Lifelines COVID-19 cohort: investigating COVID-19 infection and its health and societal impacts in a Dutch population-based cohort.

PURPOSE: The Lifelines COVID-19 cohort was set up to assess the psychological and societal impacts of the COVID-19 pandemic and investigate potential risk factors for COVID-19 within the Lifelines prospective population cohort. PARTICIPANTS: Participants were recruited from the 140 000 eligible participants of Lifelines and the Lifelines NEXT birth cohort, who are all residents of the three northern provinces of the Netherlands. Participants filled out detailed questionnaires about their physical and mental health and experiences on a weekly basis starting in late March 2020, and the cohort consists of everyone who filled in at least one questionnaire in the first 8 weeks of the project. FINDINGS TO DATE: >71 000 unique participants responded to the questionnaires at least once during the first 8 weeks, with >22 000 participants responding to seven questionnaires. Compiled questionnaire results are continuously updated and shared with the public through the Corona Barometer website. Early results included a clear signal that younger people living alone were experiencing greater levels of loneliness due to lockdown, and subsequent results showed the easing of anxiety as lockdown was eased in June 2020. FUTURE PLANS: Questionnaires were sent on a (bi)weekly basis starting in March 2020 and on a monthly basis starting July 2020, with plans for new questionnaire rounds to continue through 2020 and early 2021. Questionnaire frequency can be increased again for subsequent waves of infections. Cohort data will be used to address how the COVID-19 pandemic developed in the northern provinces of the Netherlands, which environmental and genetic risk factors predict disease susceptibility and severity and the psychological and societal impacts of the crisis. Cohort data are linked to the extensive health, lifestyle and sociodemographic data held for these participants by Lifelines, a 30-year project that started in 2006, and to data about participants held in national databases.

Shared DNA methylation signatures in childhood allergy: The MeDALL study.

BACKGROUND: Differential DNA methylation associated with allergy might provide novel insights into the shared or unique etiology of asthma, rhinitis, and eczema. OBJECTIVE: We sought to identify DNA methylation profiles associated with childhood allergy. METHODS: Within the European Mechanisms of the Development of Allergy (MeDALL) consortium, we performed an epigenome-wide association study of whole blood DNA methylation by using a cross-sectional design. Allergy was defined as having symptoms from at least 1 allergic disease (asthma, rhinitis, or eczema) and positive serum-specific IgE to common aeroallergens. The discovery study included 219 case patients and 417 controls at age 4 years and 228 case patients and 593 controls at age 8 years from 3 birth cohorts, with replication analyses in 325 case patients and 1111 controls. We performed additional analyses on 21 replicated sites in 785 case patients and 2124 controls by allergic symptoms only from 8 cohorts, 3 of which were not previously included in analyses. RESULTS: We identified 80 differentially methylated CpG sites that showed a 1% to 3% methylation difference in the discovery phase, of which 21 (including 5 novel CpG sites) passed genome-wide significance after meta-analysis. All 21 CpG sites were also significantly differentially methylated with allergic symptoms and shared between asthma, rhinitis, and eczema. The 21 CpG sites mapped to relevant genes, including ACOT7, LMAN3, and CLDN23. All 21 CpG sties were differently methylated in asthma in isolated eosinophils, and 10 were replicated in respiratory epithelium. CONCLUSION: Reduced whole blood DNA methylation at 21 CpG sites was significantly associated with childhood allergy. The findings provide novel insights into the shared molecular mechanisms underlying asthma, rhinitis, and eczema.

Lifelines NEXT: a prospective birth cohort adding the next generation to the three-generation Lifelines cohort study.

