Submitted:
10 June 2026
Posted:
11 June 2026
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
3. Results
3.1. Imaging Biomarkers
3.1.1. CIMT
3.1.2. PWV
3.1.3. FMD
3.1.4. Calcifications
3.1.5. Coronary Stenosis
3.2. Molecular Biomarkers
3.2.1. Oxidative Stress, Inflammation and Endothelial Dysfunction
3.2.2. Lipid Metabolism Dysregulation
3.2.3. Epigenetic Modulation
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Abbreviations
| AKR1C3 | Aldo-keto reductase family 1 member C3 |
| AKT1 | RAC-alpha serine/threonine-protein kinase |
| AMS | Artery Measurement Software |
| ANOVA | Analysis of variance |
| ApoE | Apolipoprotein E |
| ATF4 | Activating transcription factor 4 |
| CA2 | Carbonic anhydrase 2 |
| CASP | Caspase |
| CD | Cluster of differentiation |
| cfPWV | Carotid-femoral pulse wave velocity |
| CIMT | Carotid intima–media thickness |
| CNV | Copy number variation |
| COX-2 | Cyclooxygenase-2 |
| CT | Computed tomography |
| CXCL | C-X-C motif chemokine ligand |
| CYP | Cytochrome P450 |
| DNA | Deoxyribonucleic acid |
| DNMT3A | DNA methyltransferase 3 alpha |
| DXA | Dual-energy X-ray absorptiometry |
| eIF2α | Eukaryotic translation initiation factor 2α |
| eNOS | Endothelial nitric oxide synthase |
| ERK | Extracellular signal-regulated kinase |
| ERS | Endoplasmic reticulum stress |
| FMD | Flow-mediated dilation |
| GenX | hexafluoropropylene oxide dimer acid |
| HUVECs | Human umbilical vein endothelial cells |
| ICAM-1 | Intercellular adhesion molecule-1 |
| IL | Interleukin |
| IMT | Intima-media thickness |
| JAK | Janus Kinase |
| LDL-C | Low-density lipoprotein cholesterol |
| LDLr | Low-density lipoprotein receptor |
| MAPK | Mitogen-activated protein kinase |
| miRNA/miR | MicroRNA |
| MMP | Matrix metalloproteinase |
| NF-κB | Nuclear factor κappa -light-chain-enhancer of activated B cells |
| NHANES | National Health and Nutrition Examination Survey |
| NLR | Nod-like receptors |
| NLRP3 | NLR family pyrin domain containing 3 |
| PCA | Principal component analysis |
| PERK | Protein kinase R (PKR)-like endoplasmic reticulum kinase |
| PFAS | Per- and polyfluoroalkyl substances |
| PFDA | Perfluorodecanoic acid |
| PFDeA | Perfluorodecanoic acid |
| PFHpA | Perfluoroheptanoic acid |
| PFHxS | Perfluorohexanesulfonic acid |
| PFNA | Perfluorononanoic acid |
| PFOA | Perfluorooctanoic acid |
| PFOS | Perfluorooctane sulfonate |
| PIVUS | Prospective Investigation of the Vasculature in Uppsala Seniors |
| PPAR | Peroxisome proliferator-activated receptor |
| PWV | Pulse wave velocity |
| ROS | Reactive oxygen species |
| STAT | Signal transducer and activator of transcription |
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| First author and Year | Study type | Population | PFAS | Imaging biomarker | Statistical analysis | Effect modifiers | Main findings |
|---|---|---|---|---|---|---|---|
|
Lind et al., 2017 [28] |
Cross-sectional | 1,016 Swedish 70-year-olds | PFHpA PFHxS L-PFOS PFOA PFNA PFDA PFOSA PFUnDA |
CIMT | Linear and logistic regression, structural equation models | Sex, BMI, smoking status, BP, exercise habits, energy and alcohol intake, LDL-C, HDL-C, triglycerides, diabetes, educational level | Certain PFAS positively associated with CIMT and GSM-CIMT; possible influence of female sex |
|
Wang J et al., 2023 [26] |
Prospective | 957 mother-child pairs recruited from six hospitals in Shanghai | PFOA PFOS PFNA PFDA PFUA PFHxS PFDoA PFBS PFHpA PFOSA | CIMT | Linear regression, BKMR | Maternal age, pre-pregnancy BMI, household income, educational level, offspring sex | Maternal PFAS concentrations inversely associated with offspring CIMT |
