To evaluate the efficacy and safety of high-frequency repetitive transcranial magnetic stimulation (HF rTMS) using the H7-coil, delivered once daily over 20 consecutive weekdays, as an adjunct to stable antipsychotic treatment for persistent negative symptoms in schizophrenia, a randomized, sham-controlled trial.

We conducted an industry-independent, randomised, double-blind, sham-controlled superiority trial with concealed allocation and masked outcome assessment, between 2019 and 2025, at the Sveti Ivan Psychiatric Hospital in Zagreb, Croatia. Eligible participants were outpatients diagnosed with schizophrenia (ICD-11: F20), aged 18–55 years, of both sexes, with a PANSS negative symptom subscale score > 24 and positive subscale score < 20, and stable antipsychotic therapy for ≥3 months. The primary outcome was the change in total score on the Scale for the Assessment of Negative Symptoms (SANS), adjusted for key covariates. Bayesian modelling was employed throughout, estimating treatment effects via posterior probabilities and Bayes factors (BFs).

A total of 87 participants were randomised: 43 to the H7-coil arm (34% female) and 44 to the sham arm (32% female). Median age was 38 (IQR 27–46) years in the H7 group and 34 (IQR 26–45) years in the sham group. The groups were well balanced across key prognostic variables. Both groups showed improvement in negative symptoms over time. In the H7-coil arm, the adjusted median reduction in SANS total score was 37 points (41%), compared to 26 points (31%) in the sham group. Bayesian analysis yielded a posterior probability of 0.87 that the H7-coil was superior to sham (β < 0), with a corresponding BF of 3.4, indicating moderate evidence in favour of the H7-coil. Evidence of superiority was also observed for the SANS subdomains of blunted affect, alogia, and avolition (BFs 3.0–5.6), as well as for the BNSS total score. No serious adverse events were reported.

This trial provides bayesian evidence that HF rTMS with the H7-coil may reduce negative symptom severity in schizophrenia and appears to be safe and well tolerated. These findings support further investigation of deep rTMS as an adjunctive treatment for persistent negative symptoms.

TMS; Schizophrenia; Psychotic disorder; negative symptoms; H7-coil; sham-coil.

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Suicide is a major contributor to excess mortality in eating disorders, particularly in anorexia nervosa, and recent research highlights a convergence of clinical severity and biological dysregulation as key contributors to risk.

Across recent longitudinal, ecological, and meta-analytic studies, the most consistent clinical markers include prior suicide attempts, severe depressive symptoms, emotion dysregulation, compulsive or rigid behavioral patterns, low body mass index, chronicity of illness, and high levels of eating-disorder psychopathology, with dynamic fluctuations in negative affect and interpersonal stress closely linked to momentary suicidal ideation.

Cognitive factors predisposing to suicide risk encompass deficits in cognitive flexibility, impaired decision-making abilities, perfectionism, impulsivity, increased rumination, and reduced interoceptive awareness.

Emerging biological findings suggest that suicide risk in eating disorders is associated with alterations in stress-response systems, particularly hypothalamic–pituitary–adrenal axis dysregulation and abnormal cortisol patterns, as well as inflammatory activation (altered cytokines), metabolic and lipid abnormalities related to starvation, and serotonergic and neurotrophic changes (BDNF) affecting mood regulation, impulsivity, and cognitive control.

Integrative models propose that chronic malnutrition interacts with affective vulnerability, compulsivity, and increased pain tolerance to simultaneously heighten suicidal desire and capability, especially in restrictive phenotypes.

Overall, current evidence supports a multidimensional understanding of suicide risk in eating disorders, in which clinical severity, emotional processes, and biological stress and metabolic pathways jointly contribute to vulnerability, underscoring the need for multimodal assessment and prevention strategies. Improved knowledge of the cognitive mechanisms associated with suicide risk in this population could guide the development of tailored treatment and prevention approaches.

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Individual responses to stress are highly heterogeneous, resulting in diverse psychopathological outcomes. This variability poses challenges for traditional diagnostic frameworks and underscores the need for a transdiagnostic approach to guide interventions. This study aimed to identify distinct phenotypes within a stress-exposed population and to characterize their biological profiles using a multimodal machine learning framework.

