A Meta-analysis of Gut Microbiota in Children with Autism

Abstract

Previous studies have reported dysbiosis in the gut microbiota (GM) of children with autism spectrum disorders (ASD), which may be a determining factor on child development through the microbiota-gut-brain axis. However, it is not clear if there is a specific group of dysbiotic bacteria in ASD. The aim of this study was to carry out a meta-analysis on the studies that analyze GM in children with ASD. 18 studies fulfilled our selection criteria. Our results showed a lower relative abundance of Streptococcus (SMD+ = − 0.999; 95% CI − 1.549, − 0.449) and Bifidobacterium genera (SMD+ = − 0.513; 95% CI − 0.953, − 0.073) in children with ASD. Overall, the Bifidobacterium genera is involved. However, differences found between studies are attributed to factors such as reporting bias.

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References

  1. Adams, J. B., Johansen, L. J., Powell, L. D., Quig, D., & Rubin, R. A. (2011). Gastrointestinal flora and gastrointestinal status in children with autism—Comparisons to typical children and correlation with autism severity. BMC Gastroenterology, 11(22), 1–13. https://doi.org/10.1186/1471-230x-11-22.

    Article  Google Scholar 

  2. Andreo-Martínez, P., García-Martínez, N., Sánchez-Samper, E. P., & Martínez-González, A. E. (2019). An approach to gut microbiota profile in children with autism spectrum disorder. Environmental Microbiology Reports, 12(2), 115–135. https://doi.org/10.1111/1758-2229.12810.

    Article  PubMed  Google Scholar 

  3. APA. (2013). American Psychiatric Association. Autism spectrum disorder. In Diagnostic and statistical manual of mental disorders, 5 Eds (DSM-5). American Psychiatric Publishing.

  4. Baj, J., Sitarz, E., Forma, A., Wróblewska, K., & Karakuła-Juchnowicz, H. (2020). Alterations in the nervous system and gut microbiota after β-hemolytic Streptococcus group A infection—Characteristics and diagnostic criteria of PANDAS recognition. International Journal of Molecular Sciences, 21(4), 1476. https://doi.org/10.3390/ijms21041476.

    Article  PubMed Central  Google Scholar 

  5. Bonnet-Brilhault, F., Rajerison, T. A., Paillet, C., Guimard-Brunault, M., Saby, A., Ponson, L., Tripi, G., Malvy, J., & Roux, S. (2018). Autism is a prenatal disorder: Evidence from late gestation brain overgrowth. Autism Research, 11(12), 1635–1642. https://doi.org/10.1002/aur.2036.

    Article  PubMed  Google Scholar 

  6. Borenstein, M. (2019). Common mistakes in meta-analysis and how to avoid them. Englewood, NJ: Biostat Inc.

  7. Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley.

    Book  Google Scholar 

  8. Bridgemohan, C., Cochran, D. M., Howe, Y. J., Pawlowski, K., Zimmerman, A. W., Anderson, G. M., Choueiri, R., Sices, L., Miller, K. J., Ultmann, M., & Helt, J. (2019). Investigating potential biomarkers in autism spectrum disorder. Frontiers in Integrative Neuroscience, 13, 31. https://doi.org/10.3389/fnint.2019.00031.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). 12 Lawrence Erlbaum Associates Inc.

    Google Scholar 

  10. Cooper, H., Hedges, L. V., & Valentine, J. C. (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.

    Book  Google Scholar 

  11. Coretti, L., Paparo, L., Riccio, M. P., Amato, F., Cuomo, M., Natale, A., Borrelli, L., Corrado, G., De Caro, C., Comegna, M., & Buommino, E. (2018). Gut microbiota features in young children with autism spectrum disorders. Frontiers in Microbiology, 9, 3146. https://doi.org/10.3389/fmicb.2018.03146.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Da Silva, H. D., & Winkelströter, L. K. (2019). Universal gestational screening for Streptococcus agalactiae colonization and neonatal infection—A systematic review and meta-analysis. Journal of Infection and Public Health, 12(4), 479–481. https://doi.org/10.1016/j.jiph.2019.03.004.

