ArticleJournal of inflammation research2025
TIMP4 as a Potential Complementary Biomarker and Therapeutic Target in Membranous Nephropathy: A Multi-Omics Investigation with Clinical Validation.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Glomerular Diseases.Biomedicines · 2026Article
- Systematic prioritization of potential therapeutic targets for glomerulonephritis using multi-omics Mendelian randomization.PLoS computational biology · 2026Article
- Article
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Authors and funding
11 authors.
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Abstract
Background: Despite genome-wide association studies having revealed risk loci for membranous nephropathy (MN), the functional mechanisms linking genetic variants to disease pathogenesis remain poorly understood. Methods: We implemented a multi-stage analytical framework, integrating proteome-wide association studies (PWAS) and transcriptome-wide association studies (TWAS) to systematically prioritize MN-associated biomarkers. Genetic causality was rigorously established through summary data-based Mendelian randomization (SMR) and Bayesian colocalization analysis. Clinical validation was performed in a MN cohort. Additionally, single-cell transcriptomic profiling resolved cell-type-specific expression patterns of candidate targets. The therapeutic potential was further evaluated through drug target interaction and molecular docking. Results: PWAS identified three proteins associated with MN (PLA2R1, LY75, TIMP4), while TWAS of whole blood and kidney cortex tissues implicated significant associations for LY75, POLR2I, and NFKB1 in MN. TIMP4 was uniquely prioritized as a high-confidence candidate through concordant evidence from PWAS significance ( Conclusion: This study suggests TIMP4 may serve as a novel complementary biomarker and potential therapeutic target in MN. Systematic integration of multi-omics and clinical data provides promising insights for future drug development and mechanistic exploration.
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