HIV and CVD Do we really understand the risk? · Framingham risk assessment may underestimate MI risk in HIV HIV and MI –role of traditional risk factors 1. Regan S, et al. CROI

1

Dr Paddy Mallon

UCD HIV Molecular Research GroupAssociate Dean for Research and Innovation

UCD School of Medicine and Medical Science

[email protected]

UCD School of Medicine

& Medical Science

Scoil an Leighis agus

Eolaíocht An Leighis UCD

HIV and CVD

Do we really understand the risk?

0

2

4

6

8

10

12

14

16

0 1 2 3 4 5 6

HIV negative

HIV positive

30-39 40-49 50-59 60-69 70-79

* Within age group P<0.05

• AMI commonest cause of death in ART-treated patients1

• Rates of MI higher in HIV-positive versus HIV-negative2

1. Rodger A. et al. AIDS. 2013 Mar 27;27(6):973-9 2. Freiberg MS, et al. JAMA Int Med. 2013; 173(8):614-22,

3. Petoumenoa K et al. HIV Med 2014. May 19.

HIV and CVD – incidence of MI

* *

*

*

AMI=acute myocardial

infarction; CI=confidence

interval.

AM

I ra

tes / 1

000 p

atient

years

(95%

C.I

)

• RR of MI with age not different between HIV and the

general population risk estimates3

CVDHIV

Smoking &

lifestyle

Immune dysfunction

Dyslipidaemia

Inflammation

Diabetes &

obesity

Monocyte activation

Immune senescence

Ageing

HTN

Drug

toxicity

J O’Halloran, Future Virology 2013 Oct; 8(10):1021-1034

CVDHIV

Smoking &

lifestyle

Immune dysfunction

Dyslipidaemia

Inflammation

Diabetes &

obesity

Monocyte activation

Immune senescence

Ageing

HTN

Drug

toxicity


CVD – assessing risk

http://cvdrisk.nhlbi.nih.gov

http://www.heart.org/HEARTORG/Conditions/HeartAttack/HeartAttackToolsResources/Heart-Attack-Risk-Assessment_UCM_303944_Article.jsp

http://www.cvdcheck.org.au

http://hivpv.org/Home/Tools/tabid/91/ctl/ExamView/mid/500/eid/0/lid/0/Default.aspx. 1. Krimme M et al. HIV Med 2015 [Epub ahead of print]

D:A:D and ASCVD lower risk profile than FHS-CVD1

Sabin CA et al. Abstract 748, 20th CROI, Atlanta, 2013.

Year of MI

99-02 03-04 05-06 07-08 09-11

Number of MIs 212 194 157 171 110

Male (%) 91.0 92.8 90.5 89.5 92.7

Age (yrs) 48 49 49 51 51

CD4 (cells/mm3) 398 444 454 436 546

Smokers (%) 49.5 46.9 55.4 57.3 58.2

Family history (%) 14.2 13.9 14.7 15.2 13.6

High risk (%) 28.8 23.2 22.3 26.9 32.7

1 mth mortality (%) 26.4 24.7 19.8 16.4 8.2

HIV and MI

Characteristics of those with MI in D:A:D

http://cvdrisk.nhlbi.nih.gov

http://www.heart.org/HEARTORG/Conditions/HeartAttack/HeartAttackToolsResources/Heart-Attack-Risk-Assessment_UCM_303944_Article.jsp

http://www.cvdcheck.org.au

http://hivpv.org/Home/Tools/tabid/91/ctl/ExamView/mid/500/eid/0/lid/0/Default.aspx

2

Law MG, et al. HIV Med 2006;7:218-230.

0

1

2

3

4

5

6

7

8

Duration of HAART Exposure (years)

Rate

/1000 P

Y

< 1 1–2 2–3 3–4 4+

Observed

rates

Best

estimate of

predicted

rates

None

Observed and predicted MI rates according to ART exposure (D:A:D Study)

