Human intestinal microbiota plays a number of important roles in human health and is also implicated in several gastrointestinal disorders. Though the diversity of human gut microbiota in adults and in young children has been examined, few reports of microbiota composition are available for adolescents. In this work we used Microbiota Array for high-throughput analysis of distal gut microbiota in adolescent children 11-18 years of age. Samples obtained from healthy adults were used for comparison. Adolescent and adult groups could be separated in principal components analysis space based on the relative species abundance of their distal gut microbiota. All samples were dominated by class Clostridia. A core microbiome of 46 species that were detected in all examined samples was established; members of genera Ruminococcus, Faecalibacterium, and Roseburia were well presented among core species. Comparison of intestinal microbiota composition between adolescents and adults revealed a statistically significantly higher abundance of genera Bifidobacterium and Clostridium among adolescent samples. The number of detected species was similar between sample groups indicating that it was relative abundances of the genera and not the presence or absence of a specific genus that differentiated adolescent and adult samples. In summary, contrary to the current belief, this study suggests that the gut microbiome of adolescent children is different from that of adults.

WELLENS, RITA I, ALEX F ROCHE, HARRY J KHAMIS, ANDREW S JACKSON, MICHAEL L POLLOCK AND ROGER M SIERVOGEL.Relationships between the body mass index and body composition. Obes Res. 1996;4:35-44. The aims of this study were to evaluate the Body Mass Index (BMI) (welght/stature-i) as a proxy for percent body fat (%BF) and to determine its association with fat-free mass (FFM). Multivariate analysis of variance and partial correlations were used to examine relationships between BMI and %BF and FFM from densitometry for 504 men and 511 women, aged 20 to 45 years. Sensitivity/specificity analyses used cut offs of 28 kg/m 2 in men and 26 kglm 2 in women for BMI, and 25% in men and 33% in women for %BF. Significantly higher associations existed in each gender between BMI and %BF in the upper BMI tertile than in the lower BMI tertiles. In the lower BMI tertiles, correlations between BMI and FFM were approximately twice as large as those between BMI and %BF. The BMI correctly identified about 44% of obese men, and 52% of obese women when obesity was determined from %BF. BMI is an uncertain diagnostic index of obesity. Results of Receiver Operator Characteristic (ROC) analyses using %BF and total body fat, both provided a BMI of 25 kg/m 2 in men and 23 kg/m 2 in women as diagnostic screening cut offs for obesity.

Although at the higher taxonomical level gut microbiota was similar between healthy and IBS-D children, specific differences in the abundances of several bacterial genera were revealed. Core microbiome in children was dominated by Clostridia. Putative relationships identified among microbial genera provide testable hypotheses of cross-species associations among members of human gut microbiota

Very often, as a part of the general analyses of a set of data, a researcher wishes to determine the strength of the relationship between two variables using a single coefficient or measure of associationnamely, a number (often between -1 and +1 or between 0 and 1) that is used as a measure of how strongly the two variables are related. In such instances, it is important that the appropriate measure is used to assess the strength of the relationship. If an inappropriate measure is used, then the resulting value is meaningless, and misleading results may be concluded. For example, the commonly used Pearson correlation coefficient is not necessarily the correct measure of association in every instance. To decide on the appropriate measure of

The goal of this study was to determine if fecal metabolite and microbiota profiles can serve as biomarkers of human intestinal diseases, and to uncover possible gut microbe-metabolite associations. We employed proton nuclear magnetic resonance to measure fecal metabolites of healthy children and those diagnosed with diarrhea-predominant irritable bowel syndrome (IBS-D). Metabolite levels were associated with fecal microbial abundances. Using several ordination techniques, healthy and irritable bowel syndrome (IBS) samples could be distinguished based on the metabolite profiles of fecal samples, and such partitioning was congruent with the microbiota-based sample separation. Measurements of individual metabolites indicated that the intestinal environment in IBS-D was characterized by increased proteolysis, incomplete anaerobic fermentation and possible change in methane production. By correlating metabolite levels with abundances of microbial genera, a number of statistically significant metabolite-genus associations were detected in stools of healthy children. No such associations were evident for IBS children. This finding complemented the previously observed reduction in the number of microbe-microbe associations in the distal gut of the same cohort of IBS-D children.