Liability threshold modeling of case-control status and family history of disease increases association power
Liability threshold modeling of case-control status and family history of disease increases association power
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DOI：
10.1038/s41588-020-0613-6
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发表时间：
2020-04-20
期刊：
影响因子：
30.8
通讯作者：
Price, Alkes L.
中科院分区：
文献类型：
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作者：
Hujoel, Margaux L. A.;Gazal, Steven;Price, Alkes L.
一种使用病例对照状态和家族史的新关联方法（LT-FH）大大增加了来自英国生物银行的12种疾病分析的关联能力。家族史可以在病例-对照关联研究中提供有价值的信息，但目前尚不清楚如何最好地将病例-对照状态和家族史结合起来。我们在责任阈值模型下开发了一种基于后验平均遗传负债的关联方法，条件是病例对照状态和家族史（LT-FH）。我们分析了来自英国生物银行（UK Biobank）的12种疾病（平均N = 35万），将LT-FH与不使用家族史的全基因组关联（GWAS）和先前基于代理的结合家族史的方法（GWAX）进行了比较。LT-FH为63%（标准误差（标准差））根据在所有疾病中独立的全基因组显著位点的数量（例如，LT-FH为690个位点，而GWAS为423个位点），比GWAS强6%，比GWAS和GWAX的性状特异性最大值强36%（即4%）；将BOLT-LMM应用于GWAS， GWAX和LT-FH表型时，相对改善相似。因此，当有家族病史时，LT-FH大大增加了关联能力。
A new association method using both case-control status and family history (LT-FH) greatly increases association power in analyses of 12 diseases from the UK Biobank.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.