Metabolism-Disrupting Chemical Mixtures during Pregnancy, Folic Acid Supplementation, and Liver Injury in Mother-Child Pairs.

Background and Aims: Scarce knowledge about the impact of metabolism-disrupting chemicals (MDCs) on liver injury limits opportunities for intervention. We evaluated pregnancy MDC-mixture associations with liver injury and effect modification by folic acid (FA) supplementation in mother-child pairs. Methods: We studied ∼200 mother-child pairs from the Mexican PROGRESS cohort, with measured 43 MDCs during pregnancy (estimated air pollutants, blood/urine metals or metalloids, urine high- and low-molecular-weight phthalate [HMWPs, LMWPs] and organophosphate-pesticide [OP] metabolites), and serum liver enzymes (ALT, AST) at ∼9 years post-parturition. We defined liver injury as elevated liver enzymes in children, and using established clinical scores for steatosis and fibrosis in mothers (i.e., AST:ALT, FLI, HSI, FIB-4). Bayesian Weighted Quantile Sum regression assessed MDC-mixture associations with liver injury outcomes. We further examined chemical-chemical interactions and effect modification by self-reported FA supplementation. Results: In children, many MDC-mixtures were associated with liver injury outcomes. Per quartile HMWP-mixture increase, ALT increased by 10.1% (95%CI: 1.67%, 19.4%) and AST by 5.27% (95% CI: 0.80%, 10.1%). LMWP-mixtures and air pollutant-mixtures were associated with higher AST and ALT, respectively. Air pollutant and non-essential metal/element associations with liver enzymes were attenuated by maternal cobalt blood concentrations ( p -interactions<0.05). In mothers, only the LMWP-mixture was associated with liver injury [OR=1.53 (95%CI: 1.01, 2.28) for HSI>36, and OR=1.62 (95%CI: 1.05, 2.49) for AST:ALT<1]. In mothers and children, most associations were attenuated (null) at FA supplementation≥600mcg/day ( p -interactions<0.05). Conclusions: Pregnancy MDC exposures may increase liver injury risk, particularly in children. These associations may be attenuated by higher FA supplementation and maternal cobalt levels.

Tweeting environmental pollution: Analyzing twitter language to uncover its correlation with county-level obesity rates in the United States.

BACKGROUND: Environmental pollution has been linked to obesogenic tendencies. Using environmental-related posts from Twitter (now known as X) from U.S. counties, we aim to uncover the association between Twitter linguistic data and U.S. county-level obesity rates. METHODS: Analyzing nearly 300 thousand tweets from January 2020 to December 2020 across 207 U.S. counties, using an innovative Differential Language Analysis technique and drawing county-level obesity data from the 2020 Food Environment Atlas to identify distinct linguistic features in Twitter relating to environmental-related posts correlated with socioeconomic status (SES) index indicators, obesity rates, and obesity rates controlled for SES index indicators. We also employed predictive modeling to estimate Twitter language's predictive capacity for obesity rates. RESULTS: Results revealed a negative correlation between environmental-related tweets and obesity rates, both before and after adjusting for SES. Contrarily, non-environmental-related tweets showed a positive association with higher county-level obesity rates, indicating that individuals living in counties with lower obesity rates tend to tweet environmental-related language more frequently than those living in counties with higher obesity rates. The findings suggest that linguistic patterns and expressions employed in discussing environmental-related themes on Twitter can offer unique insights into the prevailing cross-sectional patterns of obesity rates. CONCLUSIONS: Although Twitter users are a subset of the general population, incorporating environmental-related tweets and county-level obesity rates and using a novel language analysis technique make this study unique. Our results indicated that Twitter users engaging in more active dialog about environmental concerns might exhibit healthier lifestyle practices, contributing to reduced obesity rates.

Effects of liquid nicotine concentration and flavour on the acceptability of electronic nicotine delivery systems (ENDS) among people who smoke participating in a randomised controlled trial to reduce cigarette consumption.