A total of 809 stress-exposed adults (mean age 40.5 ± 8.74 years; 53.7% female) underwent clinical, laboratory, and structural MRI assessments. Data-driven clustering of clinical variables identified phenotypes, followed by machine learning classifiers trained on neuroimaging and laboratory data to predict phenotype membership. SHapley Additive exPlanations (SHAP) analysis was used to identify key biological features distinguishing each phenotype.

Three phenotypes were identified: a multi-risk group (n = 321) characterized by prominent depression, anxiety, and sleep disturbances; an alcohol-related risk group (n = 226) with high alcohol misuse and minimal comorbidity; and a resilient low-risk group (n = 262). Machine learning models accurately classified these phenotypes, indicating distinct biological profiles. SHAP analysis revealed phenotype-specific signatures: the multi-risk phenotype was associated with frontal-subcortical structural alterations and dysregulated cortisol, whereas the alcohol-related risk phenotype was characterized by frontal-insular structural alterations and metabolic abnormalities.

This study demonstrates the stratification of stress-exposed individuals into clinically and biologically distinct phenotypes. By integrating multimodal data with machine learning, we identified phenotype-specific neurobiological and metabolic profiles that extend beyond conventional diagnostic frameworks. These findings support a transdiagnostic, data-driven approach to improve risk stratification and inform personalized interventions in stress-exposed populations.

Mental disorders are intergenerationally associated, particularly affecting adolescent offspring. However, the extent of such intergenerational associations among adult women in China remains unclear. This study aimed to examine the intergenerational associations of depression and anxiety between two adult female generations.

This cross-sectional study included 2,130 grandmother-mother dyads from the Grandmothers, Mothers, and Their Children’s Health study. Depression and anxiety of the grandmaternal (G0) and maternal (G1) generations were assessed using the 10-item version of the Center for Epidemiologic Studies Depression Scale and the 7-item Generalized Anxiety Disorder Scale, respectively, with scores of 10 or higher defined as depression and anxiety. Statistical analyses included logistic regression, negative binomial regression, and restricted cubic spline analyses.

A total of 11.4% G0 and 11.5% G1 participants reported depression, and 4.1% G0 and 3.1% G1 participants reported anxiety. Depression in G0 was associated with 4.29-fold (95% CI: 3.09–5.94) and 3.50-fold (95% CI: 1.98–6.01) higher odds of depression and anxiety in G1, respectively, while anxiety in G0 was associated with 3.95-fold (95% CI: 2.41–6.35) and 5.47-fold (95% CI: 2.64–10.60) higher odds of depression and anxiety in G1, respectively; dose–response relationships were also observed. In addition, the intergenerational association of depression was stronger among G0 participants residing in rural areas, whereas G0 depression and anxiety were more strongly associated with anxiety in G1 among those with higher household income.

Mental disorders were intergenerationally associated between mothers and their adult daughters. These findings emphasize the importance of family-based interventions for mental health.

Eating disorders (EDs) are among the most lethal psychiatric illnesses, characterized by a markedly elevated standardized mortality ratio compared to the general population. Mortality arises from both severe medical complications—particularly in anorexia nervosa—and suicide, which accounts for a substantial proportion of deaths across diagnostic subtypes. Despite this well-documented risk, suicide vulnerability in EDs remains insufficiently integrated into routine clinical assessment and care pathways.

Recent work by Sébastien Guillaume and colleagues has significantly advanced our understanding of suicidal risk in ED populations. Their findings highlight the central role of affective dysregulation, impulsivity (especially in binge–purge phenotypes), depressive comorbidity, and history of suicide attempts as key drivers of mortality risk. Beyond categorical diagnoses, dimensional constructs such as emotional pain, cognitive rigidity, and stress sensitivity appear crucial in explaining why only a subgroup of patients progresses from ideation to suicidal behavior.

From a precision suicidology perspective, EDs represent a paradigmatic case of dual vulnerability: metabolic fragility interacting with psychiatric and psychological risk trajectories. Not all patients with EDs share the same death risk. Stratification models integrating clinical phenotype (restrictive vs. binge–purge), prior suicidal behavior, depressive severity, and potentially biological markers (e.g., inflammatory or stress-related indicators) may improve identification of high-risk individuals.

