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Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort

View ORCID ProfileOliver Gale-Grant, Andrew Chew, Shona Falconer, View ORCID ProfileLucas G.S França, Sunniva Fenn-Moltu, Laila Hadaya, Nicholas Harper, Judit Ciarrusta, Tony Charman, Declan Murphy, Tomoki Arichi, Grainne McAlonan, View ORCID ProfileChiara Nosarti, View ORCID ProfileA David Edwards, View ORCID ProfileDafnis Batalle
doi: https://doi.org/10.1101/2022.09.26.508121
Oliver Gale-Grant
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
3MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
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  • ORCID record for Oliver Gale-Grant
  • For correspondence: oliver.gale-grant@kcl.ac.uk
Andrew Chew
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
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Shona Falconer
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
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Lucas G.S França
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
4Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, United Kingdom
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  • ORCID record for Lucas G.S França
Sunniva Fenn-Moltu
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
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Laila Hadaya
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
5Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
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Nicholas Harper
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
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Judit Ciarrusta
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
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Tony Charman
6Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
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Declan Murphy
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
3MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
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Tomoki Arichi
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
3MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
7Department of Paediatric Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, United Kingdom
8Department of Bioengineering, Imperial College London, United Kingdom
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Grainne McAlonan
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
3MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
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Chiara Nosarti
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
5Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
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A David Edwards
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
3MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
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Dafnis Batalle
1Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
2Centre for the Developing Brain, School of Imaging Sciences & Biomedical Engineering, King’s College London, United Kingdom
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Abstract

Background Autism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment.

Methods Clinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA).

Results A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score.

Limitations The Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses.

Conclusions Autism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Figures altered, introduction and discussion substantially altered.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 12, 2023.
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Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort
Oliver Gale-Grant, Andrew Chew, Shona Falconer, Lucas G.S França, Sunniva Fenn-Moltu, Laila Hadaya, Nicholas Harper, Judit Ciarrusta, Tony Charman, Declan Murphy, Tomoki Arichi, Grainne McAlonan, Chiara Nosarti, A David Edwards, Dafnis Batalle
bioRxiv 2022.09.26.508121; doi: https://doi.org/10.1101/2022.09.26.508121
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Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort
Oliver Gale-Grant, Andrew Chew, Shona Falconer, Lucas G.S França, Sunniva Fenn-Moltu, Laila Hadaya, Nicholas Harper, Judit Ciarrusta, Tony Charman, Declan Murphy, Tomoki Arichi, Grainne McAlonan, Chiara Nosarti, A David Edwards, Dafnis Batalle
bioRxiv 2022.09.26.508121; doi: https://doi.org/10.1101/2022.09.26.508121

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