Improved Glycemia with Hybrid Closed-Loop Versus Continuous Subcutaneous Insulin Infusion Therapy: Results from a Randomized Controlled Trial.

Objective: To evaluate safety and effectiveness of MiniMed™ 670G hybrid closed loop (HCL) in comparison with continuous subcutaneous insulin infusion (CSII) therapy for 6 months in persons with type 1 diabetes (T1D). Methods: Adults (aged 18-80 years), adolescents, and children (aged 2-17 years) with T1D who were using CSII therapy were enrolled and randomized (1:1) to 6 months of HCL intervention (n = 151, mean age of 39.9 ± 19.8 years) or CSII without continuous glucose monitoring (n = 151, 35.7 ± 18.4 years). Primary effectiveness endpoints included change in A1C for Group 1 (baseline A1C >8.0%), from baseline to the end of study, and difference in the end of study percentage of time spent below 70 mg/dL (%TBR <70 mg/dL) for Group 2 (baseline A1C ≤8.0%), to show superiority of HCL intervention versus control. Secondary effectiveness endpoints were change in A1C and %TBR <70 mg/dL for Group 2 and Group 1, respectively, to show noninferiority of HCL intervention versus control. Primary safety endpoints were rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Change in A1C and difference in %TBR <70 mg/dL for the overall group were significantly improved, in favor of HCL intervention. In addition, a significant mean (95% confidence interval) change in A1C was observed for both Group 1 (-0.8% [-1.1% to -0.4%], P < 0.0001) and Group 2 (-0.3% [-0.5% to -0.1%], P < 0.0001), in favor of HCL intervention. The same was observed for difference in %TBR <70 mg/dL for Group 1 (-2.2% [-3.6% to -0.9%]) and Group 2 (-4.9% [-6.3% to -3.6%]) (P < 0.0001 for both). There was one DKA event during run-in and six severe hypoglycemic events: two during run-in and four during study (HCL: n = 0 and CSII: n = 4 [6.08 per 100 patient-years]). Conclusions: This RCT demonstrates that the MiniMed 670G HCL safely and significantly improved A1C and %TBR <70 mg/dL compared with CSII control in persons with T1D, irrespective of baseline A1C level.

Thyroid Cancer and Pesticide Use in a Central California Agricultural Area: A Case Control Study.

OBJECTIVE: To examine environmental factors that influence risk of thyroid cancer. METHODS: We performed a case-control study utilizing thyroid cancer cases from the California Cancer Registry (1999-2012) and controls sampled in a population-based manner. Study participants were included if they were diagnosed with thyroid cancer, lived in the study area at their time of diagnosis, and were ≥35 years of age. Controls were recruited from the same area and eligible to participate if they were ≥35 years of age and had been living in California for at least 5 years prior to the interview. We examined residential exposure to 29 agricultural use pesticides, known to cause DNA damage in vitro or are known endocrine disruptors. We employed a validated geographic information system-based system to generate exposure estimates for each participant. RESULTS: Our sample included 2067 cases and 1003 controls. In single pollutant models and within a 20-year exposure period, 10 out of 29 selected pesticides were associated with thyroid cancer, including several of the most applied pesticides in the United States such as paraquat dichloride [odds ratio (OR): 1.46 (95% CI: 1.23, 1.73)], glyphosate [OR: 1.33 (95% CI: 1.12, 1.58)], and oxyfluorfen [OR: 1.21 (95% CI: 1.02, 1.43)]. Risk of thyroid cancer increased proportionately to the total number of pesticides subjects were exposed to 20 years before diagnosis or interview. In all models, paraquat dichloride was associated with thyroid cancer. CONCLUSIONS: Our study provides first evidence in support of the hypothesis that residential pesticide exposure from agricultural applications is associated with an increased risk of thyroid cancer.

Metabolomics analysis of maternal serum exposed to high air pollution during pregnancy and risk of autism spectrum disorder in offspring.

