Group Title: Arthritis Research & Therapy
Title: Differential gene expression in the salivary gland during development and onset of xerostomia in Sjögren's syndrome-like disease of the C57BL/6.NOD-Aec1Aec2 mouse
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Title: Differential gene expression in the salivary gland during development and onset of xerostomia in Sjögren's syndrome-like disease of the C57BL/6.NOD-Aec1Aec2 mouse
Series Title: Arthritis Research and Therapy
Physical Description: Book
Language: English
Creator: Nguyen, Cuong
Sharma, Ashok
Lee, Byung Ha
She, Jin-Xiong
McIndoe, Richard
Peck, Ammon
Publisher: Arthritis Research and Therapy
Publication Date: 2009
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Abstract: INTRODUCTION:Recently, we reported the development of the C57BL/6.NOD-Aec1Aec2 mouse that carries two genetic intervals derived from the non-obese diabetic (NOD) mouse capable of conferring Sjögren's syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. In an attempt to define the molecular bases underlying the onset of stomatitis sicca (xerostomia) in this C57BL/6.NOD-Aec1Aec2 mouse model, we have carried out a study using genomic microarray technology.METHODS:By means of oligonucleotide microarrays, gene expression profiles of salivary glands at 4, 8, 12, 16, and 20 weeks of age were generated for C57BL/6.NOD-Aec1Aec2 male mice. Using Linear Models for Microarray Analysis and B-statistics software, 480 genes were identified as being differentially expressed (P < 0.01 and Q < 0.0001) during the development of SjS-like disease in the salivary glands.RESULTS:The 480 genes could be arranged into four clusters, with each cluster defining a unique pattern of temporal expression, while the individual genes within each cluster could be grouped according to related biological functions. By means of pair-wise analysis, temporal changes in transcript expressions provided profiles indicating that many additional genes are differentially expressed at specific time points during the development of disease. Multiple genes reportedly showing an association with autoimmunity and/or SjS, in either humans or mouse models, were found to exhibit differential expressions, both quantitatively and temporally. Selecting various families of genes associated with specific functions (for example, antibody production, complement, and chemokines), we noted that only a limited number of family members showed differential expressions and these correlated with specific phases of disease.CONCLUSIONS:Taking advantage of known functions of these genes, investigators can construct interactive gene pathways, leading to modeling of possible underlying events inducing salivary gland dysfunction. Thus, these different approaches to analyzing microarray data permit the identification of multiple sets of genes of interest whose expressions and expression profiles may correlate with molecular mechanisms, signaling pathways, and/or immunological processes involved in the development and onset of SjS.
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Research article


Differential gene expression in the salivary gland during

development and onset of xerostomia in Sj6gren's syndrome-like

disease of the C57BL/6.NOD-AeclAec2 mouse
Cuong Q Nguyen1, Ashok Sharma2, Byung Ha Lee1, Jin-Xiong She2, Richard A Mclndoe2 and
Ammon B Peck1,3,4


1Department of Oral Biology, College of Dentistry, 1600 SW Archer Rd., University of Florida, Gainesville, FL 32610, USA
2Center for Biotechnology & Genomic Medicine, CBGM 1120 15th Street CA41 26, Medical College of Georgia, Augusta, GA 30912, USA
3Department of Pathology, Immunology & Laboratory Medicine, College of Medicine, 1600 SW Archer Rd., University of Florida, Gainesville, FL
32610, USA
4Center for Orphan Autoimmune Diseases, College of Dentistry, 1600 SW Archer Rd., University of Florida, Gainesville, FL 32610, USA

Corresponding author: Ammon B Peck, peck@pathology.ufl.edu

Received: 9 Dec 2008 Revisions requested: 17 Feb 2009 Revisions received: 13 Mar 2009 Accepted: 20 Apr 2009 Published: 20 Apr 2009

Arthritis Research & Therapy 2009, 11 :R56 (doi:1 0.11 86/ar2676)
This article is online at: http://arthritis-research.com/content/11/2/R56
C 2009 Nguyen et al.; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abstract


Introduction Recently, we reported the development of the
C57BL/6.NOD-Aec1Aec2 mouse that carries two genetic
intervals derived from the non-obese diabetic (NOD) mouse
capable of conferring Sj6gren's syndrome (SjS)-like disease in
SjS-non-susceptible C57BL/6 mice. In an attempt to define the
molecular bases underlying the onset of stomatitis sicca
(xerostomia) in this C57BL/6.NOD-Aec1Aec2 mouse model,
we have carried out a study using genomic microarray
technology.

Methods By means of oligonucleotide microarrays, gene
expression profiles of salivary glands at 4, 8, 12, 16, and 20
weeks of age were generated for C57BL/6.NOD-Aec1Aec2
male mice. Using Linear Models for Microarray Analysis and B-
statistics software, 480 genes were identified as being
differentially expressed (P < 0.01 and Q < 0.0001) during the
development of SjS-like disease in the salivary glands.

Results The 480 genes could be arranged into four clusters,
with each cluster defining a unique pattern of temporal
expression, while the individual genes within each cluster could
be grouped according to related biological functions. By means
of pair-wise analysis, temporal changes in transcript expressions
provided profiles indicating that many additional genes are


differentially expressed at specific time points during the
development of disease. Multiple genes reportedly showing an
association with autoimmunity and/or SjS, in either humans or
mouse models, were found to exhibit differential expressions,
both quantitatively and temporally. Selecting various families of
genes associated with specific functions (for example, antibody
production, complement, and chemokines), we noted that only a
limited number of family members showed differential
expressions and these correlated with specific phases of
disease.

Conclusions Taking advantage of known functions of these
genes, investigators can construct interactive gene pathways,
leading to modeling of possible underlying events inducing
salivary gland dysfunction. Thus, these different approaches to
analyzing microarray data permit the identification of multiple
sets of genes of interest whose expressions and expression
profiles may correlate with molecular mechanisms, signaling
pathways, and/or immunological processes involved in the
development and onset of SjS.


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Aec: autoimmunexocrinopathy; BIRCH: balanced iterative reducing and clustering using hierarchies; EGF: epidermal growth factor; Idd: insulin-
dependent diabetes; IL: interleukin; LIMMA: Linear Models for Microarray Analysis; mAChR: muscarinic acetylcholine receptor; NK: natural killer;
NOD: non-obese diabetic; PANTHER: protein analysis through evolutionary relationships; PCR: polymerase chain reaction; PPAR-y: peroxisome pro-
liferator-activated receptor-gamma; SjS: Sj6gren's syndrome; SLE: systemic lupus erythematosus; TH: T helper (cell); Treg: regulatory T (cell).


Open







Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.



Introduction
The salivary gland system, comprised of the parotid, sub-
mandibular, sublingual, and minor salivary glands, secretes flu-
ids rich in proteins that are critical for the maintenance of oral
health. Saliva functions to buffer the acidification produced by
bacteria residing within the oral cavity, replace ions, moisten
food, and lubricate the oral cavity and esophagus (important
for taste, speech, and swallowing). Saliva also contains diges-
tive enzymes like amylase, anti-microbial substances like
secretary immunoglobulins, histatins, and splunc, and growth
factors like epidermal growth factor (EGF). While there are
multiple underlying causes for decreased secretions of saliva,
one of the more severe causes of xerostomia sicca, or dry
mouth disease, results from an autoimmune disease, referred
to as Sjdgren's syndrome (SjS), in which the immune system
targets initially the salivary and/or lacrimal glands [1 -3].

Despite expanding efforts to define the genetic, environmen-
tal, and immunological bases of SjS, the underlying etiology of
this disease remains ill defined. Over the past 20 years, a vari-
ety of mouse strains have been developed to study the
immuno-pathophysiological nature of SjS. Based on results of
studies using non-obese diabetic (NOD) mice and various sin-
gle-gene knockout congenic partner strains of NOD, we have
postulated that the development and onset of autoimmune
exocrinopathy can be divided into at least three distinct tem-
poral, yet consecutive and overlapping, phases. In phase 1,
aberrant genetic, physiological, and biochemical activities,
resulting presumably from retarded salivary gland develop-
ment and increased acinar cell apoptosis, occur between 6
and 10 weeks of age. In phase 2, occurring around 10 to 18
weeks of age, exocrine gland injury is observed in conjunction
with the appearance of leukocytic infiltrates and formation of
lymphocytic foci consisting mostly of T- and B-cell aggregates.
In phase 3, an overt clinical disease occurs and is defined by
measurable loss of salivary and lacrimal gland secretary func-
tion, usually detected after 18 to 20 weeks of age [4,5]. Sali-
vary and lacrimal gland dysfunction in SjS is currently thought
to result from a combination of (a) pro-inflammatory cytokine
production capable of inducing cellular apoptosis and auto-
antibodies reactive with the muscarinic acetylcholine and
adrenergic receptors and (b) the action of infiltrating T cells
(possibly CD4+TH1 7 cells) [6], leading to a progressive loss
of acinar cell mass.

Pathological changes observed in this SjS mouse model
appear to occur as a consequence of altered glandular home-
ostasis [7]. Aberrant proteolytic activity, elevated apoptosis,
downregulated EGF gene expression, and reduced a-amylase
activity are commonly observed around 8 weeks of age prior
to disease onset and independent of detectable autoimmunity.
While the factors driving these physiological changes remain
unknown, this altered glandular homeostasis is hypothesized
to be the basis for why autoreactive T cells eventually attack
exocrine gland tissue [8]. Thus, as anticipated during the


development and onset of SjS, multiple genes, signaling path-
ways, molecular networks, and immunological processes will
exhibit temporal expressions that may reflect their pathogenic
functions. This concept has been strongly supported by our
recent microarray studies of differentially expressed genes in
the lacrimal glands during the development and onset of
xerophthalmia in the NOD-derived C57BL/6.NOD-AeclAec2
mouse model of primary SjS [9].

Taking advantage of microarray technology to screen for tem-
poral changes in the expression of large numbers of genes, we
recently identified a set of differentially expressed genes in the
salivary glands of C57BL/6.NOD-AeclAec2 mice at 8 versus
12 weeks of age, two time points covering the initial onset of
detectable autoimmunity in this mouse model [10]. Results of
that study identified a set of sequential activations involving
several biological processes and signaling pathways concep-
tually important in SjS disease. During the pre-autoimmune
phase, genes upregulated at 8 weeks of age encode factors
associated with interferon, Toll-like receptor, and apoptotic
signaling pathways highly indicative of pro-inflammatory stim-
uli, especially interleukin (IL)-1 and IL-18. By 12 weeks of age,
the upregulated clustered genes had switched to encode fac-
tors associated with adaptive immunity, especially B-cell acti-
vation and differentiation. In the present study, we expanded
this comparison of differentially expressed genes to cover the
full spectrum for development and onset of SjS-like disease.
Our goal has been to address the hypothesis that identifica-
tion of genes exhibiting changes in expression that correlate
with disease progression will provide an in-depth snapshot of
molecular signaling pathways associated with noted patho-
physiological alterations in the salivary glands and the subse-
quent onset of autoimmunity leading to salivary gland
dysfunction.

Materials and methods
Animals
C57BL/6.NOD-AeclAec2 and C57BL/6J mice were bred
and maintained under specific pathogen-free conditions within
the mouse facility of the Department of Pathology with over-
sight by Animal Care Services at the University of Florida,
Gainesville. The animals were maintained on a 12-hour light-
dark schedule and provided food and acidified water ad libi-
tum. Although SjS in humans is most common in post-meno-
pausal women, male mice were used exclusively in the present
study as we have not noticed differences in the salivary gland
disease in male and female C57BL/6.NOD-AeclAec2 mice.
Mice were euthanized at 4, 8, 12, 16, or 20 weeks of age by
cervical dislocation after deep anesthetization with isoflurane.
There are no indications that this procedure affects physiolog-
ical function of the exocrine glands. Both the breeding and use
of these animals for the present studies were approved by the
University of Florida Institutional Animal Care and Use Com-
mittee.


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Preparation of RNA for detection of differentially
expressed genes in microarray analyses
Salivary glands were freshly excised from individual male mice
(n = 5 per age group) at 4, 8, 12, 16, or 20 weeks of age,
snap-frozen in liquid nitrogen, and stored at -800C until all
glandular samples were obtained. With one lobe of each sali-
vary gland, comprised of a submandibular, sublingual, and
parotid gland minus any salivary lymph nodes, all 25 samples
of total RNA from the five age groups of C57BL/6.NOD-
AeclAec2 mice were isolated concurrently using the RNeasy
Mini-Kit (Qiagen, Valencia, CA, USA) in accordance with the
protocol of the manufacturer. To account for any asynchrony
of SjS-like disease within C57BL/6.NOD-AeclAec2 male
mice, the five mice in each age group were derived from at
least two litters. Hybridizations were carried out with each of
the 25 individual RNA samples using Affymetrix GeneChip
Mouse Genome 430 2.0 Arrays in accordance with the
instructions of the manufacturer (Affymetrix, Santa Clara, CA,
USA). Each GeneChip contains 45,000 probe sets that ana-
lyze the expression level of over 39,000 transcripts and vari-
ants from over 34,000 well-characterized mouse genes.
Microarray data have been deposited with Gene Expression
Omnibus accession number [GEO:GSE15640].

Differential gene expression analysis
Microarray data were normalized using the 'guanine-cytosine
robust multi-array average' (GCRMA) algorithm and analyzed
using the LIMMA (Linear Models for Microarray Analysis) pack-
age from the R Development Core Team (The R Project for
Statistical Computing [11]) to perform differential expression
analyses. LIMMA takes into account the correlation between
replicates and uses the empirical Bayes approach, which
gives stable inference for a relatively small number of arrays
[12]. In this study, the 'fdr' method to adjust the P values for
multiple testing was used to control the false discovery rate
[13]. Since the data represent five equally spaced time points,
multiple models were used to identify the temporal patterns of
gene expression. These included the linear fit (degree = 1),
quadratic fit (degree = 2), cubic fit (degree = 3), and quartic
fit (degree = 4) regression models. B-statistics (the log of the
odds of a gene showing either positive or negative trends over
time) were calculated for each gene. Genes exhibiting a B-sta-
tistic of greater than 1.5 were considered differentially
expressed in the present analysis, and this represents a
greater than 82% level of probability that a gene is differen-
tially expressed. Duplicate genes, when present, were
removed and their expression levels were averaged across the
duplicates.

Verification of selected gene expression by semi-
quantitative reverse transcriptase-polymerase chain
reaction analysis
Aliquots of salivary gland RNA were prepared for each of the
experimental time points (4, 8, 12, 16, and 20 weeks) by pool-
ing the five individual RNA samples prepared for each age


Available online http://arthritis-research.com/content/11/2/R56



group, as described above. Each pooled aliquot then was
used to synthesize cDNA. Synthesis of cDNA was carried out
with 1 upg of RNA using Superscript II reverse transcriptase
(Invitrogen Life Technologies, Fredrick, MD, USA) in accord-
ance with the protocol of the manufacturer. The cDNA was
quantified by spectrophotometry, and semi-quantitative
polymerase chain reactions (PCRs) were performed using 1
upg of cDNA as template. After an initial denaturation at 94C
for 4 minutes, each PCR was carried out for 40 cycles consist-
ing of 940C for 1 minute and annealing temperatures at 600C
for 45 seconds and 720C for 1 minute. The forward and
reverse sequences of each primer set were Aktl, forward:
AGGATGTTTCTACTGTGGGCAGCA, reverse: TGTCTCT-
GAACAGCATGGGACACA; ApoE, forward: AGATGGAG-
GAACAGACCCAGCAAA, reverse: TGTTGTTGCAGGACA
GGAGAAGGA; Ctsb, forward: AGATTTGGGCGAT-
GGCCTTCAAAC, reverse: ATGTGCTTGCTACCTTCCTCT-
GGT; Fdftl, forward: AGTCGCAAGGATGGAGTTCGTCAA,
reverse: AACGTAGTGGCAGTACTTGTCCCA; and G3pdh,
forward: GCCATCACTGCCACCCAGAAG, reverse: GTC-
CACCACCCTGTTGCTGCA. PCR products were size-sepa-
rated by electrophoresis using 1.2% agarose gels and
visualized with ethidium bromide staining. PCR band intensi-
ties were compared to G3pdh using the Quantity One 1-D
Analysis Software (Bio-Rad Laboratories, Inc., Hercules, CA,
USA). Relative band intensities were determined by dividing
the intensity of the mRNA of selected genes by the density of
the G3pdh band.

