Abstract Body: Tiziano Dallavilla, Ph.D.; Giuseppe Ciconte, M.D., Ph.D.; Ph.D., Pasquale Creo, Ph.D.; Ivana Lavota, MS; Andrea Ghiroldi, Ph.D.; Zarko Calovic, M.D.; Marco Piccoli, Ph.D.; Federica Cirillo, Ph.D.; Lorenzo Menicanti, M.D., Marcello Manfredi, Ph.D., Luigi Anastasia, Ph.D, Carlo Pappone, M.D., Ph.D.

Introduction/Background:
Brugada syndrome (BrS) is an inherited channelopathy predisposing to sudden cardiac death. The molecular landscape beyond ion channel dysfunction is uncharacterized.
Research Questions/Hypothesis:
We tested the hypothesis that integrated multi-omics profiling of peripheral blood reveals coordinated molecular axes underlying BrS.
Goals/Aims:
We aimed to identify latent molecular factors characterizing Brugada syndrome through integrated multi-omics profiling of peripheral blood.
Methods/Approach:
We profiled 587 subjects (295 BrS, 292 controls) across five platforms: whole-blood RNA-seq, immune cell proteomics, plasma proteomics, metabolomics, and lipidomics (9,970 features). Multi-omics factor analysis (MOFA+) was applied for data integration; per-layer differential analysis with covariate adjustment (age, sex, batch, cell-type) identified individual features; over-representation analysis characterized enriched pathways.
Results/Data:
MOFA+ identified two disease-associated factors: a triglyceride axis (false discovery rate, FDR=0.002, effect size=-0.31) dominated by lipidomics, and an immune remodeling axis (FDR=0.023, effect size=+0.21) driven by RNA-seq. Differential analysis revealed 146 significant features across three platforms (FDR<0.05). Among 74 downregulated genes, 66 pathways were enriched, dominated by TNF/NF-kB signaling (FDR=4.1x10-6), T cell receptor signaling (FDR=0.006), and sterol metabolism (FDR=0.010). Cell-type deconvolution showed B cell depletion (rho=-0.48, n=548) with natural killer cell (rho=+0.42) and CD8+ T cell expansion (rho=+0.45), consistent with immune cell migration to cardiac tissue. Supervised classification yielded a 164-feature stable signature (area under the curve=0.673, permutation P<0.01, n=543). An apolipoprotein cluster bridged both disease axes, and haptoglobin emerged as the top biomarker candidate.
Conclusion:
In conclusion, multi-omics profiling of the largest BrS cohort to date identifies lipid dysregulation and immune remodeling as molecular hallmarks of BrS in peripheral blood, with candidate biomarkers for prospective validation.