• Home
  • Publications
  • Distinct genetic liability profiles define clinically relevant patient strata across common diseases

Distinct genetic liability profiles define clinically relevant patient strata across common diseases


  • Trastulla L.,
  • Dolgalev G.,
  • Moser S.,
  • T. Jiménez-Barrón L.,
  • F. M. Andlauer T.,
  • Von Scheidt M.,
  • Schizophrenia Working Group Of The Psychiatric Genomics Consortium,
  • Budde M.,
  • Heilbronner U.,
  • Papiol S.,
  • Teumer A.,
  • Homuth G.,
  • Völzke H.,
  • Dörr M.,
  • Falkai P.,
  • G. Schulze T.,
  • Gagneur J.,
  • Iorio F.,
  • Müller-Myhsok B.,
  • J. Ziller  M.


Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.

  • Facebook
  • Twitter
  • LinkedIn
  • Email