Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes.

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-07-23 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.07.037
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.

db/db 2型糖尿病小鼠模型中糖尿病肾病的多组学特征
背景:尽管优化的血压控制和血糖管理降低了糖尿病肾病(DN)的发病率,但显著的残留风险仍然存在,提示独立于糖代谢和血流动力学紊乱的致病因素的贡献。方法:对db/db小鼠肾组织进行综合多组学分析,包括转录组学、代谢组学和脂质组学。正交投影潜结构判别分析(OPLS-DA)用于识别显著的代谢扰动,而双向O2PLS整合阐明代谢-转录组相关性。利用LINEX2重构脂质反应网络,然后进行局部拓扑探索,识别高度互联的模块。控制基因-代谢物-脂质相互作用的机制途径通过重新启动算法的随机行走推断,并通过基因集富集分析(GSEA)验证。结果:转录组学揭示了db/db代谢和脂质调节途径的广泛失调。代谢组学整合指出,甘氨酸-丝氨酸-苏氨酸(Gly-Ser-Thr)代谢中的扰动是最显著的扰动途径(P chpt1),这与组织再生能力受损显著相关。结论:这项多组学研究系统地描绘了DN发病机制的分子格局,揭示了以前未被重视的代谢扰动和不同的脂质失调模式。我们的研究结果阐明了额外血糖疾病驱动因素的机制见解,并提出了DN管理的潜在治疗靶点。
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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
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
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