Jong Yeob Kim1, Min Ji Son1, Chei Yun Son2, Joaquim Radua3, Michael Eisenhut4, Florence Gressier5, Ai Koyanagi6, Andre F Carvalho7, Brendon Stubbs8, Marco Solmi9, Theodor B Rais10, Keum Hwa Lee11, Andreas Kronbichler12, Elena Dragioti13, Jae Il Shin14, Paolo Fusar-Poli15. 1. Yonsei University College of Medicine, Seoul, Republic of Korea. 2. Department of Psychological & Brain Sciences, Washington University in St. Louis, MO, USA. 3. Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; FIDMAG Germanes Hospitalaries, CIBERSAM, Barcelona, Spain; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. 4. Department of Pediatrics, Luton & Dunstable University Hospital NHS Foundation Trust, Luton, UK. 5. CESP, Inserm UMR1178, Department of Psychiatry, Assistance Publique-Hôpitaux de Paris, Bicêtre University Hospital, Le Kremlin Bicêtre, France. 6. Research and Development Unit, Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Fundació Sant Joan de Déu, Barcelona, Spain; Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain; Centre for Addiction & Mental Health, Toronto, ON, Canada. 7. Centre for Addiction & Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada. 8. Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. 9. Department of Neurosciences and Neurosciences Center, University of Padua, Padua, Italy; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. 10. Department of Psychiatry, University of Toledo Medical Center, Toledo, Ohio, USA. 11. Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea; Department of Pediatrics, Severance Children's Hospital, Seoul, South Korea. 12. Department of Internal Medicine IV, Medical University Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria. 13. Pain and Rehabilitation center and Department of Medicine and Health Sciences (IMH), Faculty of Health Sciences University of Linköping, Linköping, Sweden. 14. Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea; Department of Pediatrics, Severance Children's Hospital, Seoul, South Korea. Electronic address: shinji@yuhs.ac. 15. Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK. Electronic address: paolo.fusar-poli@kcl.ac.uk.
Abstract
BACKGROUND: Numerous studies have identified potential risk factors and biomarkers for autism spectrum disorder. We aimed to study the strength and validity of the suggested environmental risk factors or biomarkers of autism spectrum disorder. METHODS: We did an umbrella review and systematically appraised the relevant meta-analyses of observational studies. We searched PubMed, Embase, and the Cochrane Database of Systematic Reviews for papers published between database inception and Oct 17, 2018, and screened the reference list of relevant articles. We obtained the summary effect, 95% CI, heterogeneity, and 95% prediction intervals. We examined small study effects and excess significance. We did analyses under credibility ceilings. This review is registered with PROSPERO, number CRD42018091704. FINDINGS: 46 eligible articles yielded data on 67 environmental risk factors (544 212 cases, 81 708 787 individuals) and 52 biomarkers (15 614 cases, 15 433 controls). Evidence of association was convincing for maternal age of 35 years or over (relative risk [RR] 1·31, 95% CI 1·18-1·45), maternal chronic hypertension (odds ratio [OR] 1·48, 1·29-1·70), maternal gestational hypertension (OR 1·37, 1·21-1·54), maternal overweight before or during pregnancy (RR 1·28, 1·19-1·36), pre-eclampsia (RR 1·32, 1·20-1·45), prepregnancy maternal antidepressant use (RR 1·48, 1·29-1·71), and maternal selective serotonin reuptake inhibitor (SSRI) use during pregnancy (OR 1·84, 1·60-2·11). Only two associations, maternal overweight before or during pregnancy and SSRI use during pregnancy, retained their high level of evidence under subset sensitivity analyses. Evidence from biomarkers was scarce, being supported by p values close to the significance threshold and too few cases. INTERPRETATION: Convincing evidence suggests that maternal factors, such as age and features of metabolic syndrome, are associated with risk of autism spectrum disorder. Although SSRI use during pregnancy was also associated with such risk when exposed and non-exposed groups were compared, this association could be affected by other confounding factors, considering that prepregnancy maternal antidepressant use was also convincingly associated with higher risk of autism spectrum disorder. Findings from previous studies suggest that one possible confounding factor is underlying maternal psychiatric disorders. FUNDING: None.
