Sensitive periods and other timing hypotheses in developmental psychopathology: A tutorial.

Researchers often aim to assess whether repeated measures of an exposure are associated with repeated measures of an outcome. A question of particular interest is how associations between exposures and outcomes may differ over time. In other words, researchers may seek the best form of a temporal model. While several models are possible, researchers often consider a few key models. For example, researchers may hypothesize that an exposure measured during a sensitive period may be associated with repeated measures of the outcome over time. Alternatively, they may hypothesize that the exposure measured immediately before the current time period may be most strongly associated with the outcome at the current time. Finally, they may hypothesize that all prior exposures are important. Many analytic methods cannot compare and evaluate these alternative temporal models, perhaps because they make the restrictive assumption that the associations between exposures and outcomes remains constant over time. Instead, we provide a tutorial describing four temporal models that allow the associations between repeated measures of exposures and outcomes to vary, and showing how to test which temporal model is best supported by the data. By finding the best temporal model, developmental psychopathology researchers can find optimal windows for intervention.

Prenatal black carbon exposure and DNA methylation in umbilical cord blood.

BACKGROUND/OBJECTIVES: Prenatal exposure to ambient air pollution is associated with adverse cardiometabolic outcomes in childhood. We previously observed that prenatal black carbon (BC) was inversely associated with adiponectin, a hormone secreted by adipocytes, in early childhood. Changes to DNA methylation have been proposed as a potential mediator linking in utero exposures to lasting health impacts. METHODS: Among 532 mother-child pairs enrolled in the Colorado-based Healthy Start study, we performed an epigenome-wide association study of the relationship between prenatal exposure to a component of air pollution, BC, and DNA methylation in cord blood. Average pregnancy ambient BC was estimated at the mother's residence using a spatiotemporal prediction model. DNA methylation was measured using the Illumina 450K array. We used multiple linear regression to estimate associations between prenatal ambient BC and 429,246 cysteine-phosphate-guanine sites (CpGs), adjusting for potential confounders. We identified differentially methylated regions (DMRs) using DMRff and ENmix-combp. In a subset of participants (n = 243), we investigated DNA methylation as a potential mediator of the association between prenatal ambient BC and lower adiponectin in childhood. RESULTS: We identified 44 CpGs associated with average prenatal ambient BC after correcting for multiple testing. Several genes annotated to the top CpGs had reported functions in the immune system. There were 24 DMRs identified by both DMRff and ENmix-combp. One CpG (cg01123250), located on chromosome 2 and annotated to the UNC80 gene, was found to mediate approximately 20% of the effect of prenatal BC on childhood adiponectin, though the confidence interval was wide (95% CI: 3, 84). CONCLUSIONS: Prenatal BC was associated with DNA methylation in cord blood at several sites and regions in the genome. DNA methylation may partially mediate associations between prenatal BC and childhood cardiometabolic outcomes.

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.

BACKGROUND: A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations. METHODS: Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach. RESULTS: When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated. CONCLUSIONS: Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.

Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.

AIM: To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents using electronic health records (EHRs) from the UF Health System. MATERIALS AND METHODS: The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012-2020). We randomly selected 536 presumed cases among individuals aged <18 years who had (1) glycated haemoglobin levels ≥ 6.5%; or (2) fasting glucose levels ≥126 mg/dL; or (3) random plasma glucose levels ≥200 mg/dL; or (4) a diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type. RESULTS: Presumed cases without type 1 (T1D) or type 2 diabetes (T2D) diagnosis codes were categorized as non-diabetes/other types of diabetes. The rest were categorized as T1D if the most recent diagnosis was T1D, or otherwise categorized as T2D if the most recent diagnosis was T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from Step 1. Among the 536 reviewed cases, 159 and 64 had T1D and T2D, respectively. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98% and 96%, respectively, for T1D and 95%, 95% and 73% for T2D. CONCLUSION: We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods.