|
Gump et al., 2023 [27] |
Cross-sectional | 291 children aged 9–11 years from Syracuse, New York | PFOS PFOA PFNA PFHxS PFDA | CIMT | General linear modelling, BKMR | Age, sex, BMI, ethnicity, blood mercury levels, urinary total arsenic, parental household income, occupation, educational level | PFDA positively associated with CIMT |
|
Lin et al., 2022 [32] |
Cross-sectional | 1,425 Taiwanese individuals aged 12–63 years from two cohorts | PFOS | CIMT | Linear regression, structural equation models | Age, sex, BMI, smoking status, alcohol consumption, household income, hypertension, diabetes, hyperlipidaemia | PFOS positively correlated with mean CIMT |
|
Lin et al., 2016 [33] |
Cross-sectional | 848 Taiwanese students aged 12–30 years | PFOA PFOS PFNA PFUA | CIMT | Logistic regression, Bonferroni correction | Age, sex, BMI, smoking status, systolic BP, LDL-C, HDL-C, triglycerides, HOMA-IR, hs-CRP | Positive association between PFOS and CIMT |
|
Lin et al., 2013 [34] |
Cross-sectional | 664 Taiwanese individuals aged 12–30 years from the Taipei area | PFOA PFOS PFNA PFUA | CIMT | Linear regression, logistic regression, Bonferroni correction | Age, sex, BMI, smoking status, systolic BP, LDL-C, triglycerides, hs-CRP, HOMA-IR | PFOS levels positively associated with mean CIMT |
|
Lind et al., 2018 [13] |
Longitudinal | 1,016 Swedish 70-year-olds at baseline | PFHpA PFHxS PFOS PFOA PFNA PFDA PFOSA PFUnDA | CIMT | Mixed-effects models, Bonferroni correction | Sex, BMI, smoking status, systolic BP, baseline PFAS levels, HDL-C, LDL-C, fasting glucose, triglycerides, statin use | Positive association between six PFAS and CIMT over 10 years |
|
Khalil et al., 2020 [31] |
Cross-sectional | 38 male firefighters from Arizona aged 49–54 years with >5 years of service; 49 controls aged 49–54 years from the 2009–2010 NHANES study | PFBuS PFDeA PFDoA PFHpA PFHxS PFNA PFOSA Et-PFOSA-AcOH Me-PFOSA-AcOH PFOS PFOA PFUA | CIMT | Linear models | Age, smoking status, exercise habits, family history of heart disease, HDL-C, triglycerides, fasting glucose, sICAM-1, hs-IL-6 | No association between PFAS and CIMT |
|
Liberda et al., 2019 [35] |
Cross-sectional | 535 Indigenous individuals from nine communi-ties in northern Quebec, aged 15–87 years | PFOA PFOS PFHxS | CIMT | PCA, linear regression, sensitivity analysis, Holm method | Age, sex, BMI, smoking status, systolic BP, LDL-C, Apo-B, triglycerides, TNF-α, hs-CRP, ox-LDL | PFOA, PFOS, and PFHxS positively associated with CIMT |
|
Wang D et al., 2023 [25] |
Controlled experimental | Male ApoE−/− mice aged 7 weeks at baseline | PFOS | CIMT, left common carotid artery PWV |
ANOVA, LSD test, Dunnett’s test | ns | PFOS exposure associated with increased CIMT, arterial stiffness, aortic plaque burden, and plaque vulnerability |
|
Lv et al., 2025 [24] |
Controlled experimental | 28 adult male C57BL/6J mice | 6:2 Cl-PFESA (trade name F-53B) | Abdominal aortic PWV | One-way ANOVA, LSD test, Dunnett’s test, factorial ANOVA | ns | Exposure associated with increased abdominal aortic PWV |
|
Wittkopp et al., 2022 [15] |
Cross-sectional | 94 adults with a mean age of 55 years from the United States without known cardiovascular disease | PFPeA PFHxA PFHpA PFOA PFNA PFDA PFUnDA PFBS PFHxS PFOS | FMD | Linear regression, WQS, BKMR, sensitivity analysis | Age, sex, BMI, smoking status, ethnicity, HbA1c, hypertension, hypercholesterolemia, waist circumference, systolic BP, diastolic BP | PFHpA inversely associated with FMD |
|
Osorio-Yanez et al., 2021 [16] |
