Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang
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引用次数: 0
Abstract
Background: Despite optimized blood pressure control and glycemic management reducing the incidence of diabetic nephropathy (DN), significant residual risk remains, suggesting the contribution of pathogenic factors independent of glucose metabolism and hemodynamic disturbances.
Methods: Renal tissues from db/db mice underwent integrative multi-omics analysis, encompassing transcriptomics, metabolomics, and lipidomics. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) was applied to identify significant metabolic perturbations, while bidirectional O2PLS integration elucidated metabolic-transcriptomic correlations. Lipid reaction networks were reconstructed using LINEX2, followed by local topology exploration to identify highly interconnected modules. Mechanistic pathways governing gene-metabolite-lipid interactions were inferred via random walk with restart algorithms and validated by gene set enrichment analysis (GSEA).
Results: Transcriptomics revealed extensive dysregulation of metabolic and lipid regulatory pathways in db/db. Metabolomic integration pinpointed perturbations within glycine-serine-threonine (Gly-Ser-Thr) metabolism as the most significantly perturbed pathway (P < 0.001), with cross-omics validation identifying GLUL as a pivotal regulatory gene through. Lipidomics uncovered pronounced abnormalities in cardiolipin species composition and plasmalogen profiles. Transcriptome-lipidome integration demonstrated impaired phosphatidylcholine (PC) biosynthesis, mechanistically linked to dysregulation of choline phosphotransferase 1 (chpt1), which correlated significantly with compromised tissue regeneration capacity.
Conclusion: This multi-omics study systematically delineates the molecular landscape of DN pathogenesis, uncovering previously underappreciated metabolic perturbations and distinct lipid dysregulation patterns. Our findings elucidate mechanistic insights into extra-glycemic disease drivers and propose potential therapeutic targets for DN management.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology