Nature computational science · 2025

A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.

СтатьяПоддержка NIH: внешняя программаResearch Support, N.I.H., IntramuralНазвание и аннотация: Перевод пока не подготовлен

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Li Xihao, Chen Han, Selvaraj Margaret Sunitha, Van Buren Eric, Zhou Hufeng, Wang Yuxuan, Sun Ryan, McCaw Zachary R, Yu Zhi, Jiang Min-Zhi, DiCorpo Daniel, Gaynor Sheila M, Dey Rounak, Arnett Donna K, Benjamin Emelia J, Bis Joshua C, Blangero John, Boerwinkle Eric, Bowden Donald W, Brody Jennifer A, Cade Brian E, Carson April P, Carlson Jenna C, Chami Nathalie, Chen Yii-Der Ida, Curran Joanne E, de Vries Paul S, Fornage Myriam, Franceschini Nora, Freedman Barry I, Gu Charles, Heard-Costa Nancy L, He Jiang, Hou Lifang, Hung Yi-Jen, Irvin Marguerite R, Kaplan Robert C, Kardia Sharon L R, Kelly Tanika N, Konigsberg Iain, Kooperberg Charles, Kral Brian G, Li Changwei, Li Yun, Lin Honghuang, Liu Ching-Ti, Loos Ruth J F, Mahaney Michael C, Martin Lisa W, Mathias Rasika A, Mitchell Braxton D, Montasser May E, Morrison Alanna C, Naseri Take, North Kari E, Palmer Nicholette D, Peyser Patricia A, Psaty Bruce M, Redline Susan, Reiner Alexander P, Rich Stephen S, Sitlani Colleen M, Smith Jennifer A, Taylor Kent D, Tiwari Hemant K, Vasan Ramachandran S, Viali Satupa'itea, Wang Zhe, Wessel Jennifer, Yanek Lisa R, Yu Bing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Dupuis Josée, Meigs James B, Auer Paul L, Raffield Laura M, Manning Alisa K, Rice Kenneth M, Rotter Jerome I, Peloso Gina M, Natarajan Pradeep, Li Zilin, Liu Zhonghua, Lin Xihong

Аннотация

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits in 61,838 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered and replicated new associations with lipid traits missed by single-trait analysis.

Предметные рубрики MeSH

Humans Whole Genome Sequencing Genome-Wide Association Study Genetic Variation Phenotype Genome, Human

A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.

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Аннотация

Предметные рубрики MeSH