Epidemiological research has shown there to be a strong relationship between preconceptional, prenatal, birth and early-life factors and lifelong health. The Lifelines NEXT is a birth cohort designed to study the effects of intrinsic and extrinsic determinants on health and disease in a four-generation design. It is embedded within the Lifelines cohort study, a prospective three-generation population-based cohort study recording the health and health-related aspects of 167,729 individuals living in Northern Netherlands. In Lifelines NEXT we aim to include 1500 pregnant Lifelines participants and intensively follow them, their partners and their children until at least 1 year after birth. Longer-term follow-up of physical and psychological health will then be embedded following Lifelines procedures. During the Lifelines NEXT study period biomaterials-including maternal and neonatal (cord) blood, placental tissue, feces, breast milk, nasal swabs and urine-will be collected from the mother and child at 10 time points. We will also collect data on medical, social, lifestyle and environmental factors via questionnaires at 14 different time points and continuous data via connected devices. The extensive collection of different (bio)materials from mother and child during pregnancy and afterwards will provide the means to relate environmental factors including maternal and neonatal microbiome composition) to (epi)genetics, health and developmental outcomes. The nesting of the study within Lifelines enables us to include preconceptional transgenerational data and can be used to identify other extended families within the cohort.

Analysis of 1135 gut metagenomes identifies sex-specific resistome profiles.

Several gastrointestinal diseases show a sex imbalance, although the underlying (patho)physiological mechanisms behind this are not well understood. The gut microbiome may be involved in this process, forming a complex interaction with host immune system, sex hormones, medication and other environmental factors. Here we performed sex-specific analyses of fecal microbiota composition in 1135 individuals from a population-based cohort. The overall gut microbiome composition of females and males was significantly different (p = 0.001), with females showing a greater microbial diversity (p = 0.009). After correcting for the effects of intrinsic factors, smoking, diet and medications, female hormonal factors such as the use of oral contraceptives and undergoing an ovariectomy were associated with microbial species and pathways. Females had a higher richness of antibiotic-resistance genes, with the most notable being resistance to the lincosamide nucleotidyltransferase (LNU) gene family. The higher abundance of resistance genes is consistent with the greater prescription of the Macrolide-Lincosamide-Streptogramin classes of antibiotics to females. Furthermore, we observed an increased resistance to aminoglycosides in females with self-reported irritable bowel syndrome. These results throw light upon the effects of common medications that are differentially prescribed between sexes and highlight the importance of sex-specific analysis when studying the gut microbiome and resistome.

Gut microbiota composition and functional changes in inflammatory bowel disease and irritable bowel syndrome.

Changes in the gut microbiota have been associated with two of the most common gastrointestinal diseases, inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). Here, we performed a case-control analysis using shotgun metagenomic sequencing of stool samples from 1792 individuals with IBD and IBS compared with control individuals in the general population. Despite substantial overlap between the gut microbiome of patients with IBD and IBS compared with control individuals, we were able to use gut microbiota composition differences to distinguish patients with IBD from those with IBS. By combining species-level profiles and strain-level profiles with bacterial growth rates, metabolic functions, antibiotic resistance, and virulence factor analyses, we identified key bacterial species that may be involved in two common gastrointestinal diseases.

DNA methylation in childhood asthma: an epigenome-wide meta-analysis.

