Early intervention in psychosis must extend beyond reducing duration of untreated psychosis; it requires adaptive systems capable of addressing clinical complexity within the socioeconomic realities of the communities they serve. ATEMPO 12, the First Episode Psychosis (FEP) program at Hospital Universitario 12 de Octubre (Madrid), has evolved over 15 years as a community-embedded, interdisciplinary model serving a predominantly low-income, culturally diverse urban population characterized by high substance use prevalence, migration-related stressors, and structural barriers to sustained care.

The program integrates psychiatry, clinical psychology, nursing, and social work within a flexible framework that connects acute inpatient units, rehabilitation and addiction services, and in-house specialized programs for alcohol-use disorder, treatment-resistant depression, resistant obsessive-compulsive disorder, and eating disorders. Community mental health centers—formally integrated into the program and offering extended afternoon schedules—facilitate additional outpatient follow-up or parallel care pathways when hospital attendance is limited by economic or social constraints. This stepped-care ecosystem enables early stabilization while preserving longitudinal continuity.

Clinical work is grounded in precision psychopathology: detailed phenomenological assessment, attention to personality structure, and rigorous differential diagnosis, including neurodevelopmental comorbidities. Psychotherapy follows a modular, stage-sensitive design combining psychoeducation, cognitive behavioral therapy for psychosis, metacognitive interventions, positive psychology strategies, family-based programs, and neuropsychological evaluation when indicated.

Psychopharmacological management emphasizes shared decision-making and fine-grained personalization, integrating pharmacokinetic principles, receptor-informed strategies, subjective experience, and functional outcomes. Long-acting injectable antipsychotics are considered early in selected cases with adherence vulnerability, while a structured clozapine pathway and access to repetitive transcranial magnetic stimulation (rTMS) and electroconvulsive therapy support treatment-resistant presentations.

Drawing on a large real-world cohort (2009–present), including patients with affective and substance-use comorbidity, ATEMPO 12 illustrates how interdisciplinary early psychosis systems can reconcile scientific rigor with social complexity. The model defends that early psychosis care must be flexible, culturally responsive, and pharmacologically sophisticated—bridging neuroscience, psychotherapy, and service design to optimize long-term trajectories.

None Declared

Integrative approaches in severe mental illness (SMI) represent a cornerstone of contemporary psychiatric practice, addressing the multifaceted needs of individuals affected by chronic and disabling mental disorders. This intervention focuses on the practical application of integrative care models that combine biological, psychological, social, and lifestyle-oriented strategies to improve clinical, functional, and recovery-related outcomes.

The presentation highlights how evidence-based pharmacological treatments can be effectively combined with psychosocial interventions, including psychotherapy, family involvement, vocational rehabilitation, and community-based support. Special emphasis is placed on the integration of physical health care, recognising the high burden of cardiometabolic comorbidity and reduced life expectancy among people with SMI. Emerging areas such as digital tools, shared decision-making, and recovery-oriented practices are also discussed as key components of truly integrative care.

Through clinical examples and real-world scenarios, the intervention illustrates common challenges in implementation, such as treatment resistance, comorbidity, fragmentation of services, and inequities in access to care. Strategies to overcome these barriers—particularly relevant for early career psychiatrists—are presented, highlighting the role of multidisciplinary teamwork, continuity of care, and personalised treatment planning across different stages of illness.

Overall, this intervention aims to provide participants with a concise, clinically oriented framework for delivering integrative, person-centred care in SMI, fostering improved outcomes, enhanced quality of life, and sustainable recovery pathways within diverse healthcare settings.

R. de Filippis Grant / Research support from: Angelini, Johnson & Johnson, Lundbeck, Neuraxpharm, and Rovi, Consultant of: Angelini, Johnson & Johnson, Lundbeck, Neuraxpharm, and Rovi

Leadership has become an essential competency in contemporary psychiatry, where clinicians are required to navigate increasing clinical complexity, multidisciplinary teamwork, and evolving healthcare systems. However, leadership development is often conceptualized primarily in terms of managerial or organizational skills, with limited attention to the role of personal wellbeing and self-management. This presentation proposes a wellbeing-centred model of leadership development in psychiatry, in which effective leadership begins with self-management capacities, including awareness of personal limits, prioritization, time management, and emotional regulation. Mentoring relationships can foster reflective learning, reduce professional isolation, and promote sustainable career trajectories. Within this perspective, wellbeing is reframed not as an individual achievement but as a prerequisite for effective and sustainable leadership in psychiatry.

None Declared

Psychiatric diagnoses traditionally rely on symptom-based classifications, which, despite providing a shared clinical and research framework, show weak alignment with underlying neurobiology. In response, data-driven, biologically informed approaches have emerged, yet most still depend on group-level comparisons that assume homogeneity and obscure individual variability. Normative modeling (NM) offers a promising alternative, quantifying individual deviations from population-derived normative distributions and enabling the detection of neurophysiological alterations at the single-subject level (Marquand et al. Biol Psychiatry 2016; 80:552-561).