BACKGROUND: Previously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring. OBJECTIVES: To identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD. METHODS: We obtained stored mid-pregnancy serum from 214 mothers who lived in California's Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman's average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 µm) during the first trimester using the California Line Source Dispersion Model, version 4 (CALINE4). By utilizing liquid chromatography-high resolution mass spectrometry, we identified the metabolic profiles of maternal serum for 116 mothers with offspring who later developed ASD and 98 control mothers. Partial least squares discriminant analysis (PLS-DA) was employed to select metabolic features associated with air pollution exposure or autism risk in offspring. We also conducted extensive pathway enrichment analysis to elucidate potential ASD-related changes in the metabolome of pregnant women. RESULTS: We extracted 4022 and 4945 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for potential confounders, we identified 167 and 222 discriminative features (HILIC and C18, respectively). Pathway enrichment analysis to discriminate metabolic features associated with ASD risk indicated various metabolic pathway perturbations linked to the tricarboxylic acid (TCA) cycle and mitochondrial function, including carnitine shuttle, amino acid metabolism, bile acid metabolism, and vitamin A metabolism. CONCLUSION: Using high resolution metabolomics, we identified several metabolic pathways disturbed in mothers with ASD offspring among women experiencing high exposure to traffic-related air pollution during pregnancy that were associated with mitochondrial dysfunction. These findings provide us with a better understanding of metabolic disturbances involved in the development of ASD under adverse environmental conditions.

Ambient Exposure to Agricultural Pesticides during Pregnancy and Risk of Cerebral Palsy: A Population-Based Study in California.

Cerebral palsy (CP) is the most common neuro-motor disability in young children. Disruptions of maternal hormone function during pregnancy have been linked to CP risk. We investigated whether prenatal exposure to pesticide compounds with endocrine-disrupting action affect CP risk. We conducted a case-control study of 3905 CP cases and 39,377 controls born between 1998 and 2010 in California to mothers who lived in proximity (within 2 km) to any agricultural pesticide application recorded in the California Pesticide Use Reporting (PUR) system. We focused on 23 pesticides considered endocrine disruptors that are frequently used, and we found that exposure to any of the 23 pesticides in the first trimester was associated with elevated CP risks in female offspring (OR = 1.19; 95% CI: 1.05-1.35) but not males (OR = 0.99; 95% CI: 0.89-1.09) compared to the unexposed offspring. Positive associations were estimated for 15 pesticides suspected to affect the estrogen and 7 pesticides suspected to affect the thyroid hormone system. Our study suggests that first trimester exposure to pesticides that are suspected endocrine disruptors are associated with CP risk in female offspring. Pesticide exposures in early pregnancy may have sex-specific influences on the neuro-motor development of the fetus by interfering with endocrine systems.

Untargeted Metabolomics Screen of Mid-pregnancy Maternal Serum and Autism in Offspring.

Discovering pathophysiologic networks in a blood-based approach may help to generate valuable tools for early treatment or preventive measures in autism. To date targeted or untargeted metabolomics approaches to identify metabolic features and pathways affecting fetal neurodevelopment have rarely been applied to pregnancy samples, that is, an early period potentially relevant for the development of autism spectrum disorders (ASD). We conducted a population-based study relying on autism diagnoses retrieved from California Department of Developmental Services record. After linking cases to and sampling controls from birth certificates, we retrieved stored maternal mid-pregnancy serum samples collected as part of the California Prenatal Screening Program from the California Biobank for children born 2004 to 2010 in the central valley of California. We retrieved serum for 52 mothers whose children developed autism and 62 population controls originally selected from all eligible children matched by birth year and child's sex. Also, we required that these mothers were relatively low or unexposed to air pollution and select pesticides during early pregnancy. We identified differences in metabolite levels in several metabolic pathways, including glycosphingolipid biosynthesis and metabolism, N-glycan and pyrimidine metabolism, bile acid pathways and, importantly, C21-steroid hormone biosynthesis and metabolism. Disturbances in these pathways have been shown to be relevant for neurodevelopment in rare genetic syndromes or implicated in previous studies of autism. This study provides new insight into maternal mid-pregnancy metabolic features possibly related to the development of autism and an incentive to explore whether these pathways and metabolites are useful for early diagnosis, treatment, or prevention. LAY SUMMARY: This study found that in mid-pregnancy the blood of mothers who give birth to a child that develops autism has some characteristic features that are different from those of blood samples taken from control mothers. These features are related to biologic mechanisms that can affect fetal brain development. In the future, these insights may help identify biomarkers for early autism diagnosis and treatment or preventive measures. Autism Res 2020, 13: 1258-1269. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Maternal serum metabolome and traffic-related air pollution exposure in pregnancy.