Cluster analysis
Cluster analysis was performed for grouping differentially
expressed genes exhibiting similar expression patterns. Differ-
entially expressed genes were analyzed using the HPCluster
program [14]. HPCluster is a two-stage algorithm: the first
stage is based on BIRCH (Balanced Iterative Reducing and
Clustering using Hierarchies), whereas the second stage is a
conventional k-Means. With BIRCH, a tree of clustered fea-
tures defining the partitioning of high-dimensional space was
generated, followed by a conventional k-Means clustering of
each cluster feature obtained with BIRCH.

Gene ontology analysis
Associations of the differentially expressed genes with biolog-
ical processes, molecular functions, and pathways were anno-
tated using the PANTHER (Protein ANalysis THrough
Evolutionary Relationships) classification system [15,16]. To
determine whether the observed number of gene counts
exceeded the expected counts, one-tailed P values for enrich-
ment of a particular biological process, molecular function, or
pathway were calculated using the standard Fisher exact test.

Results
The present study was designed to define the changing gene
expression profiles within the salivary glands of C57BL/
6.NOD-AeclAec2 mice at five time points representing a pre-


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Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.



disease stage (4 weeks), the early pre-clinical stage (8 weeks),
the initial influx of leukocytes into the salivary glands (12
weeks), the early clinical phase of autoimmunity (16 weeks),
and the early onset of clinical SjS-like disease characterized by
secretary dysfunction (20 weeks). The C57BL/6.NOD-
AeclAec2 mouse is a model of primary SjS in which the Idd3
region of chromosome 3 and the Idd5 region of chromosome
1 derived from the NOD mouse were bred into the non-autoim-
mune C57BL/6 mouse, resulting in an SjS-like disease sus-
ceptibility that mimics both the pathophysiological
characteristics and reduced secretary responses observed
with NOD mice during development and onset of disease
[4,17,18]. In C57BL/6.NOD-AeclAec2, Aeci corresponds
to Idd3 and Aec2 corresponds to Idd5 [18].

For the present study, we elected to begin the analyses at 4
weeks of age despite the fact that some intrinsic glandular
changes occur in the salivary glands of NOD mice at an earlier
age, especially around the time of birth [7]. However, salivary
glands in C57BL/6.NOD-AecIAec2 mice appear normal by
histology and protein secretion profiles at 4 weeks of age; as


a result, the 4-week-old time point was established as the
baseline for temporal analyses in these studies. Furthermore,
we hypothesized that, by examining five time points spaced 4
weeks apart, genes identified as being differentially expressed
after 4 weeks would correlate with one or more manifestations
of aberrant glandular homeostasis, initiation of autoimmunity,
and subsequent onset of salivary gland secretary dysfunction.
In addition, by carrying out parallel analyses using salivary
glands from the parental C57BL/6J strain, we should be able
to identify genes that might be differentially expressed due
merely to the natural aging process, thereby eliminating these
from further consideration as disease-associated genes.

Differential gene expressions in salivary glands of
C57BL/6.NOD-Aec1Aec2 mice during development and
onset of Sj6gren's syndrome-like disease
With a statistical discrimination P value set at less than 0.05,
LIMMA software and B-statistics analyses identified 480 spe-
cific genes as being differentially expressed in the salivary
glands of C57BL/6.NOD-AeclAec2 mice during SjS disease
development, despite the fact that many additional genes


Figure 1


4 week


8 week


12 week


16 week 20 week


I II II I I I. I


Expression profiles of differentially expressed genes depicted by Heatmap and HPCluster analyses. Heatmap of differentially expressed genes (n =
480) in the salivary glands of 25 individual C57BL/6.NOD-AeclAec2 male mice (n = 5 mice per age group) at 4, 8, 12, 16, and 20 weeks of age,
grouped into four clusters based on temporal expression profiles (left panel). Upregulated gene expressions are shown in red, and downregulated
gene expressions are shown in green. Based on HPCluster analyses, the averaged gene expression patterns for each of the four clusters are graph-
ically modeled as temporal plots over the five time points measured (right panels). Aec, autoimmunexocrinopathy; NOD, non-obese diabetic.


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appeared to be differentially expressed at any particular time
point. As illustrated in the heatmap shown in Figure 1 (left
panel), these 480 genes can be compartmentalized into one
of four highly reproducible clusters, each of which exhibits a
specific temporal gene expression profile. In addition, each
cluster can be graphically modeled as temporal plots (Figure
1, right panel), based on HPCluster analyses, showing the
averaged gene expression patterns over the five time points.
For quick verification of results obtained from the microarrays,
four genes (Ctsb, ApoE, Aktl, and Fdftl) were selected ran-
domly for semi-quantitative reverse transcriptase-PCR analy-
sis as they represented genes that were expressed at high,
intermediate, low, and depressed levels, respectively, in the
salivary glands of C57BL/6J.NOD-AeclAec2 mice at various
ages tested. The expression of these genes in the salivary
glands relative to G3pdh (Additional data file 1) proved to be
highly consistent with the relative expressions obtained from
the microarrays, thus validating the relative expressions
obtained with the current microarrays.

Pathways, biological processes, and molecular functions
of genes differentially expressed in salivary gland
tissues
By means of the PANTHER classification system, these 480
differentially expressed genes were categorized as being
associated with specific biological pathways (Table 1), biolog-
ical processes (Table 2), and/or molecular functions (Table 3).
Several of the biological pathways identified might be antici-
pated as being directly involved with age-dependent aspects
of normal development and activities; thus, it was not surpris-
ing that integrin signaling, vitamin B6 metabolism, p53-medi-
ated transcription, fibroblast growth factor signaling, and
hedgehog signaling pathways were also identified as being
differentially expressed in parental, SjS-non-susceptible
C57BL/6 mice (data not shown), suggesting that these path-
ways contain genes differentially expressed as a result of age
and probably not disease. However, the specific pathway
genes identified as differentially expressed in C57BL/6J
parental mice were only occasionally the same genes as those
differentially expressed in C57BL/6.NOD-AeclAec2 mice,
despite being assigned to the same pathway(s). An example
of this is demonstrated by the fact that, of the 21 integrin sig-
naling pathway-associated genes, 13 encoded different colla-
gen proteins in the salivary glands of C57BL/6.NOD-
AeclAec2 mice, but only 4 of these 13 collagen genes were
identified as differentially expressed in salivary glands of
C57BL/6J mice (C.Q. Nguyen, A. Sharma, B.H. Lee, J.-X. She,
R.A. Mclndoe, A.B. Peck, unpublished data). Two pathways
identified in the salivary glands as containing differentially
expressed genes unique to the C57BL/6.NOD-AeclAec2
mice are the muscarinic acetylcholine receptor (mAChR) path-
ways. Loss of saliva secretion is thought to result, in part, from
auto-antibodies reactive with the mAChRs [19-21]. In this
association, four genes (Snap23, Itpr2, Prkarlb, and Grina)
were upregulated with maximum expression levels occurring


Available online http://arthritis-research.com/content/11/2/R56



around 12 weeks of age; one gene (Sl/ca3) remained
unchanged, whereas four genes (Bche, Cptla, Gngl 11, and
Myh9) showed progressive downregulation (Figure 2a). The
latter four genes showed reduced levels of expression at 20
weeks of age, or the time that loss of saliva secretion is
detected.