This study aims to present a framework for clustering based on deviations from normative electrophysiological trajectories to identify transdiagnostic subtypes of neurodevelopmental and psychiatric disorders. The approach leverages a large, harmonized HD-EEG dataset to uncover biologically grounded brain–behavior profiles that transcend traditional diagnostic boundaries.

We analyzed a multisite EEG dataset comprising 1,701 participants, including healthy controls, and individuals with attention-deficit/hyperactivity disorder, autism spectrum disorder, anxiety, learning disorders, and their comorbidities. Normative models were built for a comprehensive set of EEG features (n = 1957), and individualized deviation scores were computed. These multivariate deviation profiles were then clustered using similarity network fusion to identify subgroups with distinct electrophysiological patterns. The resulting clusters were subsequently characterized in terms of diagnostic composition and behavioral profiles.

We identified three neurophysiological subtypes that did not align neatly with traditional diagnostic categories (Fig. 1). Electrophysiologically, C2 (predominantly HC) showed deviation scores close to normative EEG trajectories, whereas C1 (internalizing symptoms) and C3 (externalizing diagnoses) exhibited more pronounced and often opposing deviations across key features. Behavioral comparisons revealed significant differences across behavioral domains (Fig. 2). C1 showed deficits in executive function and elevated emotional reactivity; C3 had higher hyperactivity-related scores; C2 showed the lowest scores across most domains, reflecting a broadly normative profile. Finally, EEG features significantly predicted cluster-specific behavioral traits (Fig. 3).Image 1:

Our EEG-based, data-driven stratification revealed transdiagnostic subtypes with distinct electrophysiological signatures, behavioral phenotypes, and brain-behavior associations. These biologically grounded profiles, which transcend traditional diagnostic boundaries, provide a principled framework to advance transdiagnostic research in psychiatry.

None Declared

Alzheimer’s disease (AD) is still a very common cause of dementia and a common cause of death in elderly humans. No effective long-term treatment has been found so far.

TPS (Transcranial Pulse Stimulation) which can be individually tracked by MRI-scans offers new perspectives to ameliorate deficits caused by AD. Pilot studies show beneficial effects of TPS on learning and memory. There are also reports of restorative structural changes in the thickness of the cerebral cortex due to the stimulation.

65 out-patients with Alzheimer’s disease (with light to moderate symptoms) received 6.000 pulses of TPS (0.2 mJ/mm2 per single pulse, with a frequency of 4 Hz) per session. The application of the pulses with Neurolith by Storz Medical was inividually navigated by use of current MRT-images of the patients. TPS-pulses were administered bilaterally into the frontal, parietal and temporal cortex. Pulses were applicated over a period of 2 weeks (3 sessions per week). Booster TPS-sessions were applied once every 6 weeks. Cognitive capabilities (especially executive functions) of the patients were tested using the Stroop-Test (colour-word-interference-test). The Stroop-Test is a standardized test for executive functions. Patients were tested using a pre – post design (t0 pre stimulation : t1 two weeks and 6 months later).

TPS-stimulation over a period of two weeks (6 sessions) showed ameliorating effects on performance in the Stroop-Test. The mean-score was diminished significantly (pre vs. post ; p < 0.05 – paired T-test). Single patients showed extraordinary improvements by shortening completer times in the Stroop-Test by halve. Mood and depressive symptoms of the patients were also ameliorated. The mean of the BDI measured before and after the treatment period of 2 weeks diminished from 19.2 to 11.5. The beneficial effects remained up to 6 months, No significant side-effects occured during all the sessions in none of the patients. In single cases patients complained about transient headaches (4 %) and fatigue (3 %).

The results of this trial show that cognitive impairments of executive functions and depressive symptoms in Alzheimer’s disease may be ameliorated using TPS as a noninvasive brain stimulation method. No severe side-effects were observed.

Thus neuronavigated TPS may be considered as a novel promissing tool of noninvasive brain stimulation (NIBS) in severe neurodegenerative diseases like Alzheimer’s disease.

None Declared

Non-suicidal self-injury (NSSI) is a common high-risk behavior in adolescents and it occurs in various psychiatric disorders, especially major depressive disorder (MDD). It remains largely unknown whether and which brain functional networks contribute to NSSI across youth psychiatric disorders.

This study aimed to identify common brain functional networks associated with NSSI across youth psychiatric disorders, and to examine their relationships with NSSI behavior, addiction, and its functions. Furthermore, we sought to validate the generalizability of these neural correlates in independent clinical cohorts.

This study analyzed functional brain imaging data acquired from 156 adolescents (MDD+NSSI group, n = 44, age = 15.32 ± 1.51; MDD-NSSI group, n = 32, age = 15.36 ± 1.96; healthy controls, n = 80, age = 15.92 ± 2.72). NSSI behavior, addiction and its four NSSI functions (internal and external emotion regulation, social influence and sensation seeking) were assessed using the Ottawa Self-injury Inventory. Using support vector machine recursive feature elimination classification and regression models, we investigated the brain functional networks that predicted NSSI. External validations were performed in an ADHD cohort (n = 40) and a transdiagnostic cohort (n = 40).

