Exposition de la mère aux pesticides et risque de "troubles du spectre de l'autisme" chez la progéniture: une méta-analyse

Aperçu: G.M.

Cette méta-analyse a été menée pour estimer l'association globale entre l'exposition maternelle aux pesticides et le risque de TSA chez la progéniture.
Des rechertches ont été menées sur PubMed, EMBASE, Web of Science et PsycINFO jusqu'au 30 décembre 2020 pour inclure les études éligibles.
Huit études avec 50 426 participants, dont 5810 avaient un TSA, ont été impliquées dans l'étude.
Dans l'ensemble, le RC sommaire (intervalle de confiance à 95%) des TSA chez la progéniture pour l'exposition maternelle aux pesticides estimé par les mesures de proximité résidentielle et l'auto-évaluation était de 1,88 (1,10-3,20).
Cependant, l'exposition maternelle aux pesticides mesurée par des biomarqueurs n'était pas associée à un risque accru de TSA (OR combiné 1,13; IC à 95% 0,83-1,54).
D'autres études bien conçues sont nécessaires pour confirmer nos résultats.

• 2021 May 12. doi: 10.1007/s10803-021-05063-z. 

Maternal Exposure to Pesticides and Risk of Autism Spectrum Disorders in Offspring: A Meta-analysis

Li Wang  ¹ , Shiming Tang  ¹ , Songjie Wu  ² , Lihua Yao  ¹ , Dezhen Su  ¹ , Ying Wang  ³

Affiliations

• PMID: 33978908
• DOI: 10.1007/s10803-021-05063-z

Abstract

This meta-analysis was conducted to estimate the overall association between maternal exposure to pesticides and risk of ASD in offspring. PubMed, EMBASE, Web of Science, and the PsycINFO were searched until December 30, 2020 to include eligible studies. Eight studies with 50,426 participants, 5810 of whom had ASD, were involved in the study. Overall, the summary OR (95% confidence interval) of ASDs in offspring for maternal exposure to pesticide estimated by residential proximity measures and self-report was 1.88 (1.10-3.20). However, maternal exposure to pesticide measured by biomarkers was not associated with an increased risk of ASDs (pooled OR 1.13; 95% CI 0.83-1.54). Further well-designed studies are needed to confirm our findings.

Keywords: Autism; Meta-analysis; Pesticides; Risk factor.

