Reconciling founder variant multiplicity of HIV-1 infection with the rate of CD4 + decline

James Baxter, Ch Julián Villabona-Arenas, Robin N. Thompson, Stéphane Hué, Roland R. Regoes, Roger D. Kouyos, Huldrych F. Günthard, Jan Albert, Andrew Leigh Brown, Katherine E. Atkins

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

HIV-1 transmission precipitates a stringent genetic bottleneck, with 75% of new infections initiated by a single genetic variant. Where multiple variants initiate infection, recipient set point viral load (SpVL) and the rate of CD4+ T cell decline may be elevated, but these findings remain inconsistent. Here, we summarised the evidence for this phenomenon, then tested
whether previous studies possessed sufficient statistical power to reliably identify a true effect of multiple variant infection leading to higher SpVL. Next, we combined models of HIV-1 transmission, heritability and disease progression to understand whether available data suggest a faster CD4+ T cell decline would be expected to associated with multiple variant infection, without an explicit dependency between the two. First, we found that most studies had insufficient power to identify a true significant difference, prompting an explanation for previous inconsistencies. Next, our model framework revealed we would not expect to observe a positive association between multiple variant infections and faster CD4+ T cell decline, in the absence of an explicit dependency. Consequently, while empirical evidence may be consistent with a positive association between multiple variant infection and faster CD4+ T cell decline, further investigation is required to establish a causal basis.
Original languageEnglish
Article number20240255
Pages (from-to)1-14
Number of pages14
JournalJournal of The Royal Society Interface
Volume21
Issue number219
Early online date30 Oct 2024
DOIs
Publication statusPublished - 30 Oct 2024

Keywords / Materials (for Non-textual outputs)

  • infectious disease dynamics
  • bioinformatics
  • HIV/ AIDS

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