Literature DB >> 23453289

Polygenic risk and white matter integrity in individuals at high risk of mood disorder.

Heather C Whalley1, Emma Sprooten, Suzanna Hackett, Lynsey Hall, Douglas H Blackwood, David C Glahn, Mark Bastin, Jeremy Hall, Stephen M Lawrie, Jessika E Sussmann, Andrew M McIntosh.   

Abstract

BACKGROUND: Bipolar disorder (BD) and major depressive disorder (MDD) are highly heritable and genetically overlapping conditions characterized by episodic elevation and/or depression of mood. Both demonstrate abnormalities in white matter integrity, measured with diffusion tensor magnetic resonance imaging, that are also heritable. However, it is unclear how these abnormalities relate to the underlying genetic architecture of each disorder. Genome-wide association studies have demonstrated a significant polygenic contribution to BD and MDD, where risk is attributed to the summation of many alleles of small effect. Determining the effects of an overall polygenic risk profile score on neuroimaging abnormalities might help to identify proxy measures of genetic susceptibility and thereby inform models of risk prediction.
METHODS: In the current study, we determined the extent to which common genetic variation underlying risk to mood disorders (BD and MDD) was related to fractional anisotropy, an index of white matter integrity. This was conducted in unaffected individuals at familial risk of mood disorder (n = 70) and comparison subjects (n = 62). Polygenic risk scores were calculated separately for BD and MDD on the basis of genome-wide association study data from the Psychiatric GWAS Consortia.
RESULTS: We report that a higher polygenic risk allele load for MDD was significantly associated with decreased white matter integrity across both groups in a large cluster, with a peak in the right-sided superior longitudinal fasciculus.
CONCLUSIONS: These findings suggest that the polygenic approach to examining brain imaging data might be a useful means of identifying traits linked to the genetic risk of mood disorders.
Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bipolar disorder; diffusion tensor MRI; major depressive disorder; mood disorder; polygenic; white matter

Mesh:

Year:  2013        PMID: 23453289      PMCID: PMC4185278          DOI: 10.1016/j.biopsych.2013.01.027

Source DB:  PubMed          Journal:  Biol Psychiatry        ISSN: 0006-3223            Impact factor:   13.382


  55 in total

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3.  ANK3 and CACNA1C--missing genetic link for bipolar disorder and major depressive disorder in two German case-control samples.

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4.  High dimensional endophenotype ranking in the search for major depression risk genes.

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5.  Genetic variants in the ErbB4 gene are associated with white matter integrity.

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6.  White matter integrity in individuals at high genetic risk of bipolar disorder.

Authors:  Emma Sprooten; Jessika E Sussmann; April Clugston; Anna Peel; James McKirdy; T William J Moorhead; Seonaid Anderson; Allen J Shand; Stephen Giles; Mark E Bastin; Jeremy Hall; Eve C Johnstone; Stephen M Lawrie; Andrew M McIntosh
Journal:  Biol Psychiatry       Date:  2011-03-23       Impact factor: 13.382

7.  White matter changes in healthy adolescents at familial risk for unipolar depression: a diffusion tensor imaging study.

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8.  Whiter matter abnormalities in medication-naive subjects with a single short-duration episode of major depressive disorder.

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Review 9.  Neurobiology of emotion perception II: Implications for major psychiatric disorders.

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10.  White matter abnormalities and illness severity in major depressive disorder.

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5.  Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia.

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6.  Polygenic Risk of Spasmodic Dysphonia is Associated With Vulnerable Sensorimotor Connectivity.

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7.  Age and Sex Effects on White Matter Tracts in Psychosis from Adolescence through Middle Adulthood.

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9.  Common genetic variants and gene expression associated with white matter microstructure in the human brain.

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Review 10.  The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data.

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