BACKGROUND: Numerous studies have identified potential risk factors and biomarkers for autism spectrum disorder. We aimed to study the strength and validity of the suggested environmental risk factors or biomarkers of autism spectrum disorder. METHODS: We did an umbrella review and systematically appraised the relevant meta-analyses of observational studies. We searched PubMed, Embase, and the Cochrane Database of Systematic Reviews for papers published between database inception and Oct 17, 2018, and screened the reference list of relevant articles. We obtained the summary effect, 95% CI, heterogeneity, and 95% prediction intervals. We examined small study effects and excess significance. We did analyses under credibility ceilings. This review is registered with PROSPERO, number CRD42018091704. FINDINGS: 46 eligible articles yielded data on 67 environmental risk factors (544 212 cases, 81 708 787 individuals) and 52 biomarkers (15 614 cases, 15 433 controls). Evidence of association was convincing for maternal age of 35 years or over (relative risk [RR] 1·31, 95% CI 1·18-1·45), maternal chronic hypertension (odds ratio [OR] 1·48, 1·29-1·70), maternal gestational hypertension (OR 1·37, 1·21-1·54), maternal overweight before or during pregnancy (RR 1·28, 1·19-1·36), pre-eclampsia (RR 1·32, 1·20-1·45), prepregnancy maternal antidepressant use (RR 1·48, 1·29-1·71), and maternal selective serotonin reuptake inhibitor (SSRI) use during pregnancy (OR 1·84, 1·60-2·11). Only two associations, maternal overweight before or during pregnancy and SSRI use during pregnancy, retained their high level of evidence under subset sensitivity analyses. Evidence from biomarkers was scarce, being supported by p values close to the significance threshold and too few cases. INTERPRETATION: Convincing evidence suggests that maternal factors, such as age and features of metabolic syndrome, are associated with risk of autism spectrum disorder. Although SSRI use during pregnancy was also associated with such risk when exposed and non-exposed groups were compared, this association could be affected by other confounding factors, considering that prepregnancy maternal antidepressant use was also convincingly associated with higher risk of autism spectrum disorder. Findings from previous studies suggest that one possible confounding factor is underlying maternal psychiatric disorders. FUNDING: None.
Authors: Elena Dragioti; Marco Solmi; Angela Favaro; Paolo Fusar-Poli; Paola Dazzan; Trevor Thompson; Brendon Stubbs; Joseph Firth; Michele Fornaro; Dimitrios Tsartsalis; Andre F Carvalho; Eduard Vieta; Philip McGuire; Allan H Young; Jae Il Shin; Christoph U Correll; Evangelos Evangelou Journal: JAMA Psychiatry Date: 2019-12-01 Impact factor: 21.596
Authors: Elena Dragioti; Joaquim Radua; Marco Solmi; Celso Arango; Dominic Oliver; Samuele Cortese; Peter B Jones; Jae Il Shin; Christoph U Correll; Paolo Fusar-Poli Journal: Mol Psychiatry Date: 2022-04-28 Impact factor: 15.992
Authors: Marco Solmi; Minjin Song; Dong Keon Yon; Seung Won Lee; Eric Fombonne; Min Seo Kim; Seoyeon Park; Min Ho Lee; Jimin Hwang; Roberto Keller; Ai Koyanagi; Louis Jacob; Elena Dragioti; Lee Smith; Christoph U Correll; Paolo Fusar-Poli; Giovanni Croatto; Andre F Carvalho; Jae Won Oh; San Lee; Corentin J Gosling; Keun-Ah Cheon; Dimitris Mavridis; Che-Sheng Chu; Chih-Sung Liang; Joaquim Radua; Laurent Boyer; Guillaume Fond; Jae Il Shin; Samuele Cortese Journal: Mol Psychiatry Date: 2022-06-29 Impact factor: 15.992
Authors: Marco Solmi; Joaquim Radua; Brendon Stubbs; Valdo Ricca; Davide Moretti; Daniele Busatta; Andre F Carvalho; Elena Dragioti; Angela Favaro; Alessio Maria Monteleone; Jae Il Shin; Paolo Fusar-Poli; Giovanni Castellini Journal: Braz J Psychiatry Date: 2020-09-28 Impact factor: 2.697