1. Genetic clustering on the hippocampal surface for genome-wide association studies.
- Author
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Hibar DP, Medland SE, Stein JL, Kim S, Shen L, Saykin AJ, de Zubicaray GI, McMahon KL, Montgomery GW, Martin NG, Wright MJ, Djurovic S, Agartz IA, Andreassen OA, and Thompson PM
- Subjects
- Adult, Aged, Female, Genetic Predisposition to Disease genetics, Humans, Image Interpretation, Computer-Assisted methods, Male, Reproducibility of Results, Sensitivity and Specificity, Cognitive Dysfunction genetics, Cognitive Dysfunction pathology, Genome-Wide Association Study methods, Hippocampus pathology, Hippocampus physiopathology, Magnetic Resonance Imaging methods, Multigene Family genetics
- 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.
- Published
- 2013
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