Attention-Deficit/Hyperactivity Disorder (ADHD) is commonly associated with childhood, yet its prevalence and impact extend into adulthood. The diagnosis of ADHD in adults poses unique challenges due to the subtlety of symptoms and the presence of comorbidities.

The workshop aims to provide early career psychiatrists with a comprehensive understanding of the unique challenges associated with adult ADHD, emphasizing evidence-based approaches to diagnosis and effective management.

The management of adult ADHD involves a multimodal approach encompassing psychoeducation, pharmacotherapy, and psychosocial interventions. The integration of cognitive-behavioral therapy (CBT) and coaching strategies proves beneficial in addressing executive function deficits and enhancing adaptive skills.

Pharmacological interventions are a key component in the management of ADHD. These interventions aim to alleviate symptoms, improve cognitive functioning, and enhance overall functioning. The two main classes of medications commonly used for ADHD treatment are stimulants and non-stimulants.

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Sleep disorders are the commonest comorbid conditions in adult ADHD. This presentation will begin with an overview of the relationship between ADHD and sleep as well as the impact of disturbed sleep on concentration, impulvity and hyperactivity. Next, we will discuss the clinical characteristics of the sleep disorders, how to screen for them and their pharmacological and non pharmacological management. By the end of the session, participants will have a clear idea of how to investigate the various sleep disorders, to distringuish and treat them.

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My PhD research critically examines the contemporary U.K politics of mental health and Illness and mental illness amongst young adults via social media.

This presentation examines the way in which social media, like Instagram and Tiktok allows young adults to explore, express and share their selfhood and identity around ideas of mental health and illness through videos, posts and online interactions. I will briefly explore how young adults use social media content to learn, experience and criticise their lived experiences, care for and treatment of mental health and illness. Arguing that these new developments in language and social practices around mental health and illness via social media need to be further explored, acknowledged and addressed in social science and this can be supported by work in the field of psychiatry.

To illustrate this, I will share empirical data from interviews conducted in 2021 and 2022 with young adults who speak about their mental health and illness online and have engaged with psychiatric services, for example, in-patient settings. Instagram and Tiktok have become important arenas for young adults because of the informative role they play in young adults’ understanding of what a healthy person looks like, or their ideas of the mentally healthy self. A concept I introduce in my research of which I will explain and explore through the presentation. In young adults’ understandings of mental health and illness there is a movement towards social practices that are intended to achieve (an idea of) mental health and this is created in a powerful digital environment that is affected by capitalism, neoliberal discourse and exists in a context of multiple political and health crises in the U.K and globally. Overall, the presentation argues that these mental health and illness social practices have transformed young adults’s experiences by responsibilisation in self-care that both isolates and empowers their experiences.

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This presentation provides an overview of the impact of information technologies on contemporary psychiatric practice, focusing on resources and strategies beneficial for early career psychiatrists. Considering the increasing role of digital technologies in diagnosing and treating mental disorders, the presentation emphasizes the practical applications of artificial intelligence (AI) and machine learning. These technologies offer novel approaches for analyzing large volumes of clinical data, enhancing diagnostic accuracy, and personalizing treatment.

The presentation further examines ethical and legal issues associated with using digital technologies in psychiatry, including ensuring data confidentiality and complying with patient rights. The importance of developing competencies in information security and ethical principles when using digital tools is highlighted.

The talk concludes with an overview of the current and future trends in the use of digital technologies in psychiatry, including the development of virtual therapeutic environments and mobile applications for monitoring and supporting mental health. Examples of successful integration of these technologies into clinical practice are presented, emphasizing their potential to improve the quality of patient care.

Overall, the presentation underscores the importance for early career psychiatrists of mastering information technologies, highlighting their role in enhancing diagnosis, treatment, and patient care, as well as discussing the challenges and opportunities they present.

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In recent years, there has been a growing recognition of the importance of involving people with lived experience of mental health issues in psychiatric research. User involvement in research goes beyond being merely instrumental and is deeply intertwined with ethical and political considerations. Shifting from traditional research paradigms to collaborative partnerships with users is seen as a crucial step in ensuring that research is more relevant, meaningful, and respectful of the diverse perspectives within the mental health community. While there is a growing interest and responsibility regarding this matter, there is still a need to better understand the differences between participation, engagement, and user-led research alongside a respectful integration of user perspectives.

