later stages of inﬂammation, cytokines (e.g., IL—4, IL-10 and IL—13) are
produced by inﬁltrating leukocytes that limit inﬂammation and counteract hyperalgesia
(Cunha and Ferreira, 2003). Cellular sources of IL-4, IL-10 and IL-13 for analgesia
include mast cells and TH lymphocytes. The analgesic actions of IL-4, IL-10, and IL-13
are apparent in models of rat paw inﬂammation as well as in a model of peritonitis and
knee-joint incapacitation induced by zymosan (Cunha and Ferreira, 2003). Thus, during
inﬂammation, analgesic cytokines counteract the effects of the proinﬂammatory
hyperalgesic cytokines generated in the early stages of the inﬂammatory response.

Moreover, peripheral opioid receptors synthesized in dorsal root ganglia (DRG) at
the spinal cord are intra-axonally transported to the peripheral nerve endings (Mousa et
al., 2001). Upon activation by opioid ligands, opioid receptors couple to inhibitory G-
proteins (Gi/o), which leads to inhibition of calcium and (or) sodium channels, and to a
decreased level of neuronal cyclic adenosine monophosphate. Consistent with these
effects, opioids attenuate the excitability of nociceptors, the propagation of action
potentials, and the release of excitatory proinﬂammatory neuropeptides (substance P,
calcitonin gene—related peptide) from central and peripheral nociceptor endings (Stein et
al., 2003). All of these mechanisms result in analgesia.

Three families of opioid peptides are well characterized: endorphins, enkephalins,
and dynorphins. Each binds to all three opioid receptors (mu, kappa, delta) but with
varying afﬁnities. The opioid family derives from a single gene that is transcribed,

translated, and then processed into three peptides, pro-opiomelanocortin (POMC), pro-

48

enkephalin, and pro-dynorphin. All opioid peptides are expressed by leukocytes (Rittner
et al., 2005; Mousa et al., 2004), but endorphins deriving from processed POMC protein
have been studied most extensively.

The opioid-containing leukocytes are primarily T- and B-lymphocytes,
granulocytes, and monocytes/macrophages (Mousa et al., 2001; Rittner et al., 2001;
Cabot et al., 1997). These opioid-bearing cells migrate and accumulate in inﬂamed tissue
(Machelska et al., 1998, 2002, 2004; Brack et al., 2004; Brack and Stein, 2004), via
activation of adhesion molecules (e.g., CD62L) and chemokines (e.g., CXCR2 ligands
KC, MIP-2 and CINC-2). During stress stimulation (e.g., swim stress, surgery) or local
injection of corticotropin-releasing factor (CRF), leukocytes secrete opioids, which bind
to their receptors on peripheral sensory nerve endings (Stein et al., 1990; Stein, 1993;
Stein, 1996; Schafer et al., 1996). The magnitude of endogenous analgesia is reported to
be proportional to the number of opioid-containing polymorphonuclear cells (during early
inﬂammation) and mononuclear cells (during late inﬂammation) at the injury site (Brack
et al., 2004; Machelska et al., 2003). Moreover, the percent increase in proliferation of
human peripheral blood immune cells incubated with morphine ex vivo is highly
correlated with the subjects' tolerance to noxious cold stimuli (Hutchinson et al., 2004).
These data present the immune system as a potential novel source of cells in which to
investigate novel biological markers of pain tolerance. Similarly, the B-endorphin
concentration in peripheral blood mononuclear cells has been suggested as a diagnostic
tool for painful conditions such as ﬁbromyalgia (Panerai et al., 2002) and acute

myocardial infarction (Buratti et al., 1998), and certainly has the potential to be used as a

49

diagnostic tool for important painful conditions occurring in livestock, such as lameness

in dairy cows.

IV. DIAGNOSTIC BIOMARKERS OF DISEASE

A biomarker is a measurable indicator of a speciﬁc biological state, particularly
one relevant to the risk of contraction of disease or the presence and stage of disease
(Rifai et al., 2006). Biomarkers can be used clinically to screen for, diagnose or monitor
the activity of disease, and to guide molecularly targeted therapy or assess therapeutic
responses to drug treatment (Etzioni et al., 2003). The utility and importance of
biomarkers has been recognized by substantial funding from public and private
organizations, and efforts for biomarkers discovery are now commonplace in both
academic and industrial settings.

Recent developments in areas of research such as gene expression rrricroarrays,
proteomics, and immunology offer new approaches to disease screening (Henson et al.,
1999). Consequently, biomarkers have become exceedingly reﬁned. For example,
genomics researchers have moved beyond one-gene-at-a-time analyses, and are now
proﬁling thousands of gene transcripts to generate entire patterns of information that can
be used for a range of clinical purposes, including disease classiﬁcation or diagnosis,
prognosis, and treatment monitoring and surveillance. The quest for a single biomarker
for a particular disease has the illusion of analytical simplicity, but makes little sense
from a biological perspective. It is not surprising that, to date, we have failed to ﬁnd an
accurate single marker for foot and leg diseases associated with lameness in livestock,

which comes in hundreds of types and stages and is a product of several factors from

50

environmental to genetics, to nutrition and so on. Instead, why not take advantage of the
very complexity of the disease and search for several indicators that, if measured

simultaneously, may constitute a biomarker?

A. Biomarker discovery

Biomarkers can take any form, and as a consequence a variety of strategies have
been adopted for their discovery (Table 1.3). The potential for genomic biomarkers to
improve diagnosis, prognosis, treatment decisions and long-term outcomes can be
substantial, and provide an insight in disease etiology that is unprecedented. Dissection of
global changes in gene expression during pre-disease states, disease progression, and
following clinical treatment can provide great insight into disease mechanism and
treatment management (Chabas et al., 2001; Lock et al., 2002).

Global changes in gene expression during pre-disease states, disease progression,
and following clinical treatment can provide great insight into disease mechanism and
treatment management. For example, early investigations distinguished acute myeloid
and acute lymphoblastic leukemia cells using gene expression proﬁling (Golub et al.,
1999). Subsequent studies have used microarray technology to predict outcomes in breast
and ovarian cancers (Berchuck et al., 2005; Huang et al., 2003). Additionally,
classiﬁcation of diffuse large B-cell lymphomas on the basis of gene expression proﬁles
can identify clinically signiﬁcant subtypes of cancer and the new classiﬁcation has
signiﬁcant prognostic implications (Alizadeh et al., 2000). Examination of systemic lupus
erythematosus (SLE) using microarray technology identiﬁed a subgroup of patients who

may beneﬁt from new therapeutic options (Rus et al., 2002; Baechler et al., 2003).

51

Table 1.3 Different approaches for biomarker discovery. Adapted from Yun-Fu et a1.

 

 

 

 

 

 

 

 

 

processes, cells,
tissue, or organs

 

trials

 

(2005) and Crebs (2006).
Role Key activity Sources of Validation endpoints
discovery
Diagnostic Differentiates healthy Expression Correlation with a
from a speciﬁc analysis, speciﬁc disease state
disease state epidemiology
studies,
mechanism of
disease studies
Prognostic Predicts the likely Expression Correlation with a
course of disease analysis, clinical outcome
epidemiology
studies,
mechanism of
disease studies
Stratiﬁcation Prior to administration Pre-clinical Correlation with a
of a drug compound, studies, clinical clinical response to a
predicts which trials speciﬁc drug in
patients will respond controlled clinical
or suffer from adverse trials
effects
Pharmacodyna Tracks a drug’s in Metabolite Correlation with the
mic and vivo activity at analysis, animal concentration or
pharmacokinetic different models activity of a drug in
concentrations animal and human
studies
Efﬁcacy and Monitors the Molecular Correlation with the
outcome beneﬁcial effects of a targets, clinical activity of a drug in
speciﬁc drug on an trials clinical trials with
intended target or placebo controls
condition
Toxicity Indicates potentially Toxicology Correlation with the
harmful effects of a studies, concentration or
drug on any immunohistoche activity of a speciﬁc
unintended cellular mistry, clinical drug in clinical trials

 

52

 

B. Biomarker validation

Validation of the potential biomarkers can be achieved using an independent set
of samples (Koike et al., 2005). Furthermore, a second methodology platform can be used
to conﬁrm initial ﬁndings. For example, if mass spectrometry is used for biomarker
discovery, a different, more experienced platform can be used to validate and develop a
diagnostic assay (Constans, 2005). Similarly, gene expression proﬁles can be validated
using a new patient cohort and also performing real-time reverse transcriptase PCR to
support the initial ﬁndings of a microarray-based gene expression proﬁle (Gordon et al.,

2005).

C. Issues with biomarker research

As microarrays were one of the ﬁrst technologies used for large-scale discovery
of genomic biomarkers, the ﬁeld has made strides in developing standards for both
research and clinical applications. The promising results of microarray technology in
areas including cancer, cardiovascular, and inﬂammatory diseases raise the issue of
whether and how this tool could be used in other areas (i.e., lameness). However, several
issues remain to be addressed to improve conﬁdence in new biomarker discoveries and
enable comparability of datasets, including, sample quality, inter-platform differences,
user variability (e. g., hybridization techniques), and data analysis.

An obvious use of microarrays is to discover, in a “holistic” manner, genes that
are either up- or down regulated under various scenarios of interest. The high-
dimensionality of microarray data with examination of thousands of transcripts in a

relatively small number of samples raises the potential concern of creating false-positive

53

results. In addition to simple fold-changes, which fail to account for variability of
expression between groups, more advanced statistical tests based on multiple testing were
established, including the concept of the false discovery rate (FDR) which offers a
sensible balance between the number of true and false-positives and basically yields
probability values with higher stringency (Storey and Tibshirani, 2003). Given concerns
over microarray methodology, there is a demand that results of key changes in transcript
levels be conﬁrmed by independent methods. When the goal of microarray analysis is
gene discovery, usually independent methods such as quantitative real-time RT-PCR or
Western blots (for protein analysis) have been used to reproduce results of up- or down
regulated genes.

As many of these technologies produce large outputs, another major challenge is
data analyses and bioinformatics. Separating true signals associated with a speciﬁc
phenotype from background may be difﬁcult for a variety of reasons, including the
heterogeneity of the sample tissue, number of genes and clinical measurements, strength
of the signal, confounding factors, and genetic heterogeneity of the disease. While
classical biostatistical methods continue to be used, they often can not achieve the desired
power due to the large number of variables collected from relatively small sample sizes
(Allison et al., 2006), especially when studying complex diseases (e.g., lameness) on a
heterogeneous population (e.g., dairy cattle) using sub-optimal experimental designs

suited to the species being studied (e.g., farm level).

54

V. DISSERTATION’S HYPOTHESES

H1: A pressure plate is a sensitive tool for early detection of lameness in heifers suffering
from papillomatous digital dermatitis compared to Sprecher’s (1997) lameness scoring
system

H2: Circulating concentrations of key inﬂammation regulating steroids (cortisol and
DHEA) and indicators of PBMC activation (gene expression for IL-lB, CD62L, MMP-9,
POMC and GRa) are altered in lame cows showing sickness behavior and foot lesions
compared to healthy sound cows.

H3: Cows suffering from inﬂammatory and painful type of lameness derived from foot
lesions have a signature gene expression proﬁle of PBMC that is distinguishable from

that of healthy sound cows.

55

CHAPTER TWO

Early detection of lameness in heifers with hairy heel warts using a pressure plate
1. ABSTRACT

Lameness is an indicator of pain and suffering, is a welfare concern and has
economic impacts on the dairy industry. Subjective locomotion scoring is unreliable for
detecting mild cases of lameness in dairy herds. Undetected lameness can progress to a
more serious and painful state with unfavourable prognosis. The aim of this study was to
conduct an investigation on the use of a pressure plate for early detection of lameness in
dairy heifers compared to a subjective visual scoring system. Seven heifers deemed
sound on the basis of a visual scoring system were walked through a chute where an
RSscan pressure plate was disguised on the ﬂoor. Claws were inspected during trimming
and revealed either no lesions (11 = 3) or hairy heel warts on at least one hind claw (n = 4).
Peak vertical force (PVF) and right-left hindlimb PVF symmetry were calculated. Sound
heifers demonstrated signiﬁcantly higher PVF (5.32 :1: 0.62N.kg"; P = 0.01) and better
right-left hindlimb symmetry (1.04 :1: 0.02; P = 0.03) than those with hairy heel warts
(3.64 :I: 0.82 N.kg'l; 0.77 :1: 0.16). Using a pressure plate, gait abnormalities from foot
lesions, that were undiagnosed using a subjective lameness scoring system were detected.
Early detection of lameness is vital to reduce dairy industry losses and to improve animal

welfare.

