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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.

BACKGROUND: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels.METHODS: We applied summary-data-based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data-based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels.RESULTS: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before.CONCLUSIONS: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies.

Background Since evidence-based dietary guidelines are lacking for IBD patients, they tend to follow “unguided” dietary habits; potentially leading to nutritional deficiencies and detrimental effects on disease course. Therefore, we compared dietary intake of IBD patients with controls. Methods Dietary intake of macronutrients and 25 food groups of 493 patients (207 UC, 286 CD), and 1291 controls was obtained via a food frequency questionnaire. Results 38.6% of patients in remission had protein intakes below the recommended 0.8 g/kg and 86.7% with active disease below the recommended 1.2 g/kg. Multinomial logistic regression, corrected for age, gender and BMI, showed that (compared to controls) UC patients consumed more meat and spreads, but less alcohol, breads, coffee and dairy; CD patients consumed more non-alcoholic drinks, potatoes, savoury snacks and sugar and sweets but less alcohol, dairy, nuts, pasta and prepared meals. Patients with active disease consumed more meat, soup and sugar and sweets but less alcohol, coffee, dairy, prepared meals and rice; patients in remission consumed more potatoes and spreads but less alcohol, breads, dairy, nuts, pasta and prepared meals. Conclusions Patients avoiding potentially favourable foods and gourmandizing potentially unfavourable foods are of concern. Special attention is needed for protein intake in the treatment of these patients.

The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota-gut-brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential. Surveying a large microbiome population cohort (Flemish Gut Flora Project, n =1,054) with validation in independent data sets (n(total) =1,070), we studied how microbiome features correlate with host quality of life and depression. Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with Dialister, Coprococcus spp. were also depleted in depression, even after correcting for the confounding effects of antidepressants. Using a module-based analytical framework, we assembled a catalogue of neuroactive potential of sequenced gut prokaryotes. Gut-brain module analysis of faecal metagenomes identified the microbial synthesis potential of the dopamine metabolite 3,4-dihydroxyphenylacetic acid as correlating positively with mental quality of life and indicated a potential role of microbial gamma-aminobutyric acid production in depression. Our results provide population-scale evidence for microbiome links to mental health, while emphasizing confounder importance.

Contains fulltext : 209008.pdf (Publisher’s version ) (Open Access) BACKGROUND: Previous studies have reported associations between attention-deficit/hyperactivity disorder symptoms and DNA methylation in children. We report the first epigenome-wide association study meta-analysis of adult attention-deficit/hyperactivity disorder symptoms, based on peripheral blood DNA methylation (Infinium HumanMethylation450K array) in three population-based adult cohorts. METHODS: An epigenome-wide association study was performed in the Netherlands Twin Register (N = 2258, mean age 37 years), Dunedin Multidisciplinary Health and Development Study (N = 800, age 38 years), and Environmental Risk Longitudinal Twin Study (N = 1631, age 18 years), and results were combined through meta-analysis (total sample size N = 4689). Region-based analyses accounting for the correlation between nearby methylation sites were also performed. RESULTS: One epigenome-wide significant differentially methylated position was detected in the Dunedin study, but meta-analysis did not detect differentially methylated positions that were robustly associated across cohorts. In region-based analyses, six significant differentially methylation regions (DMRs) were identified in the Netherlands Twin Register, 19 in the Dunedin study, and none in the Environmental Risk Longitudinal Twin Study. Of these DMRs, 92% were associated with methylation quantitative trait loci, and 68% showed moderate to large blood-brain correlations for DNA methylation levels. DMRs included six nonoverlapping DMRs (three in the Netherlands Twin Register, three in the Dunedin study) in the major histocompatibility complex, which were associated with expression of genes in the major histocompatibility complex, including C4A and C4B, previously implicated in schizophrenia. CONCLUSIONS: Our findings point at new candidate loci involved in immune and neuronal functions that await further replication. Our work also illustrates the need for further research to examine to what extent epigenetic associations with psychiatric traits depend on characteristics such as age, comorbidities, exposures, and genetic background.

