Despite being a clinical identifiable entity, major depressive disorder (MDD) is an heterogenous clinical syndrome, with a variety of clinical presentations which likely reflects different biological underpinnings. The identification of biologically-based depression symptoms profiles would be of great importance to unravel different pathophysiological pathways in MDD and therefore to achieve more precise and personalized therapeutical approaches as well as preventive strategies.

Converging evidence from epidemiological and clinical studies, points to the importance of inflammation in MDD, shown by increased levels of pro-inflammatory proteins and increased inflammation-related comorbidities, including metabolic diseases. In fact, there exists a bidirectional relationship between inflammation and metabolic dysfunction that could be linked to multiple factors, including life style, stress and genetic predisposition. MDD patients exhibit several metabolic disturbances such as overweight, insuline resistance and dyslipidemia, among others, which are not always fully explained by life style factors. These findings have led to the formulation of an immunometabolic hypothesis, which could be present in a subgroup of MDD patients, associated to specific symptoms and clinical features.

In this presentation, data reflecting the complex relationships and interactions between immune and metabolic disturbances in MDD will be shown. In particular, it will be shown how machine learning approaches can be useful to disentangle the clinical and biological heterogeneity of MDD, using immunometabolic biomarkers.

P. Lopez-Garcia Grant / Research support from: Grant from Carlos III Health Institute ref PI15/00204 and FEDER funding from the EU

Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.

Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model’s performance. Kaplan–Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.

A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02–1.41, p = 0.027) at a 3-year follow-up.

We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.

Coercive measures (such as seclusion, mechanical restraint, and forced medication) during psychiatric inpatient treatment should be avoided whenever possible. Different interventions were already developed to reduce coercion, but for their effective application, it is crucial to know the risk factors of individuals and clinical situations that might be associated with coercion. Since the results of previous studies differ considerably the current study aims to fill this gap by evaluating the course of the exertion of coercion in detail.

In this study, we analyzed clinical, procedural, and sociodemographic data from patients (n = 16,607 cases) who were treated as inpatients in Switzerland’s largest psychiatric institution with 320 beds during the years 2017 to 2020. We used regression models to identify predictors for the exertion of coercion, the number of coercive measures during a treatment episode and time until exertion of the first and last coercive measure.

Coercive measures are mostly used during the first days of treatment. We identified clinical parameters such as manic or psychotic episodes to be the most relevant predictors for the exertion of coercion. Cases with those disorders also received coercion more often and earlier in their treatment course than other diagnostic groups. Other promoting factors for frequency and early application of coercion were involuntary admission and factors of chronicity and clinical severity.

Knowing the risk factors may help to target preventive strategies for those at highest risk. In particular, interventions should focus on the critical timeframe at the beginning of treatment.

Recently, the diffusion of sophisticated neuroimaging techniques has tremendously advanced our understanding of brain structure and function. Nevertheless, the current knowledge of the neurobiology of complex mental illnesses - like major psychoses and depression - is limited, hindering the development and validation of biomarkers for diagnosis, prognosis, and prediction of treatment response.

Increasing evidence is suggesting a crucial role of environmental, personal, and behavioral processes, interacting among themselves and with genetics, in shaping mental functioning and psychopathological risk. In this context, the study of brain maturation trajectories and of their association with genetic and environmental factors can provide key insights on the risk for the emergence of mental illnesses over lifetime.

The present lecture will provide an overview of our recent research on the brain underpinnings of psychotic and affective disorders onsetting during either adolescence/young adulthood or late adulthood. Evidence obtained from young samples of twins will be presented to provide useful information on the genetic and environmental determinants of physiological and pathological neurodevelopmental trajectories. The complex relationships among life events, brain morphology and connectivity, and psychopathology will be discussed by showing our recent findings on multicentric transdiagnostic samples of young adults and elders. Special focus will be given to the brain mechanisms affected by social stressors, including discrimination and bullyism, as well as chronic stress, and their possible role in facilitating the onset or in enhancing the severity of psychotic and affective disorders.

None Declared

The comorbidity of mental and physical disorders is gradually becoming recognized as a major problem for health care. Its public health importance is vast and growing for a variety of reasons including the extension of life expectancy, the imperfection of currently available treatments of mental and many physical disorders and the tendency of fragmentation of medicine into ever more limited specialties. The problems related to comorbidity are also rapidly increasing in low- and middle-income countries where in addition to the issues mentioned above there is also a scarcity of means to deal with them.

The presentation will remind the audience of the complexity of the problems and draw attention to action that could be taken by public health authorities and the medical profession in the areas of teaching, organization of service and research.

None Declared

The potential impact of the COVID-19 pandemic on suicidal behavior has generated predictions anticipating an increase in suicidal tendencies. The aim of this research is to study its influence on the incidence of hospital-treated suicide attempts throughout the year 2020 in Oviedo, Spain.

Data were collected on all patients admitted to the emergency department of Central University Hospital of Asturias in Oviedo for attempted suicide during 2020. Incidence rates were calculated for three lockdown periods. Suicide attempt trends in 2020 were compared with a non-COVID-19 year (2009) to avoid seasonal variations bias. Chi-square and Fisher’s exact tests were performed. The influence of COVID-19 incidence in Oviedo was analyzed using Spearman’s correlation coefficient.

The cumulative incidence rate of attempted suicide per 100,000 person-years was 136.33 (pre-lockdown), 115.15 (lockdown), and 90.25 (post-lockdown) in adults (over 19 years old), and 43.63 (pre-lockdown), 32.72 (lockdown), and 72.72 (post-lockdown) in adolescents (10–19 years old). No association was found with COVID-19 incidence rates (Spearman’s rho −0.222; p = 0.113). Comparing the years 2020 and 2009, statistically significant differences were observed in adolescents (Fisher’s exact test; p = 0.024), but no differences were observed in adults (chi-square test = 3.0401; p = 0.218).

Hospital-treated suicide rates attempted during the COVID-19 outbreak in Oviedo, Spain showed a similar trend compared with a non-COVID-19 year. In contrast, the number of adolescents hospital-treated for attempted suicide increased during lockdown, suggesting more vulnerability to COVID-19 restrictions after the initial lockdown period in this age group.

Anorexia nervosa is a persistent and often difficult to treat eating disorder with significant physical and mental health consequences. While it is known that the disorder is associated with alterations in brain functional connectivity during the phase of acute underweight, the effect of weight normalization on brain connectivity remains unclear.

This talk focuses on the recovery of intrinsic brain connectivity during weight normalization in severe anorexia nervosa, presenting data from a longitudinal study. Using resting-state functional magnetic resonance imaging, we assessed brain connectivity at three different stages of inpatient treatment. Our findings indicate that patients with severe anorexia nervosa have weaker intrinsic connectivity and altered network topology, which do not improve during treatment. These persistent disruptions in brain networks suggest that severe anorexia nervosa may have long-term effects on the way the brain processes information, even after weight is restored.

None Declared

There was no previous meta-analysis investigating the efficacy/tolerability of psychostimulants for symptoms of attention-deficit hyperactivity disorder (ADHD) in preschool children.

Databases including PubMed, the Cochrane Library, EMBASE, ScienceDirect, and ClinicalTrials.gov were searched from inception to March 2022 for randomized controlled trials (RCTs) on therapeutic efficacy of psychostimulants against ADHD symptoms in preschool children (age ≤6 years) compared with placebos. Primary outcomes were (a) changes in ADHD symptoms evaluated by validated rating scales from parents’/teacher’s observation, or (b) post-intervention improvements in neuropsychological performance. Secondary outcomes were risks of adverse events.