Lipidomics of infant mesenchymal stem cells associate with the maternal milieu and child adiposity.

Our objective was to interrogate mesenchymal stem cell (MSC) lipid metabolism and gestational exposures beyond maternal body mass that may contribute to child obesity risk. MSCs were cultured from term infants of mothers with obesity (n = 16) or normal weight (n = 15). In MSCs undergoing myogenesis in vitro, we used lipidomics to distinguish phenotypes by unbiased cluster analysis and lipid challenge (24-hour excess fatty acid [24hFA]). We measured MSC AMP-activated protein kinase (AMPK) activity and fatty acid oxidation (FAO), and a composite index of maternal glucose, insulin, triglycerides, free fatty acids, TNF-α, and high-density lipoprotein and total cholesterol in fasting blood from mid and late gestation (~17 and ~27 weeks, respectively). We measured child adiposity at birth (n = 29), 4-6 months (n = 29), and 4-6 years (n = 13). Three MSC clusters were distinguished by triacylglycerol (TAG) stores, with greatest TAGs in Cluster 2. All clusters increased acylcarnitines and TAGs with 24hFA, although Cluster 2 was more pronounced and corresponded to AMPK activation and FAO. Maternal metabolic markers predicted MSC clusters and child adiposity at 4-6 years (both highest in Cluster 3). Our data support the notion that MSC phenotypes are predicted by comprehensive maternal metabolic milieu exposures, independent of maternal BMI, and suggest utility as an at-birth predictor for child adiposity, although validation with larger longitudinal samples is warranted.

Neighborhood Food Access in Early Life and Trajectories of Child Body Mass Index and Obesity.

Importance: Limited access to healthy foods, resulting from residence in neighborhoods with low food access, is a public health concern. The contribution of this exposure in early life to child obesity remains uncertain. Objective: To examine associations of neighborhood food access during pregnancy or early childhood with child body mass index (BMI) and obesity risk. Design, Setting, and Participants: Data from cohorts participating in the US nationwide Environmental Influences on Child Health Outcomes consortium between January 1, 1994, and March 31, 2023, were used. Participant inclusion required a geocoded residential address in pregnancy (mean 32.4 gestational weeks) or early childhood (mean 4.3 years) and information on child BMI. Exposures: Residence in low-income, low-food access neighborhoods, defined as low-income neighborhoods where the nearest supermarket is more than 0.5 miles for urban areas or more than 10 miles for rural areas. Main Outcomes and Measures: BMI z score, obesity (age- and sex-specific BMI ≥95th percentile), and severe obesity (age- and sex-specific BMI ≥120% of the 95th percentile) from age 0 to 15 years. Results: Of 28 359 children (55 cohorts; 14 657 [51.7%] male and 13 702 [48.3%] female; 590 [2.2%] American Indian, Alaska Native, Native Hawaiian, or Other Pacific Islander; 1430 [5.4%] Asian; 4034 [15.3%] Black; 17 730 [67.2%] White; and 2592 [9.8%] other [unspecified] or more than 1 race; 5754 [20.9%] Hispanic and 21 838 [79.1%] non-Hispanic) with neighborhood food access data, 23.2% resided in low-income, low-food access neighborhoods in pregnancy and 24.4% in early childhood. After adjusting for individual sociodemographic characteristics, residence in low-income, low-food access (vs non-low-income, low-food access) neighborhoods in pregnancy was associated with higher BMI z scores at ages 5 years (ß, 0.07; 95% CI, 0.03-0.11), 10 years (ß, 0.11; 95% CI, 0.06-0.17), and 15 years (ß, 0.16; 95% CI, 0.07-0.24); higher obesity risk at 5 years (risk ratio [RR], 1.37; 95% CI, 1.21-1.55), 10 years (RR, 1.71; 95% CI, 1.37-2.12), and 15 years (RR, 2.08; 95% CI, 1.53-2.83); and higher severe obesity risk at 5 years (RR, 1.21; 95% CI, 0.95-1.53), 10 years (RR, 1.54; 95% CI, 1.20-1.99), and 15 years (RR, 1.92; 95% CI, 1.32-2.80). Findings were similar for residence in low-income, low-food access neighborhoods in early childhood. These associations were robust to alternative definitions of low income and low food access and additional adjustment for prenatal characteristics associated with child obesity. Conclusions: Residence in low-income, low-food access neighborhoods in early life was associated with higher subsequent child BMI and higher risk of obesity and severe obesity. We encourage future studies to examine whether investments in neighborhood resources to improve food access in early life would prevent child obesity.

