Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder

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 cor...

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Main Authors: Avillach, P. (Author), De Niz, C. (Author), DeSain, T.N (Author), Fox, K.P (Author), Gutiérrez-Sacristán, A. (Author), Jalali, N. (Author), Kohane, I. (Author), Kumar, R. (Author), Palmer, N. (Author), Sáez, C. (Author), Zachariasse, J.M (Author)
Format: Article
Language:English
Published: NLM (Medline) 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 03858nam a2200601Ia 4500
001 10-1093-jamia-ocab144
008 220420s2022 CNT 000 0 und d
020 |a 1527974X (ISSN) 
245 1 0 |a Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder 
260 0 |b NLM (Medline)  |c 2022 
300 |a 9 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1093/jamia/ocab144 
520 3 |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. 
650 0 4 |a autism 
650 0 4 |a autism spectrum disorder 
650 0 4 |a Autism Spectrum Disorder 
650 0 4 |a child 
650 0 4 |a Child 
650 0 4 |a Child, Preschool 
650 0 4 |a comorbidity 
650 0 4 |a comorbidity 
650 0 4 |a Comorbidity 
650 0 4 |a female 
650 0 4 |a Female 
650 0 4 |a human 
650 0 4 |a Humans 
650 0 4 |a infant 
650 0 4 |a Infant 
650 0 4 |a Infant, Newborn 
650 0 4 |a large-scale 
650 0 4 |a male 
650 0 4 |a Male 
650 0 4 |a newborn 
650 0 4 |a odds ratio 
650 0 4 |a Odds Ratio 
650 0 4 |a preschool child 
650 0 4 |a prevalence 
650 0 4 |a Prevalence 
650 0 4 |a sex characteristics 
650 0 4 |a Sex Characteristics 
650 0 4 |a sexual characteristics 
700 1 0 |a Avillach, P.  |e author 
700 1 0 |a De Niz, C.  |e author 
700 1 0 |a DeSain, T.N.  |e author 
700 1 0 |a Fox, K.P.  |e author 
700 1 0 |a Gutiérrez-Sacristán, A.  |e author 
700 1 0 |a Jalali, N.  |e author 
700 1 0 |a Kohane, I.  |e author 
700 1 0 |a Kumar, R.  |e author 
700 1 0 |a Palmer, N.  |e author 
700 1 0 |a Sáez, C.  |e author 
700 1 0 |a Zachariasse, J.M.  |e author 
773 |t Journal of the American Medical Informatics Association : JAMIA