Meta-analysis of nine eligible trials including 544 preschool children (mean age=4.86 years, female=11.98%, median treatment duration=4.33 weeks) supported the efficacy of psychostimulants against global symptoms from observations of parents (Hedges’ g=0.6152, p<0.0001) and teachers (Hedges’ g=0.6563, p=0.0039). Efficacy of psychostimulants was also noted against symptoms of inattention and hyperactivity/impulsivity, especially the latter (i.e., main symptoms in preschool children). Moreover, male gender, older age, and longer treatment duration were associated with better efficacy. Regarding adverse events, only the risk of poor appetite was higher in the psychostimulant group (odds ratio [OR]=2.39). However, the qualities of evidence were low to very low, indicating potential discrepancy between the true and estimated effect.

Our results showed that psychostimulants might be beneficial for preschool children with ADHD, especially hyperactivity/impulsivity from teachers’ observation, with tolerable side effects. Nevertheless, the true magnitude of the effect needs to be confirmed with more research due to low to very low certainty of the evidence.

To date, a large number of functional magnetic resonance imaging (fMRI) studies have been conducted on psychosis. However, little is known about changes in brain functioning in psychotic patients using an emotional auditory paradigm at different stages of the disease. Such knowledge is important for advancing our understanding of the disorder and thus creating more targeted interventions. This study aimed to investigate whether individuals with first-episode psychosis (FEP) and chronic schizophrenia show abnormal brain responses to emotional auditory processing and to compare the responses between FEP and chronic schizophrenia.

Patients with FEP (n = 31) or chronic schizophrenia (n = 23) and healthy controls (HCs, n = 31) underwent an fMRI scan while presented with both emotional and nonemotional words.

Using HC as a reference, patients with FEP showed decreased right temporal activation, while patients with chronic schizophrenia showed increased bilateral temporal activation. When comparing the patient groups, individuals with FEP showed lower frontal lobe activation.

To the best of our knowledge, this is the first study with an emotional auditory paradigm used in psychotic patients at different stages of the disease. Our results suggested that the temporal lobe might be a key issue in the physiopathology of psychosis, although abnormal activation could also be derived from a connectivity problem. There is lower activation in the early stage and evolution to greater activation when patients become chronic. This study highlights the relevance of using emotional paradigms to better understand brain activation at different stages of psychosis.

People with eating disorders (EDs) exhibit a prevalence of childhood maltreatment higher than general population and, as for other psychiatric conditions, a history of childhood maltreatment in the context of EDs has been found associated with an earlier age at onset, a greater clinical severity, a more frequent comorbidity with other psychiatric conditions and a poorer treatment response . Neuroendocrine modifications as well as a heightened biological and emotional vulnerability to acute social stressor exposure and cortical measures alterations have been reported in people with EDs and history of childhood maltreatment. This evidence suggests the possibility to identify a “maltreated ecophenotype” also in people affected by EDs which recommends grouping individuals affected by the same psychiatric condition into subgroups characterized by different clinical and biological correlates in order to tailor treatements.

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The burden on society by depression is undisputable, partly due to a chronic course pattern and depression’s large heterogeneity that contributes to non-response to standard treatments. Using data from the Netherlands Study of Depression and Anxiety (NESDA, www.nesda.nl), Penninx will illustrate both points. When examining the course of depression, especially when also considering the transitions into other affective disorders over time, chronicity is clearly more the rule than the exception (Verduijn et al. BMC Med 2017). Considering depression’s heterogeneity could lead to precision psychiatry approaches that help reduce depression’s chronicity. Immuno-metabolic dysregulations seem to vary as a function of depression heterogeneity: dysregulations map more consistently to “atypical” neurovegetative symptoms reflecting altered energy intake/expenditure balance (hyperphagia, weight gain, hypersomnia, fatigue and leaden paralysis). Findings are confirmed when utilizing genome-wide gene expression as well as DNA information (Milaneschi et al. Biol Psychiatry 2020). Preliminary treatment studies suggest that the presence of immuno-metabolic dysregulations in depression moderates antidepressant effects of standard or novel (immunomodulatory) interventions. An immuno-metabolic depression dimension could dissect depression’s heterogeneity and potentially match depressed subgroups to treatments with higher likelihood of clinical success.

