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Neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) have emerged as important peripheral inflammatory biomarkers. Recent data suggest a possible role of the immune system in the pathophysiology of suicidal behavior (SB). The aim of this study is to evaluate the association among NLR, MLR, and PLR and SB in patients with major depressive disorder (MDD), and to test its validity as a biomarker for suicidality. We evaluated 538 patients with MDD (mean age [standard deviation] = 43.87 [14.36] years; females: 68.8%). A logistic regression model was estimated to determine the independent factors associated with suicide risk in patients with and without a history of suicide attempt (SA). Three hundred ninety-three patients (74.7%) had a personal history of SA. Patients with a previous SA were more frequently female (71.9% vs. 59.6%; p = 0.007), significantly younger (41.20 vs. 51.77 years; p < 0.001), had lower depression severity at enrolment (15.58 vs. 18.42; p < 0.000), and significantly higher mean NLR and PLR ratios (2.27 vs. 1.68, p = 0.001; 127.90 vs. 109.97, p = 0.007, respectively). In the final logistic regression model, after controlling for age, sex, and depression severity, NLR was significantly associated with SB (β = 0.489, p = 0.000; odds ratio [95% confidence intervals] = 1.631 [1.266-2.102]). We propose a cut-off value of NLR = 1.30 (sensitivity = 75% and specificity = 35%). Our data suggest that NLR may be a valuable, reproducible, easily accessible, and cost-effective strategy to determine suicide risk in MDD.

Abstract Background and Hypothesis A pro-inflammatory phenotype has been related to psychotic disorders. The neutrophil-lymphocyte ratio (NLR) is an accessible biomarker that could be helpful to characterize this systemic inflammation state. Study Design This study evaluated the NLR in a cohort of 310 subjects with a first episode of psychosis (FEP) and a matched group of 215 healthy controls, recruited in 16 Spanish centers participating in the PEPs Project. We investigated the NLR measures over 2 years in a prospective, naturalistic study. Study Results At baseline, the FEP group showed a significant higher mean NLR compared to the control group (1.96 ± 1.11 vs 1.72 ± 0.74, P = 0.03). These ratio differences between groups grew at the 24 months follow-up visit (2.04 ± 0.86 vs 1.65 ± 0.65, P < 0.001). Within the FEP group, there were no significant differences in NLR across the follow-up visits, between genders or diagnosis groups (affective vs nonaffective). NLR values did not correlate with the Positive and Negative Symptoms Scale scores. The group of patients who did not reach remission criteria at the end of the study showed a significant higher NLR than those who remitted (2.1896 ± 0.85 vs 1.95 ± 0.87, P = 0.042). A significant correlation between antipsychotic doses and NLR was found at the two-years follow-up visit (r=0.461, P < 0.001). Conclusions Our results highlight the existence of an underlying predisposition of FEP patients to present an increased mean NLR. The use of NLR in clinical practice could be helpful to identify this inflammatory imbalance.

BackgroundThe neurobiological basis of suicidal behaviour remains poorly understood. However, emerging evidence suggests that inflammation and vascular homeostasis factors may play a role in its pathophysiology. Childhood trauma, through immune system dysfunction and increased risk of suicidal behaviours, might influence these associations. This study examined the relationships between immune-inflammatory and vascular homeostasis-related markers and their interaction with childhood trauma in relation to a history of suicide attempts in individuals with depression.MethodsA total of 328 patients with major depression were recruited: 166 with a history of suicide attempts and 162 without. Using multivariate binary logistic regression models adjusted for cofounders, we examined the associations between childhood trauma, levels of platelet-related immune markers (serotonin, MCP-1, TSP-1, TSP-2, PDGF-AB, PDGF-BB), and suicide attempt history. Independent associations between PDGF-BB, childhood trauma, and suicide attempts were further assessed using interaction models. Stratified sensitivity analyses based on childhood trauma history were also conducted.ResultsChildhood trauma consistently emerged as associated with suicide attempts across all models. Among the measured biomarkers, higher TSP-2 levels were associated with a suicide attempt history, independent of childhood trauma. Meanwhile, while PDGF-BB alone was not directly linked to suicide attempt history, the interaction analysis revealed that individuals with lower PDGF-BB levels and more severe childhood trauma were more likely to have attempted suicide.ConclusionsTSP-2 and PDGF-BB are potential biomarkers linked to suicide attempts, with distinct roles in the interplay between biological processes and early-life adversity. These insights can inform the biomarker-informed development of tailored prevention and treatment strategies.

