Risk loci involved in giant cell arteritis susceptibility: a genome-wide association study.

BACKGROUND: Giant cell arteritis is an age-related vasculitis that mainly affects the aorta and its branches in individuals aged 50 years and older. Current options for diagnosis and treatment are scarce, highlighting the need to better understand its underlying pathogenesis. Genome-wide association studies (GWAS) have emerged as a powerful tool for unravelling the pathogenic mechanisms involved in complex diseases. We aimed to characterise the genetic basis of giant cell arteritis by performing the largest GWAS of this vasculitis to date and to assess the functional consequences and clinical implications of identified risk loci. METHODS: We collected and meta-analysed genomic data from patients with giant cell arteritis and healthy controls of European ancestry from ten cohorts across Europe and North America. Eligible patients required confirmation of giant cell arteritis diagnosis by positive temporal artery biopsy, positive temporal artery doppler ultrasonography, or imaging techniques confirming large-vessel vasculitis. We assessed the functional consequences of loci associated with giant cell arteritis using cell enrichment analysis, fine-mapping, and causal gene prioritisation. We also performed a drug repurposing analysis and developed a polygenic risk score to explore the clinical implications of our findings. FINDINGS: We included a total of 3498 patients with giant cell arteritis and 15 550 controls. We identified three novel loci associated with risk of giant cell arteritis. Two loci, MFGE8 (rs8029053; p=4·96 × 10-8; OR 1·19 [95% CI 1·12-1·26]) and VTN (rs704; p=2·75 × 10-9; OR 0·84 [0·79-0·89]), were related to angiogenesis pathways and the third locus, CCDC25 (rs11782624; p=1·28 × 10-8; OR 1·18 [1·12-1·25]), was related to neutrophil extracellular traps (NETs). We also found an association between this vasculitis and HLA region and PLG. Variants associated with giant cell arteritis seemed to fulfil a specific regulatory role in crucial immune cell types. Furthermore, we identified several drugs that could represent promising candidates for treatment of this disease. The polygenic risk score model was able to identify individuals at increased risk of developing giant cell arteritis (90th percentile OR 2·87 [95% CI 2·15-3·82]; p=1·73 × 10-13). INTERPRETATION: We have found several additional loci associated with giant cell arteritis, highlighting the crucial role of angiogenesis in disease susceptibility. Our study represents a step forward in the translation of genomic findings to clinical practice in giant cell arteritis, proposing new treatments and a method to measure genetic predisposition to this vasculitis. FUNDING: Institute of Health Carlos III, Spanish Ministry of Science and Innovation, UK Medical Research Council, and National Institute for Health and Care Research.

Genome-Wide Association Study Identifies the First Germline Genetic Variant Associated With Erdheim-Chester Disease.

OBJECTIVE: Erdheim-Chester disease (ECD) is rare histiocytosis with a wide range of clinical manifestations. Somatic mutations are key to the pathogenesis of the disease; however, the relationship between germline genetic variants and ECD has not been examined so far. The present study aims to explore the inherited genetic component of ECD by performing the first genome-wide association study. METHODS: After quality controls, a cohort of 255 patients with ECD and 7,471 healthy donors was included in this study. Afterward, a logistic regression followed by in silico functional annotation was performed. RESULTS: A signal at the 18q12.3 genomic region was identified as a new susceptibility locus for ECD (P = 2.75 × 10-11 ; Odds Ratio = 2.09). This association was annotated to the SETBP1 gene, which is involved in clonal haematopoiesis. Functional annotation of this region and of the identified suggestive signals revealed additional genes that could be potentially involved in the pathogenesis of the disease. CONCLUSION: Overall, this work demonstrates that germline genetic variants can impact on the development of ECD and suggests new pathways with a potential pathogenic role.

A holistic approach to understanding immune-mediated inflammatory diseases: bioinformatic tools to integrate omics data.

Immune-mediated inflammatory diseases (IMIDs) comprise a complex group of pathologies with diverse etiologies and clinical manifestations. In particular, omics technologies have remodeled our understanding of a set of IMIDs such as systemic autoimmune rheumatic diseases (SARDs), generating vast amounts of data on the genome, epigenome, transcriptome, proteome and metabolome of immune cells and SARDs patients. However, the integration of omics data to advance our knowledge of these diseases is challenging, requiring advanced bioinformatic tools. This review explores different multi-omic integrative tools for refining previous research, exploring the biological relevance of datasets within different contexts, or translating omics results into clinical advances. We also discuss relevant multi-omic studies in SARDs research and the potential of omics data from available repositories to complement ongoing investigation in this field.

