Lancaster, T.M. and Ihssen, N. and Brindley, L.M. and Tansey, K.E. and Mantripragada, K. and O'Donovan, M.C. and Owen, M.J. and Linden, D.E.J. (2016) 'Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals.', Human brain mapping., 37 (2). pp. 491-500.
A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic-learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch–stay) and reflection upon choice outcome (reward–punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (PWHOLE-BRAIN-CORRECTED = 0.048) and the ventral striatum (PROI-CORRECTED = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies.
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|Publisher Web site:||http://dx.doi.org/10.1002/hbm.23044|
|Publisher statement:||© 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.|
|Date accepted:||19 October 2015|
|Date deposited:||17 March 2016|
|Date of first online publication:||28 October 2015|
|Date first made open access:||No date available|
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