Sally L. Hodder M.D. Professor of Medicine New Jersey Medical School – UMDNJ Newark, New Jersey

HIV AND AGING

Sally L. Hodder M.D.Professor of Medicine

New Jersey Medical School – UMDNJNewark, New Jersey

At the conclusion of this presentation, participants should be able to:

Appreciate occurrence of immune activation and relevance to aging

Describe differences in response to antiretroviral therapy in older compared with younger HIV-infected persons

Characterize selected age-related comorbidites in HIV-infected persons and appreciate implications for preventive care

Learning Objectives

This presentation will include discussion of the following investigational uses of products

Statins to decrease immune activation

OFF-Label Disclosure

HIV Cases Among Persons >50 Years of Age

2001 2004 2015 (Projected)0

10

20

30

40

50

60

17

23

50

CDC. HIV/AIDS Surveillance Report, 2005; Smith G. US Senate Special Committee on Aging. Serial no. 109-7; May 12, 2005.

Perc

enta

ge o

f Rep

orte

d H

IV C

ases

Occ

urrin

g in

Per

sons

>50

Yea

rs

Year

Assessed deaths in 13 HIV-1 cohorts comprising 39,727 persons

Of 1876 deaths, definitive cause in 85% Non-AIDS related deaths in 50.5%

◦ Of those:

Causes of Death In HIV-1 HAART Treated Persons 1996-2006

% Malignancy

Infection (non-AIDS)

CVD

Violence/Substance Abuse

Liver

Respiratory

Renal

OtherClin Inf Dis 2010;50:1387-1396

Death Rates in Persons Living With AIDS New York City 1999-2004

Sackoff J et al. Ann Intern Med. 2006;145:397-406.

Age-

Adju

sted

Mor

talit

y Ra

tes

per 1

0,00

0 PL

WA

30.3

20.423.1

11.7 12.4 11.612.6

68

0

5

10

15

20

25

30

35

Black Hispanic White/Other

CVDSubstance AbuseLung Cancer

CVD includes chronic ischemic heart disease, acute MI, hypertension related deaths

PLWA

HIV infection and immune activation◦ Relevance to aging◦ Possible importance of CMV

Responses to antiretroviral therapy◦ Immunologic◦ Virologic◦ Implications

Age-related co-morbidities◦ Cardiovascular Disease◦ Osteoporosis◦ Malignancy

Overview




Overview

HIV infection is associated with immune activation ◦In established infection, ≤50% of peripheral CD8+ T

cells appear to be activated, compared with <10% in HIV-uninfected persons

◦Similar trends in the CD4+ T-cell population ◦Frequency of activated T cells predicts disease

progression, independent of HIV-1 RNA◦Antiretroviral therapy reduces HIV-associated T-cell

activation, though often incompletely

Immune Activation in HIV

Model of Immunosenesence and Aging

SLIDE to COME

Prospective trial of valganciclovir (VAL) in CMV seropositive HIV-1 infected persons on HAART

100% with suppressed CMV DNA at 8 and 12 weeks VAL arm (n=14) with significant (p=0.01) decrease in

CD8+ cell activation ◦ Decreased 4.1% (constituted 20% reduction)

hsCRP decreased significantly in VAL arm (p=0.014), however, no significant difference between arms

CMV and possibly other viruses appear to be determinant of CD8+ activation

CMV Increases CD8+ Activation

Hunt et al. CROI 2010, San Francisco. Abrstract 380

Model of Immunosenesence and Aging

SLIDE to COME




Overview

Higher Risk of Clinical Progression in Patients ≥50 Years of Age Patients ≥50 years have higher risk of clinical progression but improved

virologic response compared with younger patients Prospective cohort study of 3015 treatment-naive patients initiating ART

◦ Aged ≥ 50 years: n=401◦ Aged < 50 years: n=2614

Median follow-up: 31.5 months At BL, older patients more likely to have

◦ AIDS-defining event (P =.0001)◦ Lower CD4 T-cell count (P =.0002)

◦ Higher HIV-1 RNA level (P =.0001)

Outcome Adjusted HR P value

Progression to ADE or death 1.52 .0035

Progression to new ADE 1.50 .0087

HIV-1 RNA <500 copies/mL 1.23 <.05

Grabar S. AIDS. 2004;18(15):2029-2038. HR, hazard ratio; yoa, years of age.ADE, AIDS-defining event; BL, baseline;

