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Epigenetic mechanisms integrate both genetic variability and environmental exposures. However, comprehensive epigenome-wide analysis has not been performed across major childhood allergic phenotypes. We examined the association of epigenome-wide DNA methylation in mid-childhood peripheral blood (Illumina HumanMethyl450K) with mid-childhood atopic sensitization, environmental/inhalant and food allergen sensitization in 739 children in two birth cohorts (Project Viva-Boston, and the Generation R Study-Rotterdam). We performed covariate-adjusted epigenome-wide association meta-analysis and employed pathway and regional analyses of results. Seven-hundred and five methylation sites (505 genes) were significantly cross-sectionally associated with mid-childhood atopic sensitization, 1411 (905 genes) for environmental and 45 (36 genes) for food allergen sensitization (FDR<0.05). We observed differential methylation across multiple genes for all three phenotypes, including genes implicated previously in innate immunity (DICER1), eosinophilic esophagitis and sinusitis (SIGLEC8), the atopic march (AP5B1) and asthma (EPX, IL4, IL5RA, PRG2, SIGLEC8, CLU). In addition, most of the associated methylation marks for all three phenotypes occur in putative transcription factor binding motifs. Pathway analysis identified multiple methylation sites associated with atopic sensitization and environmental allergen sensitization located in/near genes involved in asthma, mTOR signaling, and inositol phosphate metabolism. We identified multiple differentially methylated regions associated with atopic sensitization (8 regions) and environmental allergen sensitization (26 regions). A number of nominally significant methylation sites in the cord blood analysis were epigenome-wide significant in the mid-childhood analysis, and we observed significant methylation - time interactions among a subset of sites examined. Our findings provide insights into epigenetic regulatory pathways as markers of childhood allergic sensitization.

Numerous studies have investigated individual biomarkers in relation to risk of type 2 diabetes. However, few have considered the interconnectivity of these biomarkers in the etiology of diabetes as well as the potential changes in the biomarker correlation network during diabetes development. We conducted a secondary analysis of 27 plasma biomarkers representing glucose metabolism, inflammation, adipokines, endothelial dysfunction, IGF axis, and iron store plus age and BMI at blood collection from an existing case-control study nested in the Nurses' Health Study (NHS), including 1,303 incident diabetes case subjects and 1,627 healthy women. A correlation network was constructed based on pairwise Spearman correlations of the above factors that were statistically different between case and noncase subjects using permutation tests ( P < 0.0005). We further evaluated the network structure separately among diabetes case subjects diagnosed <5, 5-10, and >10 years after blood collection versus noncase subjects. Although pairwise biomarker correlations tended to have similar directions comparing diabetes case subjects to noncase subjects, most correlations were stronger in noncase than in case subjects, with the largest differences observed for the insulin/HbA 1c and leptin/adiponectin correlations. Leptin and soluble leptin receptor were two hubs of the network, with large numbers of different correlations with other biomarkers in case versus noncase subjects. When examining the correlation network by timing of diabetes onset, there were more perturbations in the network for case subjects diagnosed >10 years versus <5 years after blood collection, with consistent differential correlations of insulin and HbA 1c C-peptide was the most highly connected node in the early-stage network, whereas leptin was the hub for mid- or late-stage networks. Our results suggest that perturbations of the diabetes-related biomarker network may occur decades prior to clinical recognition. In addition to the persistent dysregulation between insulin and HbA 1c , our results highlight the central role of the leptin system in diabetes development., (© 2018 by the American Diabetes Association.)

Numerous studies have investigated individual biomarkers in relation to risk of type 2 diabetes. However, few have considered the interconnectivity of these biomarkers in the etiology of diabetes as well as the potential changes in the biomarker correlation network during diabetes development. We conducted a secondary analysis of 27 plasma biomarkers representing glucose metabolism, inflammation, adipokines, endothelial dysfunction, IGF axis, and iron store plus age and BMI at blood collection from an existing case-control study nested in the Nurses' Health Study (NHS), including 1,303 incident diabetes case subjects and 1,627 healthy women. A correlation network was constructed based on pairwise Spearman correlations of the above factors that were statistically different between case and noncase subjects using permutation tests (P < 0.0005). We further evaluated the network structure separately among diabetes case subjects diagnosed <5, 5-10, and >10 years after blood collection versus noncase subjects. Although pairwise biomarker correlations tended to have similar directions comparing diabetes case subjects to noncase subjects, most correlations were stronger in noncase than in case subjects, with the largest differences observed for the insulin/HbA1c and leptin/adiponectin correlations. Leptin and soluble leptin receptor were two hubs of the network, with large numbers of different correlations with other biomarkers in case versus noncase subjects. When examining the correlation network by timing of diabetes onset, there were more perturbations in the network for case subjects diagnosed >10 years versus <5 years after blood collection, with consistent differential correlations of insulin and HbA1c C-peptide was the most highly connected node in the early-stage network, whereas leptin was the hub for mid- or late-stage networks. Our results suggest that perturbations of the diabetes-related biomarker network may occur decades prior to clinical recognition. In addition to the persistent dysregulation between insulin and HbA1c, our results highlight the central role of the leptin system in diabetes development. [ABSTRACT FROM AUTHOR]