Anhedonia as a potential transdiagnostic phenotype with immune-related changes in recent onset mental health disorders.

BACKGROUND: Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes - reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in those with enduring illness, with few exploring inflammatory changes. We sought to identify an inflammatory signal and associated brain function underlying anhedonia among young people with recent onset psychosis (ROP) and recent onset depression (ROD). METHOD: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from N=108 (M age=26.2[SD 6.2]years; Female =50) participants with ROP (n=53) and ROD (n=55) from the EU-FP7-funded PRONIA study. Time-series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and functional connectivity model were developed to classify an anhedonic group, compared to a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic ROP/ROD groups with a balanced accuracy (BAC) of 63.9%, and an area under the curve (AUC) of 0.61. The functional connectivity model produced a BAC of 55.2% and an AUC of 0.57. Anhedonic group assignment was driven by higher levels of Interleukin-6, S100B, and Interleukin-1 receptor antagonist, and lower levels of Interferon gamma, in addition to connectivity within the precuneus and posterior cingulate. CONCLUSION: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Medical comorbidities in bipolar disorder (BIPCOM): clinical validation of risk factors and biomarkers to improve prevention and treatment. Study protocol.

BACKGROUND: BIPCOM aims to (1) identify medical comorbidities in people with bipolar disorder (BD); (2) examine risk factors and clinical profiles of Medical Comorbidities (MC) in this clinical group, with a special focus on Metabolic Syndrome (MetS); (3) develop a Clinical Support Tool (CST) for the personalized management of BD and medical comorbidities. METHODS: The BIPCOM project aims to investigate MC, specifically MetS, in individuals with BD using various approaches. Initially, prevalence rates, characteristics, genetic and non-genetic risk factors, and the natural progression of MetS among individuals with BD will be assessed by analysing Nordic registers, biobanks, and existing patient datasets from 11 European recruiting centres across 5 countries. Subsequently, a clinical study involving 400 participants from these sites will be conducted to examine the clinical profiles and incidence of specific MetS risk factors over 1 year. Baseline assessments, 1-year follow-ups, biomarker analyses, and physical activity measurements with wearable biosensors, and focus groups will be performed. Using this comprehensive data, a CST will be developed to enhance the prevention, early detection, and personalized treatment of MC in BD, by incorporating clinical, biological, sex and genetic information. This protocol will highlight the study's methodology. DISCUSSION: BIPCOM's data collection will pave the way for tailored treatment and prevention approaches for individuals with BD. This approach has the potential to generate significant healthcare savings by preventing complications, hospitalizations, and emergency visits related to comorbidities and cardiovascular risks in BD. BIPCOM's data collection will enhance BD patient care through personalized strategies, resulting in improved quality of life and reduced costly interventions. The findings of the study will contribute to a better understanding of the relationship between medical comorbidities and BD, enabling accurate prediction and effective management of MetS and cardiovascular diseases. TRIAL REGISTRATION: ISRCTN68010602 at https://www.isrctn.com/ISRCTN68010602 . Registration date: 18/04/2023.

Antibody Response against SARS-CoV-2 after mRNA Vaccine in a Cohort of Hospital Healthy Workers Followed for 17 Months.

The assessment of antibody response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of critical importance to verify the protective efficacy of available vaccines. Hospital healthcare workers play an essential role in the care and treatment of patients and were particularly at risk of contracting the SARS-CoV-2 infection during the pandemic. The vaccination protocol introduced in our hospital protected the workers and contributed to the containment of the infection' s spread and transmission, although a reduction in vaccine efficacy against symptomatic and breakthrough infections in vaccinated individuals was observed over time. Here, we present the results of a longitudinal and prospective analysis of the anti-SARS-CoV-2 antibodies at multiple time points over a 17-month period to determine how circulating antibody levels change over time following natural infection and vaccination for SARS-CoV-2 before (T0-T4) and after the spread of the omicron variant (T5-T6), analyzing the antibody response of 232 healthy workers at the Pio XI hospital in Desio. A General Estimating Equation model indicated a significant association of the antibody response with time intervals and hospital area, independent of age and sex. Specifically, a similar pattern of antibody response was observed between the surgery and administrative departments, and a different pattern with higher peaks of average antibody response was observed in the emergency and medical departments. Furthermore, using a logistic model, we found no differences in contracting SARS-CoV-2 after the third dose based on the hospital department. Finally, analysis of antibody distribution following the spread of the omicron variant, subdividing the cohort of positive individuals into centiles, highlighted a cut-off of 550 BAU/mL and showed that subjects with antibodies below this are more susceptible to infection than those with a concentration above the established cut-off value.

Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review.

Background: Schizophrenia spectrum disorders (SSD) can be associated with an increased risk of violent behavior (VB), which can harm patients, others, and properties. Prediction of VB could help reduce the SSD burden on patients and healthcare systems. Some recent studies have used machine learning (ML) algorithms to identify SSD patients at risk of VB. In this article, we aimed to review studies that used ML to predict VB in SSD patients and discuss the most successful ML methods and predictors of VB. Methods: We performed a systematic search in PubMed, Web of Sciences, Embase, and PsycINFO on September 30, 2023, to identify studies on the application of ML in predicting VB in SSD patients. Results: We included 18 studies with data from 11,733 patients diagnosed with SSD. Different ML models demonstrated mixed performance with an area under the receiver operating characteristic curve of 0.56-0.95 and an accuracy of 50.27-90.67% in predicting violence among SSD patients. Our comparative analysis demonstrated a superior performance for the gradient boosting model, compared to other ML models in predicting VB among SSD patients. Various sociodemographic, clinical, metabolic, and neuroimaging features were associated with VB, with age and olanzapine equivalent dose at the time of discharge being the most frequently identified factors. Conclusion: ML models demonstrated varied VB prediction performance in SSD patients, with gradient boosting outperforming. Further research is warranted for clinical applications of ML methods in this field.

Distinct multimodal biological and functional profiles of symptom-based subgroups in recent-onset psychosis.

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.

Fetal brain MRI atlases and datasets: A review.

Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., "brain template" and "brain atlas"), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging.

Antibody Response after 3-Dose Booster against SARS-CoV-2 mRNA Vaccine in Kidney Transplant Recipients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with a high rate of mortality in kidney transplant recipients (KTRs). Current vaccine strategies for KTRs seem to be unable to provide effective protection against coronavirus disease 2019 (COVID-19), and the occurrence of severe disease in some vaccinated KTRs suggested a lack of immunity. We initially analyzed the antibody response in a group of 32 kidney transplant recipients (KTRs) followed at the nephrology and dialysis unit of the Hospital Pio XI of Desio, ASST-Brianza, Italy. Thus, we studied the differences in antibody levels between subjects who contracted SARS-CoV-2 after the booster (8 individuals) and those who did not contract it (24 individuals). Furthermore, we verified if the antibody response was in any way associated with creatinine and eGFR levels. We observed a significant increase in the antibody response pre-booster compared to post-booster using both a Roche assay and DIAPRO assay. In the latter, through immunotyping, we highlight that the major contribution to this increase is specifically due to IgG S1 IgM S2. We observed a significant increase in IgA S1 and IgA NCP (p = 0.045, 0.02) in the subjects who contracted SARS-CoV-2. We did not find significant associations for the p-value corrected for false discovery rate (FDR) between the antibody response to all assays and creatinine levels. This observation allows us to confirm that patients require additional vaccine boosters due to their immunocompromised status and therapy in order to protect them from infections related to viral variants. This is in line with the data reported in the literature, and it could be worthwhile to deeply explore these phenomena to better understand the role of IgA S1 and IgA NCP antibodies in SARS-CoV-2 infection.

Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study.

Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.

Machine learning and the prediction of suicide in psychiatric populations: a systematic review.

Machine learning (ML) has emerged as a promising tool to enhance suicidal prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric populations, a formal psychiatric diagnosis emerged as a strong predictor of suicidal risk, overshadowing more subtle risk factors specific to distinct populations. To overcome this limitation, we conducted a systematic review of ML studies evaluating suicidal behaviors exclusively in psychiatric clinical populations. A systematic literature search was performed from inception through November 17, 2022 on PubMed, EMBASE, and Scopus following the PRISMA guidelines. Original research using ML techniques to assess the risk of suicide or predict suicide attempts in the psychiatric population were included. An assessment for bias risk was performed using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. About 1032 studies were retrieved, and 81 satisfied the inclusion criteria and were included for qualitative synthesis. Clinical and demographic features were the most frequently employed and random forest, support vector machine, and convolutional neural network performed better in terms of accuracy than other algorithms when directly compared. Despite heterogeneity in procedures, most studies reported an accuracy of 70% or greater based on features such as previous attempts, severity of the disorder, and pharmacological treatments. Although the evidence reported is promising, ML algorithms for suicidal prediction still present limitations, including the lack of neurobiological and imaging data and the lack of external validation samples. Overcoming these issues may lead to the development of models to adopt in clinical practice. Further research is warranted to boost a field that holds the potential to critically impact suicide mortality.

Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders.

BACKGROUND: Psychosis and depression patients exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC), allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders. METHODS: In the present study, we report the analysis of dFC in a large patient sample including 127 clinical high-risk patients (CHR), 142 recent-onset psychosis (ROP) patients, 134 recent-onset depression (ROD) patients, and 256 healthy controls (HC). A sliding window-based technique was used to calculate the time-dependent FC in resting-state MRI data, followed by clustering to reveal recurrent FC states in each diagnostic group. RESULTS: We identified five unique FC states, which could be identified in all groups with high consistency (rmean = 0.889, sd = 0.116). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly-connected FC state in ROD patients (p < 0.0005) compared to most other groups, and a common increase in the lifetime of a FC state characterised by high sensorimotor and cingulo-opercular connectivities in all patient groups compared to the HC group (p < 0.0002). Canonical correlation analysis revealed a mode which exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < 0.0029), which was associated with positive psychosis symptom severity and several dFC parameters. CONCLUSIONS: Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression, psychosis and clinical risk states.

Quantifying pH-induced changes in plasma strong ion difference during experimental acidosis: clinical implications for base excess interpretation.

It is commonly assumed that changes in plasma strong ion difference (SID) result in equal changes in whole blood base excess (BE). However, at varying pH, albumin ionic-binding and transerythrocyte shifts alter the SID of plasma without affecting that of whole blood (SIDwb), i.e., the BE. We hypothesize that, during acidosis, 1) an expected plasma SID (SIDexp) reflecting electrolytes redistribution can be predicted from albumin and hemoglobin's charges, and 2) only deviations in SID from SIDexp reflect changes in SIDwb, and therefore, BE. We equilibrated whole blood of 18 healthy subjects (albumin = 4.8 ± 0.2 g/dL, hemoglobin = 14.2 ± 0.9 g/dL), 18 septic patients with hypoalbuminemia and anemia (albumin = 3.1 ± 0.5 g/dL, hemoglobin = 10.4 ± 0.8 g/dL), and 10 healthy subjects after in vitro-induced isolated anemia (albumin = 5.0 ± 0.2 g/dL, hemoglobin = 7.0 ± 0.9 g/dL) with varying CO2 concentrations (2-20%). Plasma SID increased by 12.7 ± 2.1, 9.3 ± 1.7, and 7.8 ± 1.6 mEq/L, respectively (P < 0.01) and its agreement (bias[limits of agreement]) with SIDexp was strong: 0.5[-1.9; 2.8], 0.9[-0.9; 2.6], and 0.3[-1.4; 2.1] mEq/L, respectively. Separately, we added 7.5 or 15 mEq/L of lactic or hydrochloric acid to whole blood of 10 healthy subjects obtaining BE of -6.6 ± 1.7, -13.4 ± 2.2, -6.8 ± 1.8, and -13.6 ± 2.1 mEq/L, respectively. The agreement between ΔBE and ΔSID was weak (2.6[-1.1; 6.3] mEq/L), worsening with varying CO2 (2-20%): 6.3[-2.7; 15.2] mEq/L. Conversely, ΔSIDwb (the deviation of SID from SIDexp) agreed strongly with ΔBE at both constant and varying CO2: -0.1[-2.0; 1.7], and -0.5[-2.4; 1.5] mEq/L, respectively. We conclude that BE reflects only changes in plasma SID that are not expected from electrolytes redistribution, the latter being predictable from albumin and hemoglobin's charges.NEW & NOTEWORTHY This paper challenges the assumed equivalence between changes in plasma strong ion difference (SID) and whole blood base excess (BE) during in vitro acidosis. We highlight that redistribution of strong ions, in the form of albumin ionic-binding and transerythrocyte shifts, alters SID without affecting BE. We demonstrate that these expected SID alterations are predictable from albumin and hemoglobin's charges, or from the noncarbonic whole blood buffer value, allowing a better interpretation of SID and BE during in vitro acidosis.

