The optimal measure of linkage disequilibrium reduces error in association mapping of affection status
The optimal measure of linkage disequilibrium reduces error in association mapping of affection status
We have developed a simple yet powerful approach for disease gene association mapping by linkage disequilibrium (LD). This method is unique because it applies a model with evolutionary theory that incorporates a parameter for the location of the causal polymorphism. The method exploits LD maps, which assign a location in LD units (LDU) for each marker. This approach is based on single marker tests within a composite likelihood framework, which avoids the heavy Bonferroni correction through multiple testing. As a proof of principle, we tested an 890 kb region flanking the CYP2D6 gene associated with poor drug-metabolizing activity in order to refine the localization of a causal mutation. Previous LD mapping studies using single markers and haplotypes have identified a 390 kb significant region associated with the poor drug-metabolizing phenotype on chromosome 22. None of the 27 Single nucleotide polymorphisms was within the gene. Using a metric LDU map, the commonest functional polymorphism within the gene was located at 14.9 kb from its true location, surrounded within a 95% confidence interval of 172 kb. The kb map had a relative efficiency of 33% compared with the LDU map. Our findings indicate that the support interval and location error are smaller than any published results. Despite the low resolution and the strong LD in the region, our results provide evidence of the substantial utility of LDU maps for disease gene association mapping. These tests are robust to large numbers of markers and are applicable to haplotypes, diplotypes, whole-genome association or candidate region studies.
145-153
Maniatis, N.
af642fc2-cf37-422e-921a-1990a8d4bcfd
Morton, N.E.
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Gibson, J.
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Xu, C.-F.
e5032595-6fe7-41f5-b3e4-892ba7aac007
Hosking, L.K.
39f1f917-d7b6-4437-9ca7-be785eadf413
Collins, A.
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
1 January 2005
Maniatis, N.
af642fc2-cf37-422e-921a-1990a8d4bcfd
Morton, N.E.
c668e2be-074a-4a0a-a2ca-e8f51830ebb7
Gibson, J.
855033a6-38f3-4853-8f60-d7d4561226ae
Xu, C.-F.
e5032595-6fe7-41f5-b3e4-892ba7aac007
Hosking, L.K.
39f1f917-d7b6-4437-9ca7-be785eadf413
Collins, A.
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Maniatis, N., Morton, N.E., Gibson, J., Xu, C.-F., Hosking, L.K. and Collins, A.
(2005)
The optimal measure of linkage disequilibrium reduces error in association mapping of affection status.
Human Molecular Genetics, 14 (1), .
(doi:10.1093/hmg/ddi019).
Abstract
We have developed a simple yet powerful approach for disease gene association mapping by linkage disequilibrium (LD). This method is unique because it applies a model with evolutionary theory that incorporates a parameter for the location of the causal polymorphism. The method exploits LD maps, which assign a location in LD units (LDU) for each marker. This approach is based on single marker tests within a composite likelihood framework, which avoids the heavy Bonferroni correction through multiple testing. As a proof of principle, we tested an 890 kb region flanking the CYP2D6 gene associated with poor drug-metabolizing activity in order to refine the localization of a causal mutation. Previous LD mapping studies using single markers and haplotypes have identified a 390 kb significant region associated with the poor drug-metabolizing phenotype on chromosome 22. None of the 27 Single nucleotide polymorphisms was within the gene. Using a metric LDU map, the commonest functional polymorphism within the gene was located at 14.9 kb from its true location, surrounded within a 95% confidence interval of 172 kb. The kb map had a relative efficiency of 33% compared with the LDU map. Our findings indicate that the support interval and location error are smaller than any published results. Despite the low resolution and the strong LD in the region, our results provide evidence of the substantial utility of LDU maps for disease gene association mapping. These tests are robust to large numbers of markers and are applicable to haplotypes, diplotypes, whole-genome association or candidate region studies.
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Published date: 1 January 2005
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Local EPrints ID: 24853
URI: http://eprints.soton.ac.uk/id/eprint/24853
PURE UUID: c348cc9f-1e76-46d8-aba9-c9a1c940b3c5
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Date deposited: 03 Apr 2006
Last modified: 16 Mar 2024 03:33
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Author:
N. Maniatis
Author:
N.E. Morton
Author:
C.-F. Xu
Author:
L.K. Hosking
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