The Importance of Inflammation &
Coagulation for Risk of
Serious Non-AIDS Events:
Results of Biomarker Studies
Jason Baker MD, MS
University of Minnesota / HCMC
22nd July 2012
Biomarker and All-Cause Mortality Associations
OR (4th/1st QRT)
Univariate
P-value
12.4
<0.0001
IL-6
8.3
<0.0001
hsCRP
2.0
0.05
Baseline Level
D-dimer
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
% Diff. from General Population (MESA)
Biomarkers Remain Elevated with Treated HIV
200
175
Mortality RR (4th/1st QRT)
Unadjusted
Adjusted for age, gender, race
Fully adjusted
(ART-treated) HIV+
150
125
(SMART/
ESPRIT)
(MESA)
5.5
2.8
(SMART/
ESPRIT)
(RHS)
5.6
2.1
D-dimer
100
75
IL-6
50
HIV-
HR adjusted for age, sex, race/ethnicity
(RHS only adjusted for age and sex)
25
0
hsCRP
IL-6
D-dimer
Cystatin-C
•Among those with undetectable viral load (<400 copies/mL), hsCRP was 40% higher, IL6 was 60% higher, and D-dimer was 49% higher, compared with controls from MESA
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Harris et al Am J Med 1999; 106:506, and unpublished data (SMART adjusted ORs in table)
Cumulative Deaths Over Time by D-dimer Quartile
SMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)
# Deaths
N=45
N=31
N=15
N=5
Cumulative Deaths Over Time by IL-6 Quartile
SMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)
# Deaths
N=79
N=41
N=16
N=10
Biomarker Associations Across Outcomes
SMART/ESPRIT control arms with HIV RNA <500 at entry (n=3227)
HR for Biomarkers (4th/1st quartile)
adjusted for age, gender, race
P-value
AIDS
0.69
0.32
0.43
Non-AIDS Cancer
0.54
0.02
0.21
CVD
0.01
0.005
0.02
0.002
< 0.001
< 0.001
All-Cause Mortality
0.1
1
hsCRP
10
IL-6
D-dimer
100
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
3 Complimentary Comparisons to Study the Effects of HIV Replication
OFF ART
A) Baseline Comparison of
Untreated vs. Treated
ON ART with
HIV RNA <400
Randomize
Randomize
Defer ART
Start ART
Stop ART
Continue ART
(DC)
(VS)
(DC)
(VS)
Follow-up
Follow-up
B) Study the Effect of Starting ART
C) Study the Effect of Stopping ART
Biomarkers Studied: D-dimer, IL-6, CRP, Cystatin-C, Lipoprotein Particles,
Apolipoproteins, ADMA, >10 coagulation factors
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
D-dimer Levels 1 Month after ART Interruption
0.5
∆ D-Dimer (µg/mL)
0.4
0.3
0.28
0.2
0.11
0.1
0
0.04
0.0
P=.0005 for trend
-0.1
-0.2
≤ 400
(N=34)
401-10,000
(N=30)
10,000-50,000
(N=29)
Month 1 HIV RNA Level (copies/mL)
Kuller et al PLoS Med 2008;5(10):1496
>50,000
(N=39)
General Thrombosis Model
Net Balance of
Coagulation Factors
External Forces Triggering
Thrombin Generation
e.g., age, gene mutations,
or synthetic function
e.g., immune activation
from endotoxemia
Thrombosis
Threshold
Inciting Events
e.g., trauma, stress
Blood Clot
Slide adapted from M. Cushman & R. Tracy
Computational Model of Thrombin Generation via
‘Extrinsic’ (Tissue Factor) Coagulation Pathway
Study differences in thrombogenesis based on the plasma composition of:
100

-

-



90
Thrombin (nM)
80
Untreated n=197
70
60
ART-treated n=475
50
40
30
f-II (prothrombin)
f-V
f-VII
f-VIII
f-IX
f-X
TFPI
AT-III
Protein C
20
10
0
0
200
400
600
800
1000
Time (s)
Slide c/o K. Brummel-Ziedins (Methods: J Bio Chem 1994;269:23367, Throm Haem 2008;6:104)
1200
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
Acknowledgements
Participants in:
SMART
ESPRIT
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