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Journal Article

A genome-wide association study of the longitudinal course of executive functions


Kalman,  Janos L.
IMPRS Translational Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society;

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Wendel, B., Papiol, S., Andlauer, T. F. M., Zimmermann, J., Wiltfang, J., Spitzer, C., et al. (2021). A genome-wide association study of the longitudinal course of executive functions. TRANSLATIONAL PSYCHIATRY, 11(1): 386. doi:10.1038/s41398-021-01510-8.

Cite as: https://hdl.handle.net/21.11116/0000-0009-2DED-B
Executive functions are metacognitive capabilities that control and coordinate mental processes. In the transdiagnostic PsyCourse Study, comprising patients of the affective-to-psychotic spectrum and controls, we investigated the genetic basis of the time course of two core executive subfunctions: set-shifting (Trail Making Test, part B (TMT-B)) and updating (Verbal Digit Span backwards) in 1338 genotyped individuals. Time course was assessed with four measurement points, each 6 months apart. Compared to the initial assessment, executive performance improved across diagnostic groups. We performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with performance change over time by testing for SNP-by-time interactions using linear mixed models. We identified nine genome-wide significant SNPs for TMT-B in strong linkage disequilibrium with each other on chromosome 5. These were associated with decreased performance on the continuous TMT-B score across time. Variant rs150547358 had the lowest P value = 7.2x10(-10) with effect estimate beta=1.16 (95% c.i.: 1.11, 1.22). Implementing data of the FOR2107 consortium (1795 individuals), we replicated these findings for the SNP rs150547358 (P value=0.015), analyzing the difference of the two available measurement points two years apart. In the replication study, rs150547358 exhibited a similar effect estimate beta=0.85 (95% c.i.: 0.74, 0.97). Our study demonstrates that longitudinally measured phenotypes have the potential to unmask novel associations, adding time as a dimension to the effects of genomics.