新方法有助實現全基因組測序研究中稀有變異的關聯分析
作者：
小柯機器人發布時間：2020/8/25 14:12:14
動態整合多個計算功能注釋可實現大規模全基因組測序研究中稀有變異（RVs）的關聯分析，這一成果由哈佛大學陳曾熙公共衛生學院Pradeep Natarajan課題組經過不懈努力而取得。2020年8月24日出版的《自然-遺傳學》雜誌發表了這一研究成果。
研究人員設計了STAAR（使用注釋信息進行關聯的變量集測試），這是一種可擴展且功能強大的RV關聯測試方法，可使用動態加權有效地合併變體類別和多個互補註釋。對於後者，研究人員研發了「注釋主要組件」，即計算機模擬變體注釋的多維摘要。STAAR解決了人口結構和相關性問題，可擴展用於分析連續和二分性狀的超大型隊列和生物庫全基因組測序研究。
研究人員利用STAAR在Trans-Omics for Precision Medicine計劃包含的12,316個發現樣本和17,822個複製樣本中鑑別了與四個脂質性狀相關的RV。研究發現並複製了新的RV關聯，包括NPC1L1的破壞性錯義RV和APOC1P1附近一個與低密度脂蛋白膽固醇相關的基因間區域。
據了解，大規模全基因組測序研究能夠分析與複雜表型相關的稀有變異。常用的RV關聯測試範圍有限，無法利用各種功能。
附：英文原文
Title: Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale
Author: Xihao Li, Zilin Li, Hufeng Zhou, Sheila M. Gaynor, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K. Arnett, Stella Aslibekyan, Christie M. Ballantyne, Lawrence F. Bielak, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jai G. Broome, Matthew P. Conomos, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Barry I. Freedman, Xiuqing Guo, George Hindy, Marguerite R. Irvin, Sharon L. R. Kardia, Sekar Kathiresan, Alyna T. Khan, Charles L. Kooperberg, Cathy C. Laurie, X. Shirley Liu, Michael C. Mahaney, Ani W. Manichaikul, Lisa W. Martin, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, May E. Montasser, Jill E. Moore, Alanna C. Morrison, Jeffrey R. OConnell, Nicholette D. Palmer, Akhil Pampana, Juan M. Peralta, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Kenneth M. Rice, Stephen S. Rich, Jennifer A. Smith, Hemant K. Tiwari, Michael Y. Tsai, Ramachandran S. Vasan, Fei Fei Wang, Daniel E. Weeks, Zhiping Weng, James G. Wilson, Lisa R. Yanek, Benjamin M. Neale, Shamil R. Sunyaev, Gonalo R. Abecasis, Jerome I. Rotter, Cristen J. Willer, Gina M. Peloso, Pradeep Natarajan
Issue&Volume: 2020-08-24
Abstract: Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 『annotation principal components』, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
DOI: 10.1038/s41588-020-0676-4
Source: https://www.nature.com/articles/s41588-020-0676-4