@article{e4836055d8d9457f8290e38602f57ba7,
title = "Cortical Thickness Is Influenced by Regionally Specific Genetic Factors",
abstract = "Background: Although global brain structure is highly heritable, there is still variability in the magnitude of genetic influences on the size of specific regions. Yet, little is known about the patterning of those genetic influences, i.e., whether the same genes influence structure throughout the brain or whether there are regionally specific sets of genes. Methods: We mapped the heritability of cortical thickness throughout the brain using three-dimensional structural magnetic resonance imaging in 404 middle-aged male twins. To assess the amount of genetic overlap between regions, we then mapped genetic correlations between three selected seed points and all other points comprising the continuous cortical surface. Results: There was considerable regional variability in the magnitude of genetic influences on cortical thickness. The primary visual (V1) seed point had strong genetic correlations with posterior sensory and motor areas. The anterior temporal seed point had strong genetic correlations with anterior frontal regions but not with V1. The middle frontal seed point had strong genetic correlations with inferior parietal regions. Conclusions: These results provide strong evidence of regionally specific patterns rather than a single, global genetic factor. The patterns are largely consistent with a division between primary and association cortex, as well as broadly defined patterns of brain gene expression, neuroanatomical connectivity, and brain maturation trajectories, but no single explanation appears to be sufficient. The patterns do not conform to traditionally defined brain structure boundaries. This approach can serve as a step toward identifying novel phenotypes for genetic association studies of psychiatric disorders and normal and pathological cognitive aging.",
keywords = "Cortical thickness, MRI, endophenotypes, genetic correlation, heritability, imaging genetics, twins",
author = "Rimol, {Lars M.} and Panizzon, {Matthew S.} and Christine Fennema-Notestine and Eyler, {Lisa T.} and Bruce Fischl and Franz, {Carol E.} and Hagler, {Donald J.} and Lyons, {Michael J.} and Neale, {Michael C.} and Jennifer Pacheco and Perry, {Michele E.} and Schmitt, {J. Eric} and Grant, {Michael D.} and Seidman, {Larry J.} and Thermenos, {Heidi W.} and Tsuang, {Ming T.} and Eisen, {Seth A.} and Kremen, {William S.} and Dale, {Anders M.}",
note = "Funding Information: The results suggest that global brain measures or subregions based on traditional sulcal-based parcellation units may be of limited utility for candidate or genome-wide association studies because different sets of genes influence different subregions. The genetic correlation patterns partially parallel primary versus association divisions of cortex type, anatomical connectivity, the developmental trajectory of early brain maturation, and gene expression patterns found in animal studies. However, none of these provides an entirely adequate explanation. Rather, the observed patterns appear to reflect these processes—and perhaps others—in combination. Because brain gene expression data cannot easily be collected in adult humans, the twin method provides a valuable alternative approach to studying genetic influences. The information gleaned may lead to more optimal phenotypes for imaging genetic or other genetic association studies. Traditional ROI-based phenotypes may be considered analogous to candidate gene studies in that they are typically hypothesis-driven. By contrast, our seed point approach is more similar to the genome-wide association study in that no preconceived notion of what constitutes a homogenous region is required and results may emerge that would not be expected a priori. Genetic correlation maps also complement these approaches by providing information about the aggregate patterns of genetic influences on brain development. The three genetic correlation maps in this article serve as heuristic examples and are not intended to represent an exhaustive assessment of the patterns of genetic influences on cortical thickness. Nevertheless, this approach appears to be promising. It may generate novel parcellation schemes with novel phenotypes that may be better suited than more traditional brain structure phenotypes for use in imaging genetic studies of psychiatric and neurological disorders or normal and pathological cognitive and brain aging. Funded by National Institute on Aging AG022381 , AG018386 , AG018384 , AG022982 . The US Department of Veterans Affairs has provided financial support for the development and maintenance of the Vietnam Era Twin (VET) Registry. Numerous organizations have provided invaluable assistance in the conduct of this study, including Department of Defense; National Personnel Records Center, National Archives and Records Administration; Internal Revenue Service; National Opinion Research Center; National Research Council, National Academy of Sciences; and the Institute for Survey Research, Temple University. Most importantly, we gratefully acknowledge the continued cooperation and participation of the members of the VET Registry and their families. Without their contribution, this research would not have been possible. Anders M. Dale is a founder and holds equity in CorTechs Laboratories, Inc., and also serves on the Scientific Advisory Board. The terms of this arrangement have been reviewed and approved by the University of California, San Diego, in accordance with its conflict of interest policies. All other authors report no biomedical financial interests or potential conflicts of interest. ",
year = "2010",
month = mar,
day = "1",
doi = "10.1016/j.biopsych.2009.09.032",
language = "English",
volume = "67",
pages = "493--499",
journal = "Biological Psychiatry",
issn = "0006-3223",
number = "5",
}