Metabolomic data presents challenges for epidemiological meta-analysis: a case study of childhood body mass index from the ECHO consortium.

INTRODUCTION: Meta-analyses across diverse independent studies provide improved confidence in results. However, within the context of metabolomic epidemiology, meta-analysis investigations are complicated by differences in study design, data acquisition, and other factors that may impact reproducibility. OBJECTIVE: The objective of this study was to identify maternal blood metabolites during pregnancy (> 24 gestational weeks) related to offspring body mass index (BMI) at age two years through a meta-analysis framework. METHODS: We used adjusted linear regression summary statistics from three cohorts (total N = 1012 mother-child pairs) participating in the NIH Environmental influences on Child Health Outcomes (ECHO) Program. We applied a random-effects meta-analysis framework to regression results and adjusted by false discovery rate (FDR) using the Benjamini-Hochberg procedure. RESULTS: Only 20 metabolites were detected in all three cohorts, with an additional 127 metabolites detected in two of three cohorts. Of these 147, 6 maternal metabolites were nominally associated (P < 0.05) with offspring BMI z-scores at age 2 years in a meta-analytic framework including at least two studies: arabinose (Coefmeta = 0.40 [95% CI 0.10,0.70], Pmeta = 9.7 × 10-3), guanidinoacetate (Coefmeta = - 0.28 [- 0.54, - 0.02], Pmeta = 0.033), 3-ureidopropionate (Coefmeta = 0.22 [0.017,0.41], Pmeta = 0.033), 1-methylhistidine (Coefmeta = - 0.18 [- 0.33, - 0.04], Pmeta = 0.011), serine (Coefmeta = - 0.18 [- 0.36, - 0.01], Pmeta = 0.034), and lysine (Coefmeta = - 0.16 [- 0.32, - 0.01], Pmeta = 0.044). No associations were robust to multiple testing correction. CONCLUSIONS: Despite including three cohorts with large sample sizes (N > 100), we failed to identify significant metabolite associations after FDR correction. Our investigation demonstrates difficulties in applying epidemiological meta-analysis to clinical metabolomics, emphasizes challenges to reproducibility, and highlights the need for standardized best practices in metabolomic epidemiology.

Associations between a metal mixture and infant negative affectivity: Effect modification by prenatal cortisol and infant sex.

In-utero exposures interact in complex ways that influence neurodevelopment. Animal research demonstrates that fetal sex moderates the impact of joint exposure to metals and prenatal stress measures, including cortisol, on offspring socioemotional outcomes. Further research is needed in humans. We evaluated the joint association of prenatal exposures to a metal mixture and cortisol with infant negative affectivity, considering sex differences. Analyses included 226 (29% White, Non-Hispanic) mother-infant pairs with data on exposures and negative affectivity assessed using the Infant Behavior Questionnaire-Revised in 6-month-olds. Results showed that girls whose mothers had higher cortisol had significantly higher scores of Fear and Sadness with greater exposure to the mixture. Examining higher-order interactions may better elucidate the effects of prenatal exposure to metals and cortisol on socioemotional functioning.

Prenatal manganese biomarkers and operant test battery performance in Mexican children: Effect modification by child sex.

BACKGROUND: Manganese (Mn) is essential to healthy neurodevelopment, but both Mn deficiency and over-exposure have been linked to prefrontal cortex (PFC) impairments, the brain region that regulates cognitive and neurobehavioral processes responsible for spatial memory, learning, motivation, and time perception. These processes facilitated by attention, inhibitory control, working memory, and cognitive flexibility are often sexually dimorphic and complex, driven by multiple interconnected neurologic and cognitive domains. OBJECTIVE: We investigated the role of child sex as an effect modifier of the association between prenatal Mn exposure and performance in an operant testing battery (OTB) that assessed multiple cognitive and behavioral functional domains. METHODS: Children (N = 575) aged 6-8 years completed five OTB tasks. Blood and urinary Mn measurements were collected from mothers in the 2nd and 3rd trimesters. Multiple regression models estimated the association between Mn biomarkers at each trimester with OTB performance while adjusting for socio-demographic covariates. Covariate-adjusted weighted quantile sum (WQS) regression models were used to estimate the association of a Mn multi-media biomarker (MMB) mixture with OTB performance. Interaction terms were used to estimate modification effect by child sex. RESULTS: Higher blood Mn exposure was associated with better response rates (more motivation) on the progressive ratio task and higher overall accuracy on the delayed matching-to-sample task. In the WQS models, the MMB mixture was associated with better response rates (more motivation) on the progressive ratio task. Additionally, for the linear and WQS models, we observed a modification effect by child sex in the progressive ratio and delayed matching-to-sample tasks. Higher prenatal Mn biomarker levels were associated with improved task performance for girls and reduced performance in boys. CONCLUSION: Higher prenatal blood Mn concentrations and the MMB mixture predicted improved performance on two of five operant tasks. Higher prenatal Mn concentrations regulated executive functions in children in a sexually dimorphic manner. Higher prenatal Mn exposure is associated with improved performance on spatial memory and motivation tasks in girls, suggesting that Mn's nutritional role is sexually dimorphic, and should be considered when making dietary and/or environmental intervention recommendations.

