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Detecting AIDS restriction genes: From candidate genes to genome-wide association discovery

  1. Author:
    Hutcheson, H. B.
    Lautenberger, J. A.
    Nelson, G. W.
    Pontius, J. U.
    Kessing, B. D.
    Winkler, C. A.
    Smith, M. W.
    Johnson, R.
    Stephens, R.
    Phair, J.
    Goedert, J. J.
    Donfield, S.
    O'Brien, S. J.
  2. Author Address

    Hutcheson, H. B.; Lautenberger, J. A.; O'Brien, S. J.] Natl Canc Inst, Lab Genom Div, Frederick, MD 21702 USA. [Nelson, G. W.; Pontius, J. U.; Kessing, B. D.; Winkler, C. A.; Smith, M. W.; Johnson, R.] NCI, SAIC Frederick Inc, Lab Genom Div Basic Res Program, Frederick, MD 21702 USA. [Stephens, R.] SAIC Frederick, Adv Biomed Comp Ctr, Frederick, MD 21702 USA. [Phair, J.] NW Univ Med Sch, Div Infect Dis, Chicago, IL 60611 USA. [Goedert, J. J.] Natl Canc Inst, Viral Epidemiol Branch, Rockville, MD 20852 USA. [Donfield, S.] Rho Inc, Chapel Hill, NC 27514 USA.
    1. Year: 2008
  1. Journal: Vaccine
    1. 26
    2. 24
    3. Pages: 2951-2965
  2. Type of Article: Proceedings Paper
  1. Abstract:

    The screening of common genetic polymorphisms among candidate genes for AIDS pathology in HIV exposed cohort populations has led to the description of 20 AIDS restriction genes (ARGs), variants that affect susceptibility to HIV infection or to AIDS progression. The combination of high-throughput genotyping platforms and the recent HapMap annotation of some 3 mithon human SNP variants has been developed for and applied to gene discovery in complex and mutti-factoriat diseases. Here, we explore novel computational approaches to ARG discovery which consider interacting anaLytical modeLs, various genetic influences, and SNP-haptotype/LD structure in AIDS cohort populations to determine if these ARGs could have been discovered using an unbiased genome-wide association approach. The procedures were evaluated by tracking the performance of haplotypes and SNPs within ARG regions to detect genetic association in the same AIDS cohort populations in which the ARGs were originally discovered. The methodology captures the signats of muttiple non-independent AIDS-genetic association tests of different disease stages and uses association signal strength (odds ratio or relative hazard), statistical significance (p-vatues), gene influence, internal reptication, and hapLotype structure together as a mutti-facetted approach to identifying important genetic associations within a deLuge of genotyping/test data. The complementary approaches perform rather well. and predict the detection of a variety of undiscovered ARGs that affect different stages of HIV/AIDS pathogenesis using genome-wide association anatyses. Pubtished by Etsevier Ltd.

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External Sources

  1. PMID: 18325640

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