A HapMap harvest of insights into the genetics of common disease.

By Teri Manolio, L. Brooks, F. S. Collins. Journal of Clinical Investigation, 2008

956 citations recorded by the source corpus.

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.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/2f3caf7a06c633408ab550636145684d05881f18

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Citations in the corpus

Genome-wide association studies in diverse populations (2010, background): “as having markedly increased the number of genotype–phenotype associations documented for a wide range of phenotype”
The Genetic Signatures of Noncoding RNAs (2009, neutral): “regions [104,105].”
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The PhenX Toolkit: Get the Most From Your Measures (2011, background): “Because of the rapid progress in genomic technology, investigators can now analyze hundreds of thousands of genetic polymorphisms (2, 3) against an array of disease phenotypes to identify associations.”
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Long intergenic non-coding RNAs – New links in cancer progression (2011, background): “coding portions of the genome, some of which may be transcribed (24).”
Data sharing in neuroimaging research (2012, background): “The GenBank and Hapmap archives have been essential for major scientiﬁc discovery (Manolio et al., 2008), and have led to new research disciplines aimed at integrating and modeling data repositories.”
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