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Review
. 2008 May;118(5):1590-605.
doi: 10.1172/JCI34772.

A HapMap harvest of insights into the genetics of common disease

Affiliations
Review

A HapMap harvest of insights into the genetics of common disease

Teri A Manolio et al. J Clin Invest. 2008 May.

Abstract

The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science.

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Figures

Figure 1
Figure 1. Genetic and environmental contributions to monogenic and complex disorders.
(A) Monogenic disease. A variant in a single gene is the primary determinant of a monogenic disease or trait, responsible for most of the disease risk or trait variation (dark blue sector), with possible minor contributions of modifier genes (yellow sectors) or environment (light blue sector). (B) Complex disease. Many variants of small effect (yellow sectors) contribute to disease risk or trait variation, along with many environmental factors (blue sector).
Figure 2
Figure 2. Breakdown of LD around a new SNP.
A mutation generating a novel SNP (red circle) occurs on an existing chromosome (dark blue) with multiple preexisting SNP alleles (dark blue circles) occurring in an ancestral haplotype that spans the entire chromosomal segment shown. After multiple meioses over many generations (arrows), the chromosomal segments flanking this variant will tend to be reshuffled by recombination, as shown by different colors. Over time, therefore, the segment containing the new variant and its surrounding ancestral SNP alleles becomes shorter and occurs on a variety of haplotypes associated with different flanking SNP alleles.
Figure 3
Figure 3. Tag SNPs can define common haplotypes.
Variable sites (SNPs) are shown by colored bars in this simplified example (adjacent SNPs are generally separated by longer distances). Complete independence of these 6 SNPs would predict the possibility of 26 or 64 different haplotypes (because n biallelic SNPs could generate 2n haplotypes), but in reality just 4 haplotypes comprise 90% of observed chromosomes, indicating that LD is present. To be specific, SNP1, SNP2, and SNP3 are strongly correlated, and SNP4, SNP5, and SNP6 are strongly correlated, so that any of SNP1–SNP3 (or SNP4–SNP6) could serve as tags for the other 2 SNPs in each group. Specific tags may be chosen for genotyping platforms because of stronger associations with additional SNPs in the region or technical ease of genotyping.
Figure 4
Figure 4. SNP-trait associations detected in GWA studies.
Associations significant at P < 9.9 × 10–7 are shown according to chromosomal location and involved or nearby gene, if any. Colored boxes indicate similar diseases or traits.

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