BACKGROUND: Research is needed to understand the acceptability of electronic nicotine delivery systems (ENDS) as a smoking reduction aid. This study examines the acceptability of ENDS by liquid nicotine concentration and flavour among people who smoke using ENDS to reduce their smoking. METHODS: People who smoke cigarettes but were naïve to ENDS participated in a double-blind randomised controlled trial to reduce conventional cigarette smoking. Participants were randomised to either a control cigarette substitute (CS) or one of three ENDS groups; 0 mg/mL, 8 mg/mL or 36 mg/mL nicotine concentration. ENDS flavour was chosen by the participant (tobacco or menthol). Participants reported their CS, ENDS and cigarettes per day (CPD) from the past 7 days at 1-month, 3-month and 6-month follow-up visits. Participants also reported side effects and measures of satisfaction, psychological reward, aversion and craving relief. Outcome variables were modelled using linear mixed effects by the following groups: liquid nicotine concentration, flavour and a flavour-nicotine concentration interaction. RESULTS: Participants (n=520) were 41.2% male, 67.3% white, had a mean age of 46.2 years and smoked a mean of 18.6 CPD (SD=7.74) at baseline. All flavour and concentration groups decreased CPD from baseline to all follow-up visits with the 36 mg/mL experiencing the greatest reduction, compared with the 0 mg/mL and 8 mg/mL groups. All groups except the 36 mg/mL group decreased their product use over time. The use of menthol flavour was associated with fewer side effects at 3 months (p=0.02) and lesser aversion at 1 month (p=0.03) compared with tobacco-flavoured ENDS. The 36 mg/mL group experienced the greatest craving relief and greatest aversion compared with other groups. CONCLUSIONS: Both nicotine concentration and flavour appear to have independent, as well as interactive, effects that influence ENDS acceptability among people who use cigarettes.

Prenatal exposure to metal mixtures and childhood temporal processing in the PROGRESS Birth Cohort Study: Modification by childhood obesity.

Children are frequently exposed to various biological trace metals, some essential for their development, while others can be potent neurotoxicants. Furthermore, the inflammatory and metabolic conditions associated with obesity may interact with and amplify the impact of metal exposure on neurodevelopment. However, few studies have assessed the potential modification effect of body mass index (BMI). As a result, we investigated the role of child BMI phenotype on the relationship between prenatal exposure to metal mixtures and temporal processing. Leveraging the PROGRESS birth cohort in Mexico City, children (N = 563) aged 6-9 years completed a Temporal Response Differentiation (TRD) task where they had to hold a lever down for 10-14 s. Blood and urinary metal (As, Pb, Cd, and Mn) measurements were collected from mothers in the 2nd and 3rd trimesters. Child BMI z-scores were dichotomized to normal (between -2 and +0.99) and high (≥1.00). Covariate-adjusted weighted quantile sum (WQS) regression models were used to estimate and examine the combined effect of metal biomarkers (i.e., blood and urine) on TRD measures. Effect modification by the child's BMI was evaluated using 2-way interaction terms. Children with a high BMI and greater exposure to the metal mixture during prenatal development exhibited significant temporal processing deficits compared to children with a normal BMI. Notably, children with increased exposure to the metal mixture and higher BMI had a decrease in the percent of tasks completed (ß = -10.13; 95 % CI: -19.84, -0.42), number of average holds (ß = -2.15; 95 % CI: -3.88, -0.41), longer latency (ß = 0.78; 95 % CI: 0.13, 1.44), and greater variability in the standard deviation of the total hold time (ß = 2.08; 95 % CI: 0.34, 3.82) compared to normal BMI children. These findings implicate that high BMI may amplify the effect of metals on children's temporal processing. Understanding the relationship between metal exposures, temporal processing, and childhood obesity can provide valuable insights for developing targeted environmental interventions.

Akkermansia muciniphila modifies the association between metal exposure during pregnancy and depressive symptoms in late childhood.

