Linkage disequilibrium mapping via cladistic analysis of single-nucleotide polymorphism haplotypes.

We present a novel approach to disease-gene mapping via cladistic analysis of single-nucleotide polymorphism (SNP) haplotypes obtained from large-scale, population-based association studies, applicable to whole-genome screens, candidate-gene studies, or fine-scale mapping. Clades of haplotypes are tested for association with disease, exploiting the expected similarity of chromosomes with recent shared ancestry in the region flanking the disease gene. The method is developed in a logistic-regression framework and can easily incorporate covariates such as environmental risk factors or additional unlinked loci to allow for population structure. To evaluate the power of this approach to detect disease-marker association, we have developed a simulation algorithm to generate high-density SNP data with short-range linkage disequilibrium based on empirical patterns of haplotype diversity. The results of the simulation study highlight substantial gains in power over single-locus tests for a wide range of disease models, despite overcorrection for multiple testing.

[1]  P. Deloukas,et al.  The impact of SNP density on fine-scale patterns of linkage disequilibrium. , 2004, Human molecular genetics.

[2]  Lon R. Cardon,et al.  The complex interplay among factors that influence allelic association , 2004, Nature Reviews Genetics.

[3]  Toshihiro Tanaka.  The International HapMap Project , 2003, Nature.

[4]  P. Marjoram,et al.  Fine-scale mapping of disease genes with multiple mutations via spatial clustering techniques. , 2003, American journal of human genetics.

[5]  Peter Donnelly,et al.  A comparison of bayesian methods for haplotype reconstruction from population genotype data. , 2003, American journal of human genetics.

[6]  John Molitor,et al.  Application of Bayesian spatial statistical methods to analysis of haplotypes effects and gene mapping , 2003, Genetic epidemiology.

[7]  S. Gabriel,et al.  The Structure of Haplotype Blocks in the Human Genome , 2002, Science.

[8]  D J Balding,et al.  Fine-scale mapping of disease loci via shattered coalescent modeling of genealogies. , 2002, American journal of human genetics.

[9]  M. Daly,et al.  High-resolution haplotype structure in the human genome , 2001, Nature Genetics.

[10]  D. Goldstein.  Islands of linkage disequilibrium , 2001, Nature Genetics.

[11]  Mourad Sahbatou,et al.  Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease , 2001, Nature.

[12]  P. Donnelly,et al.  A new statistical method for haplotype reconstruction from population data. , 2001, American journal of human genetics.

[13]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[14]  M. Daly,et al.  A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms , 2001, Nature.

[15]  J. Pritchard,et al.  Use of unlinked genetic markers to detect population stratification in association studies. , 1999, American journal of human genetics.

[16]  D. Easton,et al.  Apolipoprotein E Genetic Variation and Alzheimer’s Disease , 1999, Dementia and Geriatric Cognitive Disorders.

[17]  D. Cooper.  Variation in the Human Genome , 1996 .

[18]  N Risch,et al.  The Future of Genetic Studies of Complex Human Diseases , 1996, Science.

[19]  Dauid F. Percy.  Cluster Analysis (3rd Edition) , 1994 .

[20]  The eMERGE Clinical Annotation Working Group.  A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms , 2001 .

[21]  J. Bertranpetit,et al.  Genetic and geographical variability in cystic fibrosis: evolutionary considerations. , 1996, Ciba Foundation symposium.

[22]  B. Kerem.  Identification of the cystic fibrosis gene: genetic analysis , 1989 .

[23]  Sabine Landau,et al.  Cluster Analysis , 1974 .