A large genome-wide analysis reports that common obesity traits share, and in some cases drive, risk for diabetic kidney disease, diabetic retinopathy, and diabetic neuropathy.
The study maps shared DNA signals, tests causal links, and points to pathways that could support earlier screening and treatment across organs. The findings are published in the journal Biomolecules and Biomedicine.
Diabetes is common and chronic. High glucose over time injures small blood vessels. Damage in the kidney can lead to kidney failure. Damage in the retina can lead to vision loss.
Damage in peripheral nerves can lead to pain, numbness, and autonomic dysfunction. These problems often occur together and raise death risk. Current care reduces risk but leaves many patients with progressive disease.
The research team examined seven obesity-related traits and three microvascular complications using large genome-wide association datasets. Obesity traits included body mass index, waist-to-hip ratio, the BMI-adjusted waist-to-hip ratio, LDL-cholesterol, HDL-cholesterol, total cholesterol, and triglycerides.
Diabetic complications included kidney disease, retinopathy, and neuropathy. The analysis tested global and local genetic correlations. It scanned for pleiotropic variants that affect more than one trait. It then assessed possible causal directions using Mendelian randomization and a latent causal model.
Signals were widespread. Fifteen of 21 trait–complication pairs showed significant global genetic overlap. Local sharing clustered in 97 genomic regions. An initial set of more than 37,000 candidate pleiotropic variants was refined to 828 lead signals.
Fifty-two loci colocalized with high confidence, which suggests shared mechanisms rather than chance proximity. Causal signals were detected from body mass index to diabetic kidney disease.
Waist-to-hip measures related to retinopathy and neuropathy. HDL cholesterol influenced neuropathy in the latent causal model. The gene RPS26 appeared repeatedly across tissues. Prior work ties RPS26 to p53 signaling, a pathway that governs stress responses and cell survival.
“These shared genetic signals give us a practical map,” said study author Wei Zhang. “We can better identify which patients with obesity face higher microvascular risk. We can also see which pathways may yield cross-organ protection.”
The findings highlight mechanisms in insulin secretion, lipid metabolism, MAP kinase activity, and calcium transport. These processes regulate energy balance, inflammation, and vascular tone. That makes them plausible targets for drugs that act across kidney, retina, and nerve beds.
The work also supports clinical tools that blend standard risk factors with genetics. For example, people with high body mass index and high genetic liability could be prioritized for weight reduction, lipid control, and closer monitoring of kidney function and retinal health.
The study addresses three gaps. First, it moves beyond observational links and tests shared genetic causes. Second, it narrows thousands of signals to a set of high-confidence loci that are more actionable. Third, it flags a recurrent gene, RPS26, that may connect obesity biology to microvascular injury through p53 modulation in beta cells, kidney cells, and retinal cells.
Limits remain. Most source datasets draw from European ancestry. Transferability to other groups needs testing. Causal estimates depend on valid instruments and the absence of unmeasured pleiotropy, which is hard to prove.
Colocalization does not confirm the exact causal variant or gene. Functional studies are required to verify which nodes are druggable and safe to target. Clinical value will depend on prospective validation and real-world implementation.
The authors propose three next steps. First, expand to multi-ancestry studies to improve generalizability and fine-map causal variants. Second, integrate transcriptomic and proteomic data from the kidney, retina, and nerve to connect variants to pathways and cell types.
Third, test RPS26–p53 and related nodes in cell and animal models to see if modulation protects microvasculature without harmful effects. Parallel work can build genetics-informed risk tools to guide screening intervals, lipid goals, and weight-loss strategies, including lifestyle and surgical options when indicated.
If replicated, these results suggest a coordinated prevention approach. Treat obesity early and with intent. Monitor kidneys, eyes, and nerves with genetic risk in mind. Target shared pathways rather than isolated organs when feasible. Such a strategy could delay or reduce the burden of kidney failure, vision loss, and neuropathy in people with diabetes.
If you care about diabetes, please read studies about Potatoes: friend or foe in the battle against diabetes? and findings of This blood pressure drug may protect kidney health in people with diabetes.
For more about diabetes, please read studies about Scientists find a promising treatment for type 2 diabetes and findings of Certain type 2 diabetes treatment may bring heart risks.
The study is published in Biomolecules and Biomedicine.
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