Gene-level association analysis of systemic sclerosis: A comparison of African-Americans and White populations

All authors: Olga Y. Gorlova , Yafang Li, Ivan Gorlov, Jun Ying, Wei V. Chen, Shervin Assassi, John D. Reveille, Frank C. Arnett, Xiaodong Zhou, Lara Bossini-Castillo, Elena Lopez-Isac, Marialbert Acosta-Herrera, Peter K. Gregersen, Annette T. Lee, Virginia D. Steen, Barri J. Fessler, Dinesh Khanna, Elena Schiopu, Richard M. Silver, Jerry A. Molitor, Daniel E. Furst, Suzanne Kafaja, Robert W. Simms, Robert A. Lafyatis, Patricia Carreira, Carmen Pilar Simeon, Ivan Castellvi, Emma Beltran, Norberto Ortego, Christopher I. Amos, Javier Martin, Maureen D. Mayes.Data Availability Statement: Genetic data is available from dbGaP repository (https://www.ncbi. nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_ id=phs000357.v1.p1).Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.Funding was provided to MDM by the National Institutes of Health (NIH) the National Institute of Arthritis, Musculoskeletal and Skin Diseases (NIAMS https://www.niams.nih.gov/) Centers of Research Translation (CORT) P50-AR054144, NIH grant N01-AR-02251 and R01-AR-055258, and the Department of Defense (DD) Congressionally Directed Medical Research Program (http://cdmrp.army.mil/) W81XWH-07-1-011 and WX81XWH-13-1-0452 for the collection, analysis and interpretation of the data

IRF4 Newly Identified as a Common Susceptibility Locus for Systemic Sclerosis and Rheumatoid Arthritis in a Cross-Disease Meta-Analysis of Genome-Wide Association Studies

Autoría conjunta: Spanish Scleroderma GrpObjective. Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that have similar clinical and immunologic characteristics. To date, several shared SSc-RA genetic loci have been identified independently. The aim of the current study was to systematically search for new common SSc-RA loci through an interdisease meta-genome-wide association (meta-GWAS) strategy. Methods. The study was designed as a meta-analysis combining GWAS data sets of patients with SSc and patients with RA, using a strategy that allowed identification of loci with both same-direction and opposite-direction allelic effects. The top single-nucleotide polymorphisms were followed up in independent SSc and RA case-control cohorts. This allowed an increase in the sample size to a total of 8,830 patients with SSc, 16,870 patients with RA, and 43,393 healthy controls. Results. This cross-disease meta-analysis of the GWAS data sets identified several loci with nominal association signals (P<5 x 10(-6)) that also showed evidence of association in the disease-specific GWAS scans. These loci included several genomic regions not previously reported as shared loci, as well as several risk factors that were previously found to be associated with both diseases. Follow-up analyses of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these 2 diseases (P-combined=3.29 x 10(-12)). Analysis of the biologic relevance of the known SSc-RA shared loci identified the type I interferon and interleukin-12 signaling pathways as the main common etiologic factors. Conclusion. This study identified a novel shared locus, IRF4, for the risk of SSc and RA, and highlighted the usefulness of a cross-disease GWAS meta-analysis strategy in the identification of common risk loci.Supported by a grant from the Ministerio de Educacion, Cultura y Deporte through the program FPU (to Dr. Lopez-Isac), grant 115565 from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking PRECISESADS (ref. no. 115565) and BIO-1395 from the Junta de Andalucia, grant PI-0590-2010 from the Consejeria de Salud y Bienestar Social, Junta de Andalucia, Spain (to Dr. Ortego-Centeno), a VIDI laureate from the Dutch Association of Research and Dutch Arthritis Foundation (to Dr. Radstake), and grant SAF2012-34435 from the Spanish Ministry of Economy and Competitiveness (to Dr. J. Martin). Dr. Assassi's work was supported by grants KL2-RR-024149-04 and K23-AR-061436 from the NIH, grant 3-UL1-RR-024148 from the NIH National Center for Research Resources, and grant U01-1U01AI09090 from the NIH National Institute of Allergy and Infectious Diseases. Dr. Mayes' work was supported by grant P50-AR-054144 from the NIH National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Centers of Research Translation, grant N01-AR-0-2251 from the NIAMS SSc Family Registry and DNA Repository, grant PR-1206877 from the Department of Defense, and grant R01-AR-055258 from the NIAMS.Peer reviewe

Analysis of the genetic component of systemic sclerosis in Iranian and Turkish populations through a genome-wide association study

