SA50 - CHARACTERISING COGNITIVE ENDOPHENOTYPES RELATED TO NEUROPSYCHIATRIC DISEASES

• Published in: European neuropsychopharmacology Vol. 29; pp. S849 - S850
• Main Authors: Milnik, Annette, Egli, Tobias, Auschra, Bianca, Hartmann, Francina, Spalek, Klara, Loos, Eva, de Quervain, Dominique J.F., Papassotiropoulos, Andreas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2019
• ISSN: 0924-977X; 1873-7862
• DOI: 10.1016/j.euroneuro.2017.08.122

Deep phenotyping aims at measuring large numbers of phenotypes per subject, which enables us to describe more comprehensively the subjects’ physical or cognitive state; the increased information-depth allows us to gain insight in the underlying neurophysiological and neuropsychological relationships. The concept of endophenotypes is an important link between phenotyping based on diseases and phenotyping based on healthy subjects, especially in the field of neuropsychiatric diseases. The cognitive domains episodic memory, working memory and attention are examples for endophenotypes that can be assessed in a deep-phenotyping approach; all these domains are heritable traits that are affected in neuropsychiatric disorders, such as Schizophrenia, Depression, or Posttraumatic stress disorder. These domains are based on shared but also on domain-specific neurophysiological and neuropsychological mechanisms and can be measured with a variety of different tasks. Here, we conjointly analysed data of five different studies investigating cognitive performance measurements in healthy young adults from the general population. Importantly, each of the included studies used a varying set of tasks from different domains, which hampers the usage of common multivariate approaches, like e.g. factor analysis. Instead, we applied a multitrait-multimethod approach that allowed us to successfully integrate the different datasets in one analysis. Our results illustrate a continuous phenotypic classification ranging from tasks comprising more attention-related processes on one hand to tasks comprising more episodic memory-related processes on the other hand. In summary, by applying a multitrait-multimethod approach to a heterogeneous database, we can visualize the putative underlying neurophysiological and neuropsychological mechanisms of cognitive tasks. These tasks can further be used as endophenotypes for neuropsychiatric diseases.