The predictive utility of the in utero exposome for childhood adiposity in independent and integrated frameworks.

OBJECTIVES: To assess the predictive potential of the in utero exposome in relation to childhood adiposity as indicated by body mass index z-scores (BMIz) and the fourth versus first quartile of % fat mass (FM) at median age of 4.6 years. METHODS: We leveraged data on clinical risk factors for childhood obesity during the perinatal period, along with cord blood per/polyfluoroalkyl substances (PFAS) and cord blood DNA methylation, in 268 mother-offspring pairs. We used the sparsity ranked LASSO penalized regression framework for each outcome and assessed model performance based on % variability explained for BMIz and area under the receiver operating characteristic curve (AUC) for the fourth versus first quartile of %FM. We employed cross-validation for model tuning and split-sample validation for model evaluation. RESULTS: Mean ± SD BMIz was 0.01 ± 1.1, %FM was 19.8 ± 6.34%. The optimal model for predicting BMIz explained 19.1% of the variability in the validation set and included only clinical characteristics: maternal pre-pregnancy BMI, paternal BMI, gestational weight gain, physical activity during pregnancy and child race/ethnicity. The optimal model for fourth versus first quartiles of %FM achieved an AUC of 0.82 ± 0.01 in the validation set, with the clinical features again emerging as the strongest predictors. CONCLUSION: In this study sample, perinatal chemical exposures and the epigenome have low utility in predicting childhood adiposity, beyond known clinical risk factors.

Differentially methylated regions interrogated for metastable epialleles associate with offspring adiposity.

Aim: Assess if cord blood differentially methylated regions (DMRs) representing human metastable epialleles (MEs) associate with offspring adiposity in 588 maternal-infant dyads from the Colorado Health Start Study.Materials & methods: DNA methylation was assessed via the Illumina 450K array (~439,500 CpG sites). Offspring adiposity was obtained via air displacement plethysmography. Linear regression modeled the association of DMRs potentially representing MEs with adiposity.Results & conclusion: We identified two potential MEs, ZFP57, which associated with infant adiposity change and B4GALNT4, which associated with infancy and childhood adiposity change. Nine DMRs annotating to genes that annotated to MEs associated with change in offspring adiposity (false discovery rate <0.05). Methylation of approximately 80% of DMRs identified associated with decreased change in adiposity.

[Box: see text].

Associations of urinary biomarkers of phthalates, phenols, parabens, and organophosphate esters with glycemic traits in pregnancy: The Healthy Start Study.

