Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex clinical manifestations that arise between 18 and 36 months of age. Social interaction deficiencies, a restricted range of interests, and repetitive stereotyped behaviors are characteristics which are sometimes difficult to detect early. Several studies show that microRNAs (miRs/miRNAs) are strongly implicated in the development of the disorder and affect the expression of genes related to different neurological pathways involved in ASD. The present systematic review and meta-analysis addresses the current status of miRNA studies in different body fluids and the most frequently dysregulated miRNAs in patients with ASD. We used a combined approach to summarize miRNA fold changes in different studies using the mean values. In addition, we summarized p values for differential miRNA expression using the Fisher method. Our literature search yielded a total of 133 relevant articles, 27 of which were selected for qualitative analysis based on the inclusion and exclusion criteria, and 16 studies evaluating miRNAs whose data were completely reported were ultimately included in the meta-analysis. The most frequently dysregulated miRNAs across the analyzed studies were miR-451a, miR-144-3p, miR-23b, miR-106b, miR150-5p, miR320a, miR92a-2-5p, and miR486-3p. Among the most dysregulated miRNAs in individuals with ASD, miR-451a is the most relevant to clinical practice and is associated with impaired social interaction. Other miRNAs, including miR19a-3p, miR-494, miR-142-3p, miR-3687, and miR-27a-3p, are differentially expressed in various tissues and body fluids of patients with ASD. Therefore, all these miRNAs can be considered candidates for ASD biomarkers. Saliva may be the optimal biological fluid for miRNA measurements, because it is easy to collect from children compared to other biological fluids.

The role of insight dimensions - illness recognition (IR), symptoms relabelling (SR), treatment compliance (TC) - in suicide risk in first-episode psychosis (FEP) remains unclear. The AESOP (n = 181) and GAP (n = 112) FEP cohorts were followed-up over 10- and 5 years. Survival analysis modelled time to first suicidal event in relation to baseline scores on the Schedule for the Assessment of Insight, whilst adjusting for demographic, clinical, psychopathological and neuropsychological variables. AESOP: those with previous suicide attempts scored higher on IR (7.6 ± 1.9 vs. 5.9 ± 3.0, p < 0.01) and total insight scores (TIS) (17.2 ± 5.0 vs. 13.4 ± 6.7, p = 0.03). IR (r = 0.23, p < 0.01), SR (r = 0.18, p = 0.04) and TC (r = 0.26, p < 0.01) correlated with depression. Univariable analyses: IR (HR = 1.14, 95% CI = 0.98-1.34, p = 0.09), TC (HR = 1.30, 95% CI = 0.99-1.71, p = 0.06) and TIS (HR = 1.06, 95% CI = 0.99-1.13, p = 0.08) were linked with suicidal behaviour. Multivariable regression models: depression (HR = 1.55, 95% CI = 1.22-1.97, p < 0.01) predicted suicidal behaviour. GAP: SR (6.4 ± 3.1 vs. 4.5 ± 3.4, p = 0.03) and TIS (16.8 ± 6.4 vs. 12.8 ± 7.4, p = 0.03) were higher in those with suicidal antecedents. IR (r = 0.32, p < 0.01) and SR (r = 0.27, p = 0.01) correlated with depression. Univariable analyses: TC (HR = 1.36, 95% CI = 1.01-1.83, p = 0.04) and TIS (HR = 1.06, 95% CI = 0.99-1.14, p = 0.08) were associated with suicidal behaviour. Multivariable regression models: previous suicide attempts (HR 5.17, 95% CI 1.32-20.29, p = 0.02) and depression (HR 1.16, 95% CI = 1.00-1.35, p = 0.04) predicted suicidal behaviour. Suicide attempts prior to FEP and depression at that point were associated with baseline insight levels and predicted risk of suicidal behaviour over the follow-up, which was not linked with insight. This may explain the apparent association of insight with suicidality in FEP.

Background: Suicide has been recognised as one of the major causes of premature death in psychosis. However, predicting suicidal behaviour (SB) is still challenging in the clinical setting and the association of neurocognition with SB in psychosis remains poorly understood. This study aimed to investigate the role of neurocognitive performance as predictor of SB. Also, we sought to explore differences in the evolution of clinical and neurocognitive functioning between participants with/without history of suicide attempts (SA) over follow-up period.Methods: The sample of the study is composed by 517 patients. Sociodemographic, clinical, functional and neurocognitive measures were evaluated at baseline as well as 1-year and 3 years after first episode of psychosis. Bivariate and multivariate analyses explored the influence of these variables as putative baseline predictors of SB. Repeated measures analyses of variance tested differences in clinical and neurocognitive outcomes at 1- and 3-year follow-up.Results: Global cognitive functioning (GCF) (OR = 1.83, 95% CI = 1.25–2.67) and severe depressive symptoms (OR = 1.17, 95% CI = 1.07–1.28) predicted SB. Longitudinal analyses revealed that patients with SB at follow-up presented with higher levels of remission in terms of positive psychotic symptoms and depression. In addition, those with a history of SB had worse GCF and visual memory than those without such antecedents.Conclusions: GCF was found to be the most robust predictor of SB along with severe depressive symptomatology. Hence, poorer cognitive performance in FEP appears to emerge as a risk factor for suicidal behaviour from early stages of the illness and a comprehensive neurocognitive assessment may contribute to risk assessment.

Objectives: Our aims were to confirm the relationship between lipid and lipoprotein concentrations and suicidal behaviour in first-episode psychosis (FEP) patients. Methods: Suicidal behaviour was explored in a large FEP sample (N = 383). Baseline lipid profile was compared between those who attempted or completed suicide and those who not presented suicidal behaviour. Results: Low-density lipoprotein cholesterol (LDL-c) (OR = 0.99, 95% CI= 0.98–1.00) and depressive symptoms (OR = 1.15, 95% CI = 1.06–1.24) were significantly related with suicidal behaviour. Conclusions: Lipid profile test may be considered in the assessment of suicide risk in psychosis and LDL-c an important biological marker.

Background: Understanding the evolution of negative symptoms in first-episode psychosis (FEP) requires long-term longitudinal study designs that capture the progression of this condition and the associated brain changes.Aims: To explore the factors underlying negative symptoms and their association with long-term abnormal brain trajectories.Method: We followed up 357 people with FEP over a 10-year period. Factor analyses were conducted to explore negative symptom dimensionality. Latent growth mixture modelling (LGMM) was used to identify the latent classes. Analysis of variance (ANOVA) was conducted to investigate developmental trajectories of cortical thickness. Finally, the resulting ANOVA maps were correlated with a wide set of regional molecular profiles derived from public databases.Results: Three trajectories (stable, decreasing and increasing) were found in each of the three factors (expressivity, experiential and attention) identified by the factor analyses. Patients with an increasing trajectory in the expressivity factor showed cortical thinning in caudal middle frontal, pars triangularis, rostral middle frontal and superior frontal regions from the third to the tenth year after the onset of the psychotic disorder. The F-statistic map of cortical thickness expressivity differences was associated with a receptor density map derived from positron emission tomography data.Conclusions: Stable and decreasing were the most common trajectories. Additionally, cortical thickness abnormalities found at relatively late stages of FEP onset could be exploited as a biomarker of poor symptom outcome in the expressivity dimension. Finally, the brain areas with less density of receptors spatially overlap areas that discriminate the trajectories of the expressivity dimension.