Medical Conditions in the First Years of Life Associated with Future Diagnosis of ASD in Children

Alexeeff, Stacey; Yau, Vincent; Qian, Yinge; Davignon, Meghan N.; Lynch, Frances L.; Crawford, Phillip; Davis, Robert E.; Croen, Lisa

doi:10.1007/s10803-017-3130-4

Cited by 36 publications

(47 citation statements)

References 49 publications

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“…The prevalence of other conditions previously associated with ASD and common physical problems were examined in our study population and yield inconsistent results. While being in line with previous prevalence studies regarding higher rates of comorbid neurological problems and immunological dysregulations (Davignon et al 2018 ; Kohane et al 2012 ; Schendel et al 2016 ; Schieve et al 2012 ), our data revealed no evidence for an increase of infectious diseases and congenital cardiovascular abnormalities in autism (Alexeeff et al 2017 ; Timonen-Soivio et al 2015 ). However, the trend that individuals with autism were prone to have congenital heart malformations (non-significant after the Bonferroni correction) might be associated with somatic pleiotropy of ASD-related genetic variants (Vorstman et al 2017 ).…”

Section: Discussionsupporting

confidence: 92%

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

Pan¹,

Tammimies

Bölte³

2019

Behav Genet

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This study used a twin cohort to investigate the association of autism spectrum disorder (ASD) and autistic traits with somatic health. A total of 344 twins (172 pairs; mean age 15.56 ± 5.62 years) enriched for ASD and other neurodevelopmental conditions were examined. Medical history and current physical problems were collected with a validated questionnaire to determine twin's somatic health. The Social Responsiveness Scale (SRS-2) was used to measure the participant's severity of autistic traits. Identified somatic health issues with significant within-twin pair differences were tested in relation to both ASD diagnosis and autistic traits in a co-twin control model. Twins with ASD exhibited more neurological and immunological health problems compared to those without ASD (p = 0.005 and p = 0.004, respectively). The intra-pair differences of neurological conditions and SRS-2 score were significantly correlated in monozygotic twins differing for autism traits (r = 0.40, p = 0.001), while the correlation was not found for immunological problems. In addition, a conditional model for analysis of within-twin pair effects revealed an association between neurological problems and clinical ASD diagnosis (Odds ratio per neurological problem 3.15, p = 0.02), as well as autistic traits (β = 10.44, p = 0.006), after adjusting for possible effects of co-existing attention deficit hyperactivity disorder and general intellectual abilities. Our findings suggest that neurological problems are associated with autism, and that non-shared environmental factors contribute to the overlap for both clinical ASD and autistic traits. Further population-based twin studies are warranted to validate our results and examine in detailed the shared genetic and environmental contributions of neurological problems and ASD.

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Section: Discussionsupporting

confidence: 92%

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

Pan¹,

Tammimies

Bölte³

2019

Behav Genet

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“…Peripheral concentrations of cytokines and chemokines involved in the innate and adaptive immune responses vary in individuals already diagnosed with ASD compared to controls (3,4), though the prevalence of multiple disorders of the immune system (e.g., asthma, infections, allergy, autoimmune disorders) is also higher in individuals with ASD (5)(6)(7). Integrative analyses of genetic and transcriptomic data suggest that ASD and several of these commonly co-occurring conditions may be related via shared mechanisms involving innate immunity (8).…”

Section: Introductionmentioning

confidence: 99%

Neonatal Levels of Acute Phase Proteins and Risk of Autism Spectrum Disorder

Gardner

Lee

Brynge

et al. 2021

Biological Psychiatry

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…Lingren et al [] examined COC diagnoses in electronic health records from three clinical sites and used cluster analysis to identify subtypes of ASD in a pediatric population. Clustering based on medical conditions diagnosed prior to ASD diagnosis, including COCs, was also performed by Alexeeff et al [] to predict future ASD diagnosis risk from electronic health records and medical claims of health plan members aged 2–12 years old. There is thus great potential for using recorded healthcare data to study COC diagnosis patterns and characterize possible subtypes of ASD from these diagnoses.…”

Section: Introductionmentioning

confidence: 99%

Clustering of co‐occurring conditions in autism spectrum disorder during early childhood: A retrospective analysis of medical claims data

et al. 2019

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Individuals with autism spectrum disorder (ASD) are frequently affected by co-occurring medical conditions (COCs), which vary in severity, age of onset, and pathophysiological characteristics. The presence of COCs contributes to significant heterogeneity in the clinical presentation of ASD between individuals and a better understanding of COCs may offer greater insight into the etiology of ASD in specific subgroups while also providing guidance for diagnostic and treatment protocols. This study retrospectively analyzed medical claims data from a private United States health plan between years 2000 and 2015 to investigate patterns of COC diagnoses in a cohort of 3,278 children with ASD throughout their first 5 years of enrollment compared to 279,693 children from the general population without ASD diagnoses (POP cohort). Three subgroups of children with ASD were identified by k-means clustering using these COC patterns. The first cluster was characterized by generally high rates of COC diagnosis and comprised 23.7% (n = 776) of the cohort. Diagnoses of developmental delays were dominant in the second cluster containing 26.5% (n = 870) of the cohort. Children in the third cluster, making up 49.8% (n = 1,632) of the cohort, had the lowest rates of COC diagnosis, which were slightly higher than rates observed in the POP cohort. A secondary analysis using these data found that gastrointestinal and immune disorders showed similar longitudinal patterns of prevalence, as did seizure and sleep disorders. These findings may help to better inform the development of diagnostic workup and treatment protocols for COCs in children with ASD.Lay Summary: Medical conditions that co-occur with autism spectrum disorder (ASD) vary significantly from person to person. This study analyzed patterns in diagnosis of co-occurring conditions from medical claims data and observed three subtypes of children with ASD. These results may aid with screening for co-occurring conditions in children with ASD and with understanding ASD subtypes.

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Medical Conditions in the First Years of Life Associated with Future Diagnosis of ASD in Children

Cited by 36 publications

References 49 publications

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

Neonatal Levels of Acute Phase Proteins and Risk of Autism Spectrum Disorder

Clustering of co‐occurring conditions in autism spectrum disorder during early childhood: A retrospective analysis of medical claims data

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