Approved Research
Identification of genetic risk factors and endophenotypes underlying disease subtypes in major psychiatric disorders
Approved Research ID: 93847
Approval date: January 18th 2023
Lay summary
Aims: The proposed project aims to uncover the genetic factors underlying endophenotypes implicated in development, course and treatment response of patients suffering from major psychiatric diseases, and leverage them to define distinct patient subtypes.
Scientific rationale: Major psychiatric disorders are characterized by a high level of genetic, disease course and phenotypic heterogeneity. Endophenotypes such as cognition, neuroimaging or immune status have been shown to be valuable to resolve part of the tremendous heterogeneity in symptoms, disease trajectory or treatment response. Moreover, such endophenotypes have been proven critical in the identification of more homogeneous patient subtypes that are likely also characterized by partially distinct biological mechanisms contributing to the disease. In addition, most of these endophenotypes are themselves characterized by a high heritability, providing further support for the notion of a distinct genetic and biological basis of disease subtypes. Endophenotypes related to immune system function, cognitive function, brain structure and function, disease severity and comorbid diseases are of high relevance and exhibit distinct heritability patterns and genetic correlation, providing a basis for distinct biological and intermediate phenotype-related mechanisms that contribute to disease emergence and course in distinct patient groups. However, at present, these genetic risk factors and endophenotypes remain poorly defined and have not been jointly used to uncover relevant disease subtypes within individual psychiatric illnesses or trans-diagnostically.
Project duration: Maximum of 36 months.
Public health impact: Our findings will help improve our understanding of the development and course of psychiatric illness, identify treatment-relevant disease subtypes, as well as contribute to the design of better disease management strategies in a more personalized manner.