Framingham risk assessment may underestimate MI risk in HIV

HIV and MI – role of traditional risk factors

1. Regan S, et al. CROI 2015; Seattle, WA. #7512. Thompson-Paul A, et al. CROI 2015; Seattte, WA. #747

Framingham

Risk Score

Observed vs. Predicted 5-Year CVD Outcomes

HIV and CVD – incidence of MI

• Partners Healthcare System HIV longitudinal cohort (n=2270)1

• HIV Outpatient Study cohort (n=2392)2

CVD risk prediction equations consistently underestimate

CVD risk in HIV+ subjects

HIV & CVD

What are the unmeasured risks?CVD

HIV

Smoking &

lifestyle

Immune dysfunction

Dyslipidaemia

Inflammation

Diabetes &

obesity

Monocyte activation

Immune senescence

Ageing

HTN

Drug

toxicity


RR

of

cu

mu

lati

ve

exp

osu

re/y

ear

95%

CI

# PYFU: 138,109 74,407 29,676 95,320 152,009 53,300 39,157

# MI: 523 331 148 405 554 221 139

RR

of

rece

nt*

exp

osu

re

yes/n

o

95%

CI

1.9

1.5

1.2

1.0

0.8

0.6ZDV ddI ddC d4T 3TC ABC TDF

# PYFU: 68,469 56,529 37,136 44,657 61,855 58,946

# MI: 298 197 150 221 228 221

IDV NFV LPV/RTV SQV NVP EFV

PI† NNRTI1.2

1.13

1.0

1.1

0.9

1.9

1.5

1.2

1.0

0.8

0.6

*Current or within past 6 months; †Approximate test for heterogeneity: p=0.02; **not shown due to low number of patients receiving ddC.

CVD=cardiovascular disease; MI=myocardial infarction; RR=relative risk; PYFU=patient years of follow up.

RR

of

cu

mu

lati

ve

exp

osu

re/y

ear

95%

CI

NRTI

**

Cardiovascular events: Do drugs matter?

D.A.D: MI risk is associated with recent and/or cumulative

exposure to specific NRTIs and PIs

Adapted from Lundgren JD, et al. CROI 2009. Oral presentation 44LB. Satchell CS et al. JID 2011;204:1202-10

Increased platelet reactivity

in HIV-infected patients on

abacavir-containing ART

% a

gg

reg

ati

on

to

AD

P

100

90

80

70

60

50

40

30

20

10

0

-10

ADP at 1.25uM

ABC No

ABC

ABC

No ABC

30 [25]% v 18 [18]%

P=0.032

Platelet dysfunction

May explain reversible increased risk of MI with ABC

3

Switching from Lamivudine/Abacavir (3TC/ABC) to

Emtricitabine/Tenofovir DF (FTC/TDF) Based Regimen

(SWIFT) Study

Platelet Biology Sub-study

O’Halloran JA1, Dunne E2, Tinago W1, Denieffe S1, Kenny D2,

Mallon PWG1

1HIV Molecular Research Group, School of Medicine and Medical Science, University College Dublin, Dublin,

Ireland, 2 Cardiovascular Biology Group, Royal College of Surgeons in Ireland, Dublin, Ireland

Aim of SWIFT platelet biology sub- study

To examine changes in markers of platelet function as a sub-

study of the SWIFT trial

ABC/3TC+ PI/r for ≥ 3 months

HIV RNA <200c/ml ≥ 3 months

TDF/FTC + PI/r

ABC/3TC + PI/r1

:1 r

an

do

mis

ati

on

SWIFT Study design

O’Halloran J et al. CROI 2014. Abstract LB749

Characteristic TDF/FTC n=156 ABC/3TC n=156

Age, years [mean (SD)] 46.0 (9) 46.7 (9.7)

Male [N (%)] 130 (83.3) 134 (85.9)

Caucasian ethnicity [N (%)] 97 (62.2) 106 (67.9)

History of dyslipidaemia [N

(%)]

88 (56.4) 102 (65.4)

History of hypertension [N (%)] 49 (31.4) 50 (32.1)

Current smoker [N (%)] 39 (25.0) 42 (26.9)

Protease inhibitor at baseline [N (%)]

LPV/r 47 (30.1) 52 (33.3)

ATV/r 62 (39.7) 61 (39.1)

FPV/r 35 (22.4) 30 (19.2)

DRV/r 8 (5.1) 9 (5.8)

Other 4 (2.6) 4 (2.6)

Concomitant medication

Lipid lowering therapy 97 (62.2) 107 (68.6)

NSAIDS 45 (28.8) 40 (25.6)J O’Halloran, et al. CROI 2014. Abstract 749LB

SWIFT Study - results

0 1 2 2 4 3 6 4 8

5 5

6 5

7 5

8 5

T im e in w e e k s

sP

-se

lec

tin

(n

g/m

L)

T D F /F T C

A B C /3 T C

p = 0 .5 1

0 1 2 2 4 3 6 4 8

6 0

8 0

1 0 0

1 2 0

1 4 0

T im e in w e e k s

sC

D4

0L

(n

g/m

l)

T D F /F T C

A B C /3 T C

p = 0 .4 6

0 1 2 2 4 3 6 4 8

3 0 0

6 0 0

9 0 0

1 2 0 0

1 5 0 0

1 8 0 0

T im e in w e e k s

vW

F (

mU

/ m

l)