BACKGROUND: Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and neurodevelopmental disorders. By utilizing high-resolution metabolomics (HRM), we investigated perturbations of the maternal serum metabolome in response to traffic-related air pollution to identify biological mechanisms. METHODS: We retrieved stored mid-pregnancy serum samples from 160 mothers who lived in the Central Valley of California known for high air particulate levels. We estimated prenatal traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 µm) during first-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) to select metabolic features associated with air pollution exposure. Pathway analyses were employed to identify biologic pathways related to air pollution exposure. As potential confounders we included maternal age, maternal race/ethnicity, and maternal education. RESULTS: In total we extracted 4038 and 4957 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for confounding factors, PLS-DA (Variable Importance in Projection (VIP) ≥2) yielded 181 and 251 metabolic features (HILIC and C18, respectively) that discriminated between the high (n = 98) and low exposed (n = 62). Pathway enrichment analysis for discriminatory features associated with air pollution indicated that in maternal serum oxidative stress and inflammation related pathways were altered, including linoleate, leukotriene, and prostaglandin pathways. CONCLUSION: The metabolomic features and pathways we found to be associated with air pollution exposure suggest that maternal exposure during pregnancy induces oxidative stress and inflammation pathways previously implicated in pregnancy complications and adverse outcomes.

Residential mobility in early childhood and the impact on misclassification in pesticide exposures.

Studies of environmental exposures and childhood cancers that rely on records often only use maternal address at birth or address at cancer diagnosis to assess exposures in early childhood, possibly leading to exposure misclassification and questionable validity due to residential mobility during early childhood. Our objective was to assess patterns and identify factors that may predict residential mobility in early childhood, and examine the impact of mobility on early childhood exposure assessment for agriculturally applied pesticides and childhood cancers in California. We obtained the addresses at diagnosis of all childhood cancer cases born in 1998-2011 and diagnosed at 0-5 years of age (n = 6478) from the California Cancer Registry (CCR), and their birth addresses from linked birth certificates. Controls were randomly selected from California birth records and frequency matched (20:1) to all cases by year of birth. We obtained residential histories from a public-record database LexisNexis for both case (n = 3877 with age at diagnosis 1-5 years) and control (n = 99,262) families. Logistic regression analyses were conducted to assess the socio-demographic factors in relation to residential mobility in early childhood. We employed a Geographic Information System (GIS)-based system to estimate children's first year of life exposures to agriculturally applied pesticides based on birth vs diagnosis address or residential histories based upon Lexis-Nexis Public Records and assessed agreement between exposure measures using Spearman correlations and kappa statistics. Over 20% of case and control children moved in their first year of life, and 55% of children with cancer moved between birth and diagnosis. Older age at diagnosis, younger maternal age, lower maternal education, not having a Hispanic ethnic background, use of public health insurance, and non-metropolitan residence at birth were predictors of higher residential mobility. There was moderate to strong correlation (Spearman correlation = 0.76-0.83) and good agreement (kappa = 0.75-0.81) between the first year of life exposure estimates for agricultural pesticides applied within 2 km of a residence relying on an address at birth or at diagnosis or LexisNexis addresses; this did not differ by outcome status, but agreement decreased with decreasing buffer size, and increasing distance moved or age at diagnosis. These findings suggest that residential addresses collected at one point in time may represent residential history in early childhood to a reasonable extent; nevertheless, they exposure misclassification in the first year of life remains an issue. Also, the highest proportion of women not captured by LexisNexis were Hispanic women born in Mexico and those living in the lowest SES neighborhoods, i.e. possibly those with the higher environmental exposures, as well as younger women and those with less than high school education. Though LexisNexis only captures a sub-population, its data may be useful for augmenting address information and assessing the extent of exposure misclassification when estimating environmental exposures in large record linkage studies. Future research should investigate how to correct for exposure misclassification introduced by residential mobility that is not being captured by records.

