Autistic Traits and Empathy in Children With Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorder and Co-occurring Attention Deficit Hyperactivity Disorder/Autism Spectrum Disorder

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) are two of the most represented neurodevelopmental conditions in childhood. The diagnostic shift introduced by the DSM-5, allowing a combined diagnosis of ADHD and ASD, poses different clinical challenges related to diagnostic overshadowing, accuracy of clinical judgment and potential delay in an ASD diagnosis in children presenting with ADHD. Here we tried to disentangle the clinical phenotype and specificity of the two co-occurring conditions in relation to autism traits and empathy, by comparing children with ASD with and without comorbid ADHD with children presenting ADHD only and children with typical development. The child versions of the Autism Quotient (C-AQ) and Empathy Quotient (C-EQ) were administered to a total sample of 198 male children between 6 and 14 years old with age appropriate language skills and normal intelligence. Univariate analysis demonstrated no significant differences in the C-AQ total and subscale scores as well as the C-EQ between children with ASD and children with ASD + ADHD, while children with ADHD alone presented an intermediate phenotype between ASD and TD. Furthermore, a receiver operating characteristic (ROC) analysis was applied to discriminate among the different phenotypes. We found that the C-AQ and C-EQ were accurate at distinguishing with satisfactory reliability between: (a) ASD vs. non- ASD (N-ASD) groups comprising both ADHD and TD children (Area Under the Curve AUC 88% for C-AQ and 81% for C-EQ); (b) ASD and TD (AUC 92% for C-AQ and 95% for C-EQ); (c) ASD and ADHD (AUC 80% for C-AQ and 68% for C-EQ). Our data confirm the reliability of the C-AQ and C-EQ as behavioral markers to differentiate ASD (regardless of comorbid ADHD) from an ADHD condition and TD. Interestingly, in our sample an ADHD condition does not increase the severity of the clinical phenotype in terms of autism traits distribution and empathy, suggesting that the psychological measures detected by the two quantitative instruments are independent of ADHD traits. This evidence will contribute to the translational efforts in developing better tailored treatments and preventive strategies.

The influence of child-based factors and parental inputs on expressive language abilities in children with autism spectrum disorder

Studies of language development in children with autism spectrum disorder (ASD) have been primarily focused on the influence of child-based factors such as autism traits, IQ, and initial language skills. Yet the findings of these studies are inconclusive. There has, moreover, been little research compared the relative influences of child-based factors with environmental factors, (e.g. parental inputs). The current study attempts to fill this research gap by examining a range of both child-based factors and parental inputs. We measured the structural language abilities manifested in parent-child interactions over four time points across nine months in 42 Chinese-speaking autistic children ( M = 57.42 months, SD = 11.39). Our results showed that children’s mean length of utterance (MLU), word types, and word tokens grew rapidly, but their development trajectories varied. Initial expressive language ability was a significant predictor of children’s language outcomes, while nonverbal IQ and autism traits did not relate to children’s language abilities when controlling for initial expressive language ability. Parents’ MLU, word tokens, and word types did not associate with children’s structural language abilities. The findings shed lights on the importance of one of the child-based factors in particular, that is, initial expressive language skills, in the language development of autistic children. Lay abstract Language impairment is one of the early signs of Autism Spectrum Disorder (ASD) that alerts parents to take their children for early diagnosis and intervention. Little is known about how children’s autism traits, IQ, initial language abilities and parental inputs influence their language abilities. In addition, only a few studies have compared the relative influence of these factors. The present study addressed these issues by examining the structural language in parent-child spontaneous interactions. Forty-two Cantonese (Chinese)-speaking autistic children aged four to eight were recruited. Their expressive language skills grew rapidly more than 9 months, but their development trajectories varied. Initial expressive language ability is the only significant predictor of child language outcomes and language growth trajectories. In contrast, nonverbal cognition, autism traits, and parents’ input do not affect language outcomes in children with ASD. Therefore, early language intervention is crucial for autistic children at all severity and IQ levels.

Prediction of Autism Spectrum Disorder by Facial Recognition Using Machine Learning

Autism is normally characterized as pervading disorder. The role Pervasive implies that the disorder is acute. Autism spectrum disorder (ASD) individuals face difficulties in interacting with others. They also have a problem in responding to the actions, hyperactive and behavioural issues. There have been numerous technological enhancements in prediction of autism traits. This paper focusses on various machine learning methods to classify an autistic child. It mainly focusses on classification models applying VGG16 algorithm of SVM classifier, CNN and Haar Cascade using OpenCV. Using these models, better accuracy was achieved compared to other models of classification.

Investigating the influence of autism spectrum traits on face processing mechanisms in developmental prosopagnosia

Autism traits are commonly used as exclusionary criteria in studies of developmental prosopagnosia (DP). We investigated whether autism traits result in qualitatively different face processing in 43 DPs with high vs. low autism quotient (AQ) scores and 27 controls. Compared to controls, behavioral face recognition deficits were similar between the high and low AQ DP groups aside from worse emotion recognition in the high AQ DPs. Both DP groups showed reduced face selectivity in task-based fMRI, although higher AQ DPs showed decreased face selectivity in the posterior superior temporal sulcus. Resting-state fMRI showed similar face network connectivity between DP groups. This suggests that face processing is similar between the DP groups, with additional emotion processing deficits in higher AQ DPs.

Associations of Autism Traits With Obsessive Compulsive Symptoms and Well-Being in Patients With Obsessive Compulsive Disorder: A Cross-Sectional Study

The aim of this study is to examine the association of autism traits with long-term obsessive compulsive disorder (OCD) symptoms and well-being levels in patient with OCD. Participants comprised 18 outpatients from a tertiary hospital and 100 adults who were registered in a large Japanese internet marketing research company and met OCD criteria by the Mini-International Neuropsychiatric Interview and were between the ages of 20 and 65 years. Clinical characteristics, autism trait assessed using the Autism Spectrum Quotient (AQ), OCD symptoms assessed using Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), and well-being assessed using the Flourishing Scale were assessed. Multiple regression analyses showed that a greater total score of AQ, a greater subscale score “imagination” was associated with a greater score of Y-BOCS. Greater total score of AQ, a greater subscale score “social skill,” and “imagination” were associated with lower well-being score. Autism traits, especially lack of imagination, were associated with more severe OCD symptoms. Further, autism traits, especially social skill problems and lack of imagination, were associated with lower levels of well-being. Assessment of autism traits before treatment and a strategy designed for OCD patients with autism traits may be warranted.