Repurposing large health insurance claims data to estimate genetic and environmental contributions in 560 phenotypes
Repurposing large health insurance claims data to estimate genetic and environmental contributions in 560 phenotypes
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DOI：
10.1038/s41588-018-0313-7
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发表时间：
2019-02-01
期刊：
影响因子：
30.8
通讯作者：
Patel, Chirag J.
中科院分区：
文献类型：
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作者：
Lakhani, Chirag M.;Tierney, Braden T.;Patel, Chirag J.
我们分析了一个大型健康保险数据集，以评估生活在美国的44，859，462人中的56，396对双胞胎和724，513对兄弟姐妹中560种疾病相关表型的遗传和环境贡献。我们估计了环境风险因素（社会经济地位（SES），空气污染和气候）在每个表型中的贡献。平均遗传力（h（2）= 0.311）和共享环境方差（c（2）= 0.088）高于归因于特定环境因素的方差，如邮政编码级别的SES（var（SES）= 0.002），每日空气质量（var（AQI）= 0.0004）和平均温度（var（temp）= 0.001）整体以及个体表型。我们发现了一些合并症的显著遗传力和共享环境（h（2）= 0.433，c（2）= 0.241）和平均月成本（h（2）= 0.290，c（2）= 0.302）。所有结果均可使用我们的双胞胎相关性和遗传力声明分析（CaTCH）网络应用程序获得。
We analysed a large health insurance dataset to assess the genetic and environmental contributions of 560 disease-related phenotypes in 56,396 twin pairs and 724,513 sibling pairs out of 44,859,462 individuals that live in the United States. We estimated the contribution of environmental risk factors (socioeconomic status (SES), air pollution and climate) in each phenotype. Mean heritability (h(2) = 0.311) and shared environmental variance (c(2) = 0.088) were higher than variance attributed to specific environmental factors such as zip-code-level SES (var(SES) = 0.002), daily air quality (var(AQI) = 0.0004), and average temperature (var(temp) = 0.001) overall, as well as for individual phenotypes. We found significant heritability and shared environment for a number of comorbidities (h(2) = 0.433, c(2) = 0.241) and average monthly cost (h(2) = 0.290, c(2) = 0.302). All results are available using our Claims Analysis of Twin Correlation and Heritability (CaTCH) web application.