Antiretroviral Tolerability Decreases With Age Kaiser Permanente of Northern California chart review study of all

members who initiated ART from 1995-2004 (N=5090)◦ ≥18 years of age◦ Starting ≥3 antiretrovirals in combination

Laboratory test results available for year before and year after ART initiation◦ Excluded patients with laboratory test result abnormality in year before ART

Analysis of patients who developed grade 2-4 abnormality while on ART◦ Median follow-up: 3.8 years

Parameter

% With Abnormality

All patients 18-39 years 40-49 years ≥50 years P value

TC or LDL 26.6 21.0 26.4 34.0 .04

Glucose 9.7 6.0 11.4 14.4 <.001

Creatinine 5.2 3.2 5.8 8.3 NR

Silverberg MJ. Arch Intern Med. 2007;167(7):684-691. TC, total cholesterol; LDL, low-density lipoprotein

Older Patients More Likely to Achieve HIV-1 RNA <500 Copies/mL

Kaiser Permanente study compared patients 40-49 yoa and ≥50 yoa to patients 18-39 yoa Patients >50 yoa more likely to achieve HIV-1 RNA <500 copies/mL vs patients 18-39 yoa, even when adjusting for

comorbidities Adherence major advantage for older patients

Silverberg MJ. Arch Intern Med. 2007;167(7):684-691.

Age ≥50 years

Age 40-49 years

CI, confidence interval;HR, hazard ratio; yoa, years of age

1.3

0.6

0.7

0.8

0.9

1.0

1.1

1.21.15

0.97

0.95

1.03

0.97

1.15

0.97

1.07

HR

(95%

CI)

Model: Age Age + adherence

Age + Charlson comorbidity

All predictors

Immunologic Response Slower in Patients Aged 50 Years or Older Monthly CD4 T-cell count increases significantly

lower in patients ≥50 years of age

Grabar S. AIDS. 2004;18(15):2029-2038.

Mean CD4 T-Cell Count Increase/Month, cells/mm3

Within First 6 Months of ARTa After 6 Months of ARTa

Age <50 years

Age ≥50 years

Age <50 years

Age ≥50 years

BL HIV-1 RNA <5 log10 copies/mL

17.3 14.1 11.1 9.8

BL HIV-1 RNA ≥5 log10 copies/mL

42.9 36.9 17.9 15.6aP<.0001 for <50 yoa vs ≥50 yoa in all subgroups.

yoa, years of age




Overview

Cardiovascular Disease CVD is presently the #1 cause of death in the US and

worldwide◦ An estimated 80.7 million (1 in 3) Americans have 1 or

more types of CVD Approximately 38 million of those patients are ≥ 60 years of

age◦ CVD accounted for 36.3% of all deaths in the US as of

2004

Rosamond W, et al. Circulation. 2008;117(4):e25-e146.

Source: NCHS and NHLBI. Note: No comparability ratios were applied

400

450

500

550

79 80 85 90 95 00 05

Years

Dea

ths

in T

ho

usa

nd

s

Males Females

CVD Disease Mortality Trends for Males and FemalesUnited States: 1979-2005

These data include coronary heart disease, heart failure, stroke and hypertensionSource: NCHS and NHLBI

15.9

37.9

73.3

7.8

79.385.9

38.5

72.6

0

10

20

30

40

50

60

70

80

90

100

20-39 40-59 60-79 80+

Per

cen

t of P

op

ula

tion

Men Women

CVD Prevalence in adults > 20 Years by Age and Sex (NHANES: 2005-2006)

Source: NCHS and NHLBI.

44.0 41.523.4

60.740.0 32.8

110.0

140.9

0

50

100

150

200

Coronary HeartDisease

Stroke Lung Cancer Breast Cancer

Per

100

,000

Pop

ulat

ion

White Females Black Females

Age-adjusted Death Rates Selected Diagnoses in Women

Friis-Møller N, et al. AIDS. 2003;17:1179-1193.

