Identification of candidate genes in scleroderma-related pulmonary arterial hypertension

Identification of Candidate Genes in Scleroderma-RelatedPulmonary Arterial Hypertension

DN Grigoryev1, SC Mathai2, MR Fisher2, RE Girgis2, AL Zaiman2, T Housten-Harris2, CCheadle1, L Gao1, LK Hummers3, HC Champion4, JGN Garcia5, FM Wigley3, RM Tuder6, KCBarnes1, and PM Hassoun2,§

1Division of Allergy and Clinical Immunology, Johns Hopkins University, Baltimore, Maryland 2Division ofPulmonary/Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland 3Division ofRheumatology, Johns Hopkins University, Baltimore, Maryland 4Division of Cardiology, Johns HopkinsUniversity, Baltimore, Maryland 5Department of Medicine, University of Chicago Pritzker School ofMedicine, Chicago, Illinois 6Department of Pathology, Johns Hopkins University, Baltimore, Maryland

AbstractWe hypothesize that pulmonary arterial hypertension (PAH)-associated genes identified byexpression profiling of peripheral blood mononuclear cells (PBMCs) from patients with idiopathicpulmonary arterial hypertension (IPAH) can also be identified in PBMCs from scleroderma patientswith PAH (PAH-SSc). Gene expression profiles of PBMCs collected from IPAH (n=9), PAH-SSc(n=10) patients and healthy controls (n=5) were generated using HG_U133A_2.0 GeneChips andprocessed by RMA/GCOS_1.4/SAM_1.21 data analysis pipeline. Disease severity in consecutivepatients was assessed by functional status and hemodynamic measurements. The expression profileswere analyzed using PAH severity-stratification, and identified candidate genes were validated withreal time PCR (rtPCR). Transcriptomics of PBMCs from IPAH patients was highly comparable withthat of PMBCs from PAH-SSc patients. The PBMC gene expression patterns significantly correlatewith right atrium pressure (RA) and cardiac index (CI), known predictors of survival in PAH. Arraystratification by RA and CI identified 364 PAH-associated candidate genes. Gene ontology analysisrevealed significant (Zscore > 1.96) alterations in angiogenesis genes according to PAH severity:MMP9 and VEGF were significantly upregulated in mild as compared to severe PAH and healthycontrols, as confirmed by rtPCR. These data demonstrate that PBMCs from patients with PAH-SSccarry distinct transcriptional expression. Furthermore, our findings suggest an association betweenangiogenesis-related gene expression and severity of PAH in PAH-SSc patients. Deciphering therole of genes involved in vascular remodeling and PAH development may reveal new treatmenttargets for this devastating disorder.

INTRODUCTIONAlthough poorly understood, vascular remodeling in idiopathic pulmonary arterialhypertension (IPAH) is thought to be related to a complex interaction between genetic andenvironmental factors. PAH is also recognized as a complication of autoimmune diseases,especially scleroderma (SSc), systemic lupus erythematosis, and mixed connective tissue

§ Corresponding author: Division of Pulmonary & Critical Care Medicine, Johns Hopkins University, Asthma & Allergy Center - 2B.34, 5501 Hopkins Bayview Circle, Baltimore, MD 21224, Phone: 410 550 2606, Email: [email protected]'s Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customerswe are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resultingproof before it is published in its final citable form. Please note that during the production process errors may be discovered which couldaffect the content, and all legal disclaimers that apply to the journal pertain.

NIH Public AccessAuthor ManuscriptTransl Res. Author manuscript; available in PMC 2009 April 1.

Published in final edited form as:Transl Res. 2008 April ; 151(4): 197–207.

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disease (1–4). Although PAH is one of the leading causes of mortality in patients SSc (5,6),little is known about phenotypic and genomic characteristics in PAH associated withscleroderma (PAH-SSc) or the cellular and molecular mechanisms involved in pulmonaryvascular remodeling. This limited understanding may be partly explained by the lack ofinvestigations during the early phase of the disease process due both to a delay in diagnosis ofPAH-SSc and the scarcity of available lung tissue because of the high morbidity associatedwith performing lung biopsy in patients with PAH.

