Westerman Kenneth E, Lin Joanna, Sevilla-Gonzalez Magdalena Del Rocio, Tadess Beza, Marchek Casey, Manning Alisa K
Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States.
Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States.
Front Genet. 2022 Jan 12;12:782172. doi: 10.3389/fgene.2021.782172. eCollection 2021.
Increasing evidence indicates that specific genetic variants influence the severity of outcomes after infection with COVID-19. However, it is not clear whether the effect of these genetic factors is independent of the risk due to more established non-genetic demographic and metabolic risk factors such as male sex, poor cardiometabolic health, and low socioeconomic status. We sought to identify interactions between genetic variants and non-genetic risk factors influencing COVID-19 severity a genome-wide interaction study in the UK Biobank. Of 378,051 unrelated individuals of European ancestry, 2,402 were classified as having experienced severe COVID-19, defined as hospitalization or death due to COVID-19. Exposures included sex, cardiometabolic risk factors [obesity and type 2 diabetes (T2D), tested jointly], and multiple deprivation index. Multiplicative interaction was tested using a logistic regression model, conducting both an interaction test and a joint test of genetic main and interaction effects. Five independent variants reached genome-wide significance in the joint test, one of which also reached significance in the interaction test. One of these, rs2268616 in the placental growth factor (PGF) gene, showed stronger effects in males and in individuals with T2D. None of the five variants showed effects on a similarly-defined phenotype in a lookup in the COVID-19 Host Genetics Initiative. These results reveal potential additional genetic loci contributing to COVID-19 severity and demonstrate the value of including non-genetic risk factors in an interaction testing approach for genetic discovery.
越来越多的证据表明,特定的基因变异会影响感染新冠病毒后的病情严重程度。然而,尚不清楚这些基因因素的影响是否独立于更为公认的非基因人口统计学和代谢风险因素(如男性、心脏代谢健康状况不佳和社会经济地位低下)所带来的风险。我们试图在英国生物银行中开展一项全基因组相互作用研究,以确定影响新冠病毒感染严重程度的基因变异与非基因风险因素之间的相互作用。在378,051名欧洲血统的无亲属关系个体中,2402人被归类为经历了严重的新冠病毒感染,定义为因新冠病毒感染住院或死亡。暴露因素包括性别、心脏代谢风险因素(肥胖和2型糖尿病(T2D),联合检测)以及多重剥夺指数。使用逻辑回归模型检验乘法相互作用,同时进行相互作用检验以及基因主效应和相互作用效应的联合检验。在联合检验中有五个独立变异达到全基因组显著性水平,其中一个在相互作用检验中也达到显著性水平。其中一个位于胎盘生长因子(PGF)基因中的rs2268616,在男性和患有T2D的个体中表现出更强的效应。在新冠病毒宿主遗传学倡议的一项查找研究中,这五个变异均未对类似定义的表型产生影响。这些结果揭示了可能导致新冠病毒感染严重程度的其他潜在基因位点,并证明了在基因发现的相互作用检测方法中纳入非基因风险因素的价值。