In this presentation, the state-of-the-art regarding user involvement in psychiatric research will be reviewed and possible ways to practically implement such practice will be discussed.

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Patients and the research community need better and more cost-effective randomised trials. These are the ‘gold standard’ way of seeing if a new treatment works or not, and take years of effort involving lots of patients and funding. However, around half of trials fail to show that the new treatment is better than what it is being compared with. In cancer, this problem has been recognised. They use trial designs which test multiple treatments, and find out quicker answers to more questions. These ‘efficient trials’ are able to involve patients at a faster rate and to improve the chances of patients receiving a treatment that works. In mental health, the whole toolbox of trial designs is not being used. Sometimes there are valid reasons for this, but sometimes it is simply that researchers do not know about them – this talk will expand on the concept of ‘efficient trials’ in mental health, and present the opportunities and challenges to using these.

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Psychotic experiences show a dynamic pattern over time, often in interaction with the environment. In my talk, I will discuss how Ecological Momentary Assessment (EMA) or Experience Sampling Methodology can be used to assess psychotic symptoms in the flow of daily life. I will focus on the assessment of both positive and negative symptoms, where I will discuss both how we can measure such symptoms as well as what the dynamic patterns look like in everyday life. Furthermore, I will also focus on how ESM can be used to transfer psychological treatment to daily life using an app. I will discuss the INTERACT trial, a trial in people at the early stages of psychosis, where we investigated the effect of Acceptance And Commitment Therapy in Daily Life, compared to Treatment As Usual.

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Increasing volumes of information are being collected via electronic health records and there is growing multi-site expertise in utlising these for research. This emerging field of healthcare data science is not only concerned with the technical challenges associated with complex data, but also with the need for effective security and governance in the use of sensitive information with robust structures for stakeholder input and guidance. To date, most of the focus has been on supporting observational cohort studies nested within clinical records data - particularly investigating research questions around treatment response and course/prognosis. It is likely that electronic health records will become increasingly integrated with clinical trials, providing opportunities for pre-study feasibility scoping, targeted recruitment, and enhanced and extended follow-up. In addition, there is interest in emulated trials using routine data. For mental health data science, key challenges lie in the quality and quantity of data made accessible, with a particular need for natural language processing to derive structured data from extensive clinical text. Many of the challenges have been addressed for observational research, creating exciting prospects for a transformed trials landscape.

R. Stewart Grant / Research support from: Janssen, GSK, Takeda

To contribute to this debate I offer perspectives from my PhD research which critically examines the contemporary U.K politics of mental health and illness amongst young adults via social media. My work examines the way in which social media, like Instagram and Tiktok allows young adults to explore, express and share their selfhood and identity around ideas of mental health and illness through videos, posts and online interactions. Through this work I have engaged with digital services, psychologists and medical professionals on the subject of using technology for the treatment, engagement of and knowledge of mental health and illness. I have additionally engaged with some work on the role of the Metaverse for treating mental illness, and how this could work, but also the limitations of virtual spaces. Exploring debates in digital sociology adds evidence to these arguments and can support the understanding of the political ramifications of using technologies in the clinical space. Arguing that these new developments in language and social practices around mental health and illness via social media need to be further explored, acknowledged and addressed in social science and this can be supported by work in the field of psychiatry. Overall, my contribution to the debate will be to offer political and digital social perspectives on the use of technology and highlight some of the biases and drawbacks of utilising AI to treat mental health and illness.

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The metaverse, a term first employed in Neal Stephenson’s 1992 novel “Snow Crash”, is a digital environment delivered via artificial intelligence in which multiple users can use avatars to engage in social, economic and cultural activities. Broadly speaking, metaverse encompasses technologies as diverse as augmented reality (AR), “lifelogging” (smart watches, smart phones and other wearables), “mirror” worlds (e.g. Google Earth, Waze, …) and virtual reality (VR). There is a pressing need to understand the potential of metaverse for medicine in general and psychiatry in particular. The therapeutic use of VR technologies is already a reality in clinical practice, particularly in terms of online treatments and exposure and response prevention for anxiety disorders, obsessive-compulsive and related disorders, and trauma-related disorders. Avatar integrated therapies may increase treatment seeking via anonymity, decrease in physical and communication barriers, and facilitation of expression. In terms of research, the metaverse allows manipulation of the therapeutic environment in order to answer specific questions.

