PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.
PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.
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DOI：
10.1093/bioinformatics/btq126
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发表时间：
2010-05-01
期刊：
影响因子：
--
通讯作者：
Crawford DC
中科院分区：
文献类型：
--
作者：
Denny JC;Ritchie MD;Basford MA;Pulley JM;Bastarache L;Brown-Gentry K;Wang D;Masys DR;Roden DM;Crawford DC
动机：与纵向电子病历（EMR）相结合的遗传数据的出现为疾病-基因关联的全表型关联扫描（PheWAS）提供了可能性。我们提出了一种新的方法来扫描表型数据的遗传协会使用国际疾病分类（ICD 9）计费代码，这是在大多数EMR系统。我们开发了一个代码转换表，使用来自EMR数据的流行ICD 9代码自动定义776种不同的疾病人群及其控制。作为该算法的概念证明，我们对BioVU（范德比尔特的DNA生物库）中的前6005名欧洲裔美国人进行了基因分型，其中5个单核苷酸多态性（SNP）与先前报道的疾病相关：房颤、克罗恩病、颈动脉狭窄、冠状动脉疾病、多发性硬化症、系统性红斑狼疮和类风湿性关节炎。PheWAS软件为这五种SNP中的每一种生成了所有ICD 9代码组的病例和对照人群，并分析了疾病-SNP关联。这项研究的主要结果是重复七个先前已知的SNP与这些SNP的疾病相关性。结果：使用PheWAS算法的7个已知SNP-疾病关联中有4个被重复，P值在2.8 × 10−6和0.011之间。PheWAS算法还确定了这些SNP与疾病之间的19个先前未知的统计学关联，P < 0.01。这项研究表明，PheWAS分析是一种可行的方法来调查SNP-疾病的关联。需要进一步评估以确定这些关联的有效性和临床意义的适当统计阈值。可用性：PheWAS软件和代码转换表可在http://knowledgemap.mc.vanderbilt.edu/research上免费获得。联系人：josh. vanderbilt.edu
Motivation: Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease–gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European–Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP–disease associations for these SNPs. Results: Four of seven known SNP–disease associations using the PheWAS algorithm were replicated with P-values between 2.8 × 10−6 and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP–disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance. Availability:The PheWAS software and code translation table are freely available at http://knowledgemap.mc.vanderbilt.edu/research. Contact: josh.denny@vanderbilt.edu
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