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Comparative Study
. 2012 Jan 14;26(2):157-65.
doi: 10.1097/QAD.0b013e32834dcd26.

Clinical, virologic, and immunologic correlates of HIV-1 intraclade B dual infection among men who have sex with men

Affiliations
Comparative Study

Clinical, virologic, and immunologic correlates of HIV-1 intraclade B dual infection among men who have sex with men

Mary E Pacold et al. AIDS. .

Abstract

Objective: To investigate the susceptibilities to and consequences of HIV-1 dual infection.

Design: We compared clinical, virologic, and immunologic factors between participants who were dually infected with HIV-1 subtype B and monoinfected controls who were matched by ongoing HIV risk factor.

Methods: The viral load and CD4 progressions of dually and singly infected participant groups were compared with linear mixed-effects models, and individual dynamics before and after superinfection were assessed with a structural change test (Chow test). Recombination breakpoint analysis (GARD), HLA frequency analysis, and cytotoxic T-lymphocyte (CTL) epitope mapping were also performed (HIV LANL Database).

Results: The viral loads of dually infected participants increased more over 3 years of follow-up than the viral loads of monoinfected controls, whereas CD4 progressions of the two groups did not differ. Viral escape from CTL responses following superinfection was observed in two participants whose superinfecting strain completely replaced the initial strain. This pattern was not seen among participants whose superinfecting virus persisted in a recombinant form with the initial virus or was only detected transiently. Several HLA types were over-represented in dually infected participants as compared to monoinfected controls.

Conclusions: These results identify potential factors for dual infection susceptibility and further define its clinical consequences.

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Conflict of interest statement

Conflicts of Interest and Source of Funding:

Sergei Kosakovsky Pond: has consulted for Monogram Biosciences and Gen-Probe.

Douglas D. Richman: has consulted for Biota, Chimerix, Gen-Probe, Merck, Bristol Myers Squibb, Gilead, Idenix, Monogram Biosciences, and Vertex.

Davey M. Smith: has received grant support from Pfizer and has consulted for Gen-Probe. For the remaining authors, none were declared.

Figures

Figure 1
Figure 1. Algorithm for characterizing DI status
Legend: The study flowchart for the algorithm to determine DI status.
Figure 2
Figure 2. (A) Viral load and (B) CD4 progressions of the 3 infection groups
Legend: Mean VL and mean square root CD4 per month of infection for each group are plotted, and the linear mixed model fit is shown for each group. Red arrows indicate the timing of SI for each of the 7 SI participants.
Figure 3
Figure 3. Temporal dynamics of (A) viral loads and (B) CD4 counts in the seven superinfected (SI) patients
Legend: p – significance level for a structural shift in dynamics following SI (Chow’s test); open circles – samples preceding SI; filled circles – samples following SI; black dashed line – loess fit; red dotted line – linear fit to pre-SI points; blue dotted line – linear fit to post-SI points. EDI: estimated date of infection.

References

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