Importantly, weight restoration alone does not equate to reduced suicide risk. The post-hospitalization period may constitute a critical window for targeted intervention. Precision-based approaches combining careful medical monitoring, systematic suicide risk assessment, and tailored psychotherapeutic strategies are therefore essential.

Recognizing eating disorders as illnesses with heterogeneous but potentially extreme mortality risk shifts the clinical objective: from symptom management alone to proactive, stratified, and suicide-informed care. Such an approach may ultimately reduce preventable deaths in this vulnerable population.

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Cognitive dysfunctions cause pervasive and significant disabilities in people with multiple sclerosis. This will increase the global burden of the disease. Different domains of cognition are not equally affected by multiple sclerosis. Among the vulnerable domains of cognition impaired by multiple sclerosis, it should be noted that information processing speed (IPS), verbal memory, visual memory, prospective memory, executive functions, visuospatial processing, language functions, and social cognition are affected. So far, studies have revealed that cognitive dysfunctions in people with multiple sclerosis negatively impact the quality of life, disease management, risk of falls, driving, financial management skills, employment, and attending social and leisure activities. Moreover, their caregiver partners’ health-related quality of life is also diminished. Three batteries are widely used to objectively assess cognition in persons with multiple sclerosis: the Brief Repeatable Battery of Neuropsychological Tests (BRB-N), the Minimal Assessment of Cognitive Function in MS (MACFIMS), and the Brief International Cognitive Assessment for MS (BICAMS). There are a lot of other psychiatric comorbidities or complications of multiple sclerosis that should be identified and treated, such as anxiety, depression, apathy, organic personality disorder, psychoactive substance abuse, and even suicide. All these conditions may worsen the cognitive impairments in people with multiple sclerosis. Some of the psychiatric comorbidities could be a direct consequence of disease-modifying therapy in multiple sclerosis. Whatever the case, the management of this subclinical population of people with multiple sclerosis and cognitive dysfunctions needs specific management, consisting of specific social, psychological, and pharmacological interventions.

cognitive dysfunctions, multiple sclerosis, disabilities

1. Anonymous, Stern EB. A mind “surrounded by a moat”: a first-person account of cognitive impairment in multiple sclerosis. Cogn Behav Neurol. 2011 Dec;24(4):217-26.

2. Costa SL, Genova HM, DeLuca J, Chiaravalloti ND. Information processing speed in multiple sclerosis: Past, present, and future. Mult Scler. 2017 May;23(6):772-789.

3. De Meo E, Portaccio E, Giorgio A, et al. Identifying the Distinct Cognitive Phenotypes in Multiple Sclerosis. JAMA Neurol. 2021 Apr 1;78(4):414-425.

None Declared

Narcissistic Personality Disorder (NPD) involves disturbances in self-regulation, interpersonal functioning, and personality organization. Although traditionally characterized by grandiosity, contemporary models suggest that grandiose self-states coexist with vulnerable features such as shame, emotional dysregulation, and hypersensitivity to rejection. Recent evidence indicates that metacognitive impairments may underlie both grandiose and vulnerable narcissistic presentations; however, no study has examined how metacognition interacts with personality traits and interpersonal difficulties within an integrated system.

A cross-sectional network analysis was conducted on 287 patients with NPD. Measures included the Metacognition Assessment Interview, the Pathological Narcissism Inventory, the Personality Inventory for DSM-5 (PID-5), the Inventory of Interpersonal Problems, and SCL-90-R Depression. A Gaussian graphical model with LASSO regularization was estimated, and expected influence was used as the primary index of node centrality. Network accuracy and stability were assessed through bootstrapping procedures.

Narcissistic vulnerability was the most central node, followed by interpersonal sensitivity and metacognitive integration. Narcissistic vulnerability showed strong associations with PID-5 Negative Affectivity and Detachment, whereas narcissistic grandiosity was related to PID-5 Antagonism. Metacognitive integration occupied a central position, linking maladaptive traits and interpersonal distress. Network stability indices indicated good reliability.

Findings suggest that narcissistic vulnerability and interpersonal hypersensitivity are central aspects of dysfunction in NPD, whereas metacognitive integration appears closely associated with the organization of psychological processes within the network. Although causal inferences cannot be drawn, the results are consistent with theoretical models underlying Metacognitive Interpersonal Therapy (MIT), supporting the potential relevance of targeting integrative metacognitive capacities in NPD treatment.