Early-Life Critical Windows of Susceptibility to Manganese Exposure and Sex-Specific Changes in Brain Connectivity in Late Adolescence.

Background: Early-life environmental exposures during critical windows (CWs) of development can impact life course health. Exposure to neuroactive metals such as manganese (Mn) during prenatal and early postnatal CWs may disrupt typical brain development, leading to persistent behavioral changes. Males and females may be differentially vulnerable to Mn, presenting distinctive CWs to Mn exposure. Methods: We used magnetic resonance imaging to investigate sex-specific associations between early-life Mn uptake and intrinsic functional connectivity in adolescence. A total of 71 participants (15-23 years old; 53% female) from the Public Health Impact of Manganese Exposure study completed a resting-state functional magnetic resonance imaging scan. We estimated dentine Mn concentrations at prenatal, postnatal, and early childhood periods using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses to investigate the moderating effect of sex on the associations between Mn and intrinsic functional connectivity adjusting for age and socioeconomic status. Results: We identified significant sex-specific associations between dentine Mn at all time points and intrinsic functional connectivity in brain regions involved in cognitive and motor function: 1) prenatal: dorsal striatum, occipital/frontal lobes, and middle frontal gyrus; 2) postnatal: right putamen and cerebellum; and 3) early childhood: putamen and occipital, frontal, and temporal lobes. Network associations differed depending on exposure timing, suggesting that different brain networks may present distinctive CWs to Mn. Conclusions: These findings suggest that the developing brain is vulnerable to Mn exposure, with effects lasting through late adolescence, and that females and males are not equally vulnerable to these effects. Future studies should investigate cognitive and motor outcomes related to these associations.

Functional changes in neural mechanisms underlying post-traumatic stress disorder in World Trade Center responders.

World Trade Center (WTC) responders exposed to traumatic and environmental stressors during rescue and recovery efforts have a high prevalence of chronic WTC-related post-traumatic stress disorder (WTC-PTSD). We investigated neural mechanisms underlying WTC-PTSD by applying eigenvector centrality (EC) metrics and data-driven methods on resting state functional magnetic resonance (fMRI). We identified how EC differences relate to WTC-exposure and behavioral symptoms. We found that connectivity differentiated significantly between WTC-PTSD and non-PTSD responders in nine brain regions, as these differences allowed an effective discrimination of PTSD and non-PTSD responders based solely on analysis of resting state data. Further, we found that WTC exposure duration (months on site) moderates the association between PTSD and EC values in two of the nine brain regions; the right anterior parahippocampal gyrus and the left amygdala (p = 0.010; p = 0.005, respectively, adjusted for multiple comparisons). Within WTC-PTSD, a dimensional measure of symptom severity was positively associated with EC values in the right anterior parahippocampal gyrus and brainstem. Functional neuroimaging can provide effective tools to identify neural correlates of diagnostic and dimensional indicators of PTSD.

Neuro-Environmental Interactions: a time sensitive matter.

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). We implemented an interpretable XGBoost-Shapley Additive Explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages: 13-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, cupper, nickel and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford Atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated ( p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Deciduous tooth biomarkers reveal atypical fetal inflammatory regulation in autism spectrum disorder.

