Cardiovascular Disease Pathogenicity Predictor (CVD-PP): A Tissue-Specific In Silico Tool for Discriminating Pathogenicity of Variants of Unknown Significance in Cardiovascular Disease Genes.

Background: Interpretation of variants of uncertain significance (VUSs) remains a challenge in the care of patients with inherited cardiovascular diseases (CVDs); 56% of variants within CVD risk genes are VUS, and machine learning algorithms trained upon large data resources can stratify VUS into higher versus lower probability of contributing to a CVD phenotype.

Methods: We used ClinVar pathogenic/likely pathogenic and benign/likely benign variants from 47 CVD genes to build a predictive model of variant pathogenicity utilizing measures of evolutionary constraint, deleteriousness, splicogenicity, local pathogenicity, cardiac-specific expression, and population allele frequency. Performance was validated using variants for which the ClinVar pathogenicity assignment changed.

Towards Allograft Longevity: Leveraging Omics Technologies to Improve Heart Transplant Outcomes.

Purpose Of Review: Heart transplantation (HT) remains the optimal therapy for patients living with end-stage heart disease. Despite recent improvements in peri-transplant management, the median survival after HT has remained relatively static, and complications of HT, including infection, rejection, and allograft dysfunction, continue to impact quality of life and long-term survival.

Recent Findings: Omics technologies are becoming increasingly accessible and can identify novel biomarkers for, and reveal the underlying biology of, several disease states.

Prevalence and Phenotypic Burden of Monogenic Arrhythmias Using Integration of Electronic Health Records With Genetics.

Background: Inherited primary arrhythmia syndromes and arrhythmogenic cardiomyopathies can lead to sudden cardiac arrest in otherwise healthy individuals. The burden and expression of these diseases in a real-world, well-phenotyped cardiovascular population is not well understood.

Methods: Whole exome sequencing was performed on 8574 individuals from the CATHGEN cohort (Catheterization Genetics).

Novel plasma biomarkers improve discrimination of metabolic health independent of weight.

We sought to determine if novel plasma biomarkers improve traditionally defined metabolic health (MH) in predicting risk of cardiovascular disease (CVD) events irrespective of weight. Poor MH was defined in CATHGEN biorepository participants (n > 9300), a follow-up cohort (> 5600 days) comprising participants undergoing evaluation for possible ischemic heart disease. Lipoprotein subparticles, lipoprotein-insulin resistance (LP-IR), and GlycA were measured using NMR spectroscopy (n = 8385), while acylcarnitines and amino acids were measured using flow-injection, tandem mass spectrometry (n = 3592).

Risk Factor Burden and Long-Term Prognosis of Patients With Premature Coronary Artery Disease.

Background Coronary artery disease (CAD) is increasing among young adults. We aimed to describe the cardiovascular risk factors and long-term prognosis of premature CAD. Methods and Results Using the Duke Databank for Cardiovascular Disease, we evaluated 3655 patients admitted between 1995 and 2013 with a first diagnosis of obstructive CAD before the age of 50 years.

Epigenome-Wide Association Study for All-Cause Mortality in a Cardiovascular Cohort Identifies Differential Methylation in Castor Zinc Finger 1 ().

Background DNA methylation is implicated in many chronic diseases and may contribute to mortality. Therefore, we conducted an epigenome-wide association study (EWAS) for all-cause mortality with whole-transcriptome data in a cardiovascular cohort (CATHGEN [Catheterization Genetics]). Methods and Results Cases were participants with mortality≥7 days postcatheterization whereas controls were alive with≥2 years of follow-up.