Illustration of sample size.

<p>LRTIs- lower respiratory tract infections. ^aSome versions of questionnaires did not ask about frequency/number of LRTIs. </p

Additional file 2: of Effect of maternal gestational weight gain on offspring DNA methylation: a follow-up to the ALSPAC cohort study

A table in Microsoft Excel format containing information regarding the regression model based on 0-18 week GWG

Additional file 3: of Effect of maternal gestational weight gain on offspring DNA methylation: a follow-up to the ALSPAC cohort study

Details regarding quality control of the methylation dataset

Maternal age-related DNA methylation changes in newborns (NFCS and MoBa) and adults (Sister Study) per 20 years.

<p>Methylation at each CpG (β-value) was tested for association with maternal age and the β coefficients from the regression analysis were converted into the percent difference in methylation per 20 years (maternal age). The covariates included in Model1 differed slightly across the NFCS, MoBa, and the Sister Study analyses (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156361#pone.0156361.s013" target="_blank">S1 Text</a>).</p

Epigenome-wide association results of maternal age in NFCS newborns.

<p>Volcano plot showing the relationship between the effect magnitude (coefficient) and strength of association (p-value) for Model1. The red horizontal line denotes the strict threshold for epigenome-wide significance based on a conservative Bonferroni correction for 465525 tests (p < 1.07x10^-7). The four CpGs that are circled in purple are near the second exon of the gene, <i>KLHL35</i>.</p

Boxplots showing the distribution of % CpG methylation after normalization and batch correction using COMBAT by IUS exposure for A) <i>C11orf52</i> (cg05697249), B) <i>XPNPEP1</i> (cg09352789), C) <i>FRMD4A</i> (cg25464840), and D) <i>PPEF2</i> (cg14724265) in 526 Asthma BRIDGE samples.

<p>Boxplots showing the distribution of % CpG methylation after normalization and batch correction using COMBAT by IUS exposure for A) <i>C11orf52</i> (cg05697249), B) <i>XPNPEP1</i> (cg09352789), C) <i>FRMD4A</i> (cg25464840), and D) <i>PPEF2</i> (cg14724265) in 526 Asthma BRIDGE samples.</p

CpG Loci significantly associated with IUS exposure in CAMP asthmatics (N = 527).

<p>CpG Loci significantly associated with IUS exposure in CAMP asthmatics (N = 527).</p

Replication results from beta regression and linear regression models in Asthma BRIDGE and MoBa for the 19 CpG loci identified in CAMP.

<p>Replication results from beta regression and linear regression models in Asthma BRIDGE and MoBa for the 19 CpG loci identified in CAMP.</p

Development of Land Use Regression Models for Elemental, Organic Carbon, PAH, and Hopanes/Steranes in 10 ESCAPE/TRANSPHORM European Study Areas

Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NO_<i>x</i>), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM_2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16–40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (<i>R</i>²) was found for EC – 84%. The median <i>R</i>² was 51% for OC, 67% for benzo­[a]­pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM_2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies

Additional file 5 of Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

Additional file 5. Table S4: “Direction of differential methylation of CpGs in DMRs of the at-birth and childhood analyses (preliminary analysis”)