Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank

IF 1.7 4区医学 Q3 GENETICS & HEREDITY

Genetic Epidemiology Pub Date : 2023-01-24 DOI:10.1002/gepi.22515

Zihuan Liu, Wei Dai, Shiying Wang, Yisha Yao, Heping Zhang

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引用次数: 0

Abstract

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10⁻⁹) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10⁻⁸) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

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深度学习在英国生物银行(UK Biobank)的28,097例受影响病例中发现了与covid -19相关死亡率的遗传变异

对宿主遗传成分的分析可以深入了解对病毒感染的易感性和反应，例如导致2019冠状病毒病(COVID-19)的严重急性呼吸综合征冠状病毒2 (SARS-CoV-2)。为了揭示COVID-19相关死亡率易感性的遗传决定因素，我们训练了一个深度学习模型，利用英国生物银行(UK Biobank)的数据(28,097例受影响病例和1656例死亡)来识别导致COVID-19相关死亡率风险的遗传变异组及其相互作用。我们把这样的变体组称为超级变体。我们确定了15个具有不同程度显著性的超级变异，作为COVID-19死亡率的易感性位点。具体来说，我们在7号染色体上发现了一个超级变异(优势比[OR] = 1.594, p = 5.47 × 10−9)，由rs76398985、rs6943608、rs2052130、7:150989011_CT_C、rs118033050和rs12540488等小等位基因组成。我们还在5号染色体上发现了一个超级变异(OR = 1.353, p = 2.87 × 10−8)，包含rs12517344、rs72733036、rs190052994、rs34723029、rs72734818、5:9305797_GTA_G和rs180899355。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genetic Epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

4.40

自引率

9.50%

发文量

审稿时长

6-12 weeks

期刊介绍： Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations. Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.