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Genetic clustering on the hippocampal surface for genome-wide association studies.


ABSTRACT: Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

SUBMITTER: Hibar DP 

PROVIDER: S-EPMC4024454 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Genetic clustering on the hippocampal surface for genome-wide association studies.

Hibar Derrek P DP   Medland Sarah E SE   Stein Jason L JL   Kim Sungeun S   Shen Li L   Saykin Andrew J AJ   de Zubicaray Greig I GI   McMahon Katie L KL   Montgomery Grant W GW   Martin Nicholas G NG   Wright Margaret J MJ   Djurovic Srdjan S   Agartz Ingrid A IA   Andreassen Ole A OA   Thompson Paul M PM  

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention 20130101 Pt 2


Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy usi  ...[more]

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