Evaluating residual HIV reservoirs

1. Evaluating residual HIV reservoirs • Background or why is this important? • What can be measured? • Where should we measure it? • Conclusions

2. Why study HIV persistence? • To understand the obstacles to HIV eradication (absolute or functional) • To test whether reducing residual viral levels further restores patient health • Life expectancy of a 20 year old with HIV getting effective ART is 11 years less than a similar HIV neg person (The Antiretroviral Therapy Cohort Collaboration, Lancet, 2008)

3. What markers of viral persistence can be measured? Promoter Proximal transcripts Adapted from Furtado et al NEJM 1999

4. What markers of viral persistence can be measured? Cell-free (plasma) HIV RNA Promoter Proximal transcripts Adapted from Furtado et al NEJM 1999

5. What markers of viral persistence can be measured? Cell-free (plasma) HIV RNA HIV DNA total, Integrated, 2LTR circles Promoter Proximal transcripts Adapted from Furtado et al NEJM 1999

6. What markers of viral persistence can be measured? Cell-free (plasma) HIV RNA HIV DNA: total, Integrated, 2LTR circles Cell associated HIV RNA: Promoter- proximal, Multiply spliced, Unspliced. Promoter Proximal transcripts Adapted from Furtado et al NEJM 1999

7. Total HIV DNA can be reliably detected and measured • Usually PCR-based assays • can be performed on PBMC • or purified cellular subsets • doesn’t distinguish defective • from replication competent • or recent from remote infection • abundant evidence that values • are biologically relevant Viard et al AIDS 2004

8. Integrated can be measured and unintegrated DNA can be calculated from total HIV DNA Koelsch et al JID 2008 Agosto Virology 2010 • assays for integrated HIV DNA are more cumbersome, less sensitive • don’t distinguish between replication competent/defective • unintegrated forms more likely to represent recent infection

9. 2LTR circles as a markerfor ongoing replication Subset of subjects showed a transient increase in 2LTR circles during Raltegravir intensification. Buzon et al, Nature Med, 2010

10. E TEM TTM TN TTD TCM T-cell subsets support HIV persistence variably CD45RO T0 CD45RO, CD27 CD45RO, CCR7, CD27 * * * CD45RA, CD45RO CD45RA, CCR7 Th1,2,17, Treg • TCM and TTM account for • a large majority of infected • cells. • At lower CD4 counts, fraction • of TTM increases and TCM • Decreases (not shown) N=17 Chomont et al Nat Med 2009

11. Cell associated infectivity Treatment in acute and early infection results in more rapid clearance of infected cell reservoir and smaller residual reservoir size. Finzi et al Nat Med 1999 Chun et al JID 2007

12. Cell associated infectivity Treatment in acute and early infection results in more rapid clearance of infected cell reservoir and smaller residual reservoir size. Stage of disease at initiation of ART affects Reservoir size. From Strain et al, JID 2005 Agrawal et al, MOLBPE013 New “cellular infectious viral load Assay”; 6th IAS HPTP

13. Cell free and cell associated HIV RNA • Residual viremia at very low levels (Schockmel JAIDS 1997, Dornadula JAMA 1999, Havlir JAMA 2001, Palmer JCM 2003, Palmer PNAS 2008, Hatano AIDS 2010, Chun JID 2011) • Production +/- residual viral replication • Cell associated HIV RNA (Wong PNAS 1997, Lewin JVirol 1999, Gunthard JID 2001, Fischer JID 2004) • Decays over time but frequently remains detectable • Production +/- residual viral replication (Pasternak MOPE075, 6th IAS HPTP) • Some transcription patterns more suggestive of latent infection (Adams PNAS 1994, Li Jvirol 2003, Lassen PLoS Path 2006, Tyagi Jvirol 2010)

14. Residual plasma viremia is detectable in most subjects on ART Chun et al JID 2011 Palmer et al PNAS 2008

15. Unspliced viral RNA is detectable in most patients starting ART after established HIV infection but is lower when ART is started during acute infection Furtado et al NEJM, 1999 Schmid et al PLoS One, 2010

16. T cell stores in tissues Activating environment High levels of CCR5 expression High levels of HIV replication before ART GALT 60% of T lymphocytes Poles, Anton, Markowitz, Lafeuillade, Chun, Rouzioux, Dandekar Blood 25% extracellular fluid volume 2% of T lymphocytes Everything else 35-40% of T lymphocytes

17. HIV infection frequency exceeds infection frequency of PBMC at multiple gut sites • 8 HIV+ subjects on ART, VL <50 c/ml for a median 5 years • Colonoscopy, upper EGD w/6 to 9 biopsies per site. • HIV DNA measured from cell isolates and normalized by flow cytometry data for CD4+ Tcells. • Extrapolated to total body cell numbers • ≈1.2 x 109 infected CD4+ T cells • ≈ 1.2 x 107 latently infected cells Yukl et al JID Nov 2010

18. HIV infection frequency exceeds infection frequency of PBMC at multiple gut sites • 8 HIV+ subjects on ART, VL <50 c/ml for a median 5 years • Colonoscopy, upper EGD w/6 to 9 biopsies per site. • HIV DNA measured from cell isolates and normalized by flow cytometry data for CD4+ Tcells. • Extrapolated to total body cell numbers • ≈1.2 x 109 infected CD4+ T cells • ≈ 1.2 x 107 latently infected cells Yukl et al JID Nov 2010

19. HIV RNA expression ishigher at all gut sites than in PBMC • HIV RNA measured from cell isolates and normalized to GAPDH measures and flow cytometry data • Normalized to HIV DNA content, the per-infected cell • transcriptional level is not • higher in gut Yukl et al JID Nov 2010

20. Assessment of viral load on single cell level Can reveal information on nature of infected cells not obtained by bulk measurements Schacker et al JID, 2005

21. Conclusions What is the relevant form to measure? • For many questions, total HIV DNA, residual plasma viremia are still powerful tools • Analyzing specific DNA and cell-associated RNA forms can provide additional information about different forms of persistence and how they respond to interventions. • Need to look at T-cell (and monocyte macrophage) specific viral load • Need to study these cells in relevant tissues

22. Conclusions • In gut tissues, viral loads respectably high and are amenable to current generations of sensitive molecular assays • Improvement in “high throughput technologies” may enable assessment of a larger sample of clinical materials • Need for assessment on a single cell level: improved imaging techniques/ single cell analysis techniques

23. Acknowledgements • UCSD • Matt Strain • Doug Richman • Susan Little • Karole Ignacio • U of Zurich • Huldrych Gunthard • Marek Fischer • Sara Gianella • Dept Exp Med/UCSF • Lorrie Epling • Elizabeth Sinclair SF VAMC/UCSF • Steven Yukl • Satish Pillai • Peilin Li • Harry Lampiris • Amandeep Shergill • Ken McQuaid SFGH/UCSF • Diane Havlir • Steve Deeks • Hiroyu Hatano • Peter Hunt • U Minn • Ashley Haase • Tim Schacker • Qing Sheng Li • Patient volunteers • Funding: • Dept of Veterans Affairs • NIH • UCSF CFAR

24. Persistently abnormal T-cell activation remains in ART treated patients and in elite controllers (viral load below LOD) Hunt et al JID 2008

25. HIV transcription patterns