Immune Control of Clade C HIV Infection

Bruce D Walker, MD

University of KwaZulu Natal

Ragon Institute

of MGH, Harvard and MIT

Question

• Why do children do worse than adults when they become HIV infected?

• Can answering this question shed light on important immune mechanisms?

HIV Prevalence in Antenatal Clinics: 2001

0

5

10

15

20

25

30

35

Percent

KZN Gauteng WesternCape

US

Philip Goulder

PhotiniKiepiela

Not shown: H. CoovadiaS. Abdool Karim

Doris Duke Medical Research Institute

UKZN

DDMRI

MarkSchwartz

KristaDong

KayeAjao

ThumbiNdung’u

CTL

Can we find signals indicating what is involved in immune control?

CTL

Host Genetics

Host Immune Responses

Virus

CTL

Host Genetics

HLