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Abstract
High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5–18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8–46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7–37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3–16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Background: Prenatal exposure to air pollution has been associated with childhood respiratory disease and other adverse outcomes. Epigenetics is a suggested link between exposures and health outcomes. Objectives: We aimed to investigate associations between prenatal exposure to particulate matter (PM) with diameter <10 (PM10) or <2.5 mu m (PM2.5) and DNA methylation in newborns and children. Methods: We meta-analyzed associations between exposure to PM10 (n=1,949) and PM2.5 (n=1,551) at maternal home addresses during pregnancy and newborn DNA methylation assessed by Illumina Infinium HumanMethylation450K BeadChip in nine European and American studies, with replication in 688 independent newborns and look-up analyses in 2,118 older children. We used two approaches, one focusing on single cytosine-phosphate-guanine (CpG) sites and another on differentially methylated regions (DMRs). We also related PM exposures to blood mRNA expression. Results: Six CpGs were significantly associated [false discovery rate (FDR) <0.05] with prenatal PM10 and 14 with PM2.5 exposure. Two of the PM10-related CpGs mapped to FAM13A (cg00905156) and NOTCH4 (cg06849931) previously associated with lung function and asthma. Although these associations did not replicate in the smaller newborn sample, both CpGs were significant (p<0.05) in 7- to 9-y-olds. For cg06849931, however, the direction of the association was inconsistent. Concurrent PM10 exposure was associated with a significantly higher NOTCH4 expression at age 16 y. We also identified several DMRs associated with either prenatal PM10 and or PM2.5 exposure, of which two PM10-related DMRs, including H19 and MARCH11, replicated in newborns. Conclusions: Several differentially methylated CpGs and DMRs associated with prenatal PM exposure were identified in newborns, with annotation to genes previously implicated in lung-related outcomes. ; ALSPAC: The UK Medical Research Council and the Wellcome Trust (Grant ref. 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and P.Y. will serve as guarantors for the contents of this paper. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristoLac.uk/alspac/external/documents/grant-acknowledgements.pdf). This research was specifically funded by a joint grant from the UK Economic & Social and Biotechnology & Biological Sciences Research Councils (Grant ref. ES/N000498/1). ALSPAC was funded by the BBSRC (BBI025751/1 and BB/I025263/1). Air pollution exposure assessment was funded by Public Health England as part of the MRC-PHE Centre for Environment and Health, funded also by the UK Medical Research Council (Grant ref. MR/L01341X/1). This paper does not necessarily reflect the views of Public Health England or the Department of Health. BAMSE was supported by The Swedish Research Council, The Swedish Heart-Lung Foundation, Freemason Child House Foundation in Stockholm, MeDALL (Mechanisms of the Development of ALLergy) a collaborative project conducted within the European Union (grant agreement No. 261357), Centre for Allergy Research, Stockholm County Council (ALE), Swedish Foundation for Strategic Research (SSF) (RBc08-0027), the Strategic Research Programme (SFO) in Epidemiology at Karolinska Institutet, The Swedish Research Council Foams, and the Swedish Environment Protection Agency. E.M. is supported by a grant from the European Research Council under the European Union (EU) Horizon 2020 (H2020) research and innovation programme (grant agreement number 757919, TRIBAL). O.G. is supported by Forte (Swedish Research Council for Health, Working Life and Welfare) and The Swedish Society for Medical Research. CHS: This work was supported by NIEHS grants K01ES017801, R01ES022216, and P30ES007048. EARLI: This work was supported by NIH grants R01ES016443, R01ES023780, and R01ES017646 as well as by Autism Speaks (AS 5938). ENVIRONAGE: The ENVIRONAGE birth cohort is funded by the European Research Counsil (ERC-2012-StG.310898) and by funds of the Flemisch Scientific Research Council (FWO, N1516112/G.0.873.11N.10). The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (Grant agreement no. 308610). ZH and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA-Inserm, France) and Association pour la Recherche sur le Cancer (ARC, France). Generation R Study: The general design of the Generation R Study is made possible by financial support from the Erasmus Medical Center (MC), Rotterdam, the Erasmus University Rotterdam, Netherlands Organization for Health Research and Development and the Ministry of Health, Welfare and Sport. The EWAS data was funded by a grant to VWJ from Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA; project no. 050-060-810), by funds from the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC. V.W.J. also received a grant from Netherlands Organization for Health Research and Development (VIDI 016.136.361) and a Consolidator Grant from the European Research Council (ERC-2014-CoG-648916). J.F.F. has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 633595 (DynaHEALTH). This project received funding from the European Union's Horizon 2020 Research and Innovation Programme (733206, LIFECYCLE). HELIX: The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 - the HELIX project. R.G. received the grant of the Lithuanian Agency for Science Innovation and Technology (No. 45 31V-66). The Norwegian Mother and Child Cohort Study (MoBa) is supported by the Ministry of Health and Care Services and the Ministry of Education and Research, NIH/NIEHS (contract no. N01-ES-75558), NIH/NINDS (grant no. 1 UO1 NS 047537-01 and grant no. 2 UO1 NS 047537-06A1). INMA: This study was funded by grants from Institut() de Salud Carlos III (Red INMA G03/176), Generalitat de Catalunya-CIRIT 1999SGR 00241, and EU Commission (261357; 211250; 268479). Piccolipiu: The study was approved and initially funded by the Italian National Centre for Disease Prevention and Control (CCM grant 2010) and by the Italian Ministry of Health (art 12 and 12bis Dl.gs.vo 502/92). The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (Grant agreement no: 308610). Z.H. and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA-INSERM, France) and Association pour la Recherche sur le Cancer (ARC, France). Rhea: The methylation assays were funded by the European Community's Seventh Framework Programme FP7/2007-2013 project EXPOsOMICS (grant no. 308610). Z.H. is supported by the Exposomics EC FP7 grant (grant agreement no. 308610). ZH and A.G. and the Epigenetics Group at IARC are supported by grants from the Institut National du Cancer (INCa, Plan Cancer-EVA INSERM, France) and Association pour la Recherche sur le Cancer (ARC, France). PRISM: R.J.W. received funding for the PRISM cohort under HL095606 and R01 HL1143396. A.C.J. is supported by R00 ES023450. Project Viva: This Project Viva study was supported by grants from the NIH (NIH R01 HL 111108, R01 NR013945, R01 HD 034568, K24 HD069408, K23 ES022242, P01ES009825, R01AI102960, P30 ES000002) and the U.S. Environmental Protection Agency (EPA) (R832416, RD834798). This publication's contents are solely the responsibility of the grantee and do not necessarily represent the official views of the U.S. Government, the U.S. Department of Health and Human Services or the NIH, or the EPA. Further, the EPA does not endorse the purchase of any commercial products or services mentioned in the publication. MeDALL: The methylation study of MeDALL cohorts was funded by MEDALL, a collaborative project supported by the European Union under the Health Cooperation Work Programme of the 7th Framework Programme (grant agreement no. 261357). The Biobank-Based Integrative Omics Studies (BIOS) Consortium is funded by BBMRI-NL, a research 'infrastructure financed by the Dutch government (NWO 184.021.007). BAMSE: We would like to thank all the families for their participation in the BAMSE study. In addition, we would like to thank E. Haliner, S. Nilsson, and A. Lauber at the BAMSE secretary for invaluable support, as well as Mutation Analysis Facility (MAF) at Karolinska Institutet for genome-wide methylation analysis, and I. Delin for excellent technical assistance. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project b201.4110.