The IMAGEN project: “Reinforcement-related behaviour in normal brain function and psychopathology”
A fundamental function of the brain is to evaluate motivational and emotional significance of stimuli and to adapt behaviour accordingly. We hypothesize that genetically influenced individual differences in brain responses to reward, punishment and emotional cues in adolescents mediate risk for mental disorders with a major public health impact. Neuroimaging permits the measurement of specific brain functions implicated in the etiology of mental disorders and link them to genetic variations and behavioural characteristics relevant to disease processes. The goal of the IMAGEN study is to identify the neurobiological and genetic basis of these traits and to assess their relevance for mental disorder. To this end, we have performed the first multicentre functional and structural genetic-neuroimaging study of a cohort of 2000+ 14 year old adolescents. Intermediate phenotypes of risk for adolescent mental illness have been explored based on cognitive, behavioural, clinical and neuroimaging data. To determine the predictive value of intermediate phenotypes and genetics for development of mental disorders, our cohort has been psychometrically assessed during recruitment and longitudinally at age 16, 19 and 23 years. DNA samples and phenotype database for the cohort have created a powerful resource for present and future genetic investigations. The IMAGEN study is helping to elucidate the neural basis of mental disorders and will lay the groundwork for development of treatments that target specific pathological processes across mental disorders rather than heterogeneous categories of mental illness.
IMAGEN has recruited n=2090 participants from four European countries, UK, Germany, France and Ireland. Baseline assessment was at age 14 years, with follow-up assessments at 16 years, 19 years, and 23 years. IMAGEN measures include functional neuroimaging, including resting state and tasks assessing reward processing (Monetary Incentive Delay, MID; impulsiveness (Stop Signal Reaction Time, SSRT; social-emotional processing (Emotional Faces Task, EFT; and resting state. –genomics characterisation comprise genome-wide genomic (including exome sequencing), gene expression and epigenetic methylation data. Neuropsychological measures include IQ and executive function using the Cambridge Neuropsychological Test Automated Battery (CANTAB). Clinical phenotypes were indexed using the Development and Wellbeing Assessment (DAWBA) and Strengths and Difficulties Questionnaire (SDQ). There is an extensive characterisation of behavioural measures related to externalising behaviour and substance use.
Investigation of the IMAGEN dataset has yielded significant progress in both, the identification of mechanisms and the characterization of predictors of reinforcement related disorders. Our work has significantly influenced the field: From autumn 2010 until spring 2017 we have published over 85 publications, including in Nature, Science, Nature Genetics, Nature Neurosciences, PNAS, Nature Communications, Molecular Psychiatry, American Journal of Psychiatry, JAMA Psychiatry, Biological Psychiatry, PloS Genetics and other high ranking journals.
IMAGEN was funded by the European Commission as an Integrated Project and has attracted grants from various funding agencies, including the Medical Research Council and Nat. Inst. for Health Research (UK), the European Research Council (ERC), the Swedish Research Council, the German Ministry for Research (BMBF), and NIH and NIDA.
Brain network based stratification of reinforcement-related disorders [STRATIFY]
To reduce the burden of mental disorders it is a formidable aim to identify widely applicable disease markers based on neural processes, which predict psychopathology and allow for targeted interventions. In this project we are generating a neurobehavioural framework for stratification of psychopathology by characterising links between network properties of brain function and structure and reinforcement–related behaviours, which are fundamental components of some of the most prevalent mental disorders, major depression, alcohol use disorder and ADHD. We are assessing if network configurations define subtypes within and if they correspond to comorbidity across these diagnoses. We are identifying discriminative data modalities and characterize predictors of future psychopathology.
To identify specific neurobehavioural clusters we are carrying out precision phenotyping of 600 patients with major depression, ADHD and alcohol use disorders and 200 controls, which we are investigating with innovative deep machine learning methods derived from artifical intelligence research. Development of these methods will optimize exploitation of a wide range of assessment modalities, including functional and structural neuroimaging, cognitive, emotional as well as environmental measures. The neurobehavioural clusters resulting from this analysis are being validated in a longitudinal population-based imaging genomics cohort, the IMAGEN sample of over 2000 participants spanning the period from adolescence to adulthood and integrated with information generated from genomic and imaging-genomic meta-analyses of >300.000 individuals.
By targeting specific neural processes the resulting stratification markers will serve as paradigmatic examples for a diagnostic classification, which is based upon quantifiable neurobiological measures, thus enabling targeted early intervention, identification of novel pharmaceutical targets and the establishment of neurobehaviourally informed endpoints for clinical trials.
The fundamental gain of our proposal is the exact functional and anatomical characterization of brain networks and specific configurations, which are common and distinct among these disorders, and to relate them to precise symptom clusters. This is a paradigmatic approach, which can be extended to other behavioural domains, eventually making a significant contribution to a re-classification of mental disorders. Our approach will advance personalized medicine in psychiatry by allowing accurate patient stratification. Stratification markers, while based on comprehensive multimodal characterization will be selected to be easy to administer and cost-effective. This will ensure wide application, which is not only restricted to specialized tertiary care centres. Successful patient stratification will allow the development of targeted interventions ranging from personalized psychopharmacological treatment, specific psychosocial interventions to rational selection and modification of environmental influences.
STRATIFY is funded by and ERC Advanced Investigator Grant to Gunter Schumann.
