lipodystrophy 20 years - international medical press presentations... · hiv-associated...

Lipodystrophy 20 years

David Cooper October 2017

AIDS 1998(>2000 citations)

Lipodystrophy syndrome: early report

HIV-associated lipodystrophy syndrome 20 years

One or two syndromes?

Lipoatrophy

Fat accumulation

Cardiovascular disease

Management of cardiovascular disease

Future interventions

One or Two Syndromes?HIV-associated lipodystrophy syndrome 20 years

Wide variation in range 10-80%differences in definitions and methodologydifferences in host factors

geographyagegeneticslifestyle factorsspecific ART useduration of treatment

Lipodystrophy: prevalence

Lipoatrophy and fat accumulation are different processes


HIV lipodystrophy case definition study group, Lancet 2003

Lipodystrophy: an objective case definition


SyndromeNo. (%) of men

(n=306)No. (%) of women

(n=144) P

Fat atrophy 117 (38.2) 37 (25.7) 0.009Fat deposition 123 (40.1) 77 (53.1) 0.009Mixed 44 (14.4) 19 (13.2) 0.74

NHL study: prevalence and risk factors

Nutrition for Healthy Living Study Jacobson et al, CID 2005

Fat atrophy• triceps skinfold• hip circumference• HIV disease severity• continuous duration of ART• any stavudine use

Fat deposition• female sex• triceps skinfold• percentage of body fat• TG level

Independent determinants of new fat atrophy and fat deposition


FRAM: no association of peripheral lipoatrophy with central lipohypertrophy

FRAM, JAIDS 2005

% with peripheral lipoatrophy

0102030405060708090

100

Central Lipohypertrophy Central Lipoatrophy

OR = 0.7CI = 0.47- 1.1P = 0.10

OR = 18.9CI = 5.7 – 63P < 0.001

yesno


parameter time change in limb fat mass (kg)week 72 – week 0

change in VAT(cm2)

week 72 – week 0

beta (95% CI) P beta (95% CI) P

ART

on study d4T/AZT

≥ 6 months -0.57 (-1.03, -0.10) 0.017 - -

Body composition

limb fat mass baseline 0.37 (0.26, 0.48) < 0.0001 -4.07 (-7.34, -0.79) 0.016

VAT (cm2)baseline 0.004 (0.001, 0.01) 0.023 -0.16 (-0.25, -0.07) 0.001

change at wk 72 0.02 (0.01, 0.02) < 0.0001 - -

MITOX, ROSEY: change in limb fat and VAT with ART

Wand et al, J Clin Trials 2011


One or two syndromes?

Lipoatrophy

Fat accumulation




LipoatrophyHIV-associated lipodystrophy syndrome 20 years

Lipoatrophy: clinical features


Visual inspection and physical exam

Patient self-report

Pinchable fat on abdomen

Limb circumference and skin fold thickness

CT, MRI or DEXA scanning

Staging scales for facial lipoatrophy

Lipodystrophy case definition

Metabolic abnormalities

Lipoatrophy: diagnosis and evaluation


SVH clinic cohort: changes in body composition after HAART

% ∆ from baseline (median)

Mallon et al, AIDS 2003

central abdominal fat

lean mass

limb fat

weeks after HAART


Gilead 903: total limb fat

TDF + 3TC + EFV n= 128 115d4T + 3TC + EFV n= 134 117

kilograms

weeks

Gallant et al, IAC 2004

TFV+3TC+EFV


Lipoatrophy: subcutaneous fat biopsy

AZT

CD68 control

d4T

normal


SAMA-1: adipose tissue gene expression with NRTI’s

p=0.02med % chg+83

[137]

p=0.01med % chg+25

[116]

p=0.01med % chg+42

[131]

med % chg

-63 [77]

p=0.001

med % chg

-88 [54]p=0.005

med % chg

-60 [62]