    Article  PubMed  Google Scholar 

  13. Dall’Aglio, L., Muka, T., Cecil, C. A. M., Bramer, W. M., Verbiest, M., Nano, J., Hidalgo, A. C., Franco, O. H., & Tiemeier, H. (2018). The role of epigenetic modifications in neurodevelopmental disorders: A systematic review. Neuroscience & Biobehavioral Reviews, 94, 17–30. https://doi.org/10.1016/j.neubiorev.2018.07.011.

    Article  Google Scholar 

  14. De Angelis, M., Piccolo, M., Vannini, L., Siragusa, S., De Giacomo, A., Serrazzanetti, D. I., Cristofori, F., Guerzoni, M. E., Gobbetti, M., & Francavilla, R. (2013). Fecal microbiota and metabolome of children with autism and pervasive developmental disorder not otherwise specified. PloS One, 8(10), e76993. https://doi.org/10.1371/journal.pone.0076993.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Diaz Heijtz, R. (2016). Fetal, neonatal, and infant microbiome: Perturbations and subsequent effects on brain development and behavior. Seminars in Fetal and Neonatal Medicine, 21(6), 410–417. https://doi.org/10.1016/j.siny.2016.04.012.

    Article  PubMed  Google Scholar 

  16. Ding, H. T., Taur, Y., & Walkup, J. T. (2017). Gut microbiota and autism: Key concepts and findings. Journal of Autism and Developmental Disorders, 47(2), 480–489. https://doi.org/10.1007/s10803-016-2960-9.

    Article  PubMed  Google Scholar 

  17. Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455–463. https://doi.org/10.1111/j.0006-341x.2000.00455.x.

    Article  Google Scholar 

  18. Finegold, S. M., Dowd, S. E., Gontcharova, V., Liu, C., Henley, K. E., Wolcott, R. D., Youn, E., Summanen, P. H., Granpeesheh, D., Dixon, D., & Liu, M. (2010). Pyrosequencing study of fecal microflora of autistic and control children. Anaerobe, 16(4), 444–453. https://doi.org/10.1016/j.anaerobe.2010.06.008.

    Article  PubMed  Google Scholar 

  19. Finegold, S. M., Summanen, P. H., Downes, J., Corbett, K., & Komoriya, T. (2017). Detection of Clostridium perfringens toxin genes in the gut microbiota of autistic children. Anaerobe, 45, 133–137. https://doi.org/10.1016/j.anaerobe.2017.02.008.

    Article  PubMed  Google Scholar 

  20. Haas, K. N., & Blanchard, J. L. (2017). Kineothrix alysoides, gen. nov., sp. nov., a saccharolytic butyrate-producer within the family Lachnospiraceae. International Journal of Systematic and Evolutionary Microbiology, 67(2), 402–410. https://doi.org/10.1099/ijsem.0.001643.

    Article  PubMed  Google Scholar 

  21. Hartung, J. (1999). An Alternative method for meta-analysis. Biometrical Journal, 41(8), 901–916. https://doi.org/10.1002/(sici)1521-4036(199912)41:8%3c901::aid-bimj901%3e3.0.co;2-w.

    Article  Google Scholar 

  22. Hedges, L., & Olkin, I. (1985). Statistical methods for meta-analysis. Academic Press.

    Google Scholar 

  23. Herd, P., Palloni, A., Rey, F., & Dowd, J. B. (2018). Social and population health science approaches to understand the human microbiome. Nature Human Behaviour, 2(11), 808–815. https://doi.org/10.1038/s41562-018-0452-y.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Heuer, L. S., Croen, L. A., Jones, K. L., Yoshida, C. K., Hansen, R. L., Yolken, R., Zerbo, O., DeLorenze, G., Kharrazi, M., Ashwood, P., & Van de Water, J. (2019). An exploratory examination of neonatal cytokines and chemokines as predictors of autism risk: The early markers for autism study. Biological Psychiatry, 86(4), 255–264. https://doi.org/10.1016/j.biopsych.2019.04.037.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Huedo-Medina, T. B., Sanchez-Meca, J., Marin-Martinez, F., & Botella, J. (2006). Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychological Methods, 11(2), 193–206. https://doi.org/10.1037/1082-989x.11.2.193.

