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      Differences in gut microbial composition correlate with regional brain volumes in irritable bowel syndrome

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          Abstract

          Background

          Preclinical and clinical evidence supports the concept of bidirectional brain-gut microbiome interactions. We aimed to determine if subgroups of irritable bowel syndrome (IBS) subjects can be identified based on differences in gut microbial composition, and if there are correlations between gut microbial measures and structural brain signatures in IBS.

          Methods

          Behavioral measures, stool samples, and structural brain images were collected from 29 adult IBS and 23 healthy control subjects (HCs). 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities, and various multivariate analysis approaches were used to quantitate microbial composition, abundance, and diversity. The metagenomic content of samples was inferred from 16S rRNA gene sequence data using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). T1-weighted brain images were acquired on a Siemens Allegra 3T scanner, and morphological measures were computed for 165 brain regions.

          Results

          Using unweighted Unifrac distances with hierarchical clustering on microbial data, samples were clustered into two IBS subgroups within the IBS population (IBS1 ( n = 13) and HC-like IBS ( n = 16)) and HCs ( n = 23) (AUROC = 0.96, sensitivity 0.95, specificity 0.67). A Random Forest classifier provided further support for the differentiation of IBS1 and HC groups. Microbes belonging to the genera Faecalibacterium, Blautia, and Bacteroides contributed to this subclassification. Clinical features distinguishing the groups included a history of early life trauma and duration of symptoms (greater in IBS1), but not self-reported bowel habits, anxiety, depression, or medication use. Gut microbial composition correlated with structural measures of brain regions including sensory- and salience-related regions, and with a history of early life trauma.

          Conclusions

          The results confirm previous reports of gut microbiome-based IBS subgroups and identify for the first time brain structural alterations associated with these subgroups. They provide preliminary evidence for the involvement of specific microbes and their predicted metabolites in these correlations.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40168-017-0260-z) contains supplementary material, which is available to authorized users.

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          Most cited references 37

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          Early life stress alters behavior, immunity, and microbiota in rats: implications for irritable bowel syndrome and psychiatric illnesses.

          Adverse early life events are associated with a maladaptive stress response system and might increase the vulnerability to disease in later life. Several disorders have been associated with early life stress, ranging from depression to irritable bowel syndrome. This makes the identification of the neurobiological substrates that are affected by adverse experiences in early life invaluable. The purpose of this study was to assess the effect of early life stress on the brain-gut axis. Male rat pups were stressed by separating them from their mothers for 3 hours daily between postnatal days 2-12. The control group was left undisturbed with their mothers. Behavior, immune response, stress sensitivity, visceral sensation, and fecal microbiota were analyzed. The early life stress increased the number of fecal boli in response to a novel stress. Plasma corticosterone was increased in the maternally separated animals. An increase in the systemic immune response was noted in the stressed animals after an in vitro lipopolysaccharide challenge. Increased visceral sensation was seen in the stressed group. There was an alteration of the fecal microbiota when compared with the control group. These results show that this form of early life stress results in an altered brain-gut axis and is therefore an important model for investigating potential mechanistic insights into stress-related disorders including depression and IBS.
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            The PHQ-15: validity of a new measure for evaluating the severity of somatic symptoms.

            Somatization is prevalent in primary care and is associated with substantial functional impairment and healthcare utilization. However, instruments for identifying and monitoring somatic symptoms are few in number and not widely used. Therefore, we examined the validity of a brief measure of the severity of somatic symptoms. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-15 comprises 15 somatic symptoms from the PHQ, each symptom scored from 0 ("not bothered at all") to 2 ("bothered a lot"). The PHQ-15 was administered to 6000 patients in eight general internal medicine and family practice clinics and seven obstetrics-gynecology clinics. Outcomes included functional status as assessed by the 20-item Short-Form General Health Survey (SF-20), self-reported sick days and clinic visits, and symptom-related difficulty. As PHQ-15 somatic symptom severity increased, there was a substantial stepwise decrement in functional status on all six SF-20 subscales. Also, symptom-related difficulty, sick days, and healthcare utilization increased. PHQ-15 scores of 5, 10, 15, represented cutoff points for low, medium, and high somatic symptom severity, respectively. Somatic and depressive symptom severity had differential effects on outcomes. Results were similar in the primary care and obstetrics-gynecology samples. The PHQ-15 is a brief, self-administered questionnaire that may be useful in screening for somatization and in monitoring somatic symptom severity in clinical practice and research.
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              Advancing our understanding of the human microbiome using QIIME.

              High-throughput DNA sequencing technologies, coupled with advanced bioinformatics tools, have enabled rapid advances in microbial ecology and our understanding of the human microbiome. QIIME (Quantitative Insights Into Microbial Ecology) is an open-source bioinformatics software package designed for microbial community analysis based on DNA sequence data, which provides a single analysis framework for analysis of raw sequence data through publication-quality statistical analyses and interactive visualizations. In this chapter, we demonstrate the use of the QIIME pipeline to analyze microbial communities obtained from several sites on the bodies of transgenic and wild-type mice, as assessed using 16S rRNA gene sequences generated on the Illumina MiSeq platform. We present our recommended pipeline for performing microbial community analysis and provide guidelines for making critical choices in the process. We present examples of some of the types of analyses that are enabled by QIIME and discuss how other tools, such as phyloseq and R, can be applied to expand upon these analyses. © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                jlabus@ucla.edu
                holliste@bcm.edu
                JJacobs@mednet.ucla.edu
                KKIRBACH@dom.wustl.edu
                Numan.Oezguen@bcm.edu
                agupta@mednet.ucla.edu
                jracosta79@ucla.edu
                raluna@bcm.edu
                aagaardt@bcm.edu
                jamesv@bcm.edu
                Tor.Savidge@bcm.edu
                ehsiao@ucla.edu
                ktillisch@mednet.ucla.edu
                emayer@ucla.edu
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                1 May 2017
                1 May 2017
                2017
                : 5
                Affiliations
                [1 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Division of Digestive Diseases, , David Geffen School at UCLA, ; Los Angeles, CA 90095 USA
                [2 ]ISNI 0000 0001 2200 2638, GRID grid.416975.8, Texas Children’s Microbiome Center, Department of Pathology, , Texas Children’s Hospital, ; 1102 Bates Ave., Houston, TX USA
                [3 ]ISNI 0000 0001 2160 926X, GRID grid.39382.33, Department of Pathology & Immunology, , Baylor College of Medicine, ; One Baylor Plaza, Houston, TX USA
                [4 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Center for Human Nutrition, , Washington University School of Medicine, ; St. Louis, MO 63110 USA
                [5 ]Oppenheimer Center for Neurobiology of Stress and Resilience, CHS 42-210 MC737818 10833 Le Conte Avenue, Los Angeles, CA 90095-7378 USA
                Article
                260
                10.1186/s40168-017-0260-z
                5410709
                28457228
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: P50 DK064539
                Award ID: R01 DK048351
                Funded by: FundRef http://dx.doi.org/10.13039/100000064, National Center for Complementary and Alternative Medicine;
                Award ID: R01 AT007137
                Award Recipient :
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                Research
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                © The Author(s) 2017

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