(gene : β actin)x 1000

gene : β actin

baselineweek 2

Cyt bCOX3COX1

PGC1 NRF-1 mtTFA

p=0.002

Mallon et al, JID 2005


Type of adipose tissue disturbance

Implicated antiretroviral agents

Impaired adipogenesis, adipocyte differentiation or function

LPV/r, RTV, EFV, RPV, d4T

pre-adipocyte autophagy and apoptosis

ATV

Impairment of lipid and/or glucose metabolism

ATV/r, LPV/r, RTV, DRV/r, NNRTIs, EFV, NRTIs

Impairment of mitochondrial function

ATV, ATV/r, SQV, LPV/r, RTV, NRTIs

pro-inflammatory ATV/r, LPV/r, RTV, EFV, RPV

prelamin A accumulation protease inhibitors

Adipocytes: effects of specific antiretroviral drugs

Erlandson and Lake; Curr HIV/AIDS Rep 2016


0

10

20

30

40

48 96

ACTG5142: lipoatrophy

0

10

20

30

40

50

48 96

%

lipoatrophy

EFV 188 171LPV 191 166LPV/r-EFV 197 173

d4T 93 84AZT 133 117TDF 153 136

weeks on study

Haubrich et al, AIDS 2009

P values at week 96EFV vs LPV/r 0.003EFV vs LPV/r-EFV <0.001LPV vs LPV/r-EFV 0.023

P values at week 96d4T vs AZT 0.003d4T vs TDF <0.001AZT vs TDF 0.023


Metabolic derangements

Distress of physical changes in appearance

especially facial lipoatrophy

Disclosure of HIV status

Impact on adherence

Quality of life with restricted neck movement or

breast enlargement

Lipoatrophy: rationale for treatment


Switching antiretroviralsswitching the NRTI backboneswitching the third drug

Surgical approachestemporary fillers

poly-L-lactic acid fillercalcium hydroxylapatite

permanent fillersautologous fat transplantation

Thiazolidinediones

Lipoatrophy: treatment


0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 24 48 72 108

MITOX-ABCRAVE-ABCRAVE-TDFTARHEELA5215Sd4T4030-TDF

d4T/AZT switch for lipoatrophy: cross study comparisons

Carr et al, JAMA 2002; Martin et al, AIDS 2004; McComsey et al, CID 2004 Moyle et al, AIDS 2006; Milinkovic et al, CROI 2005; Murphy et al, CROI 2005

week

change from

baseline (kg)

on-treatment analysis


FLASH: Poly-L-lactic acid for facial lipoatrophy

mean change in FSTV

(cm3)

Carey et al, HIV Med 2009


Treatment

Model of changein limb fat mass

Model of 10% increase in limb fat from baseline

Estimate 95% CI P OR 95% CI P

Pioglitazone 0.35 (0.11,0.58) 0.004 2.28 (1.07,4.88) 0.03

Rosiglitazone 0.05 (-0.10, 0.21) 0.48 1.11 (0.72, 1.72) 0.63

Placebo (ref) - - - 1.00

Thiazolidinediones: GEE regression models

Meta-analysis of 6 placebo-controlled trialsof TZD’s for HIV lipoatrophy

Raboud et al, HIV Clin Trials 2010


Lipoatrophy

Fat accumulation




One or two syndromes

Fat Accumulation


Lipohypertrophy: clinical features

Fat Accumulation


Lipohypertrophy: diagnosis and evaluationVisual inspection and physical exam

Check pinchable fat

Measurement of waist circumference

(>102cm for men and >88cm for women is abnormal)

Waist:hip ratio and BMI less accurate

Stable BMI with increasing waist circumference suggests concomitant lipoatrophy

CT or MRI (not routine)

DEXA measures trunk fat not recommended

Fat Accumulation


Lipohypertrophy: risk factors

ART but which class?

