Per- and polyfluoroalkyl substances (PFAS) and fetal growth: A nation-wide register-based study on PFAS in drinking water.

BACKGROUND: There is inconclusive evidence for an association between per- and polyfluoroalkyl substances (PFAS) and fetal growth. OBJECTIVES: We conducted a nation-wide register-based cohort study to assess the associations of the estimated maternal exposure to the sum (PFAS4) of perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA) and perfluorohexane sulfonic acid (PFHxS) with birthweight as well as risk of small- (SGA) and large-for-gestational-age (LGA). MATERIALS AND METHODS: We included all births in Sweden during 2012-2018 of mothers residing ≥ four years prior to partus in localities served by municipal drinking water where PFAS were measured in raw and drinking water. Using a one-compartment toxicokinetic model we estimated cumulative maternal blood levels of PFAS4 during pregnancy by linking residential history, municipal PFAS water concentration and year-specific background serum PFAS concentrations in Sweden. Individual birth outcomes and covariates were obtained via register linkage. Mean values and 95 % confidence intervals (CI) of ß coefficients and odds ratios (OR) were estimated by linear and logistic regressions, respectively. Quantile g-computation regression was conducted to assess the impact of PFAS4 mixture. RESULTS: Among the 248,804 singleton newborns included, no overall association was observed for PFAS4 and birthweight or SGA. However, an association was seen for LGA, multivariable-adjusted OR 1.08 (95% CI: 1.01-1.16) when comparing the highest PFAS4 quartile to the lowest. These associations remained for mixture effect approach where all PFAS, except for PFOA, contributed with a positive weight. DISCUSSIONS: We observed an association of the sum of PFAS4 - especially PFOS - with increased risk of LGA, but not with SGA or birthweight. The limitations linked to the exposure assessment still require caution in the interpretation.

Adjusting for covariates and assessing modeling fitness in machine learning using MUVR2.

Motivation: Machine learning (ML) methods are frequently used in Omics research to examine associations between molecular data and for example exposures and health conditions. ML is also used for feature selection to facilitate biological interpretation. Our previous MUVR algorithm was shown to generate predictions and variable selections at state-of-the-art performance. However, a general framework for assessing modeling fitness is still lacking. In addition, enabling to adjust for covariates is a highly desired, but largely lacking trait in ML. We aimed to address these issues in the new MUVR2 framework. Results: The MUVR2 algorithm was developed to include the regularized regression framework elastic net in addition to partial least squares and random forest modeling. Compared with other cross-validation strategies, MUVR2 consistently showed state-of-the-art performance, including variable selection, while minimizing overfitting. Testing on simulated and real-world data, we also showed that MUVR2 allows for the adjustment for covariates using elastic net modeling, but not using partial least squares or random forest. Availability and implementation: Algorithms, data, scripts, and a tutorial are open source under GPL-3 license and available in the MUVR2 R package at https://github.com/MetaboComp/MUVR2.

OMICs Signatures Linking Persistent Organic Pollutants to Cardiovascular Disease in the Swedish Mammography Cohort.

Cardiovascular disease (CVD) development may be linked to persistent organic pollutants (POPs), including organochlorine compounds (OCs) and perfluoroalkyl and polyfluoroalkyl substances (PFAS). To explore underlying mechanisms, we investigated metabolites, proteins, and genes linking POPs with CVD risk. We used data from a nested case-control study on myocardial infarction (MI) and stroke from the Swedish Mammography Cohort - Clinical (n = 657 subjects). OCs, PFAS, and multiomics (9511 liquid chromatography-mass spectrometry (LC-MS) metabolite features; 248 proteins; 8110 gene variants) were measured in baseline plasma. POP-related omics features were selected using random forest followed by Spearman correlation adjusted for confounders. From these, CVD-related omics features were selected using conditional logistic regression. Finally, 29 (for OCs) and 12 (for PFAS) unique features associated with POPs and CVD. One omics subpattern, driven by lipids and inflammatory proteins, associated with MI (OR = 2.03; 95% CI = 1.47; 2.79), OCs, age, and BMI, and correlated negatively with PFAS. Another subpattern, driven by carnitines, associated with stroke (OR = 1.55; 95% CI = 1.16; 2.09), OCs, and age, but not with PFAS. This may imply that OCs and PFAS associate with different omics patterns with opposite effects on CVD risk, but more research is needed to disentangle potential modifications by other factors.

Per- and polyfluoroalkyl substances and cardiometabolic diseases: A review.