Non-classical circulating monocytes expressing high levels of microsomal prostaglandin E2 synthase-1 tag an aberrant IFN-response in systemic sclerosis.

Systemic sclerosis (SSc) is a complex disease that affects the connective tissue, causing fibrosis. SSc patients show altered immune cell composition and activation in the peripheral blood (PB). PB monocytes (Mos) are recruited into tissues where they differentiate into macrophages, which are directly involved in fibrosis. To understand the role of CD14+ PB Mos in SSc, a single-cell transcriptome analysis (scRNA-seq) was conducted on 8 SSc patients and 8 controls. Using unsupervised clustering methods, CD14+ cells were assigned to 11 clusters, which added granularity to the known monocyte subsets: classical (cMos), intermediate (iMos) and non-classical Mos (ncMos) or type 2 dendritic cells. NcMos were significantly overrepresented in SSc patients and showed an active IFN-signature and increased expression levels of PTGES, in addition to monocyte motility and adhesion markers. We identified a SSc-related cluster of IRF7+ STAT1+ iMos with an aberrant IFN-response. Finally, a depletion of M2 polarised cMos in SSc was observed. Our results highlighted the potential of PB Mos as biomarkers for SSc and provided new possibilities for putative drug targets for modulating the innate immune response in SSc.

Identification of new risk loci shared across systemic vasculitides points towards potential target genes for drug repurposing.

OBJECTIVES: The number of susceptibility loci currently associated with vasculitis is lower than in other immune-mediated diseases due in part to small cohort sizes, a consequence of the low prevalence of vasculitides. This study aimed to identify new genetic risk loci for the main systemic vasculitides through a comprehensive analysis of their genetic overlap. METHODS: Genome-wide data from 8467 patients with any of the main forms of vasculitis and 29 795 healthy controls were meta-analysed using ASSET. Pleiotropic variants were functionally annotated and linked to their target genes. Prioritised genes were queried in DrugBank to identify potentially repositionable drugs for the treatment of vasculitis. RESULTS: Sixteen variants were independently associated with two or more vasculitides, 15 of them representing new shared risk loci. Two of these pleiotropic signals, located close to CTLA4 and CPLX1, emerged as novel genetic risk loci in vasculitis. Most of these polymorphisms appeared to affect vasculitis by regulating gene expression. In this regard, for some of these common signals, potential causal genes were prioritised based on functional annotation, including CTLA4, RNF145, IL12B, IL5, IRF1, IFNGR1, PTK2B, TRIM35, EGR2 and ETS2, each of which has key roles in inflammation. In addition, drug repositioning analysis showed that several drugs, including abatacept and ustekinumab, could be potentially repurposed in the management of the analysed vasculitides. CONCLUSIONS: We identified new shared risk loci with functional impact in vasculitis and pinpointed potential causal genes, some of which could represent promising targets for the treatment of vasculitis.

Identification of Mechanisms by Which Genetic Susceptibility Loci Influence Systemic Sclerosis Risk Using Functional Genomics in Primary T Cells and Monocytes.

OBJECTIVE: Systemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the genes associated with the disease are still unknown because associated variants affect mostly noncoding intergenic elements of the genome. We used functional genomics to translate the genetic findings into a better understanding of the disease. METHODS: Promoter capture Hi-C and RNA-sequencing experiments were performed in CD4+ T cells and CD14+ monocytes from 10 SSc patients and 5 healthy controls to link SSc-associated variants with their target genes, followed by differential expression and differential interaction analyses between cell types. RESULTS: We linked SSc-associated loci to 39 new potential target genes and confirmed 7 previously known SSc-associated genes. We highlight novel causal genes, such as CXCR5, as the most probable candidate gene for the DDX6 locus. Some previously known SSc-associated genes, such as IRF8, STAT4, and CD247, showed cell type-specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions were directly correlated with the expression of important genes implicated in cell type-specific pathways and found evidence that chromatin conformation is associated with genotype. CONCLUSION: Our study revealed potential causal genes for SSc-associated loci, some of them acting in a cell type-specific manner, suggesting novel biologic mechanisms that might mediate SSc pathogenesis.

FLT3 functional low-frequency variant rs76428106-C is associated with susceptibility to systemic sclerosis.

