P317: Clinical practice guidelines for the diagnosis, management, and surveillance of people with LMNB1 related autosomal dominant leukodystrophy: A consensus-based approach

Methods: We developed a cross-ancestry PRS model for CAD and integrated it with the Pooled Cohort Equations (PCE), a standard clinical tool used to predict the risk of atherosclerotic cardiovascular disease (ASCVD), to derive the caIRS, which estimates 10-year absolute CAD risk.We retrospectively validated the performance of the caIRS in comparison to the PCE using the diverse, US based Penn Medicine Biobank (PMBB).For prospective validation, we designed a randomized controlled clinical trial.We will recruit 1000, CAD-free participants with borderline/intermediate PCE risk (5-20%) across three large US healthcare centers.Using previously genotyped data, eligible participants will be stratified by caIRS into average (caIRS <20%) and high risk (caIRS 20%) categories and randomized into early or delayed reporting arms.Clinical genome sequencing (GS) will be performed after consent.The early reporting arm will receive their caIRS report ~2-3 months post-enrollment, while the delayed reporting arm will receive a PCE-only report initially with caIRS reported after 3 years.Participants will complete questionnaires at enrollment, post-report release, and 1-year post-enrollment to assess knowledge and behavioral impact.CAD incidence, statin use, and lab results will be tracked over 5 years and compared to evaluate the impact of caIRS on outcomes and provider behavior.Results: In the retrospective analysis of PMBB participants classified as borderline/intermediate risk using the standard PCE model (5-20%) the caIRS reclassified (20% threshold) 588 out of 6067 individuals into the high-risk group, which experienced 36.8% (95% CI: 31.3-41.8)incidence of CAD compared to 11.6% (95% CI: 10.4-12.8)incidence for all others -motivating further prospective validation study.Conclusion: Using the CAD caIRS, which combines genetic and traditional clinical risk factors, to refine clinical risk estimates has the potential to improve treatment guidance in a primary prevention setting.The results from the prospective trial will provide insights into how the integration of caIRS influences long-term cardiovascular outcomes and personalized treatment strategies.