Genome-wide study identifies the regulatory gene networks and signaling pathways from chondrocyte...

Genome-wide study identifies the regulatory gene networksand signaling pathways from chondrocyte and peripheralblood monocyte of Kashin–Beck disease

Sen Wang1, Xiong Guo1*, Weizhuo Wang2 and Shuang Wang3

1Faculty of Public Health, Medicine College of Xi’an Jiaotong University, Key Laboratory of Environment and Genes Related to

Diseases, Ministry of Education, Key Laboratory of Trace Elements and Endemic Diseases, Ministry of Health, Xi’an,

Shaanxi 710061, China2Department of Orthopedics Surgery, The Second Affiliated Hospital, Medicine College of Xi’an Jiaotong University, Xi’an,

Shaanxi 710004, China3Department of Orthodontics, Stomatological Affiliated Hospital, Medicine College of Xi’an Jiaotong University, Xi’an,

Shaanxi 710004, China

This investigation was designed to unravel gene networks in Kashin–Beck disease (KBD) and

better identify target genes of KBD for gene therapy development. RNA was isolated sepa-

rately from cartilage and peripheral blood samples of patients with KBD and healthy controls.

Agilent 44K human whole-genome oligonucleotide microarrays were used to detect differen-

tially expressed genes. Three significant canonical pathways and nine chondrocyte networks

from chondrocytic gene expression profiles were screened using ingenuity pathway analysis

(IPA), but only one network and no canonical pathways from peripheral blood monocytic

gene profile were identified. Bak1, APAF-1, CASP6, IGFBP2, Col5a2 and TGFBI extracted

from significant genes that involved in chondrocytic canonical pathways and networks may

have closer relationship with the etiopathogenesis of KBD. Those genes may be potential tar-

gets for gene diagnosis and treatment. Six physiological functions were predominant and

unique to the chondrocytic genes, whereas two were unique to peripheral blood monocytic

genes. The identified genes may represent a source of potentially novel molecular targets,

which may provide a better understanding of the molecular details in KBD pathogenesis and

also provide useful pathways and network maps for the future research in osteochondrosis.

Introduction

Kashin–Beck disease (KBD) is characterized bychondrocytic necrosis and apoptosis, cartilage degen-eration and matrix degradation (Duan et al. 2010).KBD is endemic in a crescent-shaped area fromsouth-eastern Siberia extending to northeast andsouthwest China, which affects approximately690 000 people and poses a high risk to 10.584 mil-lion others residing in 366 counties within 14 prov-inces or autonomous regions of China, according tothe 2010 Health Statistical Yearbook of China.

Kashin–Beck disease is a complex disease duemainly to interactions between environmental factorsand environmental response genes. Although KBDaetiology and pathogenesis remain elusive, risk factorsfor developing KBD are dependent on multiple envi-ronmental and genic risk factors (Suetens et al. 2001).Selenium and iodine deficiencies have been proposedas KBD risk factors (Moreno-Reyes et al. 1998;Thomson 2004), as well as mycotoxins from contam-inated storage grains (Chasseur et al. 2001) and drink-ing water contamination (Chasseur et al. 2001; Sudre& Mathieu 2001). Environmental factors contained inwater and food can be absorbed into the blood,which may affect the genic regulation of bloodmononuclear lymphocytic differentiation and prolifer-ation. Effects on cartilage and chondrocytes may

Communicated by: Hiroshi Handa*Correspondence: [email protected]

DOI: 10.1111/j.1365-2443.2012.01620.x

© 2012 The Authors

Journal compilation © 2012 by the Molecular Biology Society of Japan/Blackwell Publishing Ltd.

Genes to Cells (2012) 1

occur through the circulation of blood or synovialfluid, which includes differential chondrocytic geneexpression. Although previous studies have confirmedthat the differential genic expression of chondrocytesin patients with KBD differs from those of healthysubjects and patients with osteoarthrosis, little isknown concerning the differentially expressed genesbetween chondrocytes and peripheral blood mono-cytes.

Previous single gene expression analyses have iden-tified important target genes contributing to KBDpathogenesis. Differentially expressed genes betweenKBD and normal chondrocytes have been screenedusing microarrays (Wang et al. 2009). Further genicscreening has been investigated through their biologi-cal functions using gene set enrichment analysis(GSEA) and Bayesian analysis of variance for micro-arrays (BAM) (Zhang et al. 2011). However, networkanalyses of multiple genes could be more effective inshowing genic aetiological influences of complex dis-eases. Comparisons between KBD chondrocytic andperipheral blood monocytic gene networks have notyet been investigated. Peripheral blood monocytegene expression profiles are easily obtained and couldserve as an early diagnosis indicator for KBD. KBD isa specific type of osteochondrosis, and gene expres-sion profiles of chondrocytes are more accurate, asthe differentially expressed genes within genome-wide gene profiles both from chondrocytes andperipheral blood monocytes can provide the sub-bio-logical information from blood circulation to dam-aged cartilage in patients with KBD. In this article,we presented significant canonical pathways and net-works from chondrocytes and peripheral blood geneexpression profiles through ingenuity pathway analysis(IPA, Ingenuity Systems, Inc., Redwood City, CA,USA).