Atypical regulation of inflammation has been proposed in the etiology of autism spectrum disorder (ASD); however, measuring the temporal profile of fetal inflammation associated with future ASD diagnosis has not been possible. Here, we present a method to generate approximately daily profiles of prenatal and early childhood inflammation as measured by developmentally archived C-reactive protein (CRP) in incremental layers of deciduous tooth dentin. In our discovery population, a group of Swedish twins, we found heightened inflammation in the third trimester in children with future ASD diagnosis relative to controls (n = 66; 14 ASD cases; critical window: -90 to -50 days before birth). In our replication study, in the US, we observed a similar increase in CRP in ASD cases during the third trimester (n = 47; 23 ASD cases; -128 to -21 days before birth). Our results indicate that the third trimester is a critical period of atypical fetal inflammatory regulation in ASD.

Tobacco smoke exposure, the lower airways microbiome and outcomes of ventilated children.

BACKGROUND: Tobacco smoke exposure increases the risk and severity of lower respiratory tract infections in children, yet the mechanisms remain unclear. We hypothesized that tobacco smoke exposure would modify the lower airway microbiome. METHODS: Secondary analysis of a multicenter cohort of 362 children between ages 31 days and 18 years mechanically ventilated for >72 h. Tracheal aspirates from 298 patients, collected within 24 h of intubation, were evaluated via 16 S ribosomal RNA sequencing. Smoke exposure was determined by creatinine corrected urine cotinine levels ≥30 µg/g. RESULTS: Patients had a median age of 16 (IQR 568) months. The most common admission diagnosis was lower respiratory tract infection (53%). Seventy-four (20%) patients were smoke exposed and exhibited decreased richness and Shannon diversity. Smoke exposed children had higher relative abundances of Serratia spp., Moraxella spp., Haemophilus spp., and Staphylococcus aureus. Differences were most notable in patients with bacterial and viral respiratory infections. There were no differences in development of acute respiratory distress syndrome, days of mechanical ventilation, ventilator free days at 28 days, length of stay, or mortality. CONCLUSION: Among critically ill children requiring prolonged mechanical ventilation, tobacco smoke exposure is associated with decreased richness and Shannon diversity and change in microbial communities. IMPACT: Tobacco smoke exposure is associated with changes in the lower airways microbiome but is not associated with clinical outcomes among critically ill pediatric patients requiring prolonged mechanical ventilation. This study is among the first to evaluate the impact of tobacco smoke exposure on the lower airway microbiome in children. This research helps elucidate the relationship between tobacco smoke exposure and the lower airway microbiome and may provide a possible mechanism by which tobacco smoke exposure increases the risk for poor outcomes in children.

Associations between Elemental Metabolic Dynamics and Default Mode Network Functional Connectivity Are Altered in Autism.

Autism is a neurodevelopmental condition associated with atypical social communication, cognitive, and sensory faculties. Recent advances in exposure biology suggest that biomarkers of elemental uptake and metabolism measured in hair samples can yield an effective signal predictive of autism diagnosis. Here, we investigated if elemental biomarkers in hair were associated with functional connectivity in regions of the default mode network (DMN) previously linked to autism. In a study sample which included twin pairs with concordant and discordant diagnoses for autism, our analysis of hair samples and neuroimaging data supported two general findings. First, independent of autism diagnosis, we found a broad pattern of association between elemental biomarkers and functional connectivity in the DMN, which primarily involved dynamics in zinc metabolism. Second, we found that associations between the DMN and elemental biomarkers, particularly involving phosphorus, calcium, manganese, and magnesium, differed significantly in autistic participants from control participants. In sum, these findings suggest that functional dynamics in elemental metabolism relate broadly to persistent patterns of functional connectivity in the DMN, and that these associations are altered in the emergence of autism.

Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents.

Introduction: Adolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal-associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross-sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents. Methods: In 193 participants (53% females, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting-state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age. Results: We observed significant negative associations between the metal mixture and GE and LE [ßGE = -0.076, 95% CI (-0.122, -0.031); ßLE= -0.051, 95% CI (-0.095, -0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE. Discussion: Our results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal.

A cross-validation based approach for estimating specific gravity in elementary-school aged children using a nonlinear model.

