[FG] Schmidt AndréHead of Research Unit PD DRAndré SchmidtOverviewMembersPublicationsProjects & CollaborationsProjects & Collaborations OverviewMembersPublicationsProjects & Collaborations Projects & Collaborations 5 foundShow per page10 10 20 50 Gut microbiota - hippocampus synergisms in non-clinical subjects with high positive schizotypy Research Project | 4 Project MembersBackground and rationale: Compelling support has accumulated for the concept that psychosis develops along a continuum. The model proposes a dimensional continuity between subclinical psychotic experiences in healthy individuals from the general population (also termed schizotypy) and clinically relevant psychosis. Schizotypy can be understood as a developmental mediator between early endophenotypes and later risk for developing overt psychosis. Hippocampal dysregulation might be a key factor for the developmental trajectory of psychotic disorders and is related to poorclinical outcomes. Recent evidence from the emerging field of gut-brain communication further shows that gut microbiota can greatly influence hippocampus function. While preliminary studies indicate alterations in gut microbiota in patients with schizophrenia, it remains completely unknown whether gut microbiota alterations are already evident in people with high level of schizotypy from the general population and whether they are related to hippocampus divergences. Overall objective: To explore aberrantgut microbiota- hippocampus interactions in non-clinical individuals with high positive schizotypy from the general population. Specific aims are to investigate differences in 1) hippocampus function and neurochemistry and 2) gut microbiota composition between people from the general population with low and high positive schizotypy and 3) whether hippocampal measures can predict different microbial profiles. Methods: 1) Hippocampus function and neurochemistry: Hippocampal perfusion and activation at rest and during verbal learning will be measured with arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI). Hippocampal GABA and glutamate concentrations will be assessed with magnetic resonance spectroscopy (MRS). Imaging analyses will be performed with Statistical Parametric Mapping using two-sample t tests to compare groups (p < 0.05, corrected for family-wise error (FWE) rate). 2 ) Gut microbiota : state-of the-art Quantitative Microbiome Profiling based on 16S ribosomal RNA sequencing. Alpha-diversity by means of richness and species abundance will be tested using nonparametric Kruskal-Wallis test. Differences in species abundance (beta-diversity) will be calculated using Bray-Curtis distances and group differences will be assessed with permutational analysis of variance. 3) Gut microbiota - hippocampus synergisms : Clusters of enterotypes will be determined based on Dirichlet Multinomial Modeling. ANOVA will be conducted to test whether participants belonging to different enterotypes show differences in hippocampal measures. Furthermore, sparse partial least squares discriminant analysis will be performed to determine if hippocampal measures can predict enterotype membership. Expected results: Most prominent hippocampus differences between high and low schizotypy will be hypothesized in GABA and glutamate concentrations, with lower GABA and higher glutamate concentrations in people with positive schizotypy. We expect increased abundance of short-chain fatty acid producing bacteria in people with high positive schizotypy compared to those with low schizotypy. Finally, we expect that enterotype can be predicted by hippocampal measures with above-chance accuracy, while GABA and glutamate concentrations will provide the most explanatory power. Impact for the field This project may deliver novel prognostic and predictive biomarkers for improving psychosis prediction and developing novel interventions targeted toimprove hippocampus functioning and prevent related clinical outcomes in non-clinical and clinical people at increased risk of developing psychosis. A randomized add-on pilot trial of D-serine for depression Research Project | 3 Project MembersThe glutamate system is emerging as target for the development of novel antidepressant medication, in particular compounds modulating the NMDA receptor. While the NMDA receptor antagonist ketamine is an effective option for many treatment-restistan patients, it is also accompanied by dissociative and cognitive effects and also bears the risk to develop addiction, side effects that are significantly restricting its clinical utility. There is now compelling evidence of the antidepressant potential of D-serine, a NMDAR co-agonist. Compared to ketamine, D-serine goes along without any psychotomimetic effects or other side effects and thus might be a promising novel antidepressant. This study represents the first randomized control trial to test the efficacy of D-serine as an adjuvant therapy in patients with depression and thereby adds to recent efforts to establish novel glutamatergic antidepressants. Multidimensional