Showing papers by "Marc Jan Bonder published in 2018"

Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease

Abstract: Objective Patients with IBD display substantial heterogeneity in clinical characteristics. We hypothesise that individual differences in the complex interaction of the host genome and the gut microbiota can explain the onset and the heterogeneous presentation of IBD. Therefore, we performed a case–control analysis of the gut microbiota, the host genome and the clinical phenotypes of IBD. Design Stool samples, peripheral blood and extensive phenotype data were collected from 313 patients with IBD and 582 truly healthy controls, selected from a population cohort. The gut microbiota composition was assessed by tag-sequencing the 16S rRNA gene. All participants were genotyped. We composed genetic risk scores from 11 functional genetic variants proven to be associated with IBD in genes that are directly involved in the bacterial handling in the gut: NOD2 , CARD9 , ATG16L1 , IRGM and FUT2 . Results Strikingly, we observed significant alterations of the gut microbiota of healthy individuals with a high genetic risk for IBD: the IBD genetic risk score was significantly associated with a decrease in the genus Roseburia in healthy controls (false discovery rate 0.017). Moreover, disease location was a major determinant of the gut microbiota: the gut microbiota of patients with colonic Crohn's disease (CD) is different from that of patients with ileal CD, with a decrease in alpha diversity associated to ileal disease (p=3.28×10−13). Conclusions We show for the first time that genetic risk variants associated with IBD influence the gut microbiota in healthy individuals. Roseburia spp are acetate-to-butyrate converters, and a decrease has already been observed in patients with IBD.

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Abstract: While many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear. To identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium. We observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci. In contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology. We observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.

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

Abstract: 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

Abstract: Summary 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 −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).

DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA 1c levels: a systematic review and replication in a case–control sample of the Lifelines study

Abstract: Epigenetic mechanisms may play an important role in the aetiology of type 2 diabetes. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels. Here we present a systematic review of these studies and attempt to replicate the CpG sites (CpGs) with the most significant associations from these EWASs in a case–control sample of the Lifelines study. We performed a systematic literature search in PubMed and EMBASE for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits and reviewed the search results. For replication purposes we selected 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs, using study-specific Bonferroni-corrected significance thresholds. Methylation data (Illumina 450K array) in whole blood from 100 type 2 diabetic individuals and 100 control individuals from the Lifelines study were available. Multivariate linear models were used to examine the associations of the specific CpGs with type 2 diabetes and glycaemic traits. From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed nominally significant associations with type 2 diabetes in the Lifelines sample (p < 0.05). The results for five CpGs (in ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1) remained significant after a stringent multiple-testing correction (changes in methylation from −3% up to 3.6%, p < 0.0009). All associations were directionally consistent with the original EWAS results. None of the selected CpGs from the tissue-specific EWASs were replicated in our methylation data from whole blood. We were also unable to replicate any of the CpGs associated with HbA1c levels in the healthy control individuals of our sample, while two CpGs (in ABCG1 and CCDC57) for fasting glucose were replicated at a nominal significance level (p < 0.05). A number of differentially methylated CpGs reported to be associated with type 2 diabetes in the EWAS literature were replicated in blood and show promise for clinical use as disease biomarkers. However, more prospective studies are needed to support the robustness of these findings.

Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative

Abstract: In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed.

Individual variations in cardiovascular-disease-related protein levels are driven by genetics and gut microbiome

Abstract: Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect in cardiovascular disease and provides directions for future applications in personalized medicine.

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations

Abstract: Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them Comparing populations we find that community structure is significantly more similar between datasets than expected by chance Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses

DNA methylation signatures of educational attainment

Abstract: Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.

A linear mixed model approach to study multivariate gene-environment interactions

Abstract: Different environmental factors, including diet, physical activity, or external conditions can contribute to genotype-environment interactions (GxE). Although high-dimensional environmental data are increasingly available, and multiple environments have been implicated with GxE at the same loci, multi-environment tests for GxE are not established. Such joint analyses can increase power to detect GxE and improve the interpretation of these effects. Here, we propose the structured linear mixed model (StructLMM), a computationally efficient method to test for and characterize loci that interact with multiple environments. After validating our model using simulations, we apply StructLMM to body mass index in UK Biobank, where our method detects previously known and novel GxE signals. Finally, in an application to a large blood eQTL dataset, we demonstrate that StructLMM can be used to study interactions with hundreds of environmental variables.

