HIV, Co-morbidity and Ageing
“A good head and a good heart are always a
formidable combination”
Peter Reiss Director HIV Monitoring Foundation Professor of Medicine Division of Infectious Diseases & Department of Global Health Amsterdam Institute for Global Health and Development Academic Medical Center, University of Amsterdam
V Encuentro de Salud Pública 8 October 2015, Madrid, Spain
Disclosures Dr. Reiss reports having received:
Unrestricted investigator-initiated grant support
through his institution from Gilead Sciences,
Janssen Pharmaceutica NV., Merck&Co, Bristol-
Myers Squibb, ViiV Healthcare and Boehringer-
Ingelheim
Honoraria through his institution from Gilead
Sciences and Janssen Pharmaceutica NV. for
scientific advisory board and data safety monitoring
committee participation
Changing Age Structure of Population with HIV
in Care in The Netherlands
42% older than 50 yrs; 14% older than 60 yrs
As expected co-morbidity burden & use of
co-medication in HIV increases with ageing
0
20
40
60
80
100
Four or morecomorbidities
Three comorbidities
Two comorbidities
One comorbidity
% o
f p
art
icip
ants
<50 years 50-64 years 65+ years
Agegroups
No comorbidity
Comedications
Comorbidities
n=5761 n=2233 n=450
0
20
40
60
80
100
Four or morecomedications
Three comedications
Two comedications
One comedication
% o
f p
art
icip
ants
No comedication
Swiss
CohortStudy
H I VSwiss
CohortStudy
H I V
Hasse B. et al. Clin Infect Dis 2011 53;1130-1139
Modelling the Changing Age-structure
of PLWHIV in the Netherlands • Median age will increase from 43.9 years in 2010 to 56.6 years in
2030
• Proportion of HIV-patients aged ≥ 60 will increase from 8% to 39%
and aged ≥ 70 years from 8% to 12%
Smit M, et al, on behalf of the ATHENA observational cohort; Lancet Infect Dis 2015
Deeks SG, et al. BMJ 2009; 338:a3172
Many chronic diseases of ageing have been shown to be more common in those with HIV, even after adjustment for ART use and traditional (lifestyle-related) risk factors
Chronic liver
disease
Neurocognitive decline
Non-Aids cancers
Chronic kidney disease
Osteoporosis &
Fragility fractures
Cardiovascular
disease
Frailty Diabetes mellitus
COPD
Do HIV-positive persons age faster than HIV-uninfected persons?
Chronic disease drivers (known and suspected) acting in concert in HIV
ART
Toxicity
Host
Clinical
Chronic
Co-morbidity HIV
Persistent
Immune Dysregulation
& Inflammation
in treated
HIV disease
Deeks SG, et al. BMJ 2009; 338:a3172
AGEING
Lifestyle (smoking etc)
Genetic
Are these age-related chronic conditions
just Accentuated or also Accelerated?
Accentuated & Accelerated risk
Condition occurs more often and
at younger age among those with
HIV than among
HIV-uninfected comparators
Accentuated risk
Condition occurs at the same
age but more often in those
with HIV than among
HIV-uninfected comparators
Shiels MS. Age at Cancer Diagnosis among persons with AIDS in the US. Ann Intern Med 2010
• Prevalence and incidence of
age-associated non-communicable comorbidities (AANCC)
and their risk factors in persons ≥45 yrs
• Started October 2010
• Participants:
HIV-1-infected: from the HIV outpatient clinic at the
Academic Medical Center (Amsterdam)
HIV-1-uninfected: from the Amsterdam Public Health Service
sexual health clinic, and the ongoing
Amsterdam Cohort Studies on HIV/AIDS
Comorbidity and Ageing with HIV A prospective comparative cohort study
Populations’ Age Structure
HIV neg
(n=524)
HIV pos
(n=540) p-value
Age (years) 52.1 (47.9-58.3) 52.9 (48.3-59.6) 0.20
Male gender 85.1% 88.1% 0.15
Dutch 81.3% 72.2% <0.001
MSM 69.7% 73.9% 0.125
Time since HIV-1 diagnosis (yrs) 12.1 (6.2-17.1)
Mean CD4 count at enrollment (cells/mm3) 565 (435-745)
Nadir CD4 count (cells/mm3) 180 (78-260)
Viral load > 200 at or within 4 mos prior to
enrolment among cART-treated participants 1.5%
Prior clinical AIDS 31.3%
On cART
95.7%
• 79.1% started Rx-naive
• 20.9% started ART-exp.
Years since ART was first initiated (yrs) 10.4 (4.4-14.5)
Duration of viral load < 200 (since last > 200
) (yrs) 5.8 (2.4 – 10.2)
Known cumulative duration CD4 < 200(mos) 0.8 (0.0 – 9.6)
Data presented as median (IQR) or percentage as appropriate.