Biomarker Development for Personalized Probiotic Treatment Outcome in Depression Research Project | 1 Project MembersAdvances in understanding the role of the gut microbiota in mental health are at the forefront of medical research and hold the potential to have a direct impact on precision medicine approaches. It has been shown that changes in the composition of the gut microbiota influence normal physiology and contribute to diseases ranging from obesity to psychiatric diseases such as major depressive disorder (MDD). Emerging evidence indicate that the gut microbiota communicates with the central nervous system via endocrine, immune and neural pathways and thereby influences brain function and behaviour. Elucidating the pathways linking gut-microbiota and the brain may allow detecting potential biomarkers that could be used in psychiatry. There is a particular need in patients with MDD to identify biomarkers that can stratify patients into more homogeneous groups to achieve better treatment outcomes. This is of great importance as almost two thirds of MDD patients do not respond to current treatment approaches. This project seeks to identify multidimensional biomarkers for probiotic treatment response in patients with MDD. In particular, the present proposal investigates the effect of short-term probiotic augmentation on immunological, inflammatory, microbial, genetic and neural markers along the brain-gut axis in patients with depression and whether baseline expression of these potential biomarkers predicts the individual clinical response to probiotic treatment. In line with the concept of personalized medicine, such predictive biomarkers allow patient stratification by targeting those individuals who are actually going to benefit from probiotic augmentation. Moreover, identifying biological targets that are associated with the clinical response to probiotic treatment further enables the development of novel and more effective nutrition-based interventions for patients with MDD. Behavioural addiction or affective disorder? Clinical classification and neural substrates of excessive physical training Research Project | 6 Project MembersNo Description available Risk Prediction in Offspring of Patients with Schizophrenia and Depression using Whole-Brain Network Markers Research Project | 1 Project MembersOffspring of parents with severe mental illnesses have an increased risk for psychiatric disorders and up to one third of them may develop a severe mental illness by early adulthood. Notably, the risk is related to a range of psychiatric disorders and not exclusively to the disorder diagnosed in the parent, indicating that a transdiagnostic staging approach is going to be necessary. A key challenge in research on the early detection of psychiatric disorders is to distinguish those who are going to develop the disorder from those who will not. However, the accuracy of clinical assessment instruments to predict risk propensity in young high-risk individuals is limited because they do not capture relevant pathophysiological mechanisms. Therefore there is urgent need to find complementary data such as biological variables to improve risk prediction in young people at high-risk for developing a psychiatric disorder. Brain imaging has emerged as a powerful tool to map direct neurobiological processes associated with the development of the illness. Numerous imaging studies have demonstrated that psychiatric disorders are associated with structural and functional brain abnormalities, which are already evident in the early stages of the disorder. More recent brain network studies suggest a more fine-grained interpretation by revealing that brain abnormalities in psychiatric disorders are not solely attributable to changes in local regions and connections but rather emerge from changes in the topology of the network as a whole, the connectome of the brain. These network findings indicate that many mental disorders may be best understood in terms of brain network dysfunction rather then by localized 'lesions'. Moreover, it has been shown that psychiatric disorders often share underlying brain network pathology, which makes traditional diagnostic boundaries less meaningful. Variability in the configuration of the brain connectome may lead to variability in symptom expression and thereby producing transdiagnostic symptoms The purpose of this project is to test the clinical utility of structural and functional whole-brain network markers to predict risk propensity in children and adolescents with an increased risk for developing schizophrenia and depression. In particular, we will investigate using graphical theoretical analysis of magnetic resonance imaging (MRI) data whether complex measures of the brain connectome at initial baseline assessments can predict clinical and psychological features at follow-up assessments in offspring of parents with schizophrenia and depression. The results of this project may allow individual risk stratification and the development personalized preventive interventions in individuals at high-risk for mental illnesses. Furthermore, this project may also provide neural targets for assessing the efficacy of novel treatment scenarios. 1 1 OverviewMembersPublicationsProjects & Collaborations