Switching class does not improve FA

Increasing age, female sex, elevated baseline TG,

higher body fat %

FRAM shows no difference between HIV positives and

HIV negatives

Fat Accumulation


Women with lipohypertrophy: switch from PI/NNRTI to RAL

n=37 week 0-48 changes pooled 24-week changes

P P

SAT (cm2) -17.8 0.57 0.8 0.59

VAT (cm2) -11.7 0.68 -4.4 0.51

chol (mg/dL) -14 0.01 -17 <0.0001

LDL chol (mg/dL) -2.0 0.16 -9.1 <0.01

HDL chol (mg/dL) -4.0 0.25 -2.6 0.03

TG (mg/dL) -1.0 0.32 -18 <0.01

Lake et al, OFID 2015

Median changes in adipose tissue and lab values

Fat Accumulation


ARDENT ACTG A5260S: changes in body compositionwith PI or IntSTI initiation

McComsey et al, CID 2016

% change

from baseline

baseline week96

baseline week96

baseline week96

baseline week96

Limb fat change SAT change Trunk fat change VAT change

ATV/rRALDRV/r

P= NSfor all comparisons

Fat Accumulation


Lipohypertrophy: treatment

Diet and exercise

Metformin

Tesamorelin

Surgical approaches

Fat Accumulation


Exercise training: reduced trunk fat at 16 weeks

n=10 Baseline Final P value

Strength – leg press (kg) 220 250 0.02

Strength – chest press (kg) 31 37 0.005

Body fat (kg) 16.0 14.4 0.04

Trunk fat (kg) 8.6 7.5 0.03

Roubenoff et al; AIDS 1999

Fat Accumulation


Metformin: treatment of HIV lipodystrophy

n=25Baseline mean change at 3 mo P

Pbo Met Pbo Met

Weight (kg) 80.8 82.4 1.1 -1.3 0.005

Waist circumference (cm) 97 98 1.1 -1.1 0.02

VAT (cm2) 156 177 12 -11 0.08

SAT (cm2) 153 162 12 -7 0.08

Hadigan et al, JAMA 2000

Fat Accumulation


Tesamorelin: change in VAT from baseline to 26 wks

Falutz et al NEJM 2007

visceral adipose tissue

%

Tesamorelin n=273Placebo n=137

change in value

cm2

baseline value cm2

P < 0.001

Fat Accumulation


What happened to the lipodystrophy syndrome?

Fat Accumulation


What happened to the lipodystrophy syndrome?

Thymidine analogue N(t)RTIs stopped being used

NNRTIs and PIs were replaced with InSTIs as anchor drugs

SMART study showed that HIV was pro-inflammatory and

pro-coagulopathic

DAD study emphasised effects of N(t)RTIs, NNRTIs and PIs

on comorbidities


Lipoatrophy

Fat accumulation





Cardiovascular Disease


VA Cohort Study: rates of AMI by HIV status and age

Age group, yr

40-49 50-59 60-69

n= 21,866 19,805 4209

uninfected

AMI rates per 1000 py 1.5 2.2 3.3

HIV infected

AMI rates per 1000 py 2.0 3.9 5.0

Incidence RR 1.34 1.80 1.53

Freiberg et al; JAMA Intern Med 2013



SMART: event ratesevent DC group VS group HR (DC/VS)

[95% CI]P-

value

n rate n rateprimary endpoint: OD or death

120 3.3 47 1.3 2.6 [1.9, 3.7] <0.001

death 55 1.5 30 0.8 1.8 [1.2, 2.9] 0.007

serious OD 13 0.4 2 0.1 6.6 [1.5, 29] 0.01

non-serious OD 63 1.7 18 0.5 3.6 [2.1, 6.1] <0.001

major CVD, renal and hepatic events

65 1.8 39 1.1 1.7[1.1, 2.5] 0.009

grade 4 events 173 5.0 148 4.2 1.2 [0.9, 1.5] 0.13

grade 4 event or death 205 5.9 164 4.7 1.3 [1.03,1.6] 0.03

El-Sadr et al, NEJM 2007



SMART: baseline biomarkers and all cause mortality

unadjusted adjusted

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

hs-CRP 2.0 0.05 2.8 0.03

amyloid A 2.2 0.07 2.6 0.09

amyloid P 0.7 0.39 1.1 0.84

IL-6 8.3 < 0.0001 11.8 < 0.0001

D- dimer 12.4 < 0.0001 26.5 < 0.0001

F1.2 1.0 0.92 1.2 0.66

Insight Mtg Tlk 2/6/2008



0

5

10

15

20

25 all causedeath

non-AIDS/

violent/accidental

death

AIDS NADMCVD

14 21 35 87 6 16 23 72 15 26 24 36 13 21 33 54 10 19 28 42No events

Crud

e in

cide

nce

rate

spe

r 1,0

00 P

YFU

(95%

CI)

