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Background: Per-and polyfluoroalkyl substances (PFAS) contamination may disrupt sleep through disrupted metabolic and immune functions. The study aims to investigate the association and potential mechanism between PFAS and sleep. Methods: We included 136 young adults recruited between 2014-2018 and 76 were re-assessed between 2020-2022. Additional 8 participants only had complete data between 2020-2022. Plasma PFAS (PFOS, PFOA, PFHxS, PFHpS, PFPeS, PFNA, PFDA) were measured at both visits using liquid-chromatography high-resolution mass spectrometry. Plasma proteins were measured by Olink® Explore 384 Cardiometabolic and Inflammation Panel I. Sleep duration was self-reported at both visits along with follow-up sleep disturbance and sleep-related impairment using validated instruments. We utilized multiple linear regression to explore the association between individual PFAS (in tertile) and these sleep outcomes. PFAS associated with sleep outcomes were subjected to computational toxicology analysis using the Comparative Toxicogenomics Database and Toxicology in the 21st Century database to identify potential genetic links between them. Mediation analysis using proteomic data was then performed to confirm the findings from computational toxicology analysis. Results: At baseline, one tertile increase in PFDA was associated with 0.39 (95 % CI: 0.05, 0.73) hours of shorter nightly sleep duration, and, at follow-up, PFHxS and PFOA were associated with 0.39 (95 % CI: 0.05, 0.72) and 0.32 (95 % CI: 0.01, 0.63) hours shorter sleep duration, respectively. One tertile increase in PFOS exposure was associated with a 2.99-point increase in sleep disturbance scores (95 % CI: 0.67, 5.31) and a 3.35-point increase in sleep-related impairment scores (95 % CI: 0.51, 6.20). Computational toxicology and mediation analyses identified potential mediating roles for several proteins in the PFAS-sleep associations, including 11-beta-dehydrogenase isozyme 1 (HSD11B1), cathepsin B (CTSB) and several immune system-related proteins. Conclusion: Future large scale epidemiological and mechanistic studies should confirm our findings and test effect measure modification of the associations by age.

Abstract To assess cardiometabolic profiles and proteomics to identify biomarkers associated with the metabolically healthy and unhealthy obesity. Young adults (N = 156) enrolled were classified as not having obesity, metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO) based on NCEP ATP-III criteria. Plasma proteomics at study entry were measured using Olink Cardiometabolic Explore panel. Linear regression was used to assess associations between proteomics and obesity groups as well as cardiometabolic traits of glucose, insulin, and lipid profiles at baseline and follow-up visits. Enriched biological pathways were further identified based on the significant proteomic features. Among the baseline 95 (61%) and 61 (39%) participants classified as not having obesity and having obesity (8 MHO and 53 MUHO), respectively. Eighty of the participants were followed-up with an average 4.6 years. Forty-one proteins were associated with obesity (FDR

Abstract Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P

Background: Strong epidemiological evidence shows positive associations between exposure to per- and polyfluoroalkyl substances (PFAS) and adverse cardiometabolic outcomes (e.g., diabetes, hypertension, and dyslipidemia). However, the underlying cardiometabolic-relevant biological activities of PFAS in humans remain largely unclear. Aim: We evaluated the associations of PFAS exposure with high-throughput proteomics in Hispanic youth. Material and Methods: We included 312 overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) between 2001 and 2012, along with 137 young adults from the Metabolic and Asthma Incidence Research (Meta-AIR) between 2014 and 2018. Plasma PFAS (i.e., PFOS, PFOA, PFHxS, PFHpS, PFNA) were quantified using liquid-chromatography high-resolution mass spectrometry. Plasma proteins (n = 334) were measured utilizing the proximity extension assay using an Olink Explore Cardiometabolic Panel I. We conducted linear regression with covariate adjustment to identify PFAS-associated proteins. Ingenuity Pathway Analysis, protein-protein interaction network analysis, and protein annotation were used to investigate alterations in biological functions and protein clusters. Results: Results after adjusting for multiple comparisons showed 13 significant PFAS-associated proteins in SOLAR and six in Meta-AIR, sharing similar functions in inflammation, immunity, and oxidative stress. In SOLAR, PFNA demonstrated significant positive associations with the largest number of proteins, including ACP5, CLEC1A, HMOX1, LRP11, MCAM, SPARCL1, and SSC5D. After considering the mixture effect of PFAS, only SSC5D remained significant. In Meta-AIR, PFAS mixtures showed positive associations with GDF15 and IL6. Exploratory analysis showed similar findings. Specifically, pathway analysis in SOLAR showed PFOA- and PFNA-associated activation of immune-related pathways, and PFNA-associated activation of inflammatory response. In Meta-AIR, PFHxS-associated activation of dendric cell maturation was found. Moreover, PFAS was associated with common protein clusters of immunoregulatory interactions and JAK-STAT signaling in both cohorts. Conclusion: PFAS was associated with broad alterations of the proteomic profiles linked to pro-inflammation and immunoregulation. The biological functions of these proteins provide insight into potential molecular mechanisms of PFAS toxicity.

