Cited by 77Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersChild Nutrition and Feeding Issues

Behavioral signatures related to genetic disorders in autism

Open access
Bruining, Hilgo, Eijkemans, Marinus JC, Kas, Martien JH, Curran, Sarah R, Vorstman, Jacob AS, Bolton, Patrick F·2014·Molecular Autism

Abstract

BACKGROUND: Autism spectrum disorder (ASD) is well recognized to be genetically heterogeneous. It is assumed that the genetic risk factors give rise to a broad spectrum of indistinguishable behavioral presentations. METHODS: We tested this assumption by analyzing the Autism Diagnostic Interview-Revised (ADI-R) symptom profiles in samples comprising six genetic disorders that carry an increased risk for ASD (22q11.2 deletion, Down's syndrome, Prader-Willi, supernumerary marker chromosome 15, tuberous sclerosis complex and Klinefelter syndrome; total n = 322 cases, groups ranging in sample sizes from 21 to 90 cases). We mined the data to test the existence and specificity of ADI-R profiles using a multiclass extension of support vector machine (SVM) learning. We subsequently applied the SVM genetic disorder algorithm on idiopathic ASD profiles from the Autism Genetics Resource Exchange (AGRE). RESULTS: Genetic disorders were associated with behavioral specificity, indicated by the accuracy and certainty of SVM predictions; one-by-one genetic disorder stratifications were highly accurate leading to 63% accuracy of correct genotype prediction when all six genetic disorder groups were analyzed simultaneously. Application of the SVM algorithm to AGRE cases indicated that the algorithm could detect similarity of genetic behavioral signatures in idiopathic ASD subjects. Also, affected sib pairs in the AGRE were behaviorally more similar when they had been allocated to the same genetic disorder group. CONCLUSIONS: Our findings provide evidence for genotype-phenotype correlations in relation to autistic symptomatology. SVM algorithms may be used to stratify idiopathic cases of ASD according to behavioral signature patterns associated with genetic disorders. Together, the results suggest a new approach for disentangling the heterogeneity of ASD.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/2040-2392-5-11

Cites

47 of 47 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Raven JC Colored Progressive Matrices Sets I and II 1995 Oxford: Oxford Psychologists Press Ltd
  2. Wechsler D Wechsler Adult Intelligence Scale-Third Edition 1997 San Antonio, TX: Psychological Corporation

Cited by

Sorted by citations

Authors
Bruining, H., Eijkemans, M. J., Kas, M. J., Curran, S. R., Vorstman, J. A., & Bolton, P. F.
Affiliations
  • University Medical Center Utrecht (NL)
  • King's College London (GB)
Corresponding author
Bruining, Hilgo
Venue
Molecular Autism
Published
2014
Volume
5
Issue
1
Pages
11
ISSN
2040-2392 (ISSN-L)
OpenAlex
W2123735083
Cited by
77
References
47
Citations by year
2025: 1 · 2024: 2 · 2023: 8 · 2022: 4 · 2021: 6 · 2020: 9 · 2019: 9 · 2018: 8 · 2017: 7 · 2016: 9 · 2015: 10 · 2014: 4
FWCI
5.53
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Molecular Autism (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Portal (King's College London) (publishedVersion, cc-by)
Funders
  • Autism Speaks
  • National Institute for Health and Care Research (NF-SI-0510-10268)
  • Tuberous Sclerosis Association
  • Medical Research Council
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
autism spectrum disorder, genetic disorders, behavioral signatures, genotype-phenotype correlation, 22q11.2 deletion syndrome, Down syndrome, Prader-Willi syndrome, tuberous sclerosis complex, Klinefelter syndrome, idiopathic autism, ASD heterogeneity, affected sib pairs, support vector machine classification

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review