Lin, Ting‐Tse

Background Right ventricular (RV) maladaptation to elevated pulmonary afterload is the primary determinant of outcomes in pulmonary artery (PA) hypertension; however, the pathobiological mechanisms underlying RV decompensation remain poorly understood. Methods We performed global untargeted metabolomics on plasma from 55 patients who underwent gold‐standard RV‐PA coupling measurements using multibeat pressure volume loop assessment in a single‐center cohort and from 1027 patients with coupling surrogate measurements in a larger multicenter cohort, the PVDOMICS (Pulmonary Vascular Disease Phenomics) study. Age and sex‐adjusted linear regression was performed to identify associations between metabolites and coupling metrics. Additionally, we performed a metabolic flux analysis using gene expression data from RV tissue in an independent cohort of 32 patients. Partial least squares–discriminant analysis was used to identify metabolites and reactions characteristic of the decompensated RV. Results RV‐PA coupling was negatively associated with tricarboxylic acid (TCA) cycle intermediate levels. Specifically, plasma α‐ketoglutarate and fumarate were significantly associated with all coupling metrics in both cohorts. Metabolic flux analysis indicated that decompensated RVs exhibited aberrant TCA cycle activity, including reduced acetyl coenzyme A entry and increased lactate elimination, suggesting a shift from the TCA cycle toward glycolysis at the RV tissue level. Conclusions We identify an association between circulating TCA cycle intermediate levels and RV‐PA uncoupling in 2 independent cohorts, and dysregulated TCA cycle metabolism in decompensated PA hypertension RVs, suggesting that aberrant TCA cycle metabolism could represent a hallmark of RV maladaptation in PA hypertension. Further study of this pathway is warranted to develop novel biomarkers of RV function or RV‐targeted therapies.

Background: Brugada syndrome (BrS) is an oligogenic arrhythmic disease with increased risk of sudden cardiac arrest. Several BrS or ECG traits-related single-nucleotide polymorphisms (SNPs) were identified through previous genome-wide association studies in white patients. We aimed to validate these SNPs in BrS patients in the Taiwanese population, assessing the cumulative effect of risk alleles and the BrS-polygenic risk score in predicting cardiac events. Methods: We genotyped 190 unrelated BrS patients using the TWB Array, and Taiwan Biobank was used as controls. SNPs not included in the array were imputed by IMPUTE2. Cox proportional hazards model was used to evaluate the associations between each particular SNP, the collective BrS-polygenic risk score, and clinical outcomes. Results: Of the 88 previously reported SNPs, 22 were validated in Taiwanese BrS patients ( P <0.05). Of the 22 SNPs, 2 (rs10428132 and rs9388451) were linked with susceptibility to BrS, 10 were SNPs previously reaching genome-wide significance, and 10 were SNPs associated with ECG traits. For the 3 most commonly reported SNPs, disease risk increased consistently with the number of risk alleles (odds ratio, 3.54; P trend =1.38×10 −9 for 5 risk alleles versus 1). Similar patterns were observed in both SCN5A mutation+ (odds ratio, 3.66; P trend =0.049) and SCN5A mutation− (odds ratio, 3.75; P trend =8.54×10 −9 ) subgroups. Furthermore, BrS patients without SCN5A mutations had more risk alleles than BrS patients with SCN5A mutations regardless of the range of polygenic risk scores. Three SNPs (rs4687718, rs7784776, and rs2968863) showed significant associations with the composite outcome (sudden cardiac arrest plus syncope, hazard ratio, 2.13, 1.48, and 0.41; P =0.02, 0.006, and 0.008, respectively). Conclusions: Our findings suggested that some SNPs associated with BrS or ECG traits exist across multiple populations. The cumulative risk of the BrS-related SNPs is similar to that in white BrS patients, but it appears to correlate with the absence of SCN5A mutations.