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Genome-Wide Association of Bipolar Disorder Suggests an Enrichment of Replicable Associations in Regions near Genes
ISSN
1553-7390
Date Issued
2011
Author(s)
Smith, Erin N.
Koller, Daniel L.
Panganiban, Corrie
Szelinger, Szabolcs
Zhang, P.
Badner, Judith A.
Barrett, Thomas B.
Berrettini, Wade H.
Bloss, Cinnamon S.
Byerley, William
Coryell, William
Edenberg, Howard J.
Foroud, Tatiana
Gershon, Elliot S.
Greenwood, Tiffany A.
Guo, Yiran
Hipolito, Maria
Keating, Brendan J.
Lawson, William B.
Liu, Chunyu
Mahon, Pamela Belmonte
McInnis, Melvin G.
McMahon, Francis J.
McKinney, Rebecca
Murray, Sarah S.
Nievergelt, Caroline M.
Nurnberger, John I., Jr.
Nwulia, Evaristus A.
Potash, James B.
Rice, John
Scheftner, William A.
Shilling, Paul D.
Zandi, Peter P.
Zoellner, Sebastian
Craig, David W.
Schork, Nicholas J.
Kelsoe, John R.
DOI
10.1371/journal.pgen.1002134
Abstract
Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5 x 10(-7)). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (+/- 10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.
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