The brain networks related to NSSI behavior were mainly composed of inter-network connections between the fronto-parietal, motor, limbic, basal ganglia networks. These networks were also associated with NSSI addiction and its four functions. Notably, the fronto-parietal network was involved in all NSSI components. External validations in both the ADHD and the transdiagnostic cohorts validated the associations of these functional networks with NSSI severity.

Our results demonstrate roles of the fronto-parietal, motor, limbic and basal ganglia networks in NSSI across youth psychiatric disorders, which may serve as neural markers and potential targets for prevention and intervention.

None Declared

Irritability is a common and impairing transdiagnostic symptom across multiple psychiatric disorders in children and adolescents, including ADHD, generalized anxiety disorder, and depression. It is often manifested as a stable, trait-like phenotype that significantly impacts daily functioning and long-term outcomes. Despite its clinical relevance, the underlying neural mechanisms—particularly those that generalize across diagnostic categories—remain poorly understood.

This study aimed to identify transdiagnostic neural markers of irritability in a large developmental sample using resting-state functional connectivity. Specifically, we sought to determine whether functional network connectivity patterns could predict irritability severity and to validate their generalizability across both internal subsamples and an external clinical cohort.

We analyzed resting-state fMRI data from 1143 children and adolescents (age = 11.65 ± 3.47 years) from the Healthy Brain Network project, encompassing diagnoses such as ADHD, depression, anxiety, and autism spectrum disorder. Irritability was measured using the Affective Reactivity Index. Connectome-based predictive modeling (CPM) was employed to identify functional networks associated with irritability. Internal validation was conducted using two random subsamples and an alternative brain atlas. Furthermore, an support vector machine (SVM) classifier was applied to an independent depression cohort (n = 129) to externally validate the robustness of the identified networks.

The positive predictive network for irritability primarily featured connections between the fronto-parietal network and other networks, whereas the negative network involved connections between the basal ganglia network and other networks. Internal validations confirmed that both the fronto-parietal network and the basal ganglia network consistently predicted irritability. External validation in the depression cohort further supported the role of these networks in irritability, successfully differentiating between high- and low-anger groups using SVM classification.

Our findings underscore the central roles of the fronto-parietal network—implicated in cognitive control—and the basal ganglia network—associated with motivational and emotional processes—in pediatric irritability across diagnostic boundaries. These networks may reflect a developmental imbalance between top-down regulation and bottom-up emotional responding, offering potential neural targets for early intervention and transdiagnostic treatment strategies.

None Declared

Bullying is one of the most common adverse social experiences during early adolescence. Identifying potential brain-based biomarkers that modulate vulnerability to internalizing symptoms after bullying could inform targeted prevention strategies.

To identify potential neuroimaging biomarkers associated with subclinical anxiety, depressive, and obsessive-compulsive symptoms in adolescents who were exposed to bullying.

We collected neuroimaging and subclinical mental health data at the 18-year follow-up of the INMA-Sabadell cohort. Among 159 healthy adolescents without neuropsychiatric or neurodevelopmental disorders, a subgroup of 12 adolescents reported bullying exposure at age 11 (Olweus Bully/Victim Questionnaire). An age- and sex-matched control subsample of 12 non-victims was selected. Anatomical, functional, and diffusion magnetic resonance imaging were processed with FreeSurfer, MELODIC, and TRACULA to derive cortical surface area and thickness, subcortical volumes, functional connectivity, and diffusion metrics. Subclinical symptoms were assessed with the Obsessive-Compulsive Inventory-Child Version and the Depression, Anxiety, and Stress Scale (DASS). Symptom–brain associations were compared between bullying victims and non-victims using Fisher Z-transformed Pearson correlations (structural data) or multivariate ANOVA (functional data).

Adolescents exposed to bullying at age 11 showed a stronger positive relationship between left inferior parietal lobule (IPL) surface area and DASS-Anxiety scores at age 18 compared to non-victims (Z=5.01; pBonf=0.0004). Within-group analyses found a significant positive correlation in victims (R(9)=0.94; pBonf=0.00086), whereas non-victims exhibited a non-significant negative correlation (R(9)=-0.53; pBonf=1).Image 1:

Preadolescent bullying may modulate IPL-anxiety coupling, suggesting that early social adversity can leave lasting imprints on brain–anxiety relationships. The IPL, implicated in social cognition, blame attribution, and attentional processing of unexpected stimuli, has also been related to polygenic risk for neuroticism, with previous research pointing to an unidentified environmental moderator. Our exploratory study highlights bullying as a potential environmental risk factor shaping neurobiological vulnerability to adolescent internalizing symptoms.

None Declared

Efforts to identify EEG biomarkers in psychiatry have been hampered by poor reproducibility and inconsistent findings, limiting their clinical translation. Underpowered studies, characterized by small sample sizes and unstable effect estimates, are thought to be a major contributor to this issue.

Here, we aim to systematically investigate how sample size affects the stability and replicability of group comparisons and brain–behavior associations in psychiatric EEG research.

We analyzed a large cohort of ~2,900 participants, including individuals with neurodevelopmental or psychiatric conditions (ADHD, ASD, Anxiety, and Learning disorders) and healthy controls. Using iterative subsampling within each group, we conducted two analyses: (1) group comparisons with healthy controls via ANCOVA, controlling for age and sex, and (2) Spearman correlations between EEG features and clinical scores within each group. We examined trends in effect sizes and the significance of group differences across a wide range of sample sizes, from 10 participants to several hundred. The analyses covered 103 EEG features measured across 19 channels, with additional metrics averaged across all channels and 152 clinical scores.

At smaller sample sizes, significance detection was highly unstable, with results fluctuating across iterations (Fig. 1). We identified four distinct patterns in the evolution of significance across subsamples (Fig. 2a) and observed that overall stability improved with increasing sample size. Across disorders, the minimum sample size required for 95% reproducibility was substantially higher than the typical sample sizes used in EEG studies (Fig. 2b). Smaller samples exhibited high false-negative rates and inflated effect sizes, often overestimating and failing to detect true effects (Fig. 2c). These patterns were consistent across both group comparisons (ANCOVA) and within-group EEG–behavior correlations, highlighting the influence of sample size and clinical heterogeneity on the reliability of brain–behavior associations.Image 1:

Our findings demonstrate that typical EEG study sample sizes are insufficient to ensure reproducible results, leading to inflated or missed effects. Adequate scaling of cohorts is therefore essential for reliable biomarker discovery and clinical translation in psychiatry.

None Declared

Deep Brain Stimulation (DBS) is a treatment option for severe, treatment-refractory (TR) obsessive-compulsive disorder (OCD). Yet, real-world practices may vary across international centers potentially resulting in a variability of treatment outcomes.

To describe (i) eligibility criteria and definitions of TR OCD to qualify for DBS (ii) DBS targets (iii) governance/referral processes, and (iv) pre- and post-operative management—including programming, adverse-event handling, and rehabilitation—across five European programs of DBS for TR-OCD.

As an initiative of the Psychiatric Surgery Task Force of the World Society of Stereotactic and Functional Neurosurgery a questionnaire was sent to selected international DBS centers with a dedicated psychiatric team asking detailed questions regarding patient selection, experience and management of patients treated with DBS for TR OCD. Here we report the results from the participating European centers.

Five programs(Amsterdam, Freiburg, Grenoble, Leuven, Umeå) reported a total experience of 241 patients with severe TR OCD treated with DBS. Targets included nucleus accumbens, ventral/anterior limb of the internal capsule, superolateral medial forebrain bundle/ventral tegmental area, anteromedial subthalamic nucleus and the bed nucleus of the stria terminalis.

Common inclusion criteria included age over 18 years, primary OCD with marked severity and chronicity ranging from severe OCD on the Yale-Brown Obsessive Compulsive scale, with a minimum disease duration of ≥5 years and capacity to consent to the treatment.

Definitions of TR OCD were similar across the centers: unsuccessful trials of ≥2 selective serotonin reuptake inhibitors plus clomipramine, antipsychotic augmentation, and cognitive behavioural therapy with exposure/response prevention.

Common exclusion criteria across the centers included psychosis, major surgical/medical contraindications, significant central nervous system disease/trauma, active substance misuse, severe personality disorder, and acute suicidality. Accepted psychiatric comorbidities varied slightly between centers where some allowed for comorbidity e.g with anorexia nervosa.

All centers mentioned psychotherapy as part of the post-surgical rehabilitation

Overall the definition of TR OCD and inclusion criteria for DBS were harmonized across multiple centers in Europe. DBS may be considered for selected patients with severe, TR OCD and should be provided by a dedicated, multidisciplinary team with psychiatric expertise.

None Declared

Obsessive-compulsive disorder (OCD) is a persistent and severely impairing mental health condition. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising option for patients unresponsive to standard treatments. However, the optimal cortical target for maximizing clinical outcomes remains unclear.

This study compared the effects of low-frequency rTMS (LF-rTMS) over two different cortical targets for reducing OCD symptom severity and associated functional impairment.

Thirty patients with treatment-resistant OCD were consecutively enrolled in two OCD clinics and assigned to receive twenty sessions of 1 Hz 30min rTMS over either right orbitofrontal cortex (R-OFC) or bilateral pre-supplementary motor area (BL-preSMA). Twelve patients in the R-OFC group and fifteen in the BL-preSMA group completed the treatment. Clinical evaluations included the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) for OCD symptom severity and the Sheehan Disability Scale (SDS) for functional impairment, assessed at baseline (T0), after one week (T1), two weeks (T2), and at the end of treatment (T3). Outcomes were analyzed using Linear Mixed Models (LMM).