BACKGROUND: Certain endocrine-disrupting chemicals (EDCs) are widespread in consumer products and may alter glucose metabolism. However, the impact of EDC exposures on glucose and insulin regulation during pregnancy is incompletely understood, despite potential adverse consequences for maternal and infant health. We estimated associations between 37 urinary biomarkers of EDCs and glucose-insulin traits among pregnant women. METHODS: Seventeen phthalate or phthalate substitute metabolites, six environmental phenols, four parabens, and ten organophosphate ester metabolites were quantified in mid-pregnancy urine from 298 participants in the Healthy Start Study. Fasting blood glucose, insulin, and hemoglobin A1c were assessed concurrently, and Homeostasis Model Assessment 2-Insulin Resistance (HOMA2-IR) was calculated. Gestational diabetes diagnoses and screening results were obtained from medical records for a subset of participants. We estimated associations between each EDC and outcome separately using linear and robust Poisson regression models and analyzed EDC mixture effects. RESULTS: The EDC mixture was positively associated with glucose, insulin, and HOMA2-IR, although overall associations were attenuated after adjustment for maternal BMI. Two mixture approaches identified di(2-ethylhexyl) phthalate (DEHP) metabolites as top contributors to the mixture's positive associations. In single-pollutant models, DEHP metabolites were positively associated with fasting glucose, fasting insulin, and HOMA2-IR even after adjustment for maternal BMI. For example, each interquartile range increase in log2-transformed mono(2-ethyl-5-oxohexyl) phthalate was associated with 2.4 mg/dL (95% confidence interval (CI): 1.1, 3.6) higher fasting glucose, 11.8% (95%CI: 3.6, 20.5) higher fasting insulin, and 12.3% (95%CI: 4.2, 21.1) higher HOMA2-IR. Few EDCs were associated with hemoglobin A1c or with a combined outcome of impaired glucose tolerance or gestational diabetes. DISCUSSION: Exposures to phthalates and particularly DEHP during pregnancy are associated with altered glucose-insulin regulation. Disruptions in maternal glucose metabolism during pregnancy may contribute to adverse pregnancy outcomes including gestational diabetes and fetal macrosomia, and associated long-term consequences for maternal and child health.

Maternal allergy-preventive diet index, offspring infant diet diversity, and childhood allergic diseases.

BACKGROUND: Studies of childhood diet diversity and allergic disease have not examined additional associations with an offspring allergy-linked maternal diet index during pregnancy. We studied both associations in a pre-birth cohort. METHODS: Offspring allergic disease diagnoses were obtained from electronic medical records. Maternal and infant diet were self-reported. Adjusted parametric Weibull time-to-event models assessed associations between maternal diet index, infant diet diversity and time to development of allergic rhinitis, atopic dermatitis, asthma, wheeze, IgE-mediated food allergy, and a combined outcome of any allergic disease except for wheeze. RESULTS: Infant diet diversity at 1 year was associated with the risk of the combined outcome between 1 and 4 years of age (p = .002). While both maternal diet index and infant diet diversity at 1 year were associated with the risk of the combined outcome between 1 and 4 years of age (both p < .05), infant diet diversity at 1 year did not modify the association between maternal diet index and the risk of the combined outcome between 1 and 4 years of age (p = .5). The group with the lowest risk of the combined allergy outcome had higher maternal diet index and higher infant diet diversity. CONCLUSIONS: The novel finding that both maternal diet index during pregnancy and infant diet diversity at 12 months are associated with the risk of a combined allergic disease outcome points to two targets for preventive interventions: maternal diet index scores during pregnancy and offspring diet diversity during infancy.

A better performing algorithm for identification of implausible growth data from longitudinal pediatric medical records.

Tracking trajectories of body size in children provides insight into chronic disease risk. One measure of pediatric body size is body mass index (BMI), a function of height and weight. Errors in measuring height or weight may lead to incorrect assessment of BMI. Yet childhood measures of height and weight extracted from electronic medical records often include values which seem biologically implausible in the context of a growth trajectory. Removing biologically implausible values reduces noise in the data, and thus increases the ease of modeling associations between exposures and childhood BMI trajectories, or between childhood BMI trajectories and subsequent health conditions. We developed open-source algorithms (available on github) for detecting and removing biologically implausible values in pediatric trajectories of height and weight. A Monte Carlo simulation experiment compared the sensitivity, specificity and speed of our algorithms to three published algorithms. The comparator algorithms were selected because they used trajectory information, had open-source code, and had published verification studies. Simulation inputs were derived from longitudinal epidemiological cohorts. Our algorithms had higher specificity, with similar sensitivity and speed, when compared to the three published algorithms. The results suggest that our algorithms should be adopted for cleaning longitudinal pediatric growth data.

