This study aimed to develop an environmental risk score (ERS) of multiple pollutants (MP) causing kidney damage (KD) in Korean residents near abandoned metal mines or smelters and evaluate the association between ERS and KD by a history of occupational chemical exposure (OCE). Exposure to MP, consisting of nine metals, four polycyclic aromatic hydrocarbons, and four volatile organic compounds, was measured as urinary metabolites. The study participants were recruited from the Forensic Research via Omics Markers (FROM) study (n = 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group.

BACKGROUND: First-episode psychotic disorders comprise a heterogeneous phenotype with a complex etiology involving numerous common small-effect genetic variations and a wide range of environmental exposures. We examined whether a family of schizophrenia spectrum disorder (FH-Sz) interacts with an environmental risk score (ERS-Sz) regarding the outcome of patients with non-affective first episode psychosis (NAFEP).
METHODS: We included 288 patients with NAFEP who were evaluated after discharge from an intensive 2-year program. We evaluated three outcome measures: symptomatic remission, psychosocial functioning, and personal recovery. We analyzed the main and joint associations of a FH-Sz and the ERS-Sz on the outcomes by using the relative excess risk due to interaction (RERI) approach.
RESULTS: A FH-Sz showed a significant association with poor symptomatic remission and psychosocial functioning outcomes, although there was no significant interaction between a FH-Sz and the ERS-Sz on these outcomes. The ERS-Sz did not show a significant association with poor symptomatic remission and psychosocial functioning outcomes, even though the magnitude of the interaction between ERS-Sz and FH-Sz with the later outcome was moderate (RERI = 6.89, 95% confidence interval -16.03 to 29.81). There was no association between a FH-Sz and the ERS-Sz and personal recovery.
CONCLUSIONS: Our results provide further empirical support regarding the contribution of FH-Sz to poor symptomatic remission and poor psychosocial functioning outcomes in patients with NAFEP.

UNASSIGNED: The pathogenesis of amyotrophic lateral sclerosis (ALS) involves both genetic and environmental factors. This study investigates associations between metal measures in plasma and urine, ALS risk and survival, and exposure sources.
UNASSIGNED: Participants with and without ALS from Michigan provided plasma and urine samples for metal measurement via inductively coupled plasma mass spectrometry. Odds and hazard ratios for each metal were computed using risk and survival models. Environmental risk scores (ERS) were created to evaluate the association between exposure mixtures and ALS risk and survival and exposure source. ALS (ALS-PGS) and metal (metal-PGS) polygenic risk scores were constructed from an independent genome-wide association study and relevant literature-selected SNPs.
UNASSIGNED: Plasma and urine samples from 454 ALS and 294 control participants were analyzed. Elevated levels of individual metals, including copper, selenium, and zinc, significantly associated with ALS risk and survival. ERS representing metal mixtures strongly associated with ALS risk (plasma, OR=2.95, CI=2.38-3.62, p<0.001; urine, OR=3.10, CI=2.43-3.97, p<0.001) and poorer ALS survival (plasma, HR=1.42, CI=1.24-1.63, p<0.001; urine, HR=1.52, CI=1.31-1.76, p<0.001). Addition of the ALS-PGS or metal-PGS did not alter the significance of metals with ALS risk and survival. Occupations with high potential of metal exposure associated with elevated ERS. Additionally, occupational and non-occupational metal exposures associated with measured plasma and urine metals.
UNASSIGNED: Metals in plasma and urine associated with increased ALS risk and reduced survival, independent of genetic risk, and correlated with occupational and non-occupational metal exposures. These data underscore the significance of metal exposure in ALS risk and progression.

No single environmental factor is a necessary or sufficient cause of mental disorder; multifactorial and transdiagnostic approaches are needed to understand the impact of the environment on the development of mental disorders across the life course.
Using linked multi-agency administrative data for 71 932 children from the New South Wales Child Developmental Study, using logistic regression, we examined associations between 16 environmental risk factors in early life (prenatal period to <6 years of age) and later diagnoses of mental disorder recorded in health service data (from age 6 to 13 years), both individually and summed as an environmental risk score (ERS).
The ERS was associated with all types of mental disorder diagnoses in a dose-response fashion, such that 2.8% of children with no exposure to any of the environmental factors (ERS = 0), compared to 18.3% of children with an ERS of 8 or more indicating exposure to 8 or more environmental factors (ERS ⩾ 8), had been diagnosed with any type of mental disorder up to age 13-14 years. Thirteen of the 16 environmental factors measured (including prenatal factors, neighbourhood characteristics and more proximal experiences of trauma or neglect) were positively associated with at least one category of mental disorder.
Exposure to cumulative environmental risk factors in early life is associated with an increased likelihood of presenting to health services in childhood for any kind of mental disorder. In many instances, these factors are preventable or capable of mitigation by appropriate public policy settings.