Prospective | 666 prediabetic adults from 27 centres in the United States, enrolled in the Diabetes Prevention Program | PFOS PFOA PFHxS EtFOSAA MeFOSA-A PFNA |
Coronary and thoracic aortic calcifications | Logistic regression, sensitivity analysis | Age, sex, BMI, ethnicity, educational level, smoking status, treatment assignment, statin use | Positive association between PFOS, n-PFOS, and Et-FOSAA and coronary/aortic calcifications over 13–14 years |
|
Yang et al., 2025 [29] |
Cross-sectional | 1,005 middle-aged and older adults from the United States enrolled in the 2013–2014 NHANES study | PFDeA PFHxS PFNA | Abdominal aortic calcifications | Logistic regression, sensitivity analysis, RCS, QGC, XGBoost with SHAP, mediation analysis | Age, sex, BMI, ethnicity, smoking status, education, household income, phosphorus, vitamin B12, TC, total calcium, AST, ALT, HbA1c, total 25-hydroxyvitamin D, uric acid, eGFR, hypertension, diabetes | PFHxS, PFDeA, and PFAS mixtures associated with increased calcification risk |
|
Koskela et al., 2022 [30] |
Cross-sectional | 913 subjects aged 40–80 years enrolled in the 2013–2014 NHANES study | PFOA PFOS PFHxS PFNA | Abdominal aortic calcifications | Logistic regression, Bonferroni correction | Age, sex, ethnicity, cotinine, household income | No significant association between PFAS and abdominal aortic calcifications |
|
Li et al., 2025 [36] |
Cross-sectional | 571 subjects with acute coronary syndrome aged 18–80 years from Hebei, China | PFOA PFOS PFNA PFHxS PFUnDA PFDA | Coronary stenosis | Logistic regression, Cox regression, RCS, threshold effect model, BKMR, QGC, sensitivity analysis, FDR | Age, sex, BMI, smoking status, drinking, educational level | Positive association between PFOS and coronary stenosis |
| First author and Year | Study type | Model/ Population |
PFAS | Molecular biomarker | Statistical analysis | Effect modifiers | Main findings |
|---|---|---|---|---|---|---|---|
| Oxidative stress, inflammation and endothelial dysfunction | |||||||
|
Liao et al., 2012 [37] |
In vitro | HUVECs, THP-1 cells | PFOS | Intracellular ROS, IL-1β, IL-6, COX-2, NOS3, ICAM-1, P-selectin, PPARγ, ERα, AHR | One-way ANOVA, Tukey test | ns | PFOS increased ROS and upregulated IL-1β, IL-6, COX-2, ICAM-1 and P-selectin, enhancing THP-1 adhesion. |
|
Lin et al., 2016 [33] |
Cross-sectional | 848 Taiwanese adolescents and young adults | PFOS PFOA PFCs | CD31+/CD42a− EMPs, CD31+/CD42a+ PMPs, HDL, LDL, 8-OHdG, CD62E, TG, CRP | Multiple linear and logistic regression | Age, gender, smoking status, BMI, SBP, LDL-C, HDL-C, TG, HOMA-IR, hs-CRP. | PFOS was associated with endothelial and platelet microparticles; elevated microparticles strengthened the association with increased CIMT (OR=2.86, 95% CI 1.69–4.84). |
|
Dangudubiyyam et al., 2020 [41] |
In vivo animal model | Offspring of PFOS-exposed pregnant rats | PFOS | eNOS, phospho-eNOS | ANOVA, Dunnet’s post hoc test, unpaired Student’s t-test non-parametric Kruskal-Wallis test, Dunn’s multiple comparisons | ns | Prenatal PFOS exposure increased blood pressure, impaired acetylcholine-induced relaxation, and reduced eNOS activation/expression. |
|
Cui et al., 2022 [38] |
In vitro | HUVECs | PFOS | Lipid ROS, NO, GPX4, ACSL4, FTH1, HO-1 | ANOVA | ns | PFOS induced ferroptosis, increased lipid ROS levels and ACSL4 expression, and reduced GPX4, FTH1, HO-1 expression and NO content. |
|
Wang et al., 2023 [25] |
In vivo and in vitro | ApoE−/− mice and RAW264.7 macrophages | PFOS | TC, TG, LDL-C, HDL-C, NF-κB, iNOS, TNF-α, IL-6, IL-1β, CD206, Arg-1, IL-10 | ANOVA, LSD test, Dunnett’s test | ns | PFOS promoted M1 macrophage polarization, thereby increasing TNF-α, IL-6, IL-1β, and iNOS expression, while suppressing M2 polarization by reducing CD206, Arg-1, and IL-10 promoting atherosclerosis in mice. |
