Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study
Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study
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DOI：
10.1136/amiajnl-2011-000439
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发表时间：
2012-03-01
影响因子：
6.4
通讯作者：
Lowe, William L.
中科院分区：
文献类型：
--
作者：
Kho, Abel N.;Hayes, M. Geoffrey;Lowe, William L.
目的全基因组关联研究（GWAS）需要高特异性和大量受试者才能准确识别基因型-表型相关性。本研究的目的是确定2型糖尿病（T2D）病例和对照GWAS，使用通过五个机构使用不同的电子病历（EMR）系统进行常规临床护理获取的数据。材料和方法基于诊断、药物和实验室结果，开发了一种算法来识别T2D病例和对照组。该算法的性能在五个参与机构中的三个与临床医生的审查进行了验证。随后，使用算法识别的病例和对照进行了GWAS，并在所有五个机构中汇集了样本。结果与临床评价相比，该算法对糖尿病病例和对照的阳性预测值分别达到98%和100%。通过标准化和跨机构应用该算法，确定了3353例病例和3352例对照。随后的GWAS使用了来自五个机构的数据，复制了先前与T2D相关的TCF7L2基因变异（rs7903146）。通过对通过常规临床护理收集的EMR数据应用严格的标准，确定了GWAS的病例和对照，随后复制了已知的遗传变异。通过使用标准术语来定义数据元素，可以跨五个不同的机构汇集主题和数据，从而实现GWAS所需的健壮数字。结论一种利用5种不同EMR数据的算法可以准确地识别t2dm病例和对照组，用于跨多个机构的遗传研究。
Objective Genome-wide association studies (GWAS) require high specificity and large numbers of subjects to identify genotype-phenotype correlations accurately. The aim of this study was to identify type 2 diabetes (T2D) cases and controls for a GWAS, using data captured through routine clinical care across five institutions using different electronic medical record (EMR) systems.Materials and Methods An algorithm was developed to identify T2D cases and controls based on a combination of diagnoses, medications, and laboratory results. The performance of the algorithm was validated at three of the five participating institutions compared against clinician review. A GWAS was subsequently performed using cases and controls identified by the algorithm, with samples pooled across all five institutions.Results The algorithm achieved 98% and 100% positive predictive values for the identification of diabetic cases and controls, respectively, as compared against clinician review. By standardizing and applying the algorithm across institutions, 3353 cases and 3352 controls were identified. Subsequent GWAS using data from five institutions replicated the TCF7L2 gene variant (rs7903146) previously associated with T2D.Discussion By applying stringent criteria to EMR data collected through routine clinical care, cases and controls for a GWAS were identified that subsequently replicated a known genetic variant. The use of standard terminologies to define data elements enabled pooling of subjects and data across five different institutions to achieve the robust numbers required for GWAS.Conclusions An algorithm using commonly available data from five different EMR can accurately identify T2D cases and controls for genetic study across multiple institutions.