Association of maternal fish consumption and ω-3 supplement use during pregnancy with child autism-related outcomes: results from a cohort consortium analysis.

BACKGROUND: Prenatal fish intake is a key source of omega-3 (ω-3) polyunsaturated fatty acids needed for brain development, yet intake is generally low, and studies addressing associations with autism spectrum disorder (ASD) and related traits are lacking. OBJECTIVE: This study aimed to examine associations of prenatal fish intake and ω-3 supplement use with both autism diagnosis and broader autism-related traits. METHODS: Participants were drawn from 32 cohorts in the Environmental influences on Child Health Outcomes Cohort Consortium. Children were born between 1999 and 2019 and part of ongoing follow-up with data available for analysis by August 2022. Exposures included self-reported maternal fish intake and ω-3/fish oil supplement use during pregnancy. Outcome measures included parent report of clinician-diagnosed ASD and parent-reported autism-related traits measured by the Social Responsiveness Scale (SRS)-second edition (n = 3939 and v3609 for fish intake analyses, respectively; n = 4537 and n = 3925 for supplement intake analyses, respectively). RESULTS: In adjusted regression models, relative to no fish intake, fish intake during pregnancy was associated with reduced odds of autism diagnosis (odds ratio: 0.84; 95% confidence interval [CI]: 0.77, 0.92), and a modest reduction in raw total SRS scores (ß: -1.69; 95% CI: -3.3, -0.08). Estimates were similar across categories of fish consumption from "any" or "less than once per week" to "more than twice per week." For ω-3 supplement use, relative to no use, no significant associations with autism diagnosis were identified, whereas a modest relation with SRS score was suggested (ß: 1.98; 95% CI: 0.33, 3.64). CONCLUSIONS: These results extend previous work by suggesting that prenatal fish intake, but not ω-3 supplement use, may be associated with lower likelihood of both autism diagnosis and related traits. Given the low-fish intake in the United States general population and the rising autism prevalence, these findings suggest the need for better public health messaging regarding guidelines on fish intake for pregnant individuals.

Maternal Serum Metabolomics in Mid-Pregnancy Identifies Lipid Pathways as a Key Link to Offspring Obesity in Early Childhood.

Maternal metabolism during pregnancy shapes offspring health via in utero programming. In the Healthy Start study, we identified five subgroups of pregnant women based on conventional metabolic biomarkers: Reference (n = 360); High HDL-C (n = 289); Dyslipidemic-High TG (n = 149); Dyslipidemic-High FFA (n = 180); Insulin Resistant (IR)-Hyperglycemic (n = 87). These subgroups not only captured metabolic heterogeneity among pregnant participants but were also associated with offspring obesity in early childhood, even among women without obesity or diabetes. Here, we utilize metabolomics data to enrich characterization of the metabolic subgroups and identify key compounds driving between-group differences. We analyzed fasting blood samples from 1065 pregnant women at 18 gestational weeks using untargeted metabolomics. We used weighted gene correlation network analysis (WGCNA) to derive a global network based on the Reference subgroup and characterized distinct metabolite modules representative of the different metabolomic profiles. We used the mummichog algorithm for pathway enrichment and identified key compounds that differed across the subgroups. Eight metabolite modules representing pathways such as the carnitine-acylcarnitine translocase system, fatty acid biosynthesis and activation, and glycerophospholipid metabolism were identified. A module that included 189 compounds related to DHA peroxidation, oxidative stress, and sex hormone biosynthesis was elevated in the Insulin Resistant-Hyperglycemic vs. the Reference subgroup. This module was positively correlated with total cholesterol (R:0.10; p-value < 0.0001) and free fatty acids (R:0.07; p-value < 0.05). Oxidative stress and inflammatory pathways may underlie insulin resistance during pregnancy, even below clinical diabetes thresholds. These findings highlight potential therapeutic targets and strategies for pregnancy risk stratification and reveal mechanisms underlying the developmental origins of metabolic disease risk.

