UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

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

Ranlund, S; Calafato, S; Thygesen, JH; Lin, K; Cahn, W; Crespo-Facorro, B; de Zwarte, SMC; ... Bramon, E; + view all (2017) A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics , 177 (1) pp. 21-34. 10.1002/ajmg.b.32581. Green open access

[thumbnail of Bramon_ajmgb32581.pdf]
Preview
Text
Bramon_ajmgb32581.pdf - Published Version

Download (786kB) | Preview

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.

Type: Article
Title: A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/ajmg.b.32581
Publisher version: http://doi.org/10.1002/ajmg.b.32581
Language: English
Additional information: © 2017 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 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.
Keywords: EEG, bipolar disorder, cognition, schizophrenia, single nucleotide polymorphism (SNP)
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
URI: https://discovery.ucl.ac.uk/id/eprint/1572385
Downloads since deposit
100Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item