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Invited Commentary: Male Reproductive System Congenital Malformations and the Risk of Autism Spectrum Disorder
Author(s) -
Laura A. Schieve,
Stuart K. Shapira
Publication year - 2018
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwx369
Subject(s) - hypospadias , autism spectrum disorder , etiology , medicine , genitourinary system , offspring , population , pediatrics , risk factor , autism , pregnancy , clinical psychology , psychiatry , genetics , environmental health , surgery , biology
Autism spectrum disorder (ASD) is a prevalent developmental disorder. Studies indicate that while ASD etiology has a genetic component, the risk is polygenic, with gene-environment interactions being likely. The prenatal period is a critical exposure window for nongenetic risk factors. Previous studies have found positive associations between congenital malformations (all types) and ASD; a few also found specific associations between genitourinary system malformations and ASD; and one study found an association between hypospadias and ASD. In the accompanying article, Rotem et al. (Am J Epidemiol. 2018;187(4):656-663) describe how they conducted a comprehensive analysis focusing on the shared risk of ASD with hypospadias or cryptorchidism, using existing data from a large Israeli health services system, which afforded several advantages because of the large sample size and low attrition of the patient population. The authors conducted a careful analysis, including sensitivity analyses, to account for risk factor and case misclassifications that might have occurred had they relied solely on preexisting diagnostic codes to define exposures and outcome. They observed positive associations between both hypospadias and cryptorchidism and ASD that were independent of numerous sociodemographic and pregnancy health factors. This study advances our understanding of ASD etiology and illustrates how existing data might be used to assess some ASD risk factors.

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