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 < 0.001) and the general population cohorts (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.

“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 Two large-scale studies in Western Europe establish environment-diet-microbe-host interactions. 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.

depletion alters gastrointestinal and anxiety symptoms in irritable bowel syndrome. Am J Gastroenterol 2006; 101: 2582–7. 8. Labus JS, Mayer EA, Jarcho J, et al. Acute tryptophan depletion alters the effective connectivity of emotional arousal circuitry during visceral stimuli in healthy women. Gut 2011; 60: 1196–203. 9. Spiller R. Serotonin and GI clinical disorders. Neuropharmacology 2008; 55: 1072–80. 10. Thijssen AY, Mujagic Z, Jonkers DM, et al. Alterations in serotonin metabolism in the irritable bowel syndrome. Aliment Pharmacol Ther 2016; 43: 272–82. 11. Fitzgerald P, Cassidy Eugene M, Clarke G, et al. Tryptophan catabolism in females with irritable bowel syndrome: relationship to interferon-gamma, severity of symptoms and psychiatric co-morbidity. Neurogastroenterol Motil 2008; 20: 1291–7. 12. Drossman DA, Morris CB, Hu Y, et al. A prospective assessment of bowel habit in irritable bowel syndrome in women: defining an alternator. Gastroenterology 2005; 128: 580–9.

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.

The search for biomarkers that characterize specific aspects of inflammatory bowel disease (IBD), has received substantial interest in the past years and is moving forward rapidly with the help of modern technologies. Nevertheless, there is a direct demand to identify adequate biomarkers for predicting and evaluating therapeutic response to different therapies. In this subset, pharmacogenetics deserves more attention as part of the endeavor to provide personalized medicine. The ultimate goal in this area is the adjustment of medication for a patient's specific genetic background and thereby to improve drug efficacy and safety rates. The aim of the following review is to utilize the latest knowledge on immunopathogenesis of IBD and update the findings on the field of Immunology and Genetics, to evaluate the response to the different therapies. In the present article, more than 400 publications were reviewed but finally 287 included based on design, reproducibility (or expectancy to be reproducible and translationable into humans) or already measured in humans. A few tests have shown clinical applicability. Other, i.e., genetic associations for the different therapies in IBD have not yet shown consistent or robust results. In the close future it is anticipated that this, cellular and genetic material, as well as the determination of biomarkers will be implemented in an integrated molecular diagnostic and prognostic approach to manage IBD patients.

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.

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.