Emerging research suggests that exposures to metals during pregnancy and gut microbiome (GM) disruptions are associated with depressive disorders in childhood. Akkermansia muciniphila, a GM bacteria, has been studied for its potential antidepressant effects. However, its role in the influence of prenatal metal exposures on depressive symptoms during childhood is unknown. Leveraging a well-characterized pediatric longitudinal birth cohort and its microbiome substudy (n=112) and using a state-of-the-art machine-learning model, we investigated whether the presence of A.muciniphila in GM of 9-11-year-olds modifies the associations between exposure to a specific group of metals (or metal-clique) during pregnancy and concurrent childhood depressive symptoms. Among children with no A.muciniphila, a metal-clique of Zinc-Chromium-Cobalt was strongly associated with increased depression score (P<0.0001), whereas, for children with A.muciniphila, this same metal-clique was weakly associated with decreased depression score(P<0.4). Our analysis provides the first exploratory evidence hypothesizing A. muciniphila as a probiotic intervention attenuating the effect of prenatal metal-exposures-associated depressive disorders in late childhood.

Prenatal metal exposures and childhood gut microbial signatures are associated with depression score in late childhood.

BACKGROUND: Childhood depression is a major public health issue worldwide. Previous studies have linked both prenatal metal exposures and the gut microbiome to depression in children. However, few, if any, have studied their interacting effect in specific subgroups of children. OBJECTIVES: Using an interpretable machine-learning method, this study investigates whether children with specific combinations of prenatal metals and childhood microbial signatures (cliques or groups of metals and microbes) were more likely to have higher depression scores at 9-11 years of age. METHODS: We leveraged data from a well-characterized pediatric longitudinal birth cohort in Mexico City and its microbiome substudy (n = 112). Eleven metal exposures were measured in maternal whole blood samples in the second and third trimesters of pregnancy. The gut microbial abundances were measured at 9-11-year-olds using shotgun metagenomic sequencing. Depression symptoms were assessed using the Child Depression Index (CDI) t-scores at 9-11 years of age. We used Microbial and Chemical Exposure Analysis (MiCxA), which combines interpretable machine-learning into a regression framework to identify and estimate joint associations of metal-microbial cliques in specific subgroups. Analyses were adjusted for relevant covariates. RESULTS: We identified a subgroup of children (11.6 % of the sample) characterized by a four-component metal-microbial clique that had a significantly high depression score (15.4 % higher than the rest) in late childhood. This metal-microbial clique consisted of high Zinc in the second trimester, low Cobalt in the third trimester, a high abundance of Bacteroides fragilis, a high abundance of Faecalibacterium prausnitzii. All combinations of cliques (two-, three-, and four-components) were significantly associated with increased log-transformed t-scored CDI (ß = 0.14, 95%CI = [0.05,0.23], P < 0.01 for the four-component clique). SIGNIFICANCE: This study offers a new approach to chemical-microbial analysis and a novel demonstration that children with specific gut microbiome cliques and metal exposures during pregnancy may have a higher likelihood of elevated depression scores.

Per- and Poly-Fluoroalkyl Substances Exposure Is Associated With Later Occurrence of Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is an immune-mediated inflammatory disease of the intestinal tract of elusive etiology. Environmental chemical exposures are increasingly acknowledged as a potential IBD risk factor. Per- and poly-fluoroalkyl substances (PFASs), a large class of persistent fluorinated organic chemicals used in industrial applications and consumer products such as paints, food packaging, and nonstick cookware, for over 6 decades, may be implicated in IBD etiology. Yet, epidemiological evidence has so far been scarce. Exposures to a few legacy PFASs, including perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorodecanoic (PFDA), and perfluorohexane sulfonate (PFHxS), have been associated with immunotoxicity and increased risk of other immune-mediated diseases,1 but data for their potential association with IBD are conflicting.2,3 Further, the impact of more recently emerging PFAS chemicals on IBD risk has not been studied.

Prenatal Lead Exposure Is Associated with Reduced Abundance of Beneficial Gut Microbial Cliques in Late Childhood: An Investigation Using Microbial Co-Occurrence Analysis (MiCA).

Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multibacteria relationships (microbial cliques). We present a novel analytical approach to identify microbial cliques within the gut microbiome of children at 9-11 years associated with prenatal lead (Pb) exposure. Data came from a subset of participants (n = 123) in the Programming Research in Obesity, Growth, Environment and Social Stressors cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance. With second-trimester Pb exposure, we identified a two-taxa microbial clique that included Bifidobacterium adolescentis and Ruminococcus callidus and a three-taxa clique that also included Prevotella clara. Increasing second-trimester Pb exposure was associated with significantly increased odds of having the two-taxa microbial clique below the median relative abundance (odds ratio (OR) = 1.03, 95% confidence interval (CI) [1.01-1.05]). Using a novel combination of machine learning and causal inference, MiCA identified a significant association between second-trimester Pb exposure and the reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood.

PFAS Exposures and the Human Metabolome: A Systematic Review of Epidemiological Studies.

Purpose of Review: There is a growing interest in understanding the health effects of exposure to per- and polyfluoroalkyl substances (PFAS) through the study of the human metabolome. In this systematic review, we aimed to identify consistent findings between PFAS and metabolomic signatures. We conducted a search matching specific keywords that was independently reviewed by two authors on two databases (EMBASE and PubMed) from their inception through July 19, 2022 following PRISMA guidelines. Recent Findings: We identified a total of 28 eligible observational studies that evaluated the associations between 31 different PFAS exposures and metabolomics in humans. The most common exposure evaluated was legacy long-chain PFAS. Population sample sizes ranged from 40 to 1,105 participants at different stages across the lifespan. A total of 19 studies used a non-targeted metabolomics approach, 7 used targeted approaches, and 2 included both. The majority of studies were cross-sectional (n = 25), including four with prospective analyses of PFAS measured prior to metabolomics. Summary: Most frequently reported associations across studies were observed between PFAS and amino acids, fatty acids, glycerophospholipids, glycerolipids, phosphosphingolipids, bile acids, ceramides, purines, and acylcarnitines. Corresponding metabolic pathways were also altered, including lipid, amino acid, carbohydrate, nucleotide, energy metabolism, glycan biosynthesis and metabolism, and metabolism of cofactors and vitamins. We found consistent evidence across studies indicating PFAS-induced alterations in lipid and amino acid metabolites, which may be involved in energy and cell membrane disruption.

Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment.

A growing body of literature suggests that developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, investigating the effect of interactions among these ECs can be challenging. We introduced a combination of the classical exposure-mixture Weighted Quantile Sum (WQS) regression and a machine-learning method termed Signed iterative Random Forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In a case-control Childhood Autism Risks from Genetics and Environment (CHARGE) study, we evaluated multiordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs no). WQS-SiRF identified two synergistic two-ordered interactions between (1) trace-element cadmium (Cd) and the organophosphate pesticide metabolite diethyl-phosphate (DEP); and (2) 2,4,6-trichlorophenol (TCP-246) and DEP. Both interactions were suggestively associated with increased odds of ASD diagnosis in the subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover potentially biologically relevant chemical-chemical interactions associated with ASD.

Prenatal lead exposure is negatively associated with the gut microbiome in childhood.

Background: Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood. Objectives: This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old. Methods: Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders. Results: Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6 (SE = 2.1) ug/L and 34.9 (SE = 2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tß = -0.17, 95%CI = [-0.46,0.11]; 3Tß = -0.17, 95%CI = [-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure. Discussion: Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.

Neuronally enriched microvesicle RNAs are differentially expressed in the serums of Parkinson's patients.

