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

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)

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

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

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

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

Total HIV DNA can be reliably detected and measured Viard et al AIDS 2004 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

Integrated can be measured and unintegrated DNA can be calculated from total HIV DNA Koelsch et al JID 2008Agosto 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

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

T TM T EM TNTN T TD E T CM Th 1,2,17, T reg T-cell subsets support HIV persistence variably CD45RA, CCR7 CD45RO, CCR7, CD27 CD45RO, CD27 CD45RO CD45RA, CD45RO T CM and T TM account for a large majority of infected cells. At lower CD4 counts, fraction of T TM increases and T CM Decreases (not shown) Chomont et al Nat Med 2009 T0T0 * * * N=17

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

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”; 6 th IAS HPTP

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, 6 th IAS HPTP) Some transcription patterns more suggestive of latent infection (Adams PNAS 1994, Li Jvirol 2003, Lassen PLoS Path 2006, Tyagi Jvirol 2010)

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

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

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

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 10 9 infected CD4+ T cells ≈ 1.2 x 10 7 latently infected cells Yukl et al JID Nov 2010

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 10 9 infected CD4+ T cells ≈ 1.2 x 10 7 latently infected cells Yukl et al JID Nov 2010

HIV RNA expression is higher 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

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

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

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

Acknowledgements 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 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 U Minn Ashley Haase Tim Schacker Qing Sheng Li Patient volunteers Funding: Dept of Veterans Affairs NIH UCSF CFAR

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

HIV transcription patterns