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The delivery of mental health care worldwide often involves compulsory treatment, a practice encountered by early career psychiatrists from the outset of their training. Despite its prevalence, little research has explored the challenges faced by trainees and early career psychiatrists when compelled to administer treatment without patient’s consent. This presentation will synthesize research data and offer personal reflections on the author’s experiences.

Challenges that early career psychiatrists can face regarding compulsory treatment can be categorized into personal, professional, and institutional. Personal challenges encompass the emotional stress associated with applying coercive measures, coping with negative emotions, and managing service users’ attitudes toward treatment without consent. There is also concern that compulsory treatment may elevate the risk of emotional burnout. Professional challenges involve the administrative burden associated with organizing compulsory treatment, often exacerbated by the formalization of the process as a bureaucratic procedure in many European countries. Additionally, dealing with legal processes, including interactions with lawyers and courts, can pose significant difficulties, even though it is clearly done to protect the rights of the persons receiving care. Institutional challenges encompass the overall policy of providing compulsory psychiatric care in the psychiatrist’s home country and the specific practices of coercive measures in a given treatment facility. Furthermore, the lack of dedicated time for ethics of coercion during training is a common issue.

In the current landscape of mental health care, early career psychiatrists must undergo training to handle coercive measures. While these measures are sometimes unavoidable, ethical principles must guide their administration. Additionally, access to supervision/mentoring is crucial for early career professionals facing challenging cases.

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Electroconvulsive therapy (ECT) is a psychiatric intervention that has proven effectiveness and safety in various psychiatric conditions, such as major depressive disorder, prolonged or severe manic episodes and catatonia. Despite positive scientific evidence, ECT was always seen as controversial by patients, caregivers, and even some psychiatrists, which lead to a decrease in its use over the years.

To investigate the way young psychiatrists view the place of ECT in modern psychiatry by assessing their knowledge, attitude and access to training opportunities in ECT.

An anonymous survey was disseminated online among early career psychiatrists and psychiatric trainees. The questionnaire consisted of 36 multiple-choice and Likert scale questions.

Most of our respondents consider ECT both an effective and a safe treatment option and would recommend ECT to their patients when indicated. Early career psychiatrists who had access to ECT training are more knowledgeable about the indications, precautions and side effects of this method, but more than half of the participants mentioned ECT training was unavailable during their residency programme. Almost all respondents stated that they are interested in enhancing their theoretical and practical competencies in ECT.

Early career psychiatrists have a positive attitude towards ECT but express the need of targeted education aimed at improving levels of knowledge about ECT.

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Panic disorder (PD) and agoraphobia (AG) are highly comorbid anxiety disorders with an increasing prevalence that have a significant clinical and public health impact but are not adequately recognized and treated. Although the current functional neuroimaging literature has documented a range of neural abnormalities in these disorders, primary studies are often not sufficiently powered and their findings have been inconsistent.

This meta-analysis aims to advance our understanding of the neural underpinnings of PD and AG by identifying the most robust patterns of differential neural activation that differentiate individuals diagnosed with one of or both these disorders from age-matched healthy controls.

We conducted a comprehensive literature search in the PubMed database for all peer-reviewed, whole-brain, task-based functional magnetic resonance imaging (fMRI) activation studies that compared adults diagnosed with PD and/or AG with age-matched healthy controls. Each of these articles was screened by two independent coding teams using formal inclusion criteria and according to current PRISMA guidelines. We then performed a voxelwise, whole-brain, meta-analytic comparison of PD/AG participants with age-matched healthy controls using multilevel kernel density analysis (MKDA) with ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias and 10,000 Monte Carlo simulations to correct for multiple comparisons.