    Article  PubMed  Google Scholar 

  26. Iglesias-Vázquez, L., van Ginkel Riba, G., Arija, V., & Canals, J. (2020). Composition of gut microbiota in children with autism spectrum disorder: A systematic review and meta-analysis. Nutrients, 12, 792. https://doi.org/10.3390/nu12030792.

    Article  PubMed Central  Google Scholar 

  27. Inoue, R., Sakaue, Y., Sawai, C., Sawai, T., Ozeki, M., Romero-Perez, G. A., & Tsukahara, T. (2016). A preliminary investigation on the relationship between gut microbiota and gene expressions in peripheral mononuclear cells of infants with autism spectrum disorders. Bioscience, Biotechnology, and Biochemistry, 80(12), 2450–2458. https://doi.org/10.1080/09168451.2016.1222267.

    Article  PubMed  Google Scholar 

  28. Iovene, M. R., Bombace, F., Maresca, R., Sapone, A., Iardino, P., Picardi, A., Marotta, R., Schiraldi, C., Siniscalco, D., Serra, N., & de Magistris, L. (2017). Intestinal dysbiosis and yeast isolation in stool of subjects with autism spectrum disorders. Mycopathologia, 182(3–4), 349–363. https://doi.org/10.1007/s11046-016-0068-6.

    Article  PubMed  Google Scholar 

  29. Jiang, H. Y., Zhang, X., Yu, Z. H., Zhang, Z., Deng, M., Zhao, J. H., & Ruan, B. (2018). Altered gut microbiota profile in patients with generalized anxiety disorder. Journal of Psychiatric Research, 104, 130–136. https://doi.org/10.1016/j.jpsychires.2018.07.007.

    Article  PubMed  Google Scholar 

  30. Kang, D. W., Park, J. G., Ilhan, Z. E., Wallstrom, G., Labaer, J., Adams, J. B., & Krajmalnik-Brown, R. (2013). Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children. PloS One, 8(7), e68322. https://doi.org/10.1371/journal.pone.0068322.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Kang, D.-W., Ilhan, Z. E., Isern, N. G., Hoyt, D. W., Howsmon, D. P., Shaffer, M., Lozupone, C. A., Hahn, J., Adams, J. B., & Krajmalnik-Brown, R. (2018). Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders. Anaerobe, 49, 121–131. https://doi.org/10.1016/j.anaerobe.2017.12.007.

    Article  PubMed  Google Scholar 

  32. Knapp, G., & Hartung, J. (2003). Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine, 22, 2693–2710. https://doi.org/10.1002/sim.1482.

    Article  PubMed  Google Scholar 

  33. Krajmalnik-Brown, R., Lozupone, C., Kang, D.-W., & Adams, J. B. (2015). Gut bacteria in children with autism spectrum disorders: Challenges and promise of studying how a complex community influences a complex disease. Microbial Ecology in Health and Disease, 26, 26914. https://doi.org/10.3402/mehd.v26.26914.

    Article  PubMed  Google Scholar 

  34. Kumar, H., Lund, R., Laiho, A., Lundelin, K., Ley, R. E., Isolauri, E., & Salminen, S. (2014). Gut microbiota as an epigenetic regulator: Pilot study based on whole-genome methylation analysis. MBio, 5(6), e02113–e02114. https://doi.org/10.1128/mBio.02113-14.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lopez-Lopez, J. A., Marin-Martinez, F., Sanchez-Meca, J., Van den Noortgate, W., & Viechtbauer, W. (2014). Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study. The British Journal of Mathematical and Statistical Psychology, 67(1), 30–48. https://doi.org/10.1111/bmsp.12002.