BACKGROUND: DNA methylation profiles associated with childhood asthma might provide novel insights into disease pathogenesis. We did an epigenome-wide association study to assess methylation profiles associated with childhood asthma. METHODS: We did a large-scale epigenome-wide association study (EWAS) within the Mechanisms of the Development of ALLergy (MeDALL) project. We examined epigenome-wide methylation using Illumina Infinium Human Methylation450 BeadChips (450K) in whole blood in 207 children with asthma and 610 controls at age 4-5 years, and 185 children with asthma and 546 controls at age 8 years using a cross-sectional case-control design. After identification of differentially methylated CpG sites in the discovery analysis, we did a validation study in children (4-16 years; 247 cases and 2949 controls) from six additional European cohorts and meta-analysed the results. We next investigated whether replicated CpG sites in cord blood predict later asthma in 1316 children. We subsequently investigated cell-type-specific methylation of the identified CpG sites in eosinophils and respiratory epithelial cells and their related gene-expression signatures. We studied cell-type specificity of the asthma association of the replicated CpG sites in 455 respiratory epithelial cell samples, collected by nasal brushing of 16-year-old children as well as in DNA isolated from blood eosinophils (16 with asthma, eight controls [age 2-56 years]) and compared this with whole-blood DNA samples of 74 individuals with asthma and 93 controls (age 1-79 years). Whole-blood transcriptional profiles associated with replicated CpG sites were annotated using RNA-seq data of subsets of peripheral blood mononuclear cells sorted by fluorescence-activated cell sorting. FINDINGS: 27 methylated CpG sites were identified in the discovery analysis. 14 of these CpG sites were replicated and passed genome-wide significance (p<1·14 × 10-7) after meta-analysis. Consistently lower methylation levels were observed at all associated loci across childhood from age 4 to 16 years in participants with asthma, but not in cord blood at birth. All 14 CpG sites were significantly associated with asthma in the second replication study using whole-blood DNA, and were strongly associated with asthma in purified eosinophils. Whole-blood transcriptional signatures associated with these CpG sites indicated increased activation of eosinophils, effector and memory CD8 T cells and natural killer cells, and reduced number of naive T cells. Five of the 14 CpG sites were associated with asthma in respiratory epithelial cells, indicating cross-tissue epigenetic effects. INTERPRETATION: Reduced whole-blood DNA methylation at 14 CpG sites acquired after birth was strongly associated with childhood asthma. These CpG sites and their associated transcriptional profiles indicate activation of eosinophils and cytotoxic T cells in childhood asthma. Our findings merit further investigations of the role of epigenetics in a clinical context. FUNDING: EU and the Seventh Framework Programme (the MeDALL project).

The emerging landscape of dynamic DNA methylation in early childhood.

BACKGROUND: DNA methylation has been found to associate with disease, aging and environmental exposure, but it is unknown how genome, environment and disease influence DNA methylation dynamics in childhood. RESULTS: By analysing 538 paired DNA blood samples from children at birth and at 4-5 years old and 726 paired samples from children at 4 and 8 years old from four European birth cohorts using the Illumina Infinium Human Methylation 450 k chip, we have identified 14,150 consistent age-differential methylation sites (a-DMSs) at epigenome-wide significance of p < 1.14 × 10-7. Genes with an increase in age-differential methylation were enriched in pathways related to 'development', and were more often located in bivalent transcription start site (TSS) regions, which can silence or activate expression of developmental genes. Genes with a decrease in age-differential methylation were involved in cell signalling, and enriched on H3K27ac, which can predict developmental state. Maternal smoking tended to decrease methylation levels at the identified da-DMSs. We also found 101 a-DMSs (0.71%) that were regulated by genetic variants using cis-differential Methylation Quantitative Trait Locus (cis-dMeQTL) mapping. Moreover, a-DMS-associated genes during early development were significantly more likely to be linked with disease. CONCLUSION: Our study provides new insights into the dynamic epigenetic landscape of the first 8 years of life.

Epigenome-Wide Meta-Analysis of Methylation in Children Related to Prenatal NO2 Air Pollution Exposure.

