Analytic Choices Shape Genomic Risk Estimates from Electronic Health Records: Coronary Heart Disease in eMERGE IV
Year: 2026
Type: preprint
Abstract: Background: Electronic health records (EHR) are an important data source for genomic studies, but challenges exist in ascertaining cases and observation start time. We used data derived from the Electronic Medical Records and Genomics (eMERGE) IV study to examine how analytic assumptions regarding case ascertainment and EHR entry time influence estimation of monogenic and polygenic risks for coronary heart disease (CHD). Methods: We assessed agreement between CHD cases ascertained from EHR phenotyping and survey. Associations of monogenic variants and high (top 5%) PRS of CHD were evaluated using multivariate relative risk (RR) regression under three alternative case definitions: EHR-algorithm-defined, self-reported, and combined. Time-to-event analyses (Kaplan-Meier method and Cox proportional hazards models) were conducted under three entry time specifications: (1) entry at the first EHR record, (2) entry at the start of the latest consecutive observation period, and (3) no left truncation. Results: The agreement between CHD cases ascertained by the EHR-based algorithm versus self-report was 37.2% among individuals identified as cases by at least one source, with the EHR algorithm demonstrating higher accuracy. The adjusted RR [95% confidence interval (CI)] associated with high PRS was 2.05 [1.50, 2.81] for EHR-defined, 1.49 [1.04, 2.13] for self-reported, and 1.66 [1.27, 2.18] for combined CHD. Estimated cumulative incidence by age 75 was 0.188 using the first EHR code as left truncation and 0.225 using the most recent observation period. Hazard ratio (HR) estimates were similar across the three left truncation scenarios. Conclusion: The choice of case definition meaningfully influenced RR estimates, whereas alternative specifications of EHR entry time affected absolute cumulative incidence estimates but has minimal impact on HR. These findings highlight the impact of analytical choices in EHR and survey-data-based studies that are applicable beyond the context of CHD.
Source: medRxiv
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
Awards: EHR-based Genomic Discovery and Implementation, EHR-based Genomic Risk Assessment and Management for Diverse Populations, Genomic risk in clinic care to promote health equity in New York City patients, Vanderbilt Genome-Electronic Records (VGER) Project, eMERGE IV Northwest: A partnership to evaluate the use of genomic information in the health care of diverse participants, Utilizing Polygenic Risk to Understand and Improve Outcomes: A Model For Overturning Health Disparities Through Minority-Enriched Genomics Healthcare, Northwestern Genomic Risk Assessment and Management Program, Polygenic Risk Scores for Healthier African American Families, The eMERGE Risk Assessment Network - Coordinating Center, Integrating Genomic Risk Assessment for Chronic Disease Management in a Diverse Population, eMERGE Phase IV Clinical Center at Mass General Brigham
OpenAlex ID: W7160057104