References

1. 1. American Psychiatric Association (APA). (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th ed. American Psychiatric Association. Retrieved April 4, 2020, from https://www.psychiatry.org/psychiatrists/practice/dsm
2. 1. Andersen, H. R., Debes, F., Wohlfahrt-Veje, C., Murata, K., & Grandjean, P. (2015). Occupational pesticide exposure in early pregnancy associated with sex-specific neurobehavioral deficits in the children at school age. Neurotoxicology and Teratology, 47, 1–9. https://doi.org/10.1016/j.ntt.2014.10.006 - DOI - PubMed
3. 1. Bachelet, D., Truong, T., Verner, M.-A., Arveux, P., Kerbrat, P., Charlier, C., Guihenneuc-Jouyaux, C., & Guénel, P. (2011). Determinants of serum concentrations of 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene and polychlorinated biphenyls among French women in the CECILE study. Environmental Research, 111, 861–870. https://doi.org/10.1016/j.envres.2011.06.001 - DOI - PubMed
4. 1. Baxter, A. J., Brugha, T. S., Erskine, H. E., Scheurer, R. W., Vos, T., & Scott, J. G. (2015). The epidemiology and global burden of autism spectrum disorders. Psychological Medicine, 45, 601–613. https://doi.org/10.1017/s003329171400172x - DOI - PubMed
5. 1. Begg, C. B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50, 1088–1101 - DOI
6. 1. Bigbee, J. W., Sharma, K. V., Chan, E. L. P., & Bögler, O. (2000). Evidence for the direct role of acetylcholinesterase in neurite outgrowth in primary dorsal root ganglion neurons. Brain Research, 861, 354–362. https://doi.org/10.1016/S0006-8993(00)02046-1 - DOI - PubMed
7. 1. Bjørklund, G., Meguid, N. A., El-Bana, M. A., Tinkov, A. A., Saad, K., Dadar, M., Hemimi, M., Skalny, A. V., Hosnedlová, B., Kizek, R., Osredkar, J., Urbina, M. A., Fabjan, T., El-Houfey, A. A., Kałużna-Czaplińska, J., Gątarek, P., & Chirumbolo, S. (2020). Oxidative stress in autism spectrum disorder. Molecular Neurobiology. https://doi.org/10.1007/s12035-019-01742-2 - DOI - PubMed - PMC
8. 1. Bradman, A., Barr, D. B., Claus Henn, B. G., Drumheller, T., Curry, C., & Eskenazi, B. (2003). Measurement of pesticides and other toxicants in amniotic fluid as a potential biomarker of prenatal exposure: A validation study. Environmental Health Perspectives, 111, 1779–1782. https://doi.org/10.1289/ehp.6259 - DOI - PubMed - PMC
9. 1. Brown, A. S., Cheslack-Postava, K., Rantakokko, P., Kiviranta, H., Hinkka-Yli-Salomäki, S., McKeague, I. W., Surcel, H.-M., & Sourander, A. (2018). Association of maternal insecticide levels with autism in offspring from a national birth cohort. American Journal of Psychiatry, 175, 1094–1101. https://doi.org/10.1176/appi.ajp.2018.17101129 - DOI
10. 1. Burdorf, A., Brand, T., Jaddoe, V. W., Hofman, A., Mackenbach, J. P., & Steegers, E. A. P. (2011). The effects of work-related maternal risk factors on time to pregnancy, preterm birth and birth weight: The generation R study. Occupational and Environmental Medicine, 68, 197. https://doi.org/10.1136/oem.2009.046516 - DOI - PubMed
11. 1. Casida, J. E. (2009). Pest toxicology: The primary mechanisms of pesticide action. Chemical Research in Toxicology, 22, 609–619. https://doi.org/10.1021/tx8004949 - DOI - PubMed
12. 1. Cheslack-Postava, K., Rantakokko, P. V., Hinkka-Yli-Salomäki, S., Surcel, H.-M., McKeague, I. W., Kiviranta, H. A., Sourander, A., & Brown, A. S. (2013). Maternal serum persistent organic pollutants in the finnish prenatal study of autism: A pilot study. Neurotoxicology and Teratology, 38, 1–5. https://doi.org/10.1016/j.ntt.2013.04.001 - DOI - PubMed - PMC
13. 1. Christian, M. A., Samms-Vaughan, M., Lee, M., Bressler, J., Hessabi, M., Grove, M. L., Shakespeare-Pellington, S., Desai, C. C., Reece, J.-A., Loveland, K. A., Boerwinkle, E., & Rahbar, M. H. (2018). Maternal exposures associated with autism spectrum disorder in Jamaican children. Journal of Autism and Developmental Disorders, 48, 2766–2778. https://doi.org/10.1007/s10803-018-3537-6 - DOI - PubMed - PMC
