ArticleBMC medicine2023
Identification of genetic variants associated with diabetic kidney disease in multiple Korean cohorts via a genome-wide association study mega-analysis.
Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 16 citations in OpenAlex.
- Gene modification: Exploring the potential in treating kidney diseases.Pharmacological research · 2026Review
- Identification of novel genomic variants in diabetic nephropathy patients using whole-exome sequencing: a pilot investigation.Frontiers in endocrinology · 2026Article
- Genome-Wide Association Studies of Diabetic Kidney Disease in East Asians With Type 2 Diabetes: Achievements and Future Perspectives.Current medicinal chemistry · 2026Review
- Transcriptome-wide association study revealed novel causal genes of renal-biopsy proven diabetic nephropathy.Genome medicine · 2025Article
- Differential methylation in blood pressure control genes is associated to essential hypertension in African Brazilian populations.Epigenetics · 2025Article
- Heterogeneity in the development of diabetes-related complications: narrative review of the roles of ancestry and geographical determinants.Diabetologia · 2025Review
- Biomarker Discovery for Metabolic Dysfunction-associated Steatotic Liver Disease Utilizing Mendelian Randomization, Machine Learning, and External Validation.Journal of clinical and translational hepatology · 2025Article
- Multimodal analysis stratifies genetic susceptibility and reveals the pathogenic mechanism of kidney injury in diabetic nephropathy.Cell reports. Medicine · 2025Article
- Insights into the molecular underpinning of type 2 diabetes complications.Human molecular genetics · 2025Review
- Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025Review
- Genomics in Diabetic Kidney Disease: A 2024 Update.Current genomics · 2024Article
- Finerenone: From the Mechanism of Action to Clinical Use in Kidney Disease.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Prevalence of chronic kidney disease in Tunisian diabetics: the TUN-CKDD survey.BMC nephrology · 2024Observational
- Epigenetic link between Agent Orange exposure and type 2 diabetes in Korean veterans.Frontiers in endocrinology · 2024Article
- Pathomechanisms of Diabetic Kidney Disease.Journal of clinical medicine · 2023Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe pathogenesis of diabetic kidney disease (DKD) is complex, involving metabolic and hemodynamic factors. Although DKD has been established as a heritable disorder and several genetic studies have been conducted, the identification of unique genetic variants for DKD is limited by its multiplex classification based on the phenotypes of diabetes mellitus (DM) and chronic kidney disease (CKD). Thus, we aimed to identify the genetic variants related to DKD that differentiate it from type 2 DM and CKD.
methodsWe conducted a large-scale genome-wide association study mega-analysis, combining Korean multi-cohorts using multinomial logistic regression. A total of 33,879 patients were classified into four groups-normal, DM without CKD, CKD without DM, and DKD-and were further analyzed to identify novel single-nucleotide polymorphisms (SNPs) associated with DKD. Additionally, fine-mapping analysis was conducted to investigate whether the variants of interest contribute to a trait. Conditional analyses adjusting for the effect of type 1 DM (T1D)-associated HLA variants were also performed to remove confounding factors of genetic association with T1D. Moreover, analysis of expression quantitative trait loci (eQTL) was performed using the Genotype-Tissue Expression project. Differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus database (GSE30529). The significant eQTL DEGs were used to explore the predicted interaction networks using search tools for the retrieval of interacting genes and proteins.
resultsWe identified three novel SNPs [rs3128852 (P = 8.21×10
conclusionsWe successfully identified SNPs (rs3128852, rs117744700, and rs28366355) associated with DKD and verified the causal association between rs3128852 and DKD. According to the in silico analysis, TRIM27 and HLA-A can define DKD pathophysiology and are associated with immune response and autophagy. However, further research is necessary to understand the mechanism of immunity and autophagy in the pathophysiology of DKD and to prevent and treat DKD.
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