👤 Lydia Coulter Kwee

Risk factor-weighted clinical likelihood (RF-CL) estimates the probability of obstructive coronary artery disease (CAD) in patients without known CAD. We examined whether adding lipoprotein(a) [Lp(a)] measurements to the RF-CL model improves predictions of obstructive CAD. In a derivation cohort (N = 4262; 54% male; mean age 58 years), the prevalence of obstructive CAD at invasive angiography with fractional flow reserve was assessed by Lp(a)-strata. On the basis of initial results, an Lp(a)-adjusted model (RF-CLLp(a)) was developed: RF-CL was multiplied by 1.5 in patients with elevated Lp(a) (≥125 nmol/L) and otherwise unchanged. Discrimination, calibration, and reclassification were compared. Findings were validated in an external validation cohort (N = 1595; 49% male; mean age 60 years) using a comparative endpoint; significant stenosis at invasive angiography or coronary computed tomography.In the derivation cohort, 473 patients (11.1%) had obstructive CAD; in the validation cohort, 206 patients (12.9%) had significant stenosis. The relative risk in patients with elevated Lp(a) was 1.51 [95% confidence interval (CI) 1.23-1.86] and 1.19 (95% CI 0.88-1.60) in the derivation and validation cohort, respectively. In the derivation cohort, the RF-CLLp(a) model showed a higher area under the receiver operating curve than the RF-CL model [0.743 (standard error 0.011) vs. 0.740 (0.013)] and better calibration in patients with elevated Lp(a). Reclassification from RF-CL to RF-CLLp(a) improved likelihood stratification in the derivation cohort but not in the validation cohort. Adding elevated Lp(a) as a risk factor to the RF-CL model improves accuracy of obstructive CAD in patients with high Lp(a). Show less

Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B. We further identified associations between AF and rare structural variants owing to deletions in CTNNA3 and duplications of GATA4. We broadly replicated our findings in independent samples from MyCode, deCODE and UK Biobank. Finally, we found that CRISPR knockout of KDM5B in stem-cell-derived atrial cardiomyocytes led to a shortening of the action potential duration and widespread transcriptomic dysregulation of genes relevant to atrial homeostasis and conduction. Our results highlight the contribution of rare coding and structural variants to AF, including genetic links between AF and cardiomyopathies, and expand our understanding of the rare variant architecture for this common arrhythmia. Show less

Hepatic de novo lipogenesis is influenced by the branched-chain α-keto acid dehydrogenase (BCKDH) kinase (BCKDK). Here, we aimed to determine whether circulating levels of the immediate substrates of BCKDH, the branched-chain α-keto acids (BCKAs), and hepatic BCKDK expression are associated with the presence and severity of nonalcoholic fatty liver disease (NAFLD). Eighty metabolites (3 BCKAs, 14 amino acids, 43 acylcarnitines, 20 ceramides) were quantified in plasma from 288 patients with bariatric surgery with severe obesity and scored liver biopsy samples. Metabolite principal component analysis factors, BCKAs, branched-chain amino acids (BCAAs), and the BCKA/BCAA ratio were tested for associations with steatosis grade and presence of nonalcoholic steatohepatitis (NASH). Of all analytes tested, only the Val-derived BCKA, α-keto-isovalerate, and the BCKA/BCAA ratio were associated with both steatosis grade and NASH. Gene expression analysis in liver samples from 2 independent bariatric surgery cohorts showed that hepatic BCKDK mRNA expression correlates with steatosis, ballooning, and levels of the lipogenic transcription factor SREBP1. Experiments in AML12 hepatocytes showed that SREBP1 inhibition lowered BCKDK mRNA expression. These findings demonstrate that higher plasma levels of BCKA and hepatic expression of BCKDK are features of human NAFLD/NASH and identify SREBP1 as a transcriptional regulator of BCKDK. Show less

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. Whole exome sequencing was performed on 8574 individuals from the CATHGEN cohort (Catheterization Genetics). Variants in 55 arrhythmia-related genes (associated with 8 disorders) were identified and assessed for pathogenicity based on American College of Genetics and Genomics/Association for Molecular Pathology criteria. Individuals carrying pathogenic/likely pathogenic (P/LP) variants were grouped by arrhythmogenic disorder and matched 1:5 to noncarrier controls based on age, sex, and genetic ancestry. Long-term phenotypic data were annotated through deep electronic health record review. Fifty-eight P/LP variants were found in 79 individuals in 12 genes associated with 5 arrhythmogenic disorders (arrhythmogenic right ventricular cardiomyopathy, Brugada syndrome, hypertrophic cardiomyopathy, In a real-world cardiovascular cohort, P/LP variants in arrhythmia-related genes were relatively common (1:108 prevalence) and most penetrant in Show less

Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85-0.92, p = 6.3 × 10 Show less