Environmental research often relies on urinary biomarkers which require dilution correction to accurately measure exposures. Specific gravity (SG) and creatinine (UCr) are commonly measured urinary dilution factors. Epidemiologic studies may assess only one of these measures, making it difficult to pool studies that may otherwise be able to be combined. Participants from the National Health and Nutrition Examination Survey 2007-2008 cycle were used to perform k-fold validation of a nonlinear model estimating SG from UCr. The final estimated model was applied to participants from the School Inner-City Asthma Intervention Study, who submitted urinary samples to the Children's Health Exposure Analysis Resource. Model performance was evaluated using calibration metrics to determine how closely the average estimated SG was to the measured SG. Additional models, with interaction terms for age, sex, body mass index, race/ethnicity, relative time of day when sample was collected, log transformed 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and asthma status were estimated and assessed for improvement. The association between monobenzyl phthalate (MBZP) and asthma symptom days, controlling for measured UCr, measured SG, and each estimated SG were compared to assess validity of the estimated SG. The model estimating SG from UCr alone, resulted in a beta estimate of 1.10 (95% CI: 1.01, 1.19), indicating agreement between model-predicted SG and measured SG. Inclusion of age and sex in the model improved estimation (ß = 1.06, 95% CI: 0.98, 1.15). The full model accounting for all interaction terms with UCr resulted in the best agreement (ß = 1.01, 95% CI: 0.93,1.09). Associations between MBZP and asthma symptoms days, controlling for each estimated SG, were within the range of effect estimates when controlling for measured SG and measured UCr (Rate ratios = 1.28-1.34). Our nonlinear modeling provides opportunities to estimate SG in studies that measure UCr or vice versa, enabling data pooling despite differences in urine dilution factors.

Neuro-environmental interactions: a time sensitive matter.

Introduction: The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). Methods: We implemented an interpretable XGBoost-shapley additive explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages, 13-25 years) enrolled in the public health impact of metals exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, copper, nickel, and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood, and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Results: Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated (p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Discussion: Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Air Pollution and Maximum Temperature Are Associated with Neurodevelopmental Regressive Events in Autism Spectrum Disorder.

Neurodevelopmental regression (NDR) is an enigmatic event associated with autism spectrum disorder (ASD) during which a child loses previously acquired skills and develops ASD symptoms. In some, a trigger which precedes the NDR event, such as a fever, can be identified, but in many cases no trigger is obvious. We hypothesize that air pollution (PM2.5) may trigger NDR, especially in those children without an identified trigger. Average daily PM2.5, ozone, precipitation and maximum temperature (Tmax) were derived from Environmental Protection Agency models and National Oceanic and Atmospheric Administration monitors based on zip-code information from 83 ASD participants during the six-weeks following the onset month of an NDR event and a reference period defined as one year before and one year after the event. Seasonally adjusted logistic regression (LR) and linear mixed models (LMM) compared cases (with a history of NDR) and matched controls (without a history of NDR). LR models found that the risk of NDR was related to higher PM2.5 during 3 to 6 weeks of the NDR event period, particularly in those without a trigger. Overall, both models converged on NDR being related to a higher PM2.5 and lower Tmax both during the NDR event period as well as the reference period, particularly in those without a known trigger. This temporal pattern suggests that environmental triggers, particularly PM2.5, could be related to NDR, especially in those without an identifiable trigger. Further studies to determine the underlying biological mechanism of this observation could help better understand NDR and provide opportunities to prevent NDR.

Elemental Dynamics in Hair Accurately Predict Future Autism Spectrum Disorder Diagnosis: An International Multi-Center Study.

Autism spectrum disorder (ASD) is a neurodevelopmental condition diagnosed in approximately 2% of children. Reliance on the emergence of clinically observable behavioral patterns only delays the mean age of diagnosis to approximately 4 years. However, neural pathways critical to language and social functions develop during infancy, and current diagnostic protocols miss the age when therapy would be most effective. We developed non-invasive ASD biomarkers using mass spectrometry analyses of elemental metabolism in single hair strands, coupled with machine learning. We undertook a national prospective study in Japan, where hair samples were collected at 1 month and clinical diagnosis was undertaken at 4 years. Next, we analyzed a national sample of Swedish twins and, in our third study, participants from a specialist ASD center in the US. In a blinded analysis, a predictive algorithm detected ASD risk as early as 1 month with 96.4% sensitivity, 75.4% specificity, and 81.4% accuracy (n = 486; 175 cases). These findings emphasize that the dynamics in elemental metabolism are systemically dysregulated in autism, and these signatures can be detected and leveraged in hair samples to predict the emergence of ASD as early as 1 month of age.

