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A high-density screen for linkage in multiple sclerosis
Authors:Sawcer Stephen,Ban Maria,Maranian Mel,Yeo Tai Wai,Compston Alastair,Kirby Andrew,Daly Mark J,De Jager Philip L,Walsh Emily,Lander Eric S,Rioux John D,Hafler David A,Ivinson Adrian,Rimmler Jacqueline,Gregory Simon G,Schmidt Silke,Pericak-Vance Margaret A,Akesson Eva,Hillert Jan,Datta Pameli,Oturai Annette,Ryder Lars P,Harbo Hanne F,Spurkland Anne,Myhr Kjell-Morten,Laaksonen Mikko,Booth David,Heard Robert,Stewart Graeme,Lincoln Robin,Barcellos Lisa F,Hauser Stephen L,Oksenberg Jorge R,Kenealy Shannon J,Haines Jonathan L  International Multiple Sclerosis Genetics Consortium
Affiliation:University of Cambridge, Department of Clinical Neuroscience, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 2QQ, United Kingdom. sjs1016@mole.bio.cam.ac.uk
Abstract:To provide a definitive linkage map for multiple sclerosis, we have genotyped the Illumina BeadArray linkage mapping panel (version 4) in a data set of 730 multiplex families of Northern European descent. After the application of stringent quality thresholds, data from 4,506 markers in 2,692 individuals were included in the analysis. Multipoint nonparametric linkage analysis revealed highly significant linkage in the major histocompatibility complex (MHC) on chromosome 6p21 (maximum LOD score [MLS] 11.66) and suggestive linkage on chromosomes 17q23 (MLS 2.45) and 5q33 (MLS 2.18). This set of markers achieved a mean information extraction of 79.3% across the genome, with a Mendelian inconsistency rate of only 0.002%. Stratification based on carriage of the multiple sclerosis–associated DRB1*1501 allele failed to identify any other region of linkage with genomewide significance. However, ordered-subset analysis suggested that there may be an additional locus on chromosome 19p13 that acts independent of the main MHC locus. These data illustrate the substantial increase in power that can be achieved with use of the latest tools emerging from the Human Genome Project and indicate that future attempts to systematically identify susceptibility genes for multiple sclerosis will have to involve large sample sizes and an association-based methodology.
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