Longitudinal outcomes of a work inclusion program in mental health departments in the city of Milan.

BACKGROUND: Work functioning impairment is a key diagnostic and prognostic criterion in patients with psychiatric disorders and work inclusion is a major goal of their therapeutic pathway. Since 2009, the Regional Innovative Program (PIR) TR106, promoted by ASST Fatebenefratelli-Sacco of Milan in collaboration with other Departments of Mental Health and Addictions (DSMDs) in the town of Milan (Italy), has been developing the employment inclusion of psychiatric patients. AIMS: The objective of this study is to evaluate its outcomes over 8 years of observation. METHOD: We reported the results of a retrospective epidemiologic analysis on 2,142 interventions on 1,066 patients recruited, investigating PIR TR106 outcomes per year focusing on different subgroups. We focused on 'positive', 'negative', and 'other' outcomes. RESULTS: We preliminary calculated job maintenance interventions (5%, 107) and excluded these interventions from the overall. We observed 29 job firing (1.4%) and 15 job resignations (0.7%) as negative results (equal to 2.2% of the total) and 388 job hiring (16.6%), 647 traineeships (31.8%), and 413 work formation (20.3%) as positive outcomes (equal to 68.75%). In other outcomes (29.1%) we found 305 dismissals from PIR TR 106 (15%) and transitory outcomes (14.1%).Job hiring increased from 8.9% in 2012 to 23.8 % in 2019 (p < .001), while the dismissals diminished from 26.7% to 13.3% (p < .001). The effectiveness of traineeships in terms of job hiring increased in the ratio of annual job hiring versus job traineeship (+48.8%). The majority of hired patients (15.1%) were affected by a psychotic disorder. A significant hiring increase was observed in patients with psychotic disorders and personality disorders (p < .005). CONCLUSIONS: PIR-TR106 represents a territorial employment inclusion program with progressively increasing effectiveness and specificity, as suggested by changes in outcomes during the 8-year observation. The adaptive capacity and sustainability of the intervention are worth further investigation.

Right frontal cingulate cortex mediates the effect of prenatal complications on youth internalizing behaviors.

Prenatal and perinatal complications represent well-known risk factors for the future development of psychiatric disorders. Such influence might become manifested during childhood and adolescence, as key periods for brain and behavioral changes. Internalizing and externalizing behaviors in adolescence have been associated with the risk of psychiatric onset later in life. Both brain morphology and behavior seem to be affected by obstetric complications, but a clear link among these three aspects is missing. Here, we aimed at analyzing the association between prenatal and perinatal complications, behavioral issues, and brain volumes in a group of children and adolescents. Eighty-two children and adolescents with emotional-behavioral problems underwent clinical and 3 T brain magnetic resonance imaging (MRI) assessments. The former included information on behavior, through the Child Behavior Checklist/6-18 (CBCL/6-18), and on the occurrence of obstetric complications. The relationships between clinical and gray matter volume (GMV) measures were investigated through multiple generalized linear models and mediation models. We found a mutual link between prenatal complications, GMV alterations in the frontal gyrus, and withdrawn problems. Specifically, complications during pregnancy were associated with higher CBCL/6-18 withdrawn scores and GMV reductions in the right superior frontal gyrus and anterior cingulate cortex. Finally, a mediation effect of these GMV measures on the association between prenatal complications and the withdrawn dimension was identified. Our findings suggest a key role of obstetric complications in affecting brain structure and behavior. For the first time, a mediator role of frontal GMV in the relationship between prenatal complications and internalizing symptoms was suggested. Once replicated on independent cohorts, this evidence will have relevant implications for planning preventive interventions.

C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project.

BACKGROUND AND AIMS: Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population. METHODS: Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L). RESULTS: Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024). CONCLUSIONS: While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.

Microstructural white matter alterations associated with social anxiety disorders: A systematic review.