Prevalence of Cardiac Risk Factors at Baseline in the D:A:D Study

Family Historyof CHD

PreviousHistory of CHD

CurrentSmoking

BMI> 30 mg/m2

HTN DiabetesMellitus

↑ TotalCholesterol

↑ TG0

10

20

30

40

50

60

Perc

enta

ge o

f Coh

ort W

ith

Risk

Fac

tor a

t Bas

elin

e

Large cohort of HIV-infected patients on HAART followed longitudinally (N = 23,468) 18,962 (80.8%) with previous ART exposure; 4506 (19.2%) antiretroviral naive

11.7

4.87.2

2.81.5

56.2

32.3

21.1

D:A:D: Risk Factors for CHD in an HIV-Infected Population

Multivariable Poisson model adjusted for age, sex, BMI, HIV risk, cohort, calendar year, race, family hx CVD, smoking, previous CVD event, TC, HDL, HTN, DM.

Relative Rate of MI (95% CI)

WorseBetter

0.1 0.5 1 5 10

RR: 1.86 (1.31-2.65)Diabetes mellitus (yes vs no)

RR: 1.30 (0.99-1.72)Hypertension (yes vs no)

Family history

Previous CVD

Male sex

Age per 5 yrs older

Smoking

RR: 1.40 (0.96-2.05)

RR: 2.92 (2.04-4.18)

RR: 2.13 (1.29-3.52)

RR: 4.64 (3.22–6.69)

RR: 1.32 (1.23-1.41)

Friis-Møller, et al. N Engl J Med. 2007;326:1723-1735.

Risk Score Results

Age 50 50 30 50 50 50 50 50 50

Sex M F M M M M M M M

Total cholesterol, mg/dl 280 280 280 230

200 280 280 280 280

HDL cholesterol, mg/dL 44 44 44 44 44 35 44 44 44

Smoker No No No No No No No Yes Yes

SBP, mm Hg 125 125 125 125 125 125 150 125 150

On antihypertensive meds No No No No No No No No No

Risk score 9% 3% 1% 6% 5% 11%

11%

22% 27%

Predicting MI Risk Using Framingham Equation

National Cholesterol Education Program. Available at: http://hin.nhlbi.nih.gov/atpiii/calculator.asp. Accessed November 16, 2007.

Framingham Predicted CHD Risk High Risk (> 25% over 10 years or DM)

HIV+ men: 17%HIV+ women: 12%

Persons with income <$10,000 were more than twice as likely to have moderate/high CHD risk

In CPCRA First Study, Blacks had greater risk for cardiovascular disease◦ Unadjusted HR = 3.83 (1.28-11.5)◦ HR (after adjustment) = 2.64 (1.04-6.67)

Kaplan RC. Clin Inf Dis 2007; 45:1074-1081Tedaldi EM. JAIDS 2008;47: 441-448.

D:A:D 2003: Use of ART Increases MI Risk

126 patients had an MI during 36,199 PY Incidence of MI According to the

Duration of Exposure to ARTRR

95% CI

P value

Exposure to ART

1.26 1.12–1.41 <.001

Age (per 5 years)

1.38 1.26 – 1.50 <.001

History of smoking

2.17 1.30 – 3.62 .007

Previous history of CVD

5.813.51–9.72

<.001

Male sex 1.99 1.04 – 3.79 .04

DAD Study Group. New Engl J Med. 2003;349(21):1993-2003.

None <1 1-2 2-3 3-4 >40

1

2

3

4

5

6

7

8

Inci

denc

e pe

r 100

0 PY

Exposure (yr)No. of eventsNo. of PY

35714

94140

144801

225847

317220

478477

DAD Study Group. New Engl J Med. 2007;356(17):1723-1735.

8.0

4.0

2.0

1.0

0.5

Adju

sted

Rel

ative

Rat

e

Exposure (Years)0 <1 1 - 2 2 - 3 3 - 4 4 - 5 5 - 6 > 6

PI NNRTI

D:A:D 2007: ART Class and MI Risk

DAD 2009: PI and NNRTI Risk of MI

PIs NNRTIs1.2

1.13

1

0.9 IDV NFV LPV/r SQV NVP EFV#PYFU: 68,469 56,529 37,136 44,657 61,855 58,946#MI: 298 197 150 221 228 221

RR per year 95% CI

Lundgren J, et al. 16th CROI; 2009; Montreal. Abstract 44LB.