In addition to biological pathways, several biological proc-
esses (for example, cellular metabolism, blood circulation, and
apoptosis) (Table 2) and molecular functions (for example,
enzymatic activities) (Table 3) are identified via clustering of
the differentially expressed genes. One important example
involves the biological process of cell adhesion. Cell adhesion
molecules are critical for gland development and subsequent
remodeling of extracellular matrix during normal cellular home-
ostasis but may emerge as the consequence of pathogenic
leukocytes being recruited into the salivary glands, resulting in
glandular injury. A major feature of SjS is the presence of leu-
kocyte infiltrates within the exocrine glands during the devel-
opment and onset of disease, an event most likely mediated
directly by the activation of adhesion molecules. As shown in
Figure 2b, temporal analyses of genes encoding the adhesion
molecules revealed that 10 of 1 6 genes encoding a variety of
adhesion molecules (that is, Dst, Tmem8, Pkp4, Mtssl, Dsg2,
Ptprd, Neo1, Tspan11, Ptprzl, and Sdc4) were upregulated,
generally showing their highest expression levels around 12
weeks of age. In contrast, 6 of the 16 genes (that is, Lama2,
Matn2, Megf9, Nidl, Nid2, and Pcolce) showed a progressive
decrease in expression (Figure 2c). Although leukocyte infiltra-
tion of the salivary gland is first observed between 8 and 12
weeks of age, it is unknown which specific adhesion mole-
cules are involved in these events.

A second set of genes considered important to the develop-
ment of SjS-like disease and identified by their biological proc-
ess involves apoptosis of acinar tissue. These genes can be
separated into those that induce apoptosis (for example,
Gpr3711, Neo1, Tnfrsf19, Bcl2111, and Aifm2) (Figure 2d) and
those that inhibit apoptosis (for example, Sphkl and Birc5)
(Figure 2e). Interestingly, two genes, Aifm2 and Neo1, were
upregulated showing maximum expression levels at 12 weeks
of age, the Gpr3711 gene showed little change over time, and
the remaining genes, including Sphkl and Birc5 encoding for
inhibitory factors, were each downregulated showing a con-
sistent temporal decrease in expression levels.

Clustering of biological processes with identification of
immuno-pathophysiological processes underlying
Sj6gren's syndrome-like disease
As illustrated by the heatmap in Figure 1, four distinct clusters
of genes showing comparable temporal gene expression pro-
files were established by HPCluster software analyses. To
identify the various biological processes linked to genes
grouped within the individual clusters, gene ontology analyses
were performed separately for each cluster, and the results are


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Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.




Figure 2


(a) -- Bche
- Cptla
Gng11
--- Myh9
S - SIcla3
/ \ --Grina
-\Itpr2
Prkarlb
Snap23





0 4 8 12 16 20

(b) ---Dsg2

--d- MtssI
-Neol
--Pkp4
-4- Ptprd
Ptprzl
-Sdc4
f Tmem8
--Tspan1l


0 4 8 12 16 20


4 (d)


---Gpr3711
-*-Neol
- Tnfrsfl9
--Bc2111
- +-AifmZ


0 4 8 12 16 20


0 4 8 12 16 20


1.2 1 (e)


-4-Sphkl
-I- Birc5


0 4 8 12 16 20


Age of mice (weeks)

Representative temporal expressions of genes within biological pathways, processes, or molecular function, as identified by PANTHER (Protein
ANalysis THrough Evolutionary Relationships). These include the muscarinic acetylcholine receptor signaling pathways (a), collagen and collagen-
associated (b) or non-collagen (c) genes associated with general cell adhesion, and genes associated with induction (d) and inhibition (e) of apop-
tosis.


presented in Table 4. Again, biological and molecular proc-
esses were considered statistically significant if they reached
a Pvalue of less than 0.05. Cluster 1, consisting of 233 genes,
exhibits a temporal profile characterized by upregulated gene
expressions in salivary glands of C57BL/6.NOD-AeclAec2
mice between 8 and 16 weeks of age, with the vast majority of
genes showing maximal expressions at 12 weeks of age.
Genes of cluster 1 belong to pathways whose functions are
linked to normal metabolic functions, metabolite or ion trans-
port and trafficking, and glandular integrity. The gradual loss of
these activities after the 16-week time point most likely reflects
the gradual onset of glandular pathology and dysfunction. This


period in development of SjS-like disease represents the early
phase of immunological activity in the salivary gland, yet pre-
ceding the onset of clinical disease; thus, it is not surprising
that the differentially expressed genes are involved in either
metabolic or secretary functions, most likely demonstrating
attempts to balance injury, repair, and compensatory cellular
activities. Genes associated generally with the transport of
metabolites (for example, Abcgl, Ctns, and Sic2a4) or anions
and cations (for example, Abccl, Atp6v, and Sic22a18) and
with voltage-gated channels (for example, Kcnbl and Scnlb)
illustrate this point, as presented in Figures 3a and 3b, respec-
tively. One gene of particular interest is Kcngl, whose gene


Page 6 of 16
(page number not for citation purposes)


--- Lama2
-fr-Matn2
-*-Megf9
- Nidl
--Nid2
-*-Pcolce








Available online http://arthritis-research.com/content/11/2/R56


Table 1

Pathways represented in 480 differentially expressed genes with highest statistical discrimination


Number of genes


Percentage of genes


Pathways

Integrin signaling pathway (P00034)

Vitamin B6 metabolism (P02787)

p53 pathway (P00059)

Cell cycle (P00013)

Muscarinic acetylcholine receptor 2 and 4 signaling pathway (P00043)

Muscarinic acetylcholine receptor 1 and 3 signaling pathway (P00042)

Angiogenesis (P00005)

Metabotropic glutamate receptor group I pathway (P00041)

FGF signaling pathway (P00021)

Hedgehog signaling pathway (P00025)

VEGF signaling pathway (P00056)

PI3 kinase pathway (P00048)

FGF, fibroblast growth factor; VEGF, vascular endothelial growth factor.
product binds with the gene product of Kcnel to form a volt-
age-gated potassium channel regulator that may be functional
in muscarinic receptors [22].


Cluster 2, comprised of 96 genes, exhibits expression profiles
characterized by genes whose expressions are highly upregu-
lated in the salivary glands of C57BL/6.NOD-AecIAec2 mice


4.600/o

0.70%/

2.200/%

0.900/%

1.10%0/0

0.900/%

2.000/%

0.70%0

1.300/%

0.700/0

0.900/0

1.100/0


9.92 x 10-10

3.53 x 10-5

4.77 x 10-5

0.000843

0.002843

0.018809

0.019019

0.020464

0.023515

0.028308

0.033627

0.039324


at 4 weeks of age but downregulated thereafter. Genes of this
cluster appear to be involved primarily with maintenance of
glandular structure, especially cellular processes such as cell
cycling and cell proliferation/differentiation. However, inclu-
sion of genes associated with apoptosis and cell adhesion
may point to early events that indicate pathophysiological
activities such as changes in glandular homeostasis,


Table 2


Biological processes represented in 480 differentially expressed genes with highest statistical discrimination


Classifications

Biological process

Cell structure and motility (BP00285)

Other metabolism (BP00289)

Cell cycle (BP00203)

Cell adhesion (BP001 24)

Transport (BP001 41)

Amino acid metabolism (BP00013)

Carbohydrate metabolism (BP00001)

Phosphate metabolism (BP00095)

Protein targeting and localization (BP00137)

Homeostasis (BP00267)

Oncogenesis (BP00281)

Apoptosis (BP001 79)

Blood circulation and gas exchange (BP00209)


Number of genes


40

27

35

25

39

11

19

6

8

8

13

14

4


Percentage of genes


8.70%/o

5.90%/o

7.60%/o

5.40%/o

8.500/o

2.40%/o

4.10%/

1.30%/o

1.700/0

1.700/0

2.800/0

3.000/0

0.90%/o


Page 7 of 16
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Classifications


P value


P value


1.00 x 106

1.90 x 10-6

7.17 x 10-6

5.23 x 10-5

0.00059

0.001705

0.003036

0.009946

0.019608

0.02484

0.030304

0.043403

0.048594








Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.


