Abstract for the 2017 HEI Annual Conference
Air Pollution, Autism spectrum disorders, and brain imaging in CHildren among Europe – the APACHE project
Barcelona Institute for Global Health, Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health, Madrid, Spain; Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre–Sophia Children’s Hospital, Rotterdam, The Netherlands
Background. Air pollution effects on brain development are one of the most important emerging and newly recognized scientific challenges in air pollution research. Three of the main remaining open research questions are i) whether air pollution exposure during pregnancy is truly associated with autism spectrum disorders (ASD) after the contradictory published results between studies from the US and Europe, ii) which brain structures and functions are impaired due to air pollution exposure leading to the cognitive delays and behavioral problems observed in previous epidemiological studies; and iii) which are the relevant time windows of air pollution exposure for these effects.
Aim. The overall objective of the APACHE Project is i) to assess the association between prenatal air pollution exposure at different time windows and the development of ASD and ii) to assess the association between prenatal and postnatal air pollution exposure at different time windows and brain structural and functional changes in children.
Methods. The APACHE project will consist in two epidemiological project: i) a population-based case-control study for ASD in Catalunya (Spain), where I will link data from around 4,500 children with ASD identified through the Catalan mental health network with 9,000 controls from the Catalan birth registry matched on birth year, sex, and city/region of birth; and ii) a population-based birth cohort study, the Generation R (the Netherlands) with existing longitudinal data on brain structural and functional imaging in children at 6-8 years (n=1,060) and at 10 years (n=4,500). For both study regions I will compile existing land use regression models for PM2.5, PM2.5 composition (8 particle related polycyclic aromatic hydrocarbons, organic carbon, oxidative potential, elemental composition of PM2.5 (8 selected trace elements (copper (Cu), iron (Fe), and zinc (Zn) for representing non-tailpipe traffic emission, sulphur (S) for long-range transport, silicon (Si) for crustal material, potassium (K) for biomass burning, and nickel (Ni) and vanadium (V) for mixed oil burning/industry)), PM2.5 absorbance, PM10, PMcoarse, NO2, NOx, black carbon, and ultrafine particles. I will combine land use variables and satellite data remote sensing of aerosol optical depth to estimate different time windows of exposure of PM2.5 and PM10. I will estimate air pollution levels at participants’ home addresses at different time-windows during pregnancy (entire pregnancy, monthly, and weekly) and during childhood (entire childhood, yearly, and monthly) for the brain imaging study. I will develop and apply methods for measurement error in air pollution modeling predictions and I will implement multi-pollutant models. I will first assess the association between air pollution exposure at different time windows during pregnancy and the development of ASD. I will secondly assess the association between air pollution exposure at different time windows during pregnancy and childhood and structural and functional brain changes at 6-8 years old, at 10 years old, and the longitudinal changes between 6-8 and 10 years old.
Poster by Guxens, 2017 HEI Annual Conference