IL-6

START: crude incidence rates of clinical endpoints across biomarker quartiles

crude incidence rates per

1,000 PYFU

(95% CI)

+

˟1st quartile

2nd quartile

3rd quartile

4th quartile

Events n=



DAD: risk of MI by exposure to PIs and NNRTIs

The DAD Study Group; NEJM 2007

adjustedrelative

rate

PIsNNRTIs



DAD: rates of MI by recent use of abacavir

DAD Lancet 2008

rate per 1000

patient years

0

5

10

15

20

25

30

35

events 325 192 60 42 79 33 100 68 86 49patient years 126581 31331 57628 14754 13372 4300 6293 2095 49288 10182

overall low moderate high not known

no recent abacavirrecent abacavir



DAD: cardiovascular risk factors and rate of MI

variable relative rate 95% CIExposure to PI (per additional yr) 1.16 1.10-1.23Exposure to NNRTI (per additional yr) 1.05 0.98-1.13Age (per additional 5 yr) 1.39 1.31-1.46Male sex 1.91 1.28-2.86FH of CAD 1.56 1.10-2.23Smoking 2.83 2.04-3.93Previous cardiovascular event 4.30 3.06-6.03

The DAD Study Group; NEJM 2007

Diabetes, hypertension, total and decreased HDL cholesterolwere also risk factors in second adjusted model



Impact of HIV on inflammation, coagulation, and health

Deeks et al, Immunity 2013

Initiators of inflammation

Other risk factors

Microbial translocation

Liver fibrosis or dysfunction

Innate immunity


Hypercoagulation

Age-associated diseases

tissue factor expression

alteredcoagulome


Lipoatrophy

Fat accumulation





Management of CVR


Cardiovascular risk: calculation

Framingham risk score

AHA/ACC pooled cohort equations CV risk calculator (PCE)

Friis-Moller et al, Eur J Prev Cardiol 2016

DAD model

includes age, gender, BP, smoking, FH, DM, TC, HDL, CD4, cumulative exposure to PIs and NRTIs, current use of ABC

predicted risk more accurately than Framingham

Management of CVR


Management principles in HIV-infected persons

Same risk reduction strategies as general population

aspirin, statin, BP control, management of DM

Screen for DM and dyslipidaemia at baseline and every 3 to 6 and 6 to 12 months respectively

Use InSTI and avoid ABC in treatment naïve with increased cardiovascular risk

Switch PI to InSTI has modest benefit on dyslipidaemia in treatment experienced

atorvastatin, pitavastatin and rosuvastatin are statins of choice for dyslipidaemia on ART


Lipoatrophy

Fat accumulation





Future Intervention


HIV trials: targeting inflammation and/or end-organ disease risk

Lipid lowering

BP lowering

other risk-factor modification

anti-inflammatory

anti-coagulants

Blocking microbial translocation

anti-viral

anti-fibrotic

Future Intervention


REPRIEVE: trial design (n=6500)

http://reprievetrial.org/overview/

Screening and consent (asymptomatic HIV-infected persons with no history of CVD)

Randomisation

Mechanistic study primary(coronary plaque, vascular inflammation,

or immune activation)

Secondary end points(individual components of primary end point; all-cause death; incidence or progression

of non-calcified plaque; high-risk plaque; inflammatory, immunologic or metabolic biomarkers; predictors of statin effect; and non-AIDS-related comorbidities)

Composite primary end point(CVD-related death, myocardial infarction, unstable angina,

stroke, and arterial revascularization)

Placebo Pitavastatin 4mg daily

Future Intervention


Polypills: projected risks of ischaemic heart disease (IHD) and stroke after 2 yr of treatment at age 55-64

Wald and Law, BMJ 2003

% reduction in risk (95% CI)Risk factor Agent Reduction in

risk factorIHD event stroke

LDL cholesterol statin 1.8 mmol/l reduction in LDL cholesterol

61 (51 to 71) 17 (9 to 25)

Blood pressure 3 classes of drug at half dose

11 mm Hg diastolic

46 (39 to53) 63 (55 to 70)