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.

BackgroundThe diagnosis of irritable bowel syndrome (IBS) is challenging because of its heterogeneity and multifactorial pathophysiology. No reliable biomarkers of IBS have been identified so far.AimsIn a case-control study, using a novel application of breath analysis to distinguish IBS patients from healthy controls based on the analysis of volatile organic compounds (VOCs). Subsequently, the diagnostic VOC-biomarker set was correlated with self-reported gastrointestinal (GI) symptoms of subjects of the Maastricht IBS clinical cohort and of a general population cohort, LifeLines DEEP.MethodsBreath samples were collected from 170 IBS patients and 153 healthy controls in the clinical cohort and from 1307 participants in general population cohort. Multivariate statistics were used to identify the most discriminatory set of VOCs in the clinical cohort, and to find associations between VOCs and GI symptoms in both cohorts.ResultsA set of 16 VOCs correctly predicted 89.4% of the IBS patients and 73.3% of the healthy controls (AUC = 0.83). The VOC-biomarker set correlated moderately with a set of GI symptoms in the clinical (r = 0.55, P = 0.0003) and general population cohorts (r = 0.54, P = 0.0004). A Kruskal-Wallis test showed no influence from possible confounding factors in distinguishing IBS patients from healthy controls.ConclusionsA set of 16 breath-based biomarkers that distinguishes IBS patients from healthy controls was identified. The VOC-biomarker set correlated significantly with GI symptoms in two independent cohorts. We demonstrate the potential use of breath analysis in the diagnosis and monitoring of IBS, and a possible application of VOC analyses in a general population cohort.

Contains fulltext : 171367.pdf (Publisher’s version ) (Open Access) Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases.

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science , this issue pp. 560 and 565

Stool consistency and frequency patterns are complex traits that are often altered in GI disease, and recent studies published in Gut highlight the importance of stool frequency in relation to gut microbiota composition and the efficacy of pharmacological and dietary treatments in IBS.1–3 Despite reported heritability in invertebrates4 and similar evidence from open-field defaecation models in rats,5 the genetics of stool frequency has not been explored in humans. We undertook a genome-wide association study (GWAS) in two well-characterised population-based cohorts with genotype and defaecation data available: LifeLines-Deep (LLD) from the Netherlands (N=1546; 58% females; mean age 44 years (range 18–86)) and PopCol (PC) from Sweden (N=284; 60% females; mean age 54 years (range 22–71)).6 ,7 The average number of bowel movements per day (BM/d) was extracted from daily records kept by both populations and did not differ between cohorts (LLD=1.39±0.64SD; PC=1.42±0.74SD). Available CytoChip+Immunochip (LLD) and HumanOmniExpressExome (PC) Illumina single-nucleotide polymorphism (SNP) genotype data were imputed using IMPUTE2 (https://mathgen.stats.ox.ac.uk/impute/impute_v2.html) with the Genome of the Netherlands (http://www.nlgenome.nl/) as reference. SNPs were filtered on minor allele frequency >0.05 and Hardy–Weinberg equilibrium p>1E-04, samples were filtered on infoscore ≥0.8 and population outliers …

BackgroundIrritable bowel syndrome (IBS) shows genetic predisposition, however, large-scale, powered gene mapping studies are lacking. We sought to exploit existing genetic (genotype) and epidemiological (questionnaire) data from a series of population-based cohorts for IBS genome-wide association studies (GWAS) and their meta-analysis.MethodsBased on questionnaire data compatible with Rome III Criteria, we identified a total of 1335 IBS cases and 9768 asymptomatic individuals from 5 independent European genotyped cohorts. Individual GWAS were carried out with sex-adjusted logistic regression under an additive model, followed by meta-analysis using the inverse variance method. Functional annotation of significant results was obtained via a computational pipeline exploiting ontology and interaction networks, and tissue-specific and gene set enrichment analyses.Key ResultsSuggestive GWAS signals (P5.0x10(-6)) were detected for 7 genomic regions, harboring 64 gene candidates to affect IBS risk via functional or expression changes. Functional annotation of this gene set convincingly (best FDR-corrected P=3.1x10(-10)) highlighted regulation of ion channel activity as the most plausible pathway affecting IBS risk.Conclusion & InferencesOur results confirm the feasibility of population-based studies for gene-discovery efforts in IBS, identify risk genes and loci to be prioritized in independent follow-ups, and pinpoint ion channels as important players and potential therapeutic targets warranting further investigation.

