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Cited by 109Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersChild Nutrition and Feeding Issues

The distribution of autistic traits across the autism spectrum: evidence for discontinuous dimensional subpopulations underlying the autism continuum

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Abu-Akel, Ahmad, Allison, Carrie, Baron-Cohen, Simon, Heinke, Dietmar·2019·Molecular Autism
DOI 10.1186/s13229-019-0275-3PMC PMC6537408
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Abstract

Background: A considerable amount of research has discussed whether autism and psychiatric/neurodevelopmental conditions in general are best described categorically or dimensionally. In recent years, finite mixture models have been increasingly applied to mixed populations of autistic and non-autistic individuals to answer this question. However, the use of such methods with mixed populations may not be appropriate for two reasons: First, subgroups within mixed populations are often skewed and thus violate mixture models assumptions, which are based on weighted sum of Gaussian distributions. Second, these analyses have, to our knowledge, been solely applied to enriched samples, where the prevalence of the clinical condition within the study sample far exceeds epidemiological estimates. Method: = 3973; autism = 67) that reflects the current prevalence of autism within the general population. Results: In a mixed autistic and non-autistic population, our model provided a better description of the underlying structure of autistic traits than traditional finite Gaussian mixture models and performed well when applied to a sample that reflected the prevalence of autism in the general population. The model yielded results, which are consistent with predictions of current theories advocating for the co-existence of a mixed categorical and dimensional architecture within the autism spectrum. Conclusion: The results provide insight into the continuum nature of the distribution of autistic traits, support the complementary role of both categorical and dimensional approaches to autism spectrum condition, and underscore the importance of analyzing samples that reflect the epidemiological prevalence of the condition. Owing to its flexibility to represent a wide variety of distributions, the Weibull distribution might be better suited for latent structure studies, within enriched and prevalence-true samples.

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Authors
Abu-Akel, A., Allison, C., Baron-Cohen, S., & Heinke, D.
Affiliations
  • University of Lausanne (CH)
  • University of Cambridge (GB)
  • University of Birmingham (GB)
Corresponding author
Abu-Akel, Ahmad
ORCID
Venue
Molecular Autism
Publisher
Springer Science and Business Media LLC
Published
2019-05-27
Volume
10
Issue
1
Pages
24-24
ISSN
2040-2392 (ISSN-L)
DOI
10.1186/s13229-019-0275-3
PMC
PMC6537408
OpenAlex
W2947083223
Cited by
109
References
59
Citations by year
2026: 14 · 2025: 22 · 2024: 21 · 2023: 18 · 2022: 10 · 2021: 12 · 2020: 10 · 2019: 2
FWCI
4.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Autism (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • SERVAL (Université de Lausanne) (publishedVersion, cc-by)
  • IRIS (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo (cc-by)
Funders
Innovative Medicines Initiative (777394)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Health Sciences › Medicine › Psychiatry and Mental health › Child Nutrition and Feeding Issues
Keywords
autistic traits, autism spectrum disorder, mixture models, Weibull distribution, latent structure
MeSH terms
Autism Spectrum Disorder, Adolescent, Adult, Aged, Female, Humans, Male, Middle Aged, Population Dynamics, Models, Statistical, Prevalence, Young Adult

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