Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk

IF 31.7 1区生物学 Q1 GENETICS & HEREDITY

Nature genetics Pub Date : 2023-10-09 DOI:10.1038/s41588-023-01522-8

Xilin Jiang, Martin Jinye Zhang, Yidong Zhang, Arun Durvasula, Michael Inouye, Chris Holmes, Alkes L. Price, Gil McVean

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Abstract

The analysis of longitudinal data from electronic health records (EHRs) has the potential to improve clinical diagnoses and enable personalized medicine, motivating efforts to identify disease subtypes from patient comorbidity information. Here we introduce an age-dependent topic modeling (ATM) method that provides a low-rank representation of longitudinal records of hundreds of distinct diseases in large EHR datasets. We applied ATM to 282,957 UK Biobank samples, identifying 52 diseases with heterogeneous comorbidity profiles; analyses of 211,908 All of Us samples produced concordant results. We defined subtypes of the 52 heterogeneous diseases based on their comorbidity profiles and compared genetic risk across disease subtypes using polygenic risk scores (PRSs), identifying 18 disease subtypes whose PRS differed significantly from other subtypes of the same disease. We further identified specific genetic variants with subtype-dependent effects on disease risk. In conclusion, ATM identifies disease subtypes with differential genome-wide and locus-specific genetic risk profiles. Age-dependent topic modeling provides a low-rank representation of longitudinal disease records and identifies diseases with heterogeneous comorbidity profiles, defining subtypes that exhibit distinct genome-wide and locus-specific association patterns.

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英国生物库对合并症的年龄依赖性主题建模确定了具有不同遗传风险的疾病亚型。

对电子健康记录（EHR）纵向数据的分析有可能改善临床诊断，实现个性化医疗，从而推动从患者共病信息中识别疾病亚型的努力。在这里，我们介绍了一种与年龄相关的主题建模（ATM）方法，该方法在大型EHR数据集中提供了数百种不同疾病的纵向记录的低秩表示。我们将ATM应用于282957个英国生物库样本，确定了52种具有异质共病特征的疾病；对211908份All of Us样本的分析得出了一致的结果。我们根据52种异质性疾病的共病特征定义了它们的亚型，并使用多基因风险评分（PRS）比较了不同疾病亚型的遗传风险，确定了18种PRS与同一疾病的其他亚型显著不同的疾病亚型。我们进一步确定了对疾病风险具有亚型依赖性影响的特定遗传变异。总之，ATM识别具有不同全基因组和位点特异性遗传风险谱的疾病亚型。

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

Nature genetics 生物-遗传学

CiteScore

43.00

自引率

2.60%

发文量

241

审稿时长

3 months

期刊介绍： Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution