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      Social anxiety disorder-associated gut microbiota increases social fear

      research-article
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      Proceedings of the National Academy of Sciences of the United States of America
      National Academy of Sciences
      microbiota-gut-brain axis, social phobia, faecal transplant, microbiome

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          Significance

          Understanding the biological basis of social anxiety disorder (SAD), one of the most disabling of the anxiety disorders, will allow for novel treatment strategies to be developed. Here, we show that gut microbiota may be such a target. Mice that received SAD patient microbiota had a specific heightened sensitivity to social fear without affecting other behaviours tested. This distinct deficit in normal social fear responses was coupled with changes in immunity and the brain.

          Abstract

          Social anxiety disorder (SAD) is a crippling psychiatric disorder characterized by intense fear or anxiety in social situations and their avoidance. However, the underlying biology of SAD is unclear and better treatments are needed. Recently, the gut microbiota has emerged as a key regulator of both brain and behaviour, especially those related to social function. Moreover, increasing data supports a role for immune function and oxytocin signalling in social responses. To investigate whether the gut microbiota plays a causal role in modulating behaviours relevant to SAD, we transplanted the microbiota from SAD patients, which was identified by 16S rRNA sequencing to be of a differential composition compared to healthy controls, to mice. Although the mice that received the SAD microbiota had normal behaviours across a battery of tests designed to assess depression and general anxiety-like behaviours, they had a specific heightened sensitivity to social fear, a model of SAD. This distinct heightened social fear response was coupled with changes in central and peripheral immune function and oxytocin expression in the bed nucleus of the stria terminalis. This work demonstrates an interkingdom basis for social fear responses and posits the microbiome as a potential therapeutic target for SAD.

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          Most cited references72

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            PUVA-induced repigmentation of vitiligo: scanning electron microscopy of hair follicles.

            PUVA-i-duced repigmentation of vitiligo was studied using both the split-dopa reaction and scanning electron microscopy. Proliferation of hypertrophic, Dopa-positive melanocytes were observed in the lower portion of some hair follicles, whereas other giant melanocytes were observed along the middle portion. The existence of a melanocyte reservoir in human hair follicles is postulated.
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              Is Open Access

              Microbiome Datasets Are Compositional: And This Is Not Optional

              Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.
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                Author and article information

                Contributors
                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                26 December 2023
                2 January 2024
                26 December 2023
                : 121
                : 1
                : e2308706120
                Affiliations
                [1] aAlimentary Pharmabiotic Centre Microbiome Ireland, University College Cork , Cork T12YT20, Ireland
                [2] bDepartment of Anatomy and Neuroscience, University College Cork , Cork T12YT20, Ireland
                [3] cDepartment of Psychiatry and Neurobehavioural Science, University College Cork , Cork T12YT20, Ireland
                [4] dSchool of Microbiology, University College Cork , Cork T12K8AF, Ireland
                [5] eDepartment of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt , Frankfurt 60528, Germany
                Author notes
                3To whom correspondence may be addressed. Email: J.Cryan@ 123456ucc.ie .

                Edited by Tomas Hökfelt, Karolinska Institutet, Stockholm, Sweden; received May 29, 2023; accepted October 5, 2023

                1M.B., M.I.B., and C.S.M.C. contributed equally to this work.

                2Present address: School of Psychology, University of New South Wales, Sydney 2052, Australia.

                Author information
                https://orcid.org/0000-0002-7367-292X
                https://orcid.org/0000-0003-2991-8192
                https://orcid.org/0000-0002-2959-1380
                https://orcid.org/0000-0001-6891-734X
                https://orcid.org/0009-0008-8558-6640
                https://orcid.org/0000-0001-8908-608X
                https://orcid.org/0000-0002-5563-5607
                https://orcid.org/0000-0001-5806-251X
                https://orcid.org/0000-0002-3672-1390
                https://orcid.org/0000-0001-8753-5005
                https://orcid.org/0000-0002-2316-7220
                https://orcid.org/0000-0001-5887-2723
                Article
                202308706
                10.1073/pnas.2308706120
                10769841
                38147649
                a02ec2a8-7763-417f-9133-20181eb7d53f
                Copyright © 2023 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 29 May 2023
                : 05 October 2023
                Page count
                Pages: 9, Words: 6715
                Funding
                Funded by: Science Foundation Ireland (SFI), FundRef 501100001602;
                Award ID: 12/RC/2273_P2
                Award Recipient : Nathaniel L Ritz Award Recipient : Marta Brocka Award Recipient : Mary I Butler Award Recipient : Caitlin Sien Ming Cowan Award Recipient : Camila Barrera-Bugueño Award Recipient : Christopher JR Turkington Award Recipient : Lorraine A Draper Award Recipient : Thomaz FS Bastiaanssen Award Recipient : Valentine Turpin Award Recipient : Lorena Morales Award Recipient : David Campos Award Recipient : Cassandra E Gheorghe Award Recipient : Anna Ratsika Award Recipient : Virat Sharma Award Recipient : Anna V Golubeva Award Recipient : Maria Rodriguez Aburto Award Recipient : Andrey N Shkoporov Award Recipient : Gerard Moloney Award Recipient : Colin Hill Award Recipient : Gerard Clarke Award Recipient : David A Slattery Award Recipient : Timothy G. Dinan Award Recipient : John F. Cryan
                Funded by: EC | European Research Council (ERC), FundRef 501100000781;
                Award ID: 220646/Z/20/Z
                Award Recipient : Andrey N Shkoporov
                Categories
                dataset, Dataset
                research-article, Research Article
                neuro, Neuroscience
                424
                Biological Sciences
                Neuroscience

                microbiota-gut-brain axis,social phobia,faecal transplant,microbiome

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