Antidepressants are commonly prescribed for mood disorders. Epidemiological studies suggest antidepressant use may be associated with cataracts and glaucoma. We aim to investigate the association between antidepressants and cataracts and glaucoma.

Data was collected from the United States Food and Drug Administration Adverse Event Reporting System. Reporting odds ratio (ROR) and Bayesian information components (IC025) were calculated for antidepressants (ie, selective serotonin reuptake inhibitors [SSRIs], selective norepinephrine reuptake inhibitors [SNRIs], serotonin-norepinephrine-dopamine reuptake inhibitors, serotonin modulators and stimulators, serotonin antagonists and reuptake inhibitors [SARIs], norepinephrine reuptake inhibitors, norepinephrine-dopamine reuptake inhibitors, tricyclic antidepressants [TCAs], tetracyclic antidepressants [TeCAs], and monoamine oxidase inhibitors [MAOIs]). The reference agent was acetaminophen.

TeCAs and MAOIs were significantly associated with a decreased risk of cataracts (ROR = 0.11-0.65 and 0.16-0.69, respectively). TCAs, brexanolone, esketamine, and opipramol reported an increased cataract risk (ROR = 1.31-12.81). For glaucoma, SSRIs, SNRIs, SARIs, TCAs, MAOIs, and other investigated antidepressants reported significant RORs ranging from 1.034 to 21.17. There was a nonsignificant association of angle closure glaucoma (ACG) and open angle glaucoma (OAG) with the investigated antidepressants.

For adverse event cases, multiple suspected product names are listed, and as cases are not routinely verified, there may be a possibility of duplicate reports and causality cannot be established.

Most of the investigated antidepressants were associated with a lower risk of cataract reporting. TCAs, brexanolone, esketamine, and opipramol were associated with greater odds of cataract. For most antidepressants, there was an insignificant increase in reports of ACG and OAG.

Many psychotropic drugs are highly associated with related weight gain. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are established anti-obesity and glucose-lowering agents. Preliminary evidence also indicates they are fit for purpose in mitigating psychotropic drug-related weight gain (PDWG). This systematic review aims to synthesize the extant evidence from randomized controlled trials (RCTs) on the effects of GLP-1RAs on weight change in persons experiencing PDWG.

Online databases (ie, PubMed, OVID Medline, Google Scholar) were searched to identify relevant studies from inception to January 1, 2024. Articles were screened by title, abstract, and full-text by three independent reviewers against inclusion and exclusion criteria.

We identified six studies with participants aged ≥18 (n=374) that were eligible for inclusion in our systematic review. Most studies reported a significant and clinically meaningful effect of GLP-1RAs on anthropometrics and/or metabolics. All RCTs replicated the finding of modest or greater effects of GLP-1RAs; the most studied agents were liraglutide and exenatide. There was insufficient literature to conduct a meta-analysis.

Evidence suggests that GLP-1RAs are effective in mitigating weight gain in persons prescribed psychiatric medication. It is hypothesized that GLP-1RAs may moderate weight change in persons prescribed psychiatric medication through direct effects on metabolism and cognitive processes implicated in hunger/satiety. Future studies should aim to explore the long-term safety, tolerability, and efficacy profiles of various GLP-1RAs in the treatment and prevention of abnormal weight and metabolic homeostasis in psychiatric populations.

There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives.

In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years.

At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker.

Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

The conceptualization of negative symptoms (NS) in schizophrenia is still controversial. Recent confirmatory factor-analytic studies suggested that the bi-dimensional model (motivational deficit [MAP] and expressive deficit [EXP]) may not capture the complexity of NS structure, which could be better defined by a five-factor (five NS domains) or a hierarchical model (five NS domains as first-order factors, and MAP and EXP, as second-order factors). A validation of these models is needed to define the structure of NS. To evaluate the validity and temporal stability of the five-factor or the hierarchical structure of the brief negative symptom scale (BNSS) in individuals with schizophrenia (SCZ), exploring associations between these models with cognition, social cognition, functional capacity, and functioning at baseline and at 4 years follow-up.

Clinical variables were assessed using state-of-the-art tools in 612 SCZ at two-time points. The validity of the five-factor and the hierarchical models was analyzed through structural equation models.

The two models had both a good fit and showed a similar pattern of associations with external validators at the two-time points, with minor variations. The five-factor solution had a slightly better fit. The associations with external validators favored the five-factor structure.