Adiponectin and Glucocorticoids Modulate Risk for Preterm Birth: The Healthy Start Study.

PURPOSE: Adiponectin is a potent uterine tocolytic that decreases with gestational age, suggesting it could be a maternal metabolic quiescence factor. Maternal stress can influence preterm birth risk, and adiponectin levels may be stress-responsive. We characterized associations between adiponectin and glucocorticoids with preterm birth and modeled their predictive utility. We hypothesized maternal plasma adiponectin and cortisol are inversely related and lower adiponectin and higher cortisol associate with preterm birth. METHODS: We performed a nested case-control study using biobanked fasting maternal plasma. We included low-risk singleton pregnancies, and matched 1:3 (16 preterm, 46 term). We quantified total, high (HMW), and low molecular weight (LMW) adiponectin using ELISA. We validated an HPLC-MS/MS serum assay for use in plasma, to simultaneously measure cortisol, cortisone, and five related steroid hormones. We used linear/logistic regression to compare group means and machine learning for predictive modeling. RESULTS: The preterm group had lower mean LMW adiponectin (3.07 µg/mL vs. 3.81 µg/mL at 15w0d, P=0.045) and higher mean cortisone (34.4 ng/mL vs. 29.0 ng/mL at 15w0d, P=0.031). The preterm group had lower cortisol-to-cortisone and lower LMW adiponectin-to-cortisol ratios. We found HMW adiponectin, cortisol-to-cortisone ratio, cortisone, maternal height, age, and pre-pregnancy BMI most strongly predicted preterm birth (AUROC=0.8167). In secondary analyses, we assessed biomarker associations with maternal self-reported psychosocial stress. Lower perceived stress associated with a steeper change in cortisone in the term group. CONCLUSION: Overall, metabolic and stress biomarkers associated with preterm birth in this healthy cohort. We identify a possible mechanistic link between maternal stress and metabolism for pregnancy maintenance.

Sociodemographic Correlates of High Cardiovascular Health Across Childhood and Adolescence: A Prospective Study Among 2 Cohorts in the ECHO Consortium.

BACKGROUND: This study seeks to characterize cardiovascular health (CVH) from early childhood to late adolescence and identify sociodemographic correlates of high CVH that serve as levers for optimizing CVH across early life. METHODS AND RESULTS: Among 1530 youth aged 3 to 20 years from 2 cohorts in the ECHO (Environmental Influences on Child Health Outcomes) consortium, we first derived CVH scores on the basis of the Life's Essential 8 construct comprising 4 behavioral (nicotine use/exposure, physical activity, sleep, and diet) and 4 health factors (body mass index, blood pressure, non-high-density lipoprotein cholesterol, and fasting glucose) during early childhood (mean age, 3.5 years), middle childhood (8.0 years), early adolescence (13.3 years), and late adolescence (17.8 years). Next, we used generalized regression to estimate the probability of high (versus not high) CVH with respect to sociodemographic characteristics. Overall CVH score was stable across life stages: 81.2±7.6, 83.3±8.0, and 81.7±8.9 of 100 possible points in early childhood, middle childhood, and early adolescence, respectively. Accordingly, during these life stages, most children (63.3%-71.5%) had high CVH (80 to <100). However, CVH declined by late adolescence, with an average score of 75.5±10.2 and 39.4% high CVH. No children had optimal CVH (score=100) at any time. Correlates of high CVH include non-Hispanic White race and ethnicity, maternal college education, and annual household income >$70 000. These associations were driven by behavioral factors. CONCLUSIONS: Although most youth maintained high CVH across childhood, the decline by late adolescence indicates that cardiovascular disease prevention should occur before the early teen years. Disparities in high CVH over time with respect to sociodemographic characteristics were explained by behavioral factors, pointing toward prevention targets.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort.