With data from 34 primary studies and a substantial sample size (N=2138), PD/AG participants, relative to age-matched healthy controls, exhibited a reliable pattern of statistically significant, (p<.05-0.0001; FWE-corrected) abnormal neural activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

In this meta-analysis we found robust patterns of differential neural activation in participants diagnosed with PD/AG relative to age-matched healthy controls. These findings advance our understanding of the neural underpinnings of PD and AG and inform the development of brain-based clinical interventions such as non-invasive brain stimulation (NIBS) and treatment prediction and matching algorithms. Future studies should also investigate the neural similarities and differences between PD and AG to increase our understanding of possible differences in their etiology, diagnosis, and treatment.

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Obsessive-compulsive disorder (OCD) is a prevalent and disabling condition characterized by a wide variety of phenotypic expressions. Several studies have reinforced the hypothesis of OCD heterogeneity by proposing subtypes based on predominant symptomatology (Mataix-Cols et al., 2005), course (Tukel et al., 2007), and comorbidities (Mahasuar et al., 2011). Early-onset OCD could be considered a neurodevelopmental subtype of OCD, with evidence of distinct neurocircuits supporting disease progression (Park et al., 2022).

The aim of the present study is to evaluate the sociodemographic and clinical differences between the early-onset and late-onset subtypes in a large patient cohort.

Two hundred and eighty patients diagnosed with OCD were consecutively recruited from the OCD Tertiary Clinic at Luigi Sacco University Hospital in Milan. Sociodemographic and clinical variables were analyzed for the entire sample and compared between the two subgroups (EO: early-onset, age <18 years [40%]; LO: late-onset, age ≥ 18 years [60%]).

The EO group showed a higher frequency of male gender (65.5% vs 34.5%, p< .001, see Figure 1a), a higher presence of lifetime psychiatric comorbidities (75.7% vs 24.3%, p =.025), and higher rates of Tic and Tourette disorders (7.2% vs 0%, p=.006) compared to the LO group. Additionally, in the EO subgroup, a longer duration of untreated illness was observed (9.05 ± 10.0 vs 5 ± 7.17; p<.001, see Figure 1b), along with a lower presence of insight (33.3% vs. 66.7%, p =.024). No significant differences emerged in the Yale-Brown Obsessive-Compulsive Scale scores between the groups.

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The early-onset OCD subtype highlights a more severe psychopathological profile compared to the late-onset group. Exploring distinct manifestations and developmental trajectories of OCD can contribute to a better definition of homogeneous subtypes, useful for studying risk factors and defining targeted therapeutic strategies for treatment.

B. Benatti Speakers bureau of: Angelini, Lundbeck, Janssen, Rovi, N. Girone: None Declared, M. Vismara: None Declared, C. Bucca: None Declared, B. Dell’Osso Grant / Research support from: Angelini, Lundbeck, Janssen, Pfizer, Otzuka, Neuraxpharm, and Livanova, Speakers bureau of: Angelini, Lundbeck, Janssen, Pfizer, Otzuka, Neuraxpharm, and Livanova.

Obsessive-compulsive disorder (OCD) is a common psychiatric disorder. It is considered that dysregulation of cytokine levels is related to the pathophysiological mechanism of OCD. However, the results of previous studies on cytokine levels in OCD are inconsistent.

To perform a meta-analysis assessing cytokine levels in peripheral blood of OCD patients.

We searched in PubMed, Web of Science, and Embase from inception to March 31, 2023 for eligible studies. We conducted multivariate meta-analysis in combined proinflammatory cytokines (interleukin-6 [IL-6], IL-1β, IL-2, tumor necrosis factor-α [TNF-α], and interferon-γ [IFN-γ]) and combined anti-inflammatory cytokines (IL-10 and IL-4) respectively, and calculated the same meta-analysis in each cytokine. We also performed sensitivity analysis and publication bias tests, as well as subgroup analysis (i.e. different age groups, varied cytokine measurement methods, medication treated or naïve, and presence of psychiatric comorbidities) and meta-regression analysis (variables including patients’ sex ratio, age, age at symptom onset, illness duration, scores of Y-BOCS, family history of psychiatric disorders, and BMI).