The cumulative exposure to metals affects cardiac conduction, and the effect of polymetallic exposure on heart rate in children is unknown. To evaluate the relationship between cumulative exposure to metal mixtures and heart rate among Chinese preschoolers, the determination of urinary 24 metals was processed by high-resolution inductively coupled plasma-mass spectrometry. Heart rate was recorded when measuring blood pressure after resting 5 min or longer. As a method to compute the Environmental risk score (ERS) according to heart rate under heavy metal mixtures, adaptive elastic net (AENET) with 299 predictors which were formed by the combination of main effects, squared terms, and pairwise interactions of heavy metals with a total number of 23, 23, 253 respectively. To further assess the associations between ERS and heart rate, regression analyses were performed with complex survey designs. The construction of ERS under heart rate-related metal mixtures was returned by AENET in according to 11 main effects (tin, arsenic, zinc, iron, titanium, vanadium, nickel, manganese, cobalt, copper and chromium) and 2 squared terms (tungsten and rubidium). A high correlation was monitored between the alteration of ERS in the study population and heart rate (β = 1.030, 95% CI: 0.730 - 1.330 in 1239; β = 1.085, 95% CI: 0.777 - 1.393 in 1061). Significant associations of ERS with higher heart rates were also pointed out (Ps < 0.05). Our study elucidates the association of the cumulative exposure of heavy metals as mixtures and heart rate among Chinese preschoolers. Further research is obliged to corroborate these findings in longitudinal studies.

Determining effective means of preventing Multiple Sclerosis (MS) relies on testing preventive strategies in trial populations. However, because of the low incidence of MS, demonstrating that a preventive measure has benefit requires either very large trial populations or an enriched population with a higher disease incidence. Risk scores which incorporate genetic and environmental data could be used, in principle, to identify high-risk individuals for enrolment in preventive trials. Here we discuss the concepts of developing predictive scores for identifying individuals at high risk of MS. We discuss the empirical efforts to do so using real cohorts, and some of the challenges-both theoretical and practical-limiting this work. We argue that such scores could offer a means of risk stratification for preventive trial design, but are unlikely to ever constitute a clinically-helpful approach to predicting MS for an individual.

Gene-environment (GxE) interactions have been related to psychosis spectrum disorders, involving multiple common genetic variants in multiple genes with very small effect sizes, and several environmental factors that constitute a dense network of exposures named the exposome. Here, we aimed to analyze GxE in a cohort of 310 first-episode psychotic (FEP) and 236 healthy controls, by using aggregate scores estimated in large populations such as the polygenic risk score for schizophrenia and (PRS-SCZ) and the Maudsley environmental risk score (ERS). In contrast to previous findings, in our study, the PRS-SCZ did not discriminate cases from controls, but the ERS score explained a similar percentage of the variance as in other studies using similar approaches. Our study supports a positive additive interaction, indicating synergy between genetic susceptibility to schizophrenia (PRS-SCZ dichotomized according to the highest quartile distribution of the control population) and the exposome (ERS > 75% of the controls). This additive interaction showed genetic and environmental dose dependence. Our study shows that the use of aggregate scores derived from large and powered studies instead of statistics derived from specific sample characteristics is a powerful tool for the study of the effects of GxE on the risk of psychotic spectrum disorders. In conclusion, by using a genetic risk score and an ERS we have provided further evidence for the role of GxE in psychosis.

Preterm birth is a significant public health concern and exposure to phthalates has been shown to be associated with an increased odds of preterm birth. Even modest reductions in gestational age at delivery could entail morbid consequences for the neonate and analyzing data with this additional information may be useful. In the present analysis, we consider gestational age at delivery as our outcome of interest and examine associations with multiple phthalates.
Women were recruited early in pregnancy as part of a prospective, longitudinal birth cohort at the Brigham and Women\'s Hospital in Boston, Massachusetts. Urine samples were collected at up to four time points during gestation for urinary phthalate metabolite measurement, and birth outcomes were recorded at delivery. From this population, we selected all 130 cases of preterm birth (< 37 weeks of gestation) as well as 352 random controls. We conducted analysis with both geometric average of the exposure concentrations across the first three visits as well as using repeated measures of the exposure. Two different time to event models were used to examine associations between nine urinary phthalate metabolite concentrations and time to delivery. Two different approaches to constructing a summative phthalate risk score were also considered.
The single-pollutant analysis using a Cox proportional hazards model showed the strongest association with a hazard ratio (HR) of 1.21 (95% confidence interval (CI): 1.09, 1.33) per interquartile range (IQR) change in average log-transformed mono-2-ethyl-5-carboxypentyl phthalate (MECPP) concentration. Using the accelerated failure time model, we observed a 1.19% (95% CI: 0.26, 2.11%) decrease in gestational age in association with an IQR change in average log-transformed MECPP. We next examined associations with an environmental risk score (ERS). The fourth quartile of ERS was significantly associated with a HR of 1.44 (95% CI: 1.19, 1.75) and a reduction of 2.55% (95% CI: 0.76, 4.30%) in time to delivery (in days) compared to the first quartile.
On average, pregnant women with higher urinary metabolite concentrations of individual phthalates have shorter time to delivery. The strength of the observed associations are amplified with the risk scores when compared to individual pollutants.