Project description
Prediction models for better supporting mental health in at-risk families
Mental illness often runs in families. Family context therefore plays a crucial role in quality of life for those potentially at risk. The EU-funded FAMILY project aims to provide novel prediction models that afford enhanced understanding of the mechanisms of intergenerational transmission of mental illness. These can then be used to improve life for the mentally ill. Project work will also consider the bioethical and social issues associated with intergenerational risk transmission and risk prediction. FAMILY research will focus on risk for mood and psychosis symptoms and diagnoses in particular, aiming to discover new targets for developing preventive strategies in vulnerable families and to support strengths and resource building.
Objective
Mental illness runs in families. The FAMILY consortium aims to improve the life of mentally-ill persons with novel prediction models that are based on better understanding the mechanisms of intergenerational transmission of mental illness. The objectives are to improve causal understanding and gain prediction power from the family context by the innovative combination of statistical modelling of genetically informed designs, causal inference, multimodal and multilevel normative prediction, and molecular mapping, brought by world-leading neuroscientific expertise of the consortium, and address key bioethical and social issues raised by the concept of intergenerational risk transmission and risk prediction. FAMILY will bring together the largest existing human (epi)genetic and neuroimaging datasets from both within-family population cohorts and familial high-risk offspring studies, as well as utilise innovative animal models to shed light on pathways underlying intergenerational risk transmission. FAMILY will focus specifically on risk for mood and psychosis symptoms and diagnoses. In-depth causal analyses of how and when risk for mental illness occurs will help identify early risk and resilience factors and predict who is likely to be diagnosed or develop symptoms of mental illness. Advanced insights can uncover new targets for the development of preventive strategies to break the intergenerational cycle of mental illness and to support strengths and resource building. An immediate benefit will be to open direct translational perspectives to mental health care professionals by providing new (family-based) risk prediction tools for the early identification of adults and children at risk and to deliver ethical guidelines to guide its implementation. This will accelerate preventive and treatment intervention in vulnerable families and help target resilience strategies to prevent the transition from health to disease despite high familial risk.
Fields of science
Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
3015 GD Rotterdam
Netherlands