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      The anxiolytic effect of probiotics: A systematic review and meta-analysis of the clinical and preclinical literature

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      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          Probiotics have generated intensive research interest in recent years as a novel mode of treatment for physical and mental illness. Nevertheless, the anxiolytic potential of probiotics remains unclear. The present systematic review and meta-analysis aimed to evaluate the clinical and preclinical (animal model) evidence regarding the effect of probiotic administration on anxiety.

          Methods

          The PubMed, PsycINFO, and Web of Science databases were reviewed for preclinical and clinical studies that met the defined inclusion and exclusion criteria. The effects of probiotics on anxiety-like behavior and symptoms of anxiety were analyzed by meta-analyses. Separate subgroup analyses were conducted on diseased versus healthy animals, specific preclinical probiotic species, and clinical versus healthy human samples.

          Results

          Data were extracted from 22 preclinical studies (743 animals) and 14 clinical studies (1527 individuals). Overall, probiotics reduced anxiety-like behavior in animals (Hedges’ g = -0.47, 95% CI -0.77 –-0.16, p = 0.004). Subgroup analyses revealed a significant reduction only among diseased animals. Probiotic species-level analyses identified only Lactobacillus ( L.) rhamnosus as an anxiolytic species, but these analyses were broadly under-powered. Probiotics did not significantly reduce symptoms of anxiety in humans (Hedges’ g = -0.12, 95% CI -0.29–0.05, p = 0.151), and did not differentially affect clinical and healthy human samples.

          Conclusions

          While preclinical (animal) studies suggest that probiotics may help reduce anxiety, such findings have not yet translated to clinical research in humans, perhaps due to the dearth of extant research with clinically anxious populations. Further investigation of probiotic treatment for clinically relevant anxiety is warranted, particularly with respect to the probiotic species L. rhamnosus.

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          Most cited references62

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          The gut-brain axis: interactions between enteric microbiota, central and enteric nervous systems

          The gut-brain axis (GBA) consists of bidirectional communication between the central and the enteric nervous system, linking emotional and cognitive centers of the brain with peripheral intestinal functions. Recent advances in research have described the importance of gut microbiota in influencing these interactions. This interaction between microbiota and GBA appears to be bidirectional, namely through signaling from gut-microbiota to brain and from brain to gut-microbiota by means of neural, endocrine, immune, and humoral links. In this review we summarize the available evidence supporting the existence of these interactions, as well as the possible pathophysiological mechanisms involved. Most of the data have been acquired using technical strategies consisting in germ-free animal models, probiotics, antibiotics, and infection studies. In clinical practice, evidence of microbiota-GBA interactions comes from the association of dysbiosis with central nervous disorders (i.e. autism, anxiety-depressive behaviors) and functional gastrointestinal disorders. In particular, irritable bowel syndrome can be considered an example of the disruption of these complex relationships, and a better understanding of these alterations might provide new targeted therapies.
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            The global burden of mental disorders: An update from the WHO World Mental Health (WMH) Surveys

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              The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses.

              Variance between studies in a meta-analysis will exist. This heterogeneity may be of clinical, methodological or statistical origin. The last of these is quantified by the I(2) -statistic. We investigated, using simulated studies, the accuracy of I(2) in the assessment of heterogeneity and the effects of heterogeneity on the predictive value of meta-analyses. The relevance of quantifying I(2) was determined according to the likely presence of heterogeneity between studies (low, high, or unknown) and the calculated I(2) (low or high). The findings were illustrated by published meta-analyses of selective digestive decontamination and weaning protocols. As expected, I(2) increases and the likelihood of drawing correct inferences from a meta-analysis decreases with increasing heterogeneity. With low levels of heterogeneity, I(2) does not appear to be predictive of the accuracy of the meta-analysis result. With high levels of heterogeneity, even meta-analyses with low I(2) -values have low predictive values. Most commonly, the level of heterogeneity in a meta-analysis will be unknown. In these scenarios, I(2) determination may help to identify estimates with low predictive values (high I(2) ). In this situation, the results of a meta-analysis will be unreliable. With low I(2) -values and unknown levels of heterogeneity, predictive values of pooled estimates may range extensively, and findings should be interpreted with caution. In conclusion, quantifying statistical heterogeneity through I(2) -statistics is only helpful when the amount of clinical heterogeneity is unknown and I(2) is high. Objective methods to quantify the levels of clinical and methodological heterogeneity are urgently needed to allow reliable determination of the accuracy of meta-analyses.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: Data curationRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 June 2018
                2018
                : 13
                : 6
                : e0199041
                Affiliations
                [001]Department of Psychology, University of Kansas, Lawrence, KS, United States of America
                McMaster University, CANADA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-7806-3819
                Article
                PONE-D-18-00739
                10.1371/journal.pone.0199041
                6010276
                29924822
                139d8ee5-8073-4440-bbef-9cdaa5f87360
                © 2018 Reis et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 January 2018
                : 30 May 2018
                Page count
                Figures: 6, Tables: 4, Pages: 25
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Microbiology
                Probiotics
                Biology and Life Sciences
                Psychology
                Emotions
                Anxiety
                Social Sciences
                Psychology
                Emotions
                Anxiety
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Rodents
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Anxiolytics
                Research and Analysis Methods
                Research Design
                Field Tests
                Biology and Life Sciences
                Behavior
                Animal Behavior
                Biology and Life Sciences
                Zoology
                Animal Behavior
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

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