Serum homocysteine

folic acid(0.8 mg/day)

3mmol/l 16 (11 to 20) 24 (15 to 33)

Platelet function aspirin(75 mg/day)

not quantified 32 (23 to 40) 16 (7 to 25)

Combined effect all 88 (84 to 91) 80 (71 to 87)

Future Intervention


PolypillsFixed-dose combination therapy in a single pill to improve prevention and control of atherosclerosis

Combinations of aspirin, ACE/ARB and statin, generally low-dose, sometimes with β-blocker or CCB

Similar concept to fixed-dose combinations for malaria, TB and HIV

Concept without widespread availability and limited experience

Given increased cardiovascular risk in HIV, should the polypill be tested in HIV-infected persons?

Huffman et al, Lancet 2017

Future Intervention


HIV-comorbidities: development of clinical trial agendaPrinciple: select agent to move to phase 3 with best evidence of relevant biomarker effect

Design limitations

small sample size limiting safety assessment

low power to detect differences in key biomarkers

inability to compare drugs

different target populations

Solution: adaptive phase 2 trial design with rigid criteria for taking best agent to phase 3

Future Intervention


-70

-60

-50

-40

-30

-20

-10

0

10

% change

from baseline (median)

hsCRP

months

placebo

canakinumab 50mg

canakinumab 150mgcanakinumab 300mg

Ridker ESC 2017

CANTOS: Dose-dependent effects on inflammatory biomarkers and lipids (48 months)

All doses SC q 3 months No effect on LDL-Chol, HDL-Chol or TG

Future Intervention


CANTOS: primary clinical outcome effects on MACE/MACE+Canakinumab SC q 3 months

placebo(n=3347)

50 mg(n=2170)

150 mg(n=2284)

300 mg(n=2263)

P-trend

Primary endpointIR (per 100 person years)HR95%CIP

4.51.0

(referent)(referent)

4.10.93

0.80-1.070.30

3.90.85

0.74-0.980.021*

3.90.86

0.75-0.990.031

0.020

Secondary endpointIR (per 100 person years)HR95%CIP

5.11.00

(referent)(referent)

4.60.90

0.78-1.030.11

4.30.83

0.73-0.950.005*

4.30.83

0.72-0.940.004

0.003

* Statistically significant, adjusted for multiplicity, in accordance with the pre-specifiedclosed-testing procedures

Ridker ESC 2017

Future Intervention


CANTOS: additional outcomes (per 100 pt yrs of exposure)Canakinumab SC q 3 months

Adverse Event Placebo(n=3347)

50 mg(n=2170)

150 mg(n=2284)

300 mg(n=2263) P-trend

Any SAE 12.0 11.4 11.7 12.3 0.43Leukopenia 0.24 0.30 0.37 0.52 0.002Any infection 2.86 3.03 3.13 3.25 0.12

fatal infection 0.18 0.31 0.28 0.34 0.09/0.02*Injection site reaction 0.23 0.27 0.28 0.30 0.49Any malignancy 1.88 1.85 1.69 1.72 0.31

fatal malignancy 0.64 0.55 0.50 0.31 0.0007Arthritis 3.32 2.15 2.17 2.47 0.002Osteoarthritis 1.67 1.21 1.12 1.30 0.04Gout 0.80 0.43 0.35 0.37 0.0001ALT > 3x normal 1.4 1.9 1.9 2.0 0.19Bilirubin > 2x normal 0.8 1.0 0.7 0.7 0.34

* P-value for combined canakinumab doses vs placebo Ridker ESC 2017

Future Intervention


Grivennikov, Greten, Karin. Cell 2010

Immunity, Inflammation, and Cancer

Therapy-induced inflammation

Tumour associated inflammation

Chronic inflammation

InfectionAutoimmunity

Inflammationcaused by

environmental and dietary exposure

Tumour re-emergenceResistance to therapy

Antigen presentationCancer cell killing

Tumour growth/survivalGenomic instability

AngiogenesisImmunosuppression

MetastasisCancer cell killing

MutationsGenomic instabilityTumour promotion

Angiogenesis

MutationsGenomic instabilityTumour promotion

AngiogenesisTUMOUR

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