Periodic Reporting for period 2 - FAMILY (Running in the FAMILY - Understanding and predicting the intergenerational transmission of mental illness)
Período documentado: 2024-04-01 hasta 2025-09-30
The intergenerational transmission of risk for mental illness in offspring of patients is insufficiently considered in clinical practice. Healthcare systems do not sufficiently utilise (and in most cases substantially neglect) family history of mental illness into diagnostics and care of offspring of parents with a mental health disorder. This may lead to delays in diagnosing young offspring and missing opportunities for protective actions and resilience strengthening. Currently, healthcare professionals are in need for tools or guidelines, or even a change in the system, to pay adequate consideration to a more family-based approach.
Research in family members has shown that the onset of mental illness is governed by a complex interplay between genetic factors and environmental factors. Biological mechanisms, like epigenetic processes and brain development, may explain some of the relationship between genetic and environmental factors, and how they ultimately materialise into mental disorders along the lifespan. Importantly, the increased familial risk of mental illness can be dampened by resilience factors, including supportive parenting style or social support, that themselves can be of genetic or environmental origin (or both).
Despite ample evidence that mental illness runs in families, how and when risk for mental illness is passed from parents to offspring is still poorly understood. Therefore, FAMILY aims 1) to advance our understanding of the aetiology of familial risk for and resilience to mental illness, thereby providing new targets for prevention and intervention studies and 2) to construct a prediction model to predict who is at the highest risk to develop mental health problems later in life, using environmental, clinical, behavioural information, and biological information of parents and offspring.
Individually predicting the risk for mental disorders in children of affected parents would radically change the clinical approach to mental illness. Critically, ethical and social consequences need careful attention and appraisal, such as the right not to know or the risk of stigma. Therefore, our third aim is to provide insights into social and ethical issues related to risk prediction to inform guidelines.
FAMILY set out to collect new neuroimaging and genetic data of offspring and their parents in familial high-risk cohorts.
In already available data from population and familial high-risk cohorts, the first causal hypotheses have been tested after careful quantification of relevant constructs, such as resilience or transmission load, leveraging genetic, epigenetic and neuroimaging information. To approach the complexity of the real world, FAMILY aims to combine genetic, neuroimaging, environmental and behavioural information of individuals in such a way that they together capture a richer representation than using just one modality or one level of abstraction alone.
FAMILY’s animal models further increase mechanistic understanding of the intergenerational transmission of risk for mental illness. We have established that both nature (genetic risk for a CAMK2A mutation, which is linked to neurodevelopmental problems) as well as nurture (rearing behaviour of the mother mouse) play a role in the behaviour of the offspring.
Finally, FAMILY aims to map social and ethical consequences of risk prediction models as a first step to prepare clinical practice for its future implementation. Preparatory work has been done by identifying key ethical and social issues related to the use of prediction tools for mental disorders in clinical practice through literature search, interviews with people with lived experience of mental illness, their family members and representatives of patient organisations and a survey to mental health care professionals.
The scientific work thus far, resulted in published manuscripts, as well as in several submitted manuscripts and manuscripts in preparation.
To support data sharing and pooling of data within the FAMILY consortium a research and technical infrastructure was put in place, including a data dictionary and legal framework.
- FAMILY will go far beyond this current state-of-the-art on risk prediction of symptoms and diagnoses by applying statistical tools that use biological information (genetics, epigenetics, and brain imaging) as well as by integrating information not only about risk but also about resilience factors, in parents and offspring, for a far more accurate prediction and a better understanding of mechanisms underlying intergenerational risk.
- Exploiting environmental and genetic mouse models to study the contribution of maternal behaviour and biological factors to the transmission of disease-like behaviour from parent to offspring is unique, innovative and original. Such direct causality assessment has not been done before in females and is made possible by the previously demonstrated transmission of environmentally induced disease-like behaviour from mother to offspring.
- FAMILY specifically takes a life course perspective, which is made possible by the wide age range and many repeated assessments of population and familial high-risk cohorts available to the consortium (ranging from birth to adulthood).
- FAMILY takes a systematic approach to engage key stakeholders to 1) comprehensively map social and ethical aspects of prediction of risk of mental illness through stakeholder dialogue, interviews and questionnaires and 2) increase awareness of the major impact of intergenerational transmission of risk on offspring via the FAMILY website and social media channels