Network analysis has been used to explore the interplay between psychopathology and functioning in psychosis, but no study has used dedicated statistical techniques to focus on the bridge symptoms connecting these domains. The current study aims to estimate the network of depressive, negative, and positive symptoms, general psychopathology, and real-world functioning in people with first-episode schizophrenia or schizophreniform disorder, focusing on bridge nodes. Baseline data from the OPTiMiSE trial were analyzed. The sample included 446 participants (age 40.0 ± 10.9 years, 70% males). The network was estimated with a Gaussian graphical model, using scores on individual items of the positive and negative syndrome scale (PANSS), the Calgary depression scale for schizophrenia, and the personal and social performance scale. Stability, strength centrality, expected influence (EI), predictability, and bridge centrality statistics were computed. The top 20% scoring nodes on bridge strength were selected as bridge nodes. Nodes from different rating scales assessing similar psychopathological and functioning constructs tended to cluster together in the estimated network. The most central nodes (EI) were Delusions, Emotional Withdrawal, Depression, and Depressed Mood. Bridge nodes included Depression, Conceptual Disorganization, Active Social Avoidance, Delusions, Stereotyped Thinking, Poor Impulse Control, Guilty Feelings, Unusual Thought Content, and Hostility. Most of the bridge nodes belonged to the general psychopathology subscale of the PANSS. Depression (G6) was the bridge node with the highest value. The current study provides novel insights for understanding the complex phenotype of psychotic disorders and the mechanisms underlying the development and maintenance of comorbidity and functional impairment after psychosis onset.

One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia. Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model's accuracy (% agreement between patient classification of our model and the CGI-S). Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728). We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

Indicated prevention of mental illness is an important public health concern among youth. The aim of this study was to establish a European school-based professional screening among adolescents, which included variables on both a broad range of risk-behaviours and psychopathology; and to investigate the indicative value of adolescent risk-behaviour and self-reported psychopathology on help-seeking and psychological problems that required subsequent mental healthcare. A two-stage professional screening approach was developed and performed within the multi-centre study “Saving and Empowering Young Lives in Europe” (SEYLE). The first stage of screening comprised a self-report questionnaire on a representative sample of 3,070 adolescents from 11 European countries. In the second stage, students deemed at-risk for mental health problems were evaluated using a semi-structured clinical interview performed by healthcare professionals. 61 % of participants ( n  = 1,865) were identified as being at-risk in stage one. In stage two, 384 participants (12.5 % of the original sample) were found to require subsequent mental healthcare during semi-structured, clinical assessment. Among those, 18.5 % of pupils were identified due to screening for psychopathology alone; 29.4 % due to screening for risk-behaviours alone; and 52.1 % by a combination of both. Young age and peer victimization increased help-seeking, while very low body mass index, depression, suicidal behaviour and substance abuse were the best predictors of referral to mental healthcare. Screening of risk-behaviours significantly increased the number of detected students requiring subsequent mental healthcare. Screening of risk-behaviours added significant value in identifying the significant amount of European pupils with mental health problems. Therefore, attention to adolescent risk-behaviours in addition to psychopathology is critical in facilitating prevention and early intervention. Identifying factors that increase compliance to clinical interviews are crucial in improving screening procedures.

Abstract Background and Hypothesis Relapsing after a first episode of schizophrenia (FES) is a main predictor of clinical and functional prognosis. Brain-derived neurotrophic factor (BDNF) plays a critical role in neuronal development and plasticity, and its signaling may be altered by successive relapses. Design We assessed the impact of first relapse in the expression of the 2 isoforms of the BDNF tropomyosin-related kinase B (TrkB) receptor (active full-length TrkB-F and inactive truncated TrkB-T) in peripheral blood mononuclear cells from 53 FES patients in clinical remission followed up for 3 years. Results The group of participants that relapsed (n = 24) during the follow-up presented a significant decrease in the expression of the active TrkB-F receptor compared to baseline (M = 100 ± 28.13 vs. M = 83.42 ± 33.84, t = 2.5, P = .02), with no changes in the inactive TrkB-T receptor expression nor in BDNF plasma levels. This decrease also led to a significant decline in the F/T ratio (M = 1.13 ± 0.38 vs. 0.94 ± 0.36, t = 2.17, P = .041). No significant differences were found in the receptors’ expression nor in plasma levels in the group of cases that remained in remission (n = 29). These results were not associated with baseline differences between the groups in terms of the BDNF signaling pathway biomarkers, clinical or treatment variables. Conclusions These findings highlight the biological impact that a relapse produces over the systemic BDNF-TrkB signaling pathway, potentially undermining crucial neuronal functions. Identifying the actors involved can help design specific interventions for relapse prevention and improve the functional prognosis of people in the early stages of schizophrenia.