OBJECTIVES: rs76428106-C, a low frequency polymorphism that affects the splicing of the FLT3 gene, has recently been associated with several seropositive autoimmune diseases. Here, we aimed to evaluate the potential implication of rs76428106-C in the susceptibility to systemic sclerosis (SSc). METHODS: We analysed a total of 26 598 European ancestry individuals, 9063 SSc and 17 535 healthy controls, to test the association between FLT3 rs76428106-C and SSc and its different subphenotypes. Genotype data of rs76428106 were obtained by imputation of already available genome-wide association study data and analysed by logistic regression analysis. RESULTS: In accordance with that observed in other autoimmune disorders, the FLT3 rs76428106-C allele was significantly increased [P-value = 2.03 × 10-3, odds ratio (OR) = 1.34] in SSc patients compared with healthy controls. A similar risk effect was found when the main SSc clinical and serological subgroups were compared with controls. When comparing SSc patients with and without digital ulcers (DU), the rs76428106-C frequency was significantly increased in DU-positive SSc patients in comparison with DU-negative patients (P-value = 0.036, OR = 2.16). CONCLUSION: This study is the first to report an association between rs76428176-C and SSc. Our results support the role of FLT3 as a relevant gene in seropositive immune-mediated diseases and a potential biomarker for SSc microangiopathy.

Complement component C4 structural variation and quantitative traits contribute to sex-biased vulnerability in systemic sclerosis.

Copy number (CN) polymorphisms of complement C4 play distinct roles in many conditions, including immune-mediated diseases. We investigated the association of C4 CN with systemic sclerosis (SSc) risk. Imputed total C4, C4A, C4B, and HERV-K CN were analyzed in 26,633 individuals and validated in an independent cohort. Our results showed that higher C4 CN confers protection to SSc, and deviations from CN parity of C4A and C4B augmented risk. The protection contributed per copy of C4A and C4B differed by sex. Stronger protection was afforded by C4A in men and by C4B in women. C4 CN correlated well with its gene expression and serum protein levels, and less C4 was detected for both in SSc patients. Conditioned analysis suggests that C4 genetics strongly contributes to the SSc association within the major histocompatibility complex locus and highlights classical alleles and amino acid variants of HLA-DRB1 and HLA-DPB1 as C4-independent signals.

The Effect of Body Fat Distribution on Systemic Sclerosis.

Obesity contributes to a chronic proinflammatory state, which is a known risk factor to develop immune-mediated diseases. However, its role in systemic sclerosis (SSc) remains to be elucidated. Therefore, we conducted a two-sample mendelian randomization (2SMR) study to analyze the effect of three body fat distribution parameters in SSc. As instrumental variables, we used the allele effects described for single nucleotide polymorphisms (SNPs) in different genome-wide association studies (GWAS) for SSc, body mass index (BMI), waist-to-hip ratio (WHR) and WHR adjusted for BMI (WHRadjBMI). We performed local (pHESS) and genome-wide (LDSC) genetic correlation analyses between each of the traits and SSc and we applied several Mendelian randomization (MR) methods (i.e., random effects inverse-variance weight, MR-Egger regression, MR pleiotropy residual sum and outlier method and a multivariable model). Our results show no genetic correlation or causal relationship between any of these traits and SSc. Nevertheless, we observed a negative causal association between WHRadjBMI and SSc, which might be due to the effect of gastrointestinal complications suffered by the majority of SSc patients. In conclusion, reverse causality might be an especially difficult confounding factor to define the effect of obesity in the onset of SSc.

Integrative epigenomics in Sjögren´s syndrome reveals novel pathways and a strong interaction between the HLA, autoantibodies and the interferon signature.

Primary Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

The metabolic growth limitations of petite cells lacking the mitochondrial genome.

Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. 'Petite yeasts', characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle.

GWAS loci associated with Chagas cardiomyopathy influences DNA methylation levels.

A recent genome-wide association study (GWAS) identified a locus in chromosome 11 associated with the chronic cardiac form of Chagas disease. Here we aimed to elucidate the potential functional mechanism underlying this genetic association by analyzing the correlation among single nucleotide polymorphisms (SNPs) and DNA methylation (DNAm) levels as cis methylation quantitative trait loci (cis-mQTL) within this region. A total of 2,611 SNPs were tested against 2,647 DNAm sites, in a subset of 37 chronic Chagas cardiomyopathy patients and 20 asymptomatic individuals from the GWAS. We identified 6,958 significant cis-mQTLs (False Discovery Rate [FDR]<0.05) at 1 Mb each side of the GWAS leading variant, where six of them potentially modulate the expression of the SAC3D1 gene, the reported gene in the previous GWAS. In addition, a total of 268 cis-mQTLs showed differential methylation between chronic Chagas cardiomyopathy patients and asymptomatic individuals. The most significant cis-mQTLs mapped in the gene bodies of POLA2 (FDR = 1.04x10-11), PLAAT3 (FDR = 7.22x10-03), and CCDC88B (FDR = 1.89x10-02) that have been associated with cardiovascular and hematological traits in previous studies. One of the most relevant interactions correlated with hypermethylation of CCDC88B. This gene is involved in the inflammatory response, and its methylation and expression levels have been previously reported in Chagas cardiomyopathy. Our findings support the functional relevance of the previously associated genomic region, highlighting the regulation of novel genes that could play a role in the chronic cardiac form of the disease.