T D F /F T C

A B C /3 T C

p = 0 .6 3

No between-group difference

in the change in sP-selectin,

sCD40L and vWF to 48 weeks

J O’Halloran, et al. CROI 2014. Abstract 749LB

SWIFT Study - results

• Significant increase in sGPVI

in the TDF/FTC group

• (+0·57 ng/ml, 95% CI; 0·2 -

0·94), p=0.003

• Persisted when corrected for

age, gender ethnicity, smoking

status, history of dyslipidaemia

or hypertension, baseline

CD4+ T-cell and platelet count

and creatinine and change

from baseline to week 48 in

creatinine

0 1 2 2 4 3 6 4 8

3 .0

3 .5

4 .0

4 .5

5 .0

S o lu b le G P V I

T im e in w e e ks

GP

VI

(ng

/ml)

T D F /F T C

A B C /3 T C

P = 0 .0 0 3

J O’Halloran, et al. CROI 2014. Abstract 749LB

SWIFT Study - results SWIFT Study design

J O’Halloran, Personal Communication May 2015

4

1 Bigalke et al. Clin Chem 2011,57:898-904 2. Wurster T Platelets 2013,24:560-

565 3.Al- Tamami et al . Stroke 2011,42:498-500.

GPVI and CVD

Imbalance in soluble versus platelet-bound GPVI in both ACS1

and stroke2,3

CVDHIV

Smoking &

lifestyle

Immune dysfunction

Dyslipidaemia

Inflammation

Diabetes &

obesity

Monocyte activation

Immune senescence

Ageing

HTN

Drug

toxicity


Dyslipidaemia in HIV UPBEAT

HIV- (N=259) HIV+ (N=190) P

Age 41 (34, 48) 38 (33, 46) 0.08

Male gender 42.9% 61.6% <0.0001

Smokers 36.3% 16.2% 0.0001

(P<0.0001) (* <40mg/dl)

HDL <1mmol/L*

HIV+ 35.2%

HIV- 11.4%

Differences in HDL and TG,

but not LDL, remained

significant in fully adjusted

analyses

Cotter AG et al. 14th AIDS. 2014 Sep 10;28(14):2051-60

HIV, HDL and monocytes

Feeney ER et al. JID 2013 Feb 15;207(4):628-37 Mujawar et al. Plos Biol 2006;4:e365. .

-4 0 4 8 1 2 1 6 2 0 2 4

0 .0 0 0 0 0 0

0 .0 0 0 0 0 5

0 .0 0 0 0 1 0

0 .0 0 0 0 1 5

0 .0 0 0 0 2 0

0 .0 0 0 0 2 5

Q u a n tific a tio n o f M IC / E C s ta n d a rd is e d fo r to ta l c e ll c o u n t

in H IV n e g s u b je c ts

T im e in h o u rs

MIC

/EC

: to

tal

ce

ll c

ou

nt

LD

L l

oa

din

g

Ap

o A

1a

dd

ed

M IC w ith o u t A p o A 1

M IC w ith A p o A 1

E C w ith o u t A p o A 1

E C w ith A p o A 1

D a ta a re m e a n (S E )

L in e re p re s e n ts te n in d iv id u a ls o n o n e o c c a s s io n

Monocyte Cholesterol Efflux (MCE) assay

MCE = ratio of extracellular to intracellular cholesterol

(ECT: MICT)

Additional 24 hr measure with ApoA1 (ECa: MICa).


O’Halloran J et al. CROI 2015; abstract 732

• Monocyte Intracellular Cholesterol (MONIC) Study

• Cross-sectional, HIV+ (N=50) ART naïve and HIV- (N=50)

• Matched for age, gender, ethnicity, smoking status, hep C

5

2 4 6 2 4 2 4

0 .0

0 .5

1 .0

1 .5

T im e in h o u rs

EC

(T

):M

IC(T

)

H IV +

H IV -

A po A1

p = 0 .0 0 1p = 0 .0 0 4

p = 0 .0 1 2

p = 0 .0 0 3

p = 0 .0 5 4


O’Halloran J et al. CROI 2015; abstract 732

Untreated HIV associated with enhanced, not inhibited, MCE!

CVDHIV

Smoking &

lifestyle

Immune dysfunction

Dyslipidaemia

Inflammation

Diabetes &

obesity

Monocyte activation

Immune senescence

Ageing

HTN

Drug

toxicity


HIV, CVD and inflammation

Endothelium Platelets

Monocyte

GUT HIV

ART

CD8+

Effect of initiating antiretroviral therapy on markers of monocyte activation, endothelial dysfunction and platelet

activation in HIV-1 infection

JA O’Halloran1, 2, E Dunne3, MMP Gurwith1, JS Lambert1, 2, GJ Sheehan2, ER Feeney1, A Pozniak4, P Reiss5, D Kenny3, PWG Mallon1, 2