Results

Microarray analysis

Chondrocytic gene expression profiles of patients withKBD and healthy controls were analyzed using a high-throughput microarray containing 10 818 oligonu-cleotide-based probe sets. Cutoff values of >2.0 and<0.5 were used. The analysis showed 922 up-regulatedgenes and 54 down-regulated genes. Gene expressionprofiles of peripheral blood monocytes in patients withKBD and controls were analyzed using the same high-throughput microarray, but contained 20 381 oligo-nucleotide-based probe sets. Cutoff values of >2.0 and

<0.5 were used. The analysis showed 120 up-regulatedgenes and five down-regulated genes.

Quantitative real-time RT-PCR (qRT-PCR)

The chondrocytic analysis showed that vascular endo-thelial growth factor (VEGF), 3′-phosphoadenosine5′-phosphosulfate synthase 2 (PAPSS2), caspase-8-associated protein 2(CASP8AP2) and thymosin beta15a (TMSL8) were up-regulated with similar tran-scriptional profiles showed in the microarray data.Periostin (POSTN), transforming acidic coiled-coilprotein 10 (TACC1), carbonyl reductase 3 (CBR3)and Bcl-2-modifying factor (BMF) were down-regu-lated with similar transcriptional profiles as shown inthe microarray data. For peripheral blood monocytes,results showed that bone morphogenetic proteinreceptor type IA (BMPR1A), dual oxidase 1(DUOX1), ADAM metallopeptidase domain 28(ADAM28), immunoglobulin lambda-like polypep-tide 1 (IGLL1) and chemokine (C-C motif) receptor4 (CCR4) were up-regulated with a similar transcrip-tional profile to that of the microarray data (Fig. 1).

Significantly dysregulated genes from chondrocytesand peripheral blood monocytes identified throughmicroarray analyses have been further classified byfunction. Sixteen main functions were selected bytheir constituent ratios and are listed in Table 1.Up-regulated chondrocytic genes, which had higherconstituent ratios than peripheral blood monocytegenes, were classed into the following groups:transcription-related, signal transduction-related, cellcycle-related, cell factor, extracellular matrix-related,cytoskeleton and movement, receptor, growth factor-related, ion channels and transport protein, apoptosis-related, protein synthesis and modification, metabolism,leukocyte antigens, oncogene-related, and DNAsynthesis and repair. Down-regulated chondrocyticgenes, which had higher constituent ratios thanperipheral blood monocyte genes, mainly belonged tothe following groups: transcription-related, signaltransduction-related, cell cycle-related, cell factor,extracellular matrix-related, growth factor-related,development-related, apoptosis-related, protein syn-thesis and modification, metabolism, leukocyte anti-gens, oncogene-related, and DNA synthesis andrepair.

IPA of chondrocyte gene profiles

Ingenuity pathway analysis of gene expression profilesshowed several different associated network functions

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S Wang et al.

2

between patients with KBD and healthy controls.Chondrocytic gene data represent the logarithm of P-values calculated by the Fisher’s exact test, with athreshold for statistical significance of 0.05. Canonicalpathways with P-values > 0.05 were defined as

significant. Data for the 24 most statistically signifi-cant pathways were presented (Fig. 2).

Three significant canonical pathways (Figs 3–5)were closely associated with cartilage and chondro-cytic functions. The significant genes included

Table 1 List of main functional categories of up-regulated and down-regulated genes of chondrocytes and peripheral blood

