Structural and functional cerebral changes in patients with schizophrenia and genetic risk-allele carriers

Schizophrenia is one of the most frequent psychiatric disorders and is associated with a substantial part of worldwide disease burdon1. The clinical symptoms of patients with schizophrenia can be separated into positive symptoms such as halluciations and delusions as well as negative symptoms such as cognitive impairments, apathy, blunted affect and social withdrawal2. It has been suggested that understanding the underlying pathophysiological processes that give rise to these symptoms is a crucial step for the development of efficient treatment for schizophrenia3. In the presented work two aspects of the clinical symptomatology of schizophrenia are analyzed with respect to their potential neurobiological correlate. Following the dopamine-hypothesis, patients with schizophrenia exhibit an increase in dopaminergic neurotransmission in the striatum which might be related to the experience of positive symptoms4,5. In the first publication evidence for this dopamine-hypothesis from in-vivo neuroimaging studies was investigated in a comprehensive meta-analysis. Results are in the line with the dopamine-hypothesis and point to an increase of striatal presynaptic dopamine synthesis in schizophrenia: - Howes OD*, Kambeitz J*, Kim E, Stahl D, Slifstein M, Abi-Dargham A*, Kapur S* (2012): The nature of dopamine dysfunction in schizophrenia and what this means for treatment. Arch Gen Psychiatry 69: 776–786. * these authors contributed equally ISI Web of Knowledge: Archives of General Psychiatry (now: JAMA Psychiatry) impact factor 2012: 13.77 5-year impact factor 2012: 14.47 Ranked 3rd of all psychiatry journals The negative symptoms of schizophrenia such as cognitive impairments have frequently been associated with changes of cerebral gray matter in numerous brain regions including the hippocampus6–9. In the second publication, effects of a potential risk-gene on the hippocampus are analyzed. Results indicate reduced hippocampal structure and function in carriers of the met-allele of the BDNF polymorphism val(66)met: - Kambeitz JP*, Bhattacharyya S*, Kambeitz-Ilankovic LM, Valli I, Collier DA, McGuire P (2012): Effect of BDNF val(66)met polymorphism on declarative memory and its neural substrate: a meta-analysis. Neurosci Biobehav Rev 36: 2165–2177. * these authors contributed equally ISI Web of Knowledge: Neuroscience and Biobehavioral Reviews impact factor 2012: 9.44 5-year impact factor 2012: 9.92 Ranked 12th of all neurosciences journal

Structural and functional cerebral changes in patients with schizophrenia and genetic risk-allele carriers

Schizophrenia is one of the most frequent psychiatric disorders and is associated with a substantial part of worldwide disease burdon1. The clinical symptoms of patients with schizophrenia can be separated into positive symptoms such as halluciations and delusions as well as negative symptoms such as cognitive impairments, apathy, blunted affect and social withdrawal2. It has been suggested that understanding the underlying pathophysiological processes that give rise to these symptoms is a crucial step for the development of efficient treatment for schizophrenia3. In the presented work two aspects of the clinical symptomatology of schizophrenia are analyzed with respect to their potential neurobiological correlate. Following the dopamine-hypothesis, patients with schizophrenia exhibit an increase in dopaminergic neurotransmission in the striatum which might be related to the experience of positive symptoms4,5. In the first publication evidence for this dopamine-hypothesis from in-vivo neuroimaging studies was investigated in a comprehensive meta-analysis. Results are in the line with the dopamine-hypothesis and point to an increase of striatal presynaptic dopamine synthesis in schizophrenia: - Howes OD*, Kambeitz J*, Kim E, Stahl D, Slifstein M, Abi-Dargham A*, Kapur S* (2012): The nature of dopamine dysfunction in schizophrenia and what this means for treatment. Arch Gen Psychiatry 69: 776–786. * these authors contributed equally ISI Web of Knowledge: Archives of General Psychiatry (now: JAMA Psychiatry) impact factor 2012: 13.77 5-year impact factor 2012: 14.47 Ranked 3rd of all psychiatry journals The negative symptoms of schizophrenia such as cognitive impairments have frequently been associated with changes of cerebral gray matter in numerous brain regions including the hippocampus6–9. In the second publication, effects of a potential risk-gene on the hippocampus are analyzed. Results indicate reduced hippocampal structure and function in carriers of the met-allele of the BDNF polymorphism val(66)met: - Kambeitz JP*, Bhattacharyya S*, Kambeitz-Ilankovic LM, Valli I, Collier DA, McGuire P (2012): Effect of BDNF val(66)met polymorphism on declarative memory and its neural substrate: a meta-analysis. Neurosci Biobehav Rev 36: 2165–2177. * these authors contributed equally ISI Web of Knowledge: Neuroscience and Biobehavioral Reviews impact factor 2012: 9.44 5-year impact factor 2012: 9.92 Ranked 12th of all neurosciences journal

