Causal impact of elevated body mass index on diabetic kidney disease: an integrated Mendelian randomization and Global Burden of Disease Study 2021 analysis

• Published in: Renal failure Vol. 47; no. 1; p. 2472981
• Main Authors: Chen, Ye-xin, Hu, Dong-sen, Lin, Mao-xuan, Gao, Zi-heng, Hong, Han-zhang, Hu, Yu-xin, Yao, Ling-zi, Cui, Gai-wen, Wang, Lin
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 01.12.2025; Taylor & Francis Group
• Subjects: Adult; Aged; Basic Sciences Investigations; Bayes Theorem; Body Mass Index; chronic kidney disease; Diabetes Mellitus, Type 2 - complications; Diabetes Mellitus, Type 2 - epidemiology; diabetic kidney disease; Diabetic Nephropathies - epidemiology; Diabetic Nephropathies - etiology; Diabetic Nephropathies - mortality; Disability-Adjusted Life Years; elevated body mass index; Female; Global Burden of Disease - trends; Global Burden of Disease Study 2021; Global Health; Humans; Male; Mendelian Randomization; Mendelian Randomization Analysis; Middle Aged; Risk Factors; type 2 diabetes mellitus; diabetic kidney disease; type 2 diabetes mellitus; chronic kidney disease; Mendelian Randomization; Global Burden of Disease Study 2021; elevated body mass index
• ISSN: 0886-022X; 1525-6049; 1525-6049
• DOI: 10.1080/0886022X.2025.2472981

Elevated body mass index (BMI) has been implicated in the pathogenesis of diabetic kidney disease among patients with type 2 diabetes mellitus (T2DKD). However, establishing a causal relationship and quantifying the resultant global health impact remain challenging. A two-sample Mendelian randomization (MR) analysis was conducted using summary-level data obtained from the IEU database. Multiple MR approaches, including inverse variance weighted (IVW), MR-Egger regression, weighted median, weighted mode, and simple mode methods, were implemented to ensure robust causal inference. In parallel, Global Burden of Disease Study (GBD) 2021 were analyzed to determine the trends in mortality and disability-adjusted life years (DALYs) in T2DKD attributable to high BMI (HBMI-T2DKD) from 1990 to 2021. Joinpoint regression was used to estimate the average annual percent change (AAPC). Bayesian age-period-cohort (BAPC) models were then applied to project the disease burden through 2049. MR analyses provided strong evidence for a causal relationship between elevated BMI and T2DKD. The GBD analysis revealed a sustained global increase in HBMI-T2DKD burden over the past three decades. Between 1990 and 2021, the result of AAPC indicated a persistent upward trend. The burden was particularly high among older adults, with the highest impact observed in East Asia and middle Socio-Demographic Index (SDI) region. By 2049, HBMI-T2DKD-related disease burden were projected to continue rising. Elevated BMI is a significant causal risk factor for T2DKD. The integration of MR and GBD 2021 data underscores the urgent need for targeted public health interventions to reduce BMI levels, especially in high-risk regions and aging populations.