Projects & Collaborations 5 foundShow per page10 10 20 50 Gut microbiota - hippocampus synergisms in non-clinical subjects with high positive schizotypy Research Project | 4 Project MembersBackground and rationale: Compelling support has accumulated for the concept that psychosis develops along a continuum. The model proposes a dimensional continuity between subclinical psychotic experiences in healthy individuals from the general population (also termed schizotypy) and clinically relevant psychosis. Schizotypy can be understood as a developmental mediator between early endophenotypes and later risk for developing overt psychosis. Hippocampal dysregulation might be a key factor for the developmental trajectory of psychotic disorders and is related to poorclinical outcomes. Recent evidence from the emerging field of gut-brain communication further shows that gut microbiota can greatly influence hippocampus function. While preliminary studies indicate alterations in gut microbiota in patients with schizophrenia, it remains completely unknown whether gut microbiota alterations are already evident in people with high level of schizotypy from the general population and whether they are related to hippocampus divergences. Overall objective: To explore aberrantgut microbiota- hippocampus interactions in non-clinical individuals with high positive schizotypy from the general population. Specific aims are to investigate differences in 1) hippocampus function and neurochemistry and 2) gut microbiota composition between people from the general population with low and high positive schizotypy and 3) whether hippocampal measures can predict different microbial profiles. Methods: 1) Hippocampus function and neurochemistry: Hippocampal perfusion and activation at rest and during verbal learning will be measured with arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI). Hippocampal GABA and glutamate concentrations will be assessed with magnetic resonance spectroscopy (MRS). Imaging analyses will be performed with Statistical Parametric Mapping using two-sample t tests to compare groups (p < 0.05, corrected for family-wise error (FWE) rate). 2 ) Gut microbiota : state-of the-art Quantitative Microbiome Profiling based on 16S ribosomal RNA sequencing. Alpha-diversity by means of richness and species abundance will be tested using nonparametric Kruskal-Wallis test. Differences in species abundance (beta-diversity) will be calculated using Bray-Curtis distances and group differences will be assessed with permutational analysis of variance. 3) Gut microbiota - hippocampus synergisms : Clusters of enterotypes will be determined based on Dirichlet Multinomial Modeling. ANOVA will be conducted to test whether participants belonging to different enterotypes show differences in hippocampal measures. Furthermore, sparse partial least squares discriminant analysis will be performed to determine if hippocampal measures can predict enterotype membership. Expected results: Most prominent hippocampus differences between high and low schizotypy will be hypothesized in GABA and glutamate concentrations, with lower GABA and higher glutamate concentrations in people with positive schizotypy. We expect increased abundance of short-chain fatty acid producing bacteria in people with high positive schizotypy compared to those with low schizotypy. Finally, we expect that enterotype can be predicted by hippocampal measures with above-chance accuracy, while GABA and glutamate concentrations will provide the most explanatory power. Impact for the field This project may deliver novel prognostic and predictive biomarkers for improving psychosis prediction and developing novel interventions targeted toimprove hippocampus functioning and prevent related clinical outcomes in non-clinical and clinical people at increased risk of developing psychosis. A randomized add-on pilot trial of D-serine for depression Research Project | 3 Project MembersThe glutamate system is emerging as target for the development of novel antidepressant medication, in particular compounds modulating the NMDA receptor. While the NMDA receptor antagonist ketamine is an effective option for many treatment-restistan patients, it is also accompanied by dissociative and cognitive effects and also bears the risk to develop addiction, side effects that are significantly restricting its clinical utility. There is now compelling evidence of the antidepressant potential of D-serine, a NMDAR co-agonist. Compared to ketamine, D-serine goes along without any psychotomimetic effects or other side effects and thus might be a promising novel antidepressant. This study represents the first randomized control trial to test the efficacy of D-serine as an adjuvant therapy in patients with depression and thereby adds to recent