Background and Aim: Ambient air pollution (AAP) exposure has been associated with altered blood lipids and liver fat in young adults. MicroRNAs regulate gene expression and may mediate these relationships. This work investigated associations between AAP exposure, serum microRNA networks, lipid profiles, and non-alcoholic fatty liver disease (NAFLD) risk in young adults. Methods: Participants were 170 young adults (17–22 years) from the Meta-AIR cohort of the Children’s Health Study (CHS). Residential AAP exposure (PM2.5, PM10, NO2, 8-hour maximum O3, redox-weighted oxidative capacity [Oxwt]) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Fasting serum lipids were assayed. Liver fat was imaged by MRI and NAFLD was defined by ≥ 5.5% hepatic fat fraction. Serum microRNAs were measured via NanoString and microRNA networks were constructed by weighted gene correlation network analysis. The first principal component of each network represented its expression profile. Multivariable mixed effects regression models adjusted for sociodemographic, behavioral, and clinical covariates; baseline CHS town code was a random effect. Effects estimates are scaled to one standard deviation of exposure. Mediation analysis explored microRNA profiles as potential mediators of exposure-outcome associations. DIANA-mirPATH identified overrepresented gene pathways targeted by miRNA networks. Results: Prior-month Oxwt was associated with NAFLD (OR=3.45; p = 0.003) and inversely associated with microRNA Network A (β = −0.016; p = 0.026). Prior-year NO2 was associated with non-HDL-cholesterol (β = 7.13; p = 0.01) and inversely associated with miRNA Network A (β = −0.019; p = 0.022). Network A expression was inversely associated with NAFLD (OR=0.35; p = 0.010) and non-HDL-C (β = −6.94 mg/dL; p = 0.035). Network A members miR-199a/b-3p and miR-130a, which both target fatty acid synthase, mediated 21% of the association between prior-month Oxwt exposure with NAFLD (p = 0.048) and 23.3% of the association between prior-year NO2 exposure and non-HDL-cholesterol (p = 0.026), respectively. Conclusions: Exposure to AAP may contribute to adverse lipid profiles and NAFLD risk among young adults via altered expression of microRNA profiles.

