Short report: Social communication difficulties and restricted repetitive behaviors as predictors of anxiety in adults with autism spectrum disorder

Kuzminskaite, Erika; Begeer, Sander; Hoekstra, Rosa A.; Grove, Rachel

doi:10.1177/1362361320934218

Cited by 16 publications

(6 citation statements)

References 26 publications

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“…However, the precise reason is unknown due to its complex biological and psychological mechanism ( 59 ). In addition to impairing intelligence, RRBs can impair the physical and mental health of individuals with autism ( 59 ), affect social and daily living skills in children ( 60 ) and adolescents ( 61 ), and predict the onset of anxiety ( 62 , 63 ). Fortunately, the severity of repetitive stereotypes can be alleviated through intervention training ( 64 ), but whether RRB intervention can improve IQ levels requires further research.…”

Section: Discussionmentioning

confidence: 99%

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

Song

Jiang

et al. 2022

Front. Psychiatry

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BackgroundEarly detection of children with autism spectrum disorder (ASD) and comorbid intellectual disability (ID) can help in individualized intervention. Appropriate assessment and diagnostic tools are lacking in primary care. This study aims to explore the applicability of machine learning (ML) methods in diagnosing ASD comorbid ID compared with traditional regression models.MethodFrom January 2017 to December 2021, 241 children with ASD, with an average age of 6.41 ± 1.96, diagnosed in the Developmental Behavior Department of the Children’s Hospital Affiliated with the Medical College of Zhejiang University were included in the analysis. This study trained the traditional diagnostic models of Logistic regression (LR), Support Vector Machine (SVM), and two ensemble learning algorithms [Random Forest (RF) and XGBoost]. Socio-demographic and behavioral observation data were used to distinguish whether autistic children had combined ID. The hyperparameters adjustment uses grid search and 10-fold validation. The Boruta method is used to select variables. The model’s performance was evaluated using discrimination, calibration, and decision curve analysis (DCA).ResultAmong 241 autistic children, 98 (40.66%) were ASD comorbid ID. The four diagnostic models can better distinguish whether autistic children are complicated with ID, and the accuracy of SVM is the highest (0.836); SVM and XGBoost have better accuracy (0.800, 0.838); LR has the best sensitivity (0.939), followed by SVM (0.952). Regarding specificity, SVM, RF, and XGBoost performed significantly higher than LR (0.355). The AUC of ML (SVM, 0.835 [95% CI: 0.747–0.944]; RF, 0.829 [95% CI: 0.738–0.920]; XGBoost, 0.845 [95% CI: 0.734–0.937]) is not different from traditional LR (0.858 [95% CI: 0.770–0.944]). Only SVM observed a good calibration degree. Regarding DCA, LR, and SVM have higher benefits in a wider threshold range.ConclusionCompared to the traditional regression model, ML model based on socio-demographic and behavioral observation data, especially SVM, has a better ability to distinguish whether autistic children are combined with ID.

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Section: Discussionmentioning

confidence: 99%

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

Song

Jiang

et al. 2022

Front. Psychiatry

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“…ASD and anxiety are highly comorbid conditions, and children with ASD have increased susceptibility to anxiety disorders [ 24 , 25 ]. Researchers have assessed the increased risk of anxiety among individuals with ASD and found that they suffered from both common anxiety and ASD-related anxiety, which were less common in the nonautistic group [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Divergent projections of the prelimbic cortex mediate autism- and anxiety-like behaviors

Luo

Song

et al. 2023

Mol Psychiatry

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The comorbidity of autism spectrum disorder and anxiety is common, but the underlying circuitry is poorly understood. Here, Tmem74-/- mice showed autism- and anxiety-like behaviors along with increased excitability of pyramidal neurons (PNs) in the prelimbic cortex (PL), which were reversed by Tmem74 re-expression and chemogenetic inhibition in PNs of the PL. To determine the underlying circuitry, we performed conditional deletion of Tmem74 in the PNs of PL of mice, and we found that alterations in the PL projections to fast-spiking interneurons (FSIs) in the dorsal striatum (dSTR) (PLPNs–dSTRFSIs) mediated the hyperexcitability of FSIs and autism-like behaviors and that alterations in the PL projections to the PNs of the basolateral amygdaloid nucleus (BLA) (PLPNs–BLAPNs) mediated the hyperexcitability of PNs and anxiety-like behaviors. However, the two populations of PNs in the PL had different spatial locations, optogenetic manipulations revealed that alterations in the activity in the PL–dSTR or PL–BLA circuits led to autism- or anxiety-like behaviors, respectively. Collectively, these findings highlight that the hyperactivity of the two populations of PNs in the PL mediates autism and anxiety comorbidity through the PL–dSTR and PL–BLA circuits, which may lead to the development of new therapeutics for the autism and anxiety comorbidity.

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“…Maar ook bij de groep waarbij beperkingen minder zichtbaar zijn, vinden we veel problemen. De volwassenen die wij volgen, zijn over het algemeen gemiddeld tot hoogopgeleid, maar vaak werkloos, ze rapporteren een lager welbevinden, slaapproblemen, angst, stemmingsproblemen en zelfs suïcidaliteit [51][52][53][54] . En ook de fysieke problemen zijn groot.…”

Section: Slide Prikkelverwerkingunclassified

Achter de Spiegel: Het spectrum van autisme

Begeer¹

2022

WTA

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Oratie Sander Begeer Gehouden op 20-5-2022 aan de Vrije Universiteit Amsterdam Geachte aanwezigen, Nadat de titel van deze oratie bekend werd, kreeg ik al snel vragen van mensen met een autismediagnose. ‘Wiens spiegel?’ ‘En waarom achter de spiegel en niet ervoor?’ Aan het eind van deze oratie zal ik antwoord geven op deze vragen. Deze interactie kenmerkt echter ons huidige werk. Vroeger praatten we vooral over autisme, tegenwoordig praten we veel meer met mensen met autisme. Op allerlei manieren zijn zij betrokken bij onderzoek en onderwijs, en soms zijn ze zelf de onderzoeker of docent. Dit is inspirerend en maakt het werk veel relevanter. Bijvoorbeeld met de vraag over taal. Welke taal gebruiken we om autisme te beschrijven? Is het iets dat je hebt, of dat je bent? Het lijkt misschien een triviale vraag, maar voor veel mensen is dit een wezenlijk onderscheid, en wetenschappelijk gezien ook interessant. “Autisme hebben” was vroeger gangbaar. Je bent in de eerste plaats een persoon, en in de tweede plaats heb je autisme. Maar autistische mensen zelf brachten daar verandering in, omdat autisme juist wel als centraal onderdeel van hun identiteit gezien werd. Dus: ‘identity first’. Autistisch persoon. Je bent toch ook geen persoon met vrouwelijkheid? Je bent een vrouw. En autisme is geen ziekte die we willen genezen.

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Short report: Social communication difficulties and restricted repetitive behaviors as predictors of anxiety in adults with autism spectrum disorder

Cited by 16 publications

References 26 publications

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

Divergent projections of the prelimbic cortex mediate autism- and anxiety-like behaviors

Achter de Spiegel: Het spectrum van autisme

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