A recently developed method of detecting and monitoring disease using gene expressionprofiling of peripheral blood mononuclear cells (PBMCs) (7–10) has been also successfullyapplied in studies of PAH. Bull et al demonstrated that gene expression profiling of PBMCsefficiently discriminates between patients with PAH and normal volunteers and identifiesPAH-specific genes (11,12). We therefore hypothesized that gene expression profiling ofPBMCs from SSc patients with PAH can identify PAH-specific genes despite the presence ofdysregulated immunity in these patients. Moreover, we anticipated that analysis of differentdegrees (mild versus severe) of PAH-SSc could uncover novel candidate genes that specificallyassociate with the severity of PAH in SSc patients.

In this study we compare gene expression profiles of PBMCs from 9 IPAH and 10 PAH-SScand demonstrated striking similarities in expression of PAH-associated genes between thesepatient populations. We then evaluated 10 PAH-SSc patients using routine functional andhemodynamic measurements including the World Health Organization’s functional class, the6-minute walk distance, right atrial and mean pulmonary artery pressures, and cardiac indexand pulmonary vascular resistance. The results of these functional and hemodynamicmeasurements were used for patient stratification by severity, and gene expression profiles ofpatients with mild and severe PAH were compared. Using PBMCs, our study provides newevidence to support the concept that stratification of SSc patients by the degree of PAH severitycan successfully be applied for identification of stage-related candidate genes involved in thepulmonary vascular disease process.

METHODSStudy subjects

The current research was carried out according to the principles of the Declaration of Helsinki.The Institutional Review Board reviewed and approved the conduct of this study and informedconsent was obtained from each patient. We examined functional and hemodynamic data in 9consecutive patients diagnosed with IPAH and 10 consecutive patients diagnosed with PAH-SSc based on right heart catheterization (mean pulmonary artery pressure > 25 mm Hg andpulmonary capillary wedge pressure ≤ 15 mm Hg). The diagnosis of SSc was based on one ofthree definitions: the American College of Rheumatology criteria (13); the presence of threeof five features of the CREST syndrome; or definite Raynaud’s phenomenon, abnormal nailfold capillaries typical of SSc and the presence of a specific scleroderma-related auto-antibody.

Patients were excluded if they had pulmonary venous hypertension (pulmonary capillarywedge pressure > 15 mm Hg), significant chronic obstructive (defined as a forced expiratoryvolume in 1 second (FEV1) to forced expiratory volume (FVC) ratio < 70% and a FEV1 lessthan 60% of predicted) or interstitial lung disease (total lung capacity (TLC) less than 60% ofpredicted; Patients with a TLC between 60 and 70% of predicted were included only if theircomputed tomography scan showed only minimal interstitial fibrosis), portal hypertension,severe obstructive sleep apnea, or chronic thromboembolic disease. Patients were also excludedif they had antibodies to the human immunodeficiency virus, had a history of anorexigen use,or any other disease known to be associated with pulmonary hypertension.

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Severity of PAH in 10 PAH-SSc patients was assessed by routine functional and hemodynamicmeasurements obtained at time of first evaluation, including World Health Organizationfunctional class (WHO, our initial overall severity parameter), 6-minute walk distance(6MWD), right atrium (RA) and pulmonary artery (PA) pressure, cardiac index (CI) andpulmonary vascular resistance index (PVRI).

Study designPatient populations were stratified using values of functional and hemodynamic parametersand compared to healthy controls (cross-group analysis). The gene expression profiles of mildand severe PAH clusters in PAH-SSc population were also directly compared (intra-groupanalysis). The uneven distribution of mild (WHO I-II) versus severe (WHO III-IV) patients inIPAH group (only one severe patient) excluded the IPAH group from intra-group analysis. Theeffect of PAH drugs on PBMCs gene expression was evaluated by stratification of the patientpopulation by drug used.

Power prediction analysis for significance of transcriptional changesThe reliability of detected transcriptional changes was ensured using the 50th percentile of themost variable hybridization signals from controls (n=5) as described previously (14). Theresulting standard deviation (σ = 0.416) was submitted to the microarray sample sizeidentifying formula proposed by Wei et al (15), imposing 90% of detecting power (1-β) andaccepting a 1% or 5% false discovery rate (significance level α = 0.01 or 0.05) for cross- (n=5–10) and intra-group (n=3–4) analyses, respectively. The more relaxed false discovery rate forintra-group analysis was selected based on the less variable population (all patients had SSc,thus SSc-related variables are offset during comparison). The power.t.test function of R2.3.1program (www.r-project.org) was implemented and 2.45 and 2.60 fold change cutoffs wereidentified for cross-and intra-group comparisons, respectively.

