The effects of HIV-1 subtype and ethnicity on the rate of CD4 cell count decline in patients naive to antiretroviral therapy: a Canadian-European collaborative retrospective cohort study

Abstract

Background: Ethnic differences have the potential to confound associations between HIV-1 subtype and immunologic progression. We compared declines in CD4 cell counts during untreated infection for the most prevalent HIV-1 subtypes, focusing on distinguishing between the effects of viral subtype and ethnicity.

Methods: We combined data from 4 European and 6 Canadian cohorts, selecting adults in the stable chronic phase of untreated HIV infection. We estimated the change in square root CD4 cell count over time for subtypes and ethnicities using mixed models, adjusting for covariates selected for their potential effect on initial CD4 cell count or its decline.

Results: Data from 9772 patients were analyzed, contributing 79 175 measurements of CD4 cell count and 24 157 person-years of follow-up. Overall, there were no appreciable differences in CD4 cell count decline for viral subtypes A, CRF01_AE, CRF02_AG, C and G compared with viral subtype B; whereas the decline in CD4 cell count in patients of African ancestry was considerably slower than in patients of other ethnicity. When ethnic groups were studied separately, there was evidence for slower declines in CD4 cell count in viral subtypes C, and possibly A and G, compared with viral subtype B in patients of African ancestry but not among patients of other ethnicities, suggesting an interaction between subtype and ethnicity.

Interpretation: Ethnicity is a major determinant of CD4 cell count decline; viral subtype differences may have existed but were small compared with the effect of ethnicity and were most apparent in patients of African ancestry. In developing countries, slower CD4 cell count declines among individuals of African descent may translate to a longer asymptomatic phase and increase the opportunity for HIV transmission.

Conflict of interest statement

Competing interests:Marina Klein received grants from Merck, the Canadian Institutes of Health Research (CIHR), the National Institute of Health Research, Fonds de recherche du Québec − Santé and Schering-Plough, consulting fees from ViiV, and lecture fees from Bristol-Meyers Squibb and ViiV. She also received fees for the development of educational presentations from Gilead and ViiV. Caroline Sabin received grants from the Medical Research Council of England and Wales during the conduct of the study. Darrell Tan received grants from Gilead and ViiV, consulting fees from Gilead and ViiV, and lecture fees from Abbott, Bristol-Myers Squibb, Gilead, Janssen, Merck and ViiV. Sharon Walmsley received grants, consulting fees, lecture fees, nonfinancial support and fees for the development of educational presentations from Merck, ViiV, Gilead, Abbott, Tibotec, Janssen, , Bristol-Myers Squibb and Boehringer Ingelheim. John Gill received a grant from the CIHR and personal fees for being a member of the national advisory boards of Abbvie, Gilead, Merck, Janssen, ViiV and Bristol-Myers Squibb. No competing interests were declared by the other authors.

Figures

Figure 1:

Selection of study cohort. *At least 100 patients available per subtype with CD4 cell counts within the stable chronic phase of untreated infection. †Includes patients with ethnicity assigned based on country of origin, n = 246 (2.5%) (Table 1).

Figure 2:

Estimated CD4 cell count slope decline for each patient. Random effects representing each patient’s CD4 cell count decline (compared with the average) estimated in a mixed model without ethnicity or subtype slope parameters but adjusted for covariates. All cohorts are included in the model except Aquitaine. Grey shading = patients of African ancestry, white shading = patients of other ethnicities, + = mean.

Figure 3:

Estimated decline in CD4 cell count slope for each patient with viral subtype B. Random effects represnting each patient’s CD4 cell count decline (compared with the average) estimated in a mixed model without ethnicity or subtype slope parameters but adjusted for covariates. All cohorts are represented in the model except Aquitaine; however, the only patients shown in this plot have HIV subtype B. Grey shading = patients of African ancestry, white shading = patients of other ethnicities, + = mean.

Figure 4:

Estimated average CD4 cell count over 5 years. The average CD4 cell count estimated (A) in patients of African ancestry with viral subtype C and (B) in patients of other ethnicities with viral subtype B. Estimates were made using separate mixed models: one for patients of African ancestry and one for patients of other ethnicities and represent CD4 cell counts in a male patient with infection not transmitted by injection drug use and with age and initial HIV RNA set at the median for that ethnicity and subtype. CD4 cell count trajectories are shown for a 10% sample of patients of African ancestry with viral subtype C and for a 1% sample of patients of other ethnicities with viral subtype B.