BACKGROUND: Social anxiety disorder (SAD) is a psychiatric condition characterized by impaired social functioning that negatively impacts individuals' quality of life. Previous neuroimaging studies have revealed morphological and functional changes in various brain regions associated with SAD. Recent advances in diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) have enabled the investigation of microstructural white matter (WM) alterations in SAD. This study aims to provide an overview of DTI/DWI studies exploring WM microstructure changes in SAD. METHODS: A systematic search on PubMed, Scopus, Web of Science, and PsycINFO was conducted for relevant records on July 8, 2023. An exploratory meta-analysis was also performed. RESULTS: Eight studies were reviewed. Consistent findings indicated reduced fractional anisotropy and increased diffusivity measures in different WM tracts in SAD patients compared to healthy controls. These alterations were mostly observed within regions of the fronto-limbic network, like uncinate fasciculus (UF) and superior and inferior longitudinal fasciculi (SLF and ILF). Finally, our exploratory meta-analysis on four studies utilizing a voxel-wise analytic approach yielded no significant differences between SAD patients and controls. LIMITATIONS: Limited number of studies, small sample sizes, and heterogeneity in analysis methods. CONCLUSIONS: Patients with SAD exhibited altered WM integrity, particularly in the UF, SLF, and ILF, compared to healthy controls. However, due to the limited number of included studies, our meta-analysis yielded no significant differences between SAD patients and controls. Therefore, future research is crucial to unravel the link between altered WM structure and the involvement of other limbic and cortical structures in SAD pathogenesis.

Case report and systematic review of cerebellar vermis alterations in psychosis.

INTRODUCTION: Cerebellar alterations, including both volumetric changes in the cerebellar vermis and dysfunctions of the corticocerebellar connections, have been documented in psychotic disorders. Starting from the clinical observation of a bipolar patient with cerebellar hypoplasia, the purpose of this review is to summarize the data in the literature about the association between hypoplasia of the cerebellar vermis and psychotic disorders [schizophrenia (SCZ) and bipolar disorder (BD)]. METHODS: A bibliographic search on PubMed has been conducted, and 18 articles were finally included in the review: five used patients with BD, 12 patients with SCZ and one subject at psychotic risk. RESULTS: For SCZ patients and subjects at psychotic risk, the results of most of the reviewed studies seem to suggest a gray matter volume reduction coupled with an increase in white matter volumes in the cerebellar vermis, compared to healthy controls. Instead, the results of the studies on BD patients are more heterogeneous with evidence showing a reduction, no difference or even an increase in cerebellar vermis volume compared to healthy controls. CONCLUSIONS: From the results of the reviewed studies, a possible correlation emerged between cerebellar vermis hypoplasia and psychotic disorders, especially SCZ, ultimately supporting the hypothesis of psychotic disorders as neurodevelopmental disorders.

Chronic exposure to imipramine induces a switch from depression-like to mania-like behavior in female serotonin transporter knockout rats: Role of BDNF signaling in the infralimbic cortex.

BACKGROUND: Bipolar disorder (BD) is a highly burdensome psychiatric disorder characterized by alternating states of mania and depression. A major challenge in the clinic is the switch from depression to mania, which is often observed in female BD patients during antidepressant treatment such as imipramine. However, the underlying neural basis is unclear. METHODS: To investigate the potential neuronal pathways, serotonin transporter knockout (SERT KO) rats, an experimental model of female BD patients, were subjected to a battery of behavioral tests under chronic treatment of the antidepressant imipramine. In addition, the expression of brain-derived neurotrophic factor (BDNF) and its downstream signaling was examined in the prefrontal cortex. RESULTS: Chronic exposure to imipramine reduced anxiety and sociability and problem-solving capacity, and increased thigmotaxis and day/night activity in all animals, but specifically in female SERT KO rats, compared to female wild-type (WT) rats. Further, we found an activation of BDNF-TrkB-Akt pathway signaling in the infralimbic, but not prelimbic, cortex after chronic imipramine treatment in SERT KO, but not WT, rats. LIMITATIONS: Repeated testing behaviors could potentially affect the results. Additionally, the imipramine induced changes in behavior and in the BDNF system were measured in separate animals. CONCLUSIONS: Our study indicates that female SERT KO rats, which mirror the female BD patients with the 5-HTTLPR s-allele, are at higher risk of a switch to mania-like behaviors under imipramine treatment. Activation of the BDNF-TrkB-Akt pathway in the infralimbic cortex might contribute to this phenotype, but causal evidence remains to be provided.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness.

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.