BACKGROUND: Prenatal exposure to air pollution is considered to be associated with adverse effects on child health. This may partly be mediated by mechanisms related to DNA methylation. OBJECTIVES: We investigated associations between exposure to air pollution, using nitrogen dioxide (NO2) as marker, and epigenome-wide cord blood DNA methylation. METHODS: We meta-analyzed the associations between NO2 exposure at residential addresses during pregnancy and cord blood DNA methylation (Illumina 450K) in four European and North American studies (n = 1,508) with subsequent look-up analyses in children ages 4 (n = 733) and 8 (n = 786) years. Additionally, we applied a literature-based candidate approach for antioxidant and anti-inflammatory genes. To assess influence of exposure at the transcriptomics level, we related mRNA expression in blood cells to NO2 exposure in 4- (n = 111) and 16-year-olds (n = 239). RESULTS: We found epigenome-wide significant associations [false discovery rate (FDR) p < 0.05] between maternal NO2 exposure during pregnancy and DNA methylation in newborns for 3 CpG sites in mitochondria-related genes: cg12283362 (LONP1), cg24172570 (3.8 kbp upstream of HIBADH), and cg08973675 (SLC25A28). The associations with cg08973675 methylation were also significant in the older children. Further analysis of antioxidant and anti-inflammatory genes revealed differentially methylated CpGs in CAT and TPO in newborns (FDR p < 0.05). NO2 exposure at the time of biosampling in childhood had a significant impact on CAT and TPO expression. CONCLUSIONS: NO2 exposure during pregnancy was associated with differential offspring DNA methylation in mitochondria-related genes. Exposure to NO2 was also linked to differential methylation as well as expression of genes involved in antioxidant defense pathways. Citation: Gruzieva O, Xu CJ, Breton CV, Annesi-Maesano I, Antó JM, Auffray C, Ballereau S, Bellander T, Bousquet J, Bustamante M, Charles MA, de Kluizenaar Y, den Dekker HT, Duijts L, Felix JF, Gehring U, Guxens M, Jaddoe VV, Jankipersadsing SA, Merid SK, Kere J, Kumar A, Lemonnier N, Lepeule J, Nystad W, Page CM, Panasevich S, Postma D, Slama R, Sunyer J, Söderhäll C, Yao J, London SJ, Pershagen G, Koppelman GH, Melén E. 2017. Epigenome-wide meta-analysis of methylation in children related to prenatal NO2 air pollution exposure. Environ Health Perspect 125:104-110; http://dx.doi.org/10.1289/EHP36.

The effect of host genetics on the gut microbiome.

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 × 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 × 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 × 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.

Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity.

Deep sequencing of the gut microbiomes of 1135 participants from a Dutch population-based cohort shows relations between the microbiome and 126 exogenous and intrinsic host factors, including 31 intrinsic factors, 12 diseases, 19 drug groups, 4 smoking categories, and 60 dietary factors. These factors collectively explain 18.7% of the variation seen in the interindividual distance of microbial composition. We could associate 110 factors to 125 species and observed that fecal chromogranin A (CgA), a protein secreted by enteroendocrine cells, was exclusively associated with 61 microbial species whose abundance collectively accounted for 53% of microbial composition. Low CgA concentrations were seen in individuals with a more diverse microbiome. These results are an important step toward a better understanding of environment-diet-microbe-host interactions.

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

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 pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

Proton pump inhibitors affect the gut microbiome.

BACKGROUND AND AIMS: Proton pump inhibitors (PPIs) are among the top 10 most widely used drugs in the world. PPI use has been associated with an increased risk of enteric infections, most notably Clostridium difficile. The gut microbiome plays an important role in enteric infections, by resisting or promoting colonisation by pathogens. In this study, we investigated the influence of PPI use on the gut microbiome. METHODS: The gut microbiome composition of 1815 individuals, spanning three cohorts, was assessed by tag sequencing of the 16S rRNA gene. The difference in microbiota composition in PPI users versus non-users was analysed separately in each cohort, followed by a meta-analysis. RESULTS: 211 of the participants were using PPIs at the moment of stool sampling. PPI use is associated with a significant decrease in Shannon's diversity and with changes in 20% of the bacterial taxa (false discovery rate <0.05). Multiple oral bacteria were over-represented in the faecal microbiome of PPI-users, including the genus Rothia (p=9.8×10(-38)). In PPI users we observed a significant increase in bacteria: genera Enterococcus, Streptococcus, Staphylococcus and the potentially pathogenic species Escherichia coli. CONCLUSIONS: The differences between PPI users and non-users observed in this study are consistently associated with changes towards a less healthy gut microbiome. These differences are in line with known changes that predispose to C. difficile infections and can potentially explain the increased risk of enteric infections in PPI users. On a population level, the effects of PPI are more prominent than the effects of antibiotics or other commonly used drugs.

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

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.

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

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.