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Correlation-based multivariate analysis of genetic influence on brain volume

Research output: Contribution to journalArticle

David R. Hardoon, Ulrich Ettinger, Janaina Mourao-Miranda, Elena Antonova, David Collier, Veena Kumari, Steven C. R. Williams, Michael Brammer

Original languageEnglish
Pages (from-to)281 - 286
Number of pages6
JournalNeuroscience Letters
Volume450
Issue number3
DOIs
Publication statusPublished - 6 Feb 2009

King's Authors

Abstract

Considerable research effort has focused on achieving a better understanding of the genetic correlates of individual differences in volumetric and morphological brain measures. The importance of these efforts is underlined by evidence Suggesting that brain changes in a number of neuropsychiatric disorders are at least partly genetic in origin. The Currently used methods to study these relationships are mostly based oil single-genotype univariate analysis techniques. These methods are limited as multiple genes are likely to interact with each other in their influences on brain Structure and function. In this paper we present a feasibility study where we show that by using kernel correlation analysis, with a new genotypes representation, it is possible to analyse the relative associations of several genetic polymorphisms with brain structure. The implementation of the method is demonstrated on genetic and structural magnetic resonance imaging (MRI) data acquired from a group) Of 16 healthy subjects by showing the multivariate genetic influence on grey and white matter. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

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