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0× 10-7; replication: N = 7,182, p 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

Background: Diet is considered to be a key factor in symptom generation in Irritable Bowel Syndrome (IBS) and patients tend to exclude food products from their diet in pursue of symptom relief, which may impair diet quality.Methods: We evaluated habitual dietary intake in IBS patients with regard to nutrients and food products using an extensive food frequency questionnaire. One hundred ninety-four IBS patients were compared to 186 healthy controls using multiple logistic regression analysis. An overall diet quality score was calculated for each participant based on the criteria of the Dutch Healthy Diet (DHD) index.Key Results: A lower DHD-score was found for IBS (mean [SD]: 52.9 [9.6]) vs controls (55.1 [9.2], P=.02). The diet of patients was lower in fibers (21 g vs 25 g per day, P=.002) and fructose (14 g vs 16 g, P=.033), while higher in total fat (37% vs 36% of total energy intake, P=.010) and added sugars (46 g vs 44 g, P=.029). Differences in daily intake of food products included lower consumption of apples (40 g vs 69 g, PP=.029) and alcoholic beverages (130 g vs 193 g, P=.024) and higher consumption of processed meat (38 g vs 29 g, PConclusions and Inferences: Differences in habitual diet were described, showing lower diet quality in IBS patients compared to controls, with increased consumption of fat and lower intake of fibers and fructose. Our data support the importance of personalized and professional nutritional guidance of IBS patients.

Although genome-wide association studies and fine mapping have identified 39 non-HLA loci associated with celiac disease (CD), it is difficult to pinpoint the functional variants and susceptibility genes in these loci. We applied integrative approaches to annotate and prioritize functional single nucleotide polymorphisms (SNPs), genes and pathways affected in CD. CD-associated SNPs were intersected with regulatory elements categorized by the ENCODE project to prioritize functional variants, while results from cis-expression quantitative trait loci (eQTL) mapping in 1469 blood samples were combined with co-expression analyses to prioritize causative genes. To identify the key cell types involved in CD, we performed pathway analysis on RNA-sequencing data from different immune cell populations and on publicly available expression data on non-immune tissues. We discovered that CD SNPs are significantly enriched in B-cell-specific enhancer regions, suggesting that, besides T-cell processes, B-cell responses play a major role in CD. By combining eQTL and co-expression analyses, we prioritized 43 susceptibility genes in 36 loci. Pathway and tissue-specific expression analyses on these genes suggested enrichment of CD genes in the Th1, Th2 and Th17 pathways, but also predicted a role for four genes in the intestinal barrier function. We also discovered an intricate transcriptional connectivity between CD susceptibility genes and interferon-gamma, a key effector in CD, despite the absence of CD-associated SNPs in the IFNG locus. Using systems biology, we prioritized the CD-associated functional SNPs and genes. By highlighting a role for B cells in CD, which classically has been described as a T-cell-driven disease, we offer new insights into the mechanisms and pathways underlying CD.