Cumulative Exposure to Each Drug

D:A:D 2009: NRTIs and Risk of MI

1.9

1.5

1.2

1

0.8

0.6

RR 95% CI

ZDV ddI ddC d4T 3TC ABC TDF#PYFU: 138,109 74,407 29,676 95,320 152,009 53,300 39,157#MI: 523 331 148 405 554 221 139

**

Lundgren J, et al. 16th CROI; 2009; Montreal. Abstract 44LB.

Recent Exposure* Cumulative Exposure

• Overall 580 MIs in 33,308 patients (178,835 PY of observation)

Recent use=current or within last 6 months. **Not shown (low number of patient currently on ddC)

No further adjustmentb

Adjusted also for:Latest CD4 count

Latest VLLatest lipids

Latest blood pressureDiabetes

Fat loss/gainLatest glucose

a. Still using or stopped within last 6 months.b. All data depicted also adjusted for demographic factors, calendar year, cohort, CV risk factors unlikely to be

modified strongly by ART use, and cumulative exposure to other ARVs.

Adjusted Relative Rate (95% CI)

Relative Rate of MI Associated With Recenta ABC Use

1.90

0.5 1 1.5 2 2.5 3

D:A:D Study Group. Lancet. 2008;371:1417-1426.

Predicted 10-year CHD risk

Recent ABC

No recent ABC35

30

25

20

15

10

5

0

Overall Low Moderate High Not known

Rates of MI for Recenta Use of ABC by Predicted 10-year CHD Risk

D:A:D 2008: Recent ABC Use Is Associated With Increased Risk of MI

hsCRP and MI Risk in Healthy Men

0

0.5

1

1.5

2

2.5

3

3.5

C-Reactive Protein Concentration (mg/liter)<0.55 0.56 – 1.14 1.15 – 2.10 >2.11

Rela

tive

Risk

of M

I

Ridker et al. N Engl J Med 1997;336:973-979

Adjusted for other biomarkers

Marker RR(95% CI) hsCRP 1.4(1.1-

1.9)SAA 1.1(0.8-1.4)sICAM-1 1.1(0.9-1.4)IL-6 0.9(0.7-1.2)Chol:HDL 1.4(1.1-1.7)

Adjusted for other biomarkers AND traditional CVD Risk Factors

Marker RR(95% CI)

hsCRP 1.5(1.1-2.1)

SAA 1.1(0.8-1.6)sICAM-1 1.1(0.8-1.4)IL-6 0.8(0.6-1.1)Chol:HDL 1.4(1.1-1.9)

Adjusted Relative Risk of CV Events by Increase of 1 Quartile in Biomarker

Ridker et al. N Engl J Med 2000;342:836-843

Biomarker Levels in Untreated HIV-Infected and Uninfected Persons

Biomarker HIV+ GroupN=32

Median (IQR)

HIV- GroupN=29

Median (IQR)

P Value

hsCRP μg/mL 1.94 (0.82-5.84) 1.46 (0.68-5.04) 0.49IL-6 pg/mL 1.79 (1.32-5.35) 1.26(0.72-2.14) 0.01sICAM-1 ng/mL 312(251-488) 225(168-279) <0.01D-dimer μg/mL 0.39(0.19-0.67) 0.19(0.13-0.38) 0.02

Baker et al. J Inf Dis 2010;201:285-292

SMART Trial Study Design

Virologic Suppression (VS) Continuous ART throughout follow-up

Drug Conservation (DC) ART stopped/deferred until CD4+ < 250 cells/mm3 then episodic ART to increase CD4+to > 350 cells/mm3

HIV-1-infected patients with CD4+ cell count > 350 cells/mm3

No. of Patients With EventsParameter RR (95% CI)

Severe complications 114 1.5

CVD, liver, or renal deaths

Nonfatal CVD events

31

63

1.4

1.5

Nonfatal hepatic events

Nonfatal renal events

14

7

1.4

2.5

1.0 10.00.1 Favors TI Favors CT

Risk of Com

plicationsSMART: HIV Progression With Continuous HAART vs Interruption

CD4-guided drug conservation strategy associated with significantly greater disease progression or death compared with continuous viral suppression: RR: 2.5 (95% CI: 1.8-3.6; P < .001)

El-Sadr W, et al. N Engl J Med. 2006;355:2283-2296.

