Infection with multiple human immunodeficiency virus type 1 variants is associated with faster disease progression

Abstract

Human immunodeficiency virus type 1 (HIV-1)-infected individuals develop a genetically diverse virus population over time, but often only a limited number of viral variants are transmitted from a chronic carrier to a newly infected person. Interestingly, many women but few men are infected by multiple HIV-1 variants from a single partner. To determine whether the complexity of the infecting virus population influences clinical outcome, we examined viral diversity in the HIV-1 envelope sequences present at primary infection in 156 women from Kenya for whom we had follow-up data on viral RNA levels and CD4 T-cell counts. Eighty-nine women had multiple viral genotypes, while 67 women had a single genotype at primary infection. Women who acquired multiple viral genotypes had a significantly higher viral load (median, 4.84 versus 4.64 log(10) copies/ml, P = 0.04) and a significantly lower CD4(+)-T-cell count (median, 416 versus 617 cells/mm(3), P = 0.01) 4 to 24 months after infection compared to women who were infected with a single viral genotype. These studies suggest that early HIV-1 genetic diversity is linked to faster disease progression.

FIG. 1.

Representative HMAs of a 1.2-kb envelope fragment amplified in PCRs starting with different amounts of proviral templates from PBMCs from eight subjects. The designations represent the different subjects; Q03, Q32, Q83, and Q90 were classified as heterogeneous, and Q34, Q74, Q84, and Q96 were classified as homogeneous virus populations with a combination of two PCRs starting with approximately 10 proviral copies. For each subject, the first three lanes of product are from PCRs with 100, 10, and 1 proviral copies as determined by real-time quantitative PCR, respectively. The number of proviral copies added to the PCR is indicated above each lane. Twenty-four to 36 independent PCRs from one input template were performed for each subject, and the last lane (Mix) contains a mixture of 10 of these PCRs that yielded a positive result.

FIG. 2.

Box plots of the first viral load (A) and absolute CD4⁺-T-cell count (B) measured 4 to 24 months after infection comparing women infected with a heterogeneous virus population to those with a homogeneous virus population. The number of subjects contributing to the data and the median interval from the estimated date of infection to the day of viral RNA or CD4⁺-T-cell measurement are above each box plot. The thick black line in each box represents the median values for each group; the numbered values are presented beside the lines. Boxes show the interquartile range, the 25th and 75th percentiles of the data, while the whiskers are values 1.5 times the interquartile range above and below the median. Οpen circles represent any data outside the whiskers. Comparisons between groups were done with the Mann-Whitney U test.

FIG. 3.

Mean viral loads of women infected with a heterogeneous virus population versus those of women with a homogeneous virus population over the course of follow-up. Each symbol represents the mean of the available individual log-transformed viral loads for the women in each group for each month, starting 4 months after infection. In cases in which a woman contributed more than one viral load measurement for a month, an average was used for her results for that month. Loess-smoothed curves were generated with 99% of the mean monthly viral loads with 20 iterations. The number of women in each group with active follow-up over time is shown at the bottom.

FIG. 4.

Kaplan-Meier analysis of time to a CD4⁺-T-cell count of less than 350 cells/mm³. Survival analysis was performed on a subset of women who had at least one CD4⁺-T-cell measurement 4 to 24 months after infection. The event, a CD4⁺-T-cell count of less than 350/mm³, was assumed to have occurred on the date of the clinic visit at which the CD4⁺-T-cell count was done. Kaplan-Meier curves and log-rank tests were used for the survival analyses. The numbers of women at risk in both groups are shown at the bottom.