Background: The objective of this study was to investigate the DRD2 rs1800497, rs1799732, rs1801028, DRD3 rs6280, and HTR2A rs6314, rs7997012, and rs6311 single-nucleotide polymorphism (SNP) correlations with resistance to second-generation antipsychotics (SGAs) in a real-world sample of patients with treatment-resistant mental disorders. Methods: We divided 129 participants into a high treatment resistance (HTR) group (current treatment with two SGAs, or clozapine, or classic neuroleptics for a failure of previous SGAs trials) and a low treatment resistance (LTR) group (current treatment with one atypical antipsychotic). We used Next-Generation Sequencing on DNA isolated from peripheral blood samples to analyze the polymorphisms. We performed logistic regression to search for predictors of HTR membership. Results: A diagnosis of schizophrenia significantly predicted the HTR membership compared to other diagnoses. Other predictors were the DRD3 rs6280 C|T (OR = 22.195) and T|T (OR = 18.47) vs. C|C, HTR2A rs7997012 A|G vs. A|A (OR = 6.859) and vs. G|G (OR = 2.879), and DRD2 rs1799732 I|I vs. D|I (OR = 12.079) genotypes. Conclusions: A diagnosis of schizophrenia and the DRD2 rs1799732, DRD3 rs6280, and HTR2A rs7997012 genotypes can predict high treatment resistance to SGAs.

Major depressive disorder (MDD) and other affective disorders may surreptitiously arise in children and adolescents during their school period and impair their social and educational functioning. Besides the social and personal burden, which are increased during the SARS-CoV-2 pandemic, the onset of depression may compromise the future of the growing person with chronicity and recurrence. In this context, educators’ training is essential to detect early the onset of a depressive disorder, to spare later consequences through the timely establishment of adequate treatment. The educational staff should receive adequate training to be able to work closely with healthcare providers and parents, thus directing the young person with an affective disorder to the right psychological and pharmacological treatment provider, i.e., a specialized psychologist or psychiatrist. The first approach should be to establish a trustful relationship with the adolescent and his/her classmates, to reduce social and self-stigma and inform about mental illness. If symptoms do not subside and the suffering child or adolescent fails to reintegrate within his/her school environment, cognitive–behavioral interventions are recommended that are individual, group, or computer-based. When needed, these should be implemented with individualized pharmacotherapy.

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties in social interaction, communication, and repetitive behaviors. Neuroimaging studies have revealed structural and functional neural changes in individuals with ASD compared to healthy subjects. Objectives: This study aimed to investigate brain network structural connectivity in ASD using Morphometric Similarity Network (MSN) analysis. Methods: Data from the Autism Brain Imaging Data Exchange (ABIDE) were analyzed, comprising 597 individuals with ASD and 644 healthy controls. Structural connectivity was assessed using cortical morphometric features. Global and regional network indices, including the density index, node degree, node strength, and clustering coefficients, were evaluated. Results: Among the global network indices, when using a threshold value of 0.4, ASD patients compared to HCs showed a lower density (p = 0.041) and higher negative clustering (p = 0.0051) coefficients. For regional network indices, ASD patients showed a lower bilateral superior frontal cortices degree (left hemisphere: p = 0.014; right hemisphere: p = 0.0038) and strength (left: p = 0.017; right: p = 0.018). Additionally, they showed higher negative clustering coefficients in the bilateral superior frontal cortices (left, p = 0.0088; right, p = 0.0056) and bilateral pars orbitalis (left, p = 0.016; right, p = 0.0006), as well as lower positive clustering in the bilateral frontal pole (left, p = 0.03; right, p = 0.044). Conclusions: These findings highlight significant alterations in both global and regional brain network organization in ASD, which may contribute to the disorder’s cognitive and behavioral manifestations. Future studies are needed to investigate the pathophysiological mechanisms underlying these structural connectivity changes, to inform the development of more targeted and individualized therapeutic interventions for individuals with ASD.