Per- and polyfluoroalkyl substances (PFAS) are a group of persistent and widespread environmental pollutants that represent a high concern for human health. They have been shown to be associated with several important physiological processes such as lipid metabolism and the immune system. Consequently, PFAS are suspected to play a role in cardiometabolic disease development. However, the evidence regarding associations between PFAS and overt cardiovascular disease and type 2 diabetes remains limited and inconsistent. To address this, we conducted a review of the epidemiological evidence. A deeper understanding of potential underlying molecular mechanisms may help to explain inconsistencies in epidemiological findings. Thus, to gain more mechanistic insight, we also summarized evidence from omics and laboratory studies into an adverse outcome pathway framework. Our observations indicate the potential for associations of PFAS with multiple molecular pathways that could have opposite associations with disease risk, which could be further modified by mixture composition, lifestyle factors or genetic polymorphisms. This identifies the need for exposome studies considering mixture effects, the use of multi-omics data to gain insight in relevant pathways and the integration of epidemiological and laboratory studies to enhance mechanistic understanding and causal inference. Improved comprehension is essential for environmental health risk assessments.

Blood Levels of Organochlorine Contaminants Mixtures and Cardiovascular Disease.

Importance: Cardiovascular toxic effects derived from high exposures to individual organochlorine compounds are well documented. However, there is no evidence on low but continuous exposure to combined organochlorine compounds in the general population. Objective: To evaluate the association of combined exposure to several organochlorine compounds, including organochlorine pesticides and polychlorinated biphenyls, with incident cardiovascular disease (CVD) in the general population. Design, Setting, and Participants: This prospective nested case-control study included data from 2 cohorts: the Swedish Mammography Cohort-Clinical (SMC-C) and the Cohort of 60-Year-Olds (60YO), with matched case-control pairs based on age, sex, and sample date. Baseline blood sampling occurred from November 2003 to September 2009 (SMC-C) and from August 1997 to March 1999 (60YO), with follow-up through December 2017 (SMC-C) and December 2014 (60YO). Participants with myocardial infarction or ischemic stroke were matched with controls for composite CVD evaluation. Data were analyzed from September 2020 to May 2023. Exposures: A total of 25 organochlorine compounds were measured in blood at baseline by gas chromatography-triple quadrupole mass spectrometry. For 7 compounds, more than 75% of the samples were lower than the limit of detection and not included. Main Outcomes and Measures: Incident cases of primary myocardial infarction and ischemic stroke were ascertained via linkage to the National Patient Register (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes I21 and I63). The quantile-based g-computation method was used to estimate the association between the combined exposure to several organochlorine compounds and composite CVD. Results: Of 1528 included participants, 1024 (67.0%) were female, and the mean (SD) age was 72 (7.0) years in the SMC-C and 61 (0.1) years in the 60YO. The odds ratio of composite CVD was 1.71 (95% CI, 1.11-2.64) per 1-quartile increment of total organochlorine compounds mixture. Organochlorinated pesticides were the largest contributors, and ß-hexachlorocyclohexane and transnonachlor had the highest impact. Most of the outcome was not explained by disturbances in the main cardiometabolic risk factors, ie, high body mass index, hypertension, lipid alteration, or diabetes. Conclusions and Relevance: In this prospective nested case-control study, participants with higher exposures to organochlorines had an increased probability of experiencing a cardiovascular event, the major cause of death worldwide. Measures may be required to reduce these exposures.

PFAS and Phthalate/DINCH Exposure in Association with Age at Menarche in Teenagers of the HBM4EU Aligned Studies.

Early puberty has been found to be associated with adverse health outcomes such as metabolic and cardiovascular diseases and hormone-dependent cancers. The decrease in age at menarche observed during the past decades has been linked to an increased exposure to endocrine-disrupting compounds (EDCs). Evidence for the association between PFAS and phthalate exposure and menarche onset, however, is inconsistent. We studied the association between PFAS and phthalate/DINCH exposure and age at menarche using data of 514 teenagers (12 to 18 years) from four aligned studies of the Human Biomonitoring for Europe initiative (HBM4EU): Riksmaten Adolescents 2016-2017 (Sweden), PCB cohort (follow-up; Slovakia), GerES V-sub (Germany), and FLEHS IV (Belgium). PFAS concentrations were measured in blood, and phthalate/DINCH concentrations in urine. We assessed the role of each individual pollutant within the context of the others, by using different multi-pollutant approaches, adjusting for age, age- and sex-standardized body mass index z-score and household educational level. Exposure to di(2-ethylhexyl) phthalate (DEHP), especially mono(2-ethyl-5-hydroxyhexyl) phthalate (5OH-MEHP), was associated with an earlier age at menarche, with estimates per interquartile fold change in 5OH-MEHP ranging from -0.34 to -0.12 years in the different models. Findings from this study indicated associations between age at menarche and some specific EDCs at concentrations detected in the general European population, but due to the study design (menarche onset preceded the chemical measurements), caution is needed in the interpretation of causality.