Admixture mapping analysis reveals differential genetic ancestry associated with Chagas disease susceptibility in the Colombian population.

Chagas disease is an infection caused by the parasite Trypanosoma cruzi, endemic in Latino America. Leveraging the three-way admixture between Native American (AMR), European (EUR) and African (AFR) populations in Latin Americans, we aimed to better understand the genetic basis of Chagas disease by performing an admixture mapping study in a Colombian population. A two-stage study was conducted, and subjects were classified as seropositive and seronegative for T. cruzi. In stage 1, global and local ancestries were estimated using reference data from the 1000 Genomes Project (1KGP), and local ancestry associations were performed by logistic regression models. The AMR ancestry showed a protective association with Chagas disease within the major histocompatibility complex region [Odds ratio (OR) = 0.74, 95% confidence interval (CI) = 0.66-0.83, lowest P-value = 4.53 × 10-8]. The fine mapping assessment on imputed genotypes combining data from stage 1 and 2 from an independent Colombian cohort, revealed nominally associated variants in high linkage disequilibrium with the top signal (rs2032134, OR = 0.93, 95% CI = 0.90-0.97, P-value = 3.54 × 10-4) in the previously associated locus. To assess ancestry-specific adaptive signals, a selective sweep scan in an AMR reference population from 1KGP together with an in silico functional analysis highlighted the Tripartite Motif family and the human leukocyte antigen genes, with crucial role in the immune response against pathogens. Furthermore, these analyses emphasized the macrophages, neutrophils and eosinophils, as key players in the defense against T. cruzi. This first admixture mapping study in Chagas disease provided novel insights underlying the host immune response in the pathogenesis of this neglected disease.

Comprehensive analysis of the major histocompatibility complex in systemic sclerosis identifies differential HLA associations by clinical and serological subtypes.

OBJECTIVE: The greatest genetic effect reported for systemic sclerosis (SSc) lies in the major histocompatibility complex (MHC) locus. Leveraging the largest SSc genome-wide association study, we aimed to fine-map this region to identify novel human leucocyte antigen (HLA) genetic variants associated with SSc susceptibility and its main clinical and serological subtypes. METHODS: 9095 patients with SSc and 17 584 controls genome-wide genotyped were used to impute and test single-nucleotide polymorphisms (SNPs) across the MHC, classical HLA alleles and their composite amino acid residues. Additionally, patients were stratified according to their clinical and serological status, namely, limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), anticentromere (ACA), antitopoisomerase (ATA) and anti-RNApolIII autoantibodies (ARA). RESULTS: Sequential conditional analyses showed nine SNPs, nine classical alleles and seven amino acids that modelled the observed associations with SSc. This confirmed previously reported associations with HLA-DRB1*11:04 and HLA-DPB1*13:01, and revealed a novel association of HLA-B*08:01. Stratified analyses showed specific associations of HLA-DQA1*02:01 with lcSSc, and an exclusive association of HLA-DQA1*05:01 with dcSSc. Similarly, private associations were detected in HLA-DRB1*08:01 and confirmed the previously reported association of HLA-DRB1*07:01 with ACA-positive patients, as opposed to the HLA-DPA1*02:01 and HLA-DQB1*03:01 alleles associated with ATA presentation. CONCLUSIONS: This study confirms the contribution of HLA class II and reveals a novel association of HLA class I with SSc, suggesting novel pathways of disease pathogenesis. Furthermore, we describe specific HLA associations with SSc clinical and serological subtypes that could serve as biomarkers of disease severity and progression.

Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases.

OBJECTIVE: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis. METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time. RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient. CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.

Expression Quantitative Trait Locus Analysis in Systemic Sclerosis Identifies New Candidate Genes Associated With Multiple Aspects of Disease Pathology.

