Liability threshold modeling of case-control status and family history of disease increases association power.,Nature Genetics

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Liability threshold modeling of case-control status and family history of disease increases association power.
Nature Genetics ( IF 31.7 ) Pub Date : 2020-04-20 , DOI: 10.1038/s41588-020-0613-6
Margaux L A Hujoel ₁ , Steven Gazal _{2,

3} , Po-Ru Loh _{3,

4} , Nick Patterson ₃ , Alkes L Price _{1,

2,

3}

Affiliation

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.

中文翻译：

病例对照状态和疾病家族史的责任阈值模型增加了关联力。

疾病家族史可以为病例对照关联研究提供有价值的信息，但目前尚不清楚如何最好地将病例对照状态和疾病家族史结合起来。我们开发了一种基于责任阈值模型下的后验平均遗传责任的关联方法，以病例对照状态和家族史为条件（LT-FH）。通过分析英国生物库中的 12 种疾病（平均 N = 350,000），我们将 LT-FH 与全基因组关联进行了比较，而不使用家族史 (GWAS) 和之前基于代理的结合家族史的方法 (GWAX)。根据独立的全基因组范围的数量，LT-FH 比 GWAS 更强大 63%（标准误差 (se) 6%），比 GWAS 和 GWAX 的性状特异性最大值更强大 36%（se 4%）。所有疾病的显着基因座（例如，LT-FH 有 690 个基因座，而 GWAS 有 423 个基因座）；将 BOLT-LMM 应用于 GWAS、GWAX 和 LT-FH 表型时，相对改进相似。因此，当有家族病史时，LT-FH 大大增加了关联能力。

更新日期：2020-04-24

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