bioRxivGeneticsPreprint
Type 2 diabetes amplifies environmental Pb toxicity and intergenerational risk
Chen ZhangiD, Xiaoping Xia, Chen ZhangiD, Chenyu Pei, Zhixiang Guo, Guangnan Li, Liang XuiD, Huali Luo, Jiaoyan MaiD, Jingwen LuoiD, Hongyan CuiiD, Banghua HeiD, Qin LiiD, Ya-Ni ZhongiD, Haifeng ZhangiD, Xianguang YangiD, Xin Zhiguo LiiD
Abstract
Type 2 diabetes (T2D) and environmental lead (Pb) exposure intersect as prevalent global health challenges. Prior studies report elevated blood Pb in T2D, but the underlying mechanism and directionality remain unresolved. Here we show that T2D fundamentally alters Pb toxicokinetics, converting otherwise modest exposure into progressive organ injury and heritable risk. In a human cohort, elevated blood Pb in T2D specifically associated with impaired renal function rather than glycaemic control or adiposity. In db/db mice, diabetes increased oral Pb absorption through delayed gastrointestinal transit and epithelial barrier dysfunction, leading to enhanced systemic retention. With sustained exposure, renal Pb accumulation induced tubular stress that reduced effective clearance, creating a feed-forward loop in which diabetes promotes Pb retention and retained Pb accelerates kidney injury. Chronic Pb exposure exacerbated diabetic kidney injury without inducing hyperglycaemia, and short-course chelation attenuated renal stress markers. Beyond somatic toxicity, combined paternal T2D and Pb exposure programmed renal and neurobehavioral phenotypes across generations via sperm RNA. These findings redefine Pb from a passive environmental exposure to a context-dependent driver of disease, identify T2D as a vulnerability state that reshapes toxicant handling, and establish a mechanistic link between metabolic disease, environmental exposure and intergenerational risk. This work highlights the need for vulnerability-informed clinical management and environmental regulation in populations burdened by T2D.
- organism: human
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 1
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