Neural circuit disruptions of eye gaze processing in autism spectrum disorder and schizophrenia: An activation likelihood estimation meta-analysis.

BACKGROUND: Impairment in social cognition, particularly eye gaze processing, is a shared feature common to autism spectrum disorder (ASD) and schizophrenia. However, it is unclear if a convergent neural mechanism also underlies gaze dysfunction in these conditions. The present study examined whether this shared eye gaze phenotype is reflected in a profile of convergent neurobiological dysfunction in ASD and schizophrenia. METHODS: Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates across the whole brain to identify spatial convergence. Functional coactivation with regions emerging as significant was assessed using meta-analytic connectivity modeling. Functional decoding was also conducted. RESULTS: Fifty-six experiments (n = 30 with schizophrenia and n = 26 with ASD) from 36 articles met inclusion criteria, which comprised 354 participants with ASD, 275 with schizophrenia and 613 healthy controls (1242 participants in total). In ASD, aberrant activation was found in the left amygdala relative to unaffected controls during gaze processing. In schizophrenia, aberrant activation was found in the right inferior frontal gyrus and supplementary motor area. Across ASD and schizophrenia, aberrant activation was found in the right inferior frontal gyrus and right fusiform gyrus during gaze processing. Functional decoding mapped the left amygdala to domains related to emotion processing and cognition, the right inferior frontal gyrus to cognition and perception, and the right fusiform gyrus to visual perception, spatial cognition, and emotion perception. These regions also showed meta-analytic connectivity to frontoparietal and frontotemporal circuitry. CONCLUSION: Alterations in frontoparietal and frontotemporal circuitry emerged as neural markers of gaze impairments in ASD and schizophrenia. These findings have implications for advancing transdiagnostic biomarkers to inform targeted treatments for ASD and schizophrenia.

Systematic Review and Meta-Analysis: Clinical Utility of Continuous Performance Tests for the Identification of Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: We aimed to quantify the clinical utility of continuous performance tests (CPTs) for the diagnosis of attention-deficit/hyperactivity disorder (ADHD) compared to a clinical diagnosis in children and adolescents. METHOD: Four databases (MEDLINE, PsycINFO, EMBASE, and PubMed) were screened until January 2023. Risk of bias of included results was judged with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). We statistically pooled the area under the curve, the sensitivity, and the specificity of 3 commonly used CPTs subscales: omission/inattention, commission/impulsivity, and total number of errors/ADHD subscales (PROSPERO registration: CRD42020168091). RESULTS: A total of 19 studies using commercially available CPTs were identified. Results from up to 835 control individuals and 819 cases were combined in the summary receiver operating characteristic (ROC) curve analyses (sensitivity and specificity pooling), and up to 996 cases and 1,083 control individuals in the area under the curve (AUC) analyses. Clinical utility as measured by AUCs could be considered as barely acceptable (between 0.7 and 0.8) for the most part, with the best results for the total/ADHD score, followed by omissions/inattention, and poorest for commission/impulsivity scores. A similar pattern was found when pooling sensitivity and specificity: 0.75 (95% CI = 0.66-0.82) and 0.71 (0.62-0.78) for the total/ADHD score; 0.63 (0.49-0.75) and 0.74 (0.65-0.81) for omissions; and 0.59 (0.38-0.77) and 0.66 (CI = 0.50-0.78) for commissions. CONCLUSION: At the clinical level, CPTs as a stand-alone tool have only a modest to moderate ability to differentiate ADHD from non-ADHD samples. Hence, they should be used only within a more comprehensive diagnostic process. STUDY PREREGISTRATION INFORMATION: A systematic review of screening tools for ADHD in children and adolescents; https://www.crd.york.ac.uk/prospero/; CRD42020168091.

Association between autism spectrum disorder and diabetes: systematic review and meta-analysis.

There is mixed evidence on the link between autism spectrum disorder (ASD) and diabetes. We conducted the first systematic review/meta-analysis on their association. Based on a pre-registered protocol (PROSPERO: CRD42021261114), we searched Pubmed, Ovid, and Web of Science databases up to 6 December 2021, with no language/type of document restrictions. We assessed study quality using the Newcastle-Ottawa Scale (NOS). We included 24 studies (total: 3427,773 individuals; 237,529 with ASD and 92,832 with diabetes) in the systematic review and 20 in the meta-analysis (mean stars number on the NOS: 5.89/10). There was a significant association, albeit characterized by significant heterogeneity, when pooling unadjusted OR (1.535, 95% CI = 1.109-2.126), which remained significant when restricting the analysis to children and type 2 diabetes, but became non-significant when considering adjusted ORs (OR: 1.528, 95% CI = 0.954-2.448). No significant prospective association was found (n = 2) on diabetes predicting ASD (HR: 1.232, 0.826-11.837). Therefore, the association between ASD and diabetes is likely confounded by demographic and clinical factors that should be systematically investigated in future studies.

Systematic Review and Meta-analysis: Screening Tools for Attention-Deficit/Hyperactivity Disorder in Children and Adolescents.

OBJECTIVE: This systematic review and meta-analysis aimed to determine the accuracies of a broad range of screening tools for attention-deficit/hyperactivity disorder (ADHD) in children and adolescents, and to compare the diagnostic accuracy of tools between population-based and clinical/high-risk samples, and across reporters. METHOD: MEDLINE, PsycINFO, EMBASE, and PubMed were searched up until February 20, 2020, with no language restrictions. Studies reporting diagnostic accuracy of a screening tool against a diagnosis of ADHD in children and adolescents <18 years of age were eligible for inclusion. Meta-analyses were undertaken to provide pooled estimates of the area under the curve (AUC), and sensitivity and specificity of groups of measures. RESULTS: A total of 75 studies published between 1985 and 2021 reporting on 41 screening tools that were grouped into 4 categories (Achenbach System of Empirically Based Assessment [ASEBA], DSM-IV symptom scales, SDQ, and Other Scales) were retained. The pooled AUC for studies using a combined ADHD symptoms score was 0.82 (95% CI = 0.78-0.86), although this varied considerably across reporters (0.67-0.92) and populations (CI = 0.60-0.95). None of the measures met minimal standards for acceptable sensitivity (0.8) and specificity (0.8). CONCLUSION: Most tools have excellent overall diagnostic accuracy as indicated by the AUC. However, a single measure completed by a single reporter is unlikely to have sufficient sensitivity and specificity for clinical use or population screening.