11. INTRODUCTION
Lameness refers to an abnormal gait caused by painful lesions of the limbs or

back as the cow attempts to alleviate or avoid pain in the affected area (Scott, 1989) by

56

reducing propulsion, reducing her speed of walking, arching her back and lowering her
head. The annual lameness incidence rate in adult dairy animals, depending on farm,
location and year of study, ranges from 4 to 56% (Booth et al., 2004), and costs average
US$350 per incident (Greenough and Weaver, 1997). The most common lesions
associated with lameness are white line disease, sole and toe ulcers, heel erosion, double
sole, sole hemorrhage and papillomatous digital dermatitis (hairy heel warts) (Murray et
31,1996)

The main strategy used for lameness detection in dairy cattle consists of
subjective visual scoring that is based on qualitative assessments of kinematic measures.
Kinematic measures are descriptions of motion, during standing and walking, ranging
from a few measures of back posture and stride length (Sprecher et al., 1997) to a
combination of back posture, leg abduction, limb weight bearing, joint ﬂexion, relative
front to hind foot placement, head carriage and ‘smoothness’ of gait (Welsh et al., 1993).
Unfortunately, the subjective nature of visual scoring often results in high inter-observer
variability (Engel et al., 2003), especially in detecting subtle changes in posture and
weight bearing characteristic of mild cases of lameness (O’Callaghan et al., 2003). This
issue results in a large number of lame cows going undiagnosed and therefore treatment
is neglected, particularly in early stages of the condition when prognosis is favorable
(Logue et al., 1998). Therefore, methods of locomotion analysis that offer greater
accuracy without the biases that are inherent in a subjective analysis require investigation
as a means to improve lameness assessments in dairy cattle.

Changes in the vertical component of ground reaction forces have been

successfully used as indicators of lameness in horses (Clayton et al., 2000) and cattle

57

(Scott, 1989). Vertical ground reaction force can be measured using a pressure plate,
which offers better portability and lower cost compared to force plates. However, to date,
limited attempts have been made to objectively assess lameness in dairy cattle (e.g.
Herlin and Drevemo, 1997; Rajkondawar et al., 2002a; Tasch and Rajkondawar, 2004)
and information regarding the potential use of pressure plates for diagnosis is lacking.
The objective of this study was to perform a preliminary investigation on the
potential of a pressure plate as a tool for early detection of lameness in heifers suffering
from hairy heel warts and to determine the sensitivity of this device compared to a

subjective lameness scoring system (Sprecher et al., 1997).

H. MATERIALS AND METHODS

All procedures of the experiment were approved by the All-University Committee
on Animal Use and Care at Michigan State University. Seven Holstein heifers (age: 1.8 :1:
0.6 years, weight: 645 :1: 60 kg), deemed sound by an experienced veterinarian on the
basis of a visual lameness scoring system (Sprecher et al., 1997) were used in this study,
which was performed in early spring at a commercial dairy farm in Michigan, USA. A
pressure plate (Footscan Scientiﬁc version, RSscan International, Olen, Belgium) able to
measure vertical ground reaction force at a sample frequency of 250 Hz was used for data
collection. The pressure plate measured 100 cm x 40 cm with 8192 conductive pressure-
sensitive polymer sensors each of 0.39 cmz. The plate, and a surrounding board of the
same thickness measuring approximately 250 x 100 cm were placed level in a concrete
pathway. This pathway was located in a barn adjacent to the heifers’ home pen, which

was used to guide heifers to a trimming chute. The pressure measuring device was

58

covered and disguised with a non-slip carpet. Heifers were walked down the pathway
where measurements started at initial contact of the fore foot touching the plate.
Measurements from both fore and hindlimbs of one side of an animal were collected in a
single trial. Trials had duration of approximately 5 seconds. Data collection continued
until three good trials from each hindlimb were obtained for each heifer. A trial was
considered good when the hindlimb being analyzed was fully on the pressure plate
throughout its stance phase and the animal was walking at a constant speed (i.e. no
obvious visual signs of slowing down or speeding up) with no unusual body movements
(e. g. no stumbling or abnormal head placement).

On the following day, trimming was performed according to the farm’s standard
operating procedure and the claws were inspected. Lesion type and severity were
recorded. Heifers were then divided into a group with no foot lesions (11 = 3) and a second
group with hairy heel wart lesions on at least one hind foot (11 = 4). Trials from heifers
from these two groups were then subjected to analysis. Only one trial per hindlimb from
each heifer had acceptable quality to be included in the analysis. A trial was considered
acceptable when vertical ground reaction force exhibited a bimodal pattern on a force-
time graphical display (e.g. Scott, 1988; Rajkondawar et al., 2002a; 2002b). Insufﬁcient
trials were recorded from fore limbs from each heifer to analyze the data; hence the fore
limbs were omitted from the analysis.

Peak vertical force (PVF) was normalized by body mass (kg) and presented for
each hindlimb and as an average of both hindlimbs (N.kg") and right-left hindlimb PVF
symmetry were calculated. Differences in these variables between groups were analyzed

using SPSS statistical software (SPSS Inc., Chicago, Illinois, USA) at an alpha level of

59

0.05. As data were normally distributed (Kolmogorov-Smirnov P > 0.05), independent
Student t-tests for unequal (Levene's P < 0.05) and equal (Levene's P > 0.05) variance

were used as necessary.

IV. RESULTS

Heifers with no foot lesions demonstrated signiﬁcantly better right-left hindlimb
peak vertical force symmetry than heifers with foot lesions (1.04 :1: 0.02 vs 0.77 :1: 0.16; P
= 0.04). In addition, the presence of hairy heel wart lesions signiﬁcantly reduced the PVF
(averaged over right and left) compared to no lesions (3.64 :1: 0.82 N.kg'l vs 5.32 :1:
0.62N.kg"; P = 0.01) (Table 2.1). The subjective visual scoring system used in this study

was unable to detect lameness in heifers with hairy heel wart lesions.

V. DISCUSSION

A search for tools that can provide accuracy and account for biases inherent of
subjective analysis is timely. In this study, gait abnormalities associated with hairy heel
wart lesions undetected by Sprecher’s et al. (1997) lameness scoring system were
successfully revealed using a pressure plate. A lame animal reduces the load in the
affected limb as means of reducing pain. This study shows that the animal’s efforts at
load-reducing, which are often subjectively and unreliably assessed using visual scoring
systems, can be assessed objectively by measuring the peak vertical force using a
pressure plate. The demonstration of reduction in PVF in heifers with hairy heel wart
lesions supports the assertion that quantitatively measurable changes occur with

lameness, as previously demonstrated in cows (Rajkondawar et al., 2002a; 2002b; Scott,

60

1989) and horses (e.g. Merkens and Schamhardt, 1988) at the walk. Similarly, right-left
limb PVF symmetry changes were revealed to be a promising measure to detect lameness
associated with hairy heel wart lesions in heifers, which agrees with ﬁndings in horses
with experimentally induced lameness (Merkens et al., 1988).

To be considered an auxiliary diagnostic tool, data collection must be practical,
reliable, suit operating procedures in dairy farm settings and provide measures that can be
easily understood by people who are not necessarily knowledgeable in biomechanics.
Although the changes in the peak vertical force observed in this study characterized the
presence of hairy heel warts, further studies should be carried out to assess the sensitivity
of PVF to detect other important lameness conditions such as white line disease and sole
ulcers. Furthermore, the analysis of a single trial per limb might not be a sensitive enough
data capture method to detect lameness due to the impacts of high intra and inter—animal
variability. The variation observed between the three trials per limb within an animal
suggests that the magnitude of locomotion variation in heifers might be high and methods
to minimize it should be implemented. Overall, locomotion variability can be minimized
by using an average of multiple trials as a representative of the gait pattern, reducing
inter-trial walking velocity variation, and/or collecting data from both right and left limbs
simultaneously with a larger pressure plate. In horses, force variables are considered to be
quite stable, and analysis of three to ﬁve trials is accepted to provide a representative gait
pattern (Schamhardt, 1996). However in cattle such information is unknown. If several
trials are deemed necessary to provide representative gait pattern, the practicality of using
pressure plates for lameness assessment in dairy settings must be re-assessed and

technology would have to evolve to improve reliability of pressure plate measures.

61

Owing to the importance of maintaining a constant walking velocity to achieve reliable
pressure plate analysis (Khumsap et al., 2002), especially when data from right and left
limbs are collected in different trials, alternative ways to control cattle walking velocity

should be developed to improve detection of lameness in dairy systems.

VII. CONCLUSION AND ANIMAL WELFARE IMPLICATIONS

This study has shown that a pressure plate offers opportunities to objectively
detect lameness related gait abnormalities in heifers suffering from hairy heel warts.
Further validation of the vertical ground reaction forces and an approach for pressure
plate data collection is an important next step to develop this technique further as an
objective tool for the early detection of lameness in dairy cattle. Moreover, technology
will evolve to enable sources of variability during pressure plate data capture to be
minimized, for instance, the use of larger plates that would allow data collection from
right and left body sides simultaneously. Quantitative analysis of gait offers a means for
early and reliable detection of lameness that contributes to improvements in lameness

prognosis, reduction in dairy industry losses, and ultimately, to enhanced animal welfare.

62

Table 2.1 Mean peak vertical force (PVF) and right-left hindlimb PVF symmetry of
heifers (645 :I: 60 kg) with (n = 4) and without (11 = 3) ha' heel wart lesions. Values
marked with the same symbol were signiﬁcantly different. (P = 0.04) indicates PVF
differences between RH and LH of heifers with lesions; " (P = 0.01) indicates PVF mean
differences between hindlimbs heifers with and without lesions; ... (P = 0.04) indicates
PVF symmetry mean differences between hindlimbs of heifers with and without lesions.
RH = right hindlimb; LH = left hindlimb.

 

 

 

PVF RH PVF LH
Group PVF symmetry
(N.kg") (N.kg")
Lesions 3.08 (0.29) " 4.19 (0.82) "
Mean PVF 3.64 (0.82) " 0.77 (0.16)
No lesions 5.36 (0.60) 5.28 (0.76)
Mean PVF 5.32 (0.62) ” 1.04 (0.02)

 

63

CHAPTER THREE

P.E. Almeida, P.S.D. Weber, J .L. Burton, A.J. Zanella. 2007. Depressed DHEA and
increased sickness response behaviors in lame dairy cows with inﬂammatory foot lesions.

Domestic Animal Endocrinology. (in press).

CHAPTER THREE
Depressed DHEA and increased sickness response behaviors in lame dairy cows
with inﬂammatory foot lesions.

1. ABSTRACT

Lameness is a multifactorial condition inﬂuenced by the environment, genetics,
management and nutrition. Detection of lameness is subjective and currently limited to
visual locomotion observations which lack reliability and sensitivity. The objective of
this study was to search for potential biomarkers of inﬂammatory foot lesions that
underlie most cases of lameness in dairy cows, with a focus on the sickness response and
relevant endocrine, immune and behavioral changes. Serum and peripheral blood
mononuclear cells (PBMC) were collected from eight sound and eight lame high-
producing Holstein cows. Immune cell activation was investigated in PBMCs using a
candidate gene approach in which the expression of pro-opiomelanocortin, interleukin-
lbeta, L-selectin, matrix metalloproteinase-9 and glucocorticoid receptor-alpha was
measured via quantitative real time-RT-PCR. Endocrine changes were investigated by
monitoring serum concentrations of cortisol and dehydroepiandrosterone (DHEA).
Additionally, systematic behavioral observations were carried out to characterize a
behavioral proﬁle associated with a sickness response typical of this condition. Lame
cows showed signiﬁcantly lower eating (P = 0.004) and ruminating (P = 0.05) behaviors
and higher incidence of self-grooming (P = 0.04) compared to sound cows. Lame cows
also showed a 23% decrease in serum DHEA (P = 0.01) and 65% higher cortisol:DHEA
ratio (P = 0.06) compared to sound cows. However, no signiﬁcant differences were found

in candidate gene expression between lame and sound cows. Serum DHEA concentration

65

and cortisol:DHEA ratio are promising objective indicators of inﬂammatory foot lesions

in dairy cattle and may be useful as diagnostic targets for animals in need of treatment.

11. INTRODUCTION

Lameness in dairy cows refers to the abnormal gait used by the animals as an
attempt to alleviate or avoid pain from lesions and inﬂammation in the affected limb or
back area (Scott, 1989; Hardie, 2000). Lameness is not only perceived to affect the
welfare of the animals, but also has a high economic impact on the dairy industry with
costs averaging US$350 per clinical episode (Greenough and Weaver, 1997). These
costs include its treatment and control (Moore et al., 2001), impaired reproductive
performance (Sprecher et al., 1997), decreased milk yield (Warnick et al., 2001)
increased culling rate, and decreased carcass value of culled cows (Arendonk et al.,
1984). Estimated annual lameness incidence in adult dairy cows ranges from 4 to 55%
depending on farm, location, and year of study (Booth et al., 2004). This widely differing
estimate is suggested to be due to the sensitivity of lameness detection within individual
herds, how it is deﬁned and by whom (Whay et al., 1997). The highest incidence of
lameness is found to occur soon after calving (Offer et al., 2000) and claw horn lesions in
the hindlimbs represent about 90% of all lameness. Sole ulcers (40%) and white line
lesions (29%) are suggested to be the predominant diseases of horn, and digital dermatitis
(40%) is the most common skin disease (Murray et al., 1996). Realizing the economic
importance of lameness, its high incidence and implications to animal welfare due to pain
and discomfort, strategies to objectively diagnose, treat, and improve lameness outcomes

are urgently needed.

