B4611 - Running in the FAMILY - Understanding and predicting the intergenerational transmission of mental illness - 14/05/2024

B number: 
Principal applicant name: 
Alexander Neumann | Erasmus University Medical Center Rotterdam (Netherlands)
Charlotte Cecil, Ryan Muetzel, Fin van Uum, Raffael Kalisch, Greta Mikneviciute, Elena Isaevska, Nicole Creasy, Mina Shahisavandi, Mannan Luo
Title of project: 
Running in the FAMILY - Understanding and predicting the intergenerational transmission of mental illness
Proposal summary: 

A family history of mental illness is the most important known risk factor for the development of mental health problems. Up to 50% of children with a mentally-ill parent will develop a mental disorder in their life. In clinical practice, this intergenerational transmission of risk for mental illness is rarely taken into account, and in health care settings, family histories of mental illness are not adequately considered in diagnosis and care, leading to delays in diagnosis and missed time for protective measures and strengthening resilience. Furthermore, parents with mental illness are often unaware of the impact their condition can have on their children's well-being, are less able to reflect on their role and style as a parent, and rarely discuss this with health care professionals. This project aims to better understand the mechanisms of intergenerational transmission of mental illness. The ALSPAC data, together with data from other cohorts, will be used (i) to identify early risk and resilience factors, (ii) to predict who is likely to be diagnosed or develop symptoms of mental illness and (iii) to better define the role of genetics, epigenetics and brain metrics in the routes of transmission. This may lead to the development of new preventive strategies that can break the intergenerational cycle of mental illness and support the building of strength and resilience.

Impact of research: 
The results of this project can help researchers, healthcare professionals and policy makers to better understand how genetic, epigenetic, metabolomic and environmental risk and resilience factors interact to determine risk of mental illness over the life course. Greater awareness and knowledge about the transmission of risk from parent to offspring will support vulnerable families in taking an active role in managing their own health. Developing and implementing family-based risk prediction tools in clinical settings can lead to better prediction of future mental health, and it can facilitate the design of low-threshold, preventive actions by eliminating risk factors or strengthening resilience. Such evidence-based programs can thus empower vulnerable families and support mental health professionals in providing better care.
Date proposal received: 
Tuesday, 7 May, 2024
Date proposal approved: 
Tuesday, 14 May, 2024
Mental health - Psychology, Psychiatry, Cognition, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Developmental disorders - autism, Eating disorders - anorexia, bulimia, Mental health, GWAS, Medical imaging, Microarrays, Statistical methods, Development, Equipment - MRI, Epigenetics, Genetic epidemiology, Genetics, Parenting, Psychology - personality, Sex differences, Sleep, Statistical methods