14. 1. de Bildt, A., Sytema, S., Ketelaars, C., Kraijer, D., Mulder, E., Volkmar, F., & Minderaa, R. (2004). Interrelationship between autism diagnostic observation schedule-generic (ADOS-G), autism diagnostic interview-revised (ADI-R), and the diagnostic and statistical manual of mental disorders (DSM-IV-TR) classification in children and adolescents with mental retardation. Journal of Autism and Developmental Disorders, 34, 129–137. https://doi.org/10.1023/B:JADD.0000022604.22374.5f - DOI - PubMed
15. 1. De Felice, A., Scattoni, M. L., Ricceri, L., & Calamandrei, G. (2015). Prenatal exposure to a common organophosphate insecticide delays motor development in a mouse model of idiopathic autism. PLoS ONE, 10, e0121663. https://doi.org/10.1371/journal.pone.0121663 - DOI - PubMed - PMC
16. 1. Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315, 629. https://doi.org/10.1136/bmj.315.7109.629 - DOI - PubMed - PMC
17. 1. Eskenazi, B., Marks, A. R., Bradman, A., Harley, K., Barr, D. B., Johnson, C., Morga, N., & Jewell, N. P. (2007). Organophosphate pesticide exposure and neurodevelopment in young Mexican-American children. Environmental health perspectives, 115, 792–8. https://doi.org/10.1289/ehp.9828 - DOI - PubMed - PMC
18. 1. Evangelou, E., Ntritsos, G., Chondrogiorgi, M., Kavvoura, F. K., Hernández, A. F., Ntzani, E. E., & Tzoulaki, I. (2016). Exposure to pesticides and diabetes: A systematic review and meta-analysis. Environment International, 91, 60–68. https://doi.org/10.1016/j.envint.2016.02.013 - DOI - PubMed
19. 1. Furlong, M. A., Engel, S. M., Barr, D. B., & Wolff, M. S. (2014). Prenatal exposure to organophosphate pesticides and reciprocal social behavior in childhood. Environment International, 70, 125–131. https://doi.org/10.1016/j.envint.2014.05.011 - DOI - PubMed - PMC
20. 1. Gray, L. E., Jr., & Ostby, J. (1998). Effects of pesticides and toxic substances on behavioral and morphological reproductive development: Endocrine versus nonendocrine mechanisms. Toxicology and Industrial Health, 14, 159–184. https://doi.org/10.1177/074823379801400111 - DOI - PubMed
21. 1. Hamra, G. B., Lyall, K., Windham, G. C., Calafat, A. M., Sjödin, A., Volk, H., & Croen, L. A. (2019). Prenatal exposure to endocrine-disrupting chemicals in relation to autism spectrum disorder and intellectual disability. Epidemiology (Cambridge, Mass), 30, 418–426. https://doi.org/10.1097/ede.0000000000000983 - DOI
22. 1. Higgins, J. P., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539–1558. https://doi.org/10.1002/sim.1186 - DOI - PubMed
23. 1. Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analyses. BMJ, 327, 557. https://doi.org/10.1136/bmj.327.7414.557 - DOI - PubMed - PMC
24. 1. Keil, A. P., Daniels, J. L., & Hertz-Picciotto, I. (2014). Autism spectrum disorder, flea and tick medication, and adjustments for exposure misclassification: The CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. Environmental Health : A Global Access Science Source, 13, 3. https://doi.org/10.1186/1476-069x-13-3 - DOI
25. 1. Landrigan, P. (2017). Pesticides and human reproduction. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2017.5092 - DOI
26. 1. Lee, D.-H., Lind, L., Jacobs, D. R., Salihovic, S., van Bavel, B., & Lind, P. M. (2012). Associations of persistent organic pollutants with abdominal obesity in the elderly: The prospective investigation of the vasculature in uppsala seniors (PIVUS) study. Environment International, 40, 170–178. https://doi.org/10.1016/j.envint.2011.07.010 - DOI - PubMed