While both evidence-based medicine as well as personalized patient-centered medicine are glorified, clinical practice seems to be only partially influenced by guidelines or by patients’ views. Against this background, shared decision-making (SDM) became a hype but remains an ill-defined concept: it can be considered as an umbrella concept covering therapeutic alliance, physician and patient preferences, information giving, information retrieving, information receiving, patient involvement in goal setting, decision-making, and treatment choice.

A narrative review based on a literature search in PubMed and PsycINFO.

SDM in depression should move away from an ethical imperative where “one size fits all” toward a personalized approach, tailoring the medical encounter to the physician’s and patient’s expectations (knowledge, need for knowledge, and desire for degree of SDM) and to the patient’s clinical status. SDM cannot be conceived as a “snapshot” since it is a dynamic process where adjustments should be made depending on the growth of the doctor–patient alliance, the changes in expectations, and the changes in clinical status. The clinician should be more aware of barriers to effective implementation of SDM in him or herself, in the patient. The different definitions of SDM and the many reported SDM interventions (having different ingredients) hamper final conclusions on the effect of SDM on outcomes.

This narrative review aims to critically examine SDM in depression and proposes to conceptualize it as a dynamic, relational, and personalized process rather than a universal ethical standard.

Cardiovascular health plays a critical and often underappreciated role in shaping cognitive function across the lifespan in individuals with autism spectrum disorder (ASD) and intellectual disability (ID). From early development onward, the heart–brain connection exerts a powerful influence on neurocognitive trajectories. Children born with congenital heart defects are at increased risk of neurodevelopmental delays, including ASD and ID, partly due to impaired cerebral oxygenation during critical periods of brain maturation. These effects may be further amplified by shared genetic pathways that influence both cardiac development and neural connectivity, leading to long-term alterations in cognition, attention, and executive functioning.

As individuals with ASD/ID transition into adulthood, cardiovascular vulnerability often increases rather than diminishes. Adults in this population are more likely to develop cardiovascular diseases at a younger age compared with the general population, driven by a combination of biological susceptibility, chronic low-grade inflammation, metabolic dysregulation, and lifestyle-related risk factors such as physical inactivity, obesity, and medication effects. These cardiovascular conditions can accelerate cognitive decline through mechanisms including chronic cerebral hypoperfusion, endothelial dysfunction, and neuroinflammatory processes, all of which negatively affect brain structure and function.

Importantly, cognitive changes related to cardiovascular health in ASD/ID may remain underrecognized, as they are frequently attributed solely to neurodevelopmental factors rather than to potentially modifiable somatic conditions. This highlights the need for a lifespan-oriented model of care. Early neurodevelopmental surveillance in children with cardiac conditions should be integrated with routine cognitive and behavioral monitoring. In adulthood, proactive cardiovascular screening, risk reduction strategies, and individualized lifestyle interventions should become standard components of care.

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Cognitive impairment associated with schizophrenia (CIAS) affects over 80% of patients and represents a core feature of the disorder, demonstrating greater predictive value for functional outcomes, more than positive symptoms. Understanding the conceptual framework distinguishing “primary” from “secondary” cognitive impairment is essential for targeted therapeutic interventions.

Primary cognitive impairment reflects the intrinsic neurodevelopmental pathology of schizophrenia, manifesting across multiple domains including processing speed, attention, working memory, verbal learning, executive functions, and social cognition. These deficits typically predate psychosis onset, are observed in unaffected first-degree relatives, and remain relatively stable throughout the illness course regardless of symptom remission, with global cognitive performance averaging one standard deviation below general population.

Secondary cognitive impairment results from modifiable extrinsic factors that further compromise cognitive performance beyond the primary deficit. Key contributors include anticholinergic medication burden, first-generation antipsychotic side effects, benzodiazepine use, metabolic syndrome, sleep disturbances, sedentary lifestyle, substance abuse (particularly cannabis), and social deprivation.

