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A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains

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Siri Ranlund, Stella Calafato, Johan H. Thygesen, Kuang Lin, Wiepke Cahn, Benedicto Crespo-Facorro, Sonja M.C. de Zwarte, Álvaro Díez, Marta Di Forti, Conrad Iyegbe, Assen Jablensky, Rebecca Jones, Mei Hua Hall, Rene Kahn, Luba Kalaydjieva, Eugenia Kravariti, Colm Mcdonald, Andrew M. Mcintosh, Andrew Mcquillin, Marco Picchioni & 13 others Diana P. Prata, Dan Rujescu, Katja Schulze, Madiha Shaikh, Timothea Toulopoulou, Neeltje van Haren, Jim van Os, Evangelos Vassos, Muriel Walshe, Cathryn Lewis, Robin M. Murray, John Powell, Elvira Bramon

Original languageEnglish
Pages (from-to)21-34
JournalAmerican Journal of Medical Genetics. Part B: Neuropsychiatric Genetics
Volume177
Issue number1
Early online date29 Aug 2017
DOIs
StateE-pub ahead of print - 29 Aug 2017

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Abstract

This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N=515), lateral ventricular volume (N=798), and the cognitive measures block design (N=3,089), digit span (N=1,437), and the Ray Auditory Verbal Learning Task (N=2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p=0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p=0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p=0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.

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