27. 1. Lee, I., Eriksson, P., Fredriksson, A., Buratovic, S., & Viberg, H. (2015). Developmental neurotoxic effects of two pesticides: Behavior and neuroprotein studies on endosulfan and cypermethrin. Toxicology, 335, 1–10. https://doi.org/10.1016/j.tox.2015.06.010 - DOI - PubMed
28. 1. Lord, C., Brugha, T. S., Charman, T., Cusack, J., Dumas, G., Frazier, T., Jones, E. J. H., Jones, R. M., Pickles, A., State, M. W., Taylor, J. L., & Veenstra-VanderWeele, J. (2020). Autism spectrum disorder. Nature Reviews Disease Primers, 6, 5. https://doi.org/10.1038/s41572-019-0138-4 - DOI - PubMed
29. 1. Lu, C., Bravo, R., Caltabiano, L. M., Irish, R. M., Weerasekera, G., & Barr, D. B. (2005). The presence of dialkylphosphates in fresh fruit juices: Implication for organophosphorus pesticide exposure and risk assessments. Journal of Toxicology and Environmental Health, Part A, 68, 209–227. https://doi.org/10.1080/15287390590890554 - DOI
30. 1. Lyall, K., Croen, L. A., Sjödin, A., Yoshida, C. K., Zerbo, O., Kharrazi, M., & Windham, G. C. (2017). Polychlorinated biphenyl and organochlorine pesticide concentrations in maternal mid-pregnancy serum samples: Association with autism spectrum disorder and intellectual disability. Environmental Health Perspectives, 125, 474–480. https://doi.org/10.1289/EHP277 - DOI - PubMed
31. 1. Morales, D. R., Slattery, J., Evans, S., & Kurz, X. (2018). Antidepressant use during pregnancy and risk of autism spectrum disorder and attention deficit hyperactivity disorder: Systematic review of observational studies and methodological considerations. BMC Medicine, 16, 6. https://doi.org/10.1186/s12916-017-0993-3 - DOI - PubMed - PMC
32. 1. Mostafalou, S., & Abdollahi, M. (2017). Pesticides: An update of human exposure and toxicity. Archives of Toxicology, 91, 549–599. https://doi.org/10.1007/s00204-016-1849-x - DOI - PubMed
33. 1. World Health Organization. (2019). Fact sheet, autism spectrum disorders. World Health Organization, Retrieved April 4, 2020, from https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders
34. 1. Pang, Y., Lee, C. M., Wright, M., Shen, J., Shen, B., & Bo, J. (2018). Challenges of case identification and diagnosis of autism spectrum disorders in China: A critical review of procedures, assessment, and diagnostic criteria. Research in Autism Spectrum Disorders, 53, 53–66. https://doi.org/10.1016/j.rasd.2018.06.003 - DOI
35. 1. Pearson, B. L., Simon, J. M., McCoy, E. S., Salazar, G., Fragola, G., & Zylka, M. J. (2016). Identification of chemicals that mimic transcriptional changes associated with autism, brain aging and neurodegeneration. Nature Communications, 7, 11173. https://doi.org/10.1038/ncomms11173 - DOI - PubMed - PMC
36. 1. Philippat, C., Barkoski, J., Tancredi, D. J., Elms, B., Barr, D. B., Ozonoff, S., Bennett, D. H., & Hertz-Picciotto, I. (2018). Prenatal exposure to organophosphate pesticides and risk of autism spectrum disorders and other non-typical development at 3 years in a high-risk cohort. International Journal of Hygiene and Environmental Health, 221, 548–555. https://doi.org/10.1016/j.ijheh.2018.02.004 - DOI - PubMed - PMC
37. 1. Roberts Eric, M., English Paul, B., Grether Judith, K., Windham Gayle, C., Somberg, L., & Wolff, C. (2007). Maternal residence near agricultural pesticide applications and autism spectrum disorders among children in the california central valley. Environmental Health Perspectives, 115, 1482–1489. https://doi.org/10.1289/ehp.10168 - DOI - PubMed - PMC
38. 1. Ruediger, T., & Bolz, J. (2007). Neurotransmitters and the development of neuronal circuits. Advances in Experimental Medicine and Biology, 621, 104–115. https://doi.org/10.1007/978-0-387-76715-4_8 - DOI - PubMed