66

Lameness screening accuracy has been hindered by subjectivity, by low between-
and within-observer reproducibility of diagnosis (Wells et al., 1993; Engel et al., 2003),
and variable sensitivity and response of individual animals to pain (Hardy et al., 1967).
Currently, there are no reliable measures available to objectively screen cows for the
presence of lameness. Lameness diagnosis has been performed using subjective visual
scoring systems that focus on changes in locomotion. In addition to their unreliability,
these systems are not sensitive to detect mild cases of lameness (O’Callaghan et al.,
2003) because lesion severity is the predominant factor that leads to deterioration of
locomotion (Whay et al., 1997). As a consequence of detection unreliability, 30 to 50%
of cows are suggested to remain undiagnosed (Kopcha et al., 2003; Clarkson et al., 1996)
such that their lameness tends to progress to a more serious and/or chronic condition that
often has a compromised prognosis (Logue et al., 1998). Furthermore, the multifactorial
pathogenesis of lameness exacerbates the need for biomarkers that are not only able to
assist with diagnosis but also able to help better understand lameness etiologies.

In addition to changes in locomotion, lame cows display increased lying time,
decreased food-intake and altered social behaviors (Singh et al., 1993; 1994; Galindo et
al., 2002; Sauter-Louis et al., 2004). These behavioral modiﬁcations are intrinsic of a
psychoneuroirnmunological event known as ‘sickness response’. This event requires a bi-
directional communication between the immune system and the brain. During the
sickness response several changes in behavior and physiology occur to facilitate host
survival during infection and tissue injury (Hart, 1988). The behavioral changes noted in
lame cows support the notion that the immune system is involved in the pathogenesis of

this condition. In fact, tissue injury and infection, which are common elements of

67

lameness in dairy cows, are known to unleash the signals necessary for immune
activation. Inﬂammatory mediators released during immune activation (e.g., pro-
inﬂammatory cytokines) relay information to the brain (hypothalamus) about the events
in the periphery (Tracey, 2002). As a consequence, the brain initiates anti-inﬂammatory
mechanisms that culminate in the release of cortisol and dehydroepiandrosterone
[DHEA] by the adrenal cortex (Besedovsky et al., 1986). These anti-inﬂammatory
steroids down regulate the expression of inﬂammatory genes (e.g. proinﬂammatory
cytokines) in circulating leukocytes via steroid hormone receptors, especially
glucocorticoid receptors (GRa) (Jessop, 1999).

In response to tissue injury and infection, ruptured cells (e.g., mast cells,
neutrophils) release intracellular proteins that trigger cytokine production (e.g.,
proinﬂammatory cytokines - IL-lB, TNF-a, IL-6) In addition, vascular mast cells and
macrophages release products (e. g., histamines, eucosanoids, tryptases, pre-formed TNF,
cytokines, chemokines) that result in vasodilation and ﬂuid extravasation (swelling)
(Tracey, 2002). Leukocytes migrate from the vasculature to the injury site via adhesion
molecules, an important one being L-selectin (CD62L), and enhance inﬂammation
(Venturi et al., 2003). Neutrophils recruited to the injury site undergo degranulation,
phagocytosis, and respiratory burst (Nathan, 2002) that result in release of oxidants and
metalloproteinases (e.g., matrix metalloproteinase-9 [MMP-9]), both of which can
damage otherwise healthy tissue and up-regulate the inﬂammatory response (Di
Girolamo et al., 2006). Lymphocytes and monocytes recruited to the injury site can help
abate pain by synthesizing and delivering neuropeptides (e. g., pro-opiomelanocortin

[POMC]-derived B-endorphin) (Mousa et al., 2004). POMC is up-regulated in these

68

peripheral blood mononuclear cells (PBMC), the predominant endorphin-containing cell
types at later stages (> 96h) of acute inﬂammation (Rittner et al., 2001).

Limited and unsuccessful attempts have been made to detect physiological
changes (e.g., cortisol as in [Ley et al., 1996]) in cows suffering from lameness.
Leukocytes are known to carry gene expression signatures characteristic of other
physiological (Burton et al., 2005; Madsen et al., 2004; Weber et al., 2006a) and disease
states (Coussens et al., 2004a; 2004b; Hill et al., 2005; Meade et al., 2006). Therefore,
gene expression of these cells, along with the endocrine changes in response to brain
activation, may provide biomarkers for diagnosis of common inﬂammatory foot lesions
that result in dairy cattle lameness. We hypothesized in the current study that circulating
concentrations of key inﬂammation regulating steroids (cortisol and DHEA) and
indicators of PBMC activation (gene expression for IL-lB, CD62L, MMP-9, POMC and
GRa) would be altered in lame cows showing sickness behavior and foot lesions
compared to sound cows with no sickness behavior or foot lesions. Our objective was to
explore changes in key sickness behaviors and neuroendocrine-immune physiology as

potential biomarkers of lameness in dairy cows.

III. MATERIALS AND METHODS
A. Subjects

The study subjects were 16 Holstein cows with mean weight, age and days in
lactation of 1467 t 114 kg, 4.5 :1: 0.25 years, and 183 :1: 65 days, respectively. Use of
animals for this study was approved by the Michigan State University (MSU)’s All

University Committee on Animal Use and Care (AUF# 05/04-079-00). All cows were

69

owned by MSU, housed in a freestall housing unit built with a 10 degree slope, and fed
and cared for according to the standard operating procedures of MSU’s Kellogg
Biological Station Dairy Center research facility. Lame cows (11 = 8) selected for study
met two criteria suggesting that the animals were in pain: (i) abnormal gait and back
posture while walking and standing (Figure 3.1a), and (ii) presence of visible lesions on
at least one hindlimb at feet inspection (Figure 3.1b). The causes (i.e., sole ulcers,
footrot, sole bruising and interdigital dermatitis) and duration of lameness were not
determined and likely varied from cow to cow. Instead, lame cow selection was intended
to comprise a snap shot of clinical lameness in the herd at time of sampling, which is
representative of what may occur in health monitoring programs on commercial farms.
Sound cows (11 = 8) had normal (straight) back posture (Figure 3.1c) and no visible foot
lesions (Figure 3.1d). None of the cows on the study presented with pathological
conditions other than lameness and none of the lame cows were treated prior to blood

samples collection.

B. Blood collections and isolation of serum and PBMCs

Blood samples were obtained from animals during mid morning via jugular
venipuncture, using 2.5-cm l4-gauge needles (Fisher Scientiﬁc, Pittsburgh, PA). This
study was performed during the summer. Blood (~130 ml per cow) intended for PBMC
isolations was collected into 50 ml centrifuge tubes (BD Biosciences, San Jose, CA) that
contained 4 ml of acid-citrate dextrose (ACD) (Weber et al., 2004) as an anticoagulant,
and immediately placed on ice. An additional 8 ml of blood per cow was collected into

vacutainer tubes (10 ml tubes; BD Biosciences, San Jose, CA) containing no

70

anticoagulant. Serum was harvested (1000 x g at 4°C for 20 min) from these tubes within
an hour of blood collection and stored at —80°C until use for steroid analyses.

PBMCs were prepared from the ACD anticoagulated blood as previously
described (Coussens et al., 2002). Brieﬂy, blood tubes were centrifuged at 4°C for 30 min
at 1150 x g and resulting buffy coats containing the PBMCs were transferred into PBS
layers (32 ml) that were overlaid on 10 ml cushions of Percoll (1.084 g/ml; Sigma
Chemical Co. St. Louis, M0) in new 50 ml tubes. Buffy coats from 3 blood collection
tubes per cow were added to each Percoll gradient. The Percoll tubes were centrifuged at
500 x g for 40 min at room temperature to pellet erythrocytes and contaminating
granulocytes away from the PBMCs (lymphocytes and monocytes), which remained
ﬂoating on the top of the Percoll gradient. The PBMCs were then retrieved and
transferred to a series of new 50-ml conical tubes and washed once with 20 ml of cold
PBS. Final cell pellets were collected by centrifugation for 10 min at 800 x g at 4°C. The
cell pellets were suspended in 4 ml of TRIzol reagent (Invitrogen, Carlsbad, CA) and
incubated for 10 minutes at room temperature to ensure lysis of PBMCs and preservation
of their released RNA. This mixture was then frozen at -80°C until use for RNA isolation
(see below). Time from blood sampling until PBMC lysis in TRIzol averaged 3 h. All

procedures for PBMC preparations were done using sterile reagents and supplies.

C. RNA isolation
Total RNA was isolated from PBMCs according to the TRIzol manufacturer’s
instructions (Invitrogen) and treated with RQl RNase-Free DNase (Promega, Madison,

WI) as described previously (Madsen et al., 2004). RNA concentration and purity were

71

determined with a ND-1000 spectrophotometer (NanoDrop Technologies Inc.,
Wilmington, DE) and Agilent 2100 Bioanalyzer (Quantum Analytics Inc., Foster City,
CA), respectively. cDNA was synthesized from 2 pg of total RNA per sample using

Superscript H RN aseH- Reverse Transcriptase (Invitrogen).

D. Real time RT-PCR standard curve preparation

Quantiﬁcation of mRN A can be either relative or absolute. Absolute
quantiﬁcation of transcript abundance allows the precise determination of copy number
per cell number or unit mass of tissue. However, it requires the construction of standard
curves from various known dilutions of PCR-derived amplicons for each candidate gene
under study (Bustin, 2000). Standard curves for use in the quantitative real time RT-PCR
assays of the current study were created as recently described by Madsen-Bouterse et a1.
(2006). Brieﬂy, PCR amplicons for IL-lB, GRd, POMC, MMP-9 and CD62L were
developed from bovine-speciﬁc PCR primers (Table 3.1) that were designed using
OLIGO Primer Analysis Software (Molecular Biology Insights, Inc. Cascade, CO). A
standard curve for a control gene (B-actin) was also developed to check for sample
loading consistency across lameness groups and wells of the real time PCR plates. The
PCR reaction mixtures contained 1X PCR buffer, 3 mM MgC12, 0.2 mM dNTPs, 0.2 M
forward primer, 0.2 M reverse primer, 35 ng cDNA template (from bovine PBMCs), and
1.0 U per reaction Taq DNA polymerase (Invitrogen), brought to a ﬁnal volume of 25 ml
with sterile Milli-Q water. Reaction conditions used to generate the PCR amplicons were
as follows: denature at 95°C for 5 min followed by 35 cycles of 95°C for 30 seconds (5)

(denature), 52°C for 30 s (anneal), and 72°C for 30 s (extend), and a ﬁnal extension at

72

72°C for 10 min. The resulting single band amplicons for each candidate gene were gel
puriﬁed, ligated into the pGEM-T Easy vector (Promega), and the recombinant plasmids
were transformed into JM109 competent E. coli cells (Promega). Positive clones
containing the IL-IB, GRa, MMP-9, POMC, CD62L and B-actin cDNA inserts were
selected by blue/white colony screening and conﬁrmed by DNA sequence analysis (MSU
Research Technology Support Facility). Plasmids from white colonies were isolated
using the Mini-prep Plasmid DNA Isolation kit (Promega). Additional amplicons for IL-
113, GRa, POMC, MMP-9, CD62L and B-actin were then generated by PCR using the
respective plasmids as template and primers shown in Table 3.1, and gel puriﬁed prior to
dilution for their use as template to develop the quantitative real-time RT-PCR standard

curves.

E. Quantitative real-time RT-PCR analysis of PBMC gene expression

As described in Madsen-Bouterse (2006), ﬁve to six concentrations of each
amplicon (l x 10"8 to 1 x 10'13 g), or 20 ng of test PBMC cDNA were added as templates
for the quantitative real-time RT-PCR analyses, which utilized the SYBR Green PCR
Master Mix system for real time ﬂuorescence detection in a PE7700 thermal cycler
(Perkin Elmer Applied Bioscience; Foster City, CA). The real time RT-PCR primers for
IL-10, GRa, POMC, MMP-9, CD62L and the B-actin control gene are shown in Table

TM software (version 2.0, Applied

3.2 and were created using the Primer Express
Biosystems). Ampliﬁcation efﬁciency, observed as parallel slopes of the ampliﬁcation
curves, was similar between the standard curve amplicon and test PBMC cDNA within

gene, and the standard curves were always linear (R2 > 0.9; Figure 3.2). IL-lB, GRd,

73

POMC, CD62L and B-actin mRNA abundance in samples from lame and sound cows
was determined using the equation for each standard curve. All reactions, including a

template negative control (no cDNA template) were run in triplicate.

F. Cortisol and DHEA assays

Serum concentrations of anti-inﬂammatory steroids were determined using two
commercial kits: (i) the Cortisol Correlate-BIA (Assay Designs, Ann Arbor, MI), and (ii)
the DHEA Correlate—BIA kits (Assay Designs) following the manufacture’s instructions.
A serum dilution factor of 1:16 was used for the cortisol assay and of 1:50 for the DHEA
assay. All samples per assay were processed on single plates. Assay sensitivity for

cortisol was 56.7 pg/ml and for DHEA was 2.9 pg/ml.