Transcript profiling with Affymetrix oligonucleotide arraysAffymetrix GeneChip profiling was performed at the Johns Hopkins Lowe Family GenomicsCore as previously described for human blood (16). Briefly, total mRNA was isolated fromPBMC and hybridized to Affymetrix GeneChip HG_U133A_2.0 (22,215 transcripts) and thequality of each step was monitored on an Agilent 2100 Bioanalyzer. The fluorescent intensitiesof the resulting hybridization signals were measured by Agilent Gene Array Scanner andconverted to digitized matrix (CEL files), and processed as described in Supplement Figure 1.

Computational identification of PAH-associated candidate genesProcessed and normalized gene expression values were evaluated with the SignificanceAnalysis of Microarrays (SAM) (17) using 1000 permutation comparing control (n=5) andIPAH (n=9) or PAH-SSc (n=10) samples for cross-group analysis; and mild (n=4) and severe(n=4) PAH-SSc samples for intra-group analysis. The PAH-associated genes were identifiedby filtering for 2.45 fold-change and 1% false discovery rate (FDR) for cross-group and 2.60fold-change and 5% FDR for intra-group comparison.

Genomic clustering analysisSupervised hierarchical clustering was conducted using the MeV (MultiExperiment Viewer)component (http://www.tm4.org/mev.html) of TM4 open-source system for microarray datamanagement and analysis (18). The IPAH or PAH-SSc specific genes were combined andclustered based on their fold change values (log2), which were calculated by subtracting theaverage of healthy controls (n=5) from individual gene expression value of each patient. Patientarrays were arranged (supervised) by the disease (IPAH versus PAH-SSc) and then by PAHseverity using RA pressure as a severity indicator. The clustering of genes was conducted based



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on the gene expression pattern rather than amplitude using uncentered Pearson correlationapplying complete linkage.

Associating hemodynamic measurements and PAH-drug effects with gene expressionThe association between PAH severity and gene expression in PAH-SSc patients was evaluatedby sorting hemodynamic measurements by severity and successive (7 cycles) comparisons bySAM (100 permutations) of groups of patients with mild versus severe disease. After eachcycle the less polar measurement (middle of the sorted dataset) was removed and SAM analysisrepeated. The FDR value (q) of the 100th gene in the SAM output, which represents a groupunidirectional change in gene expression rather than sporadic transcriptional effect, was usedas the correlation factor, and q < 5 was considered significant. This correlation factor was alsoused for estimation of effects of PAH treatments on PBMC gene expression.

Real time PCRReal time RT-PCR of matrix metallopeptidase 9 (MMP9) and vascular endothelial growthfactor (VEGF) genes was conducted as described previously (19) with addition of multipleinternal controls (huACTB, huGAPDH, and huPGK1). Briefly, transcript levels of these genesin PBMCs were measured (n=3 per condition) in 96-well microtiter plates with an ABI Prism7700 Sequence Detector Systems (Perkin-Elmer/Applied Biosystems). The mRNA expressionlevels were normalized to the average concentrations of three internal controls (avrgIC):huACTB, huGAPDH, and huPGK1.

Gene ontology and PubMatrix analysesGene Ontology (GO) analysis was performed using GenMAPP and MAPPFinder software(20,21). The GenMAPP database for human GeneChip (Hs-Std_20060127.gdb) was manuallyupdated, specifically MMP9 gene was added to angiogenesis GO based on previous reports(22,23). GO pathways with Z scores of > 1.96, were considered significantly affected by PAH.The relevance of identified candidate genes to PAH and SSc was evaluated using PubMatrix(http://pubmatrix.grc.nia.nih.gov), the automated biomedical literature search engine (24). ThePubMatrix-selected citations of journal articles that referenced “pulmonary hypertension” and“scleroderma” terms in the same context with a given candidate gene were manually reviewed.

