Vol 437 27 October 2005 doi 10 1038 nature04226 ARTICLES A haplotype map of the human genome The International HapMap Consortium Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease Here we report a public database of common variation in the human genome more than one million single nucleotide polymorphisms SNPs for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations including ten 500 kilobase regions in which essentially all information about common DNA variation has been extracted These data document the generality of recombination hotspots a block like structure of linkage disequilibrium and low haplotype diversity leading to substantial correlations of SNPs with many of their neighbours We show how the HapMap resource can guide the design and analysis of genetic association studies shed light on structural variation and recombination and identify loci that may have been subject to natural selection during human evolution Despite the ever accelerating pace of biomedical research the root causes of common human diseases remain largely unknown preventative measures are generally inadequate and available treatments are seldom curative Family history is one of the strongest risk factors for nearly all diseases including cardiovascular disease cancer diabetes autoimmunity psychiatric illnesses and many others providing the tantalizing but elusive clue that inherited genetic variation has an important role in the pathogenesis of disease Identifying the causal genes and variants would represent an important step in the path towards improved prevention diagnosis and treatment of disease More than a thousand genes for rare highly heritable mendelian disorders have been identified in which variation in a single gene is both necessary and sufficient to cause disease Common disorders in contrast have proven much more challenging to study as they are thought to be due to the combined effect of many different susceptibility DNA variants interacting with environmental factors Studies of common diseases have fallen into two broad categories family based linkage studies across the entire genome and population based association studies of individual candidate genes Although there have been notable successes progress has been slow due to the inherent limitations of the methods linkage analysis has low power except when a single locus explains a substantial fraction of disease and association studies of one or a few candidate genes examine only a small fraction of the universe of sequence variation in each patient A comprehensive search for genetic influences on disease would involve examining all genetic differences in a large number of affected individuals and controls It may eventually become possible to accomplish this by complete genome resequencing In the meantime it is increasingly practical to systematically test common genetic variants for their role in disease such variants explain much of the genetic diversity in our species a consequence of the historically small size and shared ancestry of the human population Recent experience bears out the hypothesis that common variants have an important role in disease with a partial list of validated examples including HLA autoimmunity and infection 1 APOE4 Alzheimer s disease lipids 2 Factor VLeiden deep vein thrombosis 3 PPARG encoding PPARg type 2 diabetes 4 5 KCNJ11 type 2 diabetes 6 PTPN22 rheumatoid arthritis and type 1 diabetes 7 8 insulin type 1 diabetes 9 CTLA4 autoimmune thyroid disease type 1 diabetes 10 NOD2 inflammatory bowel disease 11 12 complement factor H age related macular degeneration 13 15 and RET Hirschsprung disease 16 17 among many others Systematic studies of common genetic variants are facilitated by the fact that individuals who carry a particular SNP allele at one site often predictably carry specific alleles at other nearby variant sites This correlation is known as linkage disequilibrium LD a particular combination of alleles along a chromosome is termed a haplotype LD exists because of the shared ancestry of contemporary chromosomes When a new causal variant arises through mutation whether a single nucleotide change insertion deletion or structural alteration it is initially tethered to a unique chromosome on which it occurred marked by a distinct combination of genetic variants Recombination and mutation subsequently act to erode this association but do so slowly each occurring at an average rate of about 1028 per base pair bp per generation as compared to the number of generations typically 104 to 105 since the mutational event The correlations between causal mutations and the haplotypes on which they arose have long served as a tool for human genetic research first finding association to a haplotype and then subsequently identifying the causal mutation s that it carries This was pioneered in studies of the HLA region extended to identify causal genes for mendelian diseases for example cystic fibrosis18 and diastrophic dysplasia19 and most recently for complex disorders such as age related macular degeneration13 15 Early information documented the existence of LD in the human genome20 21 however these studies were limited for technical reasons to a small number of regions with incomplete data and general patterns were challenging to discern With the sequencing of the human genome and development of high throughput genomic methods it became clear that the human genome generally displays more LD22 than under simple population genetic models23 and that LD is more varied across regions and more segmentally structured24 30 than had previously been supposed These observations indicated that LD based methods would generally have great value because nearby SNPs were typically correlated with many of their neighbours and also that LD relationships would Lists of participants and affiliations appear at the end of the paper 2005 Nature Publishing Group 1299 ARTICLES NATURE Vol 437 27 October 2005 Table 1 Genotyping centres Centre RIKEN Wellcome Trust Sanger Institute McGill University and Ge nome Que bec Innovation Centre Chinese HapMap Consortium Illumina Broad Institute of Harvard and MIT Baylor College of Medicine with ParAllele BioScience University of California San Francisco with Washington University in St Louis Perlegen Sciences Chromosomes Technology 5 11 14 15 16 17 19 1 6 10 13 20 2 4p 3 8p 21 8q 9 18q 22 X 4q 7q 18p Y