efforts to establish novel glutamatergic antidepressants. Multidimensional Biomarker Development for Personalized Probiotic Treatment Outcome in Depression Research Project | 1 Project MembersAdvances in understanding the role of the gut microbiota in mental health are at the forefront of medical research and hold the potential to have a direct impact on precision medicine approaches. It has been shown that changes in the composition of the gut microbiota influence normal physiology and contribute to diseases ranging from obesity to psychiatric diseases such as major depressive disorder (MDD). Emerging evidence indicate that the gut microbiota communicates with the central nervous system via endocrine, immune and neural pathways and thereby influences brain function and behaviour. Elucidating the pathways linking gut-microbiota and the brain may allow detecting potential biomarkers that could be used in psychiatry. There is a particular need in patients with MDD to identify biomarkers that can stratify patients into more homogeneous groups to achieve better treatment outcomes. This is of great importance as almost two thirds of MDD patients do not respond to current treatment approaches. This project seeks to identify multidimensional biomarkers for probiotic treatment response in patients with MDD. In particular, the present proposal investigates the effect of short-term probiotic augmentation on immunological, inflammatory, microbial, genetic and neural markers along the brain-gut axis in patients with depression and whether baseline expression of these potential biomarkers predicts the individual clinical response to probiotic treatment. In line with the concept of personalized medicine, such predictive biomarkers allow patient stratification by targeting those individuals who are actually going to benefit from probiotic augmentation. Moreover, identifying biological targets that are associated with the clinical response to probiotic treatment further enables the development of novel and more effective nutrition-based interventions for patients with MDD. Behavioural addiction or affective disorder? Clinical classification and neural substrates of excessive physical training Research Project | 6 Project MembersNo Description available Risk Prediction in Offspring of Patients with Schizophrenia and Depression using Whole-Brain Network Markers Research Project | 1 Project MembersOffspring of parents with severe mental illnesses have an increased risk for psychiatric disorders and up to one third of them may develop a severe mental illness by early adulthood. Notably, the risk is related to a range of psychiatric disorders and not exclusively to the disorder diagnosed in the parent, indicating that a transdiagnostic staging approach is going to be necessary. A key challenge in research on the early detection of psychiatric disorders is to distinguish those who are going to develop the disorder from those who will not. However, the accuracy of clinical assessment instruments to predict risk propensity in young high-risk individuals is limited because they do not capture relevant pathophysiological mechanisms. Therefore there is urgent need to find complementary data such as biological variables to improve risk prediction in young people at high-risk for developing a psychiatric disorder. Brain imaging has emerged as a powerful tool to map direct neurobiological processes associated with the development of the illness. Numerous imaging studies have demonstrated that psychiatric disorders are associated with structural and functional brain abnormalities, which are already evident in the early stages of the disorder. More recent brain network studies suggest a more fine-grained interpretation by revealing that brain abnormalities in psychiatric disorders are not solely attributable to changes in local regions and connections but rather emerge from changes in the topology of the network as a whole, the connectome of the brain. These network findings indicate that many mental disorders may be best understood in terms of brain network dysfunction rather then by localized 'lesions'. Moreover, it has been shown that psychiatric disorders often share underlying brain network pathology, which makes traditional diagnostic boundaries less meaningful. Variability in the configuration of the brain connectome may lead to variability in symptom expression and thereby producing transdiagnostic symptoms The purpose of this project is to test the clinical utility of structural and functional whole-brain network markers to predict risk propensity in children and adolescents with an increased risk for developing schizophrenia and depression. In particular, we will investigate using graphical theoretical analysis of magnetic resonance imaging (MRI) data whether complex measures of the brain connectome at initial baseline assessments can predict clinical and psychological features at follow-up assessments in offspring of parents with schizophrenia and depression. The results of this project may allow individual risk stratification and the development personalized preventive interventions in individuals at high-risk for mental illnesses. Furthermore, this project may also provide neural targets for assessing the efficacy of novel treatment scenarios. 1 1
