Genome-Wide Cox Regression Analysis Identifies 134 Novel Risk Loci for Disability Development: The Canadian Longitudinal Study on Aging and UK Biobank

发布时间:2026-01-12浏览量:

论文摘要

Background: Disability significantly affects the well-being of older adults and imposes substantial personal and social burdens. Although genetic effects play a role in disability, large-scale genome-wide association studies (GWAS) of disability development remain scarce.

Methods: We performed the first Cox proportional hazards GWAS on disability development on 8,421 individuals aged 65 and older from the Canadian Longitudinal Study on Aging (CLSA). Disability was defined as the inability to perform daily activities, as measured by the Activities of Daily Living (ADL) scale. A polygenic hazard score (PHS) was developed and incorporated into the predictive model, along with demographic and environmental factors.

Results: The study observed a 16.28% incidence of disability over a mean follow-up duration of 4.64 years (SD = 1.95). The COX-GWAS identified six genome-wide significant variants (p < 5E-08) and 134 independent SNPs with suggestive significance level (p < 1E−05). Replication in the UK Biobank confirmed that rs589819, rs56294014, and rs143714258 remained nominally significant and exhibited consistent effect directions. Post-GWAS analyses, including transcriptome-wide association studies TWAS, gene set, and tissue enrichment analyses, revealed genetic pathways related to inflammation regulation, neurogenesis, and metabolic processes. Incorporating PHS with demographic and environmental factors improves the prediction performance in both CLSA and UKB.

Conclusion: This study is among the first genome-wide Cox regression analyses to uncover novel genetic loci and biological pathways involved in disability development in older adults. These findings provide a foundation for predictive modeling and targeted prevention strategies.


发表截图

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作者介绍

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郑卉萍,中国人民大学统计学院2022级博士研究生。研究方向包括老年健康遗传机制、健康预期寿命、健康不平等及人口统计模型。论文接收或发表于Demography,Journal of Gerontology Series A等期刊。


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孙韬,中国人民大学统计学院副教授,博士毕业于匹兹堡大学生物统计系。研究方向包括复杂生存数据建模、老年失能失智风险管理、基于神经网络的复杂疾病风险预测。主持国家自然科学基金青年项目和面上项目,全国统计科学研究重点项目。


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王晓军,中国人民大学吴玉章讲席教授,统计学院教授。国家统计专家咨询委员会委员,兼任中国统计教育学会副会长、国务院学位委员会统计学学科评议组召集人、全国应用统计专业学位研究生教育指导委员会秘书长、国家统计局-中国人民大学数据开发中心执行主任。主要从事人口统计、人寿保险、养老金、社会保障以及与健康相关的风险量化模型与应用研究。