P-value represents Wilcoxon Rank Sum or Chi2 as appropriate
Demographic and HIV characteristics
Schouten J et al. Clin Infect Dis. 2014
Comorbidity risk factors
HIV neg
(n=524)
HIV pos
(n=540) p-value
Smoking status
currently / ever (%)
24.6 / 38.9%
32.0 / 35.0%
0.007 /
0.23
Smoking (packyears, smokers only) 15.0 (4.5-28.8) 22.2 (7.8-36.8) <0.001
Severe alcohol use 7.3% 4.8% 0.098
Daily to monthly use of:
cannabis
cocaine
ecstasy
11.6%
2.9%
8.6%
13.5%
3.7%
4.3%
0.356
0.442
0.004
BMI (kg/m2) 24.5 (22.8-27.0) 24.2 (22.3-26.6) 0.019
Blood pressure systolic (mmHg) 133 (125-143) 135 (126-147) 0.006
Blood pressure diastolic (mmHg) 79 (72-85) 81 (75-89) <0.001
Data presented as median (IQR) or percentage as appropriate.
P-value represents Wilcoxon Rank Sum or Chi2 as appropriate Schouten J et al. Clin Infect Dis. 2014
Age-associated Noncommunicable
Comorbidity Prevalence
HIV neg
(n=524)
HIV pos
(n=540) p-value
≥1 AANCC* (%) 61.8% 69.4% 0.009
Number of AANCC (mean (SD)) 1.0 (0.95) 1.3 (1.14) <0.001
Schouten J et al. Clin Infect Dis. 2014
Comorbidity in relation to age
Schouten J et al. Clin Infect Dis. 2014
Osteopenia/osteoporosis in 3 bone locations
K. Kooij et al, J Infect Dis, 2014
Hypertension
Prevalence of hypertension
0
20
40
60
80
100
Pre
vale
nce
of
hype
rte
nsio
n (
%)
HIV-infected HIV-uninfected
Antihypertensives + / HT +
Antihypertensives + / HT -
Antihypertensives - / HT +
Normotension
Hypertension, measured Hypertension, treated
55% 69%
22%
17%
23% 14%
R. Van Zoest et al 16th Int Wkshp on Comorb and ADR in HIV, Philadelphia, October 2014
More frailty and pre-frailty at any age in HIV+ participants
HIV- HIV+ HIV- HIV+ HIV- HIV+ HIV- HIV+ HIV- HIV+
K.Kooij et al 8th Netherlands Conference on HIV Pathogenesis, Epidemiology, Prevention and Treatment, Amsterdam, November 2014
All frailty factors more prevalent in HIV+ participants
K.Kooij et al 8th Netherlands Conference on HIV Pathogenesis, Epidemiology, Prevention and Treatment, Amsterdam, November 2014
Neurocognitive impairment
AIDS. 2015 Mar 13;29(5):547-57
Comorbidity in relation to age
Schouten J et al. Clin Infect Dis. 2014
baseline 2-years
% %
Comorbidity Burden After 2 Year Follow-up 436 HIV-pos en 437 HIV-neg
mean # comorbidities 1,23 (baseline) 1,26 (follow-up) mean # comorbidities 0,84 (baseline) 0,84 (follow-up)
Risk Factors Associated with Comorbidity
Nr of
AANCC
Hypertension CVD Low
BMD
Frailty
Recognized
risk factors
+ + + + +
HIV +
(- once
time spent
with low
low CD4
accounted
for)
+
( WHR;
both waist&
hip circumf. )
+
+
(
body
weight)
+
( (history of)low
BMI)
ART
duration
- - - - -
Specific ART
exposure
+/- (RTV) Prior d4T +(RTV) +(RTV) +/- (PI)
AANCC: Age Associated NonCommunicable Comorbidity
Chronic disease drivers, known and suspected
Deeks SG, et al. BMJ 2009; 338:a3172
AGING
ART
Toxicity
Host
Clinical
Chronic
Co-morbidity HIV
Persistent
Immune Dysregulation
& Inflammation
in treated
HIV disease
Lifestyle (smoking etc)
Genetic
HIV-infected individuals who are ART-naïve with
CD4+ count > 500 cells/mm3
Immediate ART Group
Initiate ART immediately
following randomization
N=2,326
Deferred ART Group
Defer ART until the CD4+ count
declines to < 350 cells/mm3 or
AIDS develops
N=2,359
Primary composite endpoint, target = 213
• Serious AIDS or death from AIDS
• Serious Non-AIDS Events and death not attributable to AIDS o CVD, ESRD, decompensated liver disease, & non-AIDS defining cancers
Early ART is associated with less inflammation during ART
Will this result in benefit?
Strategic Timing of AntiRetroviral Treatment (START) Study
Slide courtesy of Steve Deeks
Strategic Timing of AntiRetroviral Treatment
(START) Study
No. of
Participants
Type of event Imm.
ART
Def.
ART
Serious AIDS 14 50
Serious non-AIDS 29 47
Total* 42 96
* One participant in each group had both a Serious AIDS
and a Serious Non-AIDS Event
26 Lundgren et al, IAS 2015, Vancouver July 2015
Chronic disease drivers, known and suspected
Deeks SG, et al. BMJ 2009; 338:a3172
AGING
ART
Toxicity
Host
Clinical
Chronic
Co-morbidity HIV
Persistent
Immune Dysregulation
& Inflammation
in treated
HIV disease
Lifestyle (smoking etc)
Genetic
“Well treated HIV-infected individuals may lose more life years
through smoking than through HIV.
Excess mortality associated with smoking increases markedly with
age. Therefore, increases in smoking-related mortality can be
expected as the treated HIV-infected population ages. Interventions
for smoking cessation should be prioritized.”
The Host and Lifestyle:the importance of smoking
Helleberg M et al. Clin Infect Dis. 2013;56:727-734 Helleberg et al. AIDS 2015
ARTCohort Collaboration
ARTCohort Collaboration
Chronic disease drivers, known and suspected
Deeks SG, et al. BMJ 2009; 338:a3172
AGING
ART
Toxicity
Host
Clinical
Chronic
Co-morbidity HIV
Persistent
Immune Dysregulation
& Inflammation
in treated
HIV disease
Lifestyle (smoking etc)
Genetic
ART has clearly become less toxic, but…
Reasons for modifying treatment within 3 years of starting cART
it remains amongst the most common reasons for modifying treatment
http://www.hiv-monitoring.nl/english/research/monitoringrapporten/
ARV toxicities may accentuate the clinical expression of certain co-morbidities Some examples:
Some PI’s
ABC (?)
TDF ATV/r,LPV/r,(DRV/r?)
GS-US-292-0109 Switch to E/C/F/TAF in Virologically Suppressed Adults
All patients
– HIV-1 RNA <50 copies/mL for ≥96 weeks on stable TDF-based regimen
– Estimated GFR >50 mL/min
E/C/F/TAF = EVG 150 mg, COBI 150 mg, FTC 200 mg, TAF 10 mg
E/C/F/TDF = EVG 150 mg, COBI 150 mg, FTC 200 mg, TDF 300 mg
*Boosted by RTV or COBI
35
Primary Endpoint
HIV-1 RNA <50 c/mL
Week 0
Switch to E/C/F/TAF
Continue TDF-Based
Regimen
96 48
Virologically
Suppressed
Adults
E/C/F/TDF
(n=459)
EFV/FTC/TDF
(n=376)
Boosted* ATV + FTC/TDF
(n=601)
Randomized (2:1), active-controlled,
open-label study
n=959
n=477
1,79
-0,28
-3
-2
-1
0
1
2
3
4
Baseline Week 24 Week 48
GS-US-292-0109 DXA Scan Results: Spine BMD
Regardless of prior treatment regimen, differences between arms were statistically significant
More than 2% difference between the arms at Week 48 36
Me
dia
n %
Ch
an
ge
in
BM
D (
Q1
, Q
3)
E/C/F/TAF
TDF-Based Regimen
Change From Baseline to Week 48 All Participants (N=1,369)
p <0.001
1,37
-0,26
-2
-1
0
1
2
3
Baseline Week 24 Week 48
GS-US-292-0109 DXA Scan Results: Hip BMD
37
Change From Baseline to Week 48 All Participants (N=1,354)
Me
dia
n %
Ch
an
ge
in
BM
D (
Q1
, Q
3)
p <0.001
E/C/F/TAF
TDF-Based Regimen
Regardless of prior treatment regimen, differences between arms were statistically significant
More than 1.6% difference between arms at Week 48
Mills, et al, IAS 2015, Vancouver July 2015
-21 -18
-33
-52
10 9
18 19
-60
-50
-40
-30
-20
-10
0
10
20
30
UPCR UACR RBP: Cr Ratio B2MG: Cr Ratio
Me
dia
n %
Ch
an
ge
GS-US-292-0109 Renal Safety Results
Statistically significant improvements for participants who switched from either E/C/F/TDF or from
boosted ATV + FTC/TDF
Serum creatinine (p <0.001); eGFR (p <0.001)
Fractional excretion of phosphate, FEPO4 (p=0.05); fractional excretion of uric acid, FEUA (p <0.001)
Changes began by Week 2 and persisted to Week 48
38 UPCR: urine protein: creatinine ratio; UACR: urine albumin: creatinine ratio; RBP, retinol-binding protein; β-2-m:Cr , beta-2 microglobulin.
E/C/F/TAF
TDF-Based
Regimen
RBP:Cr β-2-m:Cr UPCR UACR
Tubular Proteinuria
Each difference between treatment arms
was statistically significant (p <0.001).
Mills, et al, IAS 2015, Vancouver July 2015
Do HIV-positive persons age faster than
HIV-uninfected persons?
vs.
Chronic disease drivers (known and suspected) act in concert
ART
Toxicity
Host
Clinical
Chronic
Co-morbidity
AGING
Lifestyle (smoking etc)
Genetic
May HIV and ART in Addition Interact with Biological Aging?
HIV
Persistent
Immune Dysregulation
& Inflammation
in treated
HIV disease
Hallmarks of Biological Aging
Lopez-Otin et al Cell 2013 153, 1194-1217 Torres RA & Lewis W, Lab.Investigation 2014;94:120-28
ART (nRTI/PI)
HIV & ART (nRTI)
HIV? &ART?
ART(nRTI/PI)
HIV & ART (nRTI/PI)
ART (PI)
HIV & ART (PI)
HIV
ART (PI)
Several of these may be affected by HIV and/or ART
The COHORTS
POPPY: ‘Pharmacokinetic
and Clinical Observations in
People over Fifty’
Status: • Recruited over 900 subjects
• 500 +ve over 50 • 200 +ve under 50 • 200 controls over 50
• Recruitment continue until end 2015 • Expect recruit 2000 subjects • First output last month at BHIVA meeting
Status: • Fully recruited and in follow up phase
• 598 +ve over 45 • 550 controls over 45
• Several outputs from this cohort including 3 publications
AMSTERDAM LONDON
COBRA: the clinical studies are run as sub-studies of POPPY and AGEhIV: • Collecting the extra information required • Whilst utilising the existing infrastructure
• FP7 project of 4 year duration with 12 partners from 6 countries • Primary research question: are HIV-infected patients on successful cART
prone to develop AANCC at an earlier age (accelerated ageing) ? • Establish link between HIV and AANCC:
o longitudinal HIV cohort studies in Amsterdam and London o biomarkers and neuro-imaging studies
• Elucidate causative link between HIV and AANCC o “Humanised Immune System” (HIS) mouse model
• Clarify pathogenic mechanisms underlying link between HIV and AANCC o Promising biomarkers, including those coming out of the FP7
MARK-AGE project
Summary of the COBRA project
C3NL
Neuroimaging modalities
T1-weighted
Diffusion Tensor
Imaging (DTI)
FLAIR T2-weighted Proton density
Voxel-based
morphometry Cortical thickness
C3NL
Brain age - Methods
C3NL
Brain age – Preliminary results
• Group comparisons of PAD score
MARK-AGE Project
1 April 2008 – 30 September 2013
(HEALTH-F4-2008-200880)
www.mark-age.eu
Project full title:
European Study to Establish Biomarkers of Human Ageing
Scientific Co-ordinator:
Alexander Bürkle
University of Konstanz,
Konstanz, Germany
Projections of burden of disease
- Proportion with at least one NCD increase from 29% in 2010 to 84% in 2030. - Proportion with 3 or more NCDs increase from 0.3% in 2010 to 28% in 2030. - In 2030 only 16% will have none of the NCDs investigated in this study
The increase in NCDs will be driven by CVD mainly - In 2010 19% of patients are
diagnosed with some CVD compared to 78% in 2030.
Smit M, et al, on behalf of the ATHENA observational cohort; Lancet Infect Dis 2015
The impact of antiretroviral treatment on the age composition of the HIV epidemic in sub-Saharan Africa.
Hontelez JAC. et al. AIDS 2012, 26 (Suppl 1):519-530 & NCHIV 2012, poster 44.
Aging with HIV will Increasingly Occur in
Resource-limited Settings as well
www.ias2013.org Kuala Lumpur, Malaysia , 30 June - 3 July 2013
Regional Ranking of leading causes of years of life lost
(YLL), 2010
Global Burden of Disease Study 2010, modified from Lancet 2012; 380:2095-2128
Summary and Conclusions • Burden of various co-morbidities consistently increased in
HIV • Traditional risk factors play an important role. Needs to be
reflected in our clinical management and care • Independent associations with HIV are observed for some
but not all co-morbidities • Longer time spent at low CD4 counts, rather than longer
overall exposure to ART, generally contributes to greater co-morbidity risk. Early HIV diagnosis and treatment now definitively shown to beneficially modify this risk.
• Persistent inflammation and innate immune activation generally seem to additionally contribute towards risk
• Pathogenic pathways involving effects on the biology of aging need further exploration
Do not regret growing older.
It is a privilege denied to many
Author Unknown
All our study participants
EU 7th FP for research, technological development
and demonstration under grant agreement no 305522
Grant nrs 300020007 & 2009063
2010039
2012023