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Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are increasingly acknowledged as critical tools for enhancing patient-centred, value-based care. However, research is lacking on the impact of using standardized patient-reported indicators in acute psychiatric care. The aim of this study was to explore whether subjective well-being indicators (generic PROMs) are relevant for evaluating the quality of hospital care, distinct from measures of symptom improvement (disease-specific PROMs) and from PREMs.

Two hundred and forty-eight inpatients admitted to a psychiatric university hospital were included in the study between January and June 2021. Subjective well-being was assessed using standardized generic PROMs on well-being, symptom improvement was assessed using standardized disease-specific PROMs, and experience of care using PREMs. PROMs were completed at admission and discharge, PREMs were completed at discharge. Clinicians rated their experience of providing treatment using adapted PREMs items.

Change in subjective well-being (PROMs) at discharge was significantly (p < 0.001), but moderately (r2 = 28.5%), correlated to improvement in symptom outcomes, and weakly correlated to experience of care (PREMs) (r2 = 11.0%), the latter being weakly explained by symptom changes (r2 = 6.9%). Patients and clinicians assessed the experience of care differently.

This study supports the case for routinely measuring patients’ subjective well-being to better capture the unmet needs of patients undergoing psychiatric hospital treatment, and the use of standardized patient-reported measures as key indicators of high quality of care across mental health services.

Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement in a population-based sample across three of the most common categories of psychiatric disorders: depressive disorders, anxiety disorders, and sleep–wake disorders using unsupervised machine learning approaches.

We assessed a total of 43 symptoms in a discovery sample of 6,602 participants of the population-based Rotterdam Study between 2009 and 2013, and in a replication sample of 3,005 participants between 2016 and 2020. Symptoms were assessed using the Center for Epidemiologic Studies Depression Scale, the Hospital Anxiety and Depression Scale, and the Pittsburgh Sleep Quality Index. Hierarchical clustering analysis was applied on test items and participants to investigate common patterns of symptoms co-occurrence, and further quantitatively investigated with clustering methods to find groups that may represent similar psychiatric phenotypes.

First, clustering analyses of the questionnaire items suggested a three-cluster solution representing clusters of “mixed” symptoms, “depressed affect and nervousness”, and “troubled sleep and interpersonal problems”. A highly similar clustering solution was independently established in the replication sample. Second, four groups of participants could be separated, and these groups scored differently on the item clusters.

We identified three clusters of psychiatric symptoms that most commonly co-occur in a population-based sample. These symptoms clustered stable over samples, but across the topics of depression, anxiety, and poor sleep. We identified four groups of participants that share (sub)clinical symptoms and might benefit from similar prevention or treatment strategies, despite potentially diverging, or lack of, diagnoses.

Attention deficit/hyperactivity disorder (ADHD) often co-occurs with substance use disorders (SUD). Together, these disorders are associated with significantly more burden for patients and society, than each alone. Patients with SUD and underlying ADHD have more complex SUD and have more poly-substance use compared with SUD patients without ADHD. A correct identification of ADHD in adult and adolescent individuals with SUD remains important regarding treatment, treatment effectiveness, and treatment retention.

Several screening tools are available and have been validated in individuals with ADHD and comorbid SUD. It is highly recommended that these are used routinely, followed by an ADHD diagnostic process initiated as soon as possible. While several treatment options are accessible, randomized controlled trials show only limited effect sizes of standard pharmacotherapy in adult and adolescent ADHD patients with comorbid SUD. Simultaneous and integrated treatment, with a combination of pharmacotherapy and psychotherapy and for both ADHD and SUD, should preferably be initiated.

We present an overview of the current international guidelines on screening, diagnosis and treatment of ADHD adults and adolescents with comorbid substance use disorders.

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Individuals with a first episode of psychosis (FEP) show rapid weight gain during the first months of treatment, which is associated with a reduction in general physical health. Although genetics is assumed to be a significant contributor to weight gain, its exact role is unknown.

