Detecting Interacting Mutation Clusters in HIV-1 Drug Resistance

Yu Zhang

2013

Abstract

Understanding the genetic basis of HIV-1 drug resistance is essential for antiretroviral drug development. We analyzed drug resistant mutations in HIV-1 protease and reverse transcriptase under 18 drug treatments. The analysis is challenging because there is a large number of possible mutation combinations that may jointly affect drug resistance. The mutations are also strongly correlated, imposing inference difficulties such as multi-colinearity issues. We applied a novel Bayesian algorithm to the drug resistance data. Our method efficiently identified clusters of mutations in HIV-1 protease and reverse transcriptase that are strongly and directly associated with drug resistance. In addition to marginal associations, we detected strong interactions among mutations at distant protein locations. Most identified protein positions are cross-resistant to several drugs of the same types. The effects of interactions are mostly negative, suggesting a threshold mechanism for the genetics underlying HIV drug resistance. Our method is among the first to produce detailed structures of marginal and interactive associations in HIV-1 drug resistance studies, and is generally suitable for detecting high-order interactions in large-scale datasets with complex dependencies.

References

  1. Akaike H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19:716-723
  2. Beerenwinkel, N., Schmidt, B., Walter, H., Kaiser, R., Lengauer, T., Hoffmann, D., Korn, K., Selbig, J., 2002. Diversity and complexity of HIV-1 drug resistance: A bioinformatics approach to predicting phenotype from genotype. Proc Natl Acad Sci USA, 99:8271-8276.
  3. DiCiccio, T. J., Kass, R. E., Raftery, A., Wasserman, L., 1997. Computing Bayes factors by combining simulation and asymptotic approximations, J Am Stat Assoc, 92:902-915.
  4. Haq, O., Levy, R. M., Morozov, A. V., Andrec, M., 2009. Pairwise and higher-order correlations among drugresistance mutations in HIV-1 subtype B protease. BMC Bioinformatics, 10(Suppl 8):S10.
  5. Hinkley, T., Martins, J., Chappey, C., Haddad, M., Stawiski, E., Whitcomb, J. M., Petropoulos, C., and Bonhoeffer, S., 2011. A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase. Nat Genet. 43:487-490.
  6. Johnson, V. A., Brun-Vezinet, F., Clotet, B., Gunthard, H. F., Kuritzkes, D. R., Pillay, D., Schapiro, J. M., Richman, D. D., 2008. Update of the drug resistance mutations in HIV-1. Top HIV Med, 16:62-68.
  7. Liu, T. F., and Shafer, R. W., 2006. Web resources for HIV type 1 genotypic-resistance test interpretation. Clin Infect Dis, 42:1608-1618.
  8. Pitman, J., and Yor, M., 1997. The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator. Ann Prob. 25:855-900.
  9. Saigo, H., Uno, T., Tsuda, K., 2007. Mining complex genotypic features for predicting HIV-1 drug resistance. Bioinformatics, 23:2455-2462
  10. Shafer, R. W., 2002. Genotypic testing for Human Immunodeficiency Virus type 1 drug resistance. Clin Microbiol Rev, 15:247-277.
  11. Spinelli, S., Liu, Q. Z., Alzari, P. M., Hirel, P. H., Poljak, R. J., 1991. The three-dimensional structure of the aspartyl protease from the HIV-1 isolate BRU. Biochimie. 73:1391-1396.
  12. Ravela, J., Betts, B. J., Brun-Vezinet, F., Vandamme, A. M., Descamps, D., van Laethem, K., Smith, K., Schapiro, J. M., Winslow, D. L., Reid, C., Shafer, R. W., 2003. HIV-1 protease and reverse transcriptase mutation patterns responsible for discordances between genotypic drug resistance interpretation algorithms. J Acquir Immune Defic Syndr, 33:8-14.
  13. Rhee, S. Y., Taylor, J., Wadhera, G., Ben-Hur, A., Brutlag, D. L., Shafer, R. W., 2006. Genotypic predictors of human immunodeficiency virus type 1 drug resistance. Proc Natl Acad Sci USA. 46:17355- 17360.
  14. Rodgers, D. W., Gamblin, S. J., Harris, B. A., Ray, S., Culp, J. S., Hellmig, B., Woolf, D. J., Debouck, C., Harrison, S. C., 1995. The structure of unliganded reverse transcriptase from the human immunodeficiency virus type 1. Proc Natl Acad Sci USA. 92:1222-1226.
  15. Zhang, J., Hou, T. J., Wang, W., and Liu, J. S., 2010. Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance. Proc Natl Acad Sci USA, 107:1321-1326.
  16. Zhang, Y., 2011. A Novel Bayesian Graphical Model for Genome-Wide Multi-SNP Association Mapping. Genet Epi, 36:36-37.
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Paper Citation


in Harvard Style

Zhang Y. (2013). Detecting Interacting Mutation Clusters in HIV-1 Drug Resistance . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013) ISBN 978-989-8565-35-8, pages 34-43. DOI: 10.5220/0004238800340043


in Bibtex Style

@conference{bioinformatics13,
author={Yu Zhang},
title={Detecting Interacting Mutation Clusters in HIV-1 Drug Resistance},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)},
year={2013},
pages={34-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004238800340043},
isbn={978-989-8565-35-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2013)
TI - Detecting Interacting Mutation Clusters in HIV-1 Drug Resistance
SN - 978-989-8565-35-8
AU - Zhang Y.
PY - 2013
SP - 34
EP - 43
DO - 10.5220/0004238800340043