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Proc Natl Acad Sci U S A. 2015 Feb 24;112(8):2479-84. doi: 10.1073/pnas.1415603112. Epub 2015 Feb 9.

Massively expedited genome-wide heritability analysis (MEGHA).

Author information

1
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129; Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138; tge1@mgh.harvard.edu jsmoller@hms.harvard.edu.
2
Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry CV4 7AL, United Kingdom;
3
Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138;
4
Department of Psychology, Yale University, New Haven, CT 06520;
5
Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114;
6
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129; Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114; Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138; and.
7
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139.
8
Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138; tge1@mgh.harvard.edu jsmoller@hms.harvard.edu.

Abstract

The discovery and prioritization of heritable phenotypes is a computational challenge in a variety of settings, including neuroimaging genetics and analyses of the vast phenotypic repositories in electronic health record systems and population-based biobanks. Classical estimates of heritability require twin or pedigree data, which can be costly and difficult to acquire. Genome-wide complex trait analysis is an alternative tool to compute heritability estimates from unrelated individuals, using genome-wide data that are increasingly ubiquitous, but is computationally demanding and becomes difficult to apply in evaluating very large numbers of phenotypes. Here we present a fast and accurate statistical method for high-dimensional heritability analysis using genome-wide SNP data from unrelated individuals, termed massively expedited genome-wide heritability analysis (MEGHA) and accompanying nonparametric sampling techniques that enable flexible inferences for arbitrary statistics of interest. MEGHA produces estimates and significance measures of heritability with several orders of magnitude less computational time than existing methods, making heritability-based prioritization of millions of phenotypes based on data from unrelated individuals tractable for the first time to our knowledge. As a demonstration of application, we conducted heritability analyses on global and local morphometric measurements derived from brain structural MRI scans, using genome-wide SNP data from 1,320 unrelated young healthy adults of non-Hispanic European ancestry. We also computed surface maps of heritability for cortical thickness measures and empirically localized cortical regions where thickness measures were significantly heritable. Our analyses demonstrate the unique capability of MEGHA for large-scale heritability-based screening and high-dimensional heritability profile construction.

KEYWORDS:

endophenotype; genome-wide complex trait analysis; heritability; imaging genetics; phenomics

PMID:
25675487
PMCID:
PMC4345618
DOI:
10.1073/pnas.1415603112
[Indexed for MEDLINE]
Free PMC Article

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