Application of growth modeling to assess the impact of hospital-based phthalate exposure on preterm infant growth parameters during the neonatal intensive care unit hospitalization.

In this study, we use advanced growth modeling techniques and the rich biospecimen and data repositories of the NICU Hospital Exposures and Long-Term Health (NICU-HEALTH) study to assess the impact of NICU-based phthalate exposure on extrauterine growth trajectories between birth and NICU discharge. Repeated holdout weighed quantile sum (WQS) regression was used to assess the effect of phthalate mixtures on the latency to first growth spurt and on the rate of first growth spurt. Further, we assessed sex as an effect modifier of the relationship between a phthalate mixture and both outcomes. Nine phthalate metabolites, mono-ethyl phthalate (MEP), mono-benzyl phthalate (MBzP), mono-n-butyl phthalate (MBP), mono-isobutyl phthalate (MiBP), mono-(3-carboxypropyl) phthalate (MCPP), mono-2-ethylhexyl phthalate (MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) were measured in weekly urine specimens from 101 NICU-HEALTH participants between birth and the first growth spurt. Phthalate levels varied by species but not by infant sex, and decreased over the course of the NICU hospitalization as presented in detail in Stroustrup et al., 2018. There was evidence of nonlinearity when assessing the effect of phthalates on latency to first growth spurt. Above a threshold level, a higher phthalate mixture with dominant contributors MCPP, MBzP, and MEP predicted a shorter latency to the first inflection point, or an earlier growth spurt. A higher phthalate mixture with dominant contributors MECPP, MEHHP, and MEOHP was associated with an increased rate of growth. Results of both models were clearly different for boys and girls, consistent with other studies showing the sexually dimorphic impact of early life phthalate exposure. These results suggest that growth curve modeling facilitates evaluation of discrete periods of rapid growth during the NICU hospitalization and exposure to specific phthalates during the NICU hospitalization may both alter the timing of the first growth spurt and result in more rapid growth in a sexually dimorphic manner.

Prenatal trace elements mixture is associated with learning deficits on a behavioral acquisition task among young children.

Children are exposed to many trace elements throughout their development. Given their ubiquity and potential to have effects on children's neurodevelopment, these exposures are a public health concern. This study sought to identify trace element mixture-associated deficits in learning behavior using operant testing in a prospective cohort. We included 322 participants aged 6-7 years recruited in Mexico City with complete data on prenatal trace elements measurements (third trimester blood lead and manganese levels, and & urine cadmium and arsenic levels), demographic covariates, and the Incremental Repeated Acquisition (IRA), an associative learning task. Weighted quantile sum (WQS) regression models were used to estimate the joint association of the mixture of all four trace elements and IRA performance. Performance was adversely impacted by the mixture, with different elements relating to different aspects of task performance suggesting that prenatal exposure to trace element mixtures yields a broad dysregulation of learning behavior.

Altered Periodic Dynamics in the Default Mode Network in Autism and Attention-Deficit/Hyperactivity Disorder.

BACKGROUND: Altered resting-state functional connectivity in the default mode network (DMN) is characteristic of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Standard analytical pipelines for resting-state functional connectivity focus on linear correlations in activation time courses between neural networks or regions of interest. These features may be insensitive to temporally lagged or nonlinear relationships. METHODS: In a twin cohort study comprising 292 children, including 52 with a diagnosis of ASD and 70 with a diagnosis of ADHD, we applied nonlinear analytical methods to characterize periodic dynamics in the DMN. Using recurrence quantification analysis and related methods, we measured the prevalence, duration, and complexity of periodic processes within and between DMN regions of interest. We constructed generalized estimating equations to compare these features between neurotypical children and children with ASD and/or ADHD while controlling for familial relationships, and we leveraged machine learning algorithms to construct models predictive of ASD or ADHD diagnosis. RESULTS: In within-pair analyses of twins with discordant ASD diagnoses, we found that DMN signal dynamics were significantly different in dizygotic twins but not in monozygotic twins. Considering our full sample, we found that these patterns allowed a robust predictive classification of both ASD (81.0% accuracy; area under the curve = 0.85) and ADHD (82% accuracy; area under the curve = 0.87) cases. CONCLUSIONS: These findings indicate that synchronized periodicity among regions comprising the DMN relates both to neurotypical function and to ASD and/or ADHD, and they suggest generally that a dynamical analysis of network interconnectivity may be a useful methodology for future neuroimaging studies.

