Yuchang Wu, Zhongxuan Sun, Qinwen Zheng, Jiacheng Miao, Stephen Dorn, Shubhabrata Mukherjee, Jason M. Fletcher, Qiongshi Lu
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引用次数: 0
Abstract
Almost every recent Alzheimer’s disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and nonrandom participation in parental illness surveys, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that the current AD GWAX provide highly misleading genetic correlations between AD risk and higher education, which subsequently affects a variety of genetic epidemiological applications involving AD and cognition. Our study sheds light on potential issues in the design and analysis of middle-aged biobank cohorts and underscores the need for caution when interpreting genetic association results based on proxy-reported parental disease history.
几乎所有最新的阿尔茨海默病(AD)全基因组关联研究(GWAS)都进行了荟萃分析,将临床诊断为AD的研究与使用基于父母疾病史的替代表型的研究结合起来。在此,我们报告了目前通过代理进行 GWAS(GWAX)研究的主要局限性,这些局限性是由于未校正的生存偏倚和非随机参与的父母疾病调查造成的,它们导致了 AD GWAS 和 GWAX 结果之间的巨大差异。我们证明,目前的 AD GWAX 在 AD 风险与高等教育之间提供了极具误导性的遗传相关性,进而影响了涉及 AD 和认知的各种遗传流行病学应用。我们的研究揭示了中年生物库队列的设计和分析中可能存在的问题,并强调在解释基于近亲报告的父母疾病史的遗传关联结果时需要谨慎。
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