    Article  PubMed  Google Scholar 

  36. Ma, B., Liang, J., Dai, M., Wang, J., Luo, J., Zhang, Z., & Jing, J. (2019). Altered gut microbiota in Chinese children with autism spectrum disorders. Frontiers in Cellular and Infection Microbiology, 9, 40–40. https://doi.org/10.3389/fcimb.2019.00040.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Martínez-González, A. E., & Andreo-Martínez, P. (2019). The role of gut microbiota in gastrointestinal symptoms of children with ASD. Medicina, 55(8), 408. https://doi.org/10.3390/medicina55080408.

    Article  PubMed Central  Google Scholar 

  38. Martínez-González, A. E., & Andreo-Martínez, P. (2020a). Prebiotics, probiotics and fecal microbiota transplantation in autism: A systematic review. Revista de Psiquiatría y Salud Mental, 13(3), 150–164. https://doi.org/10.1016/j.rpsm.2020.06.002.

    Article  PubMed  Google Scholar 

  39. Martínez-González, A. E., & Andreo-Martínez, P. (2020b). Una propuesta de probiótico basada en el bifidobacterium para el autismo. Revista Archivos Latinoamericanos de Nutrición, 70(4).

  40. Mayer, E. A., Labus, J., Aziz, Q., Tracey, I., Kilpatrick, L., Elsenbruch, S., Schweinhardt, P., Van Oudenhove, L., & Borsook, D. (2019). Role of brain imaging in disorders of brain–gut interaction: A Rome Working Team Report. Gut, 68(9), 1701–1715. https://doi.org/10.1136/gutjnl-2019-318308%JGut.

    Article  PubMed  PubMed Central  Google Scholar 

  41. McElhanon, B. O., McCracken, C., Karpen, S., & Sharp, W. G. (2014). Gastrointestinal symptoms in autism spectrum disorder: A meta-analysis. Pediatrics, 133(5), 872–883. https://doi.org/10.1542/peds.2013-3995.

    Article  PubMed  Google Scholar 

  42. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, a. t. P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Moya-Pérez, A., Perez-Villalba, A., Benítez-Páez, A., Campillo, I., & Sanz, Y. (2017). Bifidobacterium CECT 7765 modulates early stress-induced immune, neuroendocrine and behavioral alterations in mice. Brain, Behavior, and Immunity, 65, 43–56. https://doi.org/10.1016/j.bbi.2017.05.011.

    Article  PubMed  Google Scholar 

  44. Niu, M., Li, Q., Zhang, J., Wen, F., Dang, W., Duan, G., Li, H., Ruan, W., Yang, P., Guan, C., & Tian, H. (2019). Characterization of intestinal microbiota and probiotics treatment in children with autism spectrum disorders in China. Frontiers in Neurology, 10, 1084–1084. https://doi.org/10.3389/fneur.2019.01084.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Oh, M., Kim, S. A., & Yoo, H. J. (2020). Higher lactate level and lactate-to-pyruvate ratio in autism spectrum disorder. Experimental Neurobiology, 29(4), 314. https://doi.org/10.5607/en20030.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Ooi, Y. P., Weng, S. J., Kossowsky, J., Gerger, H., & Sung, M. (2017). Oxytocin and autism spectrum disorders: A systematic review and meta-analysis of randomized controlled trials. Pharmacopsychiatry, 50(1), 5–13. https://doi.org/10.1055/s-0042-109400.

    Article  PubMed  Google Scholar 

  47. Parracho, H. M., Bingham, M. O., Gibson, G. R., & McCartney, A. L. (2005). Differences between the gut microflora of children with autistic spectrum disorders and that of healthy children. Journal of Medical Microbiology, 54(Pt 10), 987–991. https://doi.org/10.1099/jmm.0.46101-0.