We assembled a population-based FEP cohort of 381 individuals that was split into a Training (n = 224) set and a Validation (n = 157) set to calculate the polygenic risk score (PRS) in a two-step process. In parallel, we obtained reference genome-wide association studies for body mass index (BMI) and schizophrenia (SCZ) to examine the pleiotropic landscape between the two traits. BMI PRSs were added to linear models that included sociodemographic and clinical variables to predict BMI increase (∆BMI) in the Validation set.

The results confirmed considerable shared genetic susceptibility for the two traits involving 449 near-independent genomic loci. The inclusion of BMI PRSs significantly improved the prediction of ∆BMI at 12 months after the onset of antipsychotic treatment by 49.4% compared to a clinical model. In addition, we demonstrated that the PRS containing pleiotropic information between BMI and SCZ predicted ∆BMI better at 3 (12.2%) and 12 months (53.2%).

We prove for the first time that genetic factors play a key role in determining ∆BMI during the FEP. This finding has important clinical implications for the early identification of individuals most vulnerable to weight gain and highlights the importance of examining genetic pleiotropy in the context of medically important comorbidities for predicting future outcomes.

Apathy and goal-oriented behaviors are key dimensions of late-life depression (LLD) and are iteratively associated with cognitive decline in most neuropsychiatric disorders. However, scales and criteria remains insufficient to provide robust individual biomarkers that could foster personalized therapeutic approaches. Therefore, dimensional and digital phenotyping offer new possibilities of stratifying LLD population. This presentation will show our recent results of functional connectivity cerebral networks associated with multidimensional paper-and-pen measures of apathy, including the default mode and the cingulo-opercular networks. We will also show how dimensional reduction (functional principal component analysis) of 3 days actimetry measures are associated with both FC and inflammatory measures (diffusion and multicompartment indices such as free water and neurite orientation dispersion), providing arguments for different pathophysiological mechanisms underlying goal-oriented behaviors and reinforcing actimetry as a good candidate for individual biomarker of cognitive decline in LLD. Finally, machine learning approaches using combination of different, yet correlated, indices of actimetry will be presented and discussed with their corresponding classifying accuracies (outside of cerebral imaging). Altogether, this presentation aims at bridging the gap between cerebral imaging and digital phenotyping to enhance personalized medicine in the field of old-age psychiatry and cognitive decline prevention.

None Declared

Accumulating evidence indicates that a variety of distal and proximal factors might impact a risk of suicide. However, the association between both groups of factors remains unknown. Therefore, in the present study, we aimed to investigate the interplay between distal and proximal correlates of the current suicidal ideation.

A total of 3,000 individuals (aged 18–35 years, 41.7% males), who had reported a negative history of psychiatric treatment, were enrolled through an online computer-assisted web interview. Self-reports were administered to measure: (a) distal factors: a history of childhood trauma (CT), reading disabilities (RDs), symptoms of attention-deficit/hyperactivity disorder (ADHD), lifetime history of non-suicidal self-injury (NSSI), lifetime problematic substance use as well as family history of schizophrenia and mood disorders; (b) proximal factors: depressive symptoms, psychotic-like experiences (PLEs), and insomnia; and (c) sociodemographic characteristics.

Suicidal ideation was directly associated with unemployment, being single, higher level of RD, lifetime history of NSSI as well as higher severity of PLEs, depression, and insomnia. The association of distal factors with suicidal ideation was fully (a history of CT and symptoms of ADHD) or partially (a history of NSSI and RD) mediated by proximal factors (PLEs, depression, and insomnia).

Main findings from this study posit the role of distal factors related to neurodevelopmental disorders, CT and NSSI in shaping suicide risk. Their effects might be partially or fully mediated by depression, PLEs, and insomnia.

The ghrelin system is a key regulator of appetite and food intake across species. LEAP-2, a recently discovered ghrelin antagonist, appears to be up-regulated in obesity and opposes to the orexigenic drive of ghrelin. The evolution of LEAP-2 levels could be an interesting insight to reflect the regulation of appetite in eating disorders such as anorexia nervosa (AN). We provide the first study exploring the ghrelin and LEAP-2 regulation in long-term food restriction followed by refeeding in both mice and patients suffering from AN.