39. 1. Sagiv, S. K., Harris, M. H., Gunier, R. B., Kogut, K. R., Harley, K. G., Deardorff, J., Bradman, A., Holland, N., & Eskenazi, B. (2018). Prenatal organophosphate pesticide exposure and traits related to autism spectrum disorders in a population living in proximity to agriculture. Environmental Health Perspectives, 126, 047012. https://doi.org/10.1289/ehp2580 - DOI - PubMed - PMC
40. 1. Sandin, S., Hultman, C. M., Kolevzon, A., Gross, R., MacCabe, J. H., & Reichenberg, A. (2012). Advancing maternal age is associated with increasing risk for autism: A review and meta-analysis. Journal of the American Academy of Child & Adolescent Psychiatry, 51, 477-486.e1. https://doi.org/10.1016/j.jaac.2012.02.018 - DOI
41. 1. Schmidt, R. J., Kogan, V., Shelton, J. F., Delwiche, L., Hansen, R. L., Ozonoff, S., Ma, C. C., McCanlies, E. C., Bennett, D. H., Hertz-Picciotto, I., Tancredi, D. J., & Volk, H. E. (2017). Combined prenatal pesticide exposure and folic acid intake in relation to autism spectrum disorder. Environmental Health Perspectives, 125, 097007. https://doi.org/10.1289/ehp604 - DOI - PubMed - PMC
42. 1. Shelton, J. F., Geraghty, E. M., Tancredi, D. J., Delwiche, L. D., Schmidt, R. J., Ritz, B., Hansen, R. L., & Hertz-Picciotto, I. (2014). Neurodevelopmental disorders and prenatal residential proximity to agricultural pesticides: The CHARGE study. Environmental Health Perspectives, 122, 1103–1109. https://doi.org/10.1289/ehp.1307044 - DOI - PubMed - PMC
43. 1. Stroup, D. F., Berlin, J. A., Morton, S. C., Olkin, I., Williamson, G. D., Rennie, D., Moher, D., Becker, B. J., Sipe, T. A., & Thacker, S. B. (2000). Meta-analysis of observational studies in epidemiology: A proposal for reporting. JAMA, 283, 2008–2012. https://doi.org/10.1001/jama.283.15.2008 - DOI - PubMed
44. 1. Topal, A., Alak, G., Ozkaraca, M., Yeltekin, A. C., Comaklı, S., Acıl, G., Kokturk, M., & Atamanalp, M. (2017). Neurotoxic responses in brain tissues of rainbow trout exposed to imidacloprid pesticide: Assessment of 8-hydroxy-2-deoxyguanosine activity, oxidative stress and acetylcholinesterase activity. Chemosphere, 175, 186–191. https://doi.org/10.1016/j.chemosphere.2017.02.047 - DOI - PubMed
45. 1. Viel, J.-F., Rouget, F., Warembourg, C., Monfort, C., Limon, G., Cordier, S., & Chevrier, C. (2017). Behavioural disorders in 6-year-old children and pyrethroid insecticide exposure: The PELAGIE mother-child cohort. Occupational and Environmental Medicine, 74, 275–281. https://doi.org/10.1136/oemed-2016-104035 - DOI - PubMed
46. 1. von Ehrenstein, O. S., Ling, C., Cui, X., Cockburn, M., Park, A. S., Yu, F., Wu, J., & Ritz, B. (2019). Prenatal and infant exposure to ambient pesticides and autism spectrum disorder in children: Population based case-control study. BMJ, 364, l962. https://doi.org/10.1136/bmj.l962 - DOI
47. 1. Wang, Y., Tang, S., Xu, S., Weng, S., & Liu, Z. (2016). Maternal body mass index and risk of autism spectrum disorders in offspring: A meta-analysis. Scientific Reports, 6, 34248. https://doi.org/10.1038/srep34248 - DOI - PubMed - PMC
48. 1. Wells, G. A., O’Connell, B. S. D., Peterson, J., Welch, V., Losos, M., & Tugwell, P. (2011). The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. The Ottawa Health Research Institute.
49. 1. Xu, G., Jing, J., Bowers, K., Liu, B., & Bao, W. (2014). Maternal diabetes and the risk of autism spectrum disorders in the offspring: A systematic review and meta-analysis. Journal of Autism and Developmental Disorders, 44, 766–775. https://doi.org/10.1007/s10803-013-1928-2 - DOI - PubMed - PMC
50. 1. Zhu, Z., Tang, S., Deng, X., & Wang, Y. (2020). Maternal systemic lupus erythematosus, rheumatoid arthritis, and risk for autism spectrum disorders in offspring: A meta-analysis. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-020-04400-y - DOI - PubMed

