MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK.
Eur J Hum Genet. 2012 Aug;20(8):857-62. doi: 10.1038/ejhg.2012.17. Epub 2012 Feb 15.
We surveyed gene-gene interactions (epistasis) in human body mass index (BMI) in four European populations (n<1200) via exhaustive pair-wise genome scans where interactions were computed as F ratios by testing a linear regression model fitting two single-nucleotide polymorphisms (SNPs) with interactions against the one without. Before the association tests, BMI was corrected for sex and age, normalised and adjusted for relatedness. Neither single SNPs nor SNP interactions were genome-wide significant in either cohort based on the consensus threshold (P=5.0E-08) and a Bonferroni corrected threshold (P=1.1E-12), respectively. Next we compared sub genome-wide significant SNP interactions (P<5.0E-08) across cohorts to identify common epistatic signals, where SNPs were annotated to genes to test for gene ontology (GO) enrichment. Among the epistatic genes contributing to the commonly enriched GO terms, 19 were shared across study cohorts of which 15 are previously published genome-wide association loci, including CDH13 (cadherin 13) associated with height and SORCS2 (sortilin-related VPS10 domain containing receptor 2) associated with circulating insulin-like growth factor 1 and binding protein 3. Interactions between the 19 shared epistatic genes and those involving BMI candidate loci (P<5.0E-08) were tested across cohorts and found eight replicated at the SNP level (P<0.05) in at least one cohort, which were further tested and showed limited replication in a separate European population (n>5000). We conclude that genome-wide analysis of epistasis in multiple populations is an effective approach to provide new insights into the genetic regulation of BMI but requires additional efforts to confirm the findings.
我们通过详尽的两两全基因组扫描,调查了四个欧洲人群(n<1200)中体重指数(BMI)的基因-基因相互作用(上位性),通过拟合具有相互作用的两个单核苷酸多态性(SNP)的线性回归模型来计算相互作用,该模型针对没有相互作用的模型进行检验。在关联检验之前,根据共识阈值(P=5.0E-08)和经过 Bonferroni 校正的阈值(P=1.1E-12),对性别和年龄进行校正,对 BMI 进行正态化和相关调整,分别在两个队列中,单个 SNP 或 SNP 相互作用均未达到全基因组显著水平。接下来,我们比较了跨队列的次全基因组显著 SNP 相互作用(P<5.0E-08),以识别共同的上位性信号,其中将 SNPs 注释到基因以测试基因本体论(GO)富集。在对共同富集 GO 术语有贡献的上位性基因中,有 19 个在研究队列中共享,其中 15 个是先前发表的全基因组关联位点,包括与身高相关的 CDH13(钙黏蛋白 13)和与循环胰岛素样生长因子 1 和结合蛋白 3 相关的 SORCS2(分选相关 VPS10 域包含受体 2)。在跨队列测试了 19 个共享上位性基因之间的相互作用以及涉及 BMI 候选基因座的相互作用(P<5.0E-08),并在至少一个队列中发现了 8 个在 SNP 水平上复制(P<0.05),在另一个欧洲人群(n>5000)中进一步测试和显示出有限的复制。我们的结论是,在多个人群中进行全基因组上位性分析是一种有效的方法,可以深入了解 BMI 的遗传调控,但需要进一步努力来证实这些发现。