G. MMP-9 assay

MMP-9 total activity in serum of lame and sound cows was measured using a
gelatin zymography assay as in (Weber et al., 2006a). Brieﬂy, serum volumes equivalent
to 50 pg of total protein per sample were loaded into each lane of one-dirnensional SDS-
polyacrylamine gels impregnated with 0.25% (w/v) gelatin (Precast 10% Zymogram
Ready Gel, Biorad, Hercules, CA). Gel electrophoresis was conducted at 65V for 30
min, then 120 V for an additional 60 min. Subsequently, gels were washed twice for 30
minutes in 2.5% (v/v) Triton X—100 to remove SDS, and then incubated in 50mM Tris
(pH 7.5), 5mM CaClz and 0.02% Na N3 at 37°C for 18 h to enable MMP-9 activity (i.e.,
degradation of the gelatin). Gels were stained with Coomassie brilliant blue stain in 25%

methanol, 10% glacial acetic acid for 60 min to visualize clear bands of digested gelatin.

74

Band images were collected on the Fluor-S Multilmager (BioRad) and the density of
clearings at the 92 KDa marker (indicating MMP-9) analyzed by scanning densitometry

(GS-710 Calibrated Imaging Densitometer and Multi-Analyst Software; Biorad).

H. Observation of sickness behaviors

Focal sampling and continuous recording were used to collect maintenance,
feeding, social and grooming behavior performance (Table 3.3). Brieﬂy, focal sampling
means observing one individual animal for a speciﬁed amount of time and continuous
recording means observing all instances of its behavior at that time given frame — usually
for several different categories of behavior (Martin and Bateson, 1993). During a period
of 3 consecutive days and starting on the day of blood collection, 2-minute observations
were made in lS-minute intervals for a total of 4 hours per day (96 minutes of total

observation time).

1. Statistical analysis

Statistical analyses of steroid and mRN A abundance and behavioral data sets
were performed using the MIXED procedure of SAS (SAS Institute, Cary, NC), with a
model that included lameness group as the ﬁxed effect and cattle age (in days), weight (in
kg), day in lactation (in days), and pregnancy status (yes, no) as covariates. Lesion types
were not accounted for in the statistical model because these were not diagnosed. Data
sets were checked for parametric statistical assumptions (e.g. normality and equal
variances) before statistical analysis using the One-Sample Kolmogorov-Smirnov

procedure and Levene’s test (Ott and Longnecker, 2002). Logarithmic transformation

75

was performed on variables not meeting the assumptions for parametric statistical
analysis (i.e., gene expression data sets) prior to statistical analysis. Statistical
signiﬁcance of the lameness group effect was considered when P S 0.05, and a signiﬁcant

tendency was considered when 0.05 < P S 0.10.

IV. RESULTS
A. Behavioral observations in lame versus sound cows

As expected, lame cows showed classical sickness responses in that they had
signiﬁcantly decreased eating (P = 0.01; 8.85 :1: 2.22 min), ruminating (P = 0.01; 18.41 :1:
3.34 min), and increased self-grooming (P = 0.05; 3.91 :1: 0.71 min) behaviors compared
to sound cows (17.36 i 2.03 min; 28.57 i 3.06 min; 1.13 :1: 0.65 min, respectively)

(Table 3.4).

B. Serum steroids in lame versus sound cows

< 0.05)

Lame and sound cows demonstrated signiﬁcantly different (P
concentrations of the anti-inﬂammatory steroid DHEA. DHEA was approximately 23 %
lower (P = 0.01) in lame (543.2 x 34.2 g/ml) compared to sound (702.5 :I: 37.1 pg/ml)
cows (Figure 3.3a). Although serum cortisol of lame cows (2690.7 :1: 579.2 pg/ml) was
approximately 49% higher than that of sound cows (1391.8 :1: 583.7 pg/ml), this
difference was not statistically signiﬁcant (P = 0.16) (Figure 3.3b). The ratio of
cortisol:DHEA has been suggested as being more informative than isolated cortisol
values (Butcher et al., 2005), largely due to the antagonist actions of DHEA on cortisol

actions (Kalimi et al., 1994). In the current study, the serum cortisol:DHEA ratio was

76

65% higher (P = 0.06) in the lame (5.44 :1: 1.12) than the sound (1.88 :1: 1.13) cows
(Figure 3.3c), suggesting that endocrine regulation of inﬂammation was somewhat out of

balance in the lame animals.

C. PBMC gene expression in lame versus sound cows

The cDNA for 4 of the candidate genes studied (POMC, IL-lﬂ, CD62L, and .
GROt) was readily ampliﬁed in real time RT-PCR reactions and resulting mRN A
abundances were thus quantiﬁed for statistical analysis using the corresponding linear
standard curves. Results showed that in this group of animals, no differences were
detectable in mRNA abundances for any of these 4 genes between lame and sound cows
(Table 3.5). Expression of the control gene, B-actin, also was not different from sample
to sample (or well to well), as expected. Somewhat surprisingly, the expression of MMP-
9 was so low in the PBMCs as to preclude its detection, even in PBMCs from the lame
cows, using this real time RT-PCR approach. Therefore this data set was omitted from
statistical analysis and we concluded PBMC MMP-9 gene expression did not differ

signiﬁcantly between lame and sound cows.

D. MMP-9 activity in serum of lame and sound cows

Despite lack of detectable gene expression for MMP-9, this enzyme is normally
secreted during inﬂammation by activated neutrophils and PBMCs and can thus be
detectable in serum using gelatin zymography. However, similar to MMP-9 mRN A
abundance in the PBMCs, the activity of this proteolytic enzyme in serum was too low in

most serum samples to be measured accurately by scanning densitometry and this data set

77

was omitted from statistical analysis. Because detection of a related, constitutively
expressed matrix metalloproteinase (MMP-2) showed equal band intensities across all
samples (representative zymography gel shown in Figure 3.4), neither sample loading
error nor assay conditions appeared to be the cause of the variably low MMP-9 activity in
the sera. Thus, like PBMC MMP-9 gene expression, we concluded that serum MMP-9

activity was not different between lame and sound cows.

V. DISCUSSION

The current study showed that lame cows exhibited behavioral changes consistent
with the sickness response and which occurred in conjunction with clear changes in the
neuroendocrine system but, surprisingly, with little impact on expression of classical
inﬂammatory and pain relieving genes in PBMCs. However, the low number of
biological replicates, multiple etiologies, and unknown chronicities of the lameness
included in this study likely hindered statistical power and need to be carefully
considered in future studies. Moreover, despite the obvious sickness response in severely
lame cows, the localized nature of the inﬂammatory process that underlies such lameness
cases might represent a limitation to ﬁnding changes in circulating PBMCs. Nonetheless,
the systemic endocrine changes observed here are novel and should be expanded upon
and explored further as potential candidate markers of lameness due to inﬂammatory foot
lesions.

The sickness response consists of a myriad of immune (e.g., fever and
hyperalgesia), behavioral (e.g., increased sleep and decreased locomotion, sexual

behavior, exploration, and food and water intake), and endocrine (e.g., release of classic

78

stress hormones from the sympathetic nervous system and hypothalamic-pituitary—adrenal
axis [HPA]) changes that are mainly driven by proinﬂammatory cytokines released from
damaged tissue and activated immune cells (Buckingham, 1996). Activation of the HPA
axis increases adrenocorticotrophic hormone (ACTH) synthesis in the pituitary gland that
stimulates the cortex of the adrenal glands to release stress steroids, especially
glucocorticoid (cortisol) and androgen (DHEA) (Bauer, 2005; Butcher et al., 2005). Both
of these steroids are anti-inﬂammatory, but cortisol is highly immunosuppressive (Cupps
and Fauci, 1982) while DHEA has clear immune protecting activities (Sacco et al., 2002).
In fact, there is evidence that DHEA has an ‘anti-glucocorticoid’ effect in animals and
humans (Svec and Porter, 1998). DHEA has also been described to increase resistance to
viral and bacterial infections (Loria et al., 1996; Zhang et al., 1999), inhibit the
production of IL-6 thereby reversing immunologic defects during aging (Du et al., 2001;
Daynes et al., 1993), restore immune function after thermal and trauma-hemorrhage
injury, and reduce mortality rates from septic challenge (Ben-Nathan et al., 1999; Marx et
al., 2003). DHEA concentration is reported to fall during severe infection (Rook et al.,
1997) and chronic inﬂammatory diseases such as systemic lupus erythematosus,
inﬂammatory bowel disease, rheumatoid arthritis and polymyalgia rheumatica (Masi et
al., 1984; Deighton et al., 1992; Lahita et al., 1987; Straub et al., 1998; Dillon, 2005).
DHEA also is dramatically reduced during ageing humans in conjunction with the onset
of increased risk of immune dysfunction and inﬂammatory disease (Buckingham et al.,
1996). It was thus not surprising that serum DHEA concentration was lower in the lame
compared to the sound cows, reﬂecting the chronic inﬂammatory nature of the lameness

cases included in this study. The reason for the DHEA depression during chronic

79

inﬂammation is unknown, however, it is assumed that this may lead to a heightened state
of tissue damage because DHEA normally inhibits expression of potent proinﬂammatory
cytokines such as TNF—a and IL-6 (Danenberg et al., 1992; Araghi-Niknam et al., 1997;
Di Santo et al., 1996; Kimura et al., 1998). Furthermore, the unaltered cortisol
concentration found in lame cows supports the premise that a reduced serum DHEA is
often coupled with stable or increased serum glucocorticoid concentrations (Straub et al.,
2002). The cortisol:DHEA imbalance observed in the lame cows could represent a cause
or an effect of this painful inﬂammatory disorder. Whether cause or effect, the
cortisol:DHEA ratio appears to be 1a candidate diagnostic tool for inﬂammatory foot
lesions and associated lameness worthy of further testing.

The activation of the pituitary-dependent adrenal response, characterized by
changes in DHEA and sickness behaviors, provides evidence for the fact that the stimuli
from the inﬂammatory foot lesions in lame cows does indeed reach the central nervous
system to stimulate anti-inﬂammatory and/or healing signals. Therefore, the lack of
changes in the inﬂammatory gene expression observed in PBMCs was surprising and
unexpected due to the importance of these genes as modulators of the immune-to-brain
bi-directional communication and inﬂammatory network However, unaltered expression
of these particular genes might be explained by the lack of profound change in circulating
cortisol in the lame versus sound cows. Elevated cortisol is one of the prerequisites for
anti-inﬂammatory signaling in leukocytes that includes down-regulation of its own
receptor (GRa) (Raubenheirner et al., 2006), and acute phase cytokines (e.g., IL-1 [3) and
neuropeptide (e. g., POMC derived B-endorphin) synthesis (Besedovsky et al., 1986). The

unaltered levels of MMP-9 expression between lame and sound cows also was surprising

80

because MMP-9 is involved in tissue destruction during inﬂammation and it is known to
mediate the extravasation of PBMCs to the injury sites (Constantinescu et al., 2001).

If indeed an inﬂammatory response is present in lame cows then circulating levels
of other proinﬂammatory cytokines may be altered to enable immune-to-brain
communication, which may have been represented here by the decrease in serum DHEA
concentration and increase in sickness behaviors (i.e. reduced eating, altered locomotion
and posture). Alternatively, the immune-to-brain communication could have been
achieved via stimulation of the efferent vagus nerve (Maier et al., 1998) which, through
the cholinergic anti-inﬂammatory pathway, controls inﬂammation in discrete and
localized tissues where invasion and injury typically originate (Borovikova et al., 2000).
Thus, circulating leukocytes might not be inﬂuenced by this route of immune-to-brain
activity, possibly explaining the lack of differences in PBMC gene expression observed
between lame and sound cows. On the other hand, it is also possible that PBMCs may not
be good cellular indicators of well-localized inﬂammatory events, such as in lame cows
with inﬂammatory foot lesions. Although information about the chronicity of foot lesions
included in the study is unknown, the unaltered gene expression differences in lame
versus sound cows might have been the result of the chronic nature of the foot lesions,
which could have impaired or desensitized the immune system for pain control and
healing induction. As such, a broader genome-wide search for gene expression
biomarkers of the pathological conditions that underlie lameness likely will be needed in
the future.

In conclusion, this study tested a variety of parameters as candidate biomarkers of

inﬂammatory foot lesions in lame dairy cows exhibiting sickness behavior. However, the

81

sensitivity and speciﬁcity of the current results need to be tested in a larger sample of
animals with varying etiologies and severities of foot lesions. Biomarker validation could
also be expanded to testing PBMC and serum samples using more global screening
platforms, such as those available for genomic and proteomic analyses. Nonetheless, the
depressed serum DHEA concentrations and increased serum cortisol:DHEA ratios
detected in this study appear promising for lameness detection and may indicate DHEA
as a possible anti-inﬂammatory therapy for the treatment of clinical lameness. Results of
this study thus suggest that, in combination with observations of locomotion and sickness
behaviors, assessment of serum DHEA concentration (or the cortisol:DHEA ratio) might
help target animals in need of pain relief and facilitate the monitoring of lameness

therapies.

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Table 3.3 Behavior categories recorded and their deﬁnitions.