Sexually dimorphic associations between prenatal blood lead exposure and performance on a behavioral testing battery in children.

BACKGROUND: Associations between lead (Pb) and neurodevelopment have been studied widely in the context of global measures of cognitive function, such as IQ. Operant test batteries consist of behavioral tasks that can be used to target discrete cognitive and behavioral mechanisms, which contribute to global cognitive faculties. OBJECTIVES: The goals of this study were to identify Pb-associated deficits in cognitive development and determine the underlying mechanisms involved, utilizing an operant test battery. We evaluated effect modification by child sex. METHODS: This study utilized data from a prospective cohort in Mexico City. We included 549 participants aged 6-to-7 years with complete data on prenatal blood Pb measurements, Operant Test Battery (OTB) tasks, and demographic covariates. General linear models were used to examine the association of Pb levels at each prenatal timepoint and OTB performance. Effect modification by child sex was evaluated using 2-way interaction terms. RESULTS: In three of the operant tasks, we observed that higher late-pregnancy blood Pb concentrations were associated with greater response latencies. In the temporal processing task, we observed that higher late-pregnancy Pb exposure was associated with worse overall task performance. Further, in two operant tasks, the effects of Pb were dependent on the sex of the child, such that the effects of Pb were more pronounced in females in the condition position responding task, but stronger in males in the temporal processing task. CONCLUSIONS: Our results suggest that prenatal Pb concentrations yield broad dysregulation of executive functions, which can be attributed to dysregulation of temporal processing. In addition, we observed sex differences in two operant tasks suggesting that some Pb effects on neurocognitive function may be sexually dimorphic.

Human Microbiome Mixture Analysis Using Weighted Quantile Sum Regression.

Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQSRSRH), a mixture method successfully applied to 'omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQSRSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQSRSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQSRSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQSRSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQSRSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQSRSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings.

Prenatal metal mixture concentrations and reward motivation in children.

Reward motivation is a complex umbrella term encompassing the cognitions, emotions, and behaviors involved in the activation, execution, and persistence of goal-directed behavior. Altered reward motivation in children is characteristic of many neurodevelopmental and psychiatric disorders. Previously difficult to operationalize, the Progressive Ratio (PR) task has been widely used to assess reward motivation in animal and human studies, including children. Because the neural circuitry supporting reward motivation starts developing during pregnancy, and is sensitive to disruption by environmental toxicants, including metals, the goal of this study was to examine the association between prenatal concentrations of a mixture of neurotoxic metals and reward motivation in children. We measured reward motivation by administering a PR test to 373 children ages 6-8 years enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) Study in Mexico City. Children were asked to press a response lever for a token reward; one press on the response lever was required to earn the first token and each subsequent token required an additional 10 lever presses. Maternal blood concentrations of lead, manganese, zinc, arsenic, cadmium, and selenium were measured using inductively-coupled plasma mass spectrometry during the 2nd and 3rd trimesters of pregnancy. We performed generalized Weighted Quantile Sum (gWQS) regression analyses to examine associations between the prenatal metal mixture and reward motivation; adjusting for child sex, birthweight and age; and maternal IQ, education, and socioeconomic status. The prenatal metal mixture was significantly associated with higher motivation as indicated by more lever presses (ß = 0.02, p < 0.001) and a shorter time between receiving the reinforcer and the first press (ß = 0.23, p = 0.01), and between subsequent presses (ß = 0.07, p = 0.005). Contributions of different metals to this association differed by trimester and child sex. These findings suggest that children with increased exposure to metal during the 2nd and 3rd trimesters of gestation demonstrate increased reward motivation, which may reflect a tendency to perseverate or hypersensitivity to positive reinforcement.