A method to exploit the structure of genetic ancestry space to enhance case-control studies

Bodea, Corneliu A., Neale, Benjamin M., Ripke, Stephan, Daly, Mark J., Devlin, Bernie, Roeder, Kathryn, The International IBD Genetics Consortium and Brown, Matthew A. (2016) A method to exploit the structure of genetic ancestry space to enhance case-control studies. American Journal of Human Genetics, 98 5: 857-868. doi:10.1016/j.ajhg.2016.02.025

Author Bodea, Corneliu A.
Neale, Benjamin M.
Ripke, Stephan
Daly, Mark J.
Devlin, Bernie
Roeder, Kathryn
The International IBD Genetics Consortium
Brown, Matthew A.
Title A method to exploit the structure of genetic ancestry space to enhance case-control studies
Journal name American Journal of Human Genetics   Check publisher's open access policy
ISSN 1537-6605
Publication date 2016-05-05
Year available 2016
Sub-type Article (original research)
DOI 10.1016/j.ajhg.2016.02.025
Open Access Status Not Open Access
Volume 98
Issue 5
Start page 857
End page 868
Total pages 12
Place of publication Cambridge, United States
Publisher Cell Press
Language eng
Formatted abstract
One goal of human genetics is to understand the genetic basis of disease, a challenge for diseases of complex inheritance because risk alleles are few relative to the vast set of benign variants. Risk variants are often sought by association studies in which allele frequencies in case subjects are contrasted with those from population-based samples used as control subjects. In an ideal world we would know population-level allele frequencies, releasing researchers to focus on case subjects. We argue this ideal is possible, at least theoretically, and we outline a path to achieving it in reality. If such a resource were to exist, it would yield ample savings and would facilitate the effective use of data repositories by removing administrative and technical barriers. We call this concept the Universal Control Repository Network (UNICORN), a means to perform association analyses without necessitating direct access to individual-level control data. Our approach to UNICORN uses existing genetic resources and various statistical tools to analyze these data, including hierarchical clustering with spectral analysis of ancestry; and empirical Bayesian analysis along with Gaussian spatial processes to estimate ancestry-specific allele frequencies. We demonstrate our approach using tens of thousands of control subjects from studies of Crohn disease, showing how it controls false positives, provides power similar to that achieved when all control data are directly accessible, and enhances power when control data are limiting or even imperfectly matched ancestrally. These results highlight how UNICORN can enable reliable, powerful, and convenient genetic association analyses without access to the individual-level data.
Keyword Genetics(clinical)
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
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UQ Diamantina Institute Publications
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