17 original studies (13, 13, 10, 5, 4, 3, 2 studies for IL-6, TNF-α, IL-1β, IL-10, IL-2, IL-4, and IFN-γ, respectively), 573 patients (mean age, 25.2; 50.3% female) and 498 healthy controls (HC; mean age, 25.3; 51.4% female) were included. The results showed that the levels of combined pro- or anti-inflammatory cytokines and each signle cytokine were not significantly different between OCD patients and HC (all P>0.05), with significant heterogeneities in all analyses (I2 from 79.1% to 91.7%). We did not find between-group differences in cytokine levels in all subgroup analyses. Meta-regression analysis suggested that age at onset (P=0.0003) and family history (P=0.0062) might be the source of heterogeneity in TNF-α level. Sensitivity analysis confirmed that all results were stable, except for IL-4 where different cytokine measurement methods may be the contributing factor. Egger test did not find publication bias.

Our study showed no difference in cytokine levels between OCD patients and HC, but age at onset and family history may affect TNF-α level. Confounding factors such as age at onset, family history, and cytokine measurement methods should be controlled in future studies to further explore the immune mechanism of OCD.

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Posttraumatic stress disorder (PTSD) and personality disorders (PD) often co-occur and treatment dropout remains a challenging problem for both disorders. The literature on predictors of treatment dropout is highly mixed and few reliable predictors have been identified for both PTSD and PD treatments separately, let alone for concurrent PTSD and PD treatment.

The aim of the present study was to identify predictors of treatment attendance among a wide range of variables in patients with PTSD and comorbid PD who received trauma-focused treatment with and without concurrent PD treatment.

Data were used from the prediction and outcome study in comorbid PTSD and personality disorders (PROSPER), a study consisting of two randomized clinical trials (RCT) testing the effectiveness of trauma-focused treatment (eye movement desensitization and reprocessing or imagery rescripting) with versus without concurrent PD treatment (dialectical behavior therapy or group schema therapy). 256 patients with PTSD and comorbid personality disorder participated in the study. The potential predictors included demographic (e.g. work status), patient severity (e.g. PTSD severity), patient-therapist (e.g. working alliance) and therapist (e.g. therapist experience) variables. The ordinal outcome variable was treatment attendance (0, 1-7, 8-11, 12+ trauma-focused treatment sessions). Relevant predictors were identified by a series of ordinal regression analyses (threshold for inclusion p < .10). Relevant predictors were then entered together in a final ordinal regression model. Multiple imputation was used to handle missing data.

The final model included ten predictor variables and provided a good fit for the data (pooled R2Nagelkerke = .29). Higher education level (OR = 1.22, p = .009), self-rated PTSD severity (OR = 1.04, p = .036) and working alliance (OR = 1.72, p = .047) were associated with a larger number of attended sessions. Higher levels of inadequate social support from a friend (OR = 0.90, p = .042) and being randomized in the concurrent treatment condition (OR = 0.52, p = .022) were associated with a smaller number of attended sessions.

In terms of treatment attendance rates, the results suggest that trauma-focused treatment is preferred over concurrent trauma-focused and personality disorder treatment for patients presenting with PTSD and PD. Clinicians should further be aware of the risk of lower treatment attendance for patients with a lower educational background and those reporting inadequate social support. Enhancing working alliance may protect against early treatment termination. Finally, patients with higher levels of PTSD severity at baseline may need a larger number of treatment sessions.

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Mental disorders often manifest broad cognitive deficits that detrimentally affect daily functioning. Stress indicated by heart rate variability (HRV) has been linked to these cognitive functions.

We aimed to develop a new method to assess cognitive performance and simultaneous measurement of psychophysiological signals related to stress and relaxation levels.

20 adult patients with mental disorders in a rehabilitation program were recruited along with 21 healthy volunteers. A test protocol was carried out with a purpose-developed computerized psychophysiological device. The protocol consisted of a relaxation period; digitized questionnaires on pathological distress (GHQ) and sense of coherence (SOC); gamified cognitive tasks to assess working memory, attention, and decision-making; and a final relaxation period. Acute stress was assessed by heart rate variability measured by a wireless ECG sensor. The inter-beat interval’s root mean square of successive differences (RMSSD) was calculated as an inverse stress measure. Relaxation levels were assessed by the relative power of the alpha frequency band measured by a commercial 4-channel EEG headband. Stress and relaxation levels were compared to the first relaxation period as a baseline.

