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

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationBiological and Medical Data Analysis - 7th International Symposium, ISBMDA 2006, Proceedings
PublisherSpringer Verlag
Pages1-12
Number of pages12
ISBN (Print)3540680632, 9783540680635
DOIs
StatePublished - 2006
Event7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006 - Thessaloniki, Greece
Duration: Dec 7 2006Dec 8 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4345 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006
CountryGreece
CityThessaloniki
Period12/7/0612/8/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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