PFAS association with kisspeptin and sex hormones in teenagers of the HBM4EU aligned studies.

Exposure to Perfluoroalkyl acids (PFAS) can impair human reproductive function, e.g., by delaying or advancing puberty, although their mechanisms of action are not fully understood. We therefore set out to evaluate the relationship between serum PFAS levels, both individually and as a mixture, on the Hypothalamic-Pituitary-Gonadal (HPG) axis by analyzing serum levels of reproductive hormones and also kisspeptin in European teenagers participating in three of the HBM4EU Aligned Studies. For this purpose, PFAS compounds were measured in 733 teenagers from Belgium (FLEHS IV study), Slovakia (PCB cohort follow-up), and Spain (BEA study) by high performance liquid chromatography-tandem mass spectrometry (HPLC/MS) in laboratories under the HBM4EU quality assurance quality control (QA/QC) program. In the same serum samples, kisspeptin 54 (kiss-54) protein, follicle-stimulating hormone (FSH), total testosterone (TT), estradiol (E2), and sex hormone-binding globulin (SHBG) levels were also measured using immunosorbent assays. Sex-stratified single pollutant linear regression models for separate studies, mixed single pollutant models accounting for random effects for pooled studies, and g-computation and Bayesian kernel machine regression (BKMR) models for the mixture of the three most available (PFNA, PFOA, and PFOS) were fit. PFAS associations with reproductive markers differed according to sex. Each natural log-unit increase of PFOA, PFNA, and PFOS were associated with higher TT [18.41 (6.18; 32.31), 15.60 (7.25; 24.61), 14.68 (6.18; 24.61), respectively] in girls, in the pooled analysis (all studies together). In males, G-computation showed that PFAS mixture was associated with lower FSH levels [-10.51 (-18.81;-1.36)]. The BKMR showed the same patterns observed in G-computation, including a significant increase on male Kiss-54 and SHBG levels. Overall, effect biomarkers may enhance the current epidemiological knowledge regarding the adverse effect of PFAS in human HPG axis, although further research is warranted.

Plasma protein and venous thromboembolism: prospective cohort and mendelian randomisation analyses.

We conducted cohort and Mendelian randomisation (MR) analyses to examine the associations of circulating proteins with risk of venous thromboembolism (VTE) to provide evidence basis for disease prevention and drug development. Cohort analysis was performed in 11 803 participants without baseline VTE. Cox regression was used to estimate the associations between 257 proteins and VTE risk. A machine-learning model was constructed to compare the importance of identified proteins and traditional risk factors. Genetic association data on VTE were obtained from a genome-wide meta-analysis (26 066 cases and 624 053 controls) and FinnGen (14 454 cases and 294 700 controls). The cohort analysis, including 353 incident VTE cases diagnosed during a 6.6-year follow-up, identified 21 proteins associated with VTE risk after false discovery rate correction. The machine-learning model indicated that body mass index and von Willebrand factor (vWF) made the same as well as most of the contributions to the overall model prediction. MR analysis found that genetically predicted levels of vWF, SERPINE1 (plasminogen activator inhibitor 1, known as PAI-1), EPHB4 (ephrin type-B receptor 4), TYRO3 (tyrosine-protein kinase receptor TYRO3), TNFRSF11A (tumour necrosis factor receptor superfamily member 11A), and BOC (brother of CDO) were causally associated with VTE risk.

Cross-sectional associations between exposure to per- and polyfluoroalkyl substances and body mass index among European teenagers in the HBM4EU aligned studies.

