Andrew McIntosh (Chair)
Andrew McIntosh is Professor of Biological Psychiatry and Director Designate of the Centre for Cognitive Ageing and Cognitive Epidemiology at the University of Edinburgh.
He is the Chair of the MQ Data Science Group, leads the Generation Scotland Expert Working Group for Psychiatric Disorders and is PI on the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’.
His main interests lie in using genomics and data sciences to develop better models of cognition and mental health, thereby identifying their mechanisms and new treatment targets.
David is a professor of Psychiatric epidemiology at UCL. His main interests are the interface between physical and mental health, schizophrenia, bipolar disorder and depression in working age adults.
He trained at UCL, Cambridge and LSHTM. He has led many mental health studies using UK primary care databases and is interested in methodological approaches to routine data, pharmaco-epidemiology and social determinants of mental health.
He leads the CRIS database project at Camden and Islington NHS Foundation Trust, using secondary care mental health records and he has published numerous longitudinal studies using national and international cohorts.
He has a particular interest in academic training and he works as a consultant psychiatrist in Central London.
Rob Stewart is an Old Age Psychiatrist and Epidemiologist, and has led the Clinical Record Interactive Search (CRIS) initiative since its development in 2008 at the South London and Maudsley NHS Foundation Trust.
CRIS is a novel informatics resource which renders the full electronic mental health record amenable for research use within a robust governance framework. CRIS currently contains the de-identified records of over 250,000 service users and has supported a wide range of research.
Particularly important post-implementation developments have included a number of external data linkages, a growing suite of natural language processing applications to extract information from text fields, and deployment of CRIS at four other Mental Health Trusts.
Christina has over 35 year experience as a clinician in psychiatric inpatient care and started with longitudinal case-control studies in schizophrenia. The focus of her research has mainly been early origins of psychological and mental disorders, testing the association between pre- and perinatal effects with development of psychiatric disorders (schizophrenia, affective psychosis, reactive psychosis, post-partum psychosis, anorexia nervosa, ADHD and autism) and high-risk paradigms with children at high risk for schizophrenia and bipolar disorder.
In samples of twins, siblings, half-siblings, family pairs and high-risk offspring she has studied fetal environmental hazards, maternal life style/social disadvantage, paternal age effects and genetic liability using designs that permits simultaneously evaluation of maternal and paternal genetic and environmental influences.
Over the last eight years she has been responsible for DNA collection of 5,500 patients with schizophrenia, 5,000 bipolar patients, 1300 cases with infantile autism and their parents and grandparents, 380 schizophrenia and bipolar twin pairs and 7,500 healthy controls on a population basis. More recent initiative includes collaboration with KI basic lab facilities in Huddinge to test hypothesis on aberrant cell function in schizophrenia; long-term effects of psychological trauma and genetic risk factors for post-traumatic stress disorder.
Her deep knowledge of the Swedish National Registers has been valuable in establishing epidemiological psychiatry as one of the basic sciences to support molecular studies in psychiatry.
Dermot is clinical senior lecturer at the Centre for Public Health, at Queen’s University Belfast, Operations Director for the Northern Ireland ageing cohort (NICOLA) and Director of the Administrative Data Research Centre for Northern Ireland (ADRC-NI). Dermot has been undertaking public health research for the last 20 years and is increasingly utilising a wide array of routine administrative data to understand the factors and evaluate policies that influence our health and especially our mental health.