The Importance of Inflammation & Coagulation for Risk of

Serious Non-AIDS Events: Results of Biomarker Studies

Jason Baker MD, MSUniversity of Minnesota / HCMC

22nd July 2012

Biomarker and All-Cause Mortality Associations

Baseline Level OR (4th/1st QRT)Univariate P-value

D-dimer 12.4 <0.0001

IL-6 8.3 <0.0001

hsCRP 2.0 0.05

Projects Motivated by Initial (PLoS Med) Findings

1. Additional studies of predictive biomarkers and the biology underlying non-AIDS risk

2. Funding for cohort analyses and to confirm findings in other datasets (ESPRIT and SILCAAT)

3. Leveraging the experimental intervention to study the influence of HIV replication and ART

Biomarkers Remain Elevated with Treated HIV

0

25

50

75

100

125

150

175

200

IL-6 D-dimer Cystatin-C

UnadjustedAdjusted for age, gender, raceFully adjusted

UnadjustedAdjusted for age, gender, raceFully adjusted

hsCRP

% D

iff.

from

Gen

eral

Pop

ula

tion

(M

ESA

)

Neuhaus et al JID 2010; 201(12): 1788, Folsom et al Am J Hematol 2009; 84(6):349, Harris et al Am J Med 1999; 106:506, and unpublished data (SMART adjusted ORs in table)

•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

Mortality RR (4th/1st QRT)

(ART-treated) HIV+ HIV-(SMART/ESPRIT) (MESA)

D-dimer 5.5 2.8(SMART/ESPRIT) (RHS)

IL-6 5.6 2.1

HR adjusted for age, sex, race/ethnicity (RHS only adjusted for age and sex)

# DeathsN=45N=31N=15N=5

Cumulative Deaths Over Time by D-dimer QuartileSMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)

# DeathsN=79N=41N=16N=10

Cumulative Deaths Over Time by IL-6 QuartileSMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)

0.1 1 10 100

AIDS

Non-AIDS Cancer

All-Cause Mortality

HR for Biomarkers (4th/1st quartile) adjusted for age, gender, race

hsCRP IL-6 D-dimer

Biomarker Associations Across OutcomesSMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)

CVD

P-value

0.690.320.43

0.002< 0.001< 0.001

0.010.0050.02

0.540.020.21

Central Question Raised by IL-6/D-dimer Findings:

Among people with HIV on suppressive ART, does adjunctive treatment that reduces levels

of IL-6 and D-dimer ALSO reduce risk for serious non-AIDS and mortality?

The Effects of HIV Replication and ART

OFF ART ON ART with HIV RNA <400

Start ART(VS)

Defer ART(DC)

Stop ART(DC)

Continue ART(VS)

B) Study the Effect of Starting ART

A) Baseline Comparison of Untreated vs. Treated

RandomizeRandomize

3 Complimentary Comparisons to Study the Effects of HIV Replication

C) Study the Effect of Stopping ART

Biomarkers Studied: D-dimer, IL-6, CRP, Cystatin-C, Lipoprotein Particles, Apolipoproteins, ADMA, >10 coagulation factors

Follow-up Follow-up

Baker et al JAIDS 2012, Baker & Tracy CROI 2011, Baker et al JAIDS 2011, Baker et al AIDS 2011, Mocroft et al AIDS 2009, Duprez et al Atherosclerosis 2009, Kuller et al PLoS Med 2008

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

≤ 400(N=34)

401-10,000(N=30)

10,000-50,000(N=29)

>50,000(N=39)

0.00.04

0.11

0.28

Month 1 HIV RNA Level (copies/mL)

∆ D-

Dim

er (µ

g/m

L)

P=.0005 for trend

D-dimer Levels 1 Month after ART Interruption

Kuller et al PLoS Med 2008;5(10):1496

General Thrombosis Model

Blood Clot

Thrombosis Threshold

External Forces Triggering Thrombin Generation

Net Balance of Coagulation Factors

Inciting Events

e.g., immune activation from endotoxemia

e.g., trauma, stress

e.g., age, gene mutations, or synthetic function

Slide adapted from M. Cushman & R. Tracy

0 200 400 600 800 1000 12000

102030405060708090

100

Time (s)

Thro

mbi

n (n

M)

Computational Model of Thrombin Generation via ‘Extrinsic’ (Tissue Factor) Coagulation Pathway

Untreated n=197

ART-treated n=475

Slide c/o K. Brummel-Ziedins (Methods: J Bio Chem 1994;269:23367, Throm Haem 2008;6:104)

Study differences in thrombogenesis based on the plasma composition of:

f-II (prothrombin) -- f-V f-VII f-VIII -- f-IX f-X TFPI AT-III Protein C

Summary

• Ongoing Inflammation and coagulation abnormalities likely contribute to risk for long term non-AIDS complications

• D-dimer findings specifically have motivated new research to understand the impact of HIV infection, and ART, on coagulation homeostasis and disease

• Large outcome trials like SMART change practice, establish new research agendas, and inform the design of a new generation of trials

AcknowledgementsParticipants in:

SMARTESPRIT

All INSIGHT site investigators and, in particular, the many who contributed to these biomarker data

Specific content contributions and analyses from: Jim Neaton, Jens Lundgren, Lew Kuller, Jacquie Neuhaus, Debby Wentworth, Kathleen Brummel-Ziedins and Russ Tracy