Vandeputte et al 1 recently reported a strong effect of stool consistency—as measured by the Bristol Stool Scale (BSS)—on the composition of the gut microbiota in 53 healthy females. This work potentially has a large impact on future microbiome studies as it suggests that such studies may need to be corrected for BSS scores. However, the generalisability of their study is not immediately evident as it did not include a replication cohort and was limited to females aged 20–55 years. We analysed gut microbiota in relation to BSS in LifeLines-DEEP, a large population-based cohort.2 From 1126 LifeLines-DEEP participants, with both males (n=454) and females (n=672) aged 18–81 years (table 1), the BSS score was recorded for seven consecutive days and a fresh-frozen stool sample was collected in the same week. We calculated the average stool type of 7-day records for each participant. Stool DNA was isolated using AllPrep DNA/RNA Mini Kit (Qiagen; cat. #80204), and subsequently we performed 16s rRNA gene sequencing using forward primer …

The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota-gut-brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential. Surveying a large microbiome population cohort (Flemish Gut Flora Project, n = 1,054) with validation in independent data sets (n

Background. Thousands of endogenous and exogenous volatile organic compounds (VOCs) are excreted in each breath. Inflammatory and deviant metabolic processes affect the level of endogeneous VOCs, which can serve as specific biomarkers for clinical diagnosis and disease monitoring. Important issues that still need to be tackled are related to potential confounding factors like gender and age and endogenous and exogenous factors, like f.i. smoking. Methods. The aim of this study was to systematically access the effect of endogenous and exogenous factors on VOC composition of exhaled breath. In the current study breath samples from 1417 adult participants from the LifeLines cohort, a general population cohort in the Netherlands, were collected and the total content of VOCs was measured using gas chromatography-time-of-flight-mass spectrometry. Breath samples were collected in Groningen and transferred to carbon tubes immediately. These samples were then shipped to Maastricht and measured in batches. VOCs profiles were correlated to 14 relevant characteristics of all participants including age, BMI, smoking and blood cell counts and metabolic parameters as well as to 16 classes of medications. Results. VOCs profiles were shown to be significantly influenced by smoking behavior and to a lesser extent by age, BMI and gender. These factors need to be controlled for in breath analysis studies. We found no evidence whatsoever in this 1417 subjects' cohort that white blood cell counts, cholesterol or triglycerides levels have an influence on the VOC profile. Thus they may not have to be controlled for in exhaled breath studies. Conclusion. The large cohort of volunteers used here represents a unique opportunity to gauge the factors influencing VOCs profiles in a general population i.e. the most clinically relevant population. Classical clinical parameters and smoking habits clearly influence breath content and should therefore be accounted for in future clinical studies involving breath analysis.

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1131-9) contains supplementary material, which is available to authorized users.

Most disease associated genetic risk factors are non-coding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer downstream effects of disease variants but the large majority remains unexplained.. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. However, a large-scale, combined analysis of methylome and transcriptome data to infer downstream effects of disease variants is lacking. Here, we show that disease variants have wide-spread effects on DNA methylation in trans that likely reflect the downstream effects on binding sites of cis-regulated transcription factors. Using data on 3,841 Dutch samples, we detected 272,037 independent cis-meQTLs (FDR < 0.05) and identified 1,907 trait-associated SNPs that affect methylation levels of 10,141 different CpG sites in trans (FDR < 0.05), an eight-fold increase in the number of downstream effects that was known from trans-eQTL studies. Trans-meQTL CpG sites are enriched for active regulatory regions, being correlated with gene expression and overlap with Hi-C determined interchromosomal contacts. We detected many trans-meQTL SNPs that affect expression levels of nearby transcription factors (including NFKB1, CTCF and NKX2-3), while the corresponding trans-meQTL CpG sites frequently coincide with its respective binding site. Trans-meQTL mapping therefore provides a strategy for identifying and better understanding downstream functional effects of many disease-associated variants.

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.

