Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

Background: The occurrence of asthma is weakly explained by known genetic variants. Epigenetic marks, DNA methylation (DNA-M) in particular, are considered to add to the explanation of asthma. However, no etiological model has yet been developed that integrates genetic variants and DNA-M. To explore a new model, we focused on one asthma candidate gene, the IL-4 receptor (IL4R). We hypothesized that genetic variants ofIL4Rin interaction with DNA-M at cytosine-phosphate-guanine (CpG) sites jointly alter the risk of asthma during adolescence. Blood samples were collected at age 18 years from 245 female cohort participants randomly selected for methylation analysis from a birth cohort (n = 1,456, Isle of Wight, UK). Genome-wide DNA-M was assessed using the Illumina Infinium HumanMethylation450 BeadChip.Results: Thirteen single nucleotide polymorphisms (SNPs) and twelve CpG sites ofIL4Rgene were analyzed. Based on linkage disequilibrium and association with asthma, eight SNPs and one CpG site were selected for further analyses. Of the twelve CpG sites in theIL4Rgene, only methylation levels of cg09791102 showed an association with asthma at age 18 years (Wilcoxon test:P= 0.01). Log-linear models were used to estimate risk ratios (RRs) for asthma adjusting for uncorrelated SNPs within theIL4Rgene and covariates. Testing for interaction between the eight SNPs and the methylation levels of cg09791102 on the risk for asthma at age 18 years, we identified the statistically significant interaction term of SNP rs3024685 × methylation levels of cg09791102 (P= 0.002; after adjusting for false discovery rate). A total of 84 participants had methylation levels ≤0.88, 112 participants between 0.89 and 0.90, and 35 between 0.91 and 0.92. For the SNP rs3024685 (‘CC’ vs. ‘TT’) at methylation levels of ≤0.85, 0.86, 0.90, 0.91, and 0.92, the RRs were 0.01, 0.04, 4.65, 14.76, 14.90, respectively (interaction effect,P= 0.0003).Conclusions: Adjusting for multiple testing, our results suggest that DNA-M modulates the risk of asthma related to genetic variants in theIL4Rgene. The strong interaction of one SNP and DNA-M is encouraging and provides a novel model of how a joint effect of genetic variants and DNA-M can explain occurrence of asthma.

Whole blood is frequently utilized in genome-wide association studies of DNA methylation patterns in relation to environmental exposures or clinical outcomes. These associations can be confounded by cellular heterogeneity. Algorithms have been developed to measure or adjust for this heterogeneity, and some have been compared in the literature. However, with new methods available, it is unknown whether the findings will be consistent, if not which method(s) perform better. Methods: We compared eight cell-type correction methods including the method in the minfi R package, the method by Houseman et al., the Removing unwanted variation (RUV) approach, the methods in FaST-LMM-EWASher, ReFACTor, RefFreeEWAS, and RefFreeCellMix R programs, along with one approach utilizing surrogate variables (SVAs). We first evaluated the association of DNA methylation at each CpG across the whole genome with prenatal arsenic exposure levels and with cancer status, adjusted for estimated cell-type information obtained from different methods. We then compared CpGs showing statistical significance from different approaches. For the methods implemented in minfi and proposed by Houseman et al., we utilized homogeneous data with composition of some blood cells available and compared them with the estimated cell compositions. Finally, for methods not explicitly estimating cell compositions, we evaluated their performance using simulated DNA methylation data with a set of latent variables representing “cell types”. Results: Results from the SVA-based method overall showed the highest agreement with all other methods except for FaST-LMM-EWASher. Using homogeneous data, minfi provided better estimations on cell types compared to the originally proposed method by Houseman et al. Further simulation studies on methods free of reference data revealed that SVA provided good sensitivities and specificities, RefFreeCellMix in general produced high sensitivities but specificities tended to be low when confounding is present, and FaST-LMM-EWASher gave the lowest sensitivity but highest specificity. Results from real data and simulations indicated that SVA is recommended when the focus is on the identification of informative CpGs. When appropriate reference data are available, the method implemented in the minfi package is recommended. However, if no such reference data are available or if the focus is not on estimating cell proportions, the SVA method is suggested.