Our findings suggest that both five-factor and hierarchical models provide a valid conceptualization of NS in relation to external variables and that five-factor solution provides the best balance between parsimony and granularity to summarize the BNSS structure. This finding has important implications for the study of pathophysiological mechanisms and the development of new treatments.

The structure of negative symptoms of schizophrenia is still a matter of controversy. Although a two-dimensional model (comprising the expressive deficit dimension and the motivation and pleasure dimension) has gained a large consensus, it has been questioned by recent investigations.

To investigate the latent structure of negative symptoms and its stability over time in people with schizophrenia using network analysis.

Negative symptoms were assessed in 612 people with schizophrenia using the Brief Negative Symptom Scale (BNSS) at baseline and at 4-year follow-up. A network invariance analysis was conducted to investigate changes in the network structure and strength of connections between the two time points.

The network analysis carried out at baseline and follow-up, supported by community detection analysis, indicated that the BNSS's items aggregate to form four or five distinct domains (avolition/asociality, anhedonia, blunted affect and alogia). The network invariance test indicated that the network structure remained unchanged over time (network invariance test score 0.13; P = 0.169), although its overall strength decreased (6.28 at baseline, 5.79 at follow-up; global strength invariance test score 0.48; P = 0.016).

The results lend support to a four- or five-factor model of negative symptoms and indicate overall stability over time. These data have implications for the study of pathophysiological mechanisms and the development of targeted treatments for negative symptoms.

Negative symptoms represent a fundamental aspect of schizophrenia: they have a substantial impact on patients’ real-life functioning and do not respond satisfactorily to currently available treatments. Therefore, a better understanding of the pathophysiological mechanisms underlying these symptoms could favor the development of new treatments.

To date, the most validated pathophysiological hypothesis indicates an association between the Motivational domain (consisting of avolition, anhedonia and asociality) and alterations in the neuronal circuits involved in motivation. The Expressive Deficit domain (consisting of blunted affect and alogia) would be subtended by widespread alterations of cortical connectivity and associated with impaired neurocognition, social cognition, and the presence of neurological soft signs.

The aim of the present study is to examine the neurobiological correlates of the two domains of negative symptoms, starting from the brain areas that have been most commonly found in the literature to be associated with negative symptoms.

Resting-state (rs) fMRI data were acquired in 62 subjects with schizophrenia (SZ) and 46 healthy controls (HC). The two negative symptom domains were assessed using the Brief Negative Symptom Scale. In addition, the following assessment tools were used: the Positive and Negative Syndrome Scale for the assessment of positive symptoms and disorganization, the Calgary Depression Scale for Schizophrenia for depression and the St. Hans Rating Scale for extrapyramidal symptoms. The study of the possible relationships between rs-brain activity and the negative symptoms domains was conducted through partial correlations, checking for possible confounding factors (positive, depressive, extrapyramidal symptoms and disorganization).

The SZ, compared to the HC, showed higher rs-brain activity of the right inferior parietal lobule and of the right temporoparietal junction and lower rs-brain activity of the right dorsolateral prefrontal cortex, bilateral anterior dorsal cingulate cortex, bilateral ventral caudate and bilateral dorsal caudate. Furthermore, in the group of patients, the rs-brain activity of the left ventral caudate showed a moderate negative correlation with the Expressive deficit domain (r = -0.401; p = 0.003), but not with the Motivational domain.

The results of the present study, in line with the literature, demonstrated how the two domains of negative symptomatology are subtended by different pathophysiological mechanisms. Given the role played by the ventral caudate in neurocognitive processes, these results are in line with the hypothesis that Expressive deficit may have a common etiopathogenesis with cognitive deficits. A better understanding of the neurobiology of negative symptoms could foster the development of innovative treatment strategies targeting the two negative symptom domains.

None Declared

Negative symptoms (NS) represent a heterogeneous construct of schizophrenia, whose conceptualization is still to be clarified. In the last decade, the conceptualization model that has received the most support from the literature has described 2 NS domains: the expressive deficit (EXP), which includes blunted affect and alogia, and the motivational deficit (MAP), which includes avolition, asociality, and anhedonia. However, different confirmatory factor-analytic studies suggest that the bi-dimensional model may not capture the complexity of this construct, which could be better defined by a 5-factor model (5 individual negative symptoms) or a hierarchical model (5 individual negative symptoms as first-order factors, and the 2 domains, MAP and EXP domains, as second-order factors). However, to our knowledge, no study has investigated associations between negative symptom models with social cognition and functional capacity, which are largely documented to correlate with negative symptoms, nor the associations with external validators over time, looking at the potential stability of negative symptom models validity through the course of the illness.