    Article  PubMed  Google Scholar 

  48. Plaza-Díaz, J., Gómez-Fernández, A., Chueca, N., Torre-Aguilar, M. J. D. L., Gil, Á., Perez-Navero, J. L., Flores-Rojas, K., Martín-Borreguero, P., Solis-Urra, P., Ruiz-Ojeda, F. J., & Garcia, F. (2019). Autism spectrum disorder (ASD) with and without mental regression is associated with changes in the fecal microbiota. Nutrients, 11(2), 337. https://doi.org/10.3390/nu11020337.

    Article  PubMed Central  Google Scholar 

  49. Rossignol, D. A., & Frye, R. E. (2012). Mitochondrial dysfunction in autism spectrum disorders: A systematic review and meta-analysis. Molecular Psychiatry, 17, 290. https://doi.org/10.1038/mp.2010.136.

    Article  PubMed  Google Scholar 

  50. Rothstein, H. R., Sutton, A. J., & Borenstein, M. (2005). Publication bias in meta-analysis: Prevention, assessment and adjustments. Willey.

    Book  Google Scholar 

  51. Rubio-Aparicio, M., López-López, J., Viechtbauer, W., Marín-Martínez, F., Botella, J., & Sanchez-Meca, J. (2019). Testing categorical moderators in mixed-effects meta-analysis in the presence of heteroscedasticity. The Journal of Experimental Education, 88, 288–310. https://doi.org/10.1080/00220973.2018.1561404.

    Article  Google Scholar 

  52. Rücker, G., & Schumacher, M. (2008). Simpson’s paradox visualized: The example of the rosiglitazone meta-analysis. BMC Medical Research Methodology, 8(1), 1–8.

    Article  Google Scholar 

  53. Sánchez-Meca, J., & Marín-Martínez, F. (2008). Confidence intervals for the overall effect size in random-effects meta-analysis. Psychological Methods, 13(1), 31–48. https://doi.org/10.1037/1082-989X.13.1.31.

    Article  PubMed  Google Scholar 

  54. Sanchez-Meca, J., Marin-Martinez, F., & Chacon-Moscoso, S. (2003). Effect-size indices for dichotomized outcomes in meta-analysis. Psychological Methods, 8(4), 448–467. https://doi.org/10.1037/1082-989x.8.4.448.

    Article  PubMed  Google Scholar 

  55. Shaaban, S. Y., El Gendy, Y. G., Mehanna, N. S., El-Senousy, W. M., El-Feki, H. S. A., Saad, K., & El-Asheer, O. M. (2017). The role of probiotics in children with autism spectrum disorder: A prospective, open-label study. Nutritional Neuroscience, 21(9), 1–6. https://doi.org/10.1080/1028415x.2017.1347746.

    Article  Google Scholar 

  56. Sharp, W. G., Berry, R. C., McCracken, C., Nuhu, N. N., Marvel, E., Saulnier, C. A., Klin, A., Jones, W., & Jaquess, D. L. (2013). Feeding problems and nutrient intake in children with autism spectrum disorders: A meta-analysis and comprehensive review of the literature. Journal of Autism and Developmental Disorders, 43(9), 2159–2173. https://doi.org/10.1007/s10803-013-1771-5.

    Article  PubMed  Google Scholar 

  57. Vallée, A., & Vallée, J.-N. (2018). Warburg effect hypothesis in autism Spectrum disorders. Molecular Brain, 11(1), 1. https://doi.org/10.1186/s13041-017-0343-6.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36, 1–48. https://doi.org/10.18637/jss.v036.i03.

    Article  Google Scholar 

  59. Vuong, H. E., & Hsiao, E. Y. (2017). Emerging roles for the gut microbiome in autism spectrum disorder. Biological Psychiatry, 81(5), 411–423. https://doi.org/10.1016/j.biopsych.2016.08.024.

