Founder Effects in the Assessment of HIV Polymorphisms and HLA Allele Associations

Author:

Bhattacharya Tanmoy12345,Daniels Marcus12345,Heckerman David12345,Foley Brian12345,Frahm Nicole12345,Kadie Carl12345,Carlson Jonathan12345,Yusim Karina12345,McMahon Ben12345,Gaschen Brian12345,Mallal Simon12345,Mullins James I.12345,Nickle David C.12345,Herbeck Joshua12345,Rousseau Christine12345,Learn Gerald H.12345,Miura Toshiyuki12345,Brander Christian12345,Walker Bruce12345,Korber Bette12345

Affiliation:

1. Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

2. Santa Fe Institute, Santa Fe, NM 87501, USA.

3. Machine Learning and Applied Statistics Group, Microsoft Research, Redmond, WA 98052, USA.

4. Partners AIDS Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA.

5. Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.

Abstract

Escape from T cell–mediated immune responses affects the ongoing evolution of rapidly evolving viruses such as HIV. By applying statistical approaches that account for phylogenetic relationships among viral sequences, we show that viral lineage effects rather than immune escape often explain apparent human leukocyte antigen (HLA)–mediated immune-escape mutations defined by older analysis methods. Phylogenetically informed methods identified immune-susceptible locations with greatly improved accuracy, and the associations we identified with these methods were experimentally validated. This approach has practical implications for understanding the impact of host immunity on pathogen evolution and for defining relevant variants for inclusion in vaccine antigens.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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