1HIV Molecular Research Group, School of Medicine and Medical Science, University College Dublin, Dublin, Ireland 2Department of Infectious Diseases, Mater Misericordiae University Hospital, Dublin, Ireland

3Cardiovascular Biology Group, Royal College of Surgeons in Ireland, Dublin, Ireland4 HIV Directorate, Chelsea and Westminster Hospital NHS Foundation Trust, London, United Kingdom

5 University of Amsterdam, Academic Medical Center, Department of Global Health and Stichting HIV Monitoring, Amsterdam, Netherlands

O’Halloran J et al. HIV Med. 2015 Jun 25. doi: 10.1111/hiv.12270

W e e k 0 W e e k 0 W e e k 4 W e e k 1 2

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

sC

D1

63

(n

g/m

L) n s 0 .0 0 0 1

H IV p o s it iv e H IV n e g a t iv e

0 .0 0 0 1

0 .0 0 1


0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

3 0 0 0

sC

D1

4 (

ng

/mL

)

n s

n s


0 .0 0 0 1

0 .0 0 0 1

• Both sCD14 & sCD163 were significantly higher in untreated

HIV+ subjects compared to HIV- controls

• ART initiation resulted in significant reductions in sCD163

• No effect on sCD14 with ART initiation

sCD163 baseline comparison and

post ART initiation in HIV

sCD14 baseline comparison and

post ART initiation in HIV

Markers of monocyte activation



0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

1 2 0 0

1 4 0 0

1 6 0 0

vW

F (

mU

/ m

l)

n s 0 .0 0 1

0 .0 5

0 .0 5



0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

1 2 0 0

1 4 0 0

ICA

M-1

(n

g/m

l)

n s


0 .0 0 0 1

0 .0 1

0 .0 1


0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

1 2 0 0

1 4 0 0

VC

AM

-1 (

ng

/ml)

n s


0 .0 1

0 .0 0 0 1

0 .0 0 0 1

• Pre-ART, higher ICAM-1, VCAM-1 and vWF versus controls

• Significant reductions in all endothelial markers post ART

initiation

• Remained higher than control values at week 12

ICAM-1/ VCAM-1

vWF

Markers of endothelial dysfunction


6


0

2

4

6

8

1 0

1 2

sG

PV

I (n

g/m

l) n s

n s


0 .0 1

0 .0 5


0

1 0 0

2 0 0

3 0 0

4 0 0

5 0 0

sC

D4

0 L

iga

nd

(n

g/m

L)

n s

n s


0 .0 1

0 .0 0 0 1


0

2 0

4 0

6 0

8 0

sP

-Se

lec

tin

(n

g/m

L)

n s


0 .0 0 1

0 .0 5 0 .0 5

• Pre-ART sGPVI, sCD40L and sP-selectin higher in HIV+

subjects compared with HIV- controls

• All platelet markers significantly reduced with ART, to levels

observed in controlssGPVI

sCD40L/ sP-selectin

Markers of platelet function


HIV and CVD summary

• Excess risk of CVD in those with HIV, despite effective

therapy

• Traditional risk factors do not fully explain excess CV risk

• Drug and HIV-specific effects on vascular function and

thrombosis among the potential contributory mechanisms

• Complex interactions between gut, immune activation,

coagulation and endothelial dysfunction

• Improve risk assessment – systems biology

http://reprievetrial.org/overview/ https://clinicaltrials.gov/ct2/show/NCT02344290

Accessed Sept 2015

‘Evaluating the Use of Pitavastatin to Reduce the Risk of

Cardiovascular Disease in HIV-Infected Adults’

• NHLBI / NIAID ‘A5332’

• Pitavastatin 4mg vs placebo

• N=6,500, HIV+ on ART, age >40 yrs, ASCVD risk <7.5%

• 1o endpoint time to CVD event

• 2o endpoints include non-calcified plaque, inflammation

(sCD163)

Future research to understand risk

‘Pharmacokinetic

and Clinical

Observations in

People over Fifty’

UK and Ireland The Netherlands

Future research to understand risk

Acknowledgements

HIV Molecular Research Group:

• Dr Eoin Feeney

• Dr Tara McGinty

• Dr Jane O’Halloran

• Dr Elena Alvarz-Barco

• Robert Maughan

• Willard Tinago

• Alan Macken

• Albhe Flaherty

• Sadhbh Tennant

• Aoife Lacey

• Joanne Maher

• Maria Byrne

Infectious Diseases MMUH

• Dr Jack Lambert

• Dr Gerard Sheehan

http://reprievetrial.org/overview/

https://clinicaltrials.gov/ct2/show/NCT02344290

Documents

HIV and CVD Do we really understand the risk? · Framingham risk assessment may underestimate MI risk in HIV HIV and MI –role of traditional risk factors 1. Regan S, et al. CROI