Both protocols produced significant OCD symptom reductions from baseline to T1 (Coefficient = -4.54, p = 0.008) and T3 (Coefficient = -5.64, p = 0.013), with no differences between groups. A significant treatment × time interaction emerged for SDS scores. R-OFC stimulation led to functional improvement at T2 (Coefficient = -4.94, p = 0.034) and T3 (Coefficient = -5.27, p = 0.05), while BL-preSMA stimulation was associated with relative worsening at T1 (Coefficient = 8.29, p = 0.001), T2 (Coefficient = 10.54, p < 0.001), and T3 (Coefficient = 9.27, p = 0.011). Higher baseline disability predicted greater symptom reduction in BL-preSMA patients at T2 (Coefficient = 0.75, p = 0.022) and T3 (Coefficient = 1.18, p = 0.005).

R-OFC and BL-preSMA rTMS treatment both produced OCD symptom severity reduction, while R-OFC stimulation was more effective in reducing disability, and BL-preSMA stimulation was more beneficial for patients with higher baseline functional impairment. These results highlight the importance of personalizing rTMS treatment of OCD patients based also on their associated disability.

None Declared

Schizophrenia (SCZ) is a severe psychiatric disorder with only partly understood biological mechanisms. Lipids, which account for more than half of the brain’s dry weight, play fundamental roles in myelination, neurotransmission, and immune-glial interactions. Increasing evidence has linked lipid dysregulation to psychiatric disorders, yet most studies rely on bulk lipidomics, which lacks anatomical resolution. Spatial approaches are needed to characterize lipid distribution in the human brain and to investigate disease-related alteration

The aim of this study was to perform high-resolution spatial lipidomic mapping of the dorsolateral prefrontal cortex (DLPFC) in post-mortem human brains, and to conduct preliminary analyses of lipid alterations in SCZ compared with matched controls.

Post-mortem DLPFC tissue was obtained from the NIMH Human Brain Collection Core. Five non-diagnostic cases were analyzed to define the spatial distribution of individual lipid species, while an additional cohort of five SCZ and five matched controls was included for preliminary group comparisons. Sections were processed with a standardized matrix-assisted laser desorption ionization (MALDI) imaging workflow in negative-ion mode (Figure 1). Multivariate segmentation and dimensionality reduction were applied to identify regional molecular profiles. Region- and group-level differences were tested with ANOVA including false discovery rate correction. Lipid assignments were confirmed on tissue by MALDI-LIFT MS/MS and validated through curated database and literature matching of fragment ions.

Spatial analyses revealed reproducible separation of white and grey matter subregions, with PCA showing that the first five components explained 87% of variance (Figure 2). Sulfatides were enriched in white matter, whereas N-acyl phosphatidylserines localized to upper cortical layers, with highly significant regional differences (pFDR < 10⁻¹⁰ for the most discriminant species). Preliminary SCZ versus control analyses based on Pearson’s correlation values and ROC curves stratified by white and grey matter identified phospholipid alterations suggesting possible links with compartment-specific neuroglial and metabolic processes (Figure 3).Image 1:

This work provides one of the first detailed spatial lipidomic mappings of the human DLPFC, uncovering novel region- and layer-specific signatures with potential biological relevance. Preliminary case-control analyses highlight lipid deregulations that may contribute to cortical dysfunction in SCZ. These findings emphasize the translational value of spatial omics approaches for identifying metabolic alterations and candidate biomarkers that could inform precision psychiatry.

None Declared

Theta burst stimulation (TBS) is a more time-efficient alternative to repetitive transcranial magnetic stimulation (rTMS) for depression, especially in resistant cases. Conventional protocols, however, require weeks of daily visits, limiting adherence. Accelerated intermittent TBS (aiTBS, ≥2 sessions/day) seeks to shorten treatment and improve outcomes, but evidence remains limited, warranting systematic evaluation of its efficacy, safety, and clinical utility.

To assess the efficacy of aTBS for major depressive disorder (MDD) and bipolar depression (BD); to compare the effectiveness of hyper-accelerated versus moderately accelerated schedules; to investigate potential sources of heterogeneity from subgroup analyses, including targeting method (e.g. neuronavigated approaches), acceleration schedule and type of TBS protocol.

This Systematic Review and meta-analysis followed PRISMA guidelines and was registered on PROSPERO (CRD420251081143). PubMed, Embase, Cochrane CENTRAL, ClinicalTrials.gov, and MedRxiv were searched up to July 2025. Eligibility criteria included randomized controlled trials (RCTs) enrolling adults (18–65 years) with MDD or BD treated with any aTBS protocol versus sham. The primary outcome was depressive symptom reduction; secondary outcomes were response and remission rates. Random-effects pairwise meta-analyses were performed; risk of bias was assessed with Cochrane RoB-2.

