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John J Connolly

Publications and source records attributed to John J Connolly.

2 recordsLinked to original sources

Additive value of polygenic risk and family history for coronary heart disease risk stratification in two diverse US cohorts.

Whether polygenic risk, monogenic familial hypercholesterolemia (FH), and family history (FamHx) are additively informative for coronary heart disease (CHD) risk prediction across self-identified race/ethnicity (SIRE) groups has not been established. In two diverse cohorts-Electronic Medical Records and Genomics (eMERGE) phase IV (eIV; n = 19,348) and All of Us (AoU; n = 239,645)-we quantified the associations of a polygenic risk score (PRSCHD), pathogenic/likely pathogenic variants in genes associated with FH, and FamHx with CHD and evaluated their incremental value when added to the pooled cohort equations (PCEs). CHD was defined as myocardial infarction, unstable angina, or coronary revascularization. We modeled associations with multivariable logistic regression (prevalent CHD in eIV) and Cox proportional hazards (incident CHD in AoU) and characterized predictive performance with the c-statistic and reclassification and decision-curve net benefits across actionable 10-year risk thresholds. The effects of PRSCHD and FamHx were independent and additive in both cohorts and consistent across White, Black, and Latino SIRE groups. In eIV, adding PRSCHD and FamHx to the PCE increased the c-statistic for prevalent CHD from 0.719 to 0.753 (p-diff = 9.1 × 10-3) and reclassified 18.8% of participants at the 7.5% 10-year threshold, yielding approximately 4 additional true-positive CHD identifications per 1,000 screened. Net benefit gains were observed between the 7.5% and 10% thresholds across all three SIRE groups. In conclusion, PRSCHD and FamHx were independently and additively associated with CHD across major SIRE groups in two diverse cohorts in the United States (US), motivating the addition of these factors to clinical risk algorithms.

Humans

Covering medical care costs for participants in the eMERGE Network: Challenges for equity and implementation.

PURPOSE: To investigate the complexities of covering study-recommended medical care costs for individuals (in order to prevent lack of adherence due to financial reasons), which have received little attention. METHODS: We explored the deliberations, decisions, and challenges faced by the Electronic Medical Records and Genomics (eMERGE) Network during the implementation of a genomic research project recommending clinical care based on high-risk results defined largely by polygenic risk scores. Two surveys were disseminated to eMERGE sites: to identify preferences about payment for specific care recommendations (survey 1) and to understand the operational processes of covering medical care costs (survey 2). RESULTS: Paying for a subset of care recommendations for the funded study duration was identified as the most feasible approach for covering medical care costs for participants who received high-risk genomic results. Each eMERGE site, by necessity, used diverse approaches to pay for medical care costs. CONCLUSION: eMERGE researchers balanced competing concerns about bias, equity, study design, regulatory compliance, and cost in designing a unified approach to cover some of the recommended medical care costs in the study. Many implementation challenges were encountered. Findings can inform researchers and regulatory bodies about the implications and complications of covering medical care costs in translational research studies focused on prevention.

Humans