VOCs, Air pollution and ASD Risk

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VOCs, Air pollution and ASD Risk

Postby kulkulkan » Tue Oct 07, 2014 5:27 pm

Yet another risk factor study showing correlation to higher pollution/particulate matter - East vs West coast.

Epidemiology. 2014 Oct 3. [Epub ahead of print]
Particulate Matter Exposure, Prenatal and Postnatal Windows of Susceptibility, and Autism Spectrum Disorders.
Kalkbrenner AE1, Windham GC, Serre ML, Akita Y, Wang X, Hoffman K, Thayer BP, Daniels JL.
Author information
Recent studies suggest that exposure to traffic-related air pollutants, including particulate matter (PM), is associated with autism spectrum disorder (autism).

Children with autism were identified by records-based surveillance (n = 645 born in North Carolina in 1994, 1996, 1998, or 2000, and n = 334 born in the San Francisco Bay Area in California in 1996). They were compared with randomly sampled children born in the same counties and years identified from birth records (n = 12,434 in North Carolina and n = 2,232 in California). Exposure to PM less than 10 μm (PM10) at the birth address was assigned to each child by a geostatistical interpolation method using daily concentrations from air pollution regulatory monitors. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for a 10 μg/m increase in PM10 within 3-month periods from preconception through the child's first birthday, adjusting for year, state, maternal education and age, race/ethnicity, and neighborhood-level urbanization and median household income, and including a nonparametric term for week of birth to account for seasonal trends.

Temporal patterns in PM10 were pronounced, leading to an inverse correlation between the first- and third-trimester concentrations (r = -0.7). Adjusted ORs were, for the first trimester, 0.86 (95% CI = 0.74-0.99), second trimester, 0.97 (0.83-1.15), and third trimester, 1.36 (1.13-1.63); and, after simultaneously including first- and third-trimester concentrations to account for the inverse correlation, were: first trimester, 1.01 (0.81-1.27) and third trimester, 1.38 (1.03-1.84).

Our study adds to previous work in California showing a relation between traffic-related air pollution and autism, and adds similar findings in an eastern US state, with results consistent with increased susceptibility in the third-trimester.

PMID: 25286049 [PubMed - as supplied by publisher]

Also more VOCs in urine of ASD vs control.

http://link.springer.com/article/10.100 ... 014-7855-z

Analytical and Bioanalytical Chemistry
July 2014, Volume 406, Issue 19, pp 4649-4662
Date: 15 May 2014
Use of solid-phase microextraction coupled to gas chromatography–mass spectrometry for determination of urinary volatile organic compounds in autistic children compared with healthy controls
Rosaria Cozzolino, Laura De Magistris, Paola Saggese, Matteo Stocchero, Antonella Martignetti, Michele Di Stasio, Antonio Malorni, Rosa Marotta, Floriana Boscaino, Livia Malorni

Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders which have a severe life-long effect on behavior and social functioning, and which are associated with metabolic abnormalities. Their diagnosis is on the basis of behavioral and developmental signs usually detected before three years of age, and there is no reliable biological marker. The objective of this study was to establish the volatile urinary metabolomic profiles of 24 autistic children and 21 healthy children (control group) to investigate volatile organic compounds (VOCs) as potential biomarkers for ASDs. Solid-phase microextraction (SPME) using DVB/CAR/PDMS sorbent coupled with gas chromatography–mass spectrometry was used to obtain the metabolomic information patterns. Urine samples were analyzed under both acid and alkaline pH, to profile a range of urinary components with different physicochemical properties. Multivariate statistics techniques were applied to bioanalytical data to visualize clusters of cases and to detect the VOCs able to differentiate autistic patients from healthy children. In particular, orthogonal projections to latent structures discriminant analysis (OPLS-DA) achieved very good separation between autistic and control groups under both acidic and alkaline pH, identifying discriminating metabolites. Among these, 3-methyl-cyclopentanone, 3-methyl-butanal, 2-methyl-butanal, and hexane under acid conditions, and 2-methyl-pyrazine, 2,3-dimethyl-pyrazine, and isoxazolo under alkaline pH had statistically higher levels in urine samples from autistic children than from the control group. Further investigation with a higher number of patients should be performed to outline the metabolic origins of these variables, define a possible association with ASDs, and verify the usefulness of these variables for early-stage diagnosis.

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