    Article  PubMed  Google Scholar 

  60. Wang, L., Christophersen, C. T., Sorich, M. J., Gerber, J. P., Angley, M. T., & Conlon, M. A. (2011). Low relative abundances of the mucolytic bacterium Akkermansia muciniphila and Bifidobacterium spp. in feces of children with autism. Applied and Environmental Microbiology, 77(18), 6718–6721. https://doi.org/10.1128/aem.05212-11.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Wang, L., Christophersen, C. T., Sorich, M. J., Gerber, J. P., Angley, M. T., & Conlon, M. A. (2013). Increased abundance of Sutterella spp. and Ruminococcus torques in feces of children with autism spectrum disorder. Molecular Autism, 4, 42. https://doi.org/10.1186/2040-2392-4-42.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Wang, S., Harvey, L., Martin, R., van der Beek, E. M., Knol, J., Cryan, J. F., & Renes, I. B. (2018). Targeting the gut microbiota to influence brain development and function in early life. Neuroscience & Biobehavioral Reviews, 95, 191–201. https://doi.org/10.1016/j.neubiorev.2018.09.002.

    Article  Google Scholar 

  63. Wells, G. A., Shea, B., O’Connell, D. A., Peterson, J., Welch, V., Losos, M., & Tugwell, P. (2000). The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. Ottawa: Ottawa Hospital Research Institute. http://www3.med.unipmn.it/dispense_ebm/2009-2010/Corso%20Perfezionamento%20EBM_Faggiano/NOS_oxford.pdf

  64. Williams, B. L., Hornig, M., Buie, T., Bauman, M. L., Cho Paik, M., Wick, I., Bennett, A., Jabado, O., Hirschberg, D. L., & Lipkin, W. I. (2011). Impaired carbohydrate digestion and transport and mucosal dysbiosis in the intestines of children with autism and gastrointestinal disturbances. PloS One, 6(9), e24585. https://doi.org/10.1371/journal.pone.0024585.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Williams, B. L., Hornig, M., Parekh, T., & Lipkin, W. I. (2012). Application of novel PCR-based methods for detection, quantitation, and phylogenetic characterization of Sutterella species in intestinal biopsy samples from children with autism and gastrointestinal disturbances. MBio, 3(1), e00261–00211. https://doi.org/10.1128/mBio.00261-11.

    Article  Google Scholar 

  66. Wu, W., Kong, Q., Tian, P., Zhai, Q., Wang, G., Liu, X., Zhao, J., Zhang, H., Lee, Y. K., & Chen, W. (2020). Targeting gut microbiota dysbiosis: Potential intervention strategies for neurological disorders. Engineering. https://doi.org/10.1016/j.eng.2019.07.026.

    Article  PubMed  Google Scholar 

  67. Xu, M., Xu, X., Li, J., & Li, F. (2019). Association between gut microbiota and autism spectrum disorder: A systematic review and meta-analysis. Frontiers in Psychiatry, 10, 473. https://doi.org/10.3389/fpsyt.2019.00473.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Zhang, M., Ma, W., Zhang, J., He, Y., & Wang, J. (2018). Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China. Scientific Reports, 8(1), 13981–13981. https://doi.org/10.1038/s41598-018-32219-2.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The authors would like to thank Ms. Seonaid McNabb for her English revision.

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Correspondence to Agustín Ernesto Martínez-González.

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PAM and AEMG conceived and designed the systematic review, selected and coded the articles, created a database of the identified bacteria, created the article quality database and performed the risk of bias analysis. MRA created the database of selected moderators and bacteria and performed data analysis. AV performed the risk of bias analysis. JSM performed data analysis. PAM, AEMG and MRA wrote the manuscript. JSM and AV edited the manuscript and all the authors approved the final version of the manuscript.

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Andreo-Martínez, P., Rubio-Aparicio, M., Sánchez-Meca, J. et al. A Meta-analysis of Gut Microbiota in Children with Autism. J Autism Dev Disord (2021). https://doi.org/10.1007/s10803-021-05002-y

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Keywords

  • Autism spectrum disorders (ASD)
  • Gut microbiota
  • Microbiota-gut-brain axis
  • Systematic review
  • Meta-analysis