RESULTSPatient demographics and clinical data

Nine and ten consecutive patients with IPAH and PAH-SSc, respectively, were included in thestudy (Table 1). The average age of the patients was 49 ± 10 for IPAH and 61 ± 9 years forPAH-SSc (P > 0.05). All PAH-SSc self-reported as European American and nine of the ten(90%) were women. Almost all IPAH patients (89%) were in WHO functional class 1 or 2 andthe majority of PAH-SSc patients (70%) in WHO functional class 3 or 4. The average 6MWDfor PAH-SSc and IPAH patients was 292 ± 144 and 363 ± 186 meters, respectively, suggestingmoderate to severe functional impairment. Right heart catheterization parameters revealedmoderate to severe pulmonary arterial hypertension in PAH-SSc (with mean RAP = 11 ± 4mmHg, mean PAP = 51 ± 10 mmHg, mean CI = 2.2 ± 0.8 L/min/m2, and PVRI = 1660 ± 780mmHg/L/min/m2), and IPAH (mean RAP = 8.7 ± 2.9 mmHg, mean PAP = 50 ± 12 mmHg,mean CI = 2.6 ± 0.6 L/min/m2, and PVRI = 1327± 473 mmHg/L/min/m2) patients. Patients inboth groups of diseases were treated with a variety of PAH-specific drugs (Table 1). Asidefrom calcium channel blockers which were more common in PAH-SSc patients (usually usedat low doses for treatment of Raynaud’s syndrome) there were no significant differencesbetween the two groups (Table 1). All patients with PAH-SSc had the limited form of systemicsclerosis and most of them had a positive ANA and positive anti-centromere antibody (Table



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2). The average age of the healthy controls was 34 ± 8 years. All were European American andthree of the five (60%) were women.

Genes associated with PAH in IPAH and PAH-SSc patientsA total of 12,452 probe sets representing 8,037 known genes were efficient in detecting theircorresponding targets in human PBMCs (Supplement Table 1). The cross-group SAM analysisidentified 116 and 365 PAH-affected genes in IPAH and PAH-SSc patients, respectively(Supplement Tables 1). The supervised (stratified by PAH severity) hierarchical clustering ofPAH-associated genes identified several clusters of genes with different expression patterns(Pearson correlation) including a group of PAH severity-independent genes that wereupregulated in both IPAH and PAH-SSc diseases (Figure 1, upper highlighted gene panel).However, a second set of genes (Figure 1, lower highlighted gene panel) demonstratedvariability of expression according to PAH severity with upregulation in patients with mildPAH. This observation was confirmed by SAM analysis restricted to healthy controls and fourpatients with mild PAH from IPAH group and five patients with mild PAH from PAH-SScgroup (Table 3). The stratification of patients with mild PAH demonstrated an overall higheramplitude (i.e., increase in the fold change) of PAH-associated genes, with increasedsignificance in this stratified population as compared to the analysis performed on the entireIPAH or PAH-SSc patient cohorts (i.e. IL-8, VEGF, EREG, Table 2). The contribution of PAHdrugs to these transcriptional changes was evaluated next. Patients were stratified by the mostcommonly used drugs: Intravenous epoprostenol, bosentan, calcium channel blockers, andsildenafil (Table 1) and corresponding false discovery rates (q) were computed by SAM asdescribed in Materials and Methods. We found no association of calcium channel blockers andsildenafil treatments with transcriptional changes in PBMCs (q=100) and a trend that was notsignificant for intravenous epoprostenol (q = 20.3) and bosentan (q = 23.5) treatment.

Genes associated with PAH severity in PAH-SSc patientsTo eliminate the age variable (that was introduced by the relatively younger control population)and the SSc-related variability, we restricted our severity stratification studies to the PAH-SScgroup itself. The representative false discovery rate (q) for each hemodynamic measurement(Table 2) was calculated by SAM, and identified RA and CI as the most significant parameters(q < 5%) associated with the intra-group changes in PBMC gene expression. The comparisonsets with the lowest q for CI (q = 2.05, severe (n = 4) versus mild (n = 4)) and RA (q = 1.56,severe (n = 3) versus mild (n = 2)) were selected for PAH severity-associated gene identification(Figure 2), and 364 candidate genes were thus identified (Supplement Table 2).