Distinguishing primary from secondary cognitive impairment has critical therapeutic implications. While primary deficits require evidence-based interventions, such as cognitive remediation and optimized pharmacological treatment, secondary impairments demand systematic identification and mitigation of contributing factors including medication rationalization, metabolic management, aerobic exercise programs, substance abuse treatment, and social and work inclusion programs.

This conceptual framework provides clinicians and researchers with a structured approach to assessment and personalized intervention strategies, ultimately improving functional recovery in schizophrenia.

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Esketamine has demonstrated efficacy in treatment-resistant depression (TRD), but medium-term real-world functional outcomes remain understudied. This study described 6-month depressive symptoms and functional trajectories during routine esketamine treatment, focusing on functional outcomes and remission correlates.

In this prospective multicenter study, 60 patients with TRD initiating intranasal esketamine augmentation were assessed at baseline, Month 1, Month 3, and Month 6 using the Montgomery-Åsberg Depression Rating Scale (MADRS) and Sheehan Disability Scale (SDS). Mixed-effects models, Turnbull interval-censored time-to-remission analysis, logistic regression, and ROC analyses were performed.

MADRS and SDS improved significantly at all follow-up time points (p < 0.001). At Month 6, symptomatic response and remission rates were 78.3 and 46.7%, while functional response and remission rates were 78.3 and 33.3%, respectively. Turnbull estimates showed cumulative functional remission rates of 5.0, 15.0, and 33.3% at Months 1, 3, and 6, respectively. MADRS-SDS correlations decreased over time, supporting partial symptomatic-functional dissociation. Higher baseline SDS (OR = 0.73, 95% CI: 0.59–0.89) and more previous antidepressant trials (ADTs; OR = 0.53, 95% CI: 0.35–0.82) were associated with lower odds of Month 6 functional remission; bootstrap internal validation supported coefficient stability. ROC-derived thresholds were considered sample-dependent and not clinically validated. Cumulative esketamine dosage was associated with functional response but not remission.

Depressive symptoms and functioning improved progressively over 6 months during esketamine treatment in routine clinical care. Functional remission followed a slower trajectory than symptomatic remission and had partly distinct correlates, supporting functional monitoring as a distinct TRD outcome.

The association between elevated inflammation levels and cognitive alterations in inflammation-associated diseases supports the notion that inflammation plays a role in modulating cognition under physiological circumstances. Dysregulation of the immune system could therefore contribute to the cognitive changes observed in severe psychiatric disorders such as psychotic, unipolar and bipolar affective disorders (1).

A meta-analysis of inflammation and cognition in schizophrenia (2) revealed very modest associations between peripheral inflammatory biomarkers, such as C-reactive protein (CRP), and cognition. Elevated CRP levels were associated with impaired performance in all cognitive domains except verbal fluency. Similarly, a meta-analysis of inflammation and cognition in individuals with affective and psychotic disorders (3) revealed a weak association between global cognitive ability and pro-inflammatory indicators. Peripheral markers such as CRP have been shown to be highly state-dependent in mood and psychotic illnesses, suggesting that they are more relevant as biomarkers for episodic symptoms. A study of patients presenting with their first episode of schizophrenia found that an increased neutrophil-to-lymphocyte ratio was negatively associated with cognitive function (4).

In our ongoing study (5), we assess cognitive impairments in acute psychiatric inpatients diagnosed with psychotic, bipolar or depressive disorders, using the German version of the SCIP (6). Our sample comprises routinely collected clinical data from adult psychiatric patients living in a specific catchment area who were previously indicated for acute, inevitable admission following an emergency assessment. Data examining the effect of CRP values and the neutrophil-to-lymphocyte ratio on cognitive function in our sample of acute patients is shown.

Fourrier C, Singhal G, Baune BT. Neuroinflammation and cognition across psychiatric conditions. CNS Spectr. 2019;24(1):4-15.

Bora E. Peripheral inflammatory and neurotrophic biomarkers of cognitive impairment in schizophrenia: a meta-analysis. Psychological Medicine. 2019;49(12):1971-1979.

Morrens M, et al. The relationship between immune and cognitive dysfunction in mood and psychotic disorder: a systematic review and a meta-analysis. Mol Psychiatry. 2022;27(8):3237-3246.

Liang J, et al. Neutrophil/lymphocyte ratio and cognitive performances in first-episode patients with schizophrenia and healthy controls. Prog Neuropsychopharmacol Biol Psychiatry. 2024;135:111092.