In the light of this observations, we investigated, the external validity of the five-factor model and the hierarchical model of the BNSS in subjects with schizophrenia, looking at associations with cognition, social cognition, functioning and functional capacity at baseline and at four years follow-up.

NS were assessed in 612 subjects with schizophrenia using the Brief Negative Symptom Scale at the baseline and after 4-year follow-up. State of the art assessment instruments were used to assess cognitive and functioning related variables. Structural equation models (SEM) that included the NS models and 4 external variables were used to our aim.

According to recent multicenter studies, our results confirmed the validity of the 5-factor- and the hierarchical-model of negative symptoms. In particular, these 2 models proved to be equivalent in terms of fit to the data at baseline and follow-up. As regard to the relationship of the two BNSS models with external variables, we found that there was a similar pattern of associations at the two time points despite minor variations.

The five factor and the hierarchical models provide an optimal conceptualization of negative symptoms in relation to external variables. The similar pattern of associations with external variables of the two models at the two time points despite minor variations, suggests that the simple and widely used 5-factor solution provides the best balance between parsimony and granularity to summarize BNSS structure. This data is of important relevance with consequent implications in the study of pathophysiological mechanisms and the development of targeted treatments for NS.

None Declared

Negative symptoms (NS) represent an unmet need of treatment in schizophrenia (SCZ). As a result, these symptoms pose a significant burden on patients, their families, and the health care system. In the last decade, the conceptualization model that has received the most support from the literature has described 2 domains of NS: the expressive deficit (EXP), which includes blunted affect and alogia, and the motivational deficit (MAP), which includes avolition, asociality, and anhedonia. However, different confirmatory factor-analytic studies suggest that the bi-dimensional model may not capture the complexity of this construct, which could be better defined by the 5-factor model. To date no study exploiting innovative tools and state of the art assessment instruments has yet been conducted to evaluate the NS structure stability over time.

The aim of this study was to investigate the stability of the latent structure of NS in subjects with SCZ.

NS were assessed in 612 subjects with SCZ using the Brief Negative Symptom Scale (BNSS) at the baseline and after 4-year follow-up. A network invariance analysis was conducted for the data collected longitudinally.

Results showed that the BNSS’ items aggregated to form 5 distinct domains (avolition, asociality, blunted affect, alogia and anhedonia). The result of the network invariance test indicated that the network structure remained unchanged over time (network invariance test = 0.13; p = 0.169) while its overall strength decreased significantly (6.28 baseline, 5.79 at follow-up; global strength invariance test = 0.48; p = 0.016).

The results of this study show how the construct of NS can be better explained by the 5 individual negative symptoms and that this model is almost stable over time. Therefore the 2-dimensional model may be insufficient to describe the characteristics of NS. This data is of important relevance with consequent implications in the study of pathophysiological mechanisms and the development of targeted treatments for NS.

None Declared

In recent years, numerous studies have highlighted the overlap between autism spectrum disorder (ASD) and catatonia, both from a clinical and pathophysiological perspective. This study aimed to investigate the relationship between the autism spectrum (autistic traits and ASD signs, symptoms, and behavioral manifestation) and Catatonia Spectrum (CS).

A total sample of 376 subjects was distributed in four diagnostic groups. Subjects were assessed with the Structured Clinical Interview for DSM-5, Research Version, the Adult Autism Subthreshold Spectrum (AdAS Spectrum), and CS. In the statistical analyses, the total sample was also divided into three groups according to the degree of autism severity, based on the AdAS Spectrum total score.

A statistically significant positive correlation was found between AdAS Spectrum and CS total score within the total sample, the gender subgroups, and the diagnostic categories. The AdAS Spectrum domains found to be significantly and strongly correlated with the total CS score were hyper–hypo reactivity to sensory input, verbal communication, nonverbal communication, restricted interests and rumination, and inflexibility and adherence to routine. The three groups of different autistic severity were found to be distributed across all diagnostic groups and the CS score increased significantly from the group without autistic traits to the group with ASD.

Our study reports a strong correlation between autism spectrum and CS.