PAH-associated gene ontologies and biological processesTo evaluate the effects of PAH status on biological pathways and processes in PBMC, welinked identified candidate genes to gene ontology terms using GenMAPP and MAPPFindertools (20,21). This analysis identified 9 pathways that were affected by PAH (Table 4)including most prominently angiogenesis, chemotaxis, and inflammatory response, whichwere represented by 25 genes (Table 5). PubMatrix analysis identified genes that are suspectedto be involved in both PAH and scleroderma (i.e. IL1B, MMP9, VEGF, CCL4) as well as novelgenes (i.e. EREG, CEACAM1, CXCL2, MMP25). Genes coding for the angiogenesis regulatorsMMP9 and VEGF were further analyzed using real time PCR. This analysis demonstratedsignificant up-regulation of these genes in mild PAH compared to healthy controls, while theirexpression was no different from controls in severe PAH (Figure 3). These results confirmedthe microarray data which revealed that gene expression of MMP9 and VEGF was,respectively, 4.39 and 3.56 fold higher in SSc patients with mild compared to severe PAH(Table 5).



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DISCUSSIONThe main findings of this pilot study is that PAH-associated transcriptional changes in PBMCsfrom scleroderma patients are detectable by microarray techniques and are highly comparablewith those from PBMCs obtained from IPAH patients. This provides evidence for the use ofa practical assay to discover new molecular targets and biomarkers in a large population ofSSc patients who are at risk for developing or have PAH. In addition, we provide novel evidencethat gene expression is different in subgroups of PAH-SSc and that specific biologicalprocesses may associate with stages of PAH severity, thus providing mechanistic insight intothe PAH development and progression. Stratification of PAH-SSc by level of CI and RA washighly correlated with PBMC gene expression and demonstrated interesting associations ofangiogenesis- and chemotaxis/inflammation-related genes with severity of PAH in thispopulation of scleroderma patients.

Genomic changes have been increasingly identified from peripheral blood in a variety ofdiseases. Due to their clinical accessibility, circulating blood cells represent the mostconvenient tissue source for the assessment of alteration in gene expression associated withimmune-related diseases. Recent reports on successful application of gene expression profilingof PBMCs from patients with autoimmune diseases strongly suggest that this approach is avaluable tool for investigating pathological processes that affect cellular components ofperipheral blood (9,25,26) as well as distant organs (7,8,10). Gene expression profiling ofcirculating PBMCs has been recently successfully applied for identification of PAH associatedgenes in idiopathic PAH patients (11). The authors revealed a panel of genes that weredifferentially expressed in PBMCs from subjects with PAH compared to healthy volunteers,which was interpreted as a disease signature (11). The current study confirmed this approachfor IPAH and investigated its applicability for scleroderma-related PAH. In diseases associatedwith immune response or dysregulation such as infection and autoimmunity (i.e. scleroderma),the changes in gene expression of PBMCs can be more pronounced in relevance to the immune-specific pathogenic processes, and can therefore obscure transcriptional changes associatedwith co-morbid disorders such as PAH. Therefore, we investigated whether gene expressionprofiles of PBMCs in scleroderma patients with PAH might still reflect changes germane tothe pathogenic mechanisms involved in pulmonary vascular remodeling in these patients.

This is the first attempt to identify differences in global patterns of gene expression in PBMCsfrom subjects with PAH-SSc with a particular focus on processes associated with the severityof PAH. The clustering analysis of gene expression profiles in IPAH and PAH-SSc revealedsimilarities in expression of several clusters between both patient populations (Figure 1), whichinclude known PAH and angiogenesis-associated genes such as IL-8, VEGF, and EREG (Table3). Upregulation of these genes was not only concordant between IPAH and PAH-SSc groupsbut was more pronounced in PBMCs from PAH-SSc group. These data demonstrate that SSc-related processes are not obscuring PAH-associated transcriptional signature but ratherenhance it (Table 3) underlying perhaps a causal relationship between SSc and PAH. Thepotential pharmacological effects of PAH drugs on transcriptional changes in PBMCs fromPAH patients were investigated and proven to be negligible, thus confirming that the detectedalterations in PBMC gene expression are mostly disease (PAH)-related rather than affected bytherapy.

