Viral load, CD4 cell counts and antibodies: What do we know and what does it all mean?

1. Viral load, CD4 cell counts and antibodies: What do we know and what does it all mean? Brian Williams, SACEMA, November 2007

2. We have not succeeded in answering all your problems. The answers we have found only serve to raise a whole set of new questions. In some ways we feel that we are as confused as ever but we believe that we are confused on a higher level and about more important things. Notice at the Cambridge University Computer Centre ‘Surgery’, 1970.

3. The standard model Viral load CD4 Time Time Acute phase ~ weeks Final phase ~ months Interested in the long chronic phase ~ 10 yrs Antibodies Time

4. Viral load and CD4 cell counts Virions/mL CD4 cells/mL Orange Farm, South Africa. (Auvert et al. PLOS Medicine, 2005)

5. Viral load and CD4 cell counts 10,000 1000 100 Virions/mL 10 1 0.1 0.01 CD4 cells/mL Orange Farm, South Africa. (Auvert et al. PLOS Medicine, 2005)

6. 150 100 50 0 -50 -100 -150 -200 -250 -300 CD4 slope/mL/year 0.001 0.01 0.1 1 10 100 1000 Virions/μL CD4 cell count decline for different viral loads Rodriguez et al. Jama, 2006.

7. Antibody concentration and CD4 cell counts  Up to 2000 CD4 cells /mL Optical density log(antibody concentration) ZVITAMBO (Hargrove, pers. comm.)

8. Quite solid relationships buried in a vast amount of noise... 1. What does the underlying relationship imply? 2. Where does the noise come from? Problem: We have lots of cross-sectional data but little time series data

9. Viral load distribution: Young men in Orange Farm, South Africa Frequency 0.01 0.1 1 10 100 1000 10,000 Viral load/mL Orange Farm, South Africa. (Auvert et al. PLOS Medicine 2005)

10. CD4 cell counts in HIV-positive and HIV-negative people Orange Farm, South Africa. (Auvert et al. PLOS Medicine 2005); Zambia (Kelly et al. Acta Tropica 2002)

11. Log antibody distribution: Harare Frequency Optical density i.e. ln(antibody concentration)

12. Combine the individual decline with the initial distribution 2000 Assume that survival is independent of the initial value of the CD4 cell count CD4 1000 CD4 cells/l 500 HIV– 0 10 20 Time (years) Survival

13. Assume that survival is independent of the initial value of the CD4 cell count CD4 Time CD4 in HIV– Log(Initial viral load) sets survival

14. CD4 cell counts in HIV-positive and HIV-negative people Orange Farm, South Africa. (Auvert et al. PLOS Medicine 2005); Zambia (Kelly et al. Acta Tropica 2002)

15. Distribution of CD4 cell count decline

16. Survival of young men in Orange Farm, South Africa? Survival (yrs) = 42.2 – 6.5log10(VL/mL) Viral load Weibull survival Frequency Time years Orange Farm, South Africa. (Auvert et al. PLOS Medicine 2005)

17. 1. Survival is (almost) independent of initial CD4 cell count 2. Survival is (entirely) determined by log(set-point viral load) 3. Viral load declines exponentially with CD4: 4. Antibody concentration declines exponentially with CD4: So we need to explain why:

18. Survival against age at HIV seroconversion Proportion surviving Years since infection Time from HIV-1 seroconversion to AIDS and death before widespread use of highly-active anti-retroviral therapy A collaborative re-analysis. Cascade Collaboration. Lancet 2001:355 11311137

19. Prevalence Lusaka Incidence Gauteng Death 00 00 05 10 40 05 95 95 10 90 90 40

20. Lusaka Gauteng