Use of dietary supplements is rising in countries where colorectal cancer is prevalent. We conducted a systematic literature review and meta-analyses of prospective cohort studies on dietary supplement use and colorectal cancer risk. We identified relevant studies in Medline, Embase and Cochrane up to January 2013. Original and peer-reviewed papers on dietary supplement use and colorectal cancer, colon cancer, or rectal cancer incidence were included. "Use-no use"(U-NU), "highest-lowest"(H-L) and "dose-response"(DR) meta-analyses were performed. Random-effects models were used to estimate summary estimates. In total, 24 papers were included in the meta-analyses. We observed inverse associations for colorectal cancer risk and multivitamin (U-NU: RR = 0.92; 95% CI: 0.87,0.97) and calcium supplements (U-NU: RR = 0.86; 95% CI: 0.79,0.95; H-L: RR = 0.80; 95% CI: 0.70,0.92; DR: for an increase of 100 mg/day, RR = 0.96; 95% CI: 0.94,0.99). Inconsistent associations were found for colon cancer risk and supplemental vitamin A and vitamin C, and for colorectal cancer risk and supplemental vitamin D, vitamin E, garlic and folic acid. Meta-analyses of observational studies suggest a beneficial role for multivitamins and calcium supplements on colorectal cancer risk, while the association with other supplements and colorectal cancer risk is inconsistent. Residual confounding of lifestyle factors might be present. Before recommendations can be made, an extensive assessment of dietary supplement use and a better understanding of underlying mechanisms is needed.

The human gut is colonized by a wide diversity of micro-organisms, which are now known to play a key role in the human host by regulating metabolic functions and immune homeostasis. Many studies have indicated that the genomes of our gut microbiota, known as the gut microbiome or our "other genome" could play an important role in immune-related, complex diseases, and growing evidence supports a causal role for gut microbiota in regulating predisposition to diseases. A comprehensive analysis of the human gut microbiome is thus important to unravel the exact mechanisms by which the gut microbiota are involved in health and disease. Recent advances in next-generation sequencing technology, along with the development of metagenomics and bioinformatics tools, have provided opportunities to characterize the microbial communities. Furthermore, studies using germ-free animals have shed light on how the gut microbiota are involved in autoimmunity. In this review we describe the different approaches used to characterize the human microbiome, review current knowledge about the gut microbiome, and discuss the role of gut microbiota in immune homeostasis and autoimmunity. Finally, we indicate how this knowledge could be used to improve human health by manipulating the gut microbiota. This article is part of a Special Issue entitled: From Genome to Function. (C) 2014 Elsevier B.V. All rights reserved.

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.

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 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.

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science , this issue pp. 560 and 565

Background A gluten-free diet (GFD) is the most commonly adopted special diet worldwide. It is an effective treatment for coeliac disease and is also often followed by individuals to alleviate gastrointestinal complaints. It is known there is an important link between diet and the gut microbiome, but it is largely unknown how a switch to a GFD affects the human gut microbiome. Methods We studied changes in the gut microbiomes of 21 healthy volunteers who followed a GFD for four weeks. We collected nine stool samples from each participant: one at baseline, four during the GFD period, and four when they returned to their habitual diet (HD), making a total of 189 samples. We determined microbiome profiles using 16S rRNA sequencing and then processed the samples for taxonomic and imputed functional composition. Additionally, in all 189 samples, six gut health-related biomarkers were measured. Results Inter-individual variation in the gut microbiota remained stable during this short-term GFD intervention. A number of taxon-specific differences were seen during the GFD: the most striking shift was seen for the family Veillonellaceae (class Clostridia), which was significantly reduced during the intervention (p = 2.81 × 10−05). Seven other taxa also showed significant changes; the majority of them are known to play a role in starch metabolism. We saw stronger differences in pathway activities: 21 predicted pathway activity scores showed significant association to the change in diet. We observed strong relations between the predicted activity of pathways and biomarker measurements. Conclusions A GFD changes the gut microbiome composition and alters the activity of microbial pathways. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0295-y) contains supplementary material, which is available to authorized users.

