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resistance and therapy effectiveness should increase the accuracy of the relevant prediction procedures and help further our understanding of how the viral phenotype develops.

Finally, though not included in our present analysis, host factors, including a patient’s immunotype, also play a role in disease development and the effectiveness of drug therapy. For instance, it is under debate whether the immune system initially suppresses the enrichment of preexisting X4-viruses in the viral quasi-species. If this is the case, solely detecting X4 minorities need not be clinically significant; such detection does not necessarily predict the breakthrough of the viral variants, as long as the immune system is intact. Indeed, we and others have observed that the risk of X4-virus emerging rises with decreasing immune-cell count, reflecting the decreased intensity of the patient’s immune response. Such observations strongly encourage construction of a comprehensive model that includes information on all three players— pathogen, drug, and host.

Acknowledgments

The work reported here is the result of extensive interdisciplinary collaboration. We thank all involved scientists, past and present, especially the computational biologists Niko Beerenwinkel and Tobias Sing, the Arevir consortium, especially Eugen Schülter, Martin Däumer, and Hauke Walter, and the Euresist consortium, especially, Francesca Incardona, Maurizio Zazzi, and Anders Sönnerborg. The work has been partially funded by Deutsche Forschungsgemeinschaft, grant Ho 1582/1-3, KA 1569/1-3 (Arevir) and EU grants LSHG-CT-2003-503265 ( BioSa-piens) and IST-2004-027173 (EuResist) and is being partially funded by BMBF grant 0315480 C (HIV Cell Entry), BMG grant 310/4476 (RESINA), and EU grant HEALTH-F3-2009-223131 (CHAIN).

 

References

1. Altmann, A. et al. Predicting the response to combination antiretroviral therapy: retrospective validation of geno2pheno-ThEo on a large clinical database. Journal of Infectious Diseases 199, 7 (Apr. 2009), 999–1006.

2. Altmann, A. et al. Improved prediction of response to antiretroviral combination therapy using the genetic barrier to drug resistance. Antiviral Therapy 12, 2 (2007), 169–178.

3. beerenwinkel, n. et al. Learning multiple
evolutionary pathways from cross-sectional data.
Journal of Computational Biology 12, 6 (July/Aug.
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Thomas Lengauer ( [e-mail]) is Director of the Department of Computational biology and Applied Algorithmics at the Max Planck Institute for Informatics, saarbrücken, Germany.

André Altmann ( [e-mail]) is a staff scientist in the Department of Computational biology and Applied Algorithmics at the Max Planck Institute for Informatics, saarbrücken, Germany.

Alexander Thielen ( [e-mail]) is a staff scientist in the Department of Computational biology and Applied Algorithmics at the Max Planck Institute for Informatics, saarbrücken, Germany.

Rolf Kaiser ( [e-mail]) is a staff scientist at the Virological Institute, Köln, Germany.