Background: While biological age in adults is often understood as representing general health and resilience, the conceptual interpretation of accelerated biological age in children and its relationship to development remains unclear. We aimed to clarify the relationship of accelerated biological age, assessed through two established biological age indicators, telomere length and DNA methylation age, and two novel candidate biological age indicators, to child developmental outcomes, including growth and adiposity, cognition, behavior, lung function and the onset of puberty, among European school-age children participating in the HELIX exposome cohort. Methods: The study population included up to 1173 children, aged between 5 and 12 years, from study centres in the UK, France, Spain, Norway, Lithuania, and Greece. Telomere length was measured through qPCR, blood DNA methylation, and gene expression was measured using microarray, and proteins and metabolites were measured by a range of targeted assays. DNA methylation age was assessed using Horvath’s skin and blood clock, while novel blood transcriptome and ‘immunometabolic’ (based on plasma proteins and urinary and serum metabolites) clocks were derived and tested in a subset of children assessed six months after the main follow-up visit. Associations between biological age indicators with child developmental measures as well as health risk factors were estimated using linear regression, adjusted for chronological age, sex, ethnicity, and study centre. The clock derived markers were expressed as Δ age (i.e. predicted minus chronological age). Results: Transcriptome and immunometabolic clocks predicted chronological age well in the test set (r=0.93 and r=0.84 respectively). Generally, weak correlations were observed, after adjustment for chronological age, between the biological age indicators. Conclusions: In children, as in adults, biological aging appears to be a multi-faceted process and adiposity is an important correlate of accelerated biological aging. Patterns of associations suggested that accelerated immunometabolic age may be beneficial for some aspects of child development while accelerated DNA methylation age and telomere attrition may reflect early detrimental aspects of biological aging, apparent even in children. Funding: UK Research and Innovation (MR/S03532X/1); European Commission (grant agreement numbers: 308333; 874583).

The assessment of “omics” signatures may contribute to personalized medicine and precision nutrition. However, the existing literature is still limited in the homogeneity of participants’ characteristics and in limited assessments of integrated omics layers. Our objective was to use post-prandial metabolomics and fasting proteomics to identify biological pathways and functions associated with diet quality in a population of primarily Hispanic young adults. We conducted protein and metabolite-wide association studies and functional pathway analyses to assess the relationships between a priori diet indices, Healthy Eating Index-2015 (HEI) and Dietary Approaches to Stop Hypertension (DASH) diets, and proteins (n = 346) and untargeted metabolites (n = 23,173), using data from the MetaAIR study (n = 154, 61% Hispanic). Analyses were performed for each diet quality index separately, adjusting for demographics and BMI. Five proteins (ACY1, ADH4, AGXT, GSTA1, F7) and six metabolites (undecylenic acid, betaine, hyodeoxycholic acid, stearidonic acid, iprovalicarb, pyracarbolid) were associated with both diets (p < 0.05), though none were significant after adjustment for multiple comparisons. Overlapping proteins are involved in lipid and amino acid metabolism and in hemostasis, while overlapping metabolites include amino acid derivatives, bile acids, fatty acids, and pesticides. Enriched biological pathways were involved in macronutrient metabolism, immune function, and oxidative stress. These findings in young Hispanic adults contribute to efforts to develop precision nutrition and medicine for diverse populations.

Background & Aims: Exposure to poly- and perfluoroalkyl substances (PFAS), a class of persistent organic pollutants, is ubiquitous. Animal studies suggest that PFAS may increase risk of fatty liver and hepatocellular carcinoma (HCC) via impacts on hepatic lipid, amino acid, and glucose metabolism, but human data is lacking. We examined associations between PFAS exposure, altered metabolic pathways, and risk of non-viral HCC. Methods: In this nested case-control study, pre-diagnostic plasma PFAS and metabolomics were measured in 50 incident HCC cases and 50 individually matched controls from the Multiethnic Cohort (MEC) study. Cases/controls were matched by age, sex, race, and study area. PFAS exposure and risk of HCC were examined using conditional logistic regression. A metabolome-wide association study and pathway enrichment analysis was performed for PFAS exposure and HCC risk, and key metabolites/metabolic pathways were identified using a meet in the middle approach. Results: High perfluorooctane sulfonic acid (PFOS) levels (90th percentile from NHANES; >55 μg/L) were associated with 4.5-fold increased risk of HCC (odds ratio 4.5, 95% CI 1.2-16.0). Pathway enrichment analysis showed that PFOS exposure was associated with alterations in amino acid and glycan biosynthesis pathways, which were also associated with HCC risk. We identified 4 metabolites linking PFOS exposure with HCC, including glucose, butyric acid (a short-chain fatty acid), α-ketoisovaleric acid (a branched-chain α-keto acid), and 7α-hydroxy-3-oxo-4-cholestenoate (a bile acid), each of which was positively associated with PFOS exposure and risk of HCC. Conclusion: This proof-of-concept analysis shows that exposure to high PFOS levels was associated with increased risk of non-viral HCC, likely via alterations in glucose, amino acid, and bile acid metabolism. Larger studies are needed to confirm these findings. Lay summary: Per- and polyfluoroalkyl substances (PFAS), often referred to as “forever chemicals” because they are difficult to break down and stay in the human body for years, are extremely common and can cause liver damage. In a first of its kind study, we found that exposure to high levels of perfluorooctanesulfonic acid, one of the most common PFAS chemicals, was linked to increased risk of hepatocellular carcinoma in humans. Hepatocellular carcinoma is difficult to treat and is one of the most common forms of liver cancer, and these findings may provide new avenues for helping to prevent this disease.

