Background & Aims Gastrointestinal (GI) diseases account for substantial morbidity, mortality and cost. Statistical analyses of the most recent data are necessary to guide GI research, education and clinical practice. We estimate the burden of GI disease in the US. Methods We collected information on the epidemiology of GI diseases (including cancers) and symptoms, along with data on resource utilization, quality of life, impairments to work and activity, morbidity, and mortality. These data were obtained from the National Ambulatory Medical Care Survey; National Health and Wellness Survey; Nationwide Inpatient Sample; Surveillance, Epidemiology, and End Results Program; National Vital Statistics System; Thompson Reuters MarketScan®; Medicare; Medicaid; and the Clinical Outcomes Research Initiative’s National Endoscopic Database. We estimated endoscopic use and costs and examined trends in endoscopic procedure. Results Abdominal pain was the most common gastrointestinal symptom that prompted a clinic visit (15.9 million visits). Gastroesophageal reflux was the most common GI diagnosis (8.9 million visits). Hospitalizations and mortality from Clostridium difficile infection have doubled in the last 10 years. Acute pancreatitis was the most common reason for hospitalization (274,119 discharges). Colorectal cancer accounted for more than half of all GI cancers and was the leading cause of GI-related mortality (52,394 deaths). There were 6.9 million upper, 11.5 million lower, and 228,000 biliary endoscopies performed in 2009. The total cost for outpatient gastrointestinal endoscopy examinations was $32.4 billion. Conclusions GI diseases are a source of substantial morbidity, mortality and cost in the US.

Among patients who had IBS without constipation, treatment with rifaximin for 2 weeks provided significant relief of IBS symptoms, bloating, abdominal pain, and loose or watery stools. (Funded by Salix Pharmaceuticals; ClinicalTrials.gov numbers, NCT00731679 and NCT00724126.).

Indigenous microbiota are an essential component in the modern concept of human health, but the composition and functional characteristics of a healthy microbiome remain to be precisely defined. Patterns of microbial colonization associated with disease states have been documented, but the health-associated microbial patterns and their functional characteristics are less clear. A healthy microbiome, considered in the context of body habitat or body site, could be described in terms of ecologic stability (i.e., ability to resist community structure change under stress or to rapidly return to baseline following a stress-related change), by an idealized (presumably health-associated) composition or by a desirable functional profile (including metabolic and trophic provisions to the host). Elucidation of the properties of healthy microbiota would provide a target for dietary interventions and/or microbial modifications aimed at sustaining health in generally healthy populations and improving the health of individuals exhibiting disrupted microbiota and associated diseases.

In November 2008, a group of scientists met at the 6th Meeting of the International Scientific Association of Probiotics and Prebiotics (ISAPP) in London, Ontario, Canada, to discuss the functionality of prebiotics. As a result of this, it was concluded that the prebiotic field is currently dominated by gastrointestinal events. However, in the future, it may be the case that other mixed microbial ecosystems may be modulated by a prebiotic approach, such as the oral cavity, skin and the urogenital tract. Therefore, a decision was taken to build upon the current prebiotic status and define a niche for 'dietary prebiotics'. This review is co-authored by the working group of ISAPP scientists and sets the background for defining a dietary prebiotic as ''a selectively fermented ingredient that results in specific changes in the composition and/or activity of the gastrointestinal microbiota, thus conferring benefit(s) upon host health''.

High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Distance-based analysis is a popular strategy for evaluating the overall association between microbiome diversity and outcome, wherein the phylogenetic distance between individuals' microbiome profiles is computed and tested for association via permutation. Despite their practical popularity, distance-based approaches suffer from important challenges, especially in selecting the best distance and extending the methods to alternative outcomes, such as survival outcomes. We propose the microbiome regression-based kernel association test (MiRKAT), which directly regresses the outcome on the microbiome profiles via the semi-parametric kernel machine regression framework. MiRKAT allows for easy covariate adjustment and extension to alternative outcomes while non-parametrically modeling the microbiome through a kernel that incorporates phylogenetic distance. It uses a variance-component score statistic to test for the association with analytical p value calculation. The model also allows simultaneous examination of multiple distances, alleviating the problem of choosing the best distance. Our simulations demonstrated that MiRKAT provides correctly controlled type I error and adequate power in detecting overall association. "Optimal" MiRKAT, which considers multiple candidate distances, is robust in that it suffers from little power loss in comparison to when the best distance is used and can achieve tremendous power gain in comparison to when a poor distance is chosen. Finally, we applied MiRKAT to real microbiome datasets to show that microbial communities are associated with smoking and with fecal protease levels after confounders are controlled for.