bioRxivBioinformaticsPreprint
Multi-Omics Integration Reveals Lipid Metabolic Reprogramming as a Driver of Cystogenesis in Autosomal Dominant Polycystic Kidney Disease (ADPKD)
Gökmen ZararsıziD, Leila KianmehriD, Alparslan DemirayiD, Ahu CepheiD, Halef Okan DoğaniD, Vahap EldemiD, Salih Güntuğ ÖzaytürkiD, Kadir DemirkutluiD, Serpil TaheriiD, Gözde Ertürk ZararsıziD, Necla KoçhaniD, Onur ŞenoliD, İsmail KoçyiğitiD, Enrico GlaabiD
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is a most common hereditary kidney disorder and a major contributor to end-stage kidney disease (ESKD), but its molecular progression mechanisms are unclear. We performed metabolomic and transcriptomic profiling on a longitudinal cohort of 254 and 47 ADPKD patients, respectively, to identify molecular alterations and then applied Multi-Omics Factor Analysis (MOFA) to uncover coordinated signatures. Disease progression was associated with a marked shift in dysregulated lipids profile, increased acylcarnitines, and increased glycolytic metabolites, suggesting a shift from fatty acid oxidation (FAO) toward glycolysis. Transcriptomic analysis revealed enrichment of PPAR signaling, cytoskeletal remodeling, and cystogenesis, providing a mechanistic link between metabolic alterations and structural dysregulation. Integrative analysis identified a central axis where inflammation, metabolic reprogramming, and cytoskeletal remodeling converges. Our integrated multi-omics analysis defines a molecular framework where transcriptomic dysregulation drives metabolic reprogramming contribute to cystogenesis, providing potential biomarkers and insights to guide precision therapy in ADPKD progression. Lay SummaryThe clinical heterogeneity of ADPKD limits current prognostic tools for early disease progression, often delaying therapeutic intervention. This study integrates longitudinal clinical data with multi-omics profiling (whole-blood transcriptomics and plasma metabolomics) in a large ADPKD cohort using Multi-Omics Factor Analysis. This approach identified coordinated molecular signatures linking aberrant gene expression and metabolic reprogramming directly to disease progression, hypertension, and mortality status. These findings uncover novel mechanistic drivers of ADPKD and suggest biomarkers to enhance early risk stratification, supporting the development of precision medicine strategies.
- organism: human
- assay: metabolomics
- assay: bulk RNA-seq
- research focus: benchmarking
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- Citations
- 1
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