The development of autism spectrum disorders: variability and causal complexity

Wozniak, Robert H.; Leezenbaum, Nina B.; Northrup, Jessie B.; West, Kelsey L.; Iverson, Jana M.

doi:10.1002/wcs.1426

Cited by 71 publications

(45 citation statements)

References 64 publications

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“…Given the inability for any one cognitive theory to account for all differences in presentation and the identification of many genes linked to autism, it is now proposed that, rather than a single cause, there are multiple pathways for multiple conditions (autisms), which share phenotypic similarities consistent with a diagnosis of autism but reflect the heterogeneity of the disorder . This conceptualisation is, however, not adequately explained by our current diagnostic classification systems.…”

Section: How Do We Move Towards Precision Medicine For Children With mentioning

confidence: 99%

Autism: One or many spectrums?

Ure

Rose

Bernie

et al. 2018

J Paediatrics Child Health

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Our conceptualisation of autism spectrum disorder has changed over time, with recent classifications reflecting a heterogeneous clinical presentation now regularly encountered in routine general paediatric practice. As the prevalence of autism and associated demands for services have increased so has research into understanding the cause and trials aimed at providing best care and intervention. However, the heterogeneity of autism has meant that no single aetiology can account for all differences in presentation, and not all children benefit from broad‐based interventions. Now is the time to rethink how best to understand individual differences in order to focus research efforts and take steps towards more sophisticated strategies that go beyond the behaviours we look for when making an autism diagnosis. We suggest adopting a dimensional approach to autism assessment, with the consideration of eight spectrums of abilities, ways of thinking and behaviour. This eight‐spectrum approach will assist clinicians to consider each individual's strengths and needs and personalise interventions and support accordingly. Profiling individual skills across these dimensions may also provide researchers with a greater capacity to link causal pathways with specific phenotypes, which is needed to develop precision medicine for autism.

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Section: How Do We Move Towards Precision Medicine For Children With mentioning

confidence: 99%

Autism: One or many spectrums?

Ure

Rose

Bernie

et al. 2018

J Paediatrics Child Health

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“…Recent epidemiological studies suggest that one in 59 children are diagnosed with ASD (Baio et al 2018). While genetic, environmental, and prenatal/perinatal factors have been implicated in ASD (Fiorentino et al 2016; Wozniak et al 2017), the etiology of the disorder remains largely unknown and no convincing biomarkers of ASD have been identified (Molloy et al 2006; Lyall et al 2017; Akintunde et al 2015). Disturbances in immunoinflammatory factors and adipocytokines have been observed in subjects with ASD (Molloy et al 2006; Ghaffari et al 2016).…”

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confidence: 99%

Cord and Early Childhood Plasma Adiponectin Levels and Autism Risk: A Prospective Birth Cohort Study

Raghavan

Fallin

Hong

et al. 2018

J Autism Dev Disord

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Emerging research suggests that adiponectin, a cytokine produced by adipose tissue, may be implicated in ASD. In this prospective birth cohort study (n = 847), we assessed the association between cord, early childhood plasma adiponectin and the risk of developing ASD. ASD was defined based on ICD codes of physician diagnosis. Cord adiponectin levels were inversely associated with ASD risk (aOR 0.50; 95% CI 0.33, 0.77), independent of preterm birth, early childhood adiponectin and other known ASD risk factors. Early childhood adiponectin, assessed prior to ASD diagnosis, was associated with lower risk of ASD, which attenuated after adjusting for cord adiponectin, indicating the relative importance of cord adiponectin in ASD risk. Further research is warranted to confirm our findings and elucidate biological mechanisms.

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“…ASDs are a group of neurodevelopmental disorders that frequently result in dysfunctional social interaction and communication, repetitive or disruptive behaviors, and narrow interests. Remarkably, the number and severity of symptoms are highly variable across individuals in the autism spectrum (Hu & Steinberg, ; Wozniak, Leezenbaum, Northrup, West, & Iverson, ), making it difficult to understand and characterize their cognitive and behavioral profiles. This heterogeneity is a major problem in developing a unifying theory of autism (Markram, Rinaldi, & Markram, ).…”

Section: Introductionmentioning

confidence: 99%

Atypical shape bias and categorization in autism: Evidence from children and computational simulations

Tovar

Rodríguez-Granados

Arias‐Trejo

2019

Developmental Science

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The shape bias, a preference for mapping new word labels onto the shape rather than the color or texture of referents, has been postulated as a word‐learning mechanism. Previous research has shown deficits in the shape bias in children with autism even though they acquire sizeable lexicons. While previous explanations have suggested the atypical use of color for label extension in individuals with autism, we hypothesize an atypical mapping of novel labels to novel objects, regardless of the physical properties of the objects. In Experiment 1, we demonstrate this phenomenon in some individuals with autism, but the novelty of objects only partially explains their lack of shape bias. In a second experiment, we present a computational model that provides a developmental account of the shape bias in typically developing children and in those with autism. This model is based on theories of neurological dysfunctions in autism, and it integrates theoretical and empirical findings in the literature of categorization, word learning, and the shape bias. The model replicates the pattern of results of our first experiment and shows how individuals with autism are more likely to categorize experimental objects together on the basis of their novelty. It also provides insights into possible mechanisms by which children with autism learn new words, and why their word referents may be idiosyncratic. Our model highlights a developmental approach to autism that emphasizes deficient representations of categories underlying an impaired shape bias.

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The development of autism spectrum disorders: variability and causal complexity

Cited by 71 publications

References 64 publications

Autism: One or many spectrums?

Autism: One or many spectrums?

Cord and Early Childhood Plasma Adiponectin Levels and Autism Risk: A Prospective Birth Cohort Study

Atypical shape bias and categorization in autism: Evidence from children and computational simulations

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