Running in the family – Understanding and predicting the intergenerational transmission of mental illness

FAMILY will put in place 6 empirical work packages (WPs3-8) to reach its objectives. This WP framework is characterised by strong interconnections and synergistic methodological approaches.

Genome, epigenome and brain:

Three work packages each focus on their own biological level, i.e. the genome (WP3), epigenome (WP4), and the brain (WP5). Information from these data domains may potentially act as predictors, mediators, or moderators of intergenerational transmission of risk.

Multimodal integration:

WP7 is dedicated to the integration of different data domains. Multilevel integration is not limited to the biological domains but will also include environmental or behavioural factors. Next to multilevel/multimodal integration, WP7 will develop multimodal normative prediction and causal pathway modelling approaches, thereby developing an individualised risk prediction model of mental health problems.

WPs3-5 and 7 will focus on the use of human cohort data, i.e. large population samples across different age ranges and unique cohorts of offspring with at least one parent with a severe mental illness.

Animal models:

To increase mechanistic understanding of the role of intergenerational transmission, WP6 will leverage two unique animal models; one where disease-like behaviour in the parent results from purely genetic risk, and one where maternal disease-like behaviour originates from postnatal severe stress. As in the human studies, effects on behaviour and biology in the offspring will be investigated.

Social and ethical consequences of prediction:

WP8 will utilise methods from the social sciences to map social and ethical consequences of risk prediction tools as a first step to prepare clinical practice on its future implementation.

In FAMILY, three main aims will be addressed:

Understanding:

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. We aim to identify the underlying environmental and (epi)genetic risk factors and mediating epigenetics and neural mechanisms (i.e. what are intermediate variables on the pathway from parental to offspring mental illness), and when these factors operate, e.g. during foetal development, early childhood, adolescence, and into adulthood. At the same time, we need to identify resilience factors that counteract an existing risk and elucidate their mechanisms of actions. Only then can we advance our understanding of the aetiology of mental illness and uncover new targets for the development of preventive strategies to break the intergenerational cycle of mental illness and to support strengths and resource building.

Predicting:

By utilizing the intergenerational transmission of risk of mental illness, reliable quantitative and qualitative metrics in parents and their offspring may be obtained, informative of the likelihood of offspring to develop mental illness. Such metrics should include clinical, behavioural, environmental, as well as biological factors. Thus, characteristics of parental illness, parental and offspring genetic, epigenetic, and neuroanatomical markers, but also parent-specific information, such as parental behaviour and life experiences, can contribute to the prediction of risk for mental illness in offspring. Predicting the risk for mental disorders in children of affected parents would radically change the clinical approach to mental illness. The shame and guilt associated with mental states and the resulting under-diagnostics would be diminished by the more systematic integration of the brain and its functions as an organ to take care of, just like heart and liver, leading to destigmatising on the long-term.

Societal impact:

Implementation of (family-based) risk prediction tools in health services needs fundamental changes in clinical practice and required thorough preparation of all relevant stakeholders, including policy makers. Critically, ethical and social consequences need careful attention and appraisal, such as the risk of self-fulfilling prophecies, the concept of neurodiversity, the right not to know, the risk of stigma, the use of artificial intelligence in risk prediction, and data sharing.

European Union's Horizon Europe Research and Innovation Program (FAMILY; Grant No. 101057529).

External collaborations:

• University College London (UCL), UK
• Stichting Radboud Universitair Medisch Centrum (RUMC), Netherlands
• Leibniz-Institut fur Resilienzforschung (LIR), Germany
• Universitat Zurich (UZH), Switzerland
• Latvijas Universitate (LU), Latvia
• Folkehelseinstituttet (NIPH), Norway
• Fundacio Clinic per a la Recerca Biomedica (FCRB) and Hospital Clinic De Barcelona, Spain
• Harvard Global Research and Support Services Inc. (HSPH), Spain
• Concentris Research Management Gmbh (Concentris), Germany
• Centre Hospitalier Universitaire Vaudois (CHUV), Switzerland
• Fundacion Para La Investigacion Biomedica Del Hospital Gregorio Maranon (FIBHGM), Spain
• Region Hovedstaden (RegionH), Denmark
• Università Della Svizzera Italiana (UDSI), Switzerland
• European Society for Child and Adolescent Psychiatry (ESCAP), Belgium
• Europese Federatie Van Familieverenigingen Van Psychiatrisch Zieke Personen Ivzw (EUFAMI), Belgium

Find here the Family-project website

van Houtum LAEM, Baaré WFC, Beckmann CF, Castro-Fornieles J, Cecil CAM, Dittrich J, Ebdrup BH, Fegert JM, Havdahl A, Hillegers MHJ, Kalisch R, Kushner SA, Mansuy IM, Mežinska S, Moreno C, Muetzel RL, Neumann A, Nordentoft M, Pingault JB, Preisig M, Raballo A, Saunders J, Sprooten E, Sugranyes G, Tiemeier H, van Woerden GM, Vandeleur CL, van Haren NEM. Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness. Eur Child Adolesc Psychiatry. 2024 Apr 13. doi: 10.1007/s00787-024-02423-9. Epub ahead of print. PMID: 38613677.

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  R.L. (Ryan) Muetzel, Phd

  Assistant Professor

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  Associate prof. C.A.M. (Charlotte) Cecil, PhD

  Scientific Researcher