Patients scored worse than the reference group both regarding distress (d=7, p=0.004) and sense of coherence (d=-8, p=0.047). The cognitive performance of patients was significantly lower (p<0.001) than the reference group for all tasks.

RMSSD at baseline tended to be lower for patients (d=-12.69, p=0.098), reflecting a higher level of physiological stress; 61% of patients started at an elevated stress level compared to 25% of the reference group. In addition, relative alpha levels at baseline were also lower (d=-5.8%, p=0.007) for patients.

Compared to baseline, RMSSD decreased on average to 94% during cognitive assessments in patients and decreased to 91% by the end of the final relaxation. RMSSD decreased to 76% in the reference group and reached a final value of 78% of the baseline. Alpha levels slightly increased among patients during the tasks (103.4%) and then returned close to baseline (99.1%). For the reference group, alpha decreased during the tasks (95.5%) and then slightly increased (97.3%).

Patients displayed heightened distress, reduced sense of coherence, and inferior cognitive scores compared to controls. While starting with higher stress, patients exhibited less elevation in stress during tasks, coupled with alterations in alpha levels, suggesting diminished engagement or focus. Our innovative method could aid in the diagnostics of cognitive performance in mental patients after further measurements for validation.

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Given the negative impact of anxiety and depression on society and the shortage of new antidepressants, it is of paramount importance to make the best use of available treatment options. Therapeutic drug monitoring (TDM) in escitalopram treatment can potentially be clinically useful, as underexposed patients show reduced efficacy of escitalopram treatment and as adverse drug reactions (ADRs) of escitalopram are dose-dependent.

This prospective cohort study aimed to investigate whether escitalopram treatment efficacy or safety are associated with escitalopram dose adjustment based on TDM readouts.

89 included patients aged between 15 and 65 years who suffered from depression were enrolled in the study before starting treatment with escitalopram. Patients were assessed one day before starting treatment with the recommended dose of 10 mg/day escitalopram (baseline, visit 0) and at follow-up after four and eight weeks. Dose adjustment at four-week follow-up was based on the measured escitalopram plasma level two weeks after treatment initiation; patients who required dose increase to 15 or 20 mg/day comprised comparator group, patients who did not required dose increase comprised control group, while patients who did not reach optimal exposure at eight-week follow-up were characterized as non-compliers. Treatment efficacy was approximated by the relative change on the Hamilton Depression Rating Scale (HAMD), while safety was approximated based on the changes on the Scandinavian UKU side effect rating scale and ECG readouts. Changes in HAMD, UKU score and QTc interval were compared between groups by one-way ANOVA or chi-square tests.

Compared to baseline, significant reductions in HAMD scores of 36% (95%CI, 30%-43%) and 53% (95%CI, 47%-60%) were observed at four- and eight-week follow-up, respectively; however, there were no significant differences between groups (p > 0.1). In the groups adjusted to 15 and 20 mg, 15/26 and 19/33 patients, respectively, reported adverse effects, compared with 6/17 patients in the control group and 6/13 in the non-complier group (p>0.1). A significant mean QTc prolongation of 6.40 ms (95%CI, 3.27-9.53) was observed between the baseline and eight-week follow-up (p=0.0013), without significant differences in QTc interval prolongation between groups (p > 0.1).

Escitalopram dose adjustment resulted in optimal drug exposure and solid treatment response in the majority of patients; however, no differences in efficacy were found between the patients who required dose adjustments, the ones who did not, and the ones who ultimately did not achieve optimal exposure. In addition, the selective increase of the dose to the patients who did not reach optimal drug exposure on the recommended dose of 10 mg/day did not lead to significant increase in adverse drug reactions and QTc prolongation.

