5 research outputs found

    DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring

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    Background: We examined whether the effect of maternal smoking during pregnancy on birthweight of the offspring was mediated by smoking-induced changes to DNA methylation in cord blood. Methods: First, we used cord blood of 129 Dutch children exposed to maternal smoking vs 126 unexposed to maternal and paternal smoking (53% male) participating in the GECKO Drenthe birth cohort. DNA methylation was measured using the Illumina HumanMethylation450 Beadchip. We performed an epigenome-wide association study for the association between maternal smoking and methylation followed by a mediation analysis of the top signals [false-discovery rate (FDR)<0.05]. We adjusted both analyses for maternal age, education, pre-pregnancy BMI, offspring's sex, gestational age and white blood cell composition. Secondly, in 175 exposed and 1248 unexposed newborns from two independent birth cohorts, we replicated and meta-analysed results of eight cytosine-phosphate-guanine (CpG) sites in the GFI1 gene, which showed the most robust mediation. Finally, we performed functional network and enrichment analysis. Results: We found 35 differentially methylated CpGs (FDR<0.05) in newborns exposed vs unexposed to smoking, of which 23 survived Bonferroni correction (P<1×10-7). These 23 CpGs mapped to eight genes: AHRR, GFI1, MYO1G, CYP1A1, NEUROG1, CNTNAP2, FRMD4A and LRP5. We observed partial confirmation as three of the eight CpGs in GFI1 replicated. These CpGs partly mediated the effect of maternal smoking on birthweight (Sobel P<0.05) in meta-analysis of GECKO and the two replication cohorts. Differential methylation of these three GFI1 CpGs explained 12-19% of the 202 g lower birthweight in smoking mothers. Functional enrichment analysis pointed towards activation of cell-mediated immunity. Conclusions: Maternal smoking during pregnancy was associated with cord blood methylation differences. We observed a potentially mediating role of methylation in the association between maternal smoking during pregnancy and birthweight of the offspring. Functional network analysis suggested a role in activating the immune system

    The effect of host genetics on the gut microbiome

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    Contains fulltext : 171719.pdf (publisher's version ) (Closed access)The gut microbiome is affected by multiple factors, including genetics. In this study, we assessed the influence of host genetics on microbial species, pathways and gene ontology categories, on the basis of metagenomic sequencing in 1,514 subjects. In a genome-wide analysis, we identified associations of 9 loci with microbial taxonomies and 33 loci with microbial pathways and gene ontology terms at P < 5 x 10-8. Additionally, in a targeted analysis of regions involved in complex diseases, innate and adaptive immunity, or food preferences, 32 loci were identified at the suggestive level of P < 5 x 10-6. Most of our reported associations are new, including genome-wide significance for the C-type lectin molecules CLEC4F-CD207 at 2p13.3 and CLEC4A-FAM90A1 at 12p13. We also identified association of a functional LCT SNP with the Bifidobacterium genus (P = 3.45 x 10-8) and provide evidence of a gene-diet interaction in the regulation of Bifidobacterium abundance. Our results demonstrate the importance of understanding host-microbe interactions to gain better insight into human health

    Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

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    Background The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case-control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD

    DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis

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    Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathw
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