 

 

 

Behavior categories Definition

Maintenance:

Walking Movement of legs with a change in space
Standing on 4 limbs Supported by 4 feet

Standing on 3 limbs Supported by 3 feet

Laid Not supported by feet

Feeding:

Eating Head in head-gate leading to feed bunk
Drinking Muzzle in water cup

Ruminating Chewing

 

Social Grooming:
Self-grooming
Allo-grooming
Agonist interaction

Non-agonistic interaction

Licking or rubbing a part of its own body
Licking or rubbing another animal
Initiator of contactual behavior

Receiver of contactual behavior

 

85

Table 3.4 Behavioral proﬁle of lame (n = 8) and sound (11 = 8) cows. LSMeans (1 SEM)
are represented as the duration (min) of each behavior over the time period studied (see
Materials and Methods). * P S 0.05 for main effect of lameness group.

 

Lame Sound P-value
Behavior
Time (min) Time (min)

Ruminating 18.41 1 3.34 * 28.57 1 3.06 0.05
Eating 9.09 1 2.25 * 21.83 1 2.45 0.004
Self-grooming 4.13 1 0.73 * 1.48 1 0.79 0.04
Laid 30.21 1 6.05 37.43 1 6.59 0.45
Standing on 3 limbs 6.56 1 3.26 3.59 1 3.55 0.70
Standing on 4 limbs 47.36 1 8.03 37.17 1 8.75 0.43
Walking 5.29 1 1.36 2.24 1 1.48 0.17
Drinking 1.65 1 1.12 2.40 1 1.22 0.67
Agonistic interaction 2.11 :1: 1.41 1.61 1 1.54 0.82
Non-agonistic interaction 0.67 1 0.45 0.74 1 0.49 0.92

 

86

Table 3.5 Quantitative real time RT-PCR analysis of PBMC mRN A abundance (in logz
fentograms, fg) of the inﬂammation regulating genes pro-opiomelanocortin (POMC),
interleukin-113 (IL-113), L-selectin (CD62L), and stress hormone glucocorticoid receptor
alpha (GRa) gene. B-actin is shown as a control gene. Data represent LSMeans (1 SEM)
of mRN A abundance for lame (n = 8) versus sound (11 = 8) cows.

Gene Lame Sound P-value

[mRNA] (Ln fg) [mRNA] (Ln fg)

 

POMC 2.80 1 0.70 2.62 :I: 0.78 0.95
IL-lB 0.68 1 0.17 0.67 1 0.24 0.26
CD62L 3.42 1 1.00 3.40 :1: 1.55 0.32
GRa 1.19 1 0.30 1.03 1 0.35 0.23
B-actin 10.26 1 0.63 10.56 1 0.55 0.72

 

87

Figure 3.1 General stance and foot lesion proﬁles of lame and sound cows. Lame cow:
(3) arched back posture (courtesy of Zinpr®Corporation, Eden Prairie, MN) and (b) foot
lesion. Sound cow: (c) straight back posture (courtesy of Zinpr®Corporation, Eden
Prairie, MN) and ((1) no visible foot lesions.

 

88

Figure 3.2 Standard curves used for absolute quantiﬁcation of the expression of
candidate genes.

Cycles to threshold

 

 

 

 

 

 

 

 

 

 

 

POMC CD62L
40 f
30 ». / l
20 I 1
10 . y=-l.36Ln(x)-23.17 . y=-l.28Ln(x)-20.15
0 e R2=0.99 R2=0.99
MMP-9 li-actin
40 F r
30 f /
20 .
10 — y=-l.50Ln(x)-22.69 y=-l.20Ln(x)-l3.82
0 R2=0.97 R2=0.9l
113.10 1512 115-14 113-16
40 - IL-IB r GRG
3o » .
20 ~ -
10 . y=-l.39Ln(x)-21.83 r y=-l.34Ln(x)-20.45
0 . ,R2=0,99 . 7 Itz=099 .
113-12 113-14 113-16 113-13 113-12 113-14 113-16 1E-18
cDNA (g)

89

Figure 3.3 Cortisol (a), DHEA (b) concentrations, and cortisol:DHEA (c) ratio in sera of
lame (n = 8) and sound (11 = 8) cows. The bars represent LSMeans (1 SEM) of lame (dark
bar) and sound (white bar) cows. * P = 0.01 and T P = 0.06 for the main effect of
lameness group.

3500

 

2500 1

pghnl

 

1500-;

i

500u1w-11

 

 

 

Cortisol

b)

800
__ 700 -
a. 600 a
Q.

500 ..

400 ~__-

 

 

 

 

DHEA

Ratio

   

 

 

Cortisol/DH]; A

90

Figure 3.4 Representative gelatin zymogram of MMP-9 and MMP-2 activities in serum
of lame and sound cows. Lanes 1, 3 and 5 are sera from lame (L) cows while lanes 2, 4
and 6 are sera for sound (S) cows. Little to no MMP-9 activity was detected in any sera
despite clear and consistent MMP-2 activity in all sera.

92 KDa
72 KDa

MMP-9
MMP—2

 

91

CHAPTER FOUR
Signature gene expression of peripheral mononuclear cells in lame dairy cows with

inﬂammatory foot lesions.

1. ABSTRACT

Lameness is a major health issue and likely the single most common cause of pain
and discomfort in dairy cattle. Appropriate treatment is delayed or neglected due, in part,
to lack of reliable diagnosis. Assessment of cows with lameness is currently limited to
subjective visual scoring systems based on locomotion and posture abnormalities. These
systems are unreliable to detect lameness, and therefore, a large number of cows remain
lameness associated with painful inﬂammatory foot lesions in dairy cattle using
microarray-based gene expression proﬁling of peripheral blood mononuclear cells
(PBMC). BOTLS microarrays spotted in duplicate with cDNA representing bovine
immune response genes were interrogated with cDNA samples in an 8-array, balanced
design. Samples from eight lame cows with foot lesions related-lameness and from eight
sound cows were pair-matched by age, weight, days in lactation, and pregnancy status at
time of PBMC collection and directly compared with each other on individual arrays.
Statistical analysis of resulting ﬂuorescence intensity data revealed 31 genes that were
putatively differentially expressed in lame versus sound cows (P < 0.05). Of these,
BLASTn analysis and gene ontology information showed that 28 genes had high
similarity or homology to known human and/or rodent genes. Validation of 15 of these
genes known to be important in inﬂammation and pain was carried out using relative

quantitative real-time RT-PCR, which conﬁrmed the up regulation of interleukin (IL)-2

92

(12.68 1 1.47 fold increase) and IL-10 (2.39 1 0.55 fold increase), matrix
metalloproteinase-13 (MMP-l3) (10.44 1 1.14 fold increase), and chemokine C-C motif
receptor-5 (CCR5) (5.26 1 1.05 fold increase), in lame relative to sound cows (P S 0.05).
Similarly, granulocyte-macrophage colony-stimulating factor receptor alpha chain
precursor (GM-CSF-R-alpha) (2.30 1 0.63 fold increase) and IL-4 (2.06 1 0.59 fold
increase) showed a tendency (P = 0.10) for up regulation in lame compared to sound
cows. PBMC co-expression of IL-2, MMP-l3, CCR5 and IL-10, and potentially IL-4 and
GM-CSF—R-alpha appears to be a promising, objective signature of lameness-related
inﬂammatory foot lesions in dairy cattle. In conclusion, this study revealed potential
biomarkers of severe lameness in dairy cattle. In addition to boosting diagnostic
reliability, the prospect of developing such biomarkers of lameness could help identify
animals in need of pain relief and provide appropriate molecular targets for the

development and monitoring of novel lameness therapies.

II. INTRODUCTION

Lameness in cattle is a debilitating condition which is often associated with tissue
damage, pain, and discomfort and manifests as an inability to walk normally
(O’Callaghan, 2002). This condition continues to be one of the largest ﬁnancial drains on
the North-American dairy industry, and one of the greatest concerns for animal welfare.
Visual observation, the most commonly used method for lameness recognition, is time-
consuming, unreliable, non-sensitive, and requires great skill on the pan of the herdsman
(Whay et a1. 1997; O’Callaghan et a1. 2003; Wells et al. 1993; Kopcha et a1. 2003). Due

to inappropriate diagnosis, treatment for lameness is often delayed or neglected and this

93

condition progresses to a more chronic or severe state that often has a compromised
prognosis (Logue et a1. 1998). Furthermore, common misconceptions regarding the
ability of cattle to experience pain and the paucity of licensed veterinary products
(O’Callaghan, 2002) might aggravate welfare problems. Attempts to develop objective
methods for lameness diagnosis are limited.

The use of objective measures of locomotion alterations, such as through
biomechanics, appears promising (e.g., van der Tol et al., 2004; Scott, 1989;
Rajkondawar et al., 2002b). However, because of the multifactorial and etiopathogenesis
complexity of lameness, a one-dirnensional measure (e.g., gait change) may not provide
enough accuracy and sensitivity to characterize all lameness types. Physiological
measures to assist with lameness assessment are improving (e.g., cortisol:DHEA ratio as
in Almeida et al., 2007 in press) and research aimed to expand the use of objective
measures to enhance lameness detection accuracy, and ultimately, dairy cattle welfare,
should be encouraged.

Although still in the early stages of research and development, genomic
biomarker research can provide a comprehensive insight into pathophysiological
processes as well as more precise predictors of outcome not previously attainable with
traditional biomarkers (e.g., protein, biochemical) (Ginsburg and Haga, 2006). For
instance, microarray-based gene expression proﬁling is a powerful approach for the
identiﬁcation of molecular biomarkers of disease, such as in human cancers (DePrimo et
al., 2003) and inﬂammatory disease (Heller et al., 1997). Microarrays allow rapid
measurement of the expression levels of thousands of transcripts in a single experiment

and comparison of expression patterns across many samples (Lockhart et a1, 1996). In

94

livestock, immune-based expression signatures for Johne’s disease (Coussens et al.,
2004a; 2004b), trypanosomiasis (Hill et al., 2005) and tuberculosis (Meade et a1, 2006)
have been discovered using microarray-based gene expression proﬁling.

Similar to the examples described above, a molecular diagnostic assay using a
clinically accessible tissue, such as blood, could greatly assist with detection of painful
inﬂammatory lameness in dairy cows. Gene expression proﬁling of peripheral blood
mononuclear cells (PBMC) to assist with lameness diagnosis has never been documented.
PBMCs are responsible for the comprehensive surveillance of the body for signs of
infection and disease and therefore may be good sources of information about organismal
status. For example, Vollmer-Conna et a1. (2004) demonstrated a correlation between
PBMCs derived proinﬂammatory cytokines and sickness behavior, while Maas et al.,
(2002) identiﬁed speciﬁc PBMC proﬁles in patients with autoimmune diseases such as
rheumatoid arthritis, systemic lupus erythematosus, type I diabetes, and multiple
sclerosis. Moreover, altered gene expression in PBMCs correlates with inﬂammatory
bowel disease pathogenesis (Mannick et al., 2004).

In addition to altered locomotion, lame cows experience pain (Whay et al., 1997;
Rushen et al., 2006) and show systemic signs consistent with sickness response including
decreased food-intake (Almeida et al., 2007), increased lying time (Singh et al., 1993),
altered social behaviors (Galindo and Broom, 2002), and hyperalgesia (Whay et al.,
1997). The hypothesis of this study was that cows suffering from inﬂammatory and
painful type of lameness derived from foot lesions have a signature gene expression

proﬁle of PBMC that is distinguishable from that of sound cows. The objective of this

95

study was to search for potential biomarkers of painful inﬂammatory foot lesions in lame

dairy cattle using a microarray-based gene expression proﬁling approach.

111. MATERIALS AND METHODS
A. Subjects

The study subjects were 16 Holstein cows with mean weight, age and days in
lactation of 1467 1 114 kg, 4.5 1 0.25 years and 183 1 65 days, respectively. Use of
animals for this study was approved by the Michigan State University (MSU)’s All
University Committee on Animal Use and Care (AUF# 05/04-079-00). All cows were
owned by MSU, housed in a freestall housing unit built with a 10 degree slope, and fed
and cared for according to the standard operating procedures of MSU’s Kellogg
Biological Station Dairy Center research facility. Subject selection was performed as
described in Almeida et a1. (2007). Brieﬂy, lame cows (11 = 8) met the two selection
criteria: (1) abnormal gait and back posture while walking and standing and (ii) presence
of visible lesions on at least one hindlimb at feet inspection, suggesting that the animals
were in pain. The causes (e.g., sole ulcers, footrot, sole bruising and interdigital
dermatitis) and duration of lameness were not determined and likely varied from cow to
cow. Instead, lame cow selection was intended to comprise a snap shot of clinical
lameness in the herd at time of sampling, which is representative of what may occur in
health monitoring programs on commercial farms. Sound cows (11 = 8) had normal
(straight) back posture and no visible foot lesions. Cows selected for this study did not
show any pathological conditions other than lameness at time of sample collection. None

of the lame cows were treated for lameness before blood sample collection.