Table 3

Molecular functions represented in 480 differentially expressed genes with highest statistical discrimination


Classifications


Number of genes


Molecular function
Extracellular matrix (MF001 78)
Select regulatory molecule (MF00093)
Isomerase (MF001 66)
Transporter (MF00082)
Oxidoreductase (MF001 23)
Cytoskeletal protein (MF00091)
Kinase (MF00107)
Synthase and synthetase (MF00118)
Transferase (MF00131)
Protease (MF00153)


increased cell death, and impaired structural integrity. As pre-
sented in Figure 3c, five genes involved in apoptosis were
identified as differentially expressed. Of note, at 20 weeks of
age, the apoptosis-inducing factor caspase-7 shows an
upregulated expression in the salivary glands, consistent with
the concept that this is a second wave of apoptosis occurring
at the time of immune attack possibly initiated by early apop-
totic events seen at 4 weeks of age. At the same time, BIRC5,
an anti-apoptotic factor, is strongly downregulated after the 4-
week time point. Another set of cluster 2-associated genes
that encodes cell adhesion molecules includes several colla-
gen genes plus the laminin B gene (Lama2) and two nidogen
genes (Nidl and Nid2) (Figure 3d). Nidogen is thought to
connect the laminin and collagen networks to stabilize base-
ment membranes [23].

Cluster 3, consisting of 102 genes, contains genes involved in
normal cellular physiology, but also cell adhesion, lipid/fatty
acid/steroid metabolism, and oncogenesis, three processes
that have been linked to autoimmunity in SjS. Genes in cluster
3 exhibit expression profiles similar to that of cluster 2, but dis-
tinguished in part by the fact that the decline in gene expres-
sion is less pronounced and generally remains downregulated
through the onset of glandular dysfunction (that is, 20 weeks
of age). Like cluster 2 genes, those of cluster 3 encode for a
set of adhesion molecules (Figure 3e). This set of genes con-
sists of a distinct set of collagen genes, the matrilin gene
(Matn2), the multiple EGF-like domain 9 gene (Megf9), the
procollagen-C endopeptidase enhancer gene (Pcolce), and
the Syndecan 4 gene (Sdc4). Matrilin is involved in extracellu-
lar matrix assembly, MEGF9 is a trans-membrane molecule
involved in neural development, and PCOLCE enhances pro-
collagen-C endopeptidase cleavage of procollagen to form
fibrillar collagen type 1. Expressions of these genes tend to


Percentage of genes


5.40%/o
8.30%/o
2.40%/o
5.400/0
5.000/0
5.400/0
4.800/0
2.000/0
5.000/0
3.500/0


P value


1.24 x 10-9
8.61 x 10-5
9.04 x 10-5
0.000151
0.001595
0.002244
0.003857
0.018598
0.041613
0.047429


mimic those seen for the cluster 2-associated adhesion mole-
cules with the exception of Sdc4, which is upregulated
through 12 weeks of age before being downregulated. Sdc4
encodes for an adhesion proteoglycan expressed on epithelial
cells involved in growth factor receptor signaling. A second set
of cluster 3-associated genes of particular interest involves
potential impairment of lipid, fatty acid, and steroid hormone
metabolism (Figure 3f). Of special interest is Cavl, which
encodes for caveolin-1, a molecule associated with the integ-
rity of lipid rafts, but also the Erk signaling pathway via Ras/
Raf-1. Although recent studies have suggested that impair-
ment of lipid metabolism and transport is restricted mostly to
ocular surface-related disease and not salivary gland disease,
these new data point to the possibility that lipid and fatty acid
metabolism plays an important role in salivary gland dysfunc-
tion and onset of xerostomia as well. This would be consistent
with our recent work [24,25] in which gene mapping data indi-
cate that the SjS-susceptibility region Aec2 in C57BL/6.NOD-
AeclAec2 mice contains multiple genes that regulate home-
ostasis of fatty acids, high-density lipids, and lipoproteins.

In contrast to genes associated with clusters 1 through 3,
those associated with cluster 4 represent a limited subset of
49 genes whose maximal expressions in the salivary glands
occur between 16 and 20 weeks of age, the time at which the
covert autoimmunity finally results in measurable dysfunction
of salivary and lacrimal gland secretions in these mice. As
might be expected, the genes in cluster 4 are linked predomi-
nantly to immunity (Figure 3g), with a lesser number linked to
muscle contraction (Figure 3h). The latter set of genes corre-
lates with altered neural stimulation and direct loss of secre-
tory function. Examination of the cluster 4-associated genes
indicates that several of the identified genes encode for major
histocompatibility class I (H2q5 and H2q6) and class II (H2ab


Page 8 of 16
(page number not for citation purposes)









Available online http://arthritis-research.com/content/11/2/R56


Figure 3


--Abccl
-U-Abcgl
-*-Actr2
- Atp6vlcl
---Atp6vld

--Ctns
--Itpr2
Skc22al8
-*-Sk2a4
- Sk45a4
---Snap23
-txm4a
Tomll2


0 4 8 12 16 20

(C)













0 4 8 12 16 20

(e)


---Bir
--Casp7
Gpr37
-Gulpl
-Sphkl


(b)


.A,


0 4 8 12 16 20


0 4 8 12 16 20


---Cdon


----Collal
-*-Colla2
- Col4a2
-Col6al
-e-Matn2
-Megf9
- PcoIce
Sdc4


0 4 8 12 16 20


0 4 8 12 16 20


-4B-Clqb
-*-H2-Abl
H2-Ebl
-Igh
--*-H2-Q6
-Tac
-Es22
/ H2-Q5



0 4 8 12 16 20


-4- Ptgds
-'-Cck
S/ Tad








0 4 8 12 16 20


Age of mice (weeks)


Examples of temporal changes in expression levels of selected genes associated with each of the four sets of genes identified by cluster analysis.
Genes include those present in metabolite transport (a) and voltage-gate channels (b) of cluster 1, apoptosis (c) and adhesion (d) of cluster 2,
adhesion (e) and fatty acid and lipid metabolism (f) of cluster 3, immunity (g), and muscle cell contraction (h). Each gene profile is presented as a
pair-wise comparison of expressions in the salivary glands of C57BL/6.NOD-AeclAec2 mice at 8, 12, 16, and 20 weeks of age relative to 4 weeks
of age. Aec, autoimmunexocrinopathy; NOD, non-obese diabetic.


and H2eb) products, a complement component (Clqb), an

immunoglobulin heavy chain (Igh), the apoptosis-inducing pro-
tease granzyme A (Gzma), and preprotachykinin (Tac 1). Tach-
ykinin is involved not only in inflammatory responses, but in
neural stimulation as well, thereby bridging inflammation to
muscle contraction [26].


Phase-specific gene expressions in the salivary glands
of C57BL/6.NOD-Aec1Aec2 mice during development of
Sjigren's syndrome-like disease
As described above, both functional pathways and biological

processes can be identified through the clustering of differen-
tially expressed genes based on their temporal profiles over
the five selected time points examined. Since these microarray


Page 9 of 16
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-- Atp6vOal
---Kcnbl
-i-Kcnql
-Scnlb
- Scnnla
---Sk16a3
-Sk9a2


-*-Col3al
---Col5a2
-*-Col6a2
- Col6a3
- Lama2

-NId2
--Nid2










--Cptla
-I--Gpam
--Cdsl
-CavI
-4--Phyh
--Impa2
--Sc25a20
Apol7a








Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.


