Time to give up on a single explanation of autism

Francesca Happé, Angelica Ronald and Robert Plomin are at the Institute of Psychiatry, Kings College London, De Crispigny Park, London SE5 8AF, UK.
Nature Neuroscience (Impact Factor: 16.1). 11/2006; 9(10):1218-20. DOI: 10.1038/nn1770
Source: PubMed


We argue that there will be no single (genetic or cognitive) cause for the diverse symptoms defining autism. We present recent evidence of behavioral fractionation of social impairment, communication difficulties and rigid and repetitive behaviors. Twin data suggest largely nonoverlapping genes acting on each of these traits. At the cognitive level, too, attempts at a single explanation for the symptoms of autism have failed. Implications for research and treatment are discussed.

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    • "In their 2006 review that stressed the fractionable nature of autism, Happé and colleagues stated that ''Heterogeneity within the autism spectrum…is an unavoidable consequence of variation along at least three largely independent (although of course interacting) dimensions of impairment.'' (Happe et al. 2006). These researchers were referring to the DSM- IV triad of social deficit, language and communication atypicality, and restricted interests/repetitive behaviors. "
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    ABSTRACT: A network conceptualization might contribute to understanding the occurrence and interacting nature of behavioral traits in the autism realm. Networks were constructed based on correlations of item scores of the Autism Diagnostic Observation Schedule for Modules 1, 2 and 3 obtained for a group of 477 Dutch individuals with developmental disorders. After combining Modules, networks were obtained and compared for male versus female, high- versus low-functioning, seizure versus non-seizure, autism spectrum disorder versus intellectual disability, and younger versus older subjects. The network visualizations and calculated network parameters provide new perspectives that generate new hypothesis and suggest follow-up studies. The approach should be useful in characterizing individuals and groups, in elucidating mechanisms of trait generation and routes to outcome phenotypes, and in suggesting points of intervention.
    Journal of Autism and Developmental Disorders 07/2015; 45(10). DOI:10.1007/s10803-015-2537-z · 3.06 Impact Factor
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    • "In view of the heterogeneity within the ASD population (Happé et al. 2006), the investigation of non-core deficits that are associated with core socio-communicative impairments plays an important role in therapeutic development and refinement. The role of motor and sensory impairments in ASD has become increasingly appreciated in recent years (Gowen and Hamilton 2013; Marco et al. 2011). "
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    ABSTRACT: Impairments in sensorimotor integration are reported in Autism Spectrum Disorder (ASD). Poor control of balance in challenging balance tasks is one suggested manifestation of these impairments, and is potentially related to ASD symptom severity. Reported balance and symptom severity relationships disregard age as a potential covariate, however, despite its involvement in balance development. We tested balance control during increasingly difficult balance conditions in children with ASD and typically developing peers, and investigated relationships between balance control and diagnostic/symptom severity metrics for participants with ASD, including age as a covariate. Balance deficits in ASD were exacerbated by stance alterations, but were not related to symptom severity when age was considered. These findings support impaired balance in ASD, especially in challenging conditions, but question a link between balance and symptom severity.
    Journal of Autism and Developmental Disorders 11/2014; 45(5). DOI:10.1007/s10803-014-2303-7 · 3.34 Impact Factor
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    • "This continuum view shifts us away from merely categorical diagnosis towards the quantitative support of daily difficulties associated with autism spectrum traits of each individual regardless of ASD diagnosis. Taking the quantitative support into consideration necessitates the use of an instrument that can quantify autism spectrum traits in the entire population; such an instrument could also be used to define the broader autism phenotype [8,9]. "
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    ABSTRACT: Autism spectrum traits are postulated to lie on a continuum that extends between individuals with autism and individuals with typical development (TD). Social cognition properties that are deeply associated with autism spectrum traits have been linked to functional connectivity between regions within the brain’s default mode network (DMN). Previous studies have shown that the resting-state functional connectivities (rs-FCs) of DMN are low and show negative correlation with the level of autism spectrum traits in individuals with autism spectrum disorder (ASD). However, it is unclear whether individual differences of autism spectrum traits are associated with the strength of rs-FCs of DMN in participants including the general population. Using the seed-based approach, we investigated the rs-FCs of DMN, particularly including the following two core regions of DMN: the anterior medial prefrontal cortex (aMPFC) and posterior cingulate cortex (PCC) in 19 young male adults with high-functioning ASD (mean age = 25.3 ± 6.9 years; autism-spectrum quotient (AQ) = 33.4 ± 4.2; full scale IQ (F-IQ) = 109.7 ± 12.4) compared with 21 age- and IQ-matched young male adults from the TD group (mean age = 24.8 ± 4.3 years; AQ = 18.6 ± 5.7; F-IQ = 109.5 ± 8.7). We also analyzed the correlation between the strength of rs-FCs and autism spectrum traits measured using AQ score. The strengths of rs-FCs from core regions of DMN were significantly lower in ASD participants than TD participants. Under multiple regression analysis, the strengths of rs-FCs in brain areas from aMPFC seed showed negative correlation with AQ scores in ASD participants and TD participants. Our findings suggest that the strength of rs-FCs in DMN is associated with autism spectrum traits in the TD population as well as patients with ASD, supporting the continuum view. The rs-FCs of DMN may be useful biomarkers for the objective identification of autism spectrum traits, regardless of ASD diagnosis.
    Molecular Autism 11/2014; 5(2):35. DOI:10.1186/2040-2392-5-35 · 5.41 Impact Factor
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