96

B. Blood collections and isolation of PBMCs and RNA

Blood samples were obtained from one pair of random lame and sound cow per
day for 8 days. All samples were collected at 9:00 am via jugular venipuncture, using 2.5-
cm 14-gauge needles (Fisher Scientiﬁc, Pittsburgh, PA). Blood (130 ml per cow)
intended for PBMC isolation was collected into 50 ml centrifuge tubes (BD Biosciences,
San Jose, CA) that contained 4 ml of acid-citrate dextrose (ACD) as an anticoagulant
(Weber et al., 2004) and immediately placed on ice. PBMCs were prepared from the
ACD anticoagulated blood using a Percoll gradient as previously described (Almeida et
al., 2007; Coussens et al., 2002). The cell pellets were suspended in 4 ml of TRIzol
reagent (Invitrogen, Carlsbad, CA) and incubated for 10 min at room temperature to
ensure lysis of PBMCs and preservation of their released RNA. This mixture was then
frozen at -80°C until use for RNA isolation, which was performed according to the

manufacture’s instructions (Almeida et al., 2007).

C. Experimental design

The experiment included 8 cDNA microarray arrays (BOTLS) containing 3888
total spots with duplicate spots of 932 bovine EST clone inserts developed from a
normalized bovine total leukocyte (BOTL) cDNA library and additional duplicate spots
of 459 amplicons representing targeted cytokine, receptor, signal transduction molecule,
transcription and growth factor, enzyme, cell cycle regulator and cellular component
genes. A list of genes represented on the BOTLS microarrays and their EST sequences

can be found at http://www.cafg.msu.edu under the ‘links’ icon.

97

Arrays were interrogated with the labeled cDNA samples in a balanced design
where each differently labeled sample was used equally often in the experimental layout
as described in Figure 4.1. More speciﬁcally, four randomly selected lame cDNA
samples were labeled with Cy3 and compared with cDNA samples from four sound cows
(paired matched by age, weight, days in lactation and pregnancy status at time of PBMC
collection) labeled with Cy5. The remaining 4 cDNA samples from lame cows were
labeled with Cy5 and compared with cDNA samples from sound cows labeled with Cy3

using the same pair matching criteria.

D. Preparation of labeled cDNA and hybridization

All conditions for cDNA synthesis, dye labeling, array hybridizations and
readings were as described previously (Coussens et al., 2002). Brieﬂy, PBMC total RNA
(12 pg) was converted to cDNA using the Atlas Powerscript labeling system (Biosciences
Inc., Alameda, CA) according to the manufacturer's instruction, with minor modiﬁcations
as described previously (Coussens et al., 2002). Reverse transcription was performed
using Oligo (dT)|5_|3 as primer. Following ﬁrst-strand cDNA synthesis, cDNAs from
each cow were split into two equal aliquots and these were differentially labeled using
NHS-derivatized Cy3 or Cy5 dyes (Amersham Pharmacia Biotech; Piscataway, NJ).
Labeled cDNAs were puriﬁed to remove unincorporated dyes, paired among cows
according to the experimental design described in Figure 4.1 to 10 p1 using Microcon 30
spin concentrators using (Millipore Corp., Bedford, MA).

Microarray hybridizations were performed as described in Madsen et al. (2004).

Brieﬂy, concentrated Cy3 and Cy5 labeled probe cDNA was added to 110 1.11 of

98

hybridization buffer (SlideHyb-3, Ambion Inc., Alameda, CA) and incubated at 70°C for
5 min immediately before hybridization. Hybridizations were conducted for 18 h in a
GeneTAC Hybridization Station (Genomics Solutions Inc., Ann Arbor, MI) using a step-
down hybridization protocol (65°C for 3 h, 55°C for 3 h, 50°C for 12 h). Following
hybridization, microarrays were washed within the hybridization station, followed by
rinsing once in 0.3 M NaCl, 0.03 M sodium citrate and once in ddeO, and then
immediately dried by centrifugation. Microarrays were scanned using a GeneTAC LS IV
microarray scanner and GeneTAC LS software version 3.3.0 (Genomic Solutions, Inc.,
Ann Arbor, MI). Digital Genome Pro software version 2 (MolecularWare Inc.,
Cambridge, MA) was used to process microarray images, ﬁnd spots, and ﬁnally to create

reports of raw total spot intensities.

E. Microarray data analysis

Total ﬂuorescence intensity values for Cy3 and Cy5 from each spot on the
microarrays were imported into SAS (SAS/STAT software, SAS Institute, Cary, NC) and
averaged across duplicate spots. Potential dye intensity biases in the microarray data sets
were visualized using M (logCy3 - logCyS) vs. A ((logCy3 — logCy5)/2) plots as
described in Madsen et a1. (2004). Array-speciﬁc data normalization was then performed
considering a locally-weighted regression and smoothing scatter plots (LOESS)
procedure of SAS (SAS Institute, SAS/STAT Software version 9.1) to account for dye
biases (Yang et al., 2002). The efﬁciency of LOESS normalization was assessed by
monitoring M-A plots for data from each array before and after LOESS normalization. A

two-step mixed model (Wolfmger et al., 2001) was used to analyze the LOESS-adjusted

99

log intensities. The ﬁrst step involved array speciﬁc normalization and the second step
involved gene-speciﬁc analyses to test for the effects of group (lame versus sound cows).
The normalization model included the ﬁxed effect of dye, as well as the random effects
of array, patch x array, dye x array and dye x patch within array effects. The residuals
from the ﬁrst step were scale-normalized for differences in within array variability. The
second step of the mixed model analysis consisted of gene-speciﬁc models for the
aforementioned residuals. The gene-speciﬁc model included the ﬁxed effects of dye and
group as well as random effects of array, spot within array and cow within group. The
analysis was performed with the MIXED procedure of SAS (Littell et al., 1996). In the
gene-speciﬁc analysis, lameness effect was declared signiﬁcant when P S 0.05 and

tendency towards signiﬁcance when 0.06 S P S 0.10.

F. Validation of differential gene expression using quantitative real-time RT-PCR
The spotted cDNA sequences representing genes whose expression proﬁles were
and tended to be signiﬁcantly inﬂuenced by lameness in this analysis were matched to the
nearest human and mouse homologs in TIGR by BLAST searching, facilitated by the
Michigan State University Center for Animal Functional Genomics web site at
http://wwwcafg/msuedu. Biological functions of these genes were determined through
an extensive PubMed literature search (http://www.ncbi.nlm.nih.gov/entrez/gueggfcgi).
This information was used to determine which genes to select for validation of
differential expression due to lameness. Laboratory-based validation of differential gene

expression of 15 genes was performed on genes with documented importance to immune

100

response, inﬂammation and pain, and P-value of effect of lameness S 0.05 in the
microarray data analysis (Table 4.1).

Recent evidence indicates that quantitative information from arrays may be
imprecise for transcripts showing small differences in expression, and therefore, overlook
genes of signiﬁcant interest (Chuaqui et al., 2002). Recent evidence suggests that anti-
inﬂammatory cytokines (i.e., IL-10 and IL-4) modulate widespread pain in humans
(Ugeyler, 2006). For this reason, we decided to pursue with investigation of the
expression of IL-10 and IL-4 even though microarray analysis showed no statistical
indication that these genes were affected by lameness (P > 0.10).

Real-time RT-PCR on an Applied Biosystems 7000 DNA sequence detection
system (Perkin Elmer Corp., Foster City, CA) was used for validation. Individual RNAs
from Percoll puriﬁed PBMCs of the same cows used in the microarray experiment, were
converted into ﬁrst-strand cDNA as described in Madsen et al. (2004). Brieﬂy, 2 pg of
the RNA was combined with 10 mM oligo(dT)12_.s primer and sterile water in a 10 111
volume that was incubated 5 min at 70°C followed by 5 min at 20°C. Master mix
containing 4 1.11 of buffer (supplied by the RT manufacturer; ﬁnal reagent concentrations
of 50 mM Tris.HCl, pH 8.3, 75 mM KCl, and 3 mM MgClz), 200 U of SuperScript II
RNase H' reverse transcriptase (Invitrogen Life Technologies), and a ﬁnal concentration
of 10 mM DTT and 0.5 mM dNTP were added to achieve a ﬁnal reaction volume of 20
111. Reverse transcription was allowed to proceed at 42°C for 60 min, heated to 70°C for
15 min, and cooled to 37°C prior to the addition of 2 U of DNase-free RNase H
(Invitrogen Life Technologies). Incubation at 37°C was continued for 20 min in the

presence of RNase H to remove the original RNA template followed by enzyme

101

inactivation via addition of 0.5 pl of 0.5 M EDTA (pH 8.0). First-strand cDNAs were
puriﬁed with QuickClean resin (Clontech) followed by precipitation with sodium acetate
and ethanol. Puriﬁed cDNAs were suspended in DNase/RNase-free sterile water,
quantiﬁed spectrophotometrically (NanoDrop Technologies, Wilmington, DE), diluted to
a ﬁnal concentration of 10 ng/pl, and stored at -20°C until use. Real-time RT-PCR was
performed for 15 genes using the SYBR Green PCR Master Mix (PerkinElmer Applied
Biosystems). Gene-speciﬁc primer pairs (Table 4.2) were designed using Primer Express
Software (PerkinElmer Applied Biosystems) and synthesized at a commercial facility
(Qiagen-Operon, Alameda, CA). Primers for B-actin were also made, and this gene was
included in all real-time RT-PCR analyses for the purpose of data normalization (as in
Madsen et al., 2002). The cDNA and primer concentrations used in the real-time RT-PCR
assays for determination of each gene expression were optimized prior to the experiment
(Table 4.2). Results were recorded as relative gene expression changes after normalizing
for B-actin gene expression, computed using the 2'AAC‘ method of Livak and Schmittgen
(2001). This method monitors relative gene expression changes across treatments
(lameness groups — lame versus sound) based on differences in the PCR ampliﬁed target
reaching a ﬁxed threshold cycle (Ct) number for one treatment (lame) vs. a control
treatment (sound). For our 2'AAC’ analysis, the Ct for sound cows was the calibrator used
to determine relative gene expression changes of lame cows for each B-actin-normalized
test gene. Statistical analysis of these data was performed using the MIXED of SAS
(SAS/STAT Software, SAS Institute) with a model that included lameness group as the

ﬁxed effect and cattle age (in days), weight (in kg), day in lactation (in days), and

102

pregnancy status (yes, no) as covariates when found to signiﬁcantly affect gene

expression at P < 0.05.

IV. RESULTS
A. Microarray experiment

Statistical analysis of resulting total spot ﬂuorescence intensity revealed 31 genes
that were putatively differentially expressed (P S 0.05) in lame versus sound cows (Table
4.1). Of these, BLASTn analysis and gene ontology information disclosed 28 genes with
high similarity and/or homology to known human and/or rodent genes (Table 4.1). The
false discovery rate (FDR) for the putatively differentially expressed genes was

approximately 78 %.

B. Validation of differential expression

Real-time RT-PCR assessment of 13 of the 31 genes that were putatively altered
by lameness (P S 0.05) in the microarray experiment conﬁrmed the up regulation of 3 of
these genes in lame compared to sound cows (Figure 4.2). These genes were: (1) IL-2:
12.68 1 1.47 fold increase (P = 0.03); (ii) MMP-13: 10.44 1 1.14 fold increase (P =
0.01); and (iii) CCR5: 5.26 1 1.05 fold increase (P = 0.03). Furthermore, GM-CSF-R-
alpha demonstrated a tendency (P = 0.08) for up regulation (2.30 1 0.63 fold increase) in
lame relative to sound cows (Figure 4.3).

Although microarray data suggested no effects of lameness on either IL-10 (P =
0.24) or IL-4 (P = 0.28), the expression of these two genes was investigated using real-

time RT-PCR 2M0 analysis due to their recently reported role in mediating widespread

103

pain in humans (Uceyler et al., 2004). Results revealed a signiﬁcant up regulation (P =
0.03) of IL-10 (2.39 1 0.55 fold increase) and a tendency for up regulation (P = 0.10) of

IL-4 (2.06 1 0.59 fold increase) in lame relative to sound cows (Figure 4.3).

V. DISCUSSION

The results of this study present PBMC up regulation of IL-2, MMP-13, CCR5,
IL-10, IL-4 and GM-CSF-R-alpha as potential candidates to assist the diagnosis of
inﬂammatory foot lesions in lame dairy cows. The small number of validated genes (3
out of 13) in this study supports the high false discovery rate (FDR) of 78 % found for the
genes putatively differentially expressed (P < 0.05) in the microarray experiment. FDR is
deﬁned as the expected proportion of rejected null hypotheses that are false positives
(Benjamini and Hochberg, 1995). Issues such as sampling cows with different lameness
etiologies, severities and chronicities, the lack of control for the number and speciﬁc type
of cells collected from each animal, and the small number of biological replicates, likely
contributed to the high FDR and low statistical power and precision in this experiment
(Churchill, 2002; Cui and Churchill, 2003). Despite these pitfalls, the microarray-based
gene expression approach was effective in pointing to a small group of interesting
candidate biomarkers that would not have been explored otherwise.

