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Heterogeneity within Autism Spectrum Disorders: What have We Learned from Neuroimaging Studies?

ABSTRACT: Autism spectrum disorders (ASD) display significant heterogeneity. Although most neuroimaging studies in ASD have been designed to identify commonalities among affected individuals, rather than differences, some studies have explored variation within ASD. There have been two general types of approaches used for this in the neuroimaging literature to date: comparison of subgroups within ASD, and analyses using dimensional measures to link clinical variation to brain differences. This review focuses on structural and functional magnetic resonance imaging studies that have used these approaches to begin to explore heterogeneity between individuals with ASD. Although this type of data is yet sparse, recognition is growing of the limitations of behaviorally defined categorical diagnoses for understanding neurobiology. Study designs that are more informative regarding the sources of heterogeneity in ASD have the potential to improve our understanding of the neurobiological processes underlying ASD.

SUBMITTER: Lenroot RK

PROVIDER: S-EPMC3812662 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Heterogeneity within Autism Spectrum Disorders: What have We Learned from Neuroimaging Studies?

Lenroot Rhoshel K RK Yeung Pui Ka PK

Frontiers in human neuroscience 20131030

Autism spectrum disorders (ASD) display significant heterogeneity. Although most neuroimaging studies in ASD have been designed to identify commonalities among affected individuals, rather than differences, some studies have explored variation within ASD. There have been two general types of approaches used for this in the neuroimaging literature to date: comparison of subgroups within ASD, and analyses using dimensional measures to link clinical variation to brain differences. This review focus ...[more]

PMID: 24198778

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Project description:BACKGROUND: The etiology of autism spectrum disorders (ASD) is largely determined by different genetic factors of variable impact. This genetic heterogeneity could be a factor to explain the clinical heterogeneity of autism spectrum disorders. Here, a first attempt is made to assess whether genetically more homogeneous ASD groups are associated with decreased phenotypic heterogeneity with respect to their autistic symptom profile. METHODOLOGY: The autistic phenotypes of ASD subjects with 22q11 deletion syndrome (22q11DS) and ASD subjects with Klinefelter Syndrome (KS) were statistically compared to the symptom profile of a large (genetically) heterogeneous ASD sample. Autism diagnostic interview-revised (ADI-R) variables were entered in different statistical analyses to assess differences in symptom homogeneity and the feasibility of discrimination of group-specific ASD-symptom profiles. PRINCIPAL FINDINGS: The results showed substantially higher symptom homogeneity in both the genetic disorder ASD groups in comparison to the heterogeneous ASD sample. In addition, a robust discrimination between 22q11-ASD and KS-ASD and idiopathic ASD phenotypes was feasible on the basis of a reduced number of autistic scales and symptoms. The lack of overlap in discriminating subscales and symptoms between KS-ASD and 22q11DS-ASD suggests that their autistic symptom profiles cluster around different points in the total diagnostic space of profiles present in the general ASD population. CONCLUSION: The findings of the current study indicate that the clinical heterogeneity of ASDs may be reduced when subgroups based on a specific genotype are extracted from the idiopathic ASD population. The current strategy involving the widely used ADI-R offers a relatively straightforward possibility for assessing genotype-phenotype ASD relationships. Reverse phenotype strategies are becoming more feasible, given the accumulating evidence for the existence of genetic variants of large effect in a substantial proportion of the ASD population.

Project description:BackgroundThe etiology of Autism Spectrum Disorder (ASD) has been recently debated due to emerging findings on the importance of shared environmental influences. However, two recent twin studies do not support this and instead re-affirm strong genetic effects on the liability to ASD, a finding consistent with previous reports. This study conducts a systematic review and meta-analysis of all twin studies of ASD published to date and explores the etiology along the continuum of a quantitative measure of ASD.MethodsA PubMed Central, Science Direct, Google Scholar, Web of Knowledge structured search conducted online, to identify all twin studies on ASD published to date. Thirteen primary twin studies were identified, seven were included in the meta-analysis by meeting Systematic Recruitment criterion; correction for selection and ascertainment strategies, and applied prevalences were assessed for these studies. In addition, a quantile DF extremes analysis was carried out on Childhood Autism Spectrum Test scores measured in a population sample of 6,413 twin pairs including affected twins.ResultsThe meta-analysis correlations for monozygotic twins (MZ) were almost perfect at .98 (95% Confidence Interval, .96-.99). The dizygotic (DZ) correlation, however, was .53 (95% CI .44-.60) when ASD prevalence rate was set at 5% (in line with the Broad Phenotype of ASD) and increased to .67 (95% CI .61-.72) when applying a prevalence rate of 1%. The meta-analytic heritability estimates were substantial: 64-91%. Shared environmental effects became significant as the prevalence rate decreased from 5-1%: 07-35%. The DF analyses show that for the most part, there is no departure from linearity in heritability.ConclusionsWe demonstrate that: (a) ASD is due to strong genetic effects; (b) shared environmental effects become significant as a function of lower prevalence rate; (c) previously reported significant shared environmental influences are likely a statistical artefact of overinclusion of concordant DZ twins.

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Heterogeneity within Autism Spectrum Disorders: What have We Learned from Neuroimaging Studies?

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Heterogeneity within Autism Spectrum Disorders: What have We Learned from Neuroimaging Studies?

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