Background: Circulating small RNAs (smRNAs) originate from diverse tissues and organs. Previous studies investigating smRNAs as potential biomarkers for Parkinson's disease (PD) have yielded inconsistent results. We investigated whether smRNA profiles from neuronally-enriched serum exosomes and microvesicles are altered in PD patients and discriminate PD subjects from controls. Methods: Demographic, clinical, and serum samples were obtained from 60 PD subjects and 40 age- and sex-matched controls. Exosomes and microvesicles were extracted and isolated using a validated neuronal membrane marker (CD171). Sequencing and bioinformatics analyses were used to identify differentially expressed smRNAs in PD and control samples. SmRNAs also were tested for association with clinical metrics. Logistic regression and random forest classification models evaluated the discriminative value of the smRNAs. Results: In serum CD171 enriched exosomes and microvesicles, a panel of 29 smRNAs was expressed differentially between PD and controls (false discovery rate (FDR) < 0.05). Among the smRNAs, 23 were upregulated and 6 were downregulated in PD patients. Pathway analysis revealed links to cellular proliferation regulation and signaling. Least absolute shrinkage and selection operator adjusted for the multicollinearity of these smRNAs and association tests to clinical parameters via linear regression did not yield significant results. Univariate logistic regression models showed that four smRNAs achieved an AUC ≥ 0.74 to discriminate PD subjects from controls. The random forest model had an AUC of 0.942 for the 29 smRNA panel. Conclusion: CD171-enriched exosomes and microvesicles contain the differential expression of smRNAs between PD and controls. Future studies are warranted to follow up on the findings and understand the scientific and clinical relevance.

Mediators of the association between maternal body mass index and breastfeeding duration in 3 international cohorts.

BACKGROUND: Maternal obesity has been associated with shorter breastfeeding duration, but little is known about mediating factors explaining this association. It is important to assess these relationships across diverse populations because breastfeeding is culturally patterned. OBJECTIVES: We investigated the association of prepregnancy maternal body mass index (BMI) with breastfeeding outcomes and potential mediators of this relationship in 3 culturally diverse international cohorts. METHODS: We analyzed 5120 singleton pregnancies from mother-child cohorts in Spain (INfancia y Medio Ambiente), Greece (Rhea), and the United States (Project Viva). Outcome variables were duration of any and exclusive breastfeeding. A priori hypothesized mediators in the association of maternal prepregnancy BMI with breastfeeding were birthweight (BW), maternal prenatal C-reactive protein (CRP), cesarean delivery, maternal dietary inflammatory index (DII) during pregnancy, gestational age at delivery, and gestational diabetes mellitus (GDM). We estimated the association between BMI and breastfeeding duration using linear regression adjusting for confounders. Mediation analysis estimated direct and indirect effects of maternal overweight/obesity on breastfeeding for each mediator. RESULTS: Women with overweight and obesity had shorter duration of any and exclusive breastfeeding compared with normal-weight women (any: overweight ß = -0.79 mo, 95% CI: -1.17, -0.40; obese ß = -1.75 mo 95% CI: -2.25, -1.25; exclusive: overweight ß = -0.30 mo, 95% CI: -0.42, -0.16; obese ß = -0.73 mo, 95% CI: -0.90, -0.55). Significant mediators (% change in effect estimate) of this association were higher CRP (exclusive: 5.12%), cesarean delivery (any: 6.54%; exclusive: 7.69%), and higher DII (any: 6.48%; exclusive: 7.69%). GDM, gestational age, and BW did not mediate the association of maternal weight status with breastfeeding. CONCLUSIONS: Higher prepregnancy BMI is associated with shorter duration of any and exclusive breastfeeding. Maternal dietary inflammation, systemic inflammation, and mode of delivery may be key modifiable mediators of this association. Identification of mediators provides potential targets for interventions to improve breastfeeding outcomes.

Prenatal Lead Exposure is Negatively Associated with the Gut Microbiome in Childhood.

Background: Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood. Objectives: This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old. Methods: Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders. Results: Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6(SE=2.1) ug/L and 34.9(SE=2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tß=-0.17,95%CI=[-0.46,0.11]; 3Tß=-0.17,95%CI=[-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure. Discussion: Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.

Exposure to perfluoroalkyl substances and women's fertility outcomes in a Singaporean population-based preconception cohort.