|
Vajeethaveesin et al., 2025 [39] |
In vitro and transcriptomics | HMEC-1 cells | PFOS | ATF4, C/EBPβ, COX-2, ICAM-1, IL-6, NF-κB, JAK2/STAT3 | ANOVA, Dunnett’s test | ns | PFOS activated HRI/eIF2α/ATF4 ER-stress signaling and increased COX-2, ICAM-1, and IL-6 expression. |
|
Lv et al., 2025 [24] |
In vivo and in vitro | C57BL/6J mice and HUVECs | F-53B (6:2 Cl-PFESA) | NF-κB, NLRP3, ASC, CASP1, GSDMD, IL-1β, ICAM-1, VCAM-1 | ANOVA, LSD test, Dunnett’s test | ns | F-53B plus nanoplastics activated NF-κB/NLRP3 signaling, increasing IL-1β, CASP1 and GSDMD, and inducing endothelial pyroptosis. |
|
Zhang et al., 2026 [40] |
In vivo and in vitro | ApoE−/− mice and HUVECs | OBS | ROS, PERK, IκBα, eIF2α, ATF4, NF-κB, ICAM-1, VCAM-1, IL-1β, IL-6, TNF-α, ZO-1, occludin, claudin-1, VE-cadherin | ANOVA, unpaired Student’s t-test, Kruskal-Wallis test | ns | OBS exposure → ROS accumulation, PERK–eIF2α–ATF4 ER stress and NF-κB activation; NAC and 4-PBA attenuated these effects. In vivo experiments: OBS exposure → endothelial impairment, collagen deposition, oxidative stress, ↑ ER stress markers, ↑ inflammation-related markers. |
|
Zhao et al., 2026 [42] |
Cross-sectional | 8100 Chinese adult subjects | PFAS mixture | hs-CRP, serum ferritin | t-test, Wilcoxon, χ2 test, Spearman correlation analysis, multivariable linear/logistic regression, QGC and WQS mixture analyses, BKMR and RCS exposure, mediation analysis, FDR correction | Age, gender, residence, education, household income, tobacco, alcohol, physical activity, total energy intake, total fat intake, total cholesterol intake, BMI for non-obesity outcomes, BMI and serum creatinine for hyperuricemia | PFAS mixtures were associated with hypercholesterolemia (OR=1.20), high LDL-C (OR=1.13), hypertension (OR=1.10) and hyperuricemia (OR=1.31); both inflammatory markers mediated the associations. |
| Lipid metabolism dysregulation | |||||||
|
Pan et al., 2025 [48] |
Cross-sectional | 1,099 adolescents aged 12–19 (US), enrolled in the 2005–2018 NHANES study |
PFOA PFOS PFHxS PFNA | LDL-C, TC, TG, AIP, serum folate, ALB, PPARγ, IL-10 (network), CASP1, CA2 (shared targets) | Weighted linear regression, Pearson correlation, BKMR, WQS, Mediation | Age, gender, race, family income-to-poverty ratio, albumin, uric acid, BMI, serum cotinine (tobacco exposure), diabetes, vitamin D | PFOS was positively associated with LDL-C and TC; PFNA, PFOS, and PFOA were associated with TG and AIP. PPAR signaling was identified as a core pathway. |
|
Connolly et al., 2025 [43] |
In vitro | Human U937-derived macrophages | PFOS PFOA | PPARγ, Nrf2, IL-1β, PAI-2, COX-2, AKR1C3, MMP-1, MMP-12, total cholesterol | Two-tailed unpaired t-test, one-way ANOVA, post-hoc Dunnett, post-hoc Tukey | ns | PFOS/PFOA increased lipid accumulation and induced PPARγ/Nrf2 signaling, IL-1β, PAI-2, MMP-1, and MMP-12 expression. |
|
Roth et al., 2026 [45] |
In vivo animal model | 40 LDLr−/− mice | PFAS mixture (PFOA, PFOS, PFNA, PFHxS, GenX) | Total cholesterol, IDL, LDL subfractions, HDL, LDL7 (densest subfraction), oxLDL, Fabp4, Fasn (foam cell markers), Cxcl2, Cxcl17 (chemokines), Plin1, Plin5 (perilipins), Abca1, Abcg1 (cholesterol efflux) | t-test Mann-Whitney, Shapiro-Wilk, Brown-Forsythe, RNA-seq (edgeR), FDR Benjamini-Hochberg, GO enrichment (DAVID) | ns | PFAS increased total cholesterol (+10%), IDL (+25%) and LDL7 (+206%), while upregulating foam-cell-associated genes. |
|
Zhang et al., 2025 [46] |
