ArticleFrontiers in endocrinology2023
Integrated multiple-microarray analysis and mendelian randomization to identify novel targets involved in diabetic nephropathy.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 19 citations in OpenAlex.
- Multiomics Integration Prioritizes ZFP36L1 as a Candidate Susceptibility Gene Associated With Inflammatory and Angiogenic Pathways in Diabetic Retinopathy.Journal of diabetes research · 2026Article
- Investigating the Biomarkers for Alzheimer's Disease: Insights from Microarray Analysis, Mendelian Randomization, and Experimental Validation.Current medicinal chemistry · 2026Article
- Immunoproteomic mediators of diabetic peripheral neuropathy: causal insights from Mendelian randomization and single-cell validation.Frontiers in immunology · 2026Article
- Identification of novel therapeutic targets for diabetic neuropathy through integrated proteomics and transcriptomics approaches.World journal of diabetes · 2025Article
- Unveiling the role of oxidative stress in ANCA-associated glomerulonephritis through integrated machine learning and bioinformatics analyses.Renal failure · 2025Article
- Causal roles of lipids and mediating proteins in diabetic retinopathy: insights from metabolomic and proteomic Mendelian randomization.Diabetology & metabolic syndrome · 2025Article
- The causal role between circulating immune cells and diabetic nephropathy: a bidirectional Mendelian randomization with mediating insights.Diabetology & metabolic syndrome · 2024Article
- Identification of novel therapeutic targets for chronic kidney disease and kidney function by integrating multi-omics proteome with transcriptome.Genome medicine · 2024Article
- The association between type 1 diabetes mellitus and the risk of immunoglobulin A nephropathy: a Mendelian randomization study.Frontiers in medicine · 2024Article
- Mendelian randomization analysis reveals causal factors behind diabetic nephropathy: evidence, opportunities, and challenges.Frontiers in endocrinology · 2024Review
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Authors and funding
3 authors at 3 institutions in 1 country.
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Abstract
Background: Diabetic nephropathy (DN), which is the main cause of renal failure in end-stage renal disease, is becoming a common chronic renal disease worldwide. Mendelian randomization (MR) is a genetic tool that is widely used to minimize confounding and reverse causation when identifying the causal effects of complex traits. In this study, we conducted an integrated multiple microarray analysis and large-scale plasma proteome MR analysis to identify candidate biomarkers and evaluate the causal effects of prospective therapeutic targets in DN. Methods: Five DN gene expression datasets were selected from the Gene Expression Omnibus. The robust rank aggregation (RRA) method was used to integrate differentially expressed genes (DEGs) of glomerular samples between patients with DN and controls, followed by functional enrichment analysis. Protein quantitative trait loci were incorporated from seven different proteomic genome-wide association studies, and genetic association data on DN were obtained from FinnGen (3676 cases and 283,456 controls) for two-sample MR analysis. External validation and clinical correlation were also conducted. Results: A total of 82 DEGs (53 upregulated and 29 downregulated) were identified through RRA integrated analysis. The enriched Gene Ontology annotations and Kyoto Encyclopedia of Genes and Genomes pathways of the DEGs were significantly enriched in neutrophil degranulation, neutrophil activation, proteoglycan binding, collagen binding, secretory granule lumen, gluconeogenesis, tricarboxylic acid cycle, and pentose phosphate pathways. MR analysis revealed that the genetically predicted levels of MHC class I polypeptide-related sequence B (MICB), granzyme A (GZMA), cathepsin S (CTSS), chloride intracellular channel protein 5, and ficolin-1 (FCN1) were causally associated with DN risk. Expression validation and clinical correlation analysis showed that MICB, GZMA, FCN1, and insulin-like growth factor 1 may participate in the development of DN, and carbonic anhydrase 2 and lipoprotein lipase may play protective roles in patients with DN. Conclusion: Our integrated analysis identified novel biomarkers, including MICB and GZMA, which may help further understand the complicated mechanisms of DN and identify new target pathways for intervention.
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