Gut microbiota - hippocampus synergisms in non-clinical subjects with high positive schizotypy Research Project | 4 Project MembersBackground and rationale: Compelling support has accumulated for the concept that psychosis develops along a continuum. The model proposes a dimensional continuity between subclinical psychotic experiences in healthy individuals from the general population (also termed schizotypy) and clinically relevant psychosis. Schizotypy can be understood as a developmental mediator between early endophenotypes and later risk for developing overt psychosis. Hippocampal dysregulation might be a key factor for the developmental trajectory of psychotic disorders and is related to poorclinical outcomes. Recent evidence from the emerging field of gut-brain communication further shows that gut microbiota can greatly influence hippocampus function. While preliminary studies indicate alterations in gut microbiota in patients with schizophrenia, it remains completely unknown whether gut microbiota alterations are already evident in people with high level of schizotypy from the general population and whether they are related to hippocampus divergences. Overall objective: To explore aberrantgut microbiota- hippocampus interactions in non-clinical individuals with high positive schizotypy from the general population. Specific aims are to investigate differences in 1) hippocampus function and neurochemistry and 2) gut microbiota composition between people from the general population with low and high positive schizotypy and 3) whether hippocampal measures can predict different microbial profiles. Methods: 1) Hippocampus function and neurochemistry: Hippocampal perfusion and activation at rest and during verbal learning will be measured with arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI). Hippocampal GABA and glutamate concentrations will be assessed with magnetic resonance spectroscopy (MRS). Imaging analyses will be performed with Statistical Parametric Mapping using two-sample t tests to compare groups (p < 0.05, corrected for family-wise error (FWE) rate). 2 ) Gut microbiota : state-of the-art Quantitative Microbiome Profiling based on 16S ribosomal RNA sequencing. Alpha-diversity by means of richness and species abundance will be tested using nonparametric Kruskal-Wallis test. Differences in species abundance (beta-diversity) will be calculated using Bray-Curtis distances and group differences will be assessed with permutational analysis of variance. 3) Gut microbiota - hippocampus synergisms : Clusters of enterotypes will be determined based on Dirichlet Multinomial Modeling. ANOVA will be conducted to test whether participants belonging to different enterotypes show differences in hippocampal measures. Furthermore, sparse partial least squares discriminant analysis will be performed to determine if hippocampal measures can predict enterotype membership. Expected results: Most prominent hippocampus differences between high and low schizotypy will be hypothesized in GABA and glutamate concentrations, with lower GABA and higher glutamate concentrations in people with positive schizotypy. We expect increased abundance of short-chain fatty acid producing bacteria in people with high positive schizotypy compared to those with low schizotypy. Finally, we expect that enterotype can be predicted by hippocampal measures with above-chance accuracy, while GABA and glutamate concentrations will provide the most explanatory power. Impact for the field This project may deliver novel prognostic and predictive biomarkers for improving psychosis prediction and developing novel interventions targeted toimprove hippocampus functioning and prevent related clinical outcomes in non-clinical and clinical people at increased risk of developing psychosis.
A randomized add-on pilot trial of D-serine for depression Research Project | 3 Project MembersThe glutamate system is emerging as target for the development of novel antidepressant medication, in particular compounds modulating the NMDA receptor. While the NMDA receptor antagonist ketamine is an effective option for many treatment-restistan patients, it is also accompanied by dissociative and cognitive effects and also bears the risk to develop addiction, side effects that are significantly restricting its clinical utility. There is now compelling evidence of the antidepressant potential of D-serine, a NMDAR co-agonist. Compared to ketamine, D-serine goes along without any psychotomimetic effects or other side effects and thus might be a promising novel antidepressant. This study represents the first randomized control trial to test the efficacy of D-serine as an adjuvant therapy in patients with depression and thereby adds to recent efforts to establish novel glutamatergic antidepressants.