Thirteen sham-controlled RCTs (n=488) were included. Compared with sham, aiTBS significantly reduced depressive symptoms (Hedges’ g = -0.60; 95% CI [-0.96, -0.24]; p=0.0011), a medium-to-large beneficial effect according to Cohen’s benchmarks. Heterogeneity was moderate (I²=64.1%, 95% CI [35.0–80.2]) (figure 1); leave-one-out analyses confirmed robustness. No evidence of publication bias was detected (Egger’s p=0.66). Response rates (10 RCTs, n=373) (figure 2) favored aiTBS (RR = 2.00; 95% CI [1.39, 2.89]; p=0.0002) with low heterogeneity (I²=28.5%). Remission rates (9 RCTs, n=360) (figure 3) were nearly doubled (RR = 1.97; 95% CI [1.00, 3.86]; p=0.049), with low-to-moderate heterogeneity (I²=34.5%). Subgroup analyses suggested stronger effects with functional connectivity-based targeting, higher stimulation doses (≥50 sessions, ≥90,000 pulses), 10 sessions/day, and 50-minute intersession intervals.Image 1:

aiTBS appears to be an effective and well-tolerated intervention for depression, providing significant reductions in symptoms and doubling response and remission rates. Efficacy is influenced by stimulation dose and target localization. These findings support aTBS as a rapid-acting, safe, and clinically relevant neuromodulation strategy, with potential to enhance adherence and accessibility in psychiatric care.

None Declared

Experiencing severe trauma can have lasting effects that continue into old age, often leading to physical health issues. Severe trauma can also affect future generations within a family. Such intergenerational effects may result from biological dysregulation caused by epigenetic processes, including modifications of DNA methylation. However, it remains uncertain whether the effects of parental trauma are passed down through generations to influence the biological aging of descendants.

In our studies, we focused on epigenetic age, a biological measure of aging based on changes in DNA methylation that happen over time. Epigenetic age can differ from chronological age and is thought to reflect the body’s physiological condition. We aimed to examine whether Holocaust exposure and its psychological effects are linked to epigenetic age across two generations: those who lived during WWII (G1) and their children born after the war (G2).

In Study 1, we examined a cohort of 20 G2 to Holocaust survivors (mean age=65). We explored whether their symptoms and their perceptions of their parents’ PTSD symptoms relate to epigenetic accelerated aging (EAA), calculated as the difference between epigenetic age and chronological age. In Study 2, we analyzed a larger cohort consisting of 50 parent-offspring dyads: G1 and G2 (mean age=87 and 56, respectively), some from Holocaust survivor families and others from non-Holocaust Jewish families. We investigated whether Holocaust G1 and G2 differ in EAA compared to their non-Holocaust counterparts. Additionally, we examined whether PTSD symptoms, other symptoms, and parental behaviors are associated with EAA across generations.

Study 1 found that Holocaust G2 PTSD symptoms and perceived maternal PTSD were linked to higher EAA. Study 2 confirmed some of these findings. Moreover, although there was no significant difference in EAA between the G1 groups, a high level of traumatic exposure during WWII was associated with increased EAA. Additionally, Holocaust G2 individuals exhibited higher EAA compared to non-Holocaust G2. Negative parental behaviors (reported by G1) and childhood abuse and neglect (reported by G2) were connected to higher EAA in G2.

The current findings suggest that characteristics of Holocaust G1 significantly influence the epigenetic aging of their offspring. Connections to Holocaust exposure, parental behavior, and childhood abuse suggest traumatic aftereffects in G1 may leave a lasting imprint on their descendants’ biological aging processes. Future research on epigenetic aging may improve preventive strategies addressing intergenerational effects of trauma and help evaluate the effectiveness of interventions aimed at managing age-related health issues.

None Declared

Obsessive-compulsive disorder (OCD) is a chronic and disabling psychiatric condition for which pharmacological interventions are effective, yet clinical outcomes remain heterogeneous. Identifying neural predictors of treatment response could inform precision medicine approaches. Functional magnetic resonance imaging (fMRI), particularly resting-state functional connectivity (RS-FC), has emerged as a promising tool to characterize baseline neural markers associated with treatment outcomes.

This study aimed to investigate whether baseline RS-FC patterns predict clinical improvement in OCD patients undergoing pharmacological treatment.

We analyzed a dataset comprising 27 adult OCD patients (15 females; mean age 33.5 ± 8.2 years) who underwent 3 months of pharmacological treatment. Clinical symptoms were evaluated using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) at baseline and post-treatment. Resting-state fMRI acquisitions were performed at baseline. Independent component analysis (ICA) was conducted to identify functional networks, and baseline RS-FC values were correlated with Y-BOCS difference (Post – Pre). Paired-sample t-tests assessed clinical outcomes.

Patients showed a significant reduction in global OCD symptomatology following pharmacological intervention (Y-BOCS: Mean Pre = 31.82, SD = 4.83; Mean Post = 24.19, SD = 11.10; t(26) = 4.53, p < .001). Improvements were observed in both the Obsessions subscale (Mean Pre = 17.00, SD = 2.42; Mean Post = 12.41, SD = 5.44; t(26) = 4.85, p < .001) and the Compulsions subscale (Mean Pre = 14.82, SD = 4.10; Mean Post = 11.78, SD = 6.02; t(26) = 3.61, p = .001). Resting-state analysis revealed that decreased baseline FC in the right Executive Network (MNI coordinates: = x = -34, y= 53.9, z= 53.4, cluster extent = 25, p = .042), Salience Network (MNI coordinates: x= -70, y = -43.8, z= 5.02, cluster extent = 121, p = .013), and Cerebellar network (MNI coordinates: x= -64, y= 20, z= -32.7, cluster extent = 226, p = .040) were significantly associated with greater Y-BOCS symptom reduction, suggesting predictive relevance of these networks for pharmacological response. Effect sizes were medium-to-large across symptom reductions (Cohen’s d range: 0.70–0.95).

