Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are typically stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between clinical lab tests and genetics. Clinical lab data, however, are of uneven quality, and previous studies have focused on a small number of lab traits. We present two methods, QualityLab and LabWAS, to clean and analyze EHR labs at scale in a Lab-Wide Association Scan. In a proof of concept analysis focused on blood lipids and coronary artery disease, we found that heritability estimates of QualityLab lipid values were comparable to previous reports; polygenic scores for lipids were strongly associated with the referent lipid in a LabWAS; and a LabWAS of a polygenic score for coronary artery disease recapitulated known heart disease biomarker profiles and identified novel associations. Our methods extend previous EHR-based analysis tools and increase the amount of EHR data usable for discovery.

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