In vivo and in vitro | ApoE−/− mice, HUVECs | PFOS OBS | TG, TC, LDL-C, HDL-C, IL-6, TNF-α, IL-1β, NF-κB and MAPK/ERK signaling, ZO-1, occludin, claudin-5, VE-cadherin, endothelial permeability and LDH release | Student’s t-test, one-way ANOVA, Kruskal–Wallis test | ns | OBS induced more rapid dyslipidemia and stronger vascular inflammatory responses than PFOS. OBS induced stronger endothelial barrier disruption and inflammation than PFOS, with activation of NF-κB and MAPK/ERK pathways. |
|
Du et al., 2025 [47] |
Epidemiological, in vivo, toxicogenomic analyses | 2,014 University students (CN), 120 C57BL/6J mice, toxicogenomics database | PFAS mixtures | Hematologic and lipid-metabolism-related pathways | One-way ANOVA, BKMR, WQS, toxicogenomic pathway enrichment analyses | Age, gender ethnicity, smoking, and BMI | Toxicogenomic analyses linked PFAS exposure to lipid metabolism, inflammation, apoptosis, and JAK-STAT signaling pathways. |
|
Chai et al., 2026 [44] |
In silico study | Network toxicology and molecular docking | PFHpA PFOA PFNA PFDA | STAT3, MMP9, NFκB1, CASP3, AKT1, PPARγ | PPI analysis, GO/KEGG; molecular docking | ns | PPARγ and lipid metabolism pathways emerged among the principal mechanisms linking PFAS exposure to cardiovascular disease. |
| Epigenetic modulation | |||||||
|
Xu et al., 2020 [50] |
Human observational study | 292 exposed women in Sweden | PFOS PFHxS PFOA | miR-101-3p, miR-144-3p, miR-19a-3p | EdgeR differential expression analysis, pairwise t-tests, FDR correction, 2−ΔΔCq analysis, IPA functional analysis, Fisher’s exact test | ns | PFAS exposure was associated with downregulation of miR-101-3p, miR-144-3p, and miR-19a-3p. |
|
Liu et al., 2022 [49] |
Longitudinal EWAS | HOME mother–child cohort | PFOA PFOS PFNA PFHxS | CpG DNA methylation | GEE, interaction analysis, FDR correction, GO enrichment analysis, linear regression analyses, Spearman correlation analysis, t-test, χ2, Wilcoxon | Age, gender, household income, maternal race/ethnicity, maternal smoking during pregnancy, serum cotinine, cell-type composition. | PFAS exposure was associated with 435 differentially methylated CpG sites at birth and at 12 years of age. |
|
Lin et al., 2022 [32] |
Cross-sectional | 1,425 Taiwanese participants | PFOS | Global DNA methylation (5mdC/dG) | Linear regression analysis, structural equation modelling (SEM) | Age, gender, BMI, alcohol, hyperlipidemia, hypertension, diabetes, smoking, household income | PFOS was positively associated with 5mdC/dG, suggesting a direct contribution to arteriosclerosis through DNA methylation. |
|
Karakuş et al., 2024 [52] |
In silico study | Network toxicology | Multiple PFAS | PPARα, PPARγ, miR-130b-3p, miR-130a-3p, miR-129-5p | GO/KEGG enrichment, PPI analysis | ns | PPARα, and PPARγ were identified as core PFAS-CVD genes together with several PFAS-associated miRNAs. |
|
Li et al., 2024 [51] |
Human cohort study | 176 Teen-LABs subjects (US), 64 Rhea Study subjects (GR) | Multiple PFAS, PFAS mixture | miR-148b-3p, miR-29a-3p | Linear regression analysis, pathway enrichment | Age, BMI, race, weight loss prior to surgery, parents’ income, clinical site of surgery; Rhea Study: age, BMI, sex, parental education |
PFAS exposure was associated with altered circulating miRNA profiles; miR-148b-3p and miR-29a-3p were consistently downregulated. |
| Zhang et al., 2026 [53] | In vitro transcriptomic study | HUVECs | OBS | 74 DEMs, 685 DEGs, miRNA–mRNA pairs, ROS | ANOVA, Tukey’s test, Kruskal–Wallis test | ns | OBS altered miRNA–mRNA networks associated with endothelial dysfunction and increased intracellular ROS. |
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