Ambient ozone and fine particulate matter exposures and autism spectrum disorder in metropolitan Cincinnati, Ohio.

BACKGROUND: Epidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods. OBJECTIVES: To examine associations between ASD and ambient fine particulate matter (PM2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study. METHODS: ASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows. RESULTS: We detected elevated aORs for PM2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17). DISCUSSION: We saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.

Use of Shotgun Metagenome Sequencing To Detect Fecal Colonization with Multidrug-Resistant Bacteria in Children.

Prevention of multidrug-resistant (MDR) bacterial infections relies on accurate detection of these organisms. We investigated shotgun metagenome sequencing for the detection of methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and MDR Enterobacteriaceae Fecal metagenomes were analyzed from high-risk inpatients and compared to those of low-risk outpatients and controls with minimal risk for a MDR bacterial infection. Principal-component analysis clustered patient samples into distinct cohorts, confirming that the microbiome composition was significantly different between cohorts (P = 0.006). Microbial diversity and relative anaerobe abundance were preserved in outpatients compared to those in controls. Relative anaerobe abundance was significantly reduced in inpatients compared to that in outpatients (P = 0.006). Although the potential for MDR bacteria was increased in inpatients and outpatients compared to that in controls (P < 0.001), there was no difference between inpatients and outpatients. However, 9 (53%) inpatients had colonization with a MDR bacterium that was not identified by culture. Unlike culture, shotgun sequencing quantitatively characterizes the burdens of multiple MDR bacteria relative to all of the microbiota within the intestinal community. We propose consideration of key microbiome features, such as diversity and relative anaerobe abundance, in addition to the detection of MDR bacteria by shotgun metagenome sequencing as a novel method that might better identify patients who are at increased risk of a MDR infection.

Maternal metabolic risk factors for autism spectrum disorder-An analysis of electronic medical records and linked birth data.

Past studies have suggested that conditions experienced by women during pregnancy (e.g. obesity and gestational diabetes mellitus (GDM)) may be associated with having a child with autism spectrum disorder (ASD). Our objective was to compare mothers who had a child diagnosed with ASD to mothers of children with a non-ASD developmental disorder (DD) or without any reported DD (controls). To accomplish the objective we collected medical record data from patients who resided in the Cincinnati Children's Hospital Medical Center's (CCHMC) primary catchment area and linked those data to data from birth certificates (to identify risk factors). Two comparison groups were analyzed; one with DD; and the other, controls without a reported ASD or DD. Descriptive statistics and regression analyses evaluated differences. Differences were greater comparing mothers of ASD to controls than comparing ASD to DD. Maternal obesity and GDM were associated with a statistically significant approximately 1.5-fold increased odds of having a child with an ASD. For mothers with both GDM and obesity, the association was twofold for having a child with ASD compared with controls. Maternal obesity and GDM might be associated with an increased risk of ASD in the offspring; however, no difference in risk of ASD according to BMI and GDM was seen when comparing to DD. Autism Res 2016, 9: 829-837,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Integrating public data sets for analysis of maternal airborne environmental exposures and stillbirth.

Efforts to study relationships between maternal airborne pollutant exposures and poor pregnancy outcomes have been frustrated by data limitations. Our objective was to report the proportion of Ohio women in 2006-2010 experiencing stillbirth whose pregnancy exposure to six criteria airborne pollutants could be approximated by applying a geospatial approach to vital records and Environmental Protection Agency air monitoring data. In addition, we characterized clinical and socio-demographic differences among women who lived within 10 km of monitoring stations compared to women who did not live within proximity of monitoring stations. For women who experienced stillbirth, 10.8% listed a residence within 10 km of each type of monitoring station. Maternal race, education, and marital status were significantly different (p<0.0001) comparing those within proximity to monitoring stations to those outside of monitoring range. No significant differences were identified in maternal age, ethnicity, smoking status, hypertension, or diabetes between groups.