Honoraria, advisory board, or consulting fees from Angelini, Astra Zeneca, Bristol-Myers Squibb, Gedeon Richter Bulgaria, Innova-Pharma, Janssen Pharmaceuticals, Lundbeck, Otsuka, Pfizer, and Pierre Fabre, for services not related to this abstract

An extensive literature regarding gender differences relevant to several aspects of schizophrenia is nowadays available. It includes some robust findings as well as some inconsistencies. The identification of gender differences and the understanding of their explanations may help to clarify the underlying etiopathogenetic mechanisms of specific aspects of the disorder.

The present study aimed at investigating gender differences on premorbid, clinical, cognitive and outcome indices, as well as their impact on recovery, in a large sample of patients with schizophrenia recruited within the multicenter study of the Italian Network for Research on Psychoses.

State-of-the-art instruments were used to assess the investigated domains. Group comparisons between male and female patients were performed on all considered indices. The associations of premorbid, clinical and cognitive indices with recovery in the two patient groups were investigated by means of multiple regressions.

Males with respect to females had a worse premorbid adjustment – limited to the academic dimension – an earlier age of onset, a higher frequency of history of substance and alcohol abuse, more severe negative symptoms (both avolition and expressive deficit), positive symptoms and impairment of social cognition. No gender difference was observed in neurocognition nor in the rates of recovery.

Although males showed some disadvantages in the clinical picture, this was not translated into a worse outcome. This finding may be related to the complex interplay of several factors acting as predictors or mediators of outcome.

No significant relationships.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Despite innovative treatments, the impairment in real-life functioning in subjects with schizophrenia (SCZ) remains an unmet need in the care of these patients. Recently, real-life functioning in SCZ was associated with abnormalities in different electrophysiological indices. It is still not clear whether this relationship is mediated by other variables, and how the combination of different EEG abnormalities influences the complex outcome of schizophrenia.

The purpose of the study was to find EEG patterns which can predict the outcome of schizophrenia and identify recovered patients.

Illness-related and functioning-related variables were measured in 61 SCZ at baseline and after four-years follow-up. EEGs were recorded at the baseline in resting-state condition and during two auditory tasks. We performed Sparse Partial Least Square (SPLS) Regression, using EEG features, age and illness duration to predict clinical and functional features at baseline and follow up. Through a Linear Support Vector Machine (Linear SVM) we used electrophysiological and clinical scores derived from SPLS regression, in order to classify recovered patients at follow-up.

We found one significant latent variable (p<0.01) capturing correlations between independent and dependent variables at follow-up (RHO=0.56). Among individual predictors, age and illness-duration showed the highest scores; however, the score for the combination of the EEG features was higher than all other predictors. Within dependent variables, negative symptoms showed the strongest correlation with predictors. Scores resulting from SPLS Regression classified recovered patients with 90.1% of accuracy.

A combination of electrophysiological markers, age and illness-duration might predict clinical and functional outcome of schizophrenia after 4 years of follow-up.

No significant relationships.

Central to recovery-oriented approaches in schizophrenia are treatment integration and personalization, targeting key variables beyond symptom reduction. The Italian network for research on psychoses conducted a study demonstrating, using network analysis, the central role of community activities in bridging the effects of symptoms, cognition, functional capacity and service engagement on real-word functioning. A 4-year follow-up study was recently completed and the presentation will illustrate the findings. Network analysis was used to test whether relationships among all variables at baseline were similar at follow-up. In addition, the network structure was compared between subjects classified as recovered or non-recovered at follow-up. Six hundred eighteen subjects were assessed at both baseline and 4-year follow-up. Results showed that the network structure was stable from baseline to follow-up, and the overall strength of the connections among variables did not significantly change. Functional capacity and everyday life skills were the most central variables in the network at both baseline and follow-up, while psychopathological variables were more peripheral. The network structure of non-recovered patients was similar to the one observed in the whole sample, but very different from that of recovered subjects, showing few connections among the different nodes. These data strongly suggest that connections among symptoms/dysfunctions tend to maintain over time, contributing to poor outcome in schizophrenia. Early treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia.

Armida Mucci has been a consultant and/or advisor to or has received honoraria from Gedeon Richter Bulgaria, Janssen Pharmaceuticals, Lundbeck, Otsuka, Pfizer and Pierre Fabre. None of these has any impact on this abstract and on the presented study.

No significant relationships.