Using a translational strategy, we compared the regulation of ghrelin and LEAP-2 concentrations in blood during food restriction and after refeeding in female mice exposed to a 14 days protocol combining quantitative food restriction and running wheel activity followed by progressive refeeding. We compared these results to clinical data fom in an ongoing longitudinal study of patients with AN evaluated before and after refeeding as well as 6 months after hospital discharge.

Long-term food restriction in mice was associated with increased ghrelin and decreased LEAP-2 concentrations compared to ad libitum fed controls. Refeeding led to an increase in LEAP-2 concentrations. Patients with AN displayed increased ghrelin levels but also higher LEAP-2 concentrations on admission than after refeeding. LEAP-2 decreased with refeeding. On 17 patients re-evaluated 6 months after discharge, patients with unstable weight gain exhibited a greater decrease of LEAP-2 concentrations during refeeding compared to patient with stable weight gain. Decreasing LEAP-2 concentrations was able to predict a negative outcome (i.e. unstable weight gain) in 80% of the cases.

We provide evidence that the ghrelin/LEAP-2 system is not regulated according to the nutritional status in AN as it is in the case of a physiological adaptation to food restriction. Our clinical data suggest that the evolution of LEAP-2 concentrations during refeeding is opposed to data from preclinical model and could give new insights on the outcome of weight gain in AN.

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The hormonal mediators of the stress response, such as glucocorticoids and catecholamines, have both protective and damaging effects on the body. In the short term, they are essential for adaptation, maintenance of homeostasis, and survival; but chronic exposure to stress or abnormalities in the modulation of the stress response can become maladaptive, leading to a broad range of physical and mental problems.

Allostatic load refers to the activation of physiological regulatory systems in response to stress and “the cost” of the effects of these systems on the body. Results from isolated biomarkers and allostatic load measures based on the stress response system (hypothalamic-pituitary-adrenal axis, autonomic nervous system and immuno-metabolic biomarkers) and its relationships with clinical outcomes, such as cognition, in a clinical sample of major depression patients will be presented. The usefulness and relevance in the clinical practice of those biomarkers and the allostatic load concept will be discussed. The integration of several biomarkers translating the biological and psychological impact of stress on depression development and its clinical trajectories could contribute toward understanding how to prevent and improve outcomes in major depression.

V. Soria Grant / Research support from: Instituto de Salud Carlos III and the Bellvitge Biomedical Research Institute

Approximately one-third of patients with psychotic disorders does not respond to standard antipsychotic treatments. Consensus criteria for treatment resistance (TR) may aid the identification of non-response and subsequent tailoring of treatments. Since consensus criteria require stability of clinical status, they are challenging to apply in first-episode psychosis (FEP). This study aims to investigate (a) if an adaptation of consensus criteria can be used to identify FEP patients with early signs of TR (no early clinical recovery—no-ECR) after 1 year in treatment and (b) to what extent differences in antipsychotic treatments differentiate between outcome groups.

Participants with FEP DSM-IV schizophrenia spectrum disorders were recruited during their first treatment. A total of 207 participated in the 1-year follow-up. Remission and recovery definitions were based on adaptations of the “Remission in Schizophrenia Working Group” criteria and TR on adaptations of the “Treatment Response and Resistance in Psychosis” (TRRIP) working group criteria.

97 participants (47%) could be classified as no-ECR, 61 (30%) as ECR, and 49 (23%) as with partial ECR (P-ECR). Statistically significant baseline predictors of no-ECR matched previously identified predictors of long-term TR. Only 35 no-ECR participants had two adequate treatment trials and met the full TRRIP criteria. 21 no-ECR participants were using the same medication over the follow-up year despite the lack of significant effects.

The difference in the percentage of FEP participants classified as no-ECR versus TR indicates that we may underestimate the prevalence of early TR when using consensus criteria.