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Background <p>Per- and polyfluoroalkyl substances (PFAS) have been implicated in metabolic dysregulation, yet their impact on integrated cardiometabolic risk remains unexplored. We aim to assess associations between serum PFAS and the cardiometabolic index (CMI) in U.S. adults.</p> Methods <p>We analyzed NHANES 2015–2020 data (N = 1371) using multivariable linear regression to estimate PFAS-CMI relationships across exposure quartile. Restricted cubic splines and threshold analyses characterized nonlinearity. Mixed-exposure effects were evaluated via Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS), and quantile g-computation. Stratified models tested effect modification by covariates. Comparative Toxicogenomics Database (CTD) interrogation mapped PFAS targets and pathways.</p> Results <p>After full adjustment, PFDeA (β = −&#xa0;0.06, 95% CI [−&#xa0;0.11, −&#xa0;0.01]) and PFUA (β = −&#xa0;0.11, 95% CI [−&#xa0;0.17, −&#xa0;0.06]) remained inversely associated with CMI (P &lt; 0.01). Spline models confirmed linear inverse trends for PFDeA and PFUA, whereas n-PFOS exhibited an inverted U-shape. The results of BKMR showed that the overall effect of PFAS on CMI was negative. WQS analyses consistently demonstrated a negative effect on CMI (β = &#xa0;−0.16, 95% CI [−&#xa0;0.25, −&#xa0;0.07]), with PFUA carrying the greatest weight. Associations persisted across subgroups but were stronger in non-Hispanic Whites and modified by alcohol use and obesity. CTD network analysis identified PPARA, SREBF1, and CYP7A1 as central lipid-regulatory hubs for PFDeA and PFUA.</p> Conclusion <p>This is the first study to link individual and mixed PFAS exposures to CMI, leveraging robust mixture models and bioinformatic mechanistic mapping. Our findings reveal PFDeA and PFUA as key drivers of PFAS-related cardiometabolic risk and underscore the value of CMI as an integrative biomarker in environmental health research.</p>

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Associations of per- and polyfluoroalkyl substances (PFAS) with cardiometabolic risk: a multi-method mixture and pathway analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月10日

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  • Yuelin Hu,
  • Xuli Chen,
  • Guojin Jian,
  • Qiuyu Wang,
  • Wenwen Xiao

摘要

Background

Per- and polyfluoroalkyl substances (PFAS) have been implicated in metabolic dysregulation, yet their impact on integrated cardiometabolic risk remains unexplored. We aim to assess associations between serum PFAS and the cardiometabolic index (CMI) in U.S. adults.

Methods

We analyzed NHANES 2015–2020 data (N = 1371) using multivariable linear regression to estimate PFAS-CMI relationships across exposure quartile. Restricted cubic splines and threshold analyses characterized nonlinearity. Mixed-exposure effects were evaluated via Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS), and quantile g-computation. Stratified models tested effect modification by covariates. Comparative Toxicogenomics Database (CTD) interrogation mapped PFAS targets and pathways.

Results

After full adjustment, PFDeA (β = − 0.06, 95% CI [− 0.11, − 0.01]) and PFUA (β = − 0.11, 95% CI [− 0.17, − 0.06]) remained inversely associated with CMI (P < 0.01). Spline models confirmed linear inverse trends for PFDeA and PFUA, whereas n-PFOS exhibited an inverted U-shape. The results of BKMR showed that the overall effect of PFAS on CMI was negative. WQS analyses consistently demonstrated a negative effect on CMI (β =  −0.16, 95% CI [− 0.25, − 0.07]), with PFUA carrying the greatest weight. Associations persisted across subgroups but were stronger in non-Hispanic Whites and modified by alcohol use and obesity. CTD network analysis identified PPARA, SREBF1, and CYP7A1 as central lipid-regulatory hubs for PFDeA and PFUA.

Conclusion

This is the first study to link individual and mixed PFAS exposures to CMI, leveraging robust mixture models and bioinformatic mechanistic mapping. Our findings reveal PFDeA and PFUA as key drivers of PFAS-related cardiometabolic risk and underscore the value of CMI as an integrative biomarker in environmental health research.