Control of the HIV-1 Load Varies by Viral Subtype in a Large Cohort of African Adults With Incident HIV-1 Infection

Abstract

Few human immunodeficiency virus (HIV)–infected persons can maintain low viral levels without therapeutic intervention. We evaluate predictors of spontaneous control of the viral load (hereafter, “viral control”) in a prospective cohort of African adults shortly after HIV infection. Viral control was defined as ≥2 consecutively measured viral loads (VLs) of ≤10 000 copies/mL after the estimated date of infection, followed by at least 4 subsequent measurements for which the VL in at least 75% was ≤10 000 copies/mL in the absence of ART. Multivariable logistic regression characterized predictors of viral control. Of 590 eligible volunteers, 107 (18.1%) experienced viral control, of whom 25 (4.2%) maintained a VL of 51–2000 copies/mL, and 5 (0.8%) sustained a VL of ≤50 copies/mL. The median ART-free follow-up time was 3.3 years (range, 0.3–9.7 years). Factors independently associated with control were HIV-1 subtype A (reference, subtype C; adjusted odds ratio [aOR], 2.1 [95% confidence interval {CI}, 1.3–3.5]), female sex (reference, male sex; aOR, 1.8 [95% CI, 1.1–2.8]), and having HLA class I variant allele B*57 (reference, not having this allele; aOR, 1.9 [95% CI, 1.0–3.6]) in a multivariable model that also controlled for age at the time of infection and baseline CD4+ T-cell count. We observed strong associations between infecting HIV-1 subtype, HLA type, and sex on viral control in this cohort. HIV-1 subtype is important to consider when testing and designing new therapeutic and prevention technologies, including vaccines.

Current and historic HIV-1 molecular epidemiology in paediatric and adult population from Kinshasa in the Democratic Republic of Congo

“…Since HIV-1 variability can impact transmission, pathogenesis and disease progression 13 – 15 , HIV monitoring 16 , 17 , resistance pathways 18 , cognitive impairment 19 , and HIV vaccine development 20 , an accurate HIV-1 variant identification is needed 21 . It can enable a better understanding of global HIV expansion 22 , 23 and to infer the evolutionary possibilities in the selection of new variants, such as the recently described subtype L 10 .…”

Cohort Profile: IAVI’s HIV epidemiology and early infection cohort studies in Africa to support vaccine discovery

“… 25 We also observed that ∼5% of volunteers appeared to control the virus, keeping viral load ≤2000 copies/mL. This too varied by infecting subtype; those with subtype A were more likely to control the virus compared with those with subtype C. 10 …”

“…We did allow (with permission from the volunteers via the consent process) data and samples (in this case, frozen blood plasma only) from the incidence studies to ‘roll over’ into the Early HIV Infection Cohort Study once it began. Over 90% of Protocol C volunteers were identified via Protocol B and the HT Study, with the remainder either identified at the time of screening for Protocol B by detectable p24 antigen in the absence of HIV antibodies (suggesting incident HIV infection) or through other sources ( Table 1 , see also 10 ). Suspected transmitting partners were also invited to enrol for a single study visit and 406 partners were enrolled, primarily from the HIV-discordant couple cohorts.…”

A Novel Sample Selection Approach to Aid the Identification of Factors That Correlate With the Control of HIV-1 Infection

“…The control of HIV replication in vivo is multifactorial. Indeed viral control has been shown to be associated with age at infection, time post-infection, gender, HLA type, virus subtype and route of infection (17)(18)(19)(20)(21)(22). Obtaining sufficient numbers of samples to allow for the control of all these confounders and the discovery of new correlates of disease trajectory poses a real challenge (23,24).…”