Prenatal and infant exposure to ambient pesticides and autism spectrum disorder in children: population based case-control study.

OBJECTIVE: To examine associations between early developmental exposure to ambient pesticides and autism spectrum disorder. DESIGN: Population based case-control study. SETTING: California's main agricultural region, Central Valley, using 1998-2010 birth data from the Office of Vital Statistics. POPULATION: 2961 individuals with a diagnosis of autism spectrum disorder based on the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, revised (up to 31 December 2013), including 445 with intellectual disability comorbidity, were identified through records maintained at the California Department of Developmental Services and linked to their birth records. Controls derived from birth records were matched to cases 10:1 by sex and birth year. EXPOSURE: Data from California state mandated Pesticide Use Reporting were integrated into a geographic information system tool to estimate prenatal and infant exposures to pesticides (measured as pounds of pesticides applied per acre/month within 2000 m from the maternal residence). 11 high use pesticides were selected for examination a priori according to previous evidence of neurodevelopmental toxicity in vivo or in vitro (exposure defined as ever v never for each pesticide during specific developmental periods). MAIN OUTCOME MEASURE: Odds ratios and 95% confidence intervals using multivariable logistic regression were used to assess associations between pesticide exposure and autism spectrum disorder (with or without intellectual disabilities) in offspring, adjusting for confounders. RESULTS: Risk of autism spectrum disorder was associated with prenatal exposure to glyphosate (odds ratio 1.16, 95% confidence interval 1.06 to 1.27), chlorpyrifos (1.13, 1.05 to 1.23), diazinon (1.11, 1.01 to 1.21), malathion (1.11, 1.01 to 1.22), avermectin (1.12, 1.04 to 1.22), and permethrin (1.10, 1.01 to 1.20). For autism spectrum disorder with intellectual disability, estimated odds ratios were higher (by about 30%) for prenatal exposure to glyphosate (1.33, 1.05 to 1.69), chlorpyrifos (1.27, 1.04 to 1.56), diazinon (1.41, 1.15 to 1.73), permethrin (1.46, 1.20 to 1.78), methyl bromide (1.33, 1.07 to 1.64), and myclobutanil (1.32, 1.09 to 1.60); exposure in the first year of life increased the odds for the disorder with comorbid intellectual disability by up to 50% for some pesticide substances. CONCLUSION: Findings suggest that an offspring's risk of autism spectrum disorder increases following prenatal exposure to ambient pesticides within 2000 m of their mother's residence during pregnancy, compared with offspring of women from the same agricultural region without such exposure. Infant exposure could further increase risks for autism spectrum disorder with comorbid intellectual disability.

Prenatal Exposure to Ambient Pesticides and Preterm Birth and Term Low Birthweight in Agricultural Regions of California.