Population-scale proteome variation in human induced pluripotent stem cells

Abstract: Realising the potential of human induced pluripotent stem cell (iPSC) technology for drug discovery, disease modelling and cell therapy requires an understanding of variability across iPSC lines. While previous studies have characterized iPS cell lines genetically and transcriptionally, little is known about the variability of the iPSC proteome. Here, we present the first comprehensive proteomic iPSC dataset, analysing 202 iPSC lines derived from 151 donors. We characterise the major genetic determinants affecting proteome and transcriptome variation across iPSC lines and identify key regulatory mechanisms affecting variation in protein abundance. Our data identified >700 human iPSC protein quantitative trait loci (pQTLs). We mapped trans regulatory effects, identifying an important role for protein-protein interactions. We discovered that pQTLs show increased enrichment in disease-linked GWAS variants, compared with RNA-based eQTLs.

A locus at 7p14.3 predisposes to refractory celiac disease progression from celiac disease.

Abstract: Background Approximately 5% of patients with celiac disease (CeD) do not respond to a gluten-free diet and progress to refractory celiac disease (RCD), a severe progression that is characterized by infiltration of intraepithelial T lymphocytes. Patients with RCD type II (RCDII) show clonal expansions of intraepithelial T lymphocytes that result in a poor prognosis and a high mortality rate through development of aggressive enteropathy-associated T-cell lymphoma. It is not known whether genetic variations play a role in severe progression of CeD to RCDII. Patients and methods We performed the first genome-wide association study to identify the causal genes for RCDII and the molecular pathways perturbed in RCDII. The genome-wide association study was performed in 38 Dutch patients with RCDII, and the 15 independent top-associated single nucleotide polymorphism (SNP) variants (P Results After replication, SNP rs2041570 on chromosome 7 was significantly associated with progression to RCDII (P=2.37x10(-8), odds ratio=2.36) but not with CeD susceptibility. SNP rs2041570 risk allele A was associated with lower levels of FAM188B expression in blood and small intestinal biopsies. Stratification of RCDII biopsies based on rs2041570 genotype showed differential expression of innate immune and antibacterial genes that are expressed in Paneth cells. Conclusion We have identified a novel SNP associated with the severe progression of CeD to RCDII. Our data suggest that genetic susceptibility to CeD might be distinct from the progression to RCDII and suggest a role for Paneth cells in RCDII progression. Copyright (C) 2018 Wolters Kluwer Health, Inc. All rights reserved.

Combined single cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity

Abstract: Alternative splicing is a key mechanism in eukaryotic cells to increase the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied both across human tissues and in genetically diverse individuals. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue and its determinants remain poorly understood. We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that splicing rates in single cells can be accurately predicted based on sequence composition and other genomic features. We also identified a moderate but significant contribution from DNA methylation to splicing variation across cells. By combining sequence information and DNA methylation, we derived an accurate model (AUC=0.85) for predicting different splicing modes of individual cassette exons. These explain conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation. Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.

Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants

Abstract: Decoding the clonal substructures of somatic tissues sheds light on cell growth, development and differentiation in health, ageing and disease DNA-sequencing, either using bulk or using single-cell assays, has enabled the reconstruction of clonal trees from somatic variants However, approaches to systematically characterize phenotypic and functional variations between clones are not established Here we present cardelino (https://githubcom/PMBio/cardelino), a computational method to assign single-cell transcriptome profiles to somatic clones using variant information contained in single-cell RNA-seq (scRNA-seq) data After validating our model using simulations, we apply cardelino to matched scRNA-seq and exome sequencing data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells assigned to different clones These genes were frequently enriched for cell cycle and proliferation pathways, indicating a key role for cell division genes in non-neutral somatic evolution