Periodic Reporting for period 1 - FAMILY (Running in the FAMILY - Understanding and predicting the intergenerational transmission of mental illness)
Reporting period: 2022-10-01 to 2024-03-31
A family history of severe mental illness (i.e. major depression, bipolar disorder or schizophrenia) is an important risk factor for developing mental health problems. Over 50% of children with a parent with severe mental illness will develop a mental disorder by early adulthood, demonstrating a tangible transfer of risk from affected parents to offspring, referred to as the intergenerational transmission of risk for mental illness.
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.
Predicting the risk for mental disorders in children of affected parents would radically change the clinical approach to mental illness. However, implementation of (family-based) risk prediction models in health services, once fully validated, requires fundamental changes in clinical practice and thorough preparation of all relevant stakeholders, including policymakers. 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.
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.
Predicting the risk for mental disorders in children of affected parents would radically change the clinical approach to mental illness. However, implementation of (family-based) risk prediction models in health services, once fully validated, requires fundamental changes in clinical practice and thorough preparation of all relevant stakeholders, including policymakers. 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.
During the first 18 months, FAMILY’s early career researchers have started their projects; they performed literature searches and generated ideas during interdisciplinary meetings and brainstorm sessions. Foundational work has been performed, resulting in new and innovative processing and analyses pipelines for various relevant statistical methods (e.g. trio-genetic modelling, polygenetic score and methylation profile score analyses, and multimodal data integration). Establishing such pipelines is essential and a prerequisite for expanding our knowledge on how and when intergenerational transmission of risk occurs. Also, new neuroimaging and genetic data of offspring and their parents was collected in the familial high-risk cohorts, offering the opportunity to test hypotheses in children and adolescents who have a high risk of developing mental illness. Moreover, the first testable causal hypotheses have been designed after careful quantification of relevant constructs, such as resilience. To further increase mechanistic understanding of the intergenerational transmission of risk for mental illness two unique animal models are now in place. Breeding has been performed, and for the environmentally-induced disorder-like behaviour in mothers, the disorder-like behaviour has been confirmed in mothers and offspring, and molecular analyses are ongoing. Finally, FAMILY utilised methods from the social sciences to map social and ethical consequences of risk prediction models as a first step to prepare clinical practice for its future implementation. A review of the scientific literature was performed, and key ethical and social issues related to the use of prediction tools for mental disorders in clinical practice were identified. This work and results from FAMILY’s first stakeholder dialogue event informed interview guidelines and a questionnaire for, respectively patients and their families and mental health care professionals, to learn about each stakeholders’ attitudes and views regarding prediction tools. Currently, interviews are being held and the questionnaire is being distributed, Europe-wide.
The scientific work thus far, resulted in published manuscripts on data integration methods, 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 infrastructure (including a data dictionary) was put in place.
The scientific work thus far, resulted in published manuscripts on data integration methods, 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 infrastructure (including a data dictionary) was put in place.
- Families are considered as a source of information to allow the identification of the risk of transmission of mental illness from affected parents to offspring. FAMILY applied statistical methods, which are specifically designed to use trio data (information from mother, father and offspring), and can distinguish genetic and environmental routes of risk transmission and identify underlying biological pathways.
- 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.
- 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.