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The synaptic pruning process is based on the joint action of the complement system and microglia. In schizophrenia, accumulating evidence support that abnormal synaptic pruning during adolescence may be due to an altered Complement system activity. While this hypothesis is supported by C4 overexpression in various brain regions of individuals with schizophrenia, such alterations should be replicated and extended to other brain regions. Moreover, transcriptional studies of genes encoding regulators of the complement system activity (complement control proteins, CCP) and microglia-specific genes are lacking. Furthermore, it remains unknown whether brain and peripheral expression of such genes are related.

To explore expression of C4 as well as 4 CCP encoding genes and 10 microglia-specific genes at the brain and peripheral levels in individuals with schizophrenia as compared to healthy controls.

We analyzed candidate gene expression from 9 Gene Expression Omnibus datasets obtained from 333 individuals with schizophrenia and 306 healthy controls (HC). We first compared expression of the candidate genes between individuals with schizophrenia and HC in postmortem brain samples from 7 different brain regions. Then, the same comparison was made in 4 different peripheral tissues.

Regarding the complement system, we observed C4 overexpression in the DLPFC, parietal, temporal cortex and associative striatum of individuals with schizophrenia. We report distinct altered expression patterns of CCP genes in the DLPFC, hippocampus and cerebellum of individuals with schizophrenia. Only CD46 expression was altered in the blood of individuals with schizophrenia. Regarding microglia, we report an underexpression of several microglia-specific genes in the cerebellum, associative striatum, hippocampus and parietal cortex of individuals with schizophrenia vs. HC. At the peripheral level, we observed a mixed altered expression pattern in the whole blood of individuals with schizophrenia.

Firstly, our results suggest that the CCP-mediated regulatory mechanisms of the Complement system are impaired in the brain of individuals with schizophrenia, potentially contributing to an excessive Complement system activity (CSA). Secondly, our results support the hypothesis of a widespread underexpression of microglia-specific genes in brain tissues of individuals with schizophrenia. Functionally, the observed transcriptional alterations may be related to the synaptic pruning impairment. Alternatively, they may translate a compensatory mechanism for neuroinflammation. In the whole blood, the altered transcriptional pattern may represent a potential peripheral signature of SZ.

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An early and comprehensive neurobiological characterization of severe mental disorders could elucidate mechanistic pathways, aid the development of novel therapeutics, and therefore enable timely and targeted intervention in at-risk youth and young adults. Therefore, we present an unsupervised transdiagnostic machine learning approach to investigate shared and distinct patterns of early-stage depressive and psychotic disorders on multiple clinical and neurobiological levels.

To derive multi-level neurobiological and clinical signatures of early-stage affective and psychotic disorders in adolescents and young adults.

From the multicenter prospective European PRONIA cohort, we acquired data from 678 individuals (51% female) comprising young, minimally medicated in- and outpatients with clinical high-risk (CHR) states for psychosis, with recent-onset depression (ROD) or psychosis (ROP), and healthy control (HC) individuals. Within repeated nested cross-validation frameworks, we employed Sparse Partial Least Squares Analysis to detect associations between blood markers and grey matter volume (GMV), followed by support vector machine prediction of these signatures using biographical, clinical, neurocognitive, proteomic, and functional data.

Our results demonstrated a psychosis staging signature separating ROP from CHR individuals via GMV patterns in the cortico-thalamo-cerebellar circuitry with a blood marker set of elevated of IL-6, TNF-α and CRP (ρ = 0.272; P = 0.002). A depression signature separated ROD from HC individuals via altered GMV in the limbic system with a blood marker set of elevated IL-1ß, IL-2, IL-4, S100B and BDNF (ρ = 0.186; P = 0.021). Only the psychosis staging signature showed a distinct proteomic enrichment regarding innate immune response, abnormal neutrophil function, cellular senescence, and anti-inflammatory drugs (Balanced Accuracy (BAC) = 87.73%; Area Under the Curve (AUC) = 0.94). Childhood trauma differentially predicted psychosis and depression signatures, while past level of functioning, personality and quality of life was predictive of both signatures (BAC = 67.19-78.00%; AUC = 0.71-0.83).

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Psychosis and depression exhibit distinct multi-level signatures evident in early disease stages. Enhanced insight into these signatures could help delineate individual trajectories and potentially new mechanisms for pharmacological treatment.

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