| Introduction: Systemic lupus erythematosus (SLE) is a complex autoimmune diseasewith diverse clinical manifestations, involving multi-system and a seriouslife-threatening, which often accompanied by cancer, autoimmune diseases. Themajority of patients with life-long illness have brought great harm to their marriage,employment, and physical and mental health. The disease is more common in women ofchildbearing age (ratio of male to female for1:9), which seriously affects thereproductive health of patients; its prevalence is approximately31-70/100000in China.Etiology and pathogenesis for SLE are not clear, generally, it is considered that geneticfactors, immune abnormalities, sex hormones and environmental factors are associatedwith SLE and caused by genetic and environmental interactions, which belongs to acomplex disease with involving multi-susceptibility genesIn recent years, the development of genetic research technology and the transformof research methods, domestic and foreign scholars have done much work in geneticstudies for SLE, which found a number of valuable disease susceptibility genes, but thecurrent research is insufficient to fully clarify the pathogenesis of SLE. However, thegenome-wide association analyses also have its limitations, especially for the SNPs withlow allele frequencies or small samples, the power is still not enough. Using metaanalysis method in existing GWAS data to analysis the huge data is one of the mostcommonly used methods in post GWAS, which can improve the sample scize and thestatistical power and find more susceptibility genes/loci for complex diseases. Object: To screen SLE associated SNPs in whole genome and indetify susceptibilitygenes/loci for SLE in Chinese Han population by using GWAS meta analysis.Methods: Based on our previous SLE GWAS data (1047cases and1205controls,493,955SNPs), we combine the SLE GWAS data (612cases and2193controls,514,221SNPs) from Hong Kong University; perform imputation according to theHapMap3CHB&JPT data, and than make meta analysis in two whole genomeassociation results using METAL software. Select potentiality SNPs from meta analysisresults then validate in independent samples (1104cases and3312controls) fromChinese Han population using Sequenom and TaqMan genotype system. Combined themeta analysis results and validated results, perform linkage disequilibrium analysis andrecombination rate plot to screen susceptibility genes/loci of SLE in Chinese Hanpopulation.Results: The meta analysis of genome wide association analysis revealed association atthree loci: HLA (6p21), TNFSF4(1q25.1), STAT4(2q32.3), TNFAIP3(6q23.3),IRF5(7q32.1), BLK(8p23.1), WDFY4(10q11.23) and ETS1(11q24.3) with genome-widesignificance (P<5×10-8). Association of WDFY4, ETS1, DDX6, SLC15A4, RASGRP3,HIP1, and ZNF689/PRR14with SLE was only detected from studies on Asianpopulations.We performed a replication study by genotyping31non-MHC SNPs (P <5.0×10-4)in one additional cohort of Chinese Han. Twenty-one SNPs within11loci werevalidated with independent supporting evidence for association (P <0.05) from thereplication samples. After combined the results of meta analysis and replication,rs6804441at3q13.3and rs6705628at2p13.1reached significant evidence in thecombined sample that surpassed genome-wide significance (Pcombined<5×10-8), and,rs2785197at11p13,rs2252996at10q22.1, rs11717455at3p22.2,rs10892301at 11q23.3and rs4622329at12q23.2were seggestive associated with SLE (5.38×10-7≤Pcombined≤5.98×10-6).To identify susceptibility/candidate gene underlying each of the2novelassociations and5seggestive associations, we investigated the patterns of therecombination and LD around the risk-associated SNPs and the gene(s) located withineach region harboring the association. Only one gene was implicated by each of theassociations at2p13.1(TET3) and3q13.3(CD80), where a single gene was foundwithin the LD block harboring the association. Members of the ten-eleven translocation(TET) gene family, including TET3, play a role in the DNA methylation process. Theprotein encoded by CD80is a membrane receptor that is activated by the binding ofCD28or CTLA-4. The activated protein induces T-cell proliferation and cytokineproduction. In the genetic model analysis and genotype-phenotype analysis, theassociation of rs6705628and rs6804441were under additive model (P=2.87×10-9, P=3.97×10-21), we also found rs6705628was associated with Discoid rash (P=0.0402)and Immunological disorder (P=0.0332).The suggestive associated SNPs rs2785197(11p13) located at PDHX-CD44region,CD44might play a important role in pathogenesy of SLE by cell adhesion, chemotaxisand inflammatory reaction, genotype of rs2785197was associated with SLE with onsetage <20years (P=0.028). The suggestive associated SNPs rs2252996was a missensein exom4of SLC29A3, which might be an candidate gene within10q22.1, genotype ofrs2252996was associated with Neurological disorder in SLE cases only analysis (P=0.022). Only one gene SCN10A was in the LD block surrounding suggestive associatedSNPs rs11717455(3p22.2), and the genotype of rs11717455was associated with Malarrash (P=0.038). Multi-genes were harboring in the LD block surrounding suggestiveassociated SNPs rs10892301(11q23.3), only DDX6and CXCR5had immunological function, and associated several autoimmune diseases. In the suggestive associatedregion of rs4622329(12q23.2), DRAM1might be a candidate gene for SLE, thegenotype of rs4622329was associated with Hematologic disorder in SLE (P=0.025).Conclusion: This study was the first meta analysis of SLE GWAS, which comfirmed9previously reported susceptibility genes/loci in Chinese Han population, and identified2novel susceptibility genes/loci (TET3and CD80) as well as5seggestive genes/loci(11p13,10q22.1,3p22.2,11q23.3and12q23.2) for SLE. This study not only advancedour understanding on the genetic basis of SLE susceptibility, but also providedenlightenment for future research of SLE.
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