Maihofer EIJ, Sachs G, Erfurth A. Cognitive Function in Patients with Psychotic and Affective Disorders: Effects of Combining Pharmacotherapy with Cognitive Remediation. J Clin Med. 2024;13(16):4843.

Sachs G, Lasser I, Purdon SE, Erfurth A. Screening for cognitive impairment in schizophrenia: Psychometric properties of the German version of the Screen for Cognitive Impairment in Psychiatry (SCIP-G). Schizophr Res Cogn. 2021;25:100197.

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Bipolar disorder is increasingly recognised as a disorder involving impaired cellular energy regulation and neurobiological resilience. Mitochondrial dysfunction has been consistently associated with mood instability, cognitive impairment, and illness progression. In parallel, the endocannabinoid system has emerged as a key modulator of emotional regulation, synaptic plasticity, and intracellular energy pathways. This presentation will focus on current evidence linking alterations in endocannabinoid signalling to mitochondrial dysregulation, oxidative stress, and inflammatory mechanisms relevant to bipolar disorder. By integrating preclinical and clinical findings, the talk will highlight how the interaction between the endocannabinoid system and mitochondrial function may contribute to affective symptomatology and treatment response. These insights support a more integrative pathophysiological model and may inform the development of novel biomarkers and therapeutic strategies in bipolar disorder.

None Declared

Treatment-Resistant Late-Life Depression (TRLLD) represents a significant clinical and research challenge. Studies on TRLLD use heterogeneous diagnostic criteria limiting the interpretation of results and the development of clinical guidelines.

This study aimed to establish expert consensus on the core components and definition of TRLLD through a Delphi process conducted by a European Task Force of clinicians and researchers with experience in late-life depression.

We conducted an electronic Delphi study with 30 European experts to identify key definitional elements of TRLLD. In the 1st survey round (SR), participants responded to open-ended questions on definitions of TRLLD. Responses informed the development of 70 structured items for 2nd SR, involving 58 closed (yes/no) items and 12 multiple-choice questions across six domains: symptom presentation, cognitive impairment, comorbidities, pharmacotherapy, treatment adherence, and psychosocial factors. Consensus was defined as ≥70% agreement. In 3rd SR, participants reviewed comments and validated the final categorical definition, the operational staging model, and the derived decision algorithm for TRLLD.

Consensus was reached for 72.4% of the 58 closed items. Experts agreed that the categorical definition of TRLLD should correspond to major depressive disorder in individuals aged ≥65 years who show insufficient response to two adequate antidepressant treatments, in the absence of dementia and medical conditions that could account for depressive symptoms. An operational staging model and decision-making algorithm were developed from consensus items.

This study provides the first European consensus definition of TRLLD and highlights the need for age-adapted diagnostic criteria that reflect the clinical complexity of depression in older adults.

The development of cognitive impairment (CI) is a frequent and debilitating consequence of COVID-19 and can persist for more than 1 year after the acute infection stage. Previous neuroimaging studies in COVID-19 survivors with CI have revealed widespread alterations in functional connectivity (FC), particularly within fronto-parietal circuits and subcortical nuclei such as the hippocampus, basal ganglia, and thalamus. This study focuses on neural correlates of CI in subjects who recovered from COVID-19 and the relationship between FC patterns and discrete cognitive domains.

Resting-state functional MRI data from 136 subjects were analyzed using a ROI-to-ROI approach across 246 brain regions derived from the Human Brainnetome Atlas. Group comparisons were performed based on the presence or absence of CI, and correlation analyses were conducted between FC and scores obtained from a comprehensive neuropsychological test battery.

Whole-brain FC showed no difference between patients with and without CI. In the whole study sample, hypoconnectivity between two basal ganglia regions and two frontal motor regions was associated with impaired performance in the cognitive domain “Reasoning and Problem-Solving,” while hyperconnectivity between the prefrontal thalamus and the postcentral gyrus was associated with impaired performance in the same cognitive domain.

Our findings indicate that FC alterations within the cortico-striatal and thalamo-cortical circuits may subtend deficits in higher-order executive functions in post-COVID-19 patients and highlight the importance of examining discrete cognitive domains in relation to brain connectivity.