Insecure attachment as a transdiagnostic risk factor for major psychiatric conditions: A meta-analysis in bipolar disorder, depression and schizophrenia spectrum disorder

Insecure attachment has been suggested as a major risk factor for mental health problems as well as a key element for the development and trajectory of psychiatric disorders. The aim of this meta-analysis was to assess whether insecure attachment constitutes a global transdiagnostic risk factor in bipolar disorder, depression, and schizophrenia spectrum disorders. We conducted a PRISMA-based systematic quantitative review to explore the prevalence of insecure attachment among patients of three representative psychiatric disorders - major depression, schizophrenia spectrum disorders and bipolar disorder - in comparison with healthy controls (HC) from a transdiagnostic point of view. Effect sizes on differences of anxious, avoidant and insecure prevalence were calculated based on 40 samples including a total of n = 2927 individuals. Overall, results indicated a large effect on prevalence of insecure attachment across all disorders compared to HC (k = 30, g = 0.88, I2 = 71.0%, p < 0.001). In a transdiagnostic comparison, the only difference was found in avoidant attachment, which was significantly lower (p = 0.04) compared to HC in the schizophrenia spectrum disorder subgroup (k = 10, g = 0.31, I2 = 76.60%, p < 0.0001) than the depression subgroup subgroup (k = 12, g = 0.83, I2 = 46.65%, p < 0.0001). The lack of further transdiagnostic differences between three distinct psychiatric disorders corroborates insecure attachment as a general vulnerability factor to psychopathology. Our findings warrant further investigations, which should explore the pathways from attachment insecurity towards psychopathology. Insecure attachment likely has implications on assessment, prediction and treatment of psychiatric patients

Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers

Magnetic resonance imaging-based markers of schizophrenia have been repeatedly shown to separate patients from healthy controls at the single-subject level, but it remains unclear whether these markers reliably distinguish schizophrenia from mood disorders across the life span and generalize to new patients as well as to early stages of these illnesses. The current study used structural MRI-based multivariate pattern classification to (i) identify and cross-validate a differential diagnostic signature separating patients with first-episode and recurrent stages of schizophrenia (n = 158) from patients with major depression (n = 104); and (ii) quantify the impact of major clinical variables, including disease stage, age of disease onset and accelerated brain ageing on the signature's classification performance. This diagnostic magnetic resonance imaging signature was then evaluated in an independent patient cohort from two different centres to test its generalizability to individuals with bipolar disorder (n = 35), first-episode psychosis (n = 23) and clinically defined at-risk mental states for psychosis (n = 89). Neuroanatomical diagnosis was correct in 80% and 72% of patients with major depression and schizophrenia, respectively, and involved a pattern of prefronto-temporo-limbic volume reductions and premotor, somatosensory and subcortical increments in schizophrenia versus major depression. Diagnostic performance was not influenced by the presence of depressive symptoms in schizophrenia or psychotic symptoms in major depression, but earlier disease onset and accelerated brain ageing promoted misclassification in major depression due to an increased neuroanatomical schizophrenia likeness of these patients. Furthermore, disease stage significantly moderated neuroanatomical diagnosis as recurrently-ill patients had higher misclassification rates (major depression: 23%; schizophrenia: 29%) than first-episode patients (major depression: 15%; schizophrenia: 12%). Finally, the trained biomarker assigned 74% of the bipolar patients to the major depression group, while 83% of the first-episode psychosis patients and 77% and 61% of the individuals with an ultra-high risk and low-risk state, respectively, were labelled with schizophrenia. Our findings suggest that neuroanatomical information may provide generalizable diagnostic tools distinguishing schizophrenia from mood disorders early in the course of psychosis. Disease course-related variables such as age of disease onset and disease stage as well alterations of structural brain maturation may strongly impact on the neuroanatomical separability of major depression and schizophrenia

Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers

MRI-based markers can distinguish patients with schizophrenia from healthy controls. Koutsouleris et al. now report a diagnostic signature that distinguishes major depression/bipolar disorder from schizophrenia in 80%/74% of cases. Classification accuracy generalizes to early phases of psychosis, and is moderated by disease stage, age of onset and accelerated brain agein

A systematic review of digital and face-to-face cognitive behavioral therapy for depression

Cognitive behavioral therapy (CBT) represents one of the major treatment options for depressive disorders besides pharmacological interventions. While newly developed digital CBT approaches hold important advantages due to higher accessibility, their relative effectiveness compared to traditional CBT remains unclear. We conducted a systematic literature search to identify all studies that conducted a CBT-based intervention (face-to-face or digital) in patients with major depression. Random-effects meta-analytic models of the standardized mean change using raw score standardization (SMCR) were computed. In 106 studies including n = 11854 patients face-to-face CBT shows superior clinical effectiveness compared to digital CBT when investigating depressive symptoms (p < 0.001, face-to-face CBT: SMCR = 1.97, 95%-CI: 1.74–2.13, digital CBT: SMCR = 1.20, 95%-CI: 1.08–1.32) and adherence (p = 0.014, face-to-face CBT: 82.4%, digital CBT: 72.9%). However, after accounting for differences between face-to-face and digital CBT studies, both approaches indicate similar effectiveness. Important variables with significant moderation effects include duration of the intervention, baseline severity, adherence and the level of human guidance in digital CBT interventions. After accounting for potential confounders our analysis indicates comparable effectiveness of face-to-face and digital CBT approaches. These findings underline the importance of moderators of clinical effects and provide a basis for the future personalization of CBT treatment in depression

Deciphering reward-based decision-making in schizophrenia: a meta-analysis and behavioral modeling of the Iowa Gambling Task

Background: Patients with schizophrenia (SZP) have been reported to exhibit impairments in reward-based decision-making, but results are heterogeneous with multiple potential confounds such as age, intelligence level, clinical symptoms or medication, making it difficult to evaluate the robustness of these impairments. Methods: We conducted a meta-analysis of studies comparing the performance of SZP and healthy controls (HC) in the Iowa Gambling Task (IGT) as well as comprehensive analyses based on subject-level data (n = 303 SZP, n = 188 HC) to investigate reward-based decision-making in SZP. To quantify differences in the influence of individual deck features (immediate gain, gain frequency, net loss) between SZP and HC, we additionally employed a least-squares model. Results: SZP showed statistically significant suboptimal decisions as indicated by disadvantageous deck choices (d from 0.51 to −0.62) and lower net scores (d from −0.35 to −1.03) in a meta-analysis of k = 29 samples (n = 1127 SZP, n = 1149 HC) and these results were confirmed in a complementary subject-level analysis. Moreover, decision-making in SZP was characterized by a relative overweighting of immediate gain and net losses and an underweighting of gain frequency. Moderator analyses revealed that in part, decision-making in the IGT was moderated by intelligence level, medication and general symptom scores. Conclusion: Our results indicate robust impairments in reward-based decision-making in SZP and suggest that decreased cognitive resources, such as working memory, may contribute to these alterations

