Genomics and Multi-Omics Perspectives on the Pathogenesis of Cardiorenal Syndrome

Cardiorenal syndrome (CRS) reflects bidirectional heart-kidney injury whose mechanisms extend far beyond hemodynamics. High-throughput genomics and multi-omics now illuminate the molecular circuits that couple cardiac and renal dysfunction.

We narratively synthesize animal and human studies leveraging transcriptomics, proteomics, peptidomics, metabolomics, and non-coding RNA profiling to map convergent pathways in CRS and to highlight biomarker and therapeutic implications.

Across acute and chronic CRS models, omics consistently converge on extracellular matrix (ECM) remodeling and fibrosis (e.g., FN1, POSTN, collagens), immune-inflammatory activation (IL-6 axis, macrophage/complement signatures), renin-angiotensin-aldosterone system hyperactivity, oxidative stress, and metabolic/mitochondrial derangements in both organs. Single-nucleus and bulk transcriptomes reveal tubular dedifferentiation after cardiac arrest-induced AKI and myocardial reprogramming with early CKD, while quantitative renal proteomics in heart failure demonstrates marked upregulation of ACE/Ang II and pro-fibrotic matricellular proteins despite near-normal filtration. Human translational data corroborate these signals: urinary peptidomics detects CRS-specific collagen fragments and protease activity, and circulating FN1/POSTN and selected microRNAs (notably miR-21) show diagnostic potential. Epigenetic and microRNA networks appear to integrate these axes, nominating targets such as anti-miR-21 and anti-fibrotic strategies; pathway-directed repurposing exemplifies dual-organ benefit.

Genomics and multi-omics recast CRS as a systems disease driven by intertwined fibrosis, inflammation, neurohormonal and metabolic programs. We propose a translational framework that advances (i) composite biomarker panels combining injury, fibrosis, and regulatory RNAs; (ii) precision, pathway-guided therapies; and (iii) integrated, longitudinal multi-omics of well-phenotyped CRS cohorts to enable prediction and personalized intervention.