Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
Genome Med. 2021 Jan 13;13(1):6. doi: 10.1186/s13073-020-00820-8.
Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations.
A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center's (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank.
Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB.
Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.
临床实验室（lab）测试在临床实践中用于诊断、治疗和监测疾病状况。测试结果存储在电子健康记录（EHR）中，越来越多的 EHR 与患者 DNA 相关联，为查询复杂疾病的遗传风险与大量人群中收集的定量生理测量之间的关系提供了前所未有的机会。
从范德比尔特大学医学中心（VUMC）的 EHR 系统中提取了 3075 项定量实验室测试，并根据我们的 QualityLab 方案进行了人群水平分析的清理。从 BioVU 提取的实验室值使用遗传力和遗传相关性分析与以前的人群研究进行了比较。然后，我们测试了这样一个假设，即生物标志物和复杂疾病的多基因风险评分与从 EHR 中提取的疾病生物标志物相关。在概念验证分析中，我们专注于脂质和冠状动脉疾病（CAD）。我们从 EHR 中提取的脂质实验室特征进行了 LabWAS，对 315 项可遗传实验室测试中的脂质和 CAD 多基因风险评分进行了全实验室关联扫描（LabWAS），然后在马萨诸塞州综合医院布里格姆生物库中复制了该管道和分析。
经过 QualityLab 清洗后的脂质值的遗传力估计值与以前的报告相当，并且脂质的多基因评分在 LabWAS 中与它们的参考脂质强烈相关。CAD 多基因评分的 LabWAS 再现了经典的心脏病生物标志物特征，包括欧洲和非洲裔人群中 HDL 降低、预先服用的 LDL、甘油三酯、血糖和糖化血红蛋白（HgbA1C）增加。值得注意的是，即使在调整了心血管疾病的存在后，其中许多关联仍然存在，并且在 MGBB 中得到了复制。
多基因风险评分可用于在基于大型 EHR 的基因组分析中识别复杂疾病的生物标志物，为在无症状个体中发现新的生物标志物和更深入地了解疾病轨迹提供了新的途径。我们提出了两种方法和相关软件，即 QualityLab 和 LabWAS，用于大规模清洁和分析 EHR 实验室，并进行全实验室关联扫描。
