Matthew B McQueen, B Devlin, Stephen V Faraone, Vishwajit L Nimgaonkar, Pamela Sklar, Jordan W Smoller, Rami Abou Jamra, Margot Albus, Silviu-Alin Bacanu, Miron Baron, Thomas B Barrett, Wade Berrettini, Deborah Blacker, William Byerley, Sven Cichon, Willam Coryell, Nick Craddock, Mark J Daly, J Raymond Depaulo, Howard J Edenberg, Tatiana Foroud, Michael Gill, T Conrad Gilliam, Marian Hamshere, Ian Jones, Lisa Jones, Suh-Hang Juo, John R Kelsoe, David Lambert, Christoph Lange, Bernard Lerer, Jianjun Liu, Wolfgang Maier, James D Mackinnon, Melvin G McInnis, Francis J McMahon, Dennis L Murphy, Markus M Nothen, John I Nurnberger, Carlos N Pato, Michele T Pato, James B Potash, Peter Propping, Ann E Pulver, John P Rice, Marcella Rietschel, William Scheftner, Johannes Schumacher, Ricardo Segurado, Kristel Van Steen, Weiting Xie, Peter P Zandi, Nan M Laird

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is that combining the original genotype data provides benefits of increased power and control over sources of heterogeneity that outweigh the difficulty and potential pitfalls of the implementation. We conducted a combined analysis using the original genotype data from 11 BP genomewide linkage scans comprising 5,179 individuals from 1,067 families. Heterogeneity among studies was minimized in our analyses by using uniform methods of analysis and a common, standardized marker map and was assessed using novel methods developed for meta-analysis of genome scans. To date, this collaboration is the largest and most comprehensive analysis of linkage samples involving a psychiatric disorder. We demonstrate that combining original genome-scan data is a powerful approach for the elucidation of linkage regions underlying complex disease. Our results establish genomewide significant linkage to BP on chromosomes 6q and 8q, which provides solid information to guide future gene-finding efforts that rely on fine-mapping and association approaches.