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<p>Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals commonly found in consumer products. Despite growing concern over their health effects, their associations with chronic diseases in humans are still unclear. We included 10,093 participants to examine the associations between 8 PFAS and 40 chronic diseases. Multivariable logistic regression and restricted cubic spline (RCS) models were applied to evaluate linear and nonlinear associations, and mixture effects were further assessed using weighted quantile sum regression (WQS), quantile-based g-computation (q g‑comp), and Bayesian kernel machine regression (BKMR). Overall, we identified 16 significant PFAS-chronic disease associations after false discovery rate (FDR) correction, involving 7 PFAS and 6 chronic diseases. Specifically, each 1 ng/mL increase in perfluoroundecanoic acid (PFUnA) was associated with higher odds of heart attack (OR = 1.32, <i>P</i><sub>FDR</sub> = 0.032), coronary heart disease (OR = 1.31, <i>P</i><sub>FDR</sub> = 0.040), and non-melanoma cancer (OR = 1.22, <i>P</i><sub>FDR</sub> = 0.046). Non-linear analyses showed that, 6 PFAS were significantly associated with colorectal cancer. PFAS mixture analyses consistently indicated increased risks of cardiovascular diseases, hypertension, high cholesterol, and metabolic dysfunction. Perfluorononanoic acid (PFNA) was identified as the dominant contributor to the positive mixture effect (31.8–52.7%), as evidenced by several machine learning methods. Our findings provide important evidence of associations between PFAS exposure and multiple chronic diseases, and may contribute to the development of precision management strategies for chronic diseases prevention.</p>

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Associations of serum per- and polyfluoroalkyl substances (PFAS) mixture with the risk of chronic diseases: evidence from single‑ , multi-pollutant, and machine learning models

  • 期刊论文

  • 发表日期：

    2026年6月2日

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  • Mei Li,
  • Liting Sheng,
  • Zige Ding,
  • Guangsheng Yu,
  • Yichu Chen,
  • Qitian Chen,
  • Wei Shao,
  • Bingxin Liu,
  • Mulong Du,
  • Dongying Gu,
  • Silu Chen,
  • Junyi Xin,
  • Meilin Wang

摘要

Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals commonly found in consumer products. Despite growing concern over their health effects, their associations with chronic diseases in humans are still unclear. We included 10,093 participants to examine the associations between 8 PFAS and 40 chronic diseases. Multivariable logistic regression and restricted cubic spline (RCS) models were applied to evaluate linear and nonlinear associations, and mixture effects were further assessed using weighted quantile sum regression (WQS), quantile-based g-computation (q g‑comp), and Bayesian kernel machine regression (BKMR). Overall, we identified 16 significant PFAS-chronic disease associations after false discovery rate (FDR) correction, involving 7 PFAS and 6 chronic diseases. Specifically, each 1 ng/mL increase in perfluoroundecanoic acid (PFUnA) was associated with higher odds of heart attack (OR = 1.32, PFDR = 0.032), coronary heart disease (OR = 1.31, PFDR = 0.040), and non-melanoma cancer (OR = 1.22, PFDR = 0.046). Non-linear analyses showed that, 6 PFAS were significantly associated with colorectal cancer. PFAS mixture analyses consistently indicated increased risks of cardiovascular diseases, hypertension, high cholesterol, and metabolic dysfunction. Perfluorononanoic acid (PFNA) was identified as the dominant contributor to the positive mixture effect (31.8–52.7%), as evidenced by several machine learning methods. Our findings provide important evidence of associations between PFAS exposure and multiple chronic diseases, and may contribute to the development of precision management strategies for chronic diseases prevention.