Dataset Information

Exploring Sensory Subgroups in Typical Development and Autism Spectrum Development Using Factor Mixture Modelling.

ABSTRACT: This study uses factor mixture modelling of the Short Sensory Profile (SSP) at two time points to describe subgroups of young autistic and typically-developing children. This approach allows separate SSP subscales to influence overall SSP performance differentially across subgroups. Three subgroups were described, one including almost all typically-developing participants plus many autistic participants. SSP performance of a second, largely-autistic subgroup was predominantly shaped by a subscale indexing behaviours of low energy/weakness. Finally, the third subgroup, again largely autistic, contained participants with low (or more "atypical") SSP scores across most subscales. In this subgroup, autistic participants exhibited large P1 amplitudes to loud sounds. Autistic participants in subgroups with more atypical SSP scores had higher anxiety and more sleep disturbances.

SUBMITTER: Dwyer P

PROVIDER: S-EPMC9349169 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Exploring Sensory Subgroups in Typical Development and Autism Spectrum Development Using Factor Mixture Modelling.

Dwyer Patrick P Ferrer Emilio E Saron Clifford D CD Rivera Susan M SM

Journal of autism and developmental disorders 20210909 9

This study uses factor mixture modelling of the Short Sensory Profile (SSP) at two time points to describe subgroups of young autistic and typically-developing children. This approach allows separate SSP subscales to influence overall SSP performance differentially across subgroups. Three subgroups were described, one including almost all typically-developing participants plus many autistic participants. SSP performance of a second, largely-autistic subgroup was predominantly shaped by a subscal ...[more]

PMID: 34499275

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Project description:BackgroundHeterogeneity in the phenotypic presentation of autism spectrum disorder (ASD) is apparent in the profile and the severity of sensory features. Here, we applied factor mixture modelling (FMM) to test a multidimensional factor model of sensory processing in ASD. We aimed to identify homogeneous sensory subgroups in ASD that differ intrinsically in their severity along continuous factor scores. We also investigated sensory subgroups in relation to clinical variables: sex, age, IQ, social-communication symptoms, restricted and repetitive behaviours, adaptive functioning and symptoms of anxiety and attention-deficit/hyperactivity disorder.MethodsThree hundred thirty-two children and adults with ASD between the ages of 6 and 30 years with IQs varying between 40 and 148 were included. First, three different confirmatory factor models were fit to the 38 items of the Short Sensory Profile (SSP). Then, latent class models (with two-to-six subgroups) were evaluated. The best performing factor model, the 7-factor structure, was subsequently used in two FMMs that varied in the number of subgroups: a two-subgroup, seven-factor model and a three-subgroup and seven-factor model.ResultsThe 'three-subgroup/seven-factor' FMM was superior to all other models based on different fit criteria. Identified subgroups differed in sensory severity from severe, moderate to low. Accounting for the potential confounding effects of age and IQ, participants in these sensory subgroups had different levels of social-communicative symptoms, restricted and repetitive behaviours, adaptive functioning skills and symptoms of inattention and anxiety.LimitationsResults were derived using a single parent-report measure of sensory features, the SSP, which limits the generalisability of findings.ConclusionSensory features can be best described by three homogeneous sensory subgroups that differ in sensory severity gradients along seven continuous factor scores. Identified sensory subgroups were further differentiated by the severity of core and co-occurring symptoms, and level of adaptive functioning, providing novel evidence on the associated clinical correlates of sensory subgroups. These sensory subgroups provide a platform to further interrogate the neurobiological and genetic correlates of altered sensory processing in ASD.

Project description:BackgroundAtypical reactions to the sensory environment are often reported in autistic individuals, with a high degree of variability across the sensory modalities. These sensory differences have been shown to promote challenging behaviours and distress in autistic individuals and are predictive of other functions including motor, social, and cognitive abilities. Preliminary research suggests that specific sensory differences may cluster together within individuals creating discrete sensory phenotypes. However, the manner in which these sensory differences cluster, and whether the resulting phenotypes are associated with specific cognitive and social challenges is unclear.MethodsShort sensory profile data from 599 autistic children and adults between the ages of 1 and 21 years were subjected to a K-means cluster analysis. Analysis of variances compared age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder across the resultant clusters.ResultsA five-cluster model was found to minimize error variance and produce five sensory phenotypes: (1) sensory adaptive, (2) generalized sensory differences, (3) taste and smell sensitivity, (4) under-responsive and sensation seeking, and (5) movement difficulties with low energy. Age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder were found to differ significantly across the five phenotypes.LimitationsThe results were based on parent-report measures of sensory processing, adaptive behaviour, traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder, which may limit the generalizability of the findings. Further, not all measures are standardized, or psychometrically validated with an autism population. Autistic individuals with an intellectual disability were underrepresented in this sample. Further, as these data were obtained from established records from a large provincial database, not all measures were completed for all individuals.ConclusionsThese findings suggest that sensory difficulties in autistic individuals can be clustered into sensory phenotypes, and that these phenotypes are associated with behavioural differences. Given the large degree of heterogeneity in sensory difficulties seen in the autistic population, these sensory phenotypes represent an effective way to parse that heterogeneity and create phenotypes that may aid in the development of effective treatments and interventions for sensory difficulties.

Project description:Individuals with autism spectrum disorder (ASD) have heterogeneous comorbid conditions. This study examined whether comorbid conditions in ASD are associated with polygenic risk scores (PRS) of ASD or PRS of comorbid conditions in non-ASD specific populations. Genome-wide single nucleotide polymorphism (SNP) data were obtained from 1386 patients with ASD from the Autism Genetic Resource Exchange (AGRE) study. After excluding individuals with missing clinical information concerning comorbid conditions, a total of 707 patients were included in the study. A total of 18 subgroups of comorbid conditions ('topics') were identified using a machine learning algorithm, topic modeling. PRS for ASD were computed using a genome-wide association meta-analysis of 18,381 cases and 27,969 controls. From these 18 topics, Topic 6 (over-represented by allergies) (p = 1.72 × 10-3) and Topic 17 (over-represented by sensory processing issues such as low pain tolerance) (p = 0.037) were associated with PRS of ASD. The associations between these two topics and the multi-locus contributors to their corresponding comorbid conditions based on non-ASD specific populations were further explored. The results suggest that these two topics were not associated with the PRS of allergies and chronic pain disorder, respectively. Note that characteristics of the present AGRE sample and those samples used in the original GWAS for ASD, allergies, and chronic pain disorder, may differ due to significant clinical heterogeneity that exists in the ASD population. Additionally, the AGRE sample may be underpowered and therefore insensitive to weak PRS associations due to a relatively small sample size. Findings imply that susceptibility genes of ASD may contribute more to the occurrence of allergies and sensory processing issues in individuals with ASD, compared with the susceptibility genes for their corresponding phenotypes in non-ASD individuals. Since these comorbid conditions (i.e., allergies and pain sensory issues) may not be attributable to the corresponding comorbidity-specific biological factors in non-ASD individuals, clinical management for these comorbid conditions may still depend on treatments for core symptoms of ASD.

Dataset Information

Exploring Sensory Subgroups in Typical Development and Autism Spectrum Development Using Factor Mixture Modelling.

Publications

Exploring Sensory Subgroups in Typical Development and Autism Spectrum Development Using Factor Mixture Modelling.

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