(Attenuated) hallucinations join basic symptoms in a transdiagnostic network cluster analysis

Producción CientíficaHallucinations are considered characteristic symptoms of psychosis and part of the ‘psychosis superspectrum’ of the Hierarchical Taxonomy Of Psychopathology (HiTOP) initiative. To gain insight into their psychopathological relevance, we studied their dimensional placement within a single dense transdiagnostic network constituting of basic symptoms as well as of attenuated and frank psychotic, and related symptoms. Newman's modularity analysis was used to detect symptom clusters in an earlier generated network (Jimeno, N., et al., 2020. Main symptomatic treatment targets in suspected and early psychosis: New insights from network analysis. Schizophr. Bull. 46, 884–895. https://doi.org/10.1093/schbul/sbz140). The constituting 86 symptoms were assessed with the Schizophrenia Proneness Instrument, Adult version (SPI-A), the Structured Interview for Psychosis-Risk Syndromes (SIPS), and the Positive And Negative Syndrome Scale (PANSS) in three adult samples of an early detection service: clinical high-risk (n = 203), first-episode psychosis (n = 153), and major depression (n = 104). Three clusters were detected: “subjective disturbances”, “positive symptoms and behaviors”, and “negative and anxious-depressive symptoms”. The predominately attenuated hallucinations of both SIPS and PANSS joined the basic symptoms in “subjective disturbances”, whereas other positive symptoms entered “positive symptoms and behaviors”. Our results underline the importance of insight in separating true psychotic hallucinations from other hallucinatory experiences that, albeit phenomenologically similar are still experienced with some insight, i.e., are present in an attenuated form. We conclude that, strictly, hallucinations held with any degree of insight should not be used to diagnose transition to or presence of frank psychoses and, relatedly, to justify antipsychotic medication.Deutsche Forschungsgemeinschaft (grants KL970/3-1 and KL970/3-2)Koeln Fortune Program / Faculty of Medicine of the University of Cologne (projects 8/2005 and 27/2006)Ministerio de Ciencia e Innovación - Fondo Europeo de Desarrollo Regional (projects PGC2018-098214-A-I00 and DPI2017-84280-R)Unión Europea (grant 602152)German Research Foundation (grant KA 4413/1-1

Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis

Cannabis use during adolescence is associated with an increased risk of developing psychosis. According to a current hypothesis, this results from detrimental effects of early cannabis use on brain maturation during this vulnerable period. However, studies investigating the interaction between early cannabis use and brain structural alterations hitherto reported inconclusive findings. We investigated effects of age of cannabis initiation on psychosis using data from the multicentric Personalized Prognostic Tools for Early Psychosis Management (PRONIA) and the Cannabis Induced Psychosis (CIP) studies, yielding a total sample of 102 clinically-relevant cannabis users with recent onset psychosis. GM covariance underlies shared maturational processes. Therefore, we performed source-based morphometry analysis with spatial constraints on structural brain networks showing significant alterations in schizophrenia in a previous multisite study, thus testing associations of these networks with the age of cannabis initiation and with confounding factors. Earlier cannabis initiation was associated with more severe positive symptoms in our cohort. Greater gray matter volume (GMV) in the previously identified cerebellar schizophrenia-related network had a significant association with early cannabis use, independent of several possibly confounding factors. Moreover, GMV in the cerebellar network was associated with lower volume in another network previously associated with schizophrenia, comprising the insula, superior temporal, and inferior frontal gyrus. These findings are in line with previous investigations in healthy cannabis users, and suggest that early initiation of cannabis perturbs the developmental trajectory of certain structural brain networks in a manner imparting risk for psychosis later in life