OBJECTIVES: Experimental models have demonstrated a link between exposure to perfluoroalkyl substances (PFAS) and decreased fertility and fecundability; however, human studies are scarce. We assessed the associations between preconception plasma PFAS concentrations and fertility outcomes in women. METHODS: In a case-control study nested within the population-based Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO), we measured PFAS in plasma collected in 2015-2017 from 382 women of reproductive age trying to conceive. Using Cox proportional hazards regression (fecundability ratios [FRs]) and logistic regression (odds ratios [ORs]) models, we assessed the associations of individual PFAS with time-to-pregnancy (TTP), and the likelihoods of clinical pregnancy and live birth, respectively, over one year of follow-up, adjusting for analytical batch, age, education, ethnicity, and parity. We used Bayesian weighted quantile sum (BWQS) regression to assess the associations of the PFAS mixture with fertility outcomes. RESULTS: We found a 5-10 % reduction in fecundability per quartile increase of exposure to individual PFAS (FRs [95 % CIs] for clinical pregnancy = 0.90 [0.82, 0.98] for PFDA; 0.88 [0.79, 0.99] for PFOS; 0.95 [0.86, 1.06] for PFOA; 0.92 [0.84, 1.00] for PFHpA). We observed similar decreased odds of clinical pregnancy (ORs [95 % CIs] = 0.74 [0.56, 0.98] for PFDA; 0.76 [0.53, 1.09] for PFOS; 0.83 [0.59, 1.17] for PFOA; 0.92 [0.70, 1.22] for PFHpA) and live birth per quartile increases of individual PFAS and the PFAS mixture (ORs [95 % CIs] = 0.61 [0.37, 1.02] for clinical pregnancy, and 0.66 [0.40, 1.07] for live birth). Within the PFAS mixture, PFDA followed by PFOS, PFOA, and PFHpA were the biggest contributors to these associations. We found no evidence of association for PFHxS, PFNA, and PFHpS and the fertility outcomes examined. CONCLUSIONS: Higher PFAS exposures may be associated with decreased fertility in women. The potential impact of ubiquitous PFAS exposures on infertility mechanisms requires further investigation.

Cross-sectional associations of maternal PFAS exposure on SARS-CoV-2 IgG antibody levels during pregnancy.

BACKGROUND: Perfluoroalkylated substances (PFAS) are man-made, persistent organic compounds with immune-modulating potentials. Given that pregnancy itself represents an altered state of immunity, PFAS exposure-related immunotoxicity is an important environmental factor to consider in SARS-CoV-2 infection during pregnancy as it may further affect humoral immune responses. AIM: To investigate the relationship between maternal plasma PFAS concentrations and SARS-CoV-2 antibody levels in a NYC-based pregnancy cohort. METHODS: Maternal plasma was collected from 72 SARS-CoV-2 IgG + participants of the Generation C Study, a birth cohort established at the beginning of the COVID-19 pandemic in New York City. Maternal SARS-CoV-2 anti-spike IgG antibody levels were measured using ELISA. A panel of 16 PFAS congeners were measured in maternal plasma using a targeted UHPLC-MS/MS-based assay. Spearman correlations and linear regressions were employed to explore associations between maternal IgG antibody levels and plasma PFAS concentrations. Weighted quantile sum (WQS) regression was also used to evaluate mixture effects of PFAS. Models were adjusted for maternal age, gestational age at which SARS-CoV-2 IgG titer was measured, COVID-19 vaccination status prior to IgG titer measurement, maternal race/ethnicity, parity, type of insurance and pre-pregnancy BMI. RESULTS: Our study population is ethnically diverse with an average maternal age of 32 years. Of the 16 PFAS congeners measured, nine were detected in more than 60% samples. Importantly, all nine congeners were negatively correlated with SARS-CoV-2 anti-spike IgG antibody levels; n-PFOA and PFHxS, PFHpS, and PFHxA reached statistical significance (p < 0.05) in multivariable analyses. When we examined the mixture effects using WQS, a quartile increase in the PFAS mixture-index was significantly associated with lower maternal IgG antibody titers (beta [95% CI] = -0.35 [-0.52, -0.17]). PFHxA was the top contributor to the overall mixture effect. CONCLUSIONS: Our study results support the notion that PFAS, including short-chain emerging PFAS, act as immunosuppressants during pregnancy. Whether such compromised immune activity leads to downstream health effects, such as the severity of COVID-19 symptoms, adverse obstetric outcomes or neonatal immune responses remains to be investigated.