Our findings indicate that baseline hyperconnectivity in the executive, salience and cerebellar networks predicts favorable response to pharmacological treatment in OCD. These results highlight the importance of balanced goal-directed behavior and action planning in the modulation of treatment outcomes and suggest that RS-FC markers may help stratify patients most likely to benefit from pharmacotherapy. Integrating neuroimaging predictors into clinical decision-making could support the development of personalized treatment strategies for OCD.

A. D. Costa Grant / Research support from: PhD scholarship from the Foundation for Science and Technology (2022.09472. BD), M. Picó-Pérez: None Declared, P. Morgado Grant / Research support from: FLAD Science Award Mental Health, Consultant of: Angelini, AstraZeneca, Bial, Biogen, Janssen-Cilag, Lundbeck, Viatris

Anxiety disorders represent one of the most prevalent mental health conditions in adulthood, often associated with significant impairment in daily functioning and well-being. Standard treatments include pharmacological and cognitive-behavioral approaches, but additional behavioral interventions may enhance outcomes. Behavioral Relaxation Training (BRT), grounded in Applied Behavior Analysis (ABA), focuses on the systematic acquisition of relaxation postures and breathing patterns, offering a direct behavioral strategy to reduce physiological arousal and anxiety symptoms.

This study aimed to investigate the efficacy of BRT in reducing anxiety symptoms and improving relaxation behaviors in adults diagnosed with anxiety disorders, using a controlled experimental design.

A multiple baseline design across three caregivers was employed to demonstrate experimental control. Each participant engaged in structured BRT sessions designed to teach and generalize relaxation postures and regulated breathing. Outcome measures included the Behavioral Relaxation Scale (BRS) as a direct behavioral index of relaxation, alongside standardized clinical instruments such as the Hamilton Anxiety Rating Scale (HAM-A) and the Clinician-Administered PTSD Scale (CAPS), following procedures described in previous research (Lundervold et al., 2013).

Findings revealed consistent reductions in anxiety severity and significant improvements in relaxation behavior across all participants. Decreases in HAM-A and CAPS scores paralleled improvements in BRS performance, indicating both subjective and behavioral gains. Treatment effects were maintained at follow-up, supporting the stability of outcomes over time.

Preliminary evidence suggests that BRT, when embedded within an ABA framework, represents an effective behavioral intervention for adults with anxiety disorders. The approach promotes emotional regulation, reduces physiological tension, and complements existing therapeutic models. Further studies with larger samples are warranted to strengthen the empirical base and explore generalization across broader clinical populations

None Declared

As social media use continues to increase, particularly among adolescents, understanding its impact on mental health is becoming increasingly urgent.

This study explored the relationships between alexithymia, FoMO, excessive social media use, and psychiatric symptoms in a clinical adolescent sample, hypothesizing that alexithymia would be linked to higher FoMO and social media addiction, with internalising and externalising problems as potential mediators. It also examined whether these variables differed based on daily use of popular social media platforms.

A total of 197 participants aged 14 to 18 years were recruited from child and adolescent psychiatric outpatient clinics in two public hospitals. Participants were interviewed by a child and adolescent psychiatrist and then asked to complete the Strengths and Difficulties Questionnaire, the Alexithymia Questionnaire, the Bergen Social Media Addiction Scale and the Fear of Missing Out Scale.

Mediation analyses revealed that while alexithymia significantly predicted social media addiction, it did not directly predict FoMO. Instead, the relationship between alexithymia and FoMO was fully mediated by internalizing and externalizing problems. In addition, externalising symptoms partially mediated the relationship between alexithymia and social media addiction.Image 1:Image 2:

These findings highlight the complex emotional and behavioural contexts underlying problematic social media use among adolescents and underscore the need for interventions that address emotional processing difficulties and comorbid psychopathology in this population.

None Declared

Childhood maltreatment (CM) is a widely recognized risk factor for mental disorders across the lifespan, although the underlying neurobiological mechanisms remain partially understood. The hypothalamic-pituitary-adrenal (HPA) axis is the primary physiological stress response system, and genetic and epigenetic variability in associated genes, such as FKBP5 and NR3C1, have been proposed as mechanisms of risk or resilience in interaction with environmental exposures.

i) to investigate whether CM leaves detectable epigenetic marks in exposed children and adolescents, genome-wide and in candidate genes, and (ii) to examine how epigenetic variability in FKBP5 and NR3C1 modulate HPA-axis diurnal and psychosocial stress responses.

203 children and adolescents were enrolled in the Epi_Young_Stress_Project (130 with psychiatric diagnoses and 81 controls). Cortisol diurnal profiles were assessed using four saliva samples collected throughout the day. Psychosocial stress responses were measured with five samples during the Trier-Social-Stress test. DNA methylation was quantified in PBMCs using Illumina EPIC_array_v1. Epigenome-wide association analyses (EWAS) were conducted using “Limma”. Principal component analyses were applied to characterize gene-level variability in candidate genes. Linear regression models were used for the study aims.