Depressive disorders represent the largest proportion of mental illnesses, and by 2030, they are expected to be the first cause of disability-adjusted life years [1]. The COVID-19 pandemic exacerbated prevalence and burden of depression and increased the occurrence of depressive symptoms in general population [2]. The urgency of implementing mental health services to address new barriers to care persuaded clinicians to use telemedicine to follow patients and stay in touch with them, and to explore digital therapeutics (DTx) as potential tools for clinical intervention [2]. The combination of antidepressants and psychotherapy is widely recommended for depression by international guidelines [3] but is less frequently applied in real-world practice. Commonly used treatments are pharmacological, but while being effective, some aspects such as adherence to the drug regimen, residual symptoms, resistance, lack of information, and stigma may hinder successful treatment. In case of less severe depression, standalone psychological therapies should be the first-line treatment option [3], but access to trained psychotherapists remains inequitable. DTx are evidence-based therapies driven by software programs to treat or complement treatment of a specific disease. DTx are classified as Medical Devices, and given their therapeutic purpose, they need to be validated through randomized controlled clinical trials, as for drug-based therapies. In the last 10 years, studies of digital interventions have proliferated; these studies demonstrate that digital interventions increase remission rates and lower the severity of depressive symptoms compared with waitlist, treatment as usual, and attention control conditions [4]. Despite the efficacy demonstrated in clinical trials, many of these tools never reach real-life patients; thus, it might be necessary to implement DTx in the public health system to expand access to valid treatment options. In this framework, DTx represent a good opportunity to help people with depression receive optimal psychotherapeutic care [5].

Deficits in emotional intelligence (EI) were detected in patients with bipolar disorder (BD), but little is known about whether these deficits are already present in patients after presenting a first episode mania (FEM). We sought (i) to compare EI in patients after a FEM, chronic BD and healthy controls (HC); (ii) to examine the effect exerted on EI by socio-demographic, clinical and neurocognitive variables in FEM patients. The Emotional Intelligence Quotient (EIQ) was calculated with the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). Performance on MSCEIT was compared among the three groups using generalized linear models. In patients after a FEM, the influence of socio-demographic, clinical and neurocognitive variables on the EIQ was examined using a linear regression model. In total, 184 subjects were included (FEM = 48, euthymic chronic BD type I = 75, HC = 61). BD patients performed significantly worse than HC on the EIQ [mean difference (MD) = 10.09, standard error (s.e.) = 3.14, = 0.004] and on the understanding emotions branch (MD = 7.46, s.e. = 2.53, = 0.010). FEM patients did not differ from HC and BD on other measures of MSCEIT. In patients after a FEM, EIQ was positively associated with female sex ( = -0.293, = 0.034) and verbal memory performance ( = 0.374, = 0.008). FEM patients performed worse than HC but better than BD on few neurocognitive domains. Patients after a FEM showed preserved EI, while patients in later stages of BD presented lower EIQ, suggesting that impairments in EI might result from the burden of disease and neurocognitive decline, associated with the chronicity of the illness.

In this cross-sectional study, physical activity, sport participation and associations with well-being, anxiety and depressive symptoms were examined in a large representative sample of European adolescents. A school-based survey was completed by 11,110 adolescents from ten European countries who took part in the SEYLE (Saving and Empowering Young Lives in Europe) study. The questionnaire included items assessing physical activity, sport participation and validated instruments assessing well-being (WHO-5), depressive symptoms (BDI-II) and anxiety (SAS). Multi-level mixed effects linear regression was used to examine associations between physical activity/sport participation and mental health measures. A minority of the sample (17.9 % of boys and 10.7 % of girls; p  < 0.0005) reported sufficient activity based on WHO guidelines (60 min + daily). The mean number of days of at least 60 min of moderate-to-vigorous activity in the past 2 weeks was 7.5 ± 4.4 among boys and 5.9 days ± 4.3 among girls. Frequency of activity was positively correlated with well-being and negatively correlated with both anxiety and depressive symptoms, up to a threshold of moderate frequency of activity. In a multi-level mixed effects model more frequent physical activity and participation in sport were both found to independently contribute to greater well-being and lower levels of anxiety and depressive symptoms in both sexes. Increasing activity levels and sports participation among the least active young people should be a target of community and school-based interventions to promote well-being. There does not appear to be an additional benefit to mental health associated with meeting the WHO-recommended levels of activity.