Cysteine restriction-specific effects of sulfur amino acid restriction on lipid metabolism.

Decreasing the dietary intake of methionine exerts robust anti-adiposity effects in rodents but modest effects in humans. Since cysteine can be synthesized from methionine, animal diets are formulated by decreasing methionine and eliminating cysteine. Such diets exert both methionine restriction (MR) and cysteine restriction (CR), that is, sulfur amino acid restriction (SAAR). Contrarily, SAAR diets formulated for human consumption included cysteine, and thus might have exerted only MR. Epidemiological studies positively correlate body adiposity with plasma cysteine but not methionine, suggesting that CR, but not MR, is responsible for the anti-adiposity effects of SAAR. Whether this is true, and, if so, the underlying mechanisms are unknown. Using methionine- and cysteine-titrated diets, we demonstrate that the anti-adiposity effects of SAAR are due to CR. Data indicate that CR increases serinogenesis (serine biosynthesis from non-glucose substrates) by diverting substrates from glyceroneogenesis, which is essential for fatty acid reesterification and triglyceride synthesis. Molecular data suggest that CR depletes hepatic glutathione and induces Nrf2 and its downstream targets Phgdh (the serine biosynthetic enzyme) and Pepck-M. In mice, the magnitude of SAAR-induced changes in molecular markers depended on dietary fat concentration (60% fat >10% fat), sex (males > females), and age-at-onset (young > adult). Our findings are translationally relevant as we found negative and positive correlations of plasma serine and cysteine, respectively, with triglycerides and metabolic syndrome criteria in a cross-sectional epidemiological study. Controlled feeding of low-SAA, high-polyunsaturated fatty acid diets increased plasma serine in humans. Serinogenesis might be a target for treating hypertriglyceridemia.

Association of Prenatal Exposure to Endocrine-Disrupting Chemicals With Liver Injury in Children.

Importance: Prenatal exposures to endocrine-disrupting chemicals (EDCs) may increase the risk for liver injury in children; however, human evidence is scarce, and previous studies have not considered potential EDC-mixture effects. Furthermore, the association between prenatal EDC exposure and hepatocellular apoptosis in children has not been studied previously. Objective: To investigate associations of prenatal exposure to EDC mixtures with liver injury risk and hepatocellular apoptosis in childhood. Design, Setting, and Participants: This prospective cohort study used data collected from April 1, 2003, to February 26, 2016, from mother-child pairs from the Human Early-Life Exposome project, a collaborative network of 6 ongoing, population-based prospective birth cohort studies from 6 European countries (France, Greece, Lithuania, Norway, Spain, and the UK). Data were analyzed from April 1, 2021, to January 31, 2022. Exposures: Three organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 3 phenols, 4 parabens, 10 phthalates, 4 organophosphate pesticides, 5 perfluoroalkyl substances, and 9 metals. Main Outcomes and Measures: Child serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), and CK-18 were measured at 6 to 11 years of age. Risk for liver injury was defined as having ALT, AST, and/or GGT levels above the 90th percentile. Associations of liver injury or cytokeratin 18 (CK-18) levels with each chemical group among the 45 EDCs measured in maternal blood or urine samples collected in pregnancy were estimated using 2 complimentary exposure-mixture methods: bayesian weighted quantile sum (BWQS) and bayesian kernel machine regression. Results: The study included 1108 mothers (mean [SD] age at birth, 31.0 [4.7] years) and their singleton children (mean [SD] age at liver assessment, 8.2 [1.6] years; 598 [54.0%] boys). Results of the BWQS method indicated increased odds of liver injury per exposure-mixture quartile increase for organochlorine pesticides (odds ratio [OR], 1.44 [95% credible interval (CrI), 1.21-1.71]), PBDEs (OR, 1.57 [95% CrI, 1.34-1.84]), perfluoroalkyl substances (OR, 1.73 [95% CrI, 1.45-2.09]), and metals (OR, 2.21 [95% CrI, 1.65-3.02]). Decreased odds of liver injury were associated with high-molecular-weight phthalates (OR, 0.74 [95% CrI, 0.60-0.91]) and phenols (OR, 0.66 [95% CrI, 0.54-0.78]). Higher CK-18 levels were associated with a 1-quartile increase in polychlorinated biphenyls (ß, 5.84 [95% CrI, 1.69-10.08] IU/L) and PBDEs (ß, 6.46 [95% CrI, 3.09-9.92] IU/L). Bayesian kernel machine regression showed associations in a similar direction as BWQS for all EDCs and a nonlinear association between phenols and CK-18 levels. Conclusions and Relevance: With a combination of 2 state-of-the-art exposure-mixture approaches, consistent evidence suggests that prenatal exposures to EDCs are associated with higher risk for liver injury and CK-18 levels and constitute a potential risk factor for pediatric nonalcoholic fatty liver disease.

