ArticleFrontiers in endocrinology2024
Assessing the causal relationship between gut microbiota and diabetic nephropathy: insights from two-sample Mendelian randomization.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Cecal microbiota regulates meat quality of Yanshan red jade broilers: insights from metagenomics and targeted metabolomics.Poultry science · 2026Article
- Gut microbiota-liver-kidney axis in diabetic kidney disease: mechanistic insights into amino acid metabolism and nutritional intervention strategies targeting natural bioactive compounds.Frontiers in nutrition · 2026Review
- Temporal Dynamics of Fecal Microbiome and Short-Chain Fatty Acids in Sows from Early Pregnancy to Weaning.Animals : an open access journal from MDPI · 2025Article
- Gut Microbiota and Their Metabolites: The Hidden Driver of Diabetic Nephropathy? Unveiling Gut Microbe's Role in DN.Journal of diabetes · 2025Review
- A review of advances in the treatment of diabetic nephropathy by modulating intestinal flora with natural products of traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- Gut microbiota dysbiosis in diabetic nephropathy: mechanisms and therapeutic targeting via the gut-kidney axis.Frontiers in endocrinology · 2025Review
- Evaluation of the growth performance, meat quality, and gut microbiota of broilers fed diets containing walnut green husk extract.Poultry science · 2024Article
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Authors and funding
6 authors at 5 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: The causal association between gut microbiota (GM) and the development of diabetic nephropathy (DN) remains uncertain. We sought to explore this potential association using two-sample Mendelian randomization (MR) analysis. Methods: Genome-wide association study (GWAS) data for GM were obtained from the MiBioGen consortium. GWAS data for DN and related phenotypes were collected from the FinngenR9 and CKDGen databases. The inverse variance weighted (IVW) model was used as the primary analysis model, supplemented by various sensitivity analyses. Heterogeneity was assessed using Cochran's Q test, while horizontal pleiotropy was evaluated through MR-Egger regression and the MR-PRESSO global test. Reverse MR analysis was conducted to identify any reverse causal effects. Results: Our analysis identified twenty-five bacterial taxa that have a causal association with DN and its related phenotypes (p < 0.05). Among them, only the Conclusions: This study established a causal association between specific GM and DN. Our findings contribute to current understanding of the role of GM in the development of DN, offering potential insights for the prevention and treatment strategies for this condition.
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