Table 4

Biological processes of differentially expressed genes of each cluster


Classification of clustered genes

Cluster 1 (233 differentially expressed genes)

Other metabolism (BP00289)

Carbohydrate metabolism (BP00001)

Cell structure and motility (BP00285)

Transport (BP00141 )

Phosphate metabolism (BP00095)

Cell cycle (BP00203)

Protein targeting and localization (BP00137)

Intracellular protein traffic (BP001 25)

Cluster 2 (96 differentially expressed genes)

Cell cycle (BP00203)

Cell proliferation and differentiation (BP00224)

Cell adhesion (BP001 24)

Cell structure and motility (BP00285)

Oncogenesis (BP00281)

Apoptosis (BP001 79)

Homeostasis (BP00267)

Cluster 3 (102 differentially expressed genes)

Amino acid metabolism (BP00013)

Cell adhesion (BP001 24)

Cell structure and motility (BP00285)

Lipid, fatty acid, and steroid metabolism (BP00019)

Other metabolism (BP00289)

Oncogenesis (BP00281)

Developmental processes (BP00193)

Cluster 4 (49 differentially expressed genes)

Immunity and defense (BP00148)

Muscle contraction (BP001 73)


Number of genes


Percentage of genes


6.70%/

5.80%/o

8.500/o

9.400/0

1.80%0/0

6.300/0

2.200/0

6.300/0


6.300/0

2.700/0

4.000/%

8.500/o

0.900/0

2.200/0

1.800/%


6.100/%

9.200/%

11.200/%

9.200/%

6.100/%

5.100/%

13.300/%


20.000/0

6.700/0


data measure differential gene expressions covering the
majority of the mouse genome and, at the same time, span
temporally the progressive development and early onset of
autoimmune-mediated xerostomia in salivary glands of
C57BL/6.NOD-Aec1Aec2 mice, each represented gene can
be examined individually for its expression profile, even when
not identified as being statistically significant using LIMMA
and B-statistics. When analysis is conducted in this manner, a
marked increase in the number of individual genes that exhibit
distinct expression kinetics occurs and is often associated
with a particular phase of disease. This latter point is clearly
demonstrated when one expands the gene set involved in


immunity beyond the genes presented in Figure 3g. Using a
pair-wise analysis, we have uncovered several genes that
encode factors important in T cell-antigen-presenting cell
interactions (Figure 4a), B-cell antibody production (Figure
4b), members of the chemokine-ligand families, CCL and
CxCL (Figure 4c,d), and complement-associated factors (Fig-
ure 4e,f) that show marked differential expressions during
development of SjS-like disease. These data indicate that the
expression profiles for the chemokine, T cell-associated, and
immunoglobulin genes precisely mimic the temporal appear-
ance of macrophages/dendritic cells and of T and B lym-
phocytes into the salivary glands, as determined by immuno-


Page 10 of 16
(page number not for citation purposes)


P value


8.09 x 10-5

0.000695

0.000846

0.003032

0.011909

0.019047

0.023674

0.025339


3.05 x 10-6

0.004340

0.005309

0.009058

0.016163

0.028634

0.034910


0.0002

0.0004

0.0012

0.0024

0.0172

0.0190

0.0475


0.0020

0.0030









Available online http://arthritis-research.com/content/11/2/R56


Figure 4


--H2-Ab2
-U-H2-Aa
--A- Cd74
-0- Tc-b-S.2
-a Tcra
- Thmd4


0 4 8 12 16 20


--_CdS9
-UCdl9

-Cc'21
-4-- CC122


0 4 8 12 16 20

(e) --ci.
-*-Clqb
-Clr


-4-C4
\-C2


0 4 8 12 16 20


0 4 8 12 16 20


4 (d)


0 4 8 12 16 20


0 4 8 12 16 20


Age of mice (weeks)

Temporal expressions of genes associated with autoimmunity in the salivary glands of C57BL/6.NOD-AeclAec2 mice at 8, 12, 16, and 20 weeks of
age relative to 4 weeks of age, including antigen presentation (a), immunoglobulin synthesis (b), chemokine production (c, d), C1 q genes (e), and
the alternate complement pathway (f), as identified by pair-wise analysis but not Linear Models for Microarray Analysis (LIMMA) and B-statistics.
Aec, autoimmunexocrinopathy; NOD, non-obese diabetic.


histochemical staining. More specifically, genes associated
with macrophages and dendritic cells exhibit upregulation as
early as 8 weeks of age whereas T and B cell-associated
genes exhibit upregulated expressions around 12 weeks of
age.


Although studies linking specific genes with SjS remain lim-
ited, several genes and/or gene products have been reported
as being associated with either SjS or diseases linked to SjS,
such as systemic lupus erythematosus (SLE) and rheumatoid
arthritis. These include such genes as ApoE [27], Clu [28],
Ctla4 [29], Fas/Fasl [30], Gstml [31], 117r [32], Ifihl [33],
IgG [34], Irf5 [35], Lyzs [34], Mbl [36], Ptpn22 [37], Sh2b3
[38], Stat4 [39], Tap2 [34], Tgf/i1, Tnfa [40], and Tnfaip3
[41]. At the same time, a growing list of genes and/or gene
products has been reported as being associated with SjS-like
disease in mouse models [10,42]. These genes include Abpb,
ApoA1, Baff (Blys), Ccl11, Ccr7, Ctss, Ctsb, Cstc, Cxcr3,


Cxcr4, Egf, Fgl, Fut4, 1110r, Isg, Ltb, Ltbr, Meisl, Nfkfia, Pgf,
Racl, Rafl, Socs3, Stat6, Traf3, Tnfrsf13, and Vcami.
Despite the fact that C57BL/6.NOD-AeciAec2 mice repre-
sent a single individual genetically, a surprisingly high number
of these genes, whether associated with human disease or
disease in mouse models, exhibited specific temporal changes
in their expression profiles when analyzed using a pair-wise
comparison, as presented in Figure 5.


Discussion
In the present study, we used microarray technology to identify
genes whose temporal expressions are differentially regulated
during development of sialadenitis and xerostomia in the
C57BL/6.NOD-AeciAec2 mouse model of primary SjS. The
use of C57BL/6.NOD-AeciAec2 mice offers two advantages
for microarray studies: first, the C57BL/6J background of
C57BL/6.NOD-AeciAec2 mice eliminates features of NOD
mice which complicate interpretation of potential underlying


Page 11 of 16
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--*-- Ighg
--- Igh-g2a
- Igh-gVJC
-0- Igh-VJS58
gk-C
1g IkV1-117
IgkV28
- gkV-111
IgkV-V








-CxcI17











-U*-Cfd.
_Cf p
-CA








Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.


Figure 5


-.-Ctlwt
- -Fas
-*-Gstml
--Ilfihl
---Sh2b3
-*-Stat4
-+-Tap2
-Tgfbl


0 4 8 12 16 20


3 (c)


-Ccll1
---Ctsb
--r-Fut4
-*-Ltbr
-*-Meisl
-Raf1
-Stat6
-Traf3


0 4 8 12 16 20


qu" -4-ApoE
-4&- Clu
-1- Il7r
Irsf5
Lyz
-0- PtpnZ2
Tnfaip3





0 4 8 12 16 20

(d) -- ccr7
A Cstc

-Cxcr4
-Nfkb
-- Tnfrsfl3b
Cxcr3


0 4 8 12 16 20


Age of mice (weeks)

Differential expression of genes reported to be associated with connective tissue autoimmunity in humans and/or mouse models. Temporal changes
in gene expressions in the salivary glands of C57BL/6.NOD-AeclAec2 mice for genes that are reportedly associated with Sjogren's syndrome, sys-
temic lupus erythematosus, and/or rheumatoid arthritis in humans (a, b) and genes considered important for disease development in the salivary
glands of non-obese diabetic (NOD) and NOD-derived mice (c, d). Expression profiles are presented for these genes at 8, 12, 16, and 20 weeks of
age relative to 4 weeks of age. Aec, autoimmunexocrinopathy.


genetic and pathophysiological causes of autoimmunity, and
second, non-autoimmune C57BL/6J parental mice provide an
excellent comparative control identifying normal physiological
changes. Development of SjS-like disease in C57BL/6.NOD-
AeclAec2 mice progresses through several sequential, yet
continuous, covert pathological stages, resulting eventually in
the onset of overt clinical manifestations. Our extensive stud-
ies with C57BL/6.NOD-AeclAec2 mice have defined biolog-
ical and immunological features associated with various
stages of SjS-like disease [4], thereby establishing a basis for
correlating gene expressions and pathology.


