HLA and HIV infection progression: application of the minimum description length principle to statistical genetics

  • Authors:

  • Peter T. Hraber;Bette T. Korber;Steven Wolinsky;Henry A. Erlich;Elizabeth A. Trachtenberg;Thomas B. Kepler

  • Affiliations:

  • Santa Fe Institute, Santa Fe, NM;Santa Fe Institute, Santa Fe, NM;Feinberg School of Medicine, Northwestern University, Chicago, IL;Roche Molecular Systems, Alameda, CA;Children's Hospital Oakland Research Institute, Oakland, CA;Department of Biostatistics and Bioinformatics, Duke University Medical Center, Duke University, Durham, NC

  • Venue:
  • ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
  • Year:
  • 2006

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Abstract

The minimum description length (MDL) principle was developed in the context of computational complexity and coding theory. It states that the best model to account for some data minimizes the sum of the lengths, in bits, of the descriptions of the model and the data as encoded via the model. The MDL principle gives a criterion for parameter selection, by using the description length as a test statistic. Class I HLA genes play a major role in the immune response to HIV, and are known to be associated with rates of progression to AIDS. However, these genes are extremely polymorphic, making it difficult to associate alleles with disease outcome, given statistical issues of multiple testing. Application of the MDL principle to immunogenetic data from a longitudinal cohort study (Chicago MACS) enables classification of alleles associated with plasma HIV RNA abundance, an indicator of infection progression. Variation in progression is strongly associated with HLA-B. Allele associations with viral levels support and extend previous studies. In particular, individuals without B58s supertype alleles average viral RNA levels 3.6 times greater than individuals with them. Mechanisms for these associations include variation in epitope specificity and selection that favors rare alleles.