Per- and polyfluoroalkyl substances (PFAS) are widespread pollutants that may impact youth adiposity patterns. We investigated cross-sectional associations between PFAS and body mass index (BMI) in teenagers/adolescents across nine European countries within the Human Biomonitoring for Europe (HBM4EU) initiative. We used data from 1957 teenagers (12-18 yrs) that were part of the HBM4EU aligned studies, consisting of nine HBM studies (NEBII, Norway; Riksmaten Adolescents 2016-17, Sweden; PCB cohort (follow-up), Slovakia; SLO CRP, Slovenia; CROME, Greece; BEA, Spain; ESTEBAN, France; FLEHS IV, Belgium; GerES V-sub, Germany). Twelve PFAS were measured in blood, whilst weight and height were measured by field nurse/physician or self-reported in questionnaires. We assessed associations between PFAS and age- and sex-adjusted BMI z-scores using linear and logistic regression adjusted for potential confounders. Random-effects meta-analysis and mixed effects models were used to pool studies. We assessed mixture effects using molar sums of exposure biomarkers with toxicological/structural similarities and quantile g-computation. In all studies, the highest concentrations of PFAS were PFOS (medians ranging from 1.34 to 2.79 µg/L). There was a tendency for negative associations with BMI z-scores for all PFAS (except for PFHxS and PFHpS), which was borderline significant for the molar sum of [PFOA and PFNA] and significant for single PFOA [ß-coefficient (95% CI) per interquartile range fold change = -0.06 (-0.17, 0.00) and -0.08 (-0.15, -0.01), respectively]. Mixture assessment indicated similar negative associations of the total mixture of [PFOA, PFNA, PFHxS and PFOS] with BMI z-score, but not all compounds showed associations in the same direction: whilst [PFOA, PFNA and PFOS] were negatively associated, [PFHxS] associated positively with BMI z-score. Our results indicated a tendency for associations of relatively low PFAS concentrations with lower BMI in European teenagers. More prospective research is needed to investigate this potential relationship and its implications for health later in life.

Associations of Polymorphisms in the Peroxisome Proliferator-Activated Receptor Gamma Coactivator-1 Alpha Gene With Subsequent Coronary Heart Disease: An Individual-Level Meta-Analysis.

Background: The knowledge of factors influencing disease progression in patients with established coronary heart disease (CHD) is still relatively limited. One potential pathway is related to peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A), a transcription factor linked to energy metabolism which may play a role in the heart function. Thus, its associations with subsequent CHD events remain unclear. We aimed to investigate the effect of three different SNPs in the PPARGC1A gene on the risk of subsequent CHD in a population with established CHD. Methods: We employed an individual-level meta-analysis using 23 studies from the GENetIcs of sUbSequent Coronary Heart Disease (GENIUS-CHD) consortium, which included participants (n = 80,900) with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. Three variants in the PPARGC1A gene (rs8192678, G482S; rs7672915, intron 2; and rs3755863, T528T) were tested for their associations with subsequent events during the follow-up using a Cox proportional hazards model adjusted for age and sex. The primary outcome was subsequent CHD death or myocardial infarction (CHD death/myocardial infarction). Stratified analyses of the participant or study characteristics as well as additional analyses for secondary outcomes of specific cardiovascular disease diagnoses and all-cause death were also performed. Results: Meta-analysis revealed no significant association between any of the three variants in the PPARGC1A gene and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline: rs8192678, hazard ratio (HR): 1.01, 95% confidence interval (CI) 0.98-1.05 and rs7672915, HR: 0.97, 95% CI 0.94-1.00; rs3755863, HR: 1.02, 95% CI 0.99-1.06. Similarly, no significant associations were observed for any of the secondary outcomes. The results from stratified analyses showed null results, except for significant inverse associations between rs7672915 (intron 2) and the primary outcome among 1) individuals aged ≥65, 2) individuals with renal impairment, and 3) antiplatelet users. Conclusion: We found no clear associations between polymorphisms in the PPARGC1A gene and subsequent CHD events in patients with established CHD at baseline.