Une méta-analyse du microbiote intestinal chez les enfants autistes

Aperçu: G.M.

Des études antérieures ont rapporté une dysbiose dans le microbiote intestinal (MI) d'enfants avec un diagnostic du "trouble du spectre de l'autisme" (dTSA), qui peut être un facteur déterminant sur le développement de l'enfant à travers l'axe microbiote-intestin-cerveau. Cependant, on ne sait pas s'il existe un groupe spécifique de bactéries dysbiotiques dans les TSA. 

Le but de cette étude était de réaliser une méta-analyse sur les études qui analysent le MI chez les enfants avec un dTSA. 18 études remplissaient nos critères de sélection. 

Nos résultats ont montré une plus faible abondance relative de Streptococcus (SMD + = - 0,999; IC à 95% - 1,549, - 0,449) et de genres Bifidobacterium (SMD + = - 0,513; IC à 95% - 0,953, - 0,073) chez les enfants avec un dTSA. Dans l'ensemble, les genres Bifidobacterium sont impliqués. Cependant, les différences constatées entre les études sont attribuées à des facteurs tels que le biais de déclaration.

. 2021 May 5. doi: 10.1007/s10803-021-05002-y.

A Meta-analysis of Gut Microbiota in Children with Autism

Pedro Andreo-Martínez  ^{1   2} , María Rubio-Aparicio  ³ , Julio Sánchez-Meca  ⁴ , Alejandro Veas  ⁵ , Agustín Ernesto Martínez-González  ^{6   7}

Affiliations

• PMID: 33948825
• DOI: 10.1007/s10803-021-05002-y

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.

Keywords: Autism spectrum disorders (ASD); Gut microbiota; Meta-analysis; Microbiota-gut-brain axis; Systematic review.

References

1. 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 . - DOI
2. 1. 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 . - DOI - PubMed
3. 1. APA. (2013). American Psychiatric Association. Autism spectrum disorder. In Diagnostic and statistical manual of mental disorders, 5 Eds (DSM-5). American Psychiatric Publishing.
4. 1. 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 . - DOI - PMC
5. 1. 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 . - DOI - PubMed
6. 1. Borenstein, M. (2019). Common mistakes in meta-analysis and how to avoid them. Englewood, NJ: Biostat Inc.
7. 1. Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley. - DOI
8. 1. 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 . - DOI - PubMed - PMC
9. 1. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). 12 Lawrence Erlbaum Associates Inc.
10. 1. Cooper, H., Hedges, L. V., & Valentine, J. C. (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation. - DOI
11. 1. 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 . - DOI - PubMed - PMC
12. 1. 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 . - DOI - PubMed
13. 1. 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 . - DOI
14. 1. 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 . - DOI - PubMed - PMC
15. 1. 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 . - DOI - PubMed
16. 1. 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 . - DOI - PubMed
17. 1. 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 . - DOI
18. 1. 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 . - DOI - PubMed
19. 1. 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 . - DOI - PubMed
20. 1. 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 . - DOI - PubMed
21. 1. 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%3... . - DOI
22. 1. Hedges, L., & Olkin, I. (1985). Statistical methods for meta-analysis. Academic Press.
23. 1. 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 . - DOI - PubMed - PMC
24. 1. 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 . - DOI - PubMed - PMC
25. 1. 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 . - DOI - PubMed
26. 1. 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 . - DOI - PMC
27. 1. 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 . - DOI - PubMed
28. 1. 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 . - DOI - PubMed
29. 1. 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 . - DOI - PubMed
30. 1. 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 . - DOI - PubMed - PMC
31. 1. 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 . - DOI - PubMed
32. 1. 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 . - DOI - PubMed
33. 1. 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 . - DOI - PubMed
34. 1. 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 . - DOI - PubMed - PMC
35. 1. 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 . - DOI - PubMed
36. 1. 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 . - DOI - PubMed - PMC
37. 1. 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 . - DOI - PMC
38. 1. 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 . - DOI - PubMed
39. 1. 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. 1. 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 . - DOI - PubMed - PMC
41. 1. 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 . - DOI - PubMed
42. 1. 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 . - DOI - PubMed - PMC
43. 1. 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 . - DOI - PubMed
44. 1. 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 . - DOI - PubMed - PMC
45. 1. 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 . - DOI - PubMed - PMC
46. 1. 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 . - DOI - PubMed
47. 1. 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 . - DOI - PubMed
48. 1. 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 . - DOI - PMC
49. 1. 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 . - DOI - PubMed
50. 1. Rothstein, H. R., Sutton, A. J., & Borenstein, M. (2005). Publication bias in meta-analysis: Prevention, assessment and adjustments. Willey. - DOI
51. 1. 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 . - DOI
52. 1. Rücker, G., & Schumacher, M. (2008). Simpson’s paradox visualized: The example of the rosiglitazone meta-analysis. BMC Medical Research Methodology, 8(1), 1–8. - DOI
53. 1. 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 . - DOI - PubMed
54. 1. 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 . - DOI - PubMed
55. 1. 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 . - DOI
56. 1. 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 . - DOI - PubMed
57. 1. 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 . - DOI - PubMed - PMC
58. 1. 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 . - DOI
59. 1. 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 . - DOI - PubMed
60. 1. 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 . - DOI - PubMed - PMC
61. 1. 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 . - DOI - PubMed - PMC
62. 1. 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 . - DOI
63. 1. 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...
64. 1. 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 . - DOI - PubMed - PMC
65. 1. 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 . - DOI
66. 1. 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 . - DOI - PubMed
67. 1. 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 . - DOI - PubMed - PMC
68. 1. 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 . - DOI - PubMed - PMC