1. Why is inflammation elevated in treated HIV infection and why does it matter? Steven G. Deeks Professor of Medicine University of California, San Francisco

2. Many Age-associated Diseases Are More Common in Treated HIV Disease Than In Age- matched Uninfected Persons Cardiovascular disease Cancer (non-AIDS) Bone fractures/osteopenia Left ventricular dysfunction Liver failure Kidney failure Cognitive decline Frailty Immune system Multiple factors likely explain this increased risk, including co- morbid conditions and antiretroviral drug toxicity

3. Schouten J AIDS 2012 Co-morbid conditions common in HIV-infected adults HIV-infected adults age 50-55 similar to uninfected adults > 65

4. Inflammatory Biomarkers Predict Risk for All-Cause Mortality among Treated Adults CohortDesignT cell acti- vation CRPIL-6K/T IDO Cysta- atin C sCD- 14 D- dimer Fibrin- ogen Hyalu- ronic Acid SMART ESPRIT Case- control ✔✔✔✔✔ FRAM Cohort ✔✔✔ SOCA/ SCOPE Cohort ✔✔✔✔✔✔ UARTO Cohort ✔✔ VACS Cohort ✔✔ FIRST (Pre-ART) Case- control ✔✔✔✔ Pfidisas (Pre-ART) Case- control ✔✔✔ T cells Innate Microbes Coagulation Fibrosis

5. “Over the past decade, it has become widely accepted that inflammation is a driving force behind chronic diseases that will kill nearly all of us... ” Science, 2010 Chronic inflammation is also harmful in non-HIV-infected adults Courtesy of Peter Reiss

6. Is there something unique about inflammation in HIV disease?

7. T cell “activation” is lower in treated than untreated adults, but consistently higher than “normal” Hunt et al JID 2003, PLoS ONE 2011 and unpublished HIV – (n=132) HIV + ART (n=65) HIV + Untreated (n=82)

8. % Diff. from General Population (MESA) Neuhaus et al JID 2010 Among those with undetectable viral load (<400 copies/mL), hsCRP was 40% higher, IL- 6 was 60% higher, and D-dimer was 49% higher, compared with controls from MESA Many common plasma biomarkers of inflammation are also higher in treated HIV disease than “normal”

9. Among treated adults, D-dimers (and perhaps other biomarkers) are stable over years Courtesy of Jens Lundgren

10. Effect on inflammation in predicting mortality higher in HIV disease than the general population (SOCA/SCOPE) Hunt et al CROI 12

11. A single measurement of D-dimers predicts mortality through 8 years of observation, whereas effect wanes in 2-3 years in general population (SMART/ESPRIT; n=3227) There were only 5 deaths over 8 years among those in the lowest quartile (as compared to 45 deaths in highest quartile) Lane et al; CROI 2011

12. Are all of the biomarkers describing the same mechanistic pathway?

13. Biomarkers covering apparently unique pathways (inflammation and coagulation) provided independent prognostic capacity in FRAM Associations for CRP and Fibrinogen persist when CD4 >500 Tien et. al. JAIDS 2010;55(3):316-322

14. Among adults with durable viral suppression, a low CD4+ T cell count is associated with significant T cell abnormalities Hatano CROI 2011 P = 0.0001 P < 0.0001 P = 0.05

15. After controlling for CD4+ T cell count, inflammatory biomarkers have stronger prognostic effect that T cell activationtreated infection Hunt et al CROI 12

16. Early ART Also Appears to Reduce Residual T Cell Activation during ART Jain et al, CROI 2011

17. What causes HIV- associated inflammation?

18. Inflammation ↑ Endothelium adhesion ↑ Monocyte activation Dyslipidemia Hypercoagulation/ thrombotic events Endothelial dysfunction Inflammation ↑ Endothelium adhesion ↑ Monocyte activation Dyslipidemia Hypercoagulation/ thrombotic events Endothelial dysfunction Microbial translocation HIV-associated fat Metabolic syndrome HIV production HIV replication CMV Excess pathogens HIV-mediated loss of regulatory cells (Tregs)

19. Conclusions Inflammation during treated HIV disease is unique Higher than expected Stable over time Stronger prognostic significance Multiple mechanisms cause activation Residual HIV production (or replication) Microbial translocation CMV and other co-pathogens Loss of immunoregulatory responses Lymphoid fibrosis Metabolic syndrome, abdominal obesity Treatment toxicity (e.g., telomerase inhibition)

20. Acknowledgements UCSF Peter Hunt Hiroyu Hatano Priscilla Hsue Jeff Martin Becky Hoh Ma Somsouk Vivek Jain Elizabeth Sinclair Mike Busch Steve Yukl Joe Wong Mike McCune INSIGHT Jason Baker Cliff Lane Andrew Phillips Jim Neaton Jens Lundgren Elsewhere Netanya Sandler Danny Douek Mike Lederman (CLIC) Peter Reiss Rafick Sekaly Tim Schacker