Results presented herein, similar to microarray results recently
reported for the lacrimal gland [9], indicate that HPCluster
analysis of the microarray data identifies multiple sets of genes
whose associated pathways correlate with concepts currently
hypothesized to explain the early pathophysiological proc-
esses and subsequent autoimmunity. In this regard, our statis-
tical analyses identified 480 genes that were differentially
expressed in the salivary glands over the five ages examined,
although few of these genes actually reside within either the
Aeci orAec2 genetic regions. Since the vast majority of these
480 genes are scattered throughout the genome, identifying
primary candidate genes regulating development of SjS-like
disease versus secondary genes representing either activa-
tions of downstream events or functionally linked molecular


interactions poses a daunting task. Nevertheless, the present
results appear to provide validation for the genomic microarray
approach in understanding the underlying immuno-pathophys-
iological features of SjS.


This study also provides a global genomic analysis of differen-
tially expressed genes, permitting an expansive overview of
biological processes and gene interactions revealing poten-
tially important pathways even when many genes within a par-
ticular pathway may not exhibit altered expression or be
involved in normal cellular functions. Examples of this include
the upregulation of genes involved in apoptosis, cell adhe-
sions, or homeostasis of lipid, lipoprotein, and fatty acid
metabolism, three biological processes central to salivary and
lacrimal gland functions. In addition, this study revealed indi-
vidual genes that exhibit differential expressions during spe-
cific phases of disease, pointing to additional interactive
pathways involved in pathological events. Examples of such
genes would include those encoding for chemokines, comple-
ment factors, and T- and B-cell signaling.


Although microarray data permit the identification of genes
that are differentially expressed, perhaps one of the more inter-
esting results highlighted by the present study, and in support
of our previous studies [9,10], is the ability of the microarray
analyses to confirm a rapidly changing gene expression profile


Page 12 of 16
(page number not for citation purposes)












during the chronic progression of disease development and
subsequent salivary gland dysfunction. While considerable
emphasis is placed on genes that are upregulated as being
involved in this pathogenesis, many genes exhibit statistically
significant downregulated differential expressions, as
depicted in clusters 2 and 3 of the heatmap and in the pair-
wise analyses. We suspect that this indicates two important
events. First, at 4 weeks of age, major changes in salivary
gland homeostasis depicting normal, age-related cellular proc-
esses are occurring, thus resulting in decreased expressions
of these genes at the later ages. Second, development of
pathological conditions within the salivary gland results in loss
of cellular functions, thereby decreasing gene expressions of
many biological processes. Nevertheless, the largest cluster of
genes (cluster 1) identified differentially expressed genes
upregulated with maximal expression levels at 12 to 16 weeks
of age, or the time of detectable inflammation. This would indi-
cate that numerous aberrant biochemical and physiological
activities are occurring prior to both autoimmunity and overt
disease onset. Finally, except for genes associated mainly with
inflammation and autoimmunity, most genes are no longer
upregulated at the onset of clinical disease.

Data analyses in the present study used two distinct methods.
The first was identification of genes differentially expressed
based on statistical evaluations across development of dis-
ease. For the present study, we specifically chose a cutoff
value of B-statistics P value of 0.05, which identified 480
genes with a probability of greater than 80% that each gene is
differentially expressed. These were considered genes of
interest identified in an unbiased manner. The second proc-
ess, however, was to perform pair-wise analyses in which a
gene's relative expressions at 8, 12, 16, and 20 weeks were
compared with its expression at 4 weeks, an age point arbitrar-
ily set as pre-disease. This analysis was used to identify genes
whose differential expressions might correlate with a specific
phase of SjS-like disease and indicate a specific altered bio-
logical process.

A concern, and possible weakness, in these microarray analy-
ses is whether important data are missed when differential
gene expressions are determined by statistical measurements
or pair-wise analyses. An example of this would be the
detected expressions of chemokines and their receptors, a
large family of proteins that regulate leukocyte trafficking to tis-
sue sites. It is assumed that in SjS small numbers of macro-
phages along with dendritic cells are the first leukocytes to
enter the salivary glands, acting to recruit the T and B lym-
phocytes that subsequently form lymphocytic foci commonly
seen in the exocrine glands of SjS patients and animal models.
This raises the question of whether the low numbers of these
cell populations express sufficient levels of mRNA transcripts
for detection. In the present study, we were able to detect
expression of several CXC and CC ligand genes in the salivary
glands starting at 8 weeks of age, the precise time when leu-


Available online http://arthritis-research.com/content/11/2/R56



kocytes begin entering the exocrine tissues in large numbers.
The relatively limited profile of detectable chemokines proba-
bly indicates a highly restricted transcript expression. Of inter-
est, the first CXC ligand chemokine gene detected is CxcI16,
an interferon-gamma-regulated chemokine whose product
attracts natural killer (NK) cells and memory CD4+ memory T
cells (possibly TH 7 cells). This is subsequently followed by
detectable Cxcl9, whose product attracts TH1 cells, and
CxcI13, whose product attracts B1 and B2 B lymphocytes.

Recently, Delaleu and colleagues [42] reported that several
CCL chemokines, including CCL-2, CCL-5, CCL-7, CCL-9,
CCL-19, and CCL-22, were differentially expressed in sera
and/or saliva of NOD mice at onset of SjS-like disease when
compared with levels observed in BALB/c mice, suggesting
that these proteins are biomarkers since they correlated with
the state of hyposalivation. In the present study, we found
Cc/5 (coding for Rantes), Cc/8 (coding for MCP-2), Cc/19
(coding for MIP-3), and possibly Cc/21 and Cc/22 to be
upregulated. The most prevalent Cc/ gene transcript in the sal-
ivary glands was Cc/8, whose product is a chemoattractant for
monocytes and possibly NK and T cells. Cc/6, which shows a
slight bi-modal expression and is clearly expressed prior to the
other Cc/genes, is involved in myeloid cell differentiation; thus,
this chemokine appears to be expressed in concert with
Cxcl16. Although our microarray data do not match perfectly
with the results reported by Delaleu and colleagues [42], it
must be remembered that the latter study was carried out with
fluids obtained from NOD mice predisposed for three autoim-
mune diseases: SjS, T1 D, and possibly thyroiditis.

Using pair-wise analyses, we have identified many genes that
show temporal changes in expressions correlating with spe-
cific phases of SjS. This is clearly demonstrated by consider-
ing the profiles of complement component genes. Of
particular interest is the complement factor Cl q. Polymor-
phisms present in C1 q have been shown to correlate with SLE
in humans [43], but the role of complement in SjS remains
highly speculative. Our recent studies in NOD and C57BL/
6.NOD-AeclAec2 mice indicate a crucial role for C3 in the
development of salivary and lacrimal gland dysfunction [44].
Results from the present microarray study indicate that tran-
scripts of Clqa, Clqp, and C1qy, whose products form the
core of Clq, are highly upregulated, showing maximal levels
between 12 and 16 weeks of age. Whereas transcription of
Clr was slightly elevated, transcription of Cls was slightly
depressed. Since Cls is essential for activation of the classi-
cal complement pathway, we hypothesize that the comple-
ment membrane attack complex plays little or no role in SjS-
associated salivary gland disease, a concept supported by the
fact that expressions of C6 through C9 transcripts were
unchanged, plus the high transcript levels of both Clu (clus-
terin) and CD59 protection) two complement membrane
attack complex inhibitors. In contrast, genes comprising the
alternate pathway (that is, Cfb, Cfd, Cfp, and C3) were all


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Arthritis Research & Therapy Vol 11 No 2 Nguyen et al.



