👤 Amy R Kontorovich

Coronary artery disease (CAD) is a complex, heterogeneous disease with distinct etiological mechanisms. These different etiologies may give rise to multiple subtypes of CAD that could benefit from alternative preventions and treatments. However, so far, there have been no systematic efforts to predict CAD subtypes using clinical and genetic factors. Here, we trained and applied statistical models incorporating clinical and genetic factors to predict CAD subtypes in 26 036 patients with CAD in the UK Biobank. We performed external validation of the UK Biobank models in the US-based All of Us cohort (8598 patients with CAD). Subtypes were defined as high versus normal LDL (low-density lipoprotein) levels, high versus normal Lpa (lipoprotein A) levels, ST-segment-elevation myocardial infarction versus non-ST-segment-elevation myocardial infarction, occlusive versus nonocclusive CAD, and stable versus unstable CAD. Clinical predictors included levels of ApoA, ApoB, HDL (high-density lipoprotein), triglycerides, and CRP (C-reactive protein). Genetic predictors were genome-wide and pathway-based polygenic risk scores (PRSs). Results showed that both clinical-only and genetic-only models can predict CAD subtypes, while combining clinical and genetic factors leads to greater predictive accuracy. Pathway-based PRSs had higher discriminatory power than genome-wide PRSs for the Lpa and LDL subtypes and provided insights into their etiologies. The 10-pathway PRS most predictive of the LDL subtype involved cholesterol metabolism. Pathway PRS models had poor generalizability to the All of Us cohort. In summary, we present the first systematic demonstration that CAD subtypes can be distinguished by clinical and genomic risk factors, which could have important implications for stratified cardiovascular medicine. Show less

Few reports describe the yield of postmortem genetic testing from medical examiners' offices or correlate genetic test results with autopsy-confirmed phenotypes from a large cohort. To report results from cardiomyopathy- and cardiac arrhythmia-associated genetic testing in conjunction with autopsy findings of cases investigated at the United States' largest medical examiner office. Postmortem cases tested from 2015 to 2022 with a cardiomyopathy- and cardiac arrhythmia-associated gene panel were reviewed. American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines were used to classify variant pathogenicity. Correlations of pathogenic/likely pathogenic variants (P/LPVs) with cardiac pathology were evaluated. The cohort included 1107 decedents of diverse ages and ethnicities. P/LPVs were detected in 87 (7.9%) cases, with 73 and 14 variants in cardiomyopathy and cardiac arrhythmia genes, respectively. Variants of uncertain significance were detected in 437 (39.5%) cases. The diagnostic yield (percentage of P/LPV) in decedents with cardiomyopathy (26.1%) was significantly higher than those without (P<.0001). The diagnostic yield was significantly lower in infants (0.7%) than older age groups (ranging from 1 to 74 years old, 5.7%-25.9%), which had no statistical difference between their yields. The diagnostic yields by cardiac autopsy findings were 54.0% for hypertrophic cardiomyopathy, 47.1% for arrhythmogenic cardiomyopathy, 20.0% for myocardial fibrosis, 19.0% for dilated cardiomyopathy, and 11.3% for myocarditis. Most P/LPVs were in MYBPC3, TTN, PKP2, SCN5A, MYH7, and FLNC. Ten P/LPVs were novel. Our results support the importance of performing postmortem genetic testing on decedents of all ages with cardiomyopathy, cardiac lesions insufficient to diagnosis a specific cardiomyopathy (e.g., myocardial fibrosis), and myocarditis. Combined postmortem cardiac examination and genetic analysis are advantageous in accurately determining the underlying cause of death and informing effective clinical care of family members. Show less