Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease
Version of Record online: 20 DEC 2002
Volume 190, Issue 1, pages 9–25, December 2002
How to Cite
Lazarus, R., Vercelli, D., Palmer, L. J., Klimecki, W. J., Silverman, E. K., Richter, B., Riva, A., Ramoni, M., Martinez, F. D., Weiss, S. T. and Kwiatkowski, D. J. (2002), Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease. Immunological Reviews, 190: 9–25. doi: 10.1034/j.1600-065X.2002.19002.x
- Issue online: 20 DEC 2002
- Version of Record online: 20 DEC 2002
Summary: Under selective pressure from infectious microorganisms, multicellular organisms have evolved immunological defense mechanisms, broadly categorized as innate or adaptive. Recent insights into the complex mechanisms of human innate immunity suggest that genetic variability in genes encoding its components may play a role in the development of asthma and related diseases. As part of a systematic assessment of genetic variability in innate immunity genes, we have thus far have examined 16 genes by resequencing 93 unrelated subjects from three ethnic samples (European American, African American and Hispanic American) and a sample of European American asthmatics. Approaches to discovering and understanding variation and the subsequent implementation of disease association studies are described and illustrated. Although highly conserved across a wide range of species, the innate immune genes we have sequenced demonstrate substantial interindividual variability predominantly in the form of single nucleotide polymorphisms (SNPs). Genetic variation in these genes may play a role in determining susceptibility to a range of common, chronic human diseases which have an inflammatory component. Differences in population history have produced distinctive patterns of SNP allele frequencies, linkage disequilibrium and haplotypes when ethnic groups are compared. These and other factors must be taken into account in the design and analysis of disease association studies.