Baseline Biomarkers and All Cause Mortality

Kuller L et al. PLoS 2008;10:1496-150

Biomarker OR(4th/1st

quartile)P-value OR(4th/1st

quartile)P-

value

Hs-CRP 2.0 0.05 3.1 0.02

IL-6 8.3 <0.0001 12.4 <0.0001

Amyloid A 2.2 0.07 3.1 0.05

D-dimer 12.4 <0.0001 41.2 <0.0001

Unadjusted Adjusted*

‡

* Adjusted for age, race, ART, HIV RNA level, CD4+ cell count, smoking, BMI, prior CVD, diabetes, antihypertensive and/or lipid lowering agent use, total/HDL cholesterol, Hepatitis B or C coinfection

Levels of Biomarkers Associated with Cardiovascular Disease in SMART

Duprez ACC 2009

Biomarker OR(95% CI) P-value

Hs-CRP 2.1 (1.3-3.5) 0.005

IL-6 3.3 (1.9-6.0) <0.0001

D-Dimer 2.5 (1.4-4.3) 0.002

Adjusted

‡

Increased Levels of Circulating Endothelial Activation Markers in Patients With HIV

Circulating markers of inflammation and endothelial activation were significantly elevated in treatment-naïve HIV+ patients compared with healthy HIV- controls

Initiation of ART in HIV+ patients reduced or normalized the levels of the majority of these markers after 3 months, an effect that remained at 12 months

HIV- Controls HIV+ Patients

Baseline Baseline 3 months of ART

sICAM-1*‡ 144 ±12 ng/mL 296 ±24 ng/mL 248 ±12ng/mL

hsCRP* 6665 ±2063 ng/mL

28,060 ±5530 ng/mL

14,708 ±2358 ng/mL

sVCAM-1† 876 ±39 ng/mL 957 ±40 ng/mL 766 ±33 ng/mL

E-selectin† 15.8 ±1.2 ng/mL

17.9 ±1.1 ng/mL 15.1 ±0.8 ng/mL

*P<0.001, HIV+ patients vs HIV- controls; †P<0.001, HIV+ patients baseline vs 3 months ART; ‡P>0.05, HIV+ patients baseline vs 3 months ART.Kristoffersen et al. 15th CROI. 2008; abstract #953.

hsCRP Levels and HAART

pre-HAART 42 mo HAART 73 mo HAART0

1

2

3

4

5

6

hsCR

P co

ncen

trati

on (μ

g/m

L)

P=0.0207 for trend

Henry K et al. AIDS 2004;18:2435-2437

SMART Study: D Dimer

Suggests HIV viremia

effect on endothelium, leading to increased tissue factors and initiation of coagulation cascade

*DC pts on ART at BL with HIV RNA ≤400 c/mL

μg/m

L≤400 401–

10,00010,000–50,000

>50,0000

0.1

0.2

0.3

00.04

0.11

0.28

Month 1 HIV RNA (c/mL)

Change in D-Dimer* (BL to 1 mo)P=0.0005 for trend

Kuller L, et al. PLoS 2008;10:1496-1508

Change in Log IL-6 (pg/mL) and HDL (μmol/L) from Baseline to 1 Month*

≤ 400 401-10,000 10,000-50,000 >50,000

Month 1 HIV RNA Level (copies/mL)

∆ IL

-6 (p

g/m

L)

P<0.0001 for trend

∆ H

DL

(μm

ol/L

)

* DC patients on ART at baseline with HIV RNA ≤ 400 copies/mL

∆ IL-6

∆ HDL P=0.0003 for trend

SMART/INSIGHT: Duprez et al, CROI, 2009

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

Increased Levels of Circulating Markers of Endothelial Activation in Patients With HIV Circulating inflammatory markers were significantly elevated in treatment-

naïve HIV+ patients compared with healthy HIV- controls Initiation of antiretroviral therapy in HIV+ patients reduced levels of the

majority of these markers after 3 months; effect remained at 12 months

HIV- Controls HIV+ Patients

Baseline Baseline 3 months of ART

sICAM-1*‡ 144 ±12 ng/mL 296 ±24 ng/mL 248 ±12ng/mL

hsCRP* 6665 ±2063 ng/mL 28,060 ±5530 ng/mL 14,708 ±2358 ng/mL

sVCAM-1† 876 ±39 ng/mL 957 ±40 ng/mL 766 ±33 ng/mL

E-selectin† 15.8 ±1.2 ng/mL 17.9 ±1.1 ng/mL 15.1 ±0.8 ng/mL

*P<0.001, HIV+ patients vs HIV- controls; †P<0.001, HIV+ patients baseline vs 3 months ART; ‡P>0.05, HIV+ patients baseline vs 3 months ART.Kristoffersen et al. 15th CROI. 2008; abstract #953.