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Biomarkers of Neurodegeneration and Alzheimer's Disease Neuropathology in Adolescents and Young Adults with Youth-Onset Type 1 or Type 2 Diabetes: A Proof-of-Concept Study.

Adult-onset diabetes increases one's risk of neurodegenerative disease including Alzheimer's disease (AD); however, the risk associated with youth-onset diabetes (Y-DM) remains underexplored. We quantified plasma biomarkers of neurodegeneration and AD in participants with Y-DM from the SEARCH cohort at adolescence and young adulthood (Type 1, n = 25; Type 2, n = 25; 59% female; adolescence, age = 15 y/o [2.6]; adulthood, age = 27.4 y/o [2.2]), comparing them with controls (adolescence, n = 25, age = 14.8 y/o [2.7]; adulthood, n = 21, age = 24.9 y/o [2.8]). Plasma biomarkers, including glial fibrillary acidic protein (GFAP), neurofilament light chain protein (NfL), phosphorylated tau-181 (pTau181), and amyloid beta (Aß40, Aß42), were measured via Simoa. A subset of participants (n = 7; age = 27.5 y/o [5.7]) and six controls (age = 25.1 y/o [4.5]) underwent PET scans to quantify brain amyloid and tau densities in AD sensitive brain regions. Y-DM adolescents exhibited lower plasma levels of Aß40, Aß42, and GFAP, and higher pTau181 compared to controls (p < 0.05), a pattern persisting into adulthood (p < 0.001). All biomarkers showed significant increases from adolescence to adulthood in Y-DM (p < 0.01), though no significant differences in brain amyloid or tau were noted between Y-DM and controls in adulthood. Preliminary evidence suggests that preclinical AD neuropathology is present in young people with Y-DM, indicating a potential increased risk of neurodegenerative diseases.

Intrapartum exposure to synthetic oxytocin, maternal BMI, and neurodevelopmental outcomes in children within the ECHO consortium.

BACKGROUND: Synthetic oxytocin (sOT) is frequently administered during parturition. Studies have raised concerns that fetal exposure to sOT may be associated with altered brain development and risk of neurodevelopmental disorders. In a large and diverse sample of children with data about intrapartum sOT exposure and subsequent diagnoses of two prevalent neurodevelopmental disorders, i.e., attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), we tested the following hypotheses: (1) Intrapartum sOT exposure is associated with increased odds of child ADHD or ASD; (2) associations differ across sex; (3) associations between intrapartum sOT exposure and ADHD or ASD are accentuated in offspring of mothers with pre-pregnancy obesity. METHODS: The study sample comprised 12,503 participants from 44 cohort sites included in the Environmental Influences on Child Health Outcomes (ECHO) consortium. Mixed-effects logistic regression analyses were used to estimate the association between intrapartum sOT exposure and offspring ADHD or ASD (in separate models). Maternal obesity (pre-pregnancy BMI ≥ 30 kg/m2) and child sex were evaluated for effect modification. RESULTS: Intrapartum sOT exposure was present in 48% of participants. sOT exposure was not associated with increased odds of ASD (adjusted odds ratio [aOR] 0.86; 95% confidence interval [CI], 0.71-1.03) or ADHD (aOR 0.89; 95% CI, 0.76-1.04). Associations did not differ by child sex. Among mothers with pre-pregnancy obesity, sOT exposure was associated with lower odds of offspring ADHD (aOR 0.72; 95% CI, 0.55-0.96). No association was found among mothers without obesity (aOR 0.97; 95% CI, 0.80-1.18). CONCLUSIONS: In a large, diverse sample, we found no evidence of an association between intrapartum exposure to sOT and odds of ADHD or ASD in either male or female offspring. Contrary to our hypothesis, among mothers with pre-pregnancy obesity, sOT exposure was associated with lower odds of child ADHD diagnosis.