WOS: 000459631600018PubMed ID: 30247649Objectives. SSc is an autoimmune disease characterized by alteration of the immune response, vasculopathy and fibrosis. Most genetic studies on SSc have been performed in European-ancestry populations. The aim of this study was to analyse the genetic component of SSc in Middle Eastern patients from Iran and Turkey through a genome-wide association study. Methods. This study analysed data from a total of 834 patients diagnosed with SSc and 1455 healthy controls from Iran and Turkey. DNA was genotyped using high-throughput genotyping platforms. The data generated were imputed using the Michigan Imputation Server, and the Haplotype Reference Consortium as a reference panel. A meta-analysis combining both case-control sets was conducted by the inverse variance method. Results. The highest peak of association belonged to the HLA region in both the Iranian and Turkish populations. Strong and independent associations between the classical alleles HLA-DRB1*11:04 [P = 2.10 x 10(-24), odds ratio (OR) = 3.14] and DPB1*13:01 (P = 5.37 x 10(-14), OR = 5.75) and SSc were observed in the Iranian population. HLA-DRB1*11:04 (P = 4.90 x 10(-11), OR = 2.93) was the only independent signal associated in the Turkish cohort. An omnibus test yielded HLA-DRB1 58 and HLA-DPB1 76 as relevant amino acid positions for this disease. Concerning the meta-analysis, we also identified two associations close to the genome-wide significance level outside the HLA region, corresponding to IRF5-TNPO3 rs17424921-C (P = 1.34 x 10(-7), OR = 1.68) and NFKB1 rs4648133-C (P = 3.11 x 10(-7), OR = 1.47). Conclusion. We identified significant associations in the HLA region and suggestive associations in IRF5-TNPO3 and NFKB1 loci in Iranian and Turkish patients affected by SSc through a genome-wide association study and an extensive HLA analysis.Spanish Ministry of Economy and Competitiveness [SAF2015-66761-P]; Cooperative Research Thematic Network (RETICS) program, from the Instituto de Salud Carlos III (ISCIII, Health Ministry, Madrid, Spain) [RD16/0012/0004]This work was supported by the Spanish Ministry of Economy and Competitiveness [SAF2015-66761-P to J.M. and SAF2015-66761-P to D.G.S.] and The Cooperative Research Thematic Network (RETICS) program, from the Instituto de Salud Carlos III (ISCIII, Health Ministry, Madrid, Spain) [RD16/0012/0004]

Caveolin 1 Gene Variants May Effect Disease Progression in Systemic Sclerosis Related Interstitial Lung Disease

WOS: 000370860203282

Analysis of the genetic component of systemic sclerosis in Iranian and Turkish populations through a genome-wide association study

Objectives. SSc is an autoimmune disease characterized by alteration of the immune response, vasculopathy and fibrosis. Most genetic studies on SSc have been performed in European-ancestry populations. The aim of this study was to analyse the genetic component of SSc in Middle Eastern patients from Iran and Turkey through a genome-wide association study.Methods. This study analysed data from a total of 834 patients diagnosed with SSc and 1455 healthy controls from Iran and Turkey. DNA was genotyped using high-throughput genotyping platforms. The data generated were imputed using the Michigan Imputation Server, and the Haplotype Reference Consortium as a reference panel. A meta-analysis combining both case-control sets was conducted by the inverse variance method.Results. The highest peak of association belonged to the HLA region in both the Iranian and Turkish populations. Strong and independent associations between the classical alleles HLA-DRB1*11:04 [P = 2.10 x 10(-24), odds ratio (OR) = 3.14] and DPB1*13:01 (P = 5.37 x 10(-14), OR = 5.75) and SSc were observed in the Iranian population. HLA-DRB1*11:04 (P = 4.90 x 10(-11), OR = 2.93) was the only independent signal associated in the Turkish cohort. An omnibus test yielded HLA-DRB1 58 and HLA-DPB1 76 as relevant amino acid positions for this disease. Concerning the meta-analysis, we also identified two associations close to the genome-wide significance level outside the HLA region, corresponding to IRF5-TNPO3 rs17424921-C (P = 1.34 x 10(-7), OR = 1.68) and NFKB1 rs4648133-C (P = 3.11 x 10(-7), OR = 1.47).Conclusion. We identified significant associations in the HLA region and suggestive associations in IRF5-TNPO3 and NFKB1 loci in Iranian and Turkish patients affected by SSc through a genome-wide association study and an extensive HLA analysis

Gene-level association analysis of systemic sclerosis : A comparison of African-Americans and White populations

Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans

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 Sjogren'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