Autism spectrum disorder in Down syndrome: Cluster analysis of Aberrant Behaviour Checklist data supports diagnosis

N. Y. Ji, G. T. Capone, W. E. Kaufmann

Research output: Contribution to journalArticle

Abstract

Background The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Methods Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS+ASD, DS+None (no DSM diagnosis), DS+DBD (disruptive behaviour disorder) and DS+SMD (stereotypic movement disorder), the latter two as comparison groups. Results Two clusters were identified with DS+ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS+None (71.9%) and DS+DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS+SMD were relatively evenly distributed throughout the four clusters. Conclusions Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS+ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours.

Original languageEnglish (US)
Pages (from-to)1064-1077
Number of pages14
JournalJournal of Intellectual Disability Research
Volume55
Issue number11
DOIs
StatePublished - Nov 2011

Fingerprint

Pervasive Child Development Disorders
Down Syndrome
Checklist
Cluster Analysis
Down syndrome
Cognitive impairment
Diagnostics
Cluster analysis
Stereotypic Movement Disorder
Attention Deficit and Disruptive Behavior Disorders
Autistic Disorder
Intellectual Disability
Diagnostic and Statistical Manual of Mental Disorders
Pediatrics
Wounds and Injuries
Intellectual disability
Rating scales
Onset
Self-injury
Clinic

Keywords

  • Aberrant Behaviour Checklist
  • Autism spectrum disorder
  • Cluster analysis
  • Diagnostic and Statistical Manual of Mental Disorders
  • Down syndrome
  • Factor analysis

ASJC Scopus subject areas

  • Clinical Neurology
  • Neurology
  • Psychiatry and Mental health
  • Rehabilitation
  • Arts and Humanities (miscellaneous)

Cite this

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title = "Autism spectrum disorder in Down syndrome: Cluster analysis of Aberrant Behaviour Checklist data supports diagnosis",
abstract = "Background The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Methods Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS+ASD, DS+None (no DSM diagnosis), DS+DBD (disruptive behaviour disorder) and DS+SMD (stereotypic movement disorder), the latter two as comparison groups. Results Two clusters were identified with DS+ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS+None (71.9%) and DS+DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS+SMD were relatively evenly distributed throughout the four clusters. Conclusions Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS+ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours.",
keywords = "Aberrant Behaviour Checklist, Autism spectrum disorder, Cluster analysis, Diagnostic and Statistical Manual of Mental Disorders, Down syndrome, Factor analysis",
author = "Ji, {N. Y.} and Capone, {G. T.} and Kaufmann, {W. E.}",
year = "2011",
month = "11",
doi = "10.1111/j.1365-2788.2011.01465.x",
volume = "55",
pages = "1064--1077",
journal = "Journal of Intellectual Disability Research",
issn = "0964-2633",
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T2 - Journal of Intellectual Disability Research

AU - Ji,N. Y.

AU - Capone,G. T.

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N2 - Background The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Methods Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS+ASD, DS+None (no DSM diagnosis), DS+DBD (disruptive behaviour disorder) and DS+SMD (stereotypic movement disorder), the latter two as comparison groups. Results Two clusters were identified with DS+ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS+None (71.9%) and DS+DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS+SMD were relatively evenly distributed throughout the four clusters. Conclusions Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS+ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours.

AB - Background The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Methods Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS+ASD, DS+None (no DSM diagnosis), DS+DBD (disruptive behaviour disorder) and DS+SMD (stereotypic movement disorder), the latter two as comparison groups. Results Two clusters were identified with DS+ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS+None (71.9%) and DS+DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS+SMD were relatively evenly distributed throughout the four clusters. Conclusions Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS+ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours.

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