Lin Wan-Yu
Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan.
Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan.
Front Genet. 2024 Mar 7;15:1357238. doi: 10.3389/fgene.2024.1357238. eCollection 2024.
After the era of genome-wide association studies (GWAS), thousands of genetic variants have been identified to exhibit main effects on human phenotypes. The next critical issue would be to explore the interplay between genes, the so-called "gene-gene interactions" (GxG) or epistasis. An exhaustive search for all single-nucleotide polymorphism (SNP) pairs is not recommended because this will induce a harsh penalty of multiple testing. Limiting the search of epistasis on SNPs reported by previous GWAS may miss essential interactions between SNPs without significant marginal effects. Moreover, most methods are computationally intensive and can be challenging to implement genome-wide. I here searched for GxG through variance quantitative trait loci (vQTLs) of 29 continuous Taiwan Biobank (TWB) phenotypes. A discovery cohort of 86,536 and a replication cohort of 25,460 TWB individuals were analyzed, respectively. A total of 18 nearly independent vQTLs with linkage disequilibrium measure < 0.01 were identified and replicated from nine phenotypes. 15 significant GxG were found with -values <1.1E-5 (in the discovery cohort) and false discovery rates <2% (in the replication cohort). Among these 15 GxG, 11 were detected for blood traits including red blood cells, hemoglobin, and hematocrit; 2 for total bilirubin; 1 for fasting glucose; and 1 for total cholesterol (TCHO). All GxG were observed for gene pairs on the same chromosome, except for the (chromosome 11)- (chromosome 19) interaction for TCHO. This study provided a computationally feasible way to search for GxG genome-wide and applied this approach to 29 phenotypes.
在全基因组关联研究(GWAS)时代之后,已鉴定出数千种遗传变异对人类表型具有主要影响。下一个关键问题将是探索基因之间的相互作用,即所谓的“基因-基因相互作用”(GxG)或上位性。不建议对所有单核苷酸多态性(SNP)对进行详尽搜索,因为这会导致多重检验的严重惩罚。将上位性搜索限制在前瞻性GWAS报告的SNP上可能会遗漏无显著边际效应的SNP之间的重要相互作用。此外,大多数方法计算量很大,在全基因组范围内实施可能具有挑战性。我在此通过29种台湾生物银行(TWB)连续表型的方差定量性状基因座(vQTL)搜索GxG。分别分析了86,536名个体的发现队列和25,460名TWB个体的复制队列。从9种表型中鉴定并复制了总共18个连锁不平衡度量<0.01的近乎独立的vQTL。发现了15个显著的GxG,其P值<1.1E-5(在发现队列中)且错误发现率<2%(在复制队列中)。在这15个GxG中,11个是针对血液性状检测到的,包括红细胞、血红蛋白和血细胞比容;2个针对总胆红素;1个针对空腹血糖;1个针对总胆固醇(TCHO)。除了TCHO的(染色体11)-(染色体19)相互作用外,所有GxG均在同一染色体上的基因对中观察到。本研究提供了一种计算上可行的全基因组搜索GxG的方法,并将该方法应用于29种表型。