Multidimensional Biomarker Development for Personalized Probiotic Treatment Outcome in Depression Research Project | 1 Project MembersAdvances in understanding the role of the gut microbiota in mental health are at the forefront of medical research and hold the potential to have a direct impact on precision medicine approaches. It has been shown that changes in the composition of the gut microbiota influence normal physiology and contribute to diseases ranging from obesity to psychiatric diseases such as major depressive disorder (MDD). Emerging evidence indicate that the gut microbiota communicates with the central nervous system via endocrine, immune and neural pathways and thereby influences brain function and behaviour. Elucidating the pathways linking gut-microbiota and the brain may allow detecting potential biomarkers that could be used in psychiatry. There is a particular need in patients with MDD to identify biomarkers that can stratify patients into more homogeneous groups to achieve better treatment outcomes. This is of great importance as almost two thirds of MDD patients do not respond to current treatment approaches. This project seeks to identify multidimensional biomarkers for probiotic treatment response in patients with MDD. In particular, the present proposal investigates the effect of short-term probiotic augmentation on immunological, inflammatory, microbial, genetic and neural markers along the brain-gut axis in patients with depression and whether baseline expression of these potential biomarkers predicts the individual clinical response to probiotic treatment. In line with the concept of personalized medicine, such predictive biomarkers allow patient stratification by targeting those individuals who are actually going to benefit from probiotic augmentation. Moreover, identifying biological targets that are associated with the clinical response to probiotic treatment further enables the development of novel and more effective nutrition-based interventions for patients with MDD.
Behavioural addiction or affective disorder? Clinical classification and neural substrates of excessive physical training Research Project | 6 Project MembersNo Description available
Risk Prediction in Offspring of Patients with Schizophrenia and Depression using Whole-Brain Network Markers Research Project | 1 Project MembersOffspring of parents with severe mental illnesses have an increased risk for psychiatric disorders and up to one third of them may develop a severe mental illness by early adulthood. Notably, the risk is related to a range of psychiatric disorders and not exclusively to the disorder diagnosed in the parent, indicating that a transdiagnostic staging approach is going to be necessary. A key challenge in research on the early detection of psychiatric disorders is to distinguish those who are going to develop the disorder from those who will not. However, the accuracy of clinical assessment instruments to predict risk propensity in young high-risk individuals is limited because they do not capture relevant pathophysiological mechanisms. Therefore there is urgent need to find complementary data such as biological variables to improve risk prediction in young people at high-risk for developing a psychiatric disorder. Brain imaging has emerged as a powerful tool to map direct neurobiological processes associated with the development of the illness. Numerous imaging studies have demonstrated that psychiatric disorders are associated with structural and functional brain abnormalities, which are already evident in the early stages of the disorder. More recent brain network studies suggest a more fine-grained interpretation by revealing that brain abnormalities in psychiatric disorders are not solely attributable to changes in local regions and connections but rather emerge from changes in the topology of the network as a whole, the connectome of the brain. These network findings indicate that many mental disorders may be best understood in terms of brain network dysfunction rather then by localized 'lesions'. Moreover, it has been shown that psychiatric disorders often share underlying brain network pathology, which makes traditional diagnostic boundaries less meaningful. Variability in the configuration of the brain connectome may lead to variability in symptom expression and thereby producing transdiagnostic symptoms The purpose of this project is to test the clinical utility of structural and functional whole-brain network markers to predict risk propensity in children and adolescents with an increased risk for developing schizophrenia and depression. In particular, we will investigate using graphical theoretical analysis of magnetic resonance imaging (MRI) data whether complex measures of the brain connectome at initial baseline assessments can predict clinical and psychological features at follow-up assessments in offspring of parents with schizophrenia and depression. The results of this project may allow individual risk stratification and the development personalized preventive interventions in individuals at high-risk for mental illnesses. Furthermore, this project may also provide neural targets for assessing the efficacy of novel treatment scenarios.
