Is There a Bias Towards Males in the Diagnosis of Autism? A Systematic Review and Meta-Analysis.

Autism is more frequently diagnosed in males, with evidence suggesting that females are more likely to be misdiagnosed or underdiagnosed. Possibly, the male/female ratio imbalance relates to phenotypic and camouflaging differences between genders. Here, we performed a comprehensive approach to phenotypic and camouflaging research in autism addressed in two studies. First (Study 1 - Phenotypic Differences in Autism), we conducted a systematic review and meta-analysis of gender differences in autism phenotype. The electronic datasets Pubmed, Scopus, Web of Science, and PsychInfo were searched. We included 67 articles that compared females and males in autism core symptoms, and in cognitive, socioemotional, and behavioural phenotypes. Autistic males exhibited more severe symptoms and social interaction difficulties on standard clinical measures than females, who, in turn, exhibited more cognitive and behavioural difficulties. Considering the hypothesis of camouflaging possibly underlying these differences, we then conducted a meta-analysis of gender differences in camouflaging (Study 2 - Camouflaging Differences in Autism). The same datasets as the first study were searched. Ten studies were included. Females used more compensation and masking camouflage strategies than males. The results support the argument of a bias in clinical procedures towards males and the importance of considering a 'female autism phenotype'-potentially involving camouflaging-in the diagnostic process.

A Machine Learning Approach in Autism Spectrum Disorders: From Sensory Processing to Behavior Problems.

Atypical sensory processing described in autism spectrum disorders (ASDs) frequently cascade into behavioral alterations: isolation, aggression, indifference, anxious/depressed states, or attention problems. Predictive machine learning models might refine the statistical explorations of the associations between them by finding out how these dimensions are related. This study investigates whether behavior problems can be predicted using sensory processing abilities. Participants were 72 children and adolescents (21 females) diagnosed with ASD, aged between 6 and 14 years (M = 7.83 years; SD = 2.80 years). Parents of the participants were invited to answer the Sensory Profile 2 (SP2) and the Child Behavior Checklist (CBCL) questionnaires. A collection of 26 supervised machine learning regression models of different families was developed to predict the CBCL outcomes using the SP2 scores. The most reliable predictions were for the following outcomes: total problems (using the items in the SP2 touch scale as inputs), anxiety/depression (using avoiding quadrant), social problems (registration), and externalizing scales, revealing interesting relations between CBCL outcomes and SP2 scales. The prediction reliability on the remaining outcomes was "moderate to good" except somatic complaints and rule-breaking, where it was "bad to moderate." Linear and ridge regression achieved the best prediction for a single outcome and globally, respectively, and gradient boosting machine achieved the best prediction in three outcomes. Results highlight the utility of several machine learning models in studying the predictive value of sensory processing impairments (with an early onset) on specific behavior alterations, providing evidences of relationship between sensory processing impairments and behavior problems in ASD.

Trio-based exome sequencing reveals a high rate of the de novo variants in intellectual disability.

Intellectual disability (ID), a neurodevelopmental disorder affecting 1-3% of the general population, is characterized by limitations in both intellectual function and adaptive skills. The high number of conditions associated with ID underlines its heterogeneous origin and reveals the difficulty of obtaining a rapid and accurate genetic diagnosis. However, the Next Generation Sequencing, and the whole exome sequencing (WES) in particular, has boosted the diagnosis rate associated with ID. In this study, WES performed on 244 trios of patients clinically diagnosed with isolated or syndromic ID and their respective unaffected parents has allowed the identification of the underlying genetic basis of ID in 64 patients, yielding a diagnosis rate of 25.2%. Our results suggest that trio-based WES facilitates ID's genetic diagnosis, particularly in patients who have been extensively waiting for a definitive molecular diagnosis. Moreover, genotypic information from parents provided by trio-based WES enabled the detection of a high percentage (61.5%) of de novo variants inside our cohort. Establishing a quick genetic diagnosis of ID would allow early intervention and better clinical management, thus improving the quality of life of these patients and their families.

Viability Study of Machine Learning-Based Prediction of COVID-19 Pandemic Impact in Obsessive-Compulsive Disorder Patients.

BACKGROUND: Machine learning modeling can provide valuable support in different areas of mental health, because it enables to make rapid predictions and therefore support the decision making, based on valuable data. However, few studies have applied this method to predict symptoms' worsening, based on sociodemographic, contextual, and clinical data. Thus, we applied machine learning techniques to identify predictors of symptomatologic changes in a Spanish cohort of OCD patients during the initial phase of the COVID-19 pandemic. METHODS: 127 OCD patients were assessed using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and a structured clinical interview during the COVID-19 pandemic. Machine learning models for classification (LDA and SVM) and regression (linear regression and SVR) were constructed to predict each symptom based on patient's sociodemographic, clinical and contextual information. RESULTS: A Y-BOCS score prediction model was generated with 100% reliability at a score threshold of ± 6. Reliability of 100% was reached for obsessions and/or compulsions related to COVID-19. Symptoms of anxiety and depression were predicted with less reliability (correlation R of 0.58 and 0.68, respectively). The suicidal thoughts are predicted with a sensitivity of 79% and specificity of 88%. The best results are achieved by SVM and SVR. CONCLUSION: Our findings reveal that sociodemographic and clinical data can be used to predict changes in OCD symptomatology. Machine learning may be valuable tool for helping clinicians to rapidly identify patients at higher risk and therefore provide optimized care, especially in future pandemics. However, further validation of these models is required to ensure greater reliability of the algorithms for clinical implementation to specific objectives of interest.