Background: Adolescence is a period characterized by major biological development, which may be associated with changes in DNA methylation (DNA-M). However, it is unknown to what extent DNA-M varies from pre- to post-adolescence, whether the pattern of changes is different between females and males, and how adolescence-related factors are associated with changes in DNA-M.Methods: Genome-scale DNA-M at ages 10 and 18 years in whole blood of 325 subjects (n= 140 females) in the Isle of Wight (IOW) birth cohort was analyzed using Illumina Infinium arrays (450K and EPIC). Linear mixed models were used to examine DNA-M changes between pre- and post-adolescence and whether the changes were gender-specific. Adolescence-related factors and environmental exposure factors were assessed on their association with DNA-M changes. Replication of findings was attempted in the comparable Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.Results: In the IOW cohort, after controlling for technical variation and cell compositions at both pre- and post-adolescence, 15,532 cytosine–phosphate–guanine (CpG) sites (of 400,825 CpGs, 3.88%) showed statistically significant DNA-M changes from pre-adolescence to post-adolescence invariant to gender (false discovery rate (FDR) = 0.05). Of these 15,532 CpGs, 10,212 CpGs (66%) were replicated in the ALSPAC cohort. Pathway analysis using Ingenuity Pathway Analysis (IPA) identified significant biological pathways related to growth and development of the reproductive system, emphasizing the importance of this period of transition on epigenetic state of genes. In addition, in IOW, we identified 1179 CpGs with gender-specific DNA-M changes. In the IOW cohort, body mass index (BMI) at age 10 years, age of growth spurt, nonsteroidal drugs use, and current smoking status showed statistically significant associations with DNA-M changes at 15 CpGs on 14 genes such as theAHRRgene. For BMI at age 10 years, the association was gender-specific. Findings on current smoking status were replicated in the ALSPAC cohort.Conclusion: Adolescent transition is associated with changes in DNA-M at more than 15K CpGs. Identified pathways emphasize the importance of this period of transition on epigenetic state of genes relevant to cell growth and immune system development.

In utero arsenic exposure may alter fetal developmental programming by altering DNA methylation, which may result in a higher risk of disease in later life. We evaluated the association between in utero arsenic exposure and DNA methylation (DNAm) in cord blood and its influence in later life. Genome-wide DNA methylation in cord blood from 64 subjects in the Taiwanese maternal infant and birth cohort was analyzed. Robust regressions were applied to assess the association of DNA methylation with in utero arsenic exposure. Multiple testing was adjusted by controlling false discovery rate (FDR) of 0.05. The DAVID bioinformatics tool was implemented for functional annotation analyses on the detected CpGs. The identified CpGs were further tested in an independent cohort. For the CpGs replicated in the independent cohort, linear mixed models were applied to assess the association of DNA methylation with low-density lipoprotein (LDL) at different ages (2, 5, 8, 11 and 14 years). In total, 579 out of 385,183 CpGs were identified after adjusting for multiple testing (FDR = 0.05), of which ~60% were positively associated with arsenic exposure. Functional annotation analysis on these CpGs detected 17 KEGG pathways (FDR = 0.05) including pathways for cardiovascular diseases (CVD) and diabetes mellitus. In the independent cohort, about 46% (252 out of 553 CpGs) of the identified CpGs showed associations consistent with those in the study cohort. In total, 11 CpGs replicated in the independent cohort were in the pathways related to CVD and diabetes mellitus. Via longitudinal analyses, we found at 5 out of the 11 CpGs methylation was associated with LDL over time and interactions between DNA methylation and time were observed at 4 of the 5 CpGs, cg25189764 (coeff = 0.157, p-value = 0.047), cg04986899 (coeff. For interaction [coeff.int] = 0.030, p-value = 0.024), cg04903360 (coeff.int = 0.026, p-value = 0.032), cg08198265 (coeff.int = −0.063, p-value = 0.0021), cg10473311 (coeff.int = −0.021, p-value = 0.027). In utero arsenic exposure was associated with cord blood DNA methylation at various CpGs. The identified CpGs may help determine pathological epigenetic mechanisms linked to in utero arsenic exposure. Five CpGs (cg25189764, cg04986899, cg04903360, cg08198265 and cg10473311) may serve as epigenetic markers for changes in LDL later in life.

Pre-bronchodilator lung function including forced vital capacity (FVC), forced expiratory flow in 1 second (FEV1), their ratio (FEV1/FVC), and forced expiratory flow 25–75% (FEF25–75) measured at age 10, 18, and 26 years in the Isle of Wight birth cohort was analyzed for developmental patterns (trajectories). Early life risk factors before the age of 10 years were assessed for the trajectories. Members of the birth cohort (1989/90) were followed at age 1, 2, 4, 10, 18, and 26 years. Allergic sensitization and questionnaire data were collected. Spirometry tests were performed and evaluated according to the American Thoracic Society (ATS) criteria at 10, 18, and 26 years. To identify developmental trajectories for FVC, FEV1, FEV1/FVC, and FEF25–75 from 10 to 26 years, a finite mixture model was applied to the longitudinal lung function data, separately for males and females. Associations of early life factors with the respective lung function trajectories were assessed using log-linear and logistic regression analyses. Both high and low lung function trajectories were observed in men and women. FVC continued to grow beyond 18 years in men and women, whereas FEV1 peaked at age 18 years in female trajectories and in one male trajectory. For the FEV1/FVC ratios and FEF25–75 most trajectories appeared highest at age 18 and declined thereafter. However, the low FEV1/FVC trajectory in both sexes showed an early decline at 10 years. Lower birth weight was linked with lower lung function trajectories in males and females. Eczema in the first year of life was a risk factor for later lung function deficits in females, whereas the occurrence of asthma at 4 years of age was a risk factor for later lung function deficits in males. A positive skin prick test at age four was a risk for the low FEV1 trajectory in females and for the low FEV1/FVC trajectory in males. Men and women showed distinctive lung function trajectories and associated risk factors. Lower lung function trajectories can be explained by not achieving maximally attainable function at age 18 years and by a function decline from 18 to 26 years.