monocytes

Function category

Up-regulation Down-regulation

Chondrocytes

(n)† %‡Peripheral blood

monocytes (n) %

Chondrocytes

(n) %

Peripheral blood

monocytes (n) %

Transcription related 95 10.3 7 5.8 8 14.8 0 0

Signal transduction

related

39 4.2 0 0 2 3.7 0 0

Cell cycle related 20 2.2 0 0 18 33.3 0 0

Cell factor 38 4.1 4 3.3 4 7.4 0 0

Extracellular matrix 26 2.8 2 1.7 1 1.85 0 0

Cytoskeleton and

movement

42 4.6 1 0.8 1 1.85 1 20

Receptor 36 3.9 1 0.8 5 9.26 1 20

Growth factor related 6 2.8 1 0.8 1 1.85 0 0

Ion channels and

transport protein

28 3.0 1 0.8 3 5.56 1 20

Development related 8 2.0 4 3.3 3 5.56 0 0

Apoptosis related 35 3.8 0 0 2 3.7 0 0

Protein synthesis and

modified

8 5.2 2 1.7 7 13.0 0 0

Metabolism 164 17.8 10 8.3 7 13.0 0 0

Leukocyte antigens 4 0.4 0 0 10 18.5 0 0

Oncogene related 50 5.4 4 3.3 3 5.6 0 0

DNA synthesis and

repair

2 2.4 0 0 7 13.0 0 0

†N is the number of genes.

‡: % is constituent ratio.

20(A) (B)20

15

10

5

0

15 Microarray mean

Real-time PCR mean

# #

#

∗ ∗ ∗

∗

∗ ∗∗

∗∗

∗

10

5

0

–5

–10

Rat

io o

f exp

ress

ion

leve

l

Rat

io o

f exp

ress

ion

leve

l

–15

POSTN

TACC1

CBR3BMF

VEGF

PAPSS2

CASP8AP2

TMSL8

BMPR

1A

DUOX1

ADAM

28

IGLL

1

CCR4

Microarray mean

Real-time PCR mean

Figure 1 Bars indicate the expression values of selected genes measured by microarray (black or striped bars) and qRT-PCR

(white bars) analyses. Values represent the mean ± SD. *Indicates P < 0.05, #indicates P < 0.01, calculated by the paired t-test.

(A) Chondrocytes, (B) peripheral blood monocytes.

© 2012 The Authors


Genes to Cells (2012)

Gene networks of Kashin–Beck disease

3

apoptotic peptidase activating factor 1 (Apaf-1) andapoptosis-related cysteine peptidase (caspase-6) in thedeath receptor signaling pathway, Bcl-2-antagonist/killer 1 (BAK1), Apaf-1 and caspase-6 in the apopto-sis signaling pathway, and connective tissue growthfactor (CTGF) and insulin-like growth factor bindingprotein 2, 36 kDa (IGFBP2), in the IGF-1 signalingpathway.

Nine chondrocytic networks were derived fromIPA and detailed in Table 2. Chondrocyte network 2was classified as: cellular movement, skeletal and mus-cular system development and function, hematologicalsystem development and functional pathway, whereasnetwork 4 classified was as: cellular assembly andorganization, cellular movement, skeletal and muscu-lar system development and functional pathway. Thetwo networks were most closely associated with thebiological functions of cartilage and chondrocytes(Fig. 6A,C).

IPA of peripheral blood monocytes genic profile

There was no canonical pathway indicated in theperipheral blood gene profile. Only one networkclassified as cellular assembly and organization, DNAreplication, recombination and repair, and geneexpression (Fig. 6B and Table 3) was identified.

Comparing IPA of chondrocytes and peripheral

blood monocytes

Eleven significant genes were identified from chon-drocyte network 2 and one gene from network 4(Fig. 6A,C). Only one significant gene was identifiedfrom the peripheral blood monocyte network(Fig. 6B). ACTG was used as a housekeeping gene.The remaining 12 genes were classified by their his-tological origin (Table 4).

We carried out GO analysis using IPA software.Ten common functions were selected from chondro-cytic and peripheral blood monocytic genes. Func-tions associated with cell death, cell-to-cell signalingand interaction, cellular development, cellular move-ment, cellular morphology and tissue developmentwere predominant and unique in chondrocyticgenes. Functions associated with skeletal and muscu-lar system development and function, and skeletaland muscular disorders were unique but notpredominant, whereas pathways involved in proteinsynthesis and RNA post-transcriptional modificationwere unique in peripheral blood monocytic genes(Fig. 7).F

igure

2Differentially

expressed

chondrocyte

genes

associated

withacanonicalpathway

usingIPA.Dataforthe24moststatisticallysignificantpathwayswerepresented.

Thelefty-axiscorrespondsto

dataforthebarsthat

wereusingtheFisher’sexacttest.P-values

weresetat

0.05.Therighty-axiscorrespondsto

datain

thelinegraphs.

Thesedataaretheratioofthenumber

ofmoleculesin

agiven

pathway

that

meetthetw

ofold

changecutoffcriteria

ineither

directiondivided

bythetotalnumber

of

moleculesthat

makeupthat

pathway.IPA,ingenuitypathway

analysis.



S Wang et al.

4

Discussion

Among the complicated canonical pathways and net-works described herein, only signaling pathways andnetworks significantly associated with osteochondrosiswill be discussed. Three significant canonical path-ways from the chondrocytic gene profile weredivided into two categories based on the KyotoEncyclopedia of Genes and Genomes (KEGG) andBioCarta databases, but not in peripheral bloodmonocytes.