A5152s: VL Decrease Associated With Improved Endothelial Function HIV infection itself affected

endothelial function◦ Baseline FMD: 3.7%

FMD improved during HAART No consistent correlations

between changes in FMD and changes in any lipids or glycemic parameter

Improvement in FMD significantly associated with decrease in VL at Week 24 ◦ No relationship with

baseline VL

Med

ian

Chan

ge in

FM

D F

rom

Bas

elin

e, %

LPV/NRTI EFV/NRTI EFV/LPV0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Overall

Week 4 Week 24

* * *

†

*P < .01 compared with baseline.†P < .01 compared with baseline and within group.

Torriani F, et al. Lipodystrophy Workshop 2007. Abstract O-18. Torriani F, et al. IAS 2007. Abstract WEAB302.

Needs Formatting

Abnormal Endothelial Function and hsCRP in HIV-infected Persons Abnormal endothelial function is strong risk factor for

cardiovascular disease (CVD) Endothelial function impaired in virologically suppressed

HIV-1 infected persons (3.5%) compared with HIV-uninfected controls (5.3%)

Higher hsCRP levels associated with impaired flow mediated dilation in HIV-infected persons on ART with suppressed HIV RNA viral loads (p=0.03)

Age more predictive of abnormal flow mediated dilation in HIV-uninfected controls (p=0.004)

Hsue et a .lCROI 2010; San Fracisco. Abstract 708.

Possible “Treatment” for Elevated Biomarkers Aspirin Angiotensin-converting enzyme inhibitors Eicosapentaenoic acid Dexamethasone Anti-cytokine monoclonal antibodies Statins

Why Should Statins Affect Biomarker Levels and Should we Care?

Blocking HMG-CoA reductase reduces mevalonate, a precursor to geranylpyrophosphate and farnesylpyrophosphate, necessary to turn on IL-6 gene

IL-6 stimulatesrs CRP in human hepatocytes Animal models have shown that statins decrease LPS

induced IL-6, CRP, and TNF-α

Diomede L et al. Aterioscler Thromb Vasc Biol. 2001;21:1327-1332Kleemann R et al. Circulation 2003;108:1368-1374




Overview

• Multiple studies have found increased prevalence of osteoporosis and osteopenia in HIV-infected persons compared with uninfected persons

• Meta-analytical review of studies – 67% HIV infected persons had reduced BMD (OR 6.4)– 15% HIV+ had osteoporosis (OR 3.7)

Bone Mineral Density in HIV-Infected Persons

Brown et al AIDS 2006;20:2165-2174

Triant VA et al. J Clin Endocrinaol Metab. 2008;93(9):3502.

Women Men

Fracture Prevalence Higher in HIV Fr

actu

re P

reva

lenc

e/10

0 Pe

rson

s

0.5

1.0

1.5

2.0

2.5

3.0

0

HIVNon-HIV

P=0.002

P=0.01

P=0.53

P=0.01

Any Vertebral Hip Wrist

Frac

ture

Pre

vale

nce/

100

Pers

ons

0.5

1.0

1.5

2.0

2.5

3.0

0

HIVNon-HIV

P<0.0001

P<0.0001P=0.001

P=0.001

Any Vertebral Hip Wrist

• Population: 8,525 HIV+ and 2,208792 HIV-• Patients with fracture: 245 HIV+ and 39,073 HIV-• Overall fracture prevalence (per 100 persons): 2.87 HIV+ and 1.77 HIV-

Effects of HIV on Bone Metabolism

HIV-1 p55 gag and gp120◦Significantly decrease calcium deposition in vitro1

◦Reduce RUNX-2 activity in vitro1

gp120 increases PPARγ activity1

gp120 (100 ng/ml) induces RANKL2

1. Cotter EJ et al. AIDS Res Hum Retroviruses. 2007;23(12):1521-1529.2. Fakruddin JM et al. J Biol Chem. 2003;278:48251-48258.