OBJECTIVE: To identify the genetic variants that affect gene expression (expression quantitative trait loci [eQTLs]) in systemic sclerosis (SSc) and to investigate their role in the pathogenesis of the disease. METHODS: We performed an eQTL analysis using whole-blood sequencing data from 333 SSc patients and 524 controls and integrated them with SSc genome-wide association study (GWAS) data. We integrated our findings from expression modeling, differential expression analysis, and transcription factor binding site enrichment with key clinical features of SSc. RESULTS: We detected 49,123 validated cis-eQTLs from 4,539 SSc-associated single-nucleotide polymorphisms (SNPs) (PGWAS < 10-5 ). A total of 1,436 genes were within 1 Mb of the 4,539 SSc-associated SNPs. Of those 1,436 genes, 565 were detected as having ≥1 eQTL with an SSc-associated SNP. We developed a strategy to prioritize disease-associated genes based on their expression variance explained by SSc eQTLs (r2 > 0.05). As a result, 233 candidates were identified, 134 (58%) of them associated with hallmarks of SSc and 105 (45%) of them differentially expressed in the blood cells, skin, or lung tissue of SSc patients. Transcription factor binding site analysis revealed enriched motifs of 24 transcription factors (5%) among SSc eQTLs, 5 of which were found to be differentially regulated in the blood cells (ELF1 and MGA), skin (KLF4 and ID4), and lungs (TBX4) of SSc patients. Ten candidate genes (4%) can be targeted by approved medications for immune-mediated diseases, of which only 3 have been tested in clinical trials in patients with SSc. CONCLUSION: The findings of the present study indicate a new layer to the molecular complexity of SSc, contributing to a better understanding of the pathogenesis of the disease.

Genomic Risk Score impact on susceptibility to systemic sclerosis.

OBJECTIVES: Genomic Risk Scores (GRS) successfully demonstrated the ability of genetics to identify those individuals at high risk for complex traits including immune-mediated inflammatory diseases (IMIDs). We aimed to test the performance of GRS in the prediction of risk for systemic sclerosis (SSc) for the first time. METHODS: Allelic effects were obtained from the largest SSc Genome-Wide Association Study (GWAS) to date (9 095 SSc and 17 584 healthy controls with European ancestry). The best-fitting GRS was identified under the additive model in an independent cohort that comprised 400 patients with SSc and 571 controls. Additionally, GRS for clinical subtypes (limited cutaneous SSc and diffuse cutaneous SSc) and serological subtypes (anti-topoisomerase positive (ATA+) and anti-centromere positive (ACA+)) were generated. We combined the estimated GRS with demographic and immunological parameters in a multivariate generalised linear model. RESULTS: The best-fitting SSc GRS included 33 single nucleotide polymorphisms (SNPs) and discriminated between patients with SSc and controls (area under the receiver operating characteristic (ROC) curve (AUC)=0.673). Moreover, the GRS differentiated between SSc and other IMIDs, such as rheumatoid arthritis and Sjögren's syndrome. Finally, the combination of GRS with age and immune cell counts significantly increased the performance of the model (AUC=0.787). While the SSc GRS was not able to discriminate between ATA+ and ACA+ patients (AUC<0.5), the serological subtype GRS, which was based on the allelic effects observed for the comparison between ACA+ and ATA+ patients, reached an AUC=0.693. CONCLUSIONS: GRS was successfully implemented in SSc. The model discriminated between patients with SSc and controls or other IMIDs, confirming the potential of GRS to support early and differential diagnosis for SSc.

Genome-wide whole blood transcriptome profiling in a large European cohort of systemic sclerosis patients.

OBJECTIVES: The analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations. METHODS: Samples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated. RESULTS: Overall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples. CONCLUSIONS: We discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc.

GWAS for systemic sclerosis identifies multiple risk loci and highlights fibrotic and vasculopathy pathways.

Systemic sclerosis (SSc) is an autoimmune disease that shows one of the highest mortality rates among rheumatic diseases. We perform a large genome-wide association study (GWAS), and meta-analysis with previous GWASs, in 26,679 individuals and identify 27 independent genome-wide associated signals, including 13 new risk loci. The novel associations nearly double the number of genome-wide hits reported for SSc thus far. We define 95% credible sets of less than 5 likely causal variants in 12 loci. Additionally, we identify specific SSc subtype-associated signals. Functional analysis of high-priority variants shows the potential function of SSc signals, with the identification of 43 robust target genes through HiChIP. Our results point towards molecular pathways potentially involved in vasculopathy and fibrosis, two main hallmarks in SSc, and highlight the spectrum of critical cell types for the disease. This work supports a better understanding of the genetic basis of SSc and provides directions for future functional experiments.