Two canonical pathways in chondrocytes were

related to cell apoptosis

Death receptor signaling pathway

Apaf-1 and caspase-6 were identified as significantgenes in this pathway. Cytochrome c initiates theassembly of Apaf-1 and pro-caspase-9 into a holoen-zyme complex called the apoptosome, which in turnactivates the initiator caspase-9 (Herr & Debatin2001). Initially activated caspase-9 (mitochondrialpathway) activates downstream caspases, includingcaspase-3, which results in DNA fragmentation and

apoptosis (Dirsch et al. 2003). In vitro studies havealso shown that pro-caspase-3 can be activated bycaspase-6 (Degterev et al. 2003), which functions as adownstream effector in the cell death program (Ash-kenazi & Dixit 1998). The loss of articular cartilagein patients with KBD is a result of a significantdecrease in chondrocyte number owing to increasedcell death (Pasteels et al. 2001; Guo et al. 2006).

Apoptosis signaling pathway

Bak1, caspase-6 and APAF-1 were identified as sig-nificant genes in this pathway. Bak1, which belongsto the Bcl-2 protein family, is a key protein that reg-ulates mitochondrial membrane permeabilization(Gogada et al. 2011). The levels and activation ofintercellular Bak are controlled by a myriad of relatedBcl-2 proteins within the apoptosis pathway (Under-brink et al. 2008). Bak can oligomerize to form poreson the outer mitochondrial membrane resulting inmitochondrial membrane permeabilization (Chenet al. 2007). The over-expression of Bak lowers thethreshold for DNA damage–induced apoptosis (Rade-tzki et al. 2002). Increased Bak activation can lead tomitochondrial depolarization and cytochrome c

Figure 3 Canonical pathway analysis of chondrocyte genes in death receptor pathway. Red represents up-regulated genes and

white symbols depict neighboring genes.

© 2012 The Authors




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release. After cytochrome c is released into the cytosolfrom the mitochondria, it binds to Apaf1 and ATP,which then activates caspase-9 (Kuwano et al. 2005).APAF-1 and caspase-9 were identified as factors acti-vating caspase-3, an inhibitor of caspase-6 and cas-pase-7 located downstream of caspase-3 (Kumamoto& Ooya 2005). The percentages of positive apoptoticchondrocytes from the KBD patient group were veri-fied by flow cytometry to exhibit higher levels thanthat of healthy controls in a previous study (Liu et al.2010).

One canonical pathway was related to cell

signaling

IGF-1 signaling pathway

Connective tissue growth factor and IGFBP-2 weresignificant genes in this pathway. Chondrocyte prolif-eration, the expression of type II collagen, and aggre-can production can be stimulated by CTGF amongother factors (Leask & Abraham 2006; Nishida et al.2007). CTGF over-expression in chondrocytes under

Figure 4 Canonical pathway analysis of chondrocyte genes in apoptosis signaling pathway. Red represents up-regulated genes and




S Wang et al.

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the control of the type XI collagen promoter has sug-gested that excess CTGF can lead to osteopenia(Nakanishi et al. 2001). The accumulation of CTGFadjacent to the cell surface could enhance the effectof CTGF on chondrocytes. In support of thishypothesis, there is a report showing that aggrecan-deficient mice develop short limbs and dwarfism(LaVallie et al. 1993; Watanabe et al. 1997; Gleghornet al. 2005). CTGF expression was also involved inthe development of fibrous tissue over damagedosteoarthritic (OA) cartilage (Kumar et al. 2001; Om-oto et al. 2004). Cartilage necrosis occurred mainly inthe hypertrophic chondrocytes in patients with KBD(Liang et al. 1998). CTGF may play a role in hyper-trophy of chondrocytic in KBD.

IGFBP-2 can bind with various glycosaminogly-cans found in cartilage as well as with the keyfunctional proteoglycan (Le et al. 2001). It hasbeen indicated that IGFBP2 inhibits IGF-mediatedproliferation and matrix synthesis in growth platechondrocytes and osteoblasts in vitro (De Los & Hill2000; Firth & Baxter 2002; Kiepe et al. 2002).IGFBP-2 may be involved in abnormal proliferationand matrix synthesis in chondrocytes of patients with

KBD, but this hypothesis will need to be investigatedin future studies.

