The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. Especially interesting for psychiatric research is using this approach to bridge between preclinical and clinical models to map out neural systems implicated in psychiatric disorders through genetics and modulated by legacy and known drugs. For this, species-conserved (intermediate) phenotypes that can be quantified and compared across species offer important advantages for translational research and drug discovery. In this talk we will illustrate the utility of network science methods to assess the pharmacological alterations of the large-scale architecture of brain networks in rats and humans. We demonstrate that the application of ketamine leads to a topological reconfiguration of large-scale brain networks towards less-integrated and more-segregated information processing in both the species. We then describe recently developed techniques stemming from advances in complex systems and network science that show neurogenetic and pharmacological effects related to glutamatergic neurotransmission. Building on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, this illustrates an approach using network-based methods to probe mechanisms of psychopathology and assess the effects with pharmacological, intermediate phenotype, genetic.
Update on neurogenetic and pharmacological effects and brain imaging phenotypes in mental disorders
Andreas Meyer-Lindenberg, Mannheim (Germany)
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Andreas Meyer-Lindenberg, Mannheim (Germany)
The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. Especially interesting for psychiatric research is using this approach to bridge between preclinical and clinical models to map out neural systems implicated in psychiatric disorders through genetics and modulated by legacy and known drugs. For this, species-conserved (intermediate) phenotypes that can be quantified and compared across species offer important advantages for translational research and drug discovery. In this talk we will illustrate the utility of network science methods to assess the pharmacological alterations of the large-scale architecture of brain networks in rats and humans. We demonstrate that the application of ketamine leads to a topological reconfiguration of large-scale brain networks towards less-integrated and more-segregated information processing in both the species. We then describe recently developed techniques stemming from advances in complex systems and network science that show neurogenetic and pharmacological effects related to glutamatergic neurotransmission. Building on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, this illustrates an approach using network-based methods to probe mechanisms of psychopathology and assess the effects with pharmacological, intermediate phenotype, genetic.
Polygenetic and epigenetic factors in mental disorders and brain ageing
Hans J. Grabe, Greifswald (Germany)
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Hans J. Grabe, Greifswald (Germany)
Brain aging refers to the age-depended atrophy of large parts of the brain. However, there is considerable difference in the speed of brain aging between different subjects. Based on machine learning algorithms we have determined the individual deviation from the mean regression over the population. We aim at exploring how depressive disorders, childhood traumatization and polygenetic risk scores (PRS) impact on brain age. PRS (Van der Auwera et al. Biol Psychiatry, 2015) are based on the recent results from genome-wide association analyses (GWAS) of schizophrenia, educational attainment (EA) and body-mass index (BMI). On the other hand, we investigated how cardiorespiratory fitness might counteract accelerated brain aging.
We used epidemiological data from the Study of Health in Pomerania (SHIP) in Germany. MRI scans (N>2500) and genetic data (N>3000) are available from the general population (age 35-85). Clinical interviews were performed in addition to self-rating questionnaires (Childhood Trauma Questionnaire, Beck Depression Inventory II).
BDI-II was positively associated with accelerated brain aging. Higher BMI and smoking were associated with accelerated brain aging. Interactions: Subjects with higher PRS for schizophrenia plus childhood abuse showed more age-specific brain atrophy. Moreover, subjects with a lower genetic score for EA plus current depression showed more age-specific brain atrophy. Increased cardiorespiratory fitness was highly protective against brain aging. These results will be discussed within a clincial therapeutic framework.