We also observed variability in the expression of PAH-affected genes according to PAHseverity (Figure 1). This finding was confirmed by inter-group (Table 3) and intra-groupanalysis of PAH-SSc patients, which demonstrated that stratifying PBMC expression profiles,based on functional and hemodynamic characteristics of PAH severity, allows detection ofsignificant transcriptional changes of genes involved in PAH-specific pathogenic processes(Figure 2), which can serve as potential biomarkers for the severity of the disease. Our genomic



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findings were in agreement with a recently reported PAH-transcriptional signature of PBMCs(11). Several genes identified in the present study were also identified in the prior study (11)including ADM, IL7R, ZFP36, GLUL, JUND, and BCL6 (Table 3). In addition, our intra-groupanalysis identified adrenomedulin and herpesvirus entry mediator genes (convincingly linkedto IPAH and secondary PAH (11), respectively), as severity related (Supplement Table 2). Thesignificant association between transcriptional changes and hemodynamic characteristics wasdetected for CI and RA while an associative trend was observed for 6MWD. Such differencesin the level of association between transcriptional changes and hemodynamic or functionalcharacteristics can be explained by biological variability and will likely be reduced withincreasing number of studied subjects.

The most consistent PBMC gene expression changes were recorded when CI and RAmeasurements were used for stratification according to PAH severity (Figure 2). Thesehemodynamic parameters are the best predictors of survival in idiopathic (27) and scleroderma-associated PAH (28). Therefore, genes that were detected using stratification by CI and RAwere considered associated with PAH severity. Gene ontology (GO) analysis identified severalbioprocesses (Table 4), potentially involved in PAH severity, which have been previouslyimplicated in vascular and PAH pathogenesis (e.g., angiogenesis and inflammation) and arerepresented by genes such as IL8, VEGF, ILB, and MMP9 (Table 5). We also identified severalnovel genes not previously associated with PAH pathogenesis (EREG, CXCL2, andMMP25), and which represent potential new biomarkers and/or therapeutic targets for futurestudies.

As a proof of concept, a more detailed analysis of VEGF and MMP9 genes, which are directlyimplicated in angiogenesis, demonstrated that these genes were expressed at lower levels orwere undetectable in patients with severe compared to mild PAH (Table 3), suggestingdysregulation of angiogenic processes in advanced forms of PAH. Real time PCR analysis ofVEGF and MMP9 confirmed this observation by demonstrating significantly lower transcriptabundance of these genes in PBMCs from patients with severe compared to mild PAH. WhenPBMC expression levels of VEGF and MMP9 in patients with mild PAH were compared withthose in healthy volunteers, there was approximately 4 and 20 fold increase in VEGF andMMP9 expression, respectively (Figure 3). Taken together, these observations support thenotion that development of PAH is associated with active vascular remodeling involvingvascular growth and matrix regulating genes. Furthermore, these findings are in concordancewith our previous report on circulating regulators of angiogenesis, including VEGF and MMP9proteins, in scleroderma patients (23). Increased levels of these angiogenic regulators wereindeed identified in 115 scleroderma patients and linked to the manifestations of SSc-relatedvascular pathology (23). MMP9, known to facilitate angiogenesis through collagen remodeling(29), also controls excessive neovascularization (22). Therefore our findings are in agreementwith the general concept of angiogenic dysregulation in the scleroderma spectrum of diseases(30) and further suggest an association between angiogenesis and PAH severity in SSc patients.

Gene ontology analysis also linked chemotaxis and inflammatory pathways to severity of PAHin scleroderma patients. Increased levels of multiple chemokines and their receptors have beenobserved in blood and affected tissue from scleroderma patients, and their involvement in tissuefibrosis and pulmonary hypertension has been suggested (31). Our genomic approach identifiedseveral chemokines including CXCL1 and -2, and CCL-3 and -4, and demonstrated theirdifferential expression in mild versus severe PAH patients (Table 5). The CCL3 and CCL4genes that code for monocyte/macrophage chemoattractant protein-1 alpha and beta (MCP-1aand MCP-1b), respectively, are of particular interest. Inhibition of these genes has been shownto prevent monocrotaline-induced pulmonary hypertension, suggesting a role for thischemokine in the pathogenesis of pulmonary vascular remodeling (32).



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Despite a general up-regulatory trend of most PAH-severity related genes identified in thisstudy, several genes were downregulated including CCR2 and TLR7 (Table 5). One possibilityis that highly expressed genes in patients with mild PAH (Table 3), whose expression subsidesin the severe cases of the disease, could represent PAH protective genes, while genes that areactively transcribed in severe PAH might be implicated in sustaining the disease. Alternatively,expression of these genes could merely represent novel biomarkers for PAH severity. Clearly,these potential patterns and their exact clinical and pathogenic significance need to be testedin future larger prospective as well as longitudinal studies.