Although we have not yet identified a peripheralblood monocytic canonical pathway, the significantgenes in the chondrocytic canonical pathways men-tioned previously are involved in the following net-works. CASP6 and IGFBP2 are involved in network2, which has been classified under cellular movement,skeletal and muscular system development and func-tion, and hematological system development andfunction; BAK1 and CTGF1 are involved in network1, which is classified under cardiovascular systemdevelopment and function, organismal development,cellular growth and proliferation; and APAF1 isinvolved in network 3, which is classified under tis-sue development, cancer, and reproductive systemdevelopment and function.

Chondrocyte networks 2 and 4 were most closelyassociated with biological functions of cartilage andchondrocytes, so the significant genes involved inthese two networks will be the key points of discus-sion. The 11 genes (Table 4) in chondrocytenetworks 2 or 4, but not in peripheral blood mono-cyte networks, were specific to KBD.

Figure 5 Canonical pathway analysis of chondrocyte genes in IGF-1 signaling pathway. Red represents up-regulated genes and


© 2012 The Authors




7

Ten genes were in network 2. CASP6 and IGFBP2have been described in the canonical pathways before.Chromosome 5 open reading frame 13 (C5orf13) caninhibit collagen expression and may be involved inreducing the amount of scarring produced duringwound repair (Pan et al. 2002). It has also been associ-ated with aversive behavior induced by painful stimuli(Sun et al. 2008). Fibulins, and particularly the splicevariants of fibulin-1 (FBLN1), are important adhesion

modulatory proteins that can affect cell–matrix interac-tions and tissue remodeling (Li et al. 2010), which hasbeen implicated in limb malformations and syndactylytype II (Malik et al. 2006). It was the solitary down-regulated gene in network 2. The developmental pat-tern of collagen type V alpha 2 (Col5a2) expressionclosely resembles that of type I collagen, thus furthersubstantiating the notion that these macromoleculescooperate in the formation of fibrillar networks in

Table 2 Ingenuity pathway analysis of chondrocytic gene networks

ID Molecules in network Score†Focus

molecules Top functions

1 ACAN, BAK1↑‡, BMI1, BTG1↑, COL11A1↑,CTGF↑, E2F4, ENPP2↑, Eotaxin, ETS1,FASN, FGF7↑, FN1↑, FOXO4, HDAC2,

ID4↑, IL13, ITGA3, JAG1↑, LOXL2↑, LRP,

MAP2K1, Nfat (family), Pka, PPAP2B, PTP4A3,

RPS6KB1, SMARCA4, SMURF2, TGFA↑,TGFB2, TMSB15A↑, TP53, VIM, YES1

20 12 Cardiovascular system development and function,

organismal development, cellular growth and

proliferation

2 ACTG1, Alp, C5orf13↑, CASP6↑, COL5A1,

COL5A2↑, Cpla2, Eotaxin, FBLN1↓§, HMGB1,

IGFBP2↑, IL1B, ITGA4, lymphotoxin-alpha1-

beta2, MMP3, MUC2, MUC5AC/MUC5B,

NEDD9, PPARD, PRKCZ, PRSS23↑, RAC1,

RETN, SAA, SATB1, SERPINE1, STMN2↑,TGFB1, TGFBI↑, TIMP1, TNC, TNF,

TNFAIP6↑, TP73, VCAM1↑

18 11 Cellular movement, skeletal and muscular system

development and function, hematological system

development and function

3 APAF1↑, BCL2L1, CASP9, CFLAR, COL18A1,

DDX3Y↑, EREG, FSH, hCG, HIF1A↑, HK2,

HSD17B1, Hsp70, Hsp90, ILK, INHA, INHBA,

INHBB↑, ITGA3, LDLR, LEP, Lh, MAP2K1,

mir-21, MMP2, OSM, PTGS2, SMAD3,

SMAD7, TFRC, TNFRSF11B↑, TPM1↑, VCL,Vegf, VEGFA

8 6 Tissue development, cancer, reproductive system


4 CALD1↑, CHI3L1 2 1 Cellular assembly and organization, cellular

movement, skeletal and muscular system


5 SCYL1, XPOT↑ 2 1 Molecular transport, RNA trafficking, cellular

assembly and organization

6 HAPLN1↑, ZNF217 2 1 Cellular development, respiratory system

ellular assembly and organization, cellular growth

and proliferation, Tissue morphology

8 LMO7, YWHAG, ZNF143 2 1 Gene expression, endocrine system disorders,

gastrointestinal disease

9 DDX39A, ERH↑, SARNP, THOC2 2 1 Molecular transport, RNA trafficking, DNA

replication, recombination and repair

†Scores were based on the number of focus genes and network size.

‡,§: ↑ and ↓ indicate significantly up-regulated and down-regulated genes, respectively.