RUNX-2 (Runt-related transcription factor-s) promotes osteoblast differentiation.PPARγ (Peroxisome proliferator-activated receptor gamma) promotes adipogenesis.RANKL (Receptor Activator for Nuclear Factor κ B Ligand), activates osteoclasts.

Changes in Hip Bone Mineral Density with Antiretroviral Therapy

Intermittent (Fracture 0.03/100 PY)Continuous (Fracture 0.13/100 PY)

n = 109 86 51 9 n = 95 75 47 15

Est. diff.: 1.3 1.7 1.0 2.5P values: .002 .005 .27 .21

Gallant et al. JAMA 2004, 292:191. Grund B et al. ICAAC/IDSA 2008. Abstract 2312a.

d4T + 3TC + EFVTDF + 3TC + EFV

n=301 267 246 226 205 185 181 n=299 261 234 221 209 193 185

-4

-3

-2

-1

0

1

0 1 3 4Years

Chan

ge F

rom

Ba

selin

e (%

)

2

Gilead 903 Study SMART Study

-8

-6

-2

0

4

8

2

6

Baseline 24 48 72 96 120 144Weeks

P=0.06-4Ch

ange

Fro

m

Base

line

(%)

Association of Osteoporosis with Antiretroviral Therapy

Brown TT et al. AIDS. 2006, 22:2168.

Antiretroviral Therapy Overall Protease Inhibitor Therapy

Odds ratio0.01 100

Study

Amiel (2004)

Bruera (2003)

Garcia (2001)

Knobel (2001)

Knishi (2005)

Mededdu (2004)

Vescini (2003)

Overall (95%CI)

Odds ratio (95%CI)

2.41 (0.77, 7.58)

4.81 (0.60, 38.74)

1.60 (0.13, 19.84)

2.68 (0.70, 10.33)

0.84 (0.03, 22.43)

11.00 (0.65, 187.76)

0.54 (0.05, 5.68)

2.38 (1.20, 4.75)

Odds ratio0.01 100

Odds ratio (95%CI)

0.61 (0.21, 1.72)

11.09 (0.57, 217.66)

1.18 (0.37, 3.78)

0.71 (0.11, 4.51)

1.57 (0.05, 43.79)

1.97 (0.47, 8.27)

2.63 (1.13, 7.03)

1.89 (0.23, 15.81)

3.25 (2.08, 9.83)

1.83 (0.35, 9.62)

1.24 (0.34, 4.52)

0.77 (0.15, 2.34)

1.57 (1.05, 2.34)

Study

Amiel (2004)

Brown (2004)

Bruera (2003)

Dolan (2004)

Huang (2002)

Knobel (2001)

Mededdu (2004)

Mondy (2003)

Nolan (2001)

Tebas (2000)

Vescini (2003)

Yiu (2005)

Overall (95%CI)

Caveat: Few studies adjusted for age or duration of infection

25-OH Vitamin D Deficiency Prevalent in HIV-Infection

1. Rodriguez M et al. AIDS Res Hum Retroviruses. 2009;25(1):9-14.2. Seminari E et al. HIV Med. 2005;6:145-150.3. Garcia Aparicio AM et al. Clin Rheumatol. 2006;25(4):537-539.

• 47% Boston outpatient HIV clinic (n=57)1

– Low Vitamin D intake in 31% < 50 years and 76% 51-70 years

– Low calcium intake in in 37% < 50 years and 71% 51-70 years

• 81% Italian HIV treatment-experienced patients (n=48)2

• 86% in Spanish cohort of men (n=30)3

– Mean 25,OH Vitamin D level 14.3 ng/ml in healthy controls vs.11.4 ng/ml (p=0.044)

Inflammatory marker Q1 Q2 Q3 Q4

CRP 13.5 13.7 16.5 17.4

IL-6 14.2 15.6 13.0 17.5

TNF 12.5 15.1 14.6 20.8†

IL-2sR 10.9 13.8 15.9 25.4§

IL-6sR 12.0 13.6 17.6 22.3‡§

TNF sRI 14.0 10.5 14.8 26.7‡§

TNF sRII 8.6 15.9 17.9 22.3

Cauley JA et al. J Bone Miner Res. 2007;22:1091.