Per- and Polyfluoroalkyl Substances and Risk of Myocardial Infarction and Stroke: A Nested Case-Control Study in Sweden.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are widespread and persistent pollutants that have been associated with elevated cholesterol levels. However, data on incident cardiovascular disease (CVD) is lacking. OBJECTIVES: We investigated the association of exposure to PFAS with risk of myocardial infarction and stroke and, subsidiary, with baseline blood lipids. METHODS: This population-based nested case-control study included first incident myocardial infarction and stroke cases with matched controls from two Swedish cohorts: the Swedish Mammography Cohort-Clinical (SMC-C) and the Cohort of 60-year-olds (60YO). Baseline blood sampling occurred during 2003-2009 and 1997-1999 with follow-up through 2017 and 2014 for the SMC-C and the 60YO, respectively. Eight plasma PFAS concentrations were measured using targeted liquid chromatography-triple quadrupole mass spectrometry. Five of these were quantifiable in both cohorts; individual values and their standardized sum were categorized into tertiles based on the controls. First incident myocardial infarction (n=345) and ischemic stroke (n=354) cases were ascertained via linkage to the National Inpatient Register and the Cause of Death Register. Controls were randomly selected from each cohort after matching for age, sex, and sample date. Baseline blood lipids were measured in plasma or serum after overnight fasting. RESULTS: Among the 1,528 case-control subjects, the mean (standard deviation) age was 66 (7.7) y and 67% of them were women. In multivariable-adjusted analyses, the third tertile of the standardized sum of five PFAS associated with higher cholesterol and lower triglyceride levels among controls at baseline (n=631). The corresponding results were odds ratios=0.70 [95% confidence interval (CI): 0.53, 0.93] for CVD, 0.60 (95% CI: 0.39, 0.92) for myocardial infarction, and 0.83 (95% CI: 0.46, 1.50) for stroke. DISCUSSION: This study indicated that exposure to PFAS, although associated with increased cholesterol levels, did not associate with an increased risk of myocardial infarction, stroke, or their composite end point. The findings improve our knowledge on potential health effects of environmental contaminants in the CVD context. https://doi.org/10.1289/EHP9791.

Plasma metabolites associated with exposure to perfluoroalkyl substances and risk of type 2 diabetes - A nested case-control study.

Perfluoroalkyl substances (PFAS) are widespread persistent environmental pollutants. There is evidence that PFAS induce metabolic perturbations in humans, but underlying mechanisms are still unknown. In this exploratory study, we investigated PFAS-related plasma metabolites for their associations with type 2 diabetes (T2D) to gain potential mechanistic insight in these perturbations. We used untargeted LC-MS metabolomics to find metabolites related to PFAS exposures in a case-control study on T2D (n = 187 matched pairs) nested within the Västerbotten Intervention Programme cohort. Following principal component analysis (PCA), six PFAS measured in plasma appeared in two groups: 1) perfluorononanoic acid, perfluorodecanoic acid and perfluoroundecanoic acid and 2) perfluorohexane sulfonic acid, perfluorooctane sulfonic acid and perfluorooctanoic acid. Using a random forest algorithm, we discovered metabolite features associated with individual PFAS and PFAS exposure groups which were subsequently investigated for associations with risk of T2D. PFAS levels correlated with 171 metabolite features (0.16 ≤ |r| ≤ 0.37, false discovery rate (FDR) adjusted p < 0.05). Out of these, 35 associated with T2D (p < 0.05), with 7 remaining after multiple testing adjustment (FDR < 0.05). PCA of the 35 PFAS- and T2D-related metabolite features revealed two patterns, dominated by glycerophospholipids and diacylglycerols, with opposite T2D associations. The glycerophospholipids correlated positively with PFAS and associated inversely with risk for T2D (Odds Ratio (OR) per 1 standard deviation (1-SD) increase in metabolite PCA pattern score = 0.2; 95% Confidence Interval (CI) = 0.1-0.4). The diacylglycerols also correlated positively with PFAS, but they associated with increased risk for T2D (OR per 1-SD = 1.9; 95% CI = 1.3-2.7). These results suggest that PFAS associate with two groups of lipid species with opposite relations to T2D risk.

Visualization and Interpretation of Multivariate Associations with Disease Risk Markers and Disease Risk-The Triplot.

Metabolomics has emerged as a promising technique to understand relationships between environmental factors and health status. Through comprehensive profiling of small molecules in biological samples, metabolomics generates high-dimensional data objectively, reflecting exposures, endogenous responses, and health effects, thereby providing further insights into exposure-disease associations. However, the multivariate nature of metabolomics data contributes to high complexity in analysis and interpretation. Efficient visualization techniques of multivariate data that allow direct interpretation of combined exposures, metabolome, and disease risk, are currently lacking. We have therefore developed the 'triplot' tool, a novel algorithm that simultaneously integrates and displays metabolites through latent variable modeling (e.g., principal component analysis, partial least squares regression, or factor analysis), their correlations with exposures, and their associations with disease risk estimates or intermediate risk factors. This paper illustrates the framework of the 'triplot' using two synthetic datasets that explore associations between dietary intake, plasma metabolome, and incident type 2 diabetes or BMI, an intermediate risk factor for lifestyle-related diseases. Our results demonstrate advantages of triplot over conventional visualization methods in facilitating interpretation in multivariate risk modeling with high-dimensional data. Algorithms, synthetic data, and tutorials are open source and available in the R package 'triplot'.