CALD1, caldesmon 1; CTGF, connective tissue growth factor; FBLN1, fibulin-1; MMP, matrix MP; TGFBI, transforming

growth factor-beta-induced; TNF-alpha-induced protein 6; TNFAIP6, TNF-alpha-induced protein 6; VCAM1, vascular cell

adhesion molecule 1; VEGF, vascular endothelial growth factor.



S Wang et al.

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abnormal cartilaginous matrices in KBD (Andrikopou-los et al. 1992). Protease, serine, 23 (PRSS23) encodesa member of the trypsin family of serine proteases.Mouse studies found a decrease in PRSS23 mRNAlevels after induced ovulation. This gene seems to behighly conserved in vertebrates and may be an impor-tant ovarian protease (Miyakoshi et al. 2006). Stath-min-like 2 (STMN2) encodes a member of thestathmin family of phosphoproteins. Stathmin proteinsfunction in microtubule dynamics and signal trans-duction (Alves et al. 2010). STMN2 mRNA levelsincreased during osteogenesis of bone marrow mesen-chymal stromal (hBMS) cells (Chiellini et al. 2008).TNF-alpha-induced protein 6 (TNFAIP6), which isexpressed excessively in cartilage and synovium inrheumatoid arthritis and OA, codes a protein that

appears to have a suppressive effect on matrix MP(MMP) activation in arthritic processes (Bardos et al.2001) and plays a crucial role in extracellular matrixformation, inflammatory cell migration, cell prolifera-tion and developmental processes (Yoshioka et al.2000; Carrette et al. 2001). Transforming growth fac-tor-beta-induced (TGFBI) encodes a collagen-associ-ated protein that binds to type I, II and IV collagensand plays an important role in cell–collagen interac-tions in various tissues including developing cartilage.This gene was expressed in chondrocytes throughoutall stages, although the expression level was highestduring the prehypertrophic stage. The protein isinduced by TGFBI and acts to inhibit cell adhesion(Hashimoto et al. 1997). It can be isolated from carti-lage and was found to inhibit mineralization of

Figure 6 Top interaction network. (A) Chondrocyte gene network 2 was classified as: cellular movement, skeletal and muscu-

lar system development and function, hematological system development and functional pathway. (B) The peripheral blood mono-

cyte gene network was classified as cellular assembly and organization, DNA replication, recombination and repair, and gene

expression. (C) Chondrocyte gene network 4 was classified as: cellular assembly and organization, cellular movement, skeletal and

muscular system development and functional pathway. Red represents up-regulated genes, green represents down-regulated genes

and white symbols depict neighboring genes.

© 2012 The Authors




9

hypertrophic chondrocytes (Ohno et al. 2002). Vas-cular cell adhesion molecule 1 (VCAM1) may act onosteoclast lineage cells and osteoclasts, but this rela-tionship remains unclear (Hopwood et al. 2007).

Table 3 Ingenuity pathway analysis of the peripheral blood

monocytic gene network

Molecules in

network Score†Focus

molecules Top functions

BRCA1, CHD4,

Ferritin, FN3K,

GATA1, HBB↓‡,HIST2H3C

(includes others),

HLTF,

HNRNPC, IL8,

MTA2, NFE2,

ORC2, RECQL,

RECQL4, RNA

polymerase II,

SATB1,

SMARCA4, SP1

3 1 Cellular assembly

and organization,

DNA

replication,

recombination

and repair, gene

expression

†Score was based on the number of focus genes and network

size.

‡: ↓ indicates down-regulation of significant genes.

HBB, hemoglobin beta; SMARCA4, SWI/SNF-related,

matrix-associated, actin-dependent regulator of chromatin

subfamily a member 4.

Table 4 Significant genes identified from chondrocytic and

peripheral blood monocytic networks

Gene name In chondrocytes

In peripheral

blood monocytes

CALD1 + �C5orf13 + �FBLN1 + �PRSS23 + �STMN2 + �TGFBI + �TNFAIP6 + �VCAM1 + �CASP6 + �IGFBP2 + �COL5A2 + �HBB - +

CALD1, caldesmon 1; FBLN1, fibulin-1; HBB, Hemoglobin

beta; TGFBI, transforming growth factor-beta-induced;

TNFAIP6, TNF-alpha-induced protein 6; VCAM1, vascular

cell adhesion molecule 1.

Figure

7Comparisonofcommonanddistinct

geneexpressionprofilesacrossthedifferentially

expressed

genes

ofchondrocytic(skyblue)

andperipheral

bloodmono-

cyticgene(darkblue)

profilesofbiologicalfunctions.Topfunctionsthat

meetaP-valuecutoffof0.05weredisplayed.



S Wang et al.

