Multi-omics analysis of human right atrial tissue ıdentifies molecular signatures of remodeling in tricuspid regurgitation.

BACKGROUND

Tricuspid regurgitation (TR) is associated with adverse clinical outcomes, yet the underlying right atrial (RA) molecular remodeling remains poorly understood. We aimed to define TR-associated RA remodeling using metabolomic and lipidomic profiling of human RA tissue.

METHODS

RA appendage tissue was obtained intraoperatively from 24 adults undergoing cardiac surgery (11 with ≥severe TR; 13 controls). Gas chromatography mass spectrometry (GC-MS) was used for targeted small-molecule metabolomics, and liquid chromatography quadrupole time of flight mass spectrometry (LC-qTOF-MS) for untargeted lipidomics. Mann Whitney U testing, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and variable importance in projection (VIP) scoring were used to identify discriminatory multi-omics patterns between groups.

RESULTS

Patients with TR demonstrated a distinct metabolic phenotype characterized by reduced glycolysis-related intermediates (glucose-6-phosphate, β-alanine, α-glucosamine-1-phosphate; all p < 0.05) and metabolites consistent with oxidative stress and amino acid catabolism markers (6-hydroxycaproic acid, porphine, phosphoric acid; all p < 0.05). Lipidomic analysis revealed broad phospholipid remodeling and signals consistent with mitochondrial-associated alterations, including a decreased phosphatidylcholine/phosphatidylethanolamine (PC/PE) ratio and reductions in selected diacylglycerol and ceramide species. PCA and PLS-DA demonstrated clear group separation with consistent VIP signals, indicating consistent multi-omics discrimination.

CONCLUSIONS

TR is associated with coordinated metabolic and lipidomic reprogramming in the RA, a pattern compatible with, though not direct evidence of, mitochondrial stress, impaired bioenergetics, and membrane destabilization. These findings support a model in which RA remodeling is tightly linked to TR pathophysiology, highlighting candidate molecular features for future validation. Multi-omics biomarkers may enhance risk stratification, inform the timing of intervention, and guide the development of future point-of-care molecular diagnostics.