Lithium remains the most effective mood stabilizer for bipolar disorder (BD), significantly reducing suicide risk and overall mortality. However, treatment response is highly heterogeneous and heritable (SNP-h² = 0.22–0.29), with familial clustering observed. The Consortium on Lithium Genetics (ConLiGen) was established to identify genetic determinants of lithium response able to disentangle such heterogeneity in lithium response.

ConLiGen Phase 1 conducted a genome-wide association study (GWAS) of 2,563 BD patients from 22 sites, evaluating lithium response both dichotomously and continuously via the Alda Scale. Four linked polymorphisms on chromosome 21 met genome-wide significance criteria for association with lithium response. The response-associated region contains two genes for long, non-coding RNA. ConLiGen Phase 2 is expanding recruitment to new sites, targeting > 6,000 participants, mainly including European cohorts.

We will present the results of Phase 1 ConLiGen study and also interim results adding new Phase 2 cohorts to the study. Likewise, we will also present ongoing analyses that use genetic information to define clusters of patients mapping to response/non-response phenotype.

ConLiGen Phase 2 will substantially increase statistical power and global representation to unravel the genetic basis of lithium response. This collaborative framework will accelerate discovery for personalized BD treatment and suicide prevention. Data sharing and new partnerships are actively encouraged.

None Declared

Fibromyalgia (FM) profoundly affects not only physical functioning but also the lived experience of time, space, the body, selfhood, and relationships. Although many qualitative studies describe these challenges, their heterogeneity makes it difficult to identify common experiential patterns.

We conducted a qualitative meta-analysis of 69 studies reporting first-person accounts of adults diagnosed with FM. Following PRISMA-ScR guidelines, we extracted patient quotations and analyzed them using Consensual Qualitative Research (CQR), incorporating triangulation, consensus-building, reflexive dialogue, and external auditing.

Across studies, FM emerged as a disruption of core experiential structures. Patients described collapsed futurity, fluctuating daily rhythms, and a biographical split between “before” and “after” illness. Their lived space narrowed due to pain, immobility, and fear of unpredictability. Embodiment became marked by pervasive pain, exhaustion, and bodily estrangement. Selfhood was threatened by loss of roles and diminished agency, while invisibility, disbelief, and isolation profoundly shaped intersubjective experience. Diagnosis brought both relief and misrecognition, sometimes fostering over-identification with the label.

FM constitutes an existential transformation rather than solely a somatic condition. Clinicians should adopt phenomenologically informed, person-centred approaches that recognize patients’ lived experiences, avoid reductive interpretations, and support processes of validation, bodily reconnection, and identity reconstruction.

None Declared

Gaming disorder (GD), i.e., persistent problematic gaming with clinically significant impairment, is a growing concern; however, estimates of GD in representative adolescent samples are limited. This study aimed to examine GD prevalence, incidence, persistence, and risk factors for different epidemiological parameters across 6 years, covering pre- to post-COVID-19 pandemic.

Population-based longitudinal data, including 3358 German adolescents, were collected annually from 2019 to 2024 using online surveys. GD prevalence estimates were assessed by standardized International Classification of Diseases (ICD-11)-based self-report questionnaires. Between-wave persistence and incidence of GD, sociodemographic data, gaming time, and stress perception were measured. Risk factors for incidence and persistence of GD were examined using generalized-estimating equation (GEE) models.

GD prevalence doubled from 2.9% in 2019 to 6.5% in 2023 and remained above prepandemic levels in 2024 (3.9%). Males showed higher prevalence estimates compared to females across most waves, and prevalence peaked in 2023 (8%). For females, GD prevalence doubled between 2019 (1.7%) and 2020 (3.4%), peaked in 2022 (6.1%), and declined thereafter. The incidence of GD increased during the pandemic. According to GEE models, male sex, higher perceived stress, and longer gaming times were risk factors for GD incidence; older age and higher education were protective factors. The persistence of GD reached its peak in 2020 (36.2%). Significant risk factors for GD persistence were higher stress perception and longer gaming time.

Prevalence and incidence rates indicate that GD continues to be a significant concern, and pandemic-related increases affected both males and females. Prevention and intervention programs should target identified risk groups.