Predictors of Diffusing Capacity in Children With Sickle Cell Disease: A Longitudinal Study.

Background: Gas exchange abnormalities in Sickle Cell Disease (SCD) may represent cardiopulmonary deterioration. Identifying predictors of these abnormalities in children with SCD (C-SCD) may help us understand disease progression and develop informed management decisions. Objectives: To identify pulmonary function tests (PFT) estimates and biomarkers of disease severity that are associated with and predict abnormal diffusing capacity (DLCO) in C-SCD. Methods: We obtained PFT data from 51 C-SCD (median age:12.4 years, male: female = 29:22) (115 observations) and 22 controls (median age:11.1 years, male: female = 8:14), formulated a rank list of DLCO predictors based on machine learning algorithms (XGBoost) or linear mixed-effect models, and compared estimated DLCO to the measured values. Finally, we evaluated the association between measured or estimated DLCO and clinical outcomes, including SCD crises, pulmonary hypertension, and nocturnal desaturation. Results: Hemoglobin-adjusted DLCO (%) and several PFT indices were diminished in C-SCD compared to controls. Both statistical approaches ranked FVC (%), neutrophils (%), and FEF25-75 (%) as the top three predictors of DLCO. XGBoost had superior performance compared to the linear model. Both measured and estimated DLCO demonstrated a significant association with SCD severity: higher DLCO, estimated by XGBoost, was associated with fewer SCD crises [beta = -0.084 (95%CI: -0.13, -0.033)] and lower TRJV [beta = -0.009 (-0.017, -0.001)], but not with nocturnal desaturation (p = 0.12). Conclusions: In this cohort of C-CSD, DLCO was associated with PFT estimates representing restrictive lung disease (FVC, TLC), airflow obstruction (FEF25-75, FEV1/FVC, R5), and inflammation (neutrophilia). We used these indices to estimate DLCO, and show association with disease outcomes, underscoring the prediction models' clinical relevance.

Factors Associated with SARS-CoV-2 Infection in Physician Trainees in New York City during the First COVID-19 Wave.

Occupational and non-occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported in healthcare workers (HCWs), but studies evaluating risk factors for infection among physician trainees are lacking. We aimed to identify sociodemographic, occupational, and community risk factors among physician trainees during the first wave of coronavirus disease 2019 (COVID-19) in New York City. In this retrospective study of 328 trainees at the Mount Sinai Health System in New York City, we administered a survey to assess risk factors for SARS-CoV-2 infection between 1 February and 30 June 2020. SARS-CoV-2 infection was determined by self-reported and laboratory-confirmed IgG antibody and reverse transcriptase-polymerase chain reaction test results. We used Bayesian generalized linear mixed effect regression to examine associations between hypothesized risk factors and infection odds. The cumulative incidence of infection was 20.1%. Assignment to medical-surgical units (OR, 2.51; 95% CI, 1.18-5.34), and training in emergency medicine, critical care, and anesthesiology (OR, 2.93; 95% CI, 1.24-6.92) were independently associated with infection. Caring for unfamiliar patient populations was protective (OR, 0.16; 95% CI, 0.03-0.73). Community factors were not statistically significantly associated with infection after adjustment for occupational factors. Our findings may inform tailored infection prevention strategies for physician trainees responding to the COVID-19 pandemic.