Overall, the PBMC gene expression pattern observed in this study indicates that
lame cows have systemic changes consistent with immune system activation. For
example, IL-2 is a growth factor for antigen-stimulated T lymphocytes that is responsible
for T cell clonal expansion after antigen. recognition. IL-2 is involved in several

immunological events including the increase in monocyte-mediated natural cytotoxicity

104

against certain tumor cells in vitro and in vivo (Malkovsky et al., 1987), stimulation of
IFN-y production, and enhancement of B lymphocyte responses (Mosmann and Coffrnan,
1989; Abbas et al., 1996; Opal and DePalo, 2000). IL—2 also induces other cytokines that
exert their effects largely through the cyclooxygenase pathway. Moreover, it has a unique
role in activation-induced cell death and in the maintenance of peripheral regulatory T
(Treg) cells, which makes it important in pathogenesis of autoimmune diseases (Fontenot
et al., 2005; D’Cruz and Klein, 2005; Maloy and Powrie, 2005). The up regulation of IL-
2 noted in the lame cows agrees with previous research dealing with other types of
inﬂammatory and infectious conditions such as in vasculitis and meningitis (Zucker et al.,
2006), and in tuberculosis (Guntupova et al., 2006; Turgut et al., 2006). Signals triggered
by IL-2 initiate integrated host responses to infection and injury (Michie et al., 1988), and
therefore, the up-regulation of this gene in lame cows indicates that in addition to the
inﬂammatory lesions in the foot, lame cows have systemic changes that are amenable of
objective measurement.

The disease ﬁghting scenario painted by the PBMC gene expression proﬁles
observed was re-enforced by the up regulation of MMP-13 and GM-CSF—R-alpha in lame
cows. Matrix metalloproteinases (MMPs) were discovered in connection with their
capacity to degrade extracellular matrix (ECM) proteins such as collagen and elastin.
MMP-13 is the third member of the collagenase subfamily of MMPs and modulates ECM
metabolism directly by degrading matrix molecules, as well as indirectly by activating
other MMPs (e.g., MMP-2, MMP-9) (Leeman et al., 2002). It is expressed in
chondrocytes, osteoblasts and periosteal cells, but also in PBMCs of humans with

rheumatoid arthritis (Vazquez-Del Mercado et al., 1999). MMP-13 release is modulated

105

by proinﬂammatory cytokines and growth factors (Neidel et al., 1995) and it plays a
major role in joint destruction (Firestein, 1996, Nagase and Woessner, 1999). Therefore,
MMP-13 is of special interest for the pathogenesis of arthritic conditions such as
rheumatoid arthritis (RA) and osteoarthritis (0A) in which its concentration is found to
be up-regulated in both serum and synovial ﬂuid (Itoh et al., 2002; Andereya et al.,
2006). GM-CSF-R-alpha, a low afﬁnity receptor for granulocyte-macrophage colony-
stimulating factor (GM-CSF), transduces a signal that results in the proliferation,
differentiation, and functional activation of hematopoietic cells. GM-CSF stimulates stem
cells to produce granulocytes (neutrophils, eosinophils, and basophils) and macrophages.
GM-CSF-R-alpha and its ligand are thus part of the immune/inﬂammatory cascade.
Similar to IL-2, the up regulation of MMP-13 and GM-CSF—R-alpha in PBMCs of lame
cows highlights the pro-inﬂammatory state of these animals and suggests the immune
system as an important source of candidate biomarkers of inﬂammatory lameness in dairy
cows.

Chemokine receptors (called CCRl though CCRl 1) are expressed in leukocytes,
with the greatest number of distinct chemokine receptors observed on T cells (Weber et
al., 2000; Mueller and Strange, 2004). The increased chemokine receptor-5 (CCR5)
expression in lame cows was an interesting ﬁnding of this study because previous in vivo
studies conﬁrm a direct role of chemokines in nociception. For example, when injected
intradermally into a rat’s paw, CCL5 (ligand for CCRI, CCR3 and CCR5) induces pain
(Abbadie, 2005). In addition, chemokines are important for the extravasation of
leukocytes from blood to the injury site, an essential step for the inﬂammatory process

and subsequent wound healing (Johnson et al., 2005; Khan et al., 2006). CCR5 is one of

106

the major inﬂammatory chemokine receptors in immune cells and has been the focus of
several studies because of its function as a co-receptor for entry of HIV into host cells
(Murphy, 2001). Moreover, CCR5 is an important regulator of the analgesic activity of
opioids in the brain (Szabo et al., 2002). CCR5 ligands apparently can exacerbate pain
experience by inactivating normal neuronal signaling pathways involved in reducing the
pain sensation (Scholtz and Woolf, 2002; Marcth et al., 2005). The up-regulation of
molecules involved in pain modulation, such as CCR5, suggests the importance of pain
within the lameness scenario (as in Rushen et al., 2006).

In addition to the importance of inﬂammation as means of immune defense and
healing, strong inhibitory mechanisms to the inﬂammatory process are needed to avoid
uncontrolled inﬂammation and consequent severe tissue damage. Endogenously, the
“stop signals” for inﬂammation are mediated by several factors including lipoxins (block
neutrophils inﬂux to injury site) (Levy et al., 2001), cyclooxygenases, and anti-
inﬂammatory cytokines produced by TH2 class T cells, such as IL-10 and H.-4. IL-10
inhibits activated macrophages and dendritic cells and thus is involved in the control of
innate immune inﬂammatory reactions and cell-mediated immunity (Abbas and
Lichtman, 2003). IL-4 on the other hand, mediates adaptive humoral immunity. It is the
signature cytokine of the TH2 subset and functions as both the inducer and an effector of
these cells (Okada et al., 2003), and the major stimulus for the production of Igl and IgE
antibodies by B cells, and for the development of TH2 cells from na'r've CD4+ T cells. IL-4
also antagonizes the macrophage-activating effects of IFN-y and thus inhibits cell-
mediated immune reactions (Abbas and Lichtman, 2003). Contrary to what was

demonstrated in models of chronic widespread pain (Uceyler et a1, 2006), lame cows

107

demonstrated an increase in expression of both IL-10 and IL-4. These results suggest that
lame cows have an active acquired anti-inﬂammatory response that is toning down
inﬂammatory THI type activity, perhaps in an attempt to limit further tissue damage and
pain.

This study utilized a microarray-based gene expression approach to discover
candidate biomarkers for inﬂammatory foot lesions in lame dairy cattle. Our results
support the premise that PBMCs serve as a surrogate tissue for evaluation of disease-
induced gene expression in cows suffering from inﬂammatory lameness. Considering the
subjective and unreliable nature of lameness screening methods currently used in dairy
herds, our ﬁndings foster the possibility of using objective measures to assist with
lameness detection. However, before any genomic biomarkers are incorporated into
clinical practice, several issues need to be addressed in order to generate the necessary
levels of evidence to demonstrate analytical and clinical validity, and utility (Chuaqui et
al., 2002). For example, in addition to validating array results at the mRNA level, it is
equally important to evaluate expression levels of the corresponding protein products.
Moreover, the universality of results (if the gene expression signatures are an essential
feature of lameness) needs to be investigated. This can be addressed by evaluating a
critical gene set in a larger and more extensive study group with different lameness types
and severities. In addition to boosting diagnostic reliability, the prospect of developing
such biomarkers of foot inﬂammation related-lameness could help identify animals in
need of pain relief and provide appropriate molecular targets for the development and

monitoring of novel lameness therapies.

108

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110

Table 4.2 Sequence of primers used for real-time RT-PCR measurement of gene
expression and concentration of template PBMC cDNA used in the reactions. F =
forward, R = reverse.

 

 

Gene name Sequence (5’ to 3’) [Primer] [CDNA]

(11M) ('18)
RDCl-F ACCTACI‘ GCCGGGC'I'IT CT AC
RDC 1 -R GACCAGCTCCATGCTGATGA 600 10
ILZ-F GGAGAAAG'ITAAAAATCCI‘GAGAACCT
IL2-R AACC'I'I‘GGGCGCGTAAAAG 300 10
TGFRII—F GCTTCGCCGAGGTCTACAAG
TGFRII-R GGCCACGGTCT CGAACT G 600 10
CCR5-F GAGGCTCATCI'PCGTGATCATG
CCR5-R GGAAGGTGCTCAGGAGAAGGA 300 40
WP] 3-F 'I'ITITCCCCC'I’ITAATCC’I'I‘CAT
MMP] 3-R ACACAATGGTI‘C’I'I‘CCC'ITCAAG 600 30
CD34-F TGGCTGAGCCI‘GGAACCA
CD34-R CCAGATCCI‘CCAAACACACAGA 600 30
Jak I -F GACT CT GCATGAGCT GCIT ACI'I' ACT
Jak l -R TGGGCCI‘ATCATI'ITCAGGAA 300 10
MAPK-F GCACTGGA'ITI‘CCTGGAACAA
MAPK-R AGCGC'IT CIT CT GCI‘ GT CAAC 300 30
Tcergl-F CACCI‘GTGCAAACCGTICCT 300 10
Tcergl-R AGGCAC'I‘GAATGCGGAACA
GM-CSF—Ralpha-F CGGCT GCCCAAAACI‘PCT C 300 10
GM-CSF-Ralpha-R GGCCCAGCTGCAG'I'I‘CAT
IFNR2-F CC'I‘I‘CTG'I'I‘CC'I'I‘CGCACAAG
IFNRZ-R GCTCCCI‘GCTG’I'ITGATGCT 600 10
KSrasl-F GCCCCTGCCTGTAGAATATCCT
KSrasl-R CGAGGGCACGGA'ITCI‘ GT 300 10
VDAC3-F ACCAGAAGGTGAATGAGAAGA'ITGA
VDAC3-R CCGAAGCGGGTG'ITGTI‘ACT 300 10
IL-lO-F CCTTGTCGGAAATGATCCAG’I'ITI‘
IL-lO-R TCAGGCCCGTGGTI‘C'PCA 300 10
IL—4-F GCCACACGTGCI‘TGAACAAA

300 10

IL-4-R TGC'ITGCCAAGCTG'ITGAGA

 

lll

Lame 1 Cy3
Lame 2 Cy5
Lame 3 Cy3
Lame 4 Cy5
Lame 5 Cy3
Lame 6 Cy5
Lame 7 Cy3

Lame 8 Cy5

Figure 4.1 Microarray experimental design.

 

 

 

 

 

 

 

 

112

Sound 1 Cy5
Sound 2 Cy3
Sound 3 Cy5
Sound 4 Cy3
Sound 5 Cy5
Sound 6 Cy3
Sound 7 Cy5

Sound 8 Cy3

Figure 4.2 Real-time RT-PCR of lameness effects on PBMC expression of IL-2, CCR5
and MMP-13. The bars represent means of expression ratios between lame (n = 8) and
sound (11 = 8) cows derived using the 2M0 method of Livak and Schmittgen (2001), with
B-actin as the control gene and sound cows as the calibrator. The asterisks (*) represent
mean differences between lame and sound cows (P S 0.05).

16 —
14 ~1
12

10*
81
6'“
41
21
0.

MMP-131L-2

Relative gene expression

 

 

 

113

Figure 4.3 Real time RT-PCR of lameness effects on PBMC expression of the anti-
inﬂammatory cytokines IL-10, IL-4, and pro-inﬂammatory GM-CSF-R-alpha. The bars
represent means of expression ratios between lame (n = 8) and sound (n = 8) derived
using the 2M0 method of Livak and Schmittgen (2001), with B-actin as the control gene
and sound cows as the calibrator. The asterisk (*) represents mean differences (P S 0.05)
and the crosses (T) represent a tendency for means differences (0.05 _<_ P S O. 10) between
lame and sound cows.

3.5
3 e:

   

g—s
kl]

Relative gene expression

 

 

 

 

 

 

I '_—“I

IL-10 IL-4 GM-CSF-R-alpha

114

CHAPTER FIVE

General Discussion

Lameness is a signiﬁcant economic factor for the dairy industry (Blowey, 1993),
and an indicator of pain and compromised animal welfare (Whay et al., 1998; 2003).
Several scoring systems that consider posture and gait have been proposed to allow
categorization of lameness by severity. However, these methods are observer dependent
(Whay et al., 2002) and thus lack reliability. The experiments described in Chapter Two
through Chapter Four of this dissertation highlight several novel ﬁndings regarding the
use of objective markers of locomotion abnormalities, and immune and neuroendocrine
activation for detection of inﬂammatory foot lesions that cause pain and lameness in
dairy cows.

The ﬁrst prominent ﬁnding of these studies was that a pressure plate was sensitive
in detecting the presence of papillomatous digital dermatitis (hairy heel wart) type
lameness in heifers otherwise diagnosed as sound using the subjective lameness scoring
system of Sprecher et a1. (1997). Asymmetry in peak vertical ground reaction force
(PVF) between the hindlimbs of heifers was shown to be a prominent marker for the
diagnosis of hairy heel wart type lameness lesions. These results support previous
ﬁndings in cows (Rajkondawar et al., 2002a; Scott 1989) and horses (e.g. Merkens and
Schamhardt, 1988) and, importantly, highlight the potential of PVF for objective and
early detection of lameness when compared to conventional subjective lameness scoring
systems. If lameness is detected accurately and early, lameness prognosis and the overall

welfare of the cows may be enhanced (Logue et al., 1998). However, to be considered an

115

auxiliary diagnostic tool, ground reaction force data collection must be practical, reliable,
suit operating procedures in dairy farm settings, and interpreted easily. Furthermore, the
magnitude of locomotor variability of dairy cattle at walk is unknown and needs to be
explored. Locomotion variability dictates the number of trials necessary to have a
representative proﬁle of the animal’s motion. Variability in locomotion can be minimized
by using an average of multiple trials as a representative of the gait pattern, reducing
inter-trial walking velocity variation, and (or) collecting data from both right and left
limbs simultaneously. If multiple trials are indeed required to account for the locomotion
variability at walk, then the feasibility of using PVF as an objective marker for lameness
assessment ‘at walk’ at the farm level likely will be hindered. Therefore, measuring
ground reaction forces with the cow standing (e. g., at the milking parlor or robot milking
system) instead of walking might represent an alternative solution to this issue, as
recently demonstrated by Pastel] et a]. (2006).

