Negi Sapna, Juyal Garima, Senapati Sabyasachi, Prasad Pushplata, Gupta Aditi, Singh Shalini, Kashyap Sujit, Kumar Ashok, Kumar Uma, Gupta Rajiva, Kaur Satbir, Agrawal Suraksha, Aggarwal Amita, Ott Jurg, Jain Sanjay, Juyal Ramesh C, Thelma B K
National Institute of Immunology, New Delhi, India.
Arthritis Rheum. 2013 Dec;65(12):3026-35. doi: 10.1002/art.38110.
Genome-wide association studies (GWAS) and their subsequent meta-analyses have changed the landscape of genetics in rheumatoid arthritis (RA) by uncovering several novel genes. Such studies are heavily weighted by samples from Caucasian populations, but they explain only a small proportion of total heritability. Our previous studies in genetically distinct North Indian RA cohorts have demonstrated apparent allelic/genetic heterogeneity between North Indian and Western populations, warranting GWAS in non-European populations. We undertook this study to detect additional disease-associated loci that may be collectively important in the presence or absence of genes with a major effect.
High-quality genotypes for >600,000 single-nucleotide polymorphisms (SNPs) in 706 RA patients and 761 controls from North India were generated in the discovery stage. Twelve SNPs showing suggestive association (P < 5 × 10(-5)) were then tested in an independent cohort of 927 RA patients and 1,148 controls. Additional disease-associated loci were determined using support vector machine (SVM) analyses. Fine-mapping of novel loci was performed by using imputation.
In addition to the expected association of the HLA locus with RA, we identified association with a novel intronic SNP of ARL15 (rs255758) on chromosome 5 (Pcombined = 6.57 × 10(-6); odds ratio 1.42). Genotype-phenotype correlation by assaying adiponectin levels demonstrated the functional significance of this novel gene in disease pathogenesis. SVM analysis confirmed this association along with that of a few more replication stage genes.
In this first GWAS of RA among North Indians, ARL15 emerged as a novel genetic risk factor in addition to the classic HLA locus, which suggests that population-specific genetic loci as well as those shared between Asian and European populations contribute to RA etiology. Furthermore, our study reveals the potential of machine learning methods in unraveling gene-gene interactions using GWAS data.
全基因组关联研究（GWAS）及其后续的荟萃分析通过发现多个新基因改变了类风湿关节炎（RA）的遗传学研究格局。此类研究在很大程度上依赖白种人群样本，但它们仅解释了总遗传力的一小部分。我们之前对遗传背景不同的北印度RA队列的研究表明，北印度人群与西方人群之间存在明显的等位基因/遗传异质性，这使得在非欧洲人群中开展GWAS很有必要。我们开展本研究以检测其他可能在有或无主效基因情况下共同发挥重要作用的疾病相关基因座。
在发现阶段，对来自北印度的706例RA患者和761例对照进行了超过60万个单核苷酸多态性（SNP）的高质量基因分型。然后在一个由927例RA患者和1148例对照组成的独立队列中对12个显示出提示性关联（P < 5×10⁻⁵）的SNP进行检测。使用支持向量机（SVM）分析确定其他疾病相关基因座。通过填充对新基因座进行精细定位。
除了预期的HLA基因座与RA的关联外，我们还发现了5号染色体上ARL15基因一个新的内含子SNP（rs255758）与RA相关（合并P值 = 6.57×10⁻⁶；比值比1.42）。通过检测脂联素水平进行的基因型-表型相关性分析证明了这个新基因在疾病发病机制中的功能意义。SVM分析证实了这一关联以及另外一些在验证阶段基因的关联。
在北印度人群中开展的这项首次RA的GWAS研究中，除了经典的HLA基因座外，ARL15成为一个新的遗传风险因素，这表明特定人群的遗传基因座以及亚洲和欧洲人群共有的基因座都对RA病因有影响。此外，我们的研究揭示了机器学习方法在利用GWAS数据解析基因-基因相互作用方面的潜力。
