Published in

Springer Nature [academic journals on nature.com], Translational Psychiatry, 1(9), 2019

DOI: 10.1038/s41398-019-0547-x

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The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractCognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.