One of the more notorious quotes in the history of HIV research came from David Ho at an International AIDS Conference in 1994. During a presentation on the factors driving HIV pathogenesis, Ho put up a slide with the line “it’s the virus, stupid!” A study published in the journal Science in 1996 showing that viral load levels are a strong predictor of disease progression further solidified the view that there is a very direct connection between viral replication (as inferred by counting copies of HIV’s genetic material using viral load assays) and the development of immunodeficiency. However, a number researchers – particularly the late Janis Giorgi from UCLA - continued to investigate the effects of HIV on the immune system and published papers showing that the degree of immune activation associated with HIV infection is also a very strong predictor of immune system decline. Over recent years, researchers focused on studying HIV pathogenesis have reached a consensus that Giorgi was on the right track; the accumulated evidence strongly suggests that immune activation is a (perhaps the) major driver of HIV pathogenesis.
On Sept 27, a new study was published in JAMA that offers additional support for this viewpoint. The authors, led by Benigno Rodriguez from Mike Lederman’s immunology research group at Case Western Reserve in Cleveland, looked at the ability of viral load measurements to predict future CD4 declines in individuals with HIV infection (the data were obtained from three large cohorts over a 12 year period). The researchers first confirmed that, on average, people with higher viral loads lose CD4 T cells from the peripheral blood faster than those with lower viral loads (e.g. people with viral loads less than 500 had an average loss of CD4 cells of 20 per year whereas those with viral loads over 40,000 had an average loss of 78 a year). These data were completely consistent with the Science study from 1996.
However, the researchers also conducted a complex stastistical analysis to try and unearth how much of an individual’s CD4 T cell decline over a six month period could be accounted for by their initial viral load measurement. This analysis showed that only 5-6% of the inter-individual variation in CD4 T cell decline could be explained by the initial viral load level. So while it held true that higher viral loads are associated with faster CD4 decline and vice versa, the data showed that you cannot use the viral load to accurately predict the actual specific number of CD4 T cells that will be lost from the peripheral blood in a given individual over a six month period. The authors do offer the caveat that some studies have suggested that there may be an "inflection point" wherein viral load increases immediately prior to a clinically significant CD4 decline and the onset of AIDS; if such a phenomenon does occur, they note it would not necessarily be captured in their analysis. But an exploratory look at the predictive value of the viral load slope over time (in individuals with multiple sequential measurements available) did not reveal an increased ability of viral load levels to predict CD4 decline compared to the analysis based on a single viral load measurement.
In the discussion section of the JAMA paper, the authors note that immune activation may be a key factor explaining the observed variation in CD4 T cell decline between individuals. As a hypothetical example, if two individuals have the same viral load but one loses CD4 T cells faster (as the JAMA study suggests can often happen), it's possible that differences in the levels of immune activation would explain - at least in part - the divergent outcomes. This would be consistent with previous studies that have reported stronger associations between immune activation and disease progression than those seen between viral load levels and disease progression. There are also a number of complex factors that might impact how much immune activation occurs in the setting of HIV infection (e.g. co-infections, the functionality of the HIV-specific memory T cell response, the genetic make-up - particularly the HLA genes - of the individual, antigen-presenting cell function & turnover, the genetic make-up of the virus, etc.). There may also be additional factors that have yet to be uncovered. The authors close their discussion by noting:
“In humans, the predictive value of immune activation level on HIV disease course, independent of plasma HIV RNA levels, can be demonstrated even when measured during early infection or before actual seroconversion. Thus, immune activation may be a major determinant of T-cell turnover and CD4 cell depletion in chronic HIV infection both in human and animal hosts. Our results provide further support for additional studies exploring the relative contribution of immune activation to the pathogenesis of immune deterioration in treatment naive, HIV-infected persons.”