Consortium on Vulnerability to Externalizing Disorders and Addictions [c-VEDA]
Alcohol use disorders (AUD) account for a disproportionately high share of the health burden in India and other low- and middle-income countries. This increasing burden is linked to societal changes in emerging nations, which include growing availability of alcohol, greater normalization of use and rapid changes in socio-economic conditions. Individuals with externalising behaviour, which are characterised by altered brain activity during reward processing and behavioural control have a higher risk for AUD. AUD and externalizing disorders share moderate to high heritability with environmental factors being important contributors. While both environmental and genetic factors conveying risk and resilience have been identified it is not established to what extent these factors are dependent on the wider socio-cultural and psychosocial context they are embedded in, or whether they are influenced by epigenetic and genetic factors that are specific for certain ethnicities. It is therefore unknown to what extent environmental and genetic risk factors are similar or distinct in industrialised nations and emerging societies such as in India. Furthermore, some environmental risk factors are largely specific to emerging societies, including exposure to nutritional stress, environmental neurotoxins and culturally dependent forms of psychosocial stress.
We are investigating in collaboration with Prof. Vivek Benegal of the National Institute for Mental Health and Neurosciences (NIMHANS), Bangalore and our Indian partners from Bangalore, Mysore, Calcutta, Chandigarh and Manupur if environmental and genetic risk factors in industrialised countries and emerging societies shape brain function and behaviour in distinct ways, thus leading to different risk constellations and neurobehavioural trajectories for substance misuse and externalising disorders.
To address this aim we will establish a comprehensive database allowing comparative analyses of behavioural trajectories in childhood and adolescence, which provide a platform for sustained India-UK collaborations in mental health research. This platform will ascertain a great variety of environmental factors (exposome), biological samples as well as detailed neuroimaging analyses. We propose to compare insights into etiology and trajectories into substance abuse and externalising disorders gained from major European and UK studies including the longitudinal imaging genetics study "Reinforcement-related behaviour in normal development and psychopathology" (IMAGEN) and the "Avon Longitudinal Study of Parents and Children" (ALSPAC) with existing Indian cohorts. The Indian cohorts, which comprise >14.000 participants with aged 0-25 years include both high risk for substance misuse and population-based individuals from different social and environmental (rural and urban) backgrounds. They have been selected to cover the developmental period assessed in the UK cohorts, thus rendering the studies comparable. We aim to enrich the Indian cohorts, which have mainly been designed to investigate somatic disorders by adding a comprehensive assessment of mental health, externalising behaviour and substance use disorders involving psychometric and neuropsychological characterisation, as well as biological sampling in >10.000 participants with an age range of 6-23 years. Assessment instruments and protocols have been selected to allow comparison to IMAGEN and ALSPAC. We will randomly select among the cohort participants 1000 individuals aged between 10 and 23 years for neuroimaging, genetic and epigenetic analyses. We will control for socio-cultural and environmental influences by investigating determinants of substance abuse in SCAMP, a UK cohort recruiting 6.500 11-13 year old adolescents, >1000 of which are of South Asian descent. Together these data will allow for the most comprehensive comparative analysis of brain development and behaviour across different social and cultural environments to date.
cVEDA is funded by an MRC-ICMR Newton Grant to Gunter Schumann and Vivek Benegal.
Testing and applying neurobehavioural symptom clusters from shared brain mechanisms [TANS] Human Brain Project
To reduce the burden of mental disorders it is a formidable aim to identify widely applicable disease markers based on neural processes that predict psychopathology and allow for targeted interventions. We have recently developed an innovative neurophysiological model that identifies symptom clusters defined by neurobiological mechanisms using sparse Canonical Correlation Analysis. We now propose a use-case for the Medical Informatics Platform (MIP) to adapt and test this model in data from clinical research and population-based studies that involve over 30.000 neuroimaging scans derived from a pool of over 200.000 individuals. Our investigation will result in stratification of clinical representations, which unlike traditional psychiatric classification systems (DSM/ICD), reflect underlying brain processes. This knowledge is essential for the development of unifying ontologies in the domain of brain diseases and identification of targets for therapeutic manipulation of core psychopathology. The project will address HBP Flagship Objectives by providing normative data, identifying mechanisms of normal brain function and generate a mechanistic model of brain disease that underlie psychopathology for further in-vivo, in-vitro and in-silico testing. Our vision is to expand and refine our project in order to contribute to a psychiatric classification based on quantifiable neurobiological phenotypes. Knowledge thus generated has the potential to transform patient care, as well as to inform human brain organization involving model systems that range from human and animal models to neurocomputational simulations.
MATRICS - The overarching goal of the project is to test the key hypothesis that different aggression phenotypes result from differential impairment of arousal mechanisms which in turn dysregulates three basic neural functions: regulation of control mechanisms of aggression, emotional value rating of others, and empathy and moral decision making. The expertise of the team encompasses the range of skills required to deliver a program of research that meets all of the call’s requirements and provides access to a number of unique animal models and already existing integrated DNA x MRI clinical and control cohorts. MATRICS builds on existing fruitful EU collaborations which maximize feasibility and successful output.
eMED - SysMedAlcoholism: Alcohol Addiction: A Systems-Oriented Approach with the main goal to identify genetic and neural determinants predicting development of addiction.
ERANID focuses on strengthening cross-border research (mainly in the EU) in various aspects of the illicit drugs problem, i.e. drug demand and drug supply issues, and in interventions and policies to tackle the problems. ERANID will make knowledge on these issues better available for the stakeholders. To this end, it cooperates with organisations as the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), and the Pompidou-group. ERANID will promote multidisciplinary research activities in the field of social sciences and humanities, and, if necessary beyond. Our aim is to improve understanding on the cause and nature of drug problems and how these develop in society, analyse trends and developments (e.g. patterns of consumption, drug markets).