We recognize that this pilot study presents data in a small population of patients and thatcomparison with other disease subtypes would be ideal. Certainly, multiple other factors mayinfluence gene expression including drugs, co-morbid conditions and extra-pulmonaryscleroderma vascular disease. It would also be important to follow a population of patientswith both mild and severe PAH-SSc over time and to study patients with SSc who are at riskfor developing PAH. However, the data reported therein provide strong evidence that geneexpression can be studied in the PBMC and that biologically relevant genes are detected thatassociate with disease severity. We also demonstrated that our intra-group severity-basedstratification approach can identify disease severity-associated genes without utilization ofhealthy control population, thus facilitating clinical research.

In summary, our findings indicate that gene expression alterations in response to PAH aredetectable by microarray techniques in PBMCs from patients with PAH-SSc. Stratification ofgene expression profiles by CI and RA was highly correlated with PBMC gene expression anddemonstrated association of angiogenesis- and chemotaxis/inflammation-related genes withseverity of PAH in scleroderma patients. Deciphering the role of these pathways and theircomponents in PAH might reveal new targets for early detection, prevention and treatment ofthis devastating disorder.

Supplementary MaterialRefer to Web version on PubMed Central for supplementary material.

Acknowledgements

This study was supported by NHLBI P50 HL084946 SCCOR

This study was supported by NHLBI P50 Grant number HL084946 (Specialized Center for Clinically-OrientedResearch). KCB was supported in part by the Mary Beryl Patch Turnbull Scholar Program. The Scleroderma ResearchFoundation has provided support for the Johns Hopkins Scleroderma Center. The authors wish to thank Ellen G.Reather for expert manuscript assistance.

AbbreviationsPBMC

peripheral blood mononuclear cells

IPAH idiopathic pulmonary arterial hypertension

SSc scleroderma

PAH-SSc scleroderma patients with PAH

WHO



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World Health Organization

6MWD 6 minute walk distance

RA right atrium pressure

PA pulmonary artery pressure

CI cardiac index

PVRI pulmonary vascular resistance index

rtPCR real time PCR

SAM significance analysis of microarrays

FDR false discovery rate

MeV multi experiment viewer

VEGF vascular endothelial growth factor

MMP9 matrix metallopeptidase 9

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Figure 1. Hierarchical clustering of genes significantly affected by IPAH or PAH-SScThe 287 PAH-associated genes were combined and clustered using MeV as described inMaterials and Methods. Each column represents a PAH affected patient and each rowrepresents the expression pattern of a specific gene throughout all patients. Hierarchicalclustering, which was conducted using uncentered Pearson correlation (complete linkage),identified 6 major clusters of which one cluster (third from the bottom) demonstrated clearexpression differences between severe and mild patients in both diseases. The specific groupof genes in the neighboring cluster (third from the top) demonstrated severity- and disease-independent upregulation. Both groups of genes are highlighted with blue rectangles, and mostrepresentative genes within each group are listed on the right.Red color indicates up-regulation and green color indicates down-regulation of gene expressionrelative to healthy controls, with color intensity corresponding to the fold-change amplitude(fold-change scale shown on the left).



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Figure 2. Association between hemodynamic measurements and genomic changes in PAH-SScpatientsThe gene expression profiles of PAH-SSc patients were sorted by severity in ascending orderusing each hemodynamic (CI, RA, PA, and PVRI) or functional (WHO functional class and 6MWD) measurement as a severity indicator. The SAM analysis (100 permutations) wasperformed comparing severity-polar patient groups (i.e., groups of patients deemed have severeversus mild disease). After each of 7 cycles (x axes) the less polar patients (middle profile) wasremoved and SAM analysis repeated. The number of compared profiles depicted on the x axes(mild vs severe) and groups that were compared for each cycle are presented as circle underthe x axes. An open circle represents the patient with the most mild PAH and solid circle



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represents patient with the most severe PAH. The gray scale intensity corresponds to the PAHseverity in SS patients. The beginning comparison was between 5 mild and 5 severe profiles,and final comparison was between 2 mild and 2 severe profiles. The lowest FDR point for eachhemodynamic or functional measurement is labeled with corresponding abbreviation.



