Abstract for the 2019 HEI Annual Conference
Air Pollution, Autism spectrum disorders, and brain imaging in CHildren among Europe – the APACHE project
Mònica Guxens1-4, Małgorzata J Lubczyńska1-4, Laura Perez1-3, Albert Ambrós1-3, Matteo Renzi5, Matteo Scortichini5, Maciej Strak6, Xavier Basagaña1-3, Ryan Muetzel4, Antònia Valentín1-3, Itai Kloog7, Gerard Hoek6, Joel Schwartz8, Francesco Forastiere5, Tonya White4, Jordi Sunyer1-3, Henning Tiemeier4,8, Bert Brunekreef6,9, Massimo Stafoggia5, Hanan El Marroun4
1ISGlobal, Barcelona, Spain; 2Pompeu Fabra University, Barcelona, Spain; 3Spanish Consortium for Research on Epidemiology and Public Health, Madrid, Spain; 4Erasmus University Medical Centre–Sophia Children’s Hospital, Rotterdam, the Netherlands; 5Lazio Regional Health Service, Rome, Italy; 6Institute for Risk Assessment Sciences, Utrecht, The Netherlands; 7Ben-Gurion University of the Negev, Beer Sheva, Israel; 8Harvard T.H. Chan School of Public Health, Boston, MA, USA; 9Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands
Background. We aim to investigate 1) the association between prenatal air pollution exposure at different time windows and the development of autism spectrum disorders (ASD) and 2) the association between prenatal and postnatal air pollution exposure at different time windows and brain structural and functional changes in children.
Methods. We use data from two epidemiological studies: (1) a population-based case-cohort study of ASD in Catalunya (Spain), where children diagnosed with ASD identified through the Catalan mental health network are linked to the Catalan birth registry and (2) the Generation R population-based birth cohort study (the Netherlands), with existing longitudinal data on brain imaging in children at 6-10 years and at 8-12 years. For both study regions we compile existing land use regression models for a large number of pollutants. For the study of Catalunya, we also combine land use variables and satellite data remote sensing of aerosol optical depth to develop new PM2.5 and PM10 models. We estimate air pollution levels at participants’ home addresses at different time-windows during pregnancy (entire pregnancy, monthly, and weekly) and childhood (entire childhood, yearly, and monthly). We apply methods for measurement error and multi-pollutant models. We assess the association between air pollution exposure at different time windows during pregnancy and the development of ASD. We also assess the association between air pollution exposure at different time windows during pregnancy and childhood and structural and functional brain changes at 6-10 years old and at 8-12 years old.
Results and conclusions. We are setting up the case-cohort study on ASD and developing new air pollution models for Catalunya. There are no results from that study yet. Regarding the imaging study, we found that prenatal PM2.5 exposure was associated with a thinner cortex in several brain regions in 6-10 years old children and these alterations partially mediated the association between prenatal PM2.5 exposure and impaired child inhibitory control. Regarding white matter microstructure, in single pollutant analysis, higher prenatal and postnatal exposure to several air pollutants was associated with a decrease in fractional anisotropy and an increase in mean diffusivity in 9-12 years old children, indicating a developmental delay in white matter miscrostructure. In the multi-pollutant analyses and mutually adjusting between prenatal and postnatal exposures, higher prenatal levels of silicon content in PM2.5 and higher postnatal levels of zinc content in PM2.5 were associated with an increase in mean diffusivity (0.07 [95%CI 0.01; 0.13] and 0.03 [95%CI 0.01; 0.06] for each 10 ng/m3 increase of airborne silicon and zinc, respectively). Measurement error correction methods were applied.
Poster by Guxens et al., 2019 Annual Conference