Inflammatory Biomarkers Associated With Bone Fracture

† P<.05 from trend test.‡ P<.01 from trend test.§ P<.001 from trend test.

Incidence Rate (per 1000 Person-Years) of Fracture by Quartiles of Inflammatory

Cauley JA et al. J Bone Miner Res. 2007;22:1092.

Cumulative Nonspine Fracture by Highest Quartile Inflammatory Markers*

Years

0

4

8

12

16

20

% W

ith N

on-s

pine

Fra

ctur

e

0 81 2 3 4 65 7

2

6

10

14

18

2+

0 or 1

P = 0.0093 (log rank test)

*CRP, IL-6, TNFα




Overview

Incidence of Fatal Malignancies Among HIV Patients (N=23,437)

PYFU, person-years of follow-up

Monforte A. AIDS. 2008;22(16):2143-2153.ADM, AIDS-defining malignancies (n=112)

nADM, non-AIDS-defining malignancies (n=193)

Even

t Rat

e 1

,000

PYF

U

Age Group

<30 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-690

2

20

18

16

14

12

10

8

6

4

ADM, n=112nADM, n=193

Impact of Current CD4+ on Non-AIDS–Defining Cancer Risk

Retrospective database analysis of 19,280 HIV-infected patients; 202,313 HIV-uninfected patients

Silverberg M, et al. CROI 2010. Abstract 28. Table reproduced with permission.

Adjusted HR* HIV Infected CD4+ Cell Count, cells/mm3

< 200 201-499 ≥ 500 P Value

Any infection related 12.8† 5.9† 3.2† < .001

Anal 164.2† 83.1† 34.2† < .001

Hodgkin’s lymphoma 55.0† 11.0† 11.6† < .001

Oral/pharyngeal 3.1† 1.9‡ 0.8 .030

Any infection unrelated 1.8† 1.2 1.1 .002

Lung 2.1‡ 1.0 1.2 .083

Colorectal 2.2‡ 1.0 0.9 .050

*Adjusted for age, sex, smoking, overweight, alcohol/drug abuse, viral hepatitis; reference = uninfected cohort. †P < .001 relative to uninfected. ‡P < .05 relative to uninfected.

Temporal trends in US cohort - incidence of anal cancer (/100,000 PYs)◦ 19 (1992-95), 48.3 (1996-99), 78.2 (2000-2003)

Impact of ART on risk of malignant transformation ◦ ART was not associated with altered risk of cytological

progression or regression Oral HPV infection in HIV may enhance smoking

induced risk of oropharyngeal cancer Anal HPV infection may increase risk of HIV

transmission

HPV Cancers and HIV Transmission

Patel et al, Ann Intern Med 2008; Paramsothy et al, Obstet and Gynecol 2009; Chin-Hong et al, AIDS 2009;Gillison, Curr Opin Oncol 2009.

Risk of AIDS-related cancers decreased due to benefit of ART◦ Except HPV-induced genital cancers

HIV-infected population is aging◦ Risk of fatal non-AIDS-defining cancers increases 47% per 5 year older

age (i.e. >2-fold increase over a 10 year period Secondary cancers - may further increase the 47% estimate1

Immunodeficiency Chronic pro-oncogenic viral infections

e.g. HPV, EBV, viral hepatitis Other cancers (and associated therapy hereof)

e.g. bladder cancer after prostate cancer2; leukemia after NHL3

ART ?

Why Will Incidence of Cancers Increase in the Next 10 Years

1 D:A:D study group, AIDS 20082 Shirodkar et al, Curr Opin Urol 20093 Mudie et al, J Clin Oncol 2006

For 20 / 28 cancers examined there was significantly increased incidencein both groups – strongly suggesting a link with immunodeficiency

Standardized Incidence RatioHIV/AIDS Transplant

Lung 2.7 2.2Leukaemia 3.2 2.4Kidney 1.5 6.8Oesophagus 1.6 3.1Stomach 1.9 2.0

Meta-analysis: 444,172 people with HIV, 31,977 transplant patients

Grulich et al, Lancet 2007.

HIV and Risk of Non-AIDS Malignancies

Documents

Sally L. Hodder M.D. Professor of Medicine New Jersey Medical School – UMDNJ Newark, New Jersey