EWAS analyses revealed 29 differentially methylated positions between maltreated and non-maltreated youths, although none of them survived FDR correction. CM was associated with methylation in FKBP5, but not NR3C1. Diurnal cortisol profile was related to methylation in both genes, and interaction effects between genes were detected. TSST cortisol profile was associated with FKBP5 methylation.

CM leaves epigenetic signatures HPA-axis related genes, which may influence diurnal and psychosocial cortisol secretion in youths.

None Declared

Post-traumatic stress disorder (PTSD) is a psychiatric condition characterized by intrusive memories, avoidance, negative mood alterations, and hyperarousal following trauma. Beyond its psychological burden, PTSD exerts multisystemic effects, including autonomic dysregulation, hypothalamic–pituitary–adrenal axis imbalance, inflammation, and health-risk behaviors, which increase cardiovascular disease (CVD) risk. Conversely, acute cardiac events can themselves precipitate PTSD, suggesting a bidirectional relationship.

This meta-analysis examined: (1) the risk of incident CVD among individuals with PTSD, and (2) the prevalence of PTSD in patients with CVD

Following PRISMA guidelines, PubMed, Scopus, and Web of Science were searched up to May 2025. Eligible studies included observational or interventional human research reporting CVD incidence in PTSD or PTSD prevalence following CVD. Effect sizes were pooled using random-effects models. Heterogeneity was assessed with Q, I², and τ². Publication bias was evaluated with funnel plots and Egger’s test.

Twenty-nine studies (n ≈ 2.7 million) met inclusion. Eighteen assessed CVD risk in PTSD populations (n ≈ 2.6 million). Pooled analysis showed PTSD increased CVD risk by 75% (log RR = 0.56, 95% CI = 0.42–0.69; p < 0.0001). Eleven studies (n ≈ 148,000) reported PTSD prevalence following CVD, with pooled estimates indicating 25.3% (95% CI = 0.19–0.31) of cardiac patients met diagnostic criteria or exhibited clinically significant PTSD symptoms. Both directions showed substantial heterogeneity but consistent effects across study designs and populations.Image 1:

PTSD and CVD are reciprocally linked. PTSD substantially elevates cardiovascular risk, while cardiovascular events act as potent psychological stressors, frequently triggering PTSD. These findings highlight the need for integrated care: trauma-informed strategies in cardiology and cardiovascular risk monitoring in psychiatric practice. Early identification and multidisciplinary interventions may help disrupt this pathological cycle and improve long-term prognosis.

None Declared

Obsessive–compulsive disorder (OCD) carries a markedly higher risk of suicidal thoughts and behaviors than the general population. Risk is amplified by affective and anxiety comorbidities, childhood trauma, persistent psychological distress, and certain symptom dimensions. Despite these insights, no reliable strategy exists to predict suicide risk in OCD. Machine-learning approaches are emerging as powerful tools for risk prediction in psychiatry and have shown promise in OCD populations.

To develop and validate a machine-learning predictive model of suicide risk in OCD using routinely collected clinical and sociodemographic variables.

Longitudinal study of 199 OCD patients (mean follow-up 17.8 years). Input variables: sociodemographic data (age at onset/diagnosis, years untreated, sex), psychiatric comorbidities, substance use (alcohol, cannabis, stimulants, benzodiazepines, opioids; tobacco excluded), family history of OCD and suicide, medical comorbidities, childhood trauma (Childhood Trauma Questionnaire subscales), and OCD severity (Yale–Brown Obsessive Compulsive Scale).

Target variable: suicide risk classified into three categories—(1) no suicidal behavior, (2) suicidal ideation or thoughts of death, (3) suicide attempt or completed suicide.

Suicidal behaviors were identified through clinical interviews and confirmed in psychiatric records. Supervised machine-learning models (linear discriminant analysis, naive Bayes) were trained with leave-one-out cross-validation. Performance was assessed with Cohen’s kappa, sensitivity, specificity, F1-score, and AUC.

The optimal model identified three key predictors: family history of suicide, affective comorbidity, and substance use (excluding tobacco). This combination achieved κ = 26.8 %, sensitivity 71.4 %, specificity 74.4 %, F1 = 62.7 %, and AUC = 0.80, indicating moderate predictive capability. Neither OCD severity (Y-BOCS) nor childhood trauma improved accuracy. In the cohort, 25 % experienced suicidal ideation or behavior and 2.5 % (5 patients) died by suicide.Image 1:

A straightforward machine-learning model based on standard clinical data predicts suicide risk in OCD with moderate accuracy. The three predictors are routinely assessed, showing that data-driven modeling validates traditional evaluation for early detection and preventive monitoring.

Machine-learning analysis confirms and strengthens standard psychiatric assessment. The presence of family history of suicide, affective comorbidity, and substance use provides sufficient information for a moderate-accuracy estimate of suicide risk in OCD, proving that careful routine evaluation remains the cornerstone of early detection and targeted prevention.

None Declared