Biological markers that measure gut health and diagnose functional gastro-intestinal (GI) disorders, such as irritable bowel syndrome (IBS), are lacking. The objective was to identify and validate a biomarker panel associated with the pathophysiology of IBS that discriminates IBS from healthy controls (HC) and correlates with GI symptom severity. In a case-control design, various plasma and fecal markers were measured in a cohort of 196 clinical IBS patients and 160 HC without GI symptoms. A combination of biomarkers, which best discriminates between IBS and HC was identified and validated in an independent internal validation set and by permutation testing. The correlation between the biomarker panel and GI symptom severity was tested in IBS patients and in a general population cohort of 958 subjects. A set of 8 biomarker panel was identified to discriminate IBS from HC with high sensitivity (88.1%) and specificity (86.5%). The results for the IBS subtypes were comparable. Moreover, a moderate correlation was found between the biomarker panel and GI symptom scores in the IBS (r = 0.59, p r = 0.51, p = 0.003). A novel multi-domain biomarker panel has been identified and validated, which correlated moderately to GI symptom severity in IBS and general population subjects.

Genetic risk factors often localize in non-coding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying the association of genetic risk factors with disease. More mechanistic insights can be derived from knowledge of the context, such as cell type or the activity of signaling pathways, influencing the nature and strength of eQTLs. Here, we generated peripheral blood RNA-seq data from 2,116 unrelated Dutch individuals and systematically identified these context-dependent eQTLs using a hypothesis-free strategy that does not require prior knowledge on the identity of the modifiers. Out of the 23,060 significant cis-regulated genes (false discovery rate ≤ 0.05), 2,743 genes (12%) show context-dependent eQTL effects. The majority of those were influenced by cell type composition, revealing eQTLs that are particularly strong in cell types such as CD4+ T-cells, erythrocytes, and even lowly abundant eosinophils. A set of 145 cis-eQTLs were influenced by the activity of the type I interferon signaling pathway and we identified several cis-eQTLs that are modulated by specific transcription factors that bind to the eQTL SNPs. This demonstrates that large-scale eQTL studies in unchallenged individuals can complement perturbation experiments to gain better insight in regulatory networks and their stimuli.

Purpose: There is a critical need for population-based prospective cohort studies because they follow individuals before the onset of disease, allowing for studies that can identify biomarkers and disease-modifying effects, and thereby contributing to systems epidemiology.Participants: This paper describes the design and baseline characteristics of an intensively examined subpopulation of the LifeLines cohort in the Netherlands. In this unique subcohort, LifeLines DEEP, we included 1539 participants aged 18 years and older.Findings to date: We collected additional blood (n= 1387), exhaled air (n= 1425) and faecal samples (n= 1248), and elicited responses to gastrointestinal health questionnaires (n= 1176) for analysis of the genome, epigenome, transcriptome, microbiome, metabolome and other biological levels. Here, we provide an overview of the different data layers in LifeLines DEEP and present baseline characteristics of the study population including food intake and quality of life. We also describe how the LifeLines DEEP cohort allows for the detailed investigation of genetic, genomic and metabolic variation for a wide range of phenotypic outcomes. Finally, we examine the determinants of gastrointestinal health, an area of particular interest to us that can be addressed by LifeLines DEEP.Future plans: We have established a cohort of which multiple data levels allow for the integrative analysis of populations for translation of this information into biomarkers for disease, and which will offer new insights into disease mechanisms and prevention.

Rationale: Evidence suggests that the gut microbiome is involved in the development of cardiovascular disease, with the host–microbe interaction regulating immune and metabolic pathways. However, there was no firm evidence for associations between microbiota and metabolic risk factors for cardiovascular disease from large-scale studies in humans. In particular, there was no strong evidence for association between cardiovascular disease and aberrant blood lipid levels. Objectives: To identify intestinal bacteria taxa, whose proportions correlate with body mass index and lipid levels, and to determine whether lipid variance can be explained by microbiota relative to age, sex, and host genetics. Methods and Results: We studied 893 subjects from the LifeLines-DEEP population cohort. After correcting for age and sex, we identified 34 bacterial taxa associated with body mass index and blood lipids; most are novel associations. Cross-validation analysis revealed that microbiota explain 4.5% of the variance in body mass index, 6% in triglycerides, and 4% in high-density lipoproteins, independent of age, sex, and genetic risk factors. A novel risk model, including the gut microbiome explained ≤25.9% of high-density lipoprotein variance, significantly outperforming the risk model without microbiome. Strikingly, the microbiome had little effect on low-density lipoproteins or total cholesterol. Conclusions: Our studies suggest that the gut microbiome may play an important role in the variation in body mass index and blood lipid levels, independent of age, sex, and host genetics. Our findings support the potential of therapies altering the gut microbiome to control body mass, triglycerides, and high-density lipoproteins.