Developing children are particularly vulnerable to the effects of exposure to per- and polyfluoroalkyl substances (PFAS), a group of endocrine disrupting chemicals. We hypothesized that early life exposure to PFASs is associated with poor metabolic health in children.We studied the association between prenatal and postnatal PFASs mixture exposure and cardiometabolic health in children, and the role of inflammatory proteins.In 1,101 mothers-child pairs from the Human Early Life Exposome project, we measured the concentrations of PFAS in blood collected in pregnancy and at 8 years (range = 6–12 years). We applied Bayesian Kernel Machine regression (BKMR) to estimate the associations between exposure to PFAS mixture and the cardiometabolic factors as age and sex- specific z-scores of waist circumference (WC), systolic and diastolic blood pressures (BP), and concentrations of triglycerides (TG), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) cholesterol. We measured thirty six inflammatory biomarkers in child plasma and examined the underlying role of inflammatory status for the exposure-outcome association by integrating the three panels into a network.Exposure to the PFAS mixture was positively associated with HDL-C and systolic BP, and negatively associated with WC, LDL-C and TG. When we examined the independent effects of the individual chemicals in the mixture, prenatal PFHxS was negatively associated with HDL-C and prenatal PFNA was positively associated with WC and these were opposing directions from the overall mixture. Further, the network consisted of five distinct communities connected with positive and negative correlations. The selected inflammatory biomarkers were positively, while the postnatal PFAS were negatively related with the included cardiometabolic factors, and only prenatal PFOA was positively related with the pro-inflammatory cytokine IL-1beta and WC.Our study supports that prenatal, rather than postnatal, PFAS exposure might contribute to an unfavorable lipidemic profile and adiposity in childhood.

Objective: To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children. Methods: Forty overweight and obese Hispanic children (8–14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1–3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile. Results: Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8–52.4) and 10.2 mg/dL (95% CI: 2.7–17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5–34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns. Conclusions: This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms. Keywords: Perfluoroalkyl substances, Type 2 diabetes, Glucose metabolism, Metabolomics, Children

We aimed to determine if the newborn gut microbiota is an underlying determinant of early life growth trajectories. 132 Hispanic infants were recruited at 1-month postpartum. The infant gut microbiome was characterized using 16S rRNA amplicon sequencing. Rapid infant growth was defined as a weight-for-age z-score (WAZ) change greater than 0.67 between birth and 12-months of age. Measures of infant growth included change in WAZ, weight-for-length z-score (WLZ), and body mass index (BMI) z-scores from birth to 12-months and infant anthropometrics at 12-months (weight, skinfold thickness). Of the 132 infants, 40% had rapid growth in the first year of life. Multiple metrics of alpha-diversity predicted rapid infant growth, including a higher Shannon diversity (OR = 1.83; 95% CI: 1.07–3.29; p = .03), Faith’s phylogenic diversity (OR = 1.41, 95% CI: 1.05–1.94; p = .03), and richness (OR = 1.04, 95% CI: 1.01–1.08; p = .02). Many of these alpha-diversity metrics were also positively associated with increases in WAZ, WLZ, and BMI z-scores from birth to 12-months (pall