Although gait changes (e.g., PVF) are useful indicators of hoof discomfort
associated with inﬂammatory and painful lesions (Neveux et al., 2006), these changes
also might indicate conditions that are not animal welfare concerns. For example, factors
such as physical constraints [e.g., distended udder; (Flower et al., 2006), conformational
abnormalities, and rough ﬂooring surfaces (Rushen and de Passille, 2006; Phillips and
Morris, 2001)] are known to alter locomotion in otherwise sound cows. Therefore, gait
changes alone will likely not provide accurate detection of lameness caused by painful
inﬂammatory foot lesions. Accordingly, ﬁndings from the second and third studies of this

dissertation present alternatives to the one-dimensionality of current lameness

116

assessments by providing new evidence that physiological markers (biomarkers)
amenable of objective measurement may be useful in lameness diagnosis.

This alternative dimension of measures encompasses the changes within the
immune and neuroendocrine systems in response to tissue injury and infection. For
example, cows with behavioral alterations indicative of lameness from painful
inﬂammatory foot lesions had lower serum DHEA concentrations and higher
cortisol:DHEA ratios. These hormonal changes are characteristic of pituitary-dependent
adrenal response stimulation, and, along with the sickness behaviors, they provide
evidence to support the hypothesis that a sensitization of the central nervous system
occurred in the subjects suffering from inﬂammatory painful foot lesions. To the author’s
knowledge, such observations have not been documented before in dairy cows. These
ﬁndings characterize a potential dysregulation of the HPA axis and cortisol:DHEA which
can cause immunological changes that predispose to pathologies by altering THIITHZ
balance. DHEA favors a THI immune response by increasing T cell production of IL-2
(Daynes et al., 1990; Suzuki et al., 1991), and decreases synthesis of proinﬂammatory
cytokines by tissue macrophages and dendritic cells, such as IL-6 and TNF-a (Di Santo et
al., 1996; Straub et al., 1998). On the other hand, cortisol favors a TH2 response by
suppressing macrophage production of IL-12 (Elenkov et al., 1996; Blotta et al., 1997).
Thus, the steroid imbalance observed in the lame cows of the current study may be linked
to a physiological coping strategy involving THIITHZ imbalance, such that T32 dependent
humoral immune activity was favored over THl dependent inﬂammatory activity. In light
of the importance of discovering diagnostic biomarkers of lameness, this hypothesis is

worthy of further testing.

117

The immune system is considered one of the most important indicators of
organismal status because it is responsible not only for protecting the organism against
pathogens but also for modulating different types of pain experiences (e.g., acute,
neuropathic) (Moalem and Tracey, 2006) and sickness responses (Hart, 1988). In Chapter
Four of this dissertation, activation of the immune system was characterized as an
increased abundance of speciﬁc expressed genes in circulating PBMC in lame compared
to sound cows. These data provide evidence that lame cows were systemically engaged in
ﬁghting infection and controlling inﬂammation. Speciﬁcally, PBMC co-regulation of IL-
2, MMP-13, CCR5, IL-10, IL-4 and GM-CSF—R-alpha were presented as candidates’
biomarkers for screening lame dairy cows with inﬂammatory foot lesions. Although not
characterized in this study, the release of proinﬂammatory cytokines from damaged tissue
and activated immune cells is assumed to be the main trigger for the sickness behaviors
and immunological changes demonstrated by lame cows with painful inﬂammatory
painful foot lesions (Buckingham, 1994). Thus, these up regulated PBMC genes may
have contributed to the sickness behaviors and endocrine changes in lame cows that were
documented in Chapter Three of this dissertation.

During injury and infection, activation of T cells by antigens and co-stimulators
induces transcription of the IL-2 gene (13 fold increase in lame compared to sound cows)
and synthesis and secretion of the IL-2 protein, which initiates integrated host responses
to infection and injury (Michie et al., 1988). The secretion of IL-2 leads to T-cell
proliferation and other activities that are crucial for regulation of the immune response,
including immune cell survival (activation of Bcl-2), stimulation of adjacent T cells,

proliferation and differentiation of B cells and NK cells, and increase in production of

118

other cytokines such as IFN-y by THI cells and IL-4 by TH2 cells. Therefore, the up
regulation of IL—2 observed in lame cows suggests that these animals are actively
responding to microbial infection at the site of tissue injury.

Similarly, the approximate 2-fold up regulation of IL-4 observed in lame cows
supports the hypothesis that the animals are trying to cope with inﬂammation by
expressing a cytokine that suppresses inﬂammatory responses via inhibition of IFN-y
macrophage-dependent reactions. If true, there would be an imbalance in the TH1/TH2
ratio in lame cows such that TH2 cell responses and subsequent antibody production
would be favored. One way to test this would be to measure serum concentration of
antibodies that are induced by TH2 type cells cytokines, such as IgE and IgG1.

Likewise, IL-IO (up regulated 2.4 fold in lame cows) also participates in the down
regulation of inﬂammatory immune responses by hampering activation of macrophages
and dendritic cells and thus inhibiting THI responses. The mechanism by which this
occurs is similar to that of IL-4. That is, IL-10 is an inhibitor of IFN-y and also of IL-12,
which provide the main stimuli for THl cell differentiation and effector functions. IL-10
is produced by activated macrophages (Abbas and Litchman, 2003). Because most
macrophages are settled within tissues and not in the circulating PBMC population, the
increased abundance of IL-10 gene observed in PBMC of the lame cows of this study
might have derived from T lymphocytes, which also can produce IL-lO (Abbas and
Litchman, 2003). Overall, the up regulation of IL-4 and IL-10 in PBMC of lame cows
may indicate an attempt by the animal’s immune system to squelch ongoing

inﬂammation in the affected foot (Figure 5.1). Irnportantly, this physiological change

119

was readily detectable and quantiﬁable in blood PBMC and thus may be amenable to
objective measurement as a potential biomarker of lameness.

However, contrary to the putative anti-inﬂammatory defense scenario suggested
by the PBMC IL-4 and IL-10 changes in lame cows, the increased expression of MMP-
13, CCR5 and GM-CSF—R-alpha indicated that an active inﬂammatory and algesic state
was also present. For example, MMP-13 plays a major role in joint destruction (Firestein,
1996, Nagase and Woessner, 1999) and its release is modulated by proinﬂammatory
cytokines and growth factors (Neidel et al., 1995). Thus MMP-13 is actively involved in
the pathogenesis of arthritic conditions such as rheumatoid arthritis and osteoarthritis
(Itoh et al., 2002; Andereya et al., 2006). Similarly, the observed up regulation of GM-
CSF—R-alpha and chemokine receptor CCR5 in PBMCs of lame cows of this study
suggests the presence of an active immune response. GM-CSF is important for the
production of granulocytes and macrophages, and chemokines are essential to attract and
direct circulating leukocytes into peripheral sites of inﬂammation and infection (Foxman
et al., 1997). Furthermore, CCR5 also is involved in exacerbating pain experience
because its ligands (e.g., RANTES, macrophage inﬂammatory protein [MIP]-a, and MIP-
B) inactivate normal neuronal signaling pathways involved in reducing pain sensation
(Scholtz and Woolf, 2002; Marchand et al., 2005) (Figure 5.1). Pain is a major element
of inﬂammatory type lameness (Whay et al., 1998) and is one of the reasons why cows
alter their locomotion (Rushen et al., 2006). Overall, the results of the studies described
in this dissertation begin to portray a picture of key physiological changes that occur in
the immune and neuroendocrine systems as lame animals try to cope with their condition.

These physiological indicators, together, may provide a signature that could be used for

120

diagnosis of painful inﬂammatory foot lesions and thus should be conﬁrmed in future
ﬁeld studies.
Figure 5.1 Tentative model to summarize the changes observed in the lame cows of the

studies of this dissertation. Genes in orange and blue boxes are involved in pro- and anti-
inﬂammatory activities, respectively.

 

 

 

 

 

Systemic
. . physiological
Biomechanical changes
changes

 

 

 

Lame cow with painful
inﬂammatory foot lesion
and sickness behavior

   

 

 

  
  

Activation of
The HPA axis

 

 

 

 

 

Lower peak vertical
force than healthy sound
cows

we?

. CortisolzDHEA
PBMC up regulation ofthe _ imbalance
expression of important
gene

 

 

 

   

 

 

 

 

 

 

 

 

121

It is clear that lameness is a complex disease with multiple etiologies. As such, its
study using genome level technologies is appropriate. However, such studies must be
designed very carefully, especially in terms of statistical power. For example, the high
false discovery rate observed in the presented microarray study suggests that there were
several drawbacks in the study design. This might have included too few animals studied,
poor choice of cells for study, lack of purifying one cell type from another prior to
microarray analysis, lack of control for lameness types, or chronicities, and so on.
Statistical power and precision of the microarray experiment described in Chapter Four,
and potentially the candidate gene approach described in Chapter Three, could have been
better if a speciﬁc cell type within the PBMC population (e.g., monocytes), or if a cell
type with a greater presence in blood with known sensitivity to changes in the serum
cortisol:DHEA ratio (e. g. neutrophils) were used instead. Furthermore, an alternative
tissue sample, such as from the lesion area could also have enhanced the experimental
outcome. However, although pitfalls in the experimental design must be considered, the
feasibility of actually isolating a pure cell population under the conditions in which the
study was performed (at the farm level) would not have been possible due to lack of
appropriate laboratorial instrumentation at the farm site. Furthermore, the practicability of
harvesting a tissue sample from the lesion area (foot) would likely need to involve
considerable restraining of the cow, similar to what is performed during trimming, and a
thoroughly cleansing of the foot area prior to tissue collection. Once again, the feasibility
of this procedure would have been constrained by issues with practicality and the stress
associated with restraining of the animal, which might compromise the validity of results.

The current need for ‘practical’ and ‘clinically applicable at the farm level’ biomarkers

122

for inﬂammatory lameness lesions detection supports the choice of blood samples and
PBMCs as a surrogate tissue for evaluation of disease-induced gene expression in cows
suffering from inﬂammatory lameness. Overall, systemic physiological changes detected
in blood provide a novel spectrum to be explored in future lameness studies and foster the
possibility of having objective measures available for diagnosis of important diseases that
debilitate the welfare of animals, such as lameness detection.

However, the preliminary nature of the ﬁndings described in this dissertation
needs to be acknowledged. The translation of biomarkers to clinical practice will depend
on several factors, including the accuracy of testing methodologies, strength of
correlation with clinical phenotype or outcome, and utility of information. They may be
discovered at the bench, but getting them to the clinic is another story altogether. That is,
ﬁnding a useful biomarker is necessary, but hardly sufﬁcient, for getting it validated and
eventually approved by regulators for clinical practice (Chuaqui et al., 2002). This can be
addressed by evaluating the candidate biomarker genes in alternative and more extensive
group of cows, by exploring different lameness types and severities, and by including
different diseases in the study design. Moreover, in addition to validating array results at
the mRNA level, connecting function of the genes to the actual disease pathogenesis
would require an evaluation of expression levels of the corresponding protein products.

As a ﬁnal comment, the multifactorial nature of lameness, and inappropriate level
of understanding on the pathophysiology and etiology of different lameness types impairs
the progress with objective biomarkers discovery for this condition and consequently,
slows down the development of effective therapies and prevention strategies for

lameness. In addition to boosting diagnostic reliability, the prospect of developing

123

reliable biomarkers of painful inflammatory lameness-related foot lesions could help
identify animals in need of pain relief and provide appropriate targets for the

development and monitoring of novel lameness therapies.

124

APPENDIX ONE

125

Table A.l Real-time RT-PCR on PBMC expression of genes with no lameness effect
from Chapter Four. Fold change represents means of expression ratios between lame (n
= 8) and sound (11 = 8) derived using the 2MCI method of Livak and Schmittgen (2001),
with B-actin as the control gene and sound cows as a calibrator. The P-values represent
the main effect of lameness.

 

Gene Fold change P-value
RDCl 1.73 :1: 0.49 0.13
CD34 1.62 :1: 0.43 0.13
MAPK 1.47 :1: 0.36 0.15
IFNR2 2.27 :l: 0.88 0.19
TGFR2 0.71 i 0.39 0.22
VDAC3 1.63 :1: 0.70 0.33
JAKl 1.17 :1: 0.28 0.42
Tcerg 1.44 :l: 0.71 0.47
KSrasl 1.44 :1: 0.35 0.54

 

126

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