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Figure 3. Real time PCR expression of genes associated with PAH severityThe relative MMP9 and VEGF message abundance was detected by real time RT-PCR usingtotal PBMC RNA. Results are represented as mean ± SEM. Statistical significance (P < 0.05)of the gene expression difference between patients and healthy volunteers was derived withtwo-tailed t-test of normalized to three different internal controls threshold cycle (Ct) values.



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Table 1Summary of patient demographics and drugs.

IPAH (n=9) PAH-SSc (n=10)Age (yrs) 49 (10)Δ 61 (9)Gender (n, % women) 7 (78) 9 (90)Race (n, % caucasian) 9 (100) 10 (100)WHO functional class I: 2

II: 6III:1IV: 0

I: 1II: 2III: 5IV: 2

6MWD(m)* 363 (186) 292 (144)RAP (mmHg) 8.7 (2.9) 11 (4)mPAP (mmHg) 50 (12) 51 (10)CI (L/min/m2) 2.6 (0.6) 2.2 (0.8)PVRI (mmHg/L/min/m2) 1327 (473) 1660 (780)Treatment† Bosentan 3 (1) 4(2) CCB 1(0) 5(2) I.V. epoprostenol 7(5) 2(0) Sildenafil 1(0) 3(1) Treprostinil 0 2(1)*N=9; one patient wheel-chair bound (leg amputation).

ΔAll values expressed as mean (SD) unless otherwise specified.

†Number of patients treated, numbers in brackets represent monotherapy with a given drug.

CCB-calcium channel blockers; I.V. –intravenous


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Table 5Genes representing top three ontologies listed in Table 4.

Gene Symbol Gene Title Fold Change PubMatrixPH SS

Angiogenesis (1525) §EREG Epiregulin 5.46 0 0MMP9 Matrix metallopeptidase 9 (gelatinase B) 4.39 16 5IL8* Interleukin 8 4.08 0 3VEGF* Vascular endothelial growth factor 3.56 104 29CEACAM1 Carcinoembryonic antigen-related cell adhesion 1 3.08 0 0ANPEP Alanyl (membrane) aminopeptidase 2.76 0 0Chemotaxis (6935)CXCL2* Chemokine (C-X-C motif) ligand 2 11.71 0 0CXCL1 Chemokine (C-X-C motif) ligand 1 8.59 0 1CCR2* Chemokine (C-C motif) receptor 2 −5.34 0 1IL8RB* Interleukin 8 receptor, beta 5.25 0 1PLAUR Plasminogen activator, urokinase receptor 4.83 1 3FPR1* Formyl peptide receptor 1 3.56 0 0CCL3* Chemokine (C-C motif) ligand 3 3.53 3 3CCL4* Chemokine (C-C motif) ligand 4 3.00 4 3+2 shared† IL8, VEGF (1525)Inflammatory response (6954)MMP25 Matrix metallopeptidase 25 6.67 0 0TNFAIP6 Tumor necrosis factor, alpha-induced protein 6 6.40 1 0PTGS2 Prostaglandin-endoperoxide synthase 2 (COX-2) 5.55 13 1TLR7 Toll-like receptor 7 −5.34 0 0IL1B Interleukin 1, beta 5.02 30 66IL1RN Interleukin 1 receptor antagonist 4.68 4 5PTX3 Pentraxin-related gene, rapidly induced by IL-1 beta 4.20 0 2TPST1 Tyrosylprotein sulfotransferase 1 3.70 0 0ADORA2A Adenosine A2a receptor 3.11 0 2IL1RAP Interleukin 1 receptor accessory protein 2.84 0 0LY64 lymphocyte antigen 64 −2.72 0 0+7 shared IL8, IL8RB, CXCL2, CCR2, CCL3, CCL4, FPR1 (6935)§gene ontology (GO) title and identification number

*gene which belong to more than one GO (shared)

†shared genes (italic) detailed information for which is provided in another GO (corresponding identification number is shown in brackets)

The terms “pulmonary hypertension” (PH) and “scleroderma” (SSc) were automatically matched against gene symbols/titles using PubMatrix, and numberof PubMed publications where these terms and a given gene were referenced together are presented in corresponding columns.


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Identification of candidate genes in scleroderma-related pulmonary arterial hypertension

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