Abstract 4366327: Diagnostic Yield and Clinical Impact of Routine Genome Sequencing in Cardiovascular Patients

Abstract

Introduction/Background: Cardiovascular disease (CVD) is the leading cause of death for American adults and has a multifactorial onset including genetic factors. However, there is poor uptake of guideline-directed genetic testing, and the clinical utility of more routine genetic testing in the setting of CVD is uncertain. Research Questions/Hypothesis: Determine the diagnostic yield and clinical impact of a comprehensive clinical genome sequencing (cGS) test applied in a broad sample of typical CVD patients. Methods: A prospective, open-label, single arm, single-center clinical trial was conducted. Inclusion required a diagnosis of at least one among: cardiomyopathy/heart failure, aortopathy, arrhythmia, coronary or peripheral artery disease, or dyslipidemia. Participants (n=1000) received a CLIA/CAP certified genetic sequencing test that included: pathogenic and likely pathogenic variants from 215 CVD-associated genes, 4 common risk alleles for CVD, and 35 non-CVD ACMG secondary finding genes, as well as 65 functional pharmacogenetic alleles from 10 genes. The rate of new genetic diagnoses and changes in clinical management (medication changes, diagnostic tests, or new specialty consultation) occurring within 6 months of genetic test results were collected. Results: Of the 1000 participants, 50% were female, 39% self-identified as Black, and average age was 68 years (Table). A total of 167 participants received a monogenic or risk-allele finding (16.7%). Among these, 74 had CVD gene findings, roughly half of which were within three genes: TTR (n = 16), TTN (n = 14), and LDLR (n = 8). Non-CVD ACMG secondary findings occurred in 14 patients. Risk allele findings were reported in 100 participants. Among those with vs. without (n=833) a monogenic or risk allele finding, a change in management occurred in 27 (16.2%) compared to 16 (1.9%, p<0.0001). The most common changes made were: a radiologic test (n=16), a referral a specialist (n=13), a new genetic diagnosis (n=11), a medication change (n=8), or a lab test (n=4)[DL1] [K2] . Pharmacogenetic findings were present in >99% of patients and led to medication change recommendations in 30 patients. Conclusion(s): In this study utilization of routine genetic testing in CVD patients found functional genetic variants in ~1 in 6 patients, among whom a new genetic diagnosis or a change in management occurred in 16.2% within 6 months. Longer follow up is needed to capture the full potential impact of genetic testing.