A couple of news articles have also reported on these findings. Erika Check profiled the immunology researchers behind the JAMA paper in Nature News and Jon Cohen wrote a piece in Science which interviewed John Mellors (author of the 1996 Science paper on viral load); Mellors simply refuses to accept that that the JAMA paper is accurate. David Ho offers an uninterpretable defense of his view of the primacy of viral replication. Conversely, leading immunologists note that these data fit perfectly with understanding of HIV pathogenesis that has emerged over recent years based on studies of T cell turnover and immune activaton markers. Key goals for future research will include analyzing the predictive value of immune activation markers in more detail, delineating the precise mechanisms by which HIV causes immune activation and investigating whether it's possible to develop novel & safe approaches to diminishing activation (potentially ameliorating it's apparently harmful immunological consequences) in people with HIV.
Study abstract:
Predictive Value of Plasma HIV RNA Level on Rate of CD4 T-Cell Decline in Untreated HIV Infection
Benigno Rodríguez, MD, MSc; Ajay K. Sethi, PhD, MHS; Vinay K. Cheruvu, MSc, MS; Wilma Mackay, MS; Ronald J. Bosch, PhD; Mari Kitahata, MD, MPH; Stephen L. Boswell, MD; W. Christopher Mathews, MD, MSPH; David R. Bangsberg, MD; Jeffrey Martin, MD; Christopher C. Whalen, MD, MS; Scott Sieg, PhD; Suhrida Yadavalli, MSM-IS; Steven G. Deeks, MD; Michael M. Lederman, MD
JAMA. 2006;296:1498-1506.
Context Plasma human immunodeficiency virus (HIV) RNA level predicts HIV disease progression, but the extent to which it explains the variability in rate of CD4 cell depletion is poorly characterized.
Objective To estimate the proportion of variability in rate of CD4 cell loss predicted by presenting plasma HIV RNA levels in untreated HIV-infected persons.
Design Repeated-measures analyses of 2 multicenter cohorts, comprising observations beginning on May 12, 1984, and ending on August 26, 2004. Analyses were conducted between August 2004 and March 2006.
Setting Two cohorts of HIV-infected persons: patients followed up at 4 US teaching medical institutions or participating in either the Research in Access to Care for the Homeless Cohort (REACH) or the San Francisco Men's Health Study (SFMHS) cohorts and participants in the Multicenter AIDS Cohort Study (MACS) cohort.
Participants Antiretroviral treatment–naive, chronically HIV-infected persons (n = 1289 and n = 1512 for each of the 2 cohorts) untreated during the observation period (6 months) and with at least 1 HIV RNA level and 2 CD4 cell counts available. Approximately 35% were nonwhite, and 35% had risk factors other than male-to-male sexual contact.
Main Outcome Measures The extent to which presenting plasma HIV RNA level could explain the rate of model-derived yearly CD4 cell loss, as estimated by the coefficient of determination (R2).
Results In both cohorts, higher presenting HIV RNA levels were associated with greater subsequent CD4 cell decline. In the study cohort, median model–estimated CD4 cell decrease among participants with HIV RNA levels of 500 or less, 501 to 2000, 2001 to 10 000, 10 001 to 40 000, and more than 40 000 copies/mL were 20, 39, 48, 56, and 78 cells/µL, respectively. Despite this trend across broad categories of HIV RNA levels, only a small proportion of CD4 cell loss variability (4%-6%) could be explained by presenting plasma HIV RNA level. Analyses using multiple HIV RNA measurements or restricting to participants with high HIV RNA levels improved this correlation minimally (R2, 0.09), and measurement error was estimated to attenuate these associations only marginally (deattenuated R2 in the 2 cohorts, 0.05 and 0.08, respectively).
Conclusions Presenting HIV RNA level predicts the rate of CD4 cell decline only minimally in untreated persons. Other factors, as yet undefined, likely drive CD4 cell losses in HIV infection. These findings have implications for treatment decisions in HIV infection and for understanding the pathogenesis of progressive immune deficiency.
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