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10-1093-jamia-ocab144 |
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|a 1527974X (ISSN)
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|a Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder
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|b NLM (Medline)
|c 2022
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|a 9
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|z View Fulltext in Publisher
|u https://doi.org/10.1093/jamia/ocab144
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|a OBJECTIVE: To identify differences related to sex and define autism spectrum disorder (ASD) comorbidities female-enriched through a comprehensive multi-PheWAS intersection approach on big, real-world data. Although sex difference is a consistent and recognized feature of ASD, additional clinical correlates could help to identify potential disease subgroups, based on sex and age. MATERIALS AND METHODS: We performed a systematic comorbidity analysis on 1860 groups of comorbidities exploring all spectrum of known disease, in 59 140 individuals (11 440 females) with ASD from 4 age groups. We explored ASD sex differences in 2 independent real-world datasets, across all potential comorbidities by comparing (1) females with ASD vs males with ASD and (2) females with ASD vs females without ASD. RESULTS: We identified 27 different comorbidities that appeared significantly more frequently in females with ASD. The comorbidities were mostly neurological (eg, epilepsy, odds ratio [OR] > 1.8, 3-18 years of age), congenital (eg, chromosomal anomalies, OR > 2, 3-18 years of age), and mental disorders (eg, intellectual disability, OR > 1.7, 6-18 years of age). Novel comorbidities included endocrine metabolic diseases (eg, failure to thrive, OR = 2.5, ages 0-2), digestive disorders (gastroesophageal reflux disease: OR = 1.7, 6-11 years of age; and constipation: OR > 1.6, 3-11 years of age), and sense organs (strabismus: OR > 1.8, 3-18 years of age). DISCUSSION: A multi-PheWAS intersection approach on real-world data as presented in this study uniquely contributes to the growing body of research regarding sex-based comorbidity analysis in ASD population. CONCLUSIONS: Our findings provide insights into female-enriched ASD comorbidities that are potentially important in diagnosis, as well as the identification of distinct comorbidity patterns influencing anticipatory treatment or referrals. The code is publicly available (https://github.com/hms-dbmi/sexDifferenceInASD). © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.
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|a autism
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|a autism spectrum disorder
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|a Autism Spectrum Disorder
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|a child
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|a Child
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|a Child, Preschool
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|a comorbidity
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|a comorbidity
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|a Comorbidity
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|a female
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|a Female
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|a human
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|a Humans
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|a infant
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|a Infant
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|a Infant, Newborn
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|a large-scale
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|a male
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|a Male
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|a newborn
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|a odds ratio
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|a Odds Ratio
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|a preschool child
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|a prevalence
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|a Prevalence
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|a sex characteristics
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|a Sex Characteristics
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|a sexual characteristics
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|a Avillach, P.
|e author
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|a De Niz, C.
|e author
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|a DeSain, T.N.
|e author
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|a Fox, K.P.
|e author
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|a Gutiérrez-Sacristán, A.
|e author
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|a Jalali, N.
|e author
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|a Kohane, I.
|e author
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|a Kumar, R.
|e author
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|a Palmer, N.
|e author
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|a Sáez, C.
|e author
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|a Zachariasse, J.M.
|e author
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|t Journal of the American Medical Informatics Association : JAMIA
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