10

One gene was in network 4: caldesmon 1(CALD1), which plays a pivotal role in regulating cellmigration via the reorganization of the actin cytoskel-eton (Mayanagi et al. 2008), but it was not found inany significant canonical pathway in this study.

Hemoglobin beta (HBB), which was in peripheralblood monocyte, but not in chondrocytes (Table 4),is a hematopoietic-related gene and may be nonspe-cific to KBD.

SWI/SNF-related, matrix-associated, actin-depen-dent regulator of chromatin subfamily a member 4(SMARCA4) is the only common gene in the chondr-ocytic and peripheral blood monocytic networks. It isa transcription-related gene, but its expression ratio didnot meet the IPA cutoff (log2 ratio 2.5), and was notdeemed as a significant network gene. Expressing inboth chondrocytes and peripheral blood monocytes,SMARCA4 is nonspecific to KBD.

Three significant canonical pathways and ninechondrocyte networks from chondrocytic gene expres-sion profiles were identified through IPA, but only onenetwork and no canonical pathways were detectedfrom peripheral blood gene profiles. Bak1, APAF-1,CASP-6, CTGF and IGFBP-2 were significant genescontained in chondrocytic canonical pathways.CALD1, C5orf13, CASP6, COL5A2, FBLN1, IG-FBP2, PRSS23, TGFBI, STMN2, TNFAIP6 andVCAM1 were the significant genes involved in KBDchondrocytic networks, but not in peripheral bloodmonocytic networks; those 11 genes may be specific toKBD and could be potential targets for gene diagnosisand treatment. Bak1, APAF-1, CASP6, IGFBP2,Col5a2 and TGFBI may have closer relations withKBD pathogenesis through extrapolating from forego-ing published reports in paragraphs of discussion andshould be focused on in future studies.

Six functions were predominant and unique inchondrocyte genes, and two functions were unique inperipheral blood monocyte genes. Furthermore, theidentified genes might represent a source of poten-tially novel molecular targets, which may provide abetter understanding of the molecular details in KBDpathogenesis and also provide useful pathways andnetwork maps for future research in osteochondrosis.

Experimental procedures

Cartilage sample collection

Samples of articular cartilage collected from nine patients with

KBD and nine healthy controls were matched by age and

gender. Patients with KBD (three women and six men,

aged 42–69 years) from the KBD-affected areas of Linyou and

Yongshou in the Shaanxi Province of China were diagnosed

as grade II and grade III stages based on diagnostic criteria of

KBD in China (WS/T 207-2010) and underwent free total

knee replacement surgery. Diagnosis criteria: exposure at

endemic area more than 6 months. Diagnostic criteria of hand

X-ray signs were according to the ‘2010 WS/T Diagnosis of

Kashin-Beck Disease of China’. Patients with osteoarthritis,

rheumatoid arthritis, rickets and cretinism were excluded. The

disease is classified as follows: early stage: flexion of distal joint

part of fingers, bow-like fingers and pain in knee and angle

joints; first degree:enlargement and crepitus of small joints;

second degree: short fingers, enlargement and dysfunction of

medium-sized joints; third degree: enlargement and dysfunc-

tion of large joints (stunted growth). The cartilage samples

from normal controls (three women and six men, aged 34–60 years) were collected from the knees of recently deceased

organ donors within 8 h of dying through traffic accidents or

by other means from the KBD area. After washed by physio-

logical saline, cartilage samples were stored in liquid nitrogen

at �196 °C before RNA extraction.

Peripheral blood sample collection

Samples of human peripheral blood collected from 20 patients

with KBD and 12 normal controls were matched by age and

gender. Patients with KBD (11 women and nine men, aged

38–67 years) from the KBD-affected areas of Linyou and

Yongshou in the Shaanxi Province of China were diagnosed

as grade II and grade III based on diagnostic criteria of KBD

in China (WS/T 207-2010). The samples of normal controls

(nine women and three men, aged 27–68 years) were col-

lected from healthy donors from the KBD area.

All blood specimens (2.5 mL) were collected in PAX-

geneTM Blood RNA tubes (PreAnalytiX GmbH, Hombrechti-

kon, Switzerland) containing lysis buffer and RNA stabilizing

solution. Each sample was incubated at room temperature for

4 h for RNA stabilization and then stored at �80 °C.All cartilage and peripheral blood samples from healthy

controls were screened and excluded from the study if genetic

bone or cartilage diseases, osteoarthritis or rheumatoid arthritis

was indicated. Informed consent was obtained from each sub-

ject involved in the investigation. This investigation was

approved by the Human Ethics Committee of Xi’an Jiaotong

University, Xi’an, Shaanxi, China.