Findings from studies of prenatal exposure to pesticides and adverse birth outcomes have been equivocal so far. We examined prenatal exposure to agricultural pesticides in relation to preterm birth and term low birthweight, respectively, in children born between 1998 and 2010, randomly selected from California birth records. We estimated residential exposure to agriculturally applied pesticides within 2 km of residential addresses at birth by pregnancy trimester for 17 individual pesticides and three chemical classes (organophosphates, pyrethroids, and carbamates). Among maternal addresses located within 2 km of any agricultural pesticide application, we identified 24,693 preterm and 220,297 term births, and 4412 term low birthweight and 194,732 term normal birthweight infants. First or second trimester exposure to individual pesticides (e.g., glyphosates, paraquat, imidacloprid) or exposure to 2 or more pesticides in the three chemical classes were associated with a small increase (3⁻7%) in risk for preterm birth; associations were stronger for female offspring. We did not find associations between term low birthweight and exposure to pesticides other than myclobutanil (OR: 1.11; 95% CI: 1.04⁻1.20) and possibly the pyrethroids class. Our improved exposure assessment revealed that first and second trimester exposure to pesticides is associated with preterm delivery but is rarely linked with term low birthweight.

Cognitive decline, mortality, and organophosphorus exposure in aging Mexican Americans.

BACKGROUND: Cognitive impairment is a major health concern among older Mexican Americans, associated with significant morbidity and mortality, and may be influenced by environmental exposures. OBJECTIVES: To investigate whether agricultural based ambient organophosphorus (OP) exposure influences 1) the rate of cognitive decline and mortality and 2) whether these associations are mediated through metabolic or inflammatory biomarkers. METHODS: In a subset of older Mexican Americans from the Sacramento Area Latino Study on Aging (n = 430), who completed modified mini-mental state exams (3MSE) up to 7 times (1998-2007), we examined the relationship between estimated ambient OP exposures and cognitive decline (linear repeated measures model) and time to dementia or being cognitively impaired but not demented (CIND) and time to mortality (cox proportional hazards model). We then explored metabolic and inflammatory biomarkers as potential mediators of these relationships (additive hazards mediation). OP exposures at residential addresses were estimated with a geographic information system (GIS) based exposure assessment tool. RESULTS: Participants with high OP exposure in the five years prior to baseline experienced faster cognitive decline (ß = 0.038, p = 0.02) and higher mortality over follow-up (HR = 1.91, 95% CI = 1.12, 3.26). The direct effect of OP exposure was estimated at 241 (95% CI = 27-455) additional deaths per 100,000 person-years, and the proportion mediated through the metabolic hormone adiponectin was estimated to be 4% 1.5-19.2). No other biomarkers were associated with OP exposure. CONCLUSIONS: Our study provides support for the involvement of OP pesticides in cognitive decline and mortality among older Mexican Americans, possibly through biologic pathways involving adiponectin.

Exposure to ambient dichloromethane in pregnancy and infancy from industrial sources and childhood cancers in California.

BACKGROUND: The incidence of childhood cancers has been increasing and environmental exposure to air toxics has been suggested as a possible risk factor. This study aims to explore ambient exposure to dichloromethane (methylene chloride). METHODS: We frequency matched by birth year approximately 20 cancer-free controls identified from birth records to all childhood cancers ages 0-5 in the California Cancer Registry diagnosed from 1988 to 2012; i.e. 13,636 cases and a total of 270,673 controls. Information on industrial releases of dichloromethane within 3km of birth addresses was retrieved from mandatory industry reports to the EPA's Toxics Release Inventory (TRI). We derived exposure to dichloromethane within close vicinity of birth residences using several modeling techniques including unconditional logistic regression models with multiple buffer distances, inverse distance weighting, and quadratic decay models. RESULTS: We observed elevated risks for germ cell tumors [Odds Ratio (OR): 1.52, 95% Confidence Interval (CI) 1.11, 2.08], particularly teratomas (OR: 2.08, 95% CI 1.38-3.13), and possible increased risk for acute myeloid leukemias (AML) (OR: 1.64, 95% CI 1.15-2.32 in the quadratic decay model). Risk estimates were similar in magnitude whether releases occurred in pregnancy or the child's first year of life. CONCLUSION: Our findings suggest that exposure to industrial dichloromethane releases may be a risk factor for childhood germ cell tumors, teratomas, and possibly AML.