There is a critical need for population-based prospective cohort studies because they follow individuals before the onset of disease, allowing for studies that can identify biomarkers and disease-modifying effects and thereby contributing to systems epidemiology. This paper describes the design and baseline characteristics of an intensively examined subpopulation of the LifeLines cohort in the Netherlands. For this unique sub-cohort, LifeLines DEEP, additional blood (n=1387), exhaled air (n=1425), fecal samples (n=1248) and gastrointestinal health questionnaires (n=1176) were collected for analysis of the genome, epigenome, transcriptome, microbiome, metabolome and other biological levels. Here, we provide an overview of the different data layers in LifeLines DEEP and present baseline characteristics of the study population including food intake and quality of life. We also describe how the LifeLines DEEP cohort allows for the detailed investigation of genetic, genomic and metabolic variation on a wealth of phenotypic outcomes. Finally, we examine the determinants of gastrointestinal health, an area of particular interest to us that can be addressed by LifeLines DEEP.

Use of dietary supplements is rising in countries where colorectal cancer is prevalent. We conducted a systematic literature review and meta-analyses of prospective cohort studies on dietary supplement use and colorectal cancer risk. We identified relevant studies in Medline, Embase and Cochrane up to January 2013. Original and peer-reviewed papers on dietary supplement use and colorectal cancer, colon cancer, or rectal cancer incidence were included. "Use-no use"(U-NU), "highest-lowest"(H-L) and "dose-response"(DR) meta-analyses were performed. Random-effects models were used to estimate summary estimates. In total, 24 papers were included in the meta-analyses. We observed inverse associations for colorectal cancer risk and multivitamin (U-NU: RR = 0.92; 95% CI: 0.87,0.97) and calcium supplements (U-NU: RR = 0.86; 95% CI: 0.79,0.95; H-L: RR = 0.80; 95% CI: 0.70,0.92; DR: for an increase of 100 mg/day, RR = 0.96; 95% CI: 0.94,0.99). Inconsistent associations were found for colon cancer risk and supplemental vitamin A and vitamin C, and for colorectal cancer risk and supplemental vitamin D, vitamin E, garlic and folic acid. Meta-analyses of observational studies suggest a beneficial role for multivitamins and calcium supplements on colorectal cancer risk, while the association with other supplements and colorectal cancer risk is inconsistent. Residual confounding of lifestyle factors might be present. Before recommendations can be made, an extensive assessment of dietary supplement use and a better understanding of underlying mechanisms is needed.

In the present longitudinal study, we followed volatile organic compounds (VOCs) excreted in exhaled breath of 20 healthy individuals over time, while adhering to a gluten-free diet for 4 weeks prior to adherence to a normal diet. We used gas chromatography coupled with mass spectrometry (TD-GC-tof-MS) in combination with chemometric analysis to detect an array of VOCs in exhaled breath. Multivariate analysis was applied to extract the maximal information from the obtained data. Dietary intake was assessed to verify adherence to the diet and to get insight into macronutrient intake during the intervention period. A set of 12 volatile compounds distinguished the samples obtained during the gluten-free diet from those obtained during a normal diet. Seven compounds could be chemically identified (2-butanol, octane, 2-propyl-1pentanol, nonanal, dihydro-4-methyl-2(3H)-furanone, nonanoic acid and dodecanal) and speculated on a possible origin. Our findings suggest that a gluten-free dietary period had a reversible impact on participants' excreted metabolites visible in their breath. Several explanations are proposed of influencing metabolic status through dietary interventions. Although the exact origin of the discriminating compounds is not yet known, the main goal of this paper was to share a new potential use of exhaled air analysis and might become a useful tool in fields of nutrition and metabolism.