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Background: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. Objective: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. Methods: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. Results: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. Conclusion: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.
Abstract BACKGROUND Nutritional metabolomics is rapidly evolving to integrate nutrition with complex metabolomics data to discover new biomarkers of nutritional exposure and status. CONTENT The purpose of this review is to provide a broad overview of the measurement techniques, study designs, and statistical approaches used in nutrition metabolomics, as well as to describe the current knowledge from epidemiologic studies identifying metabolite profiles associated with the intake of individual nutrients, foods, and dietary patterns. SUMMARY A wide range of technologies, databases, and computational tools are available to integrate nutritional metabolomics with dietary and phenotypic information. Biomarkers identified with the use of high-throughput metabolomics techniques include amino acids, acylcarnitines, carbohydrates, bile acids, purine and pyrimidine metabolites, and lipid classes. The most extensively studied food groups include fruits, vegetables, meat, fish, bread, whole grain cereals, nuts, wine, coffee, tea, cocoa, and chocolate. We identified 16 studies that evaluated metabolite signatures associated with dietary patterns. Dietary patterns examined included vegetarian and lactovegetarian diets, omnivorous diet, Western dietary patterns, prudent dietary patterns, Nordic diet, and Mediterranean diet. Although many metabolite biomarkers of individual foods and dietary patterns have been identified, those biomarkers may not be sensitive or specific to dietary intakes. Some biomarkers represent short-term intakes rather than long-term dietary habits. Nonetheless, nutritional metabolomics holds promise for the development of a robust and unbiased strategy for measuring diet. Still, this technology is intended to be complementary, rather than a replacement, to traditional well-validated dietary assessment methods such as food frequency questionnaires that can measure usual diet, the most relevant exposure in nutritional epidemiologic studies.
Background Exposure to tobacco smoke in utero is suspected to be associated with attention deficit hyperactivity disorder (ADHD) and ADHD symptoms in the offspring. Other lifestyle factors during pregnancy may also associate with these disorders. Many studies have suffered from methodological shortcomings, such as recall bias, inaccurate exposure assessment, low statistical power and lack of or insufficient control of confounders. Objective We investigated the association between maternal smoking during pregnancy and ADHD symptoms in adolescence. Method The geographically defined general population based study consisted of 6888 15-year-old adolescents with exposure and outcome data (74% of eligible) from the Northern Finland Birth Cohort born in 1985–86 (NFBC1986). Mothers provided information during pregnancy on their smoking and social standing (SES). At child's age 15 years, parent's assessed adolescent's behaviour by a SWAN questionnaire developed in USA. Scores on the three SWAN subscales-Inattentive (INN), Hyperactive-Impulsive (HI) or Combined (C) are defined from 18 items on the questionnaire. A subject was defined to have potentially ADHD (“ADHD symptoms”), if he/she falls in the upper 5%ile of INN, HI, or C subscales. Unadjusted analyses and stratification were used to study associations and confounding of a wide variety of theoretically associated factors. A multivariate logistic regression model was fitted to assess the independent association between smoking and outcome. Results In unadjusted analyses maternal smoking (yes vs. no), family structure (single parent or reconstructed family vs. always two-parent family), young maternal age at child's birth (< 19y) but not alcohol use during pregnancy (yes vs. no) were significantly associated by about 2-fold risk of ADHD symptoms. Maternal smoking was independently associated with increased risk of ADHD (OR 1.4, 95%CI 1.03–1.8) when adjusted for sex and family structure. After additional adjustment for SES, maternal age and alcohol use during pregnancy, the risk for ADHD symptoms was 1.3 times that of those not exposed to maternal smoking (95%CI 1.0–1.7) Conclusion This study, the largest population-based prospective follow-up on fetal tobacco smoke exposure and later behavioural disorders by age 15 years, supports suggested link between maternal smoking during gestation and ADHD symptoms. The known correlation between family structure, SES and maternal age and the fact that ADHD symptoms fade with age making them more difficult to detect in screening may explain that the association in the “fully adjusted” model was only marginally significant. Prenatal care should encourage pregnant mothers to abstain from smoking during pregnancy.
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