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pmid:40597902
Involvement of dysregulated RNA binding protein and alternative splicing regulatory networks in diabetic nephropathy from type 2 albuminuric cohorts.
Yu Wang · Jingjing Zhang · Qian Tang
BMC nephrology · 2025 doi:10.1186/s12882-025-04237-6
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Experiment
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Complete file
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This study aims to elucidate the role of RNA-binding proteins (RBPs) and RBP-alternative splicing (AS) regulatory networks in the pathogenesis of DN.\nMETHODS: Two RNA-seq datasets (GSE117085 and GSE142025) were retrieved from the Sequence Read Archive (SRA) database. Regulated alternative splicing events (RASEs) and genes (RASGs) of RASEs, along with differentiated RBPs, were identified. Validated differentiated RBPs were correlated with clinical features using the Nephroseq v5 online platform. Using the DN mouse model and RT-qPCR, validated the alternative splicing of RNA.\nRESULTS: Our analysis revealed 15 differentiated RBP genes and 423 RASEs in the kidney cortex of DN rats compared to controls. Enrichment analysis highlighted lipid metabolism pathways for RASGs. Seven of the identified RBPs were validated in kidney biopsy samples from DN patients versus controls. A co-deregulatory network was constructed based on dysregulated RBPs and RASEs, with select RASGs identified. In vivo experiments, compared to normal mice, the mRNA levels of RPS19 were significantly elevated in the renal tissues of DN mice, while the levels of CPEB4 and CRYZ were markedly decreased.\nCONCLUSION: In conclusion, this study provides evidence implicating dysregulated RBPs and RBP-AS regulatory networks in the development of diabetic nephropathy. The validated RBPs exhibited close associations with clinical biomarkers, reinforcing their potential as therapeutic targets for DN. These findings enhance our understanding of the molecular basis of DN and offer new insights for future research and intervention strategies.\nCLINICAL TRIAL: Not applicable.", "claims": [{"id": "claim-method", "statement": "Therefore, the Spearman correlation for each differentially expressed RBP and RASE pair was calculated, and a dysregulation network was created (Fig. 3D).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40597902", "locator": "sections[13] \"Differentially expressed RBPs are co-expressed with the alternative splicing genes\" paragraph 2", "quote": "Therefore, the Spearman correlation for each differentially expressed RBP and RASE pair was calculated, and a dysregulation network was created (Fig. 3D)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "SRA database (https://catalog.data.gov/dataset/sequence-read-archive-sra, accession number: SRP153385 and SRP237545. 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Enrichment analysis hi"], "order_basis": "paper_text_order:781", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["nline platform. Using the DN mouse model and RT-qPCR, validated the alternative splicing of RNA.", "ne platform. Using the DN mouse model and RT-qPCR, validated the alternative splicing of RNA.", "Mix II (VAZYME). Quantitative real-time PCR (RT-qPCR) was subsequently performed using the AceQ q", "II (VAZYME). Quantitative real-time PCR (RT-qPCR) was subsequently performed using the AceQ q"], "order_basis": "paper_text_order:797", "id": "assay:3"}, {"role": "analysis", "definition_id": "correlation_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["spearman_rho"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Therefore, the Spearman correlation for each differentially expressed RBP and RASE pair was calculated, and a dysregulation network was created (Fig. 3D)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}