Evidence map›Paper›PMID 42556871›Full record

ArticleRenal failure2026

A study on risk factors for the progression from T2DM to end-stage renal disease based on Mendelian randomization and logistic regression analysis.

Yakun Wang, Xinjia Guo, Yanhong Li, Qiyu Fu, Chong Zhang, Shoujun Bai

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Article in Renal failure, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yakun WangDepartment of Nephrology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, China.
Xinjia GuoSchool of Digital Economics, Shanghai University of Finance and Economics, Shanghai, China.
Yanhong LiSchool of Digital Economics, Shanghai University of Finance and Economics, Shanghai, China.
Qiyu FuDepartment of Nephrology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, China.
Chong ZhangDepartment of Nephrology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-9353-5359
Shoujun BaiDepartment of Nephrology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using two-sample Mendelian randomization (MR) based on GWAS data from the IEU OpenGWAS project and a retrospective clinical cohort, this study investigated risk factors for progression from type 2 diabetes mellitus (T2DM) to end-stage renal disease (ESRD) and developed a predictive model. The T2DM GWAS dataset (ebi-a-GCST010118; 2020) included 433,540 individuals (77,418 cases and 356,122 controls). Multivariable MR, with inverse variance weighted as the primary method, was used to evaluate the causal effects of metabolic and hematologic traits on ESRD, while MR-Egger and Cochran's Q test assessed pleiotropy and heterogeneity. MR-PRESSO was used for outlier removal. In parallel, 875 patients with T2DM were analyzed using univariable and multivariable logistic regression; 140 patients (16%) progressed to ESRD. MR showed that elevated body mass index (BMI) was a causal risk factor, whereas higher hematocrit was protective. In the clinical cohort, BMI, diastolic blood pressure, and creatinine were identified as independent risk factors, while albumin and hematocrit were protective. Sensitivity analyses showed no significant horizontal pleiotropy, and all instrumental variables were sufficiently strong (F-statistics >10). A logistic regression-based nomogram achieved an AUC of 0.88 (95% CI: 0.85-0.91) with good calibration and outperformed XGBoost, Random Forest, and support vector machine models. Elevated BMI and lower hematocrit increase ESRD risk in T2DM, and the nomogram may support early risk stratification and precision intervention.

Indexed as

Diabetes Mellitus, Type 2Kidney Failure, ChronicBody Mass IndexDisease ProgressionFemaleHematocritHumansLogistic ModelsMaleMendelian Randomization AnalysisMiddle AgedRetrospective StudiesRisk Factorsend stage renal diseasemachine learningMendelian randomizationrisk factorType 2 diabetes mellitus

Identifiers

PMID42556871
PMCPMC13446056

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.