近日，美国哈佛大学Alkes L. Price、Margaux L. A. Hujoel等研究人员合作，利用疾病可能性阈值模型与家族病史建立了更具关联性的预测方法。相关论文于2020年4月20日在线发表在《自然—遗传学》杂志上。

Title: Liability threshold modeling of case–control status and family history of disease increases association power

Author: Margaux L. A. Hujoel, Steven Gazal, Po-Ru Loh, Nick Patterson, Alkes L. Price

Issue&Volume: 2020-04-20

Abstract: Family history of disease can provide valuable information in case–control association studies, but it is currently unclear how to best combine case–control status and family history of disease. We developed an association method based on posterior mean genetic liabilities under a liability threshold model, conditional on case–control status and family history (LT-FH). Analyzing 12 diseases from the UK Biobank (average N=350,000) we compared LT-FH to genome-wide association without using family history (GWAS) and a previous proxy-based method incorporating family history (GWAX). LT-FH was 63% (standard error (s.e.) 6%) more powerful than GWAS and 36% (s.e. 4%) more powerful than the trait-specific maximum of GWAS and GWAX, based on the number of independent genome-wide-significant loci across all diseases (for example, 690 loci for LT-FH versus 423 for GWAS); relative improvements were similar when applying BOLT-LMM to GWAS, GWAX and LT-FH phenotypes. Thus, LT-FH greatly increases association power when family history of disease is available.

DOI: 10.1038/s41588-020-0613-6

Source: https://www.nature.com/articles/s41588-020-0613-6