Social Camouflaging in Females with Autism Spectrum Disorder: A Systematic Review.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with increasing prevalence, and a male-to-female ratio of 4:1. Research has been suggesting that discrepancy in prevalence may be due to the fact that females camouflage their symptoms. In this study, we aimed to systematically review evidence on the camouflage effect in females with ASD. Following the PRISMA guidelines, we reviewed empirical research published from January 2009 to September 2019 on PubMed, Web of Science, PsychInfo and Scopus databases. Thirteen empirical articles were included in this review. Overall, evidence supports that camouflaging seems to be an adaptive mechanism for females with ASD, despite the negative implications of these behaviours in their daily life.

Executive impairments in obsessive compulsive disorder: a systematic review with emotional and non-emotional paradigms / Alteraciones ejecutivas en el Trastorno Obsesivo Compulsivo: una revisión sistemática con paradigmas emocionales y no emocionales

PRECEDENT: Impairments in executive functioning may be associated with compulsive symptoms in Obsessive Compulsive Disorder (OCD). The aim of this study was to conduct a systematic review of cognitive flexibility, inhibitory control and working memory in OCD patients, using emotional and non-emotional paradigms. METHOD: we reviewed research published in PubMed, Web of Science, PsychInfo, Scopus, Scielo, and ProQuest Psychology databases, from January 2008 to April 2019. The review followed a two-stage process. In the first stage, we selected only studies using neutral stimuli paradigms, while in the second we selected executive-emotional paradigms. RESULTS: The first stage of the review provided 16 final results, while the second stage, with emotional stimuli, provided 3 results. CONCLUSIONS: There is some initial evidence for the existence of executive impairments in OCD, as expressed in the performance and/or processing of working memory inhibitory control and cognitive flexibility. There is also initial evidence that these latter two could be modulated by the presentation or mental representation of negative valence stimuli or images, as well as the presence of aversive contingencies

ANTECEDENTES: las alteraciones en el funcionamiento ejecutivo podrían estar asociadas a los síntomas compulsivos del Trastorno Obsesivo Compulsivo (TOC). El objetivo de este estudio fue realizar una revisión sistemática en flexibilidad cognitiva, control inhibitorio y memoria de trabajo en pacientes con TOC, empleando paradigmas emocionales y no emocionales. MÉTODO: revisamos investigaciones publicadas en PubMed, Web of Science, PsychInfo, Scopus, Scielo y ProQuest Psychology databases, desde enero de 2008 hasta abril de 2019. La revisión siguió un proceso de dos etapas: la primera centrada en estudios con paradigmas ejecutivos neutros y la segunda con paradigmas ejecutivos emocionales. RESULTADOS: la primera etapa de búsqueda arrojó un resultado de 16 estudios, mientras que la segunda, con paradigmas emocionales, arrojó tres resultados. CONCLUSIONES: a pesar de la escasa cantidad de investigación, existen evidencias de alteraciones ejecutivas en TOC que se expresan en la ejecución o en el procesamiento de memoria de trabajo, control inhibitorio y flexibilidad cognitiva. También hay evidencias de que estos dos últimos componentes podrían estar modulados por la presentación o representación mental de estímulos negativos, así como por la presencia de contingencias aversivas

Executive impairments in Obsessive Compulsive Disorder: A systematic review with emotional and non-emotional paradigms.

Precedent: Impairments in executive functioning may be associated with compulsive symptoms in Obsessive Compulsive Disorder (OCD). The aim of this study was to conduct a systematic review of cognitive flexibility, inhibitory control and working memory in OCD patients, using emotional and non-emotional paradigms. METHOD: we reviewed research published in PubMed, Web of Science, PsychInfo, Scopus, Scielo, and ProQuest Psychology databases, from January 2008 to April 2019. The review followed a two-stage process. In the first stage, we selected only studies using neutral stimuli paradigms, while in the second we selected executive-emotional paradigms. RESULTS: The first stage of the review provided 16 final results, while the second stage, with emotional stimuli, provided 3 results. CONCLUSIONS: There is some initial evidence for the existence of executive impairments in OCD, as expressed in the performance and/or processing of working memory inhibitory control and cognitive flexibility. There is also initial evidence that these latter two could be modulated by the presentation or mental representation of negative valence stimuli or images, as well as the presence of aversive contingencies.