Total RNA extraction and microarray analysis

Cartilage samples from the KBD or control group were divided

into four pairs for microarray analysis. Cartilage samples were

removed from liquid nitrogen and ground in liquid nitrogen

after being weighed. Trizol reagent (1 mL; Invitrogen, Carls-

bad, CA, USA) was added to per 100 mg cartilage tissue. Then,

total RNA was extracted using the RNeasy Mini Kit (Qiagen,

Hilden, Germany). Peripheral blood samples from the KBD or

© 2012 The Authors




11

control group were also divided into four pairs. Peripheral

blood samples were removed from �80 °C and thawed at room

temperature for 2 h before RNA isolation. Total RNA was

extracted with the Paxgene Blood RNA Kit (PreAnalytix;

Qiagen) following the manufacturer’s instructions.

RNA integrity was validated using 1% agarose gel electro-

phoresis and stained with ethidium bromide. Extracted RNA

was stored at �80 °C until cDNA synthesis. We labeled and

converted total RNA samples into cDNA with the Amino Al-

lyl MessageAmp aRNA Kit (Ambion, Austin, TX, USA)

using 500 ng of total RNA. We used the Agilent 44K human

whole-genome oligonucleotide microarray (Agilent Technolo-

gies, Santa Clara, CA, USA), and transcription was carried out

using an Agilent Low RNA Input Fluorescent Linear Amplifi-

cation Kit (Agilent Technologies) in the presence of Cy3-

CTP and Cy5-CTP. The fluorescent-labeled cRNA was used

for oligo microarray hybridization. Differentially expressed

genes were selected based on fold change. The data were

recorded and transferred to text files using FEATURE EXTRAC-

TION 9.3 Software (Agilent Technologies) and SPOTFIRE 8.0

(Spotfire Inc., Cambridge, MA, USA). Fold change >2 or

<0.5 was used for analysis.

qRT-PCR

To validate the microarray results from different experimental

groups, eight significant differentially expressed chondrocytic

genes and five significant differentially expressed peripheral

blood monocytic genes were separately selected as target genes

for qRT-PCR. Down-regulated genes in peripheral blood

samples were too few to be analyzed, so we only selected

up-regulated genes for the qRT-PCR analysis. Total RNA was

isolated in the same way as for the oligonucleotide array analy-

sis. We used Superscript II reverse transcriptase (Invitrogen)

and random primers to convert isolated total RNA into cDNA.

An ABI7500 Real-Time RT-PCR System (Applied Biosys-

tems, Foster City, CA, USA) was used for qRT-PCR analysis

using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as

an endogenous control. Specific primers and probes

[NM_001003940 (BMF), NM_001236 (CBR3), NM_006475

(POSTN), NM_006283 (TACC1), NM_003376 (VEGF),

NM_001015880 (PAPSS2), NM_012115 (CASP8AP2) and

NM_021992 (TMSL8)] were chosen for chondrocytes. Specific

primers and probes [NM_004329 (BMPR1A), NM_017434

(DUOX1), NM_021777 (ADAM28), NM_020070 (IGLL1)

and NM_005508 (CCR4)] were chosen for peripheral blood

monocytes. qRT-PCR data were log-transformed to ensure

normal distribution and analyzed using paired t-tests.

IPA

Gene symbols of chondrocytes and peripheral blood mono-

cytes were imported into IPA (version 8.5; Ingenuity Sys-

tems Inc.) web-based software. IPA is a repository of

biological interactions and functional annotations from many

relations between proteins, genes, complexes, cells, tissues,

metabolites, drugs and diseases. IPA selected sources and

databases including major NCBI databases (EntrezGene, Ref-

Seq, OMIM disease asso ciations), miRNA–mRNA target

databases, GWAS databases, KEGG and so on. IPA is easy to

operate and offers high-quality diagrams of pathways and net-

works that contain much information using a visual interface.

IPA is intuitive and easy to use, offering high-quality dia-

grams of pathway and network that contain much informa-

tion with a visual interface. The trial version of IPA software

was used. Genes from the dataset that met the log ratio cut-

off of 2.5 were considered for analysis. Networks were

graphically displayed that described the relationships between

a subset of genes and their neighboring genes. To find the

most relevant canonical pathways, we chose pathways that

were statistically significant with a P-value < 0.05 using the

Fisher’s exact test. Networks and canonical pathways of

chondrocytes and peripheral blood monocytes were generated

and compared by IPA.

Acknowledgements

This study was supported by the National Natural Scientific

Foundation of China (30972556); the Specialized Research

Fund for the Doctoral Program of Higher Education of

China (20090201110049); and “13115” Major Program on

Technology Science Innovation Project of Shaanxi Province

(2009ZDKG-79).

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Received: 19 February 2012

Accepted: 11 April 2012



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