upregulated, suggesting that the alternate pathway may be
active in the disease process. At the same time, C1q may be
upregulated in response to a decreased efficacy in the clear-
ance of apoptotic cells/debris that could affect tissue homeos-
tasis, antigen presentation, and subsequent regulatory T (Treg)
cell activation. In addition to C1 q, factors involved in the clear-
ance of apoptotic debris by phagocytes include CD91/LRP-1,
CD93, and calreticulin, as modeled in Figure 6a. In brief, C1 q
is one of the known molecules responsible for binding to apop-
totic cells in order for efficient clearance, especially by macro-
phages [45,46]. Whether this function requires the C1 r and
Cis subunits is unclear, but deficiencies in a subunit of C1q
can increase susceptibility to autoimmunity [47]. The interac-
tion between C1q and its receptors on phagocytes is medi-
ated by calreticulin, a molecule that ultimately binds to the
receptor, CD91/LRP-1, expressed in conjunction with CD93.
CD93, in turn, is a cell surface molecule that is tethered to the
cytoskeleton via moesin [45]. Moesin translocates to the
nucleus during retinoic acid-induced differentiation, but this
latter process involving RAR/PPAR-y (retinoic acid receptor/
peroxisome proliferator-activated receptor-gamma) signaling
is hypothesized to be defective in this model [25]. Moesin, a
member of the FERM (4.1 protein, ezrin, radixin, moesin)
domain-containing family of proteins interacting with cytosolic
tails of trans-membrane proteins, can activate the IL-2/IL-2R
pathway [48], a system well known to be inefficient in main-
taining Treg cells in this model of autoimmunity. Expression pro-
files for these genes, presented in Figure 6b, indicate that the
transcript levels of these interactive factors are either down-
regulated or unchanged throughout the course of disease
development, thereby suggesting that this mechanism of
apoptotic cell clearance may not be functioning. Interestingly,
other components known to participate in clearance of apop-
totic cells (that is, the surfactant proteins SP-A, SP-B, SP-C,


and SP-D or the mannose-binding lectin MBL) exhibit no tem-
poral changes in gene expression levels.

Lastly, it is imperative to comment on the relevance of our
microarray data with respect to human SjS and whether differ-
entially expressed genes provide any clues to understanding
the immuno-pathophysiological processes underlying SjS-like
disease. As presented in Figure 5, our results demonstrated
that a large number of genes/factors that have been reported
to correlate with SjS or other rheumatic diseases in humans
are also differentially expressed in the salivary glands of
C57BL/6.NOD-Aec1Aec2 mice. Furthermore, the microarray
study of Hjelmervik and colleagues [49], to date the most
extensive microarray study of human SjS patients, shows a
remarkable overlap with the current mouse studies, not neces-
sarily between specific genes but within biological processes
and functions of differentially expressed genes. These include
upregulation of interferon-associated genes, antigen process-
ing and presentation, T- and B-cell differentiation and func-
tions, and apolipoproteins, plus downregulation of secretary
and cell proliferation. Specific genes include 116, Cd74, Call,
Bcl212, Cxc113, and Ccr7. Thus, given the extent of the over-
laps already seen, C57BL/6.NOD-Aec1Aec2 mice appear to
offer a unique opportunity to identify genetic factors regulating
processes leading to SjS.

In summary, our earlier microarray studies [9] with lacrimal
glands from C57BL/6.NOD-Aec1Aec2 mice and now the
present studies with salivary glands are permitting us to pro-
pose several new concepts pertaining to what molecular
events may lead to SjS and SjS-like disease. These include (a)
retarded maturation of myeloid cells, especially macrophages
and dendritic cells, possibly due to depressed response medi-
ated by low levels of retinoic acid receptors and PPAR-y; (b)
reduced efficacy of macrophages and dendritic cells in anti-


Figure 6


(a) Reduction of apoptotic cell
phagocytosis & IL2 signaling








inBR

f cap.^ ^ WS^~


(b) Gene expression profiles


0 4 8 12 16 20


-.-U9g
-40--Cal,
-4-MbI21
-Cd93
-Msn
SftpB, C, D


Age of mice (weeks)


Temporal changes in gene expressions in the salivary glands of C57BL/6.NOD-AeclAec2 mice for genes associated with clearance of apoptotic
cells. (a) Model of the proposed mechanism for the (lack of) clearance of apoptotic cell debris by phagocytic cells, resulting in reduced interleukin-2
(IL-2) production by phagocytic cells. (b) Expression of genes associated with apoptotic cell clearance. Expression profiles are presented for these
genes at 8, 12, 16, and 20 weeks of age relative to 4 weeks of age. Aec, autoimmunexocrinopathy; AP-1, activation protein-1; CR, complement
receptor; NFAT, nuclear factor of activated T cells; NF-KB, nuclear factor-kappa-B; NOD, non-obese diabetic.


Page 14 of 16
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Available online http://arthritis-research.com/content/11/2/R56


gen presentation, possibly due to an overexpression of cathe-
psin-S, leading to increased auto-antigen presentation by B
cells; (c) lack of regulation of the THI 7 effector cell population
by reduced activation of both Treg1 and TFoxp3 cells, possibly
due to low levels of IL-2; (d) depositions of fatty acids and lipo-
proteins in the lacrimal glands, due to changes in lipid recep-
tors and transporters; and (e) decreased efficacy in the
clearance of apoptotic cells/debris, due to reduced signal
transduction and activation of phagocytes via the C1 q/CD91/
CD93/moesin pathway. Functional studies should be able to
determine which of these biological processes is (are) critical
pathological entities for SjS.

Conclusions
We have used a genomic approach to identify genes that are
differentially expressed in the salivary glands during the devel-
opment and early-onset phases of SjS-like disease of C57BL/
6.NOD-AeclAec2 mice. This approach identified 480 genes
that could be grouped into one of four expression patterns dur-
ing development of disease. However, additional genes exhib-
ited marked changes in their expressions during the time frame
studied, based on simple pair-wise analyses. While a more
complete analysis of these data will require considerable time,
a number of expected and unexpected biological processes,
signaling pathways, and potential dysfunctions have been
identified. As might be predicted, virtually all biological proc-
esses during the early stages of disease (4 to 16 weeks of
age) relate to altered cell functions, with inflammation- and
autoimmunity-related processes appearing much later (1 6 to
20 weeks of age). Most importantly, these types of analyses
permit construction of hypothetical models for SjS which now
can be examined in greater detail in vivo, possibly confirming
the identification of specific SjS-susceptibility candidate
genes and their subsequent downstream molecular pathways.

Competing interests
The authors declare that they have no competing interests.

Authors' contributions
ABP designed the study and participated in the pair-wise anal-
yses and in the preparation of the manuscript. CQN prepared
the mRNA for microarray analysis and participated in the pair-
wise analyses and in the preparation of the manuscript. BHL
carried out the reverse transcriptase-polymerase chain reac-
tion validation studies and participated in the preparation of
the manuscript. JXS carried out the microarrays. AS and RAM
provided the initial analyses of microarray data. All authors
read and approved the final manuscript.


Additional files


The following Additional files are available online:

Additional file 1
Verification of microarray data by RT-PCR. Four genes,
Ctsb, Apoe, Aktl and Fdftl, identified as displaying
different levels of transcripts in the microarrays of salivary
glands over time were selected for RT-PCR analyses. A.
PCR band intensities visualized with ethidium bromide
staining. B. Plot of PCR band intensities. C.
Corresponding plot of transcripts as determined by
microarray. G3pdh was used to control for fidelity of the
RT-PCRs. As the band intensities of G3pdh remained
constant over all the time points, the relative band
intensities are not shown here.
See http://www.biomedcentral.com/content/
supplementary/ar2676-S1 .ppt




Acknowledgements
We wish to thank Janet Cornelius for overseeing the breeding of the
mice used in this study. This study was supported in part by Public
Health Service (PHS) grant DE014344 from the National Institutes of
Health (to ABP) and by the University of Florida's Center for Orphaned
Autoimmune Disorders. CON was supported by post-doctoral fellow-
ships from PHS grants T32 DE07200 and T32 AR007603.

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