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      Associations between gut microbiota and Alzheimer’s disease, major depressive disorder, and schizophrenia

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          Abstract

          Background

          Growing evidence has shown that alterations in the gut microbiota composition were associated with a variety of neuropsychiatric conditions. However, whether such associations reflect causality remains unknown. We aimed to reveal the causal relationships among gut microbiota, metabolites, and neuropsychiatric disorders including Alzheimer’s disease (AD), major depressive disorder (MDD), and schizophrenia (SCZ).

          Methods

          A two-sample bi-directional Mendelian randomization analysis was performed by using genetic variants from genome-wide association studies as instrumental variables for gut microbiota, metabolites, AD, MDD, and SCZ, respectively.

          Results

          We found suggestive associations of host-genetic-driven increase in Blautia (OR, 0.88; 95%CI, 0.79–0.99; P = 0.028) and elevated γ-aminobutyric acid (GABA) (0.96; 0.92–1.00; P = 0.034), a downstream product of Blautia-dependent arginine metabolism, with a lower risk of AD. Genetically increased Enterobacteriaceae family and Enterobacteriales order were potentially associated with a higher risk of SCZ (1.09; 1.00–1.18; P = 0.048), while Gammaproteobacteria class (0.90; 0.83–0.98; P = 0.011) was related to a lower risk for SCZ. Gut production of serotonin was potentially associated with an increased risk of SCZ (1.07; 1.00–1.15; P = 0.047). Furthermore, genetically increased Bacilli class was related to a higher risk of MDD (1.07; 1.02–1.12; P = 0.010). In the other direction, neuropsychiatric disorders altered gut microbiota composition.

          Conclusions

          These data for the first time provide evidence of potential causal links between gut microbiome and AD, MDD, and SCZ. GABA and serotonin may play an important role in gut microbiota-host crosstalk in AD and SCZ, respectively. Further investigations in understanding the underlying mechanisms of associations between gut microbiota and AD, MDD, and SCZ are required.

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          Most cited references59

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          Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

          ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
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            Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease.

            Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
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              Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

              Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association (GWA) meta-analysis based in 135,458 cases and 344,901 control, We identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression, and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relations of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine and define the basis of major depression and imply a continuous measure of risk underlies the clinical phenotype.
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                Author and article information

                Contributors
                lqi1@tulane.edu
                huangtaotao@pku.edu.cn
                Journal
                J Neuroinflammation
                Journal of Neuroinflammation
                BioMed Central (London )
                1742-2094
                2 October 2020
                2 October 2020
                2020
                : 17
                : 288
                Affiliations
                [1 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Department of Epidemiology & Biostatistics, School of Public Health, , Peking University, ; 38 Xueyuan Road, Beijing, 100191 China
                [2 ]GRID grid.265219.b, ISNI 0000 0001 2217 8588, Department of Epidemiology, School of Public Health and Tropical Medicine, , Tulane University, ; New Orleans, LA USA
                [3 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Nutrition, , Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [4 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Department of Global Health, School of Public Health, , Peking University, ; Beijing, 100191 China
                [5 ]GRID grid.419897.a, ISNI 0000 0004 0369 313X, Key Laboratory of Molecular Cardiovascular Sciences (Peking University), , Ministry of Education, ; Beijing, 100191 China
                [6 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Center for Intelligent Public Health, Institute for Artificial Intelligence, , Peking University, ; Beijing, 100191 China
                Author information
                http://orcid.org/0000-0002-0328-1368
                Article
                1961
                10.1186/s12974-020-01961-8
                7532639
                33008395
                8c5a13fc-e107-4fa3-9b57-c9170dc08686
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 2 July 2020
                : 23 September 2020
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Neurosciences
                gut microbiota,neuropsychiatric disorder,mendelian randomization,genetic association,causality

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