Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America.
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
PLoS Genet. 2022 Apr 28;18(4):e1010113. doi: 10.1371/journal.pgen.1010113. eCollection 2022 Apr.
The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (nrs495828 = 53 and nrs505922 = 59); strongest association with venous embolism, odds ratio (ORrs495828 1.33 (p = 1.32 x 10-199), and thrombosis ORrs505922 1.33, p = 2.2 x10-265. Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10-191; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10-12. The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10-23, lupus OR 0.84, p = 3.97 x 10-06. PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10-13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.
本研究旨在利用电子健康记录 (EHR) 数据,确定 COVID-19 严重程度与现有医疗条件之间的共同遗传结构。我们使用宿主遗传计划 (Host Genetics Initiative) 的全基因组关联汇总数据,对因严重 COVID-19 而导致的危重症 (n = 35) 或住院 (n = 42) 的与遗传变异相关的进行了全基因组关联研究 (PheWAS)。PheWAS 分析使用退伍军人事务百万退伍军人计划 (MVP) 的基因型-表型数据进行。表型通过国际疾病分类 (ICD) 代码定义,这些代码通过已发表的 PheWAS 方法映射到临床相关组。在 658582 名退伍军人中,对与严重 COVID-19 相关的变异进行了测试,以在 1559 种表型中进行关联。ABO 基因座 (rs495828、rs505922) 与最多数量的表型相关(rs495828 = 53,rs505922 = 59);与静脉栓塞的关联最强,比值比 (ORrs495828 1.33(p = 1.32 x 10-199) 和血栓形成 ORrs505922 1.33,p = 2.2 x10-265。在 67 种呼吸系统疾病中,有 11 种有显著相关性,包括 MUC5B 基因座 (rs35705950) 与特发性纤维化性肺泡炎风险增加相关,比值比 2.83,p = 4.12×10-191;CRHR1(rs61667602) 与肺纤维化风险降低相关,比值比 0.84,p = 2.26×10-12。TYK2 基因座 (rs11085727) 与自身免疫性疾病风险降低相关,例如银屑病 OR 0.88,p = 6.48 x10-23,狼疮 OR 0.84,p = 3.97 x 10-06。按祖源进行的 PheWAS 分层显示了基因型-表型关联的差异。LMNA(rs581342) 与中性粒细胞减少症相关,比值比为 1.29,p = 4.1 x 10-13,在非裔和西班牙裔退伍军人中,但不在欧洲裔退伍军人中。总体而言,我们观察到 COVID-19 严重程度与严重和不良 COVID-19 结局相关的潜在危险因素之间存在共同的遗传结构。不同祖源之间的基因型-表型关联差异可能会影响到 COVID-19 观察到的异质结果。严重 COVID-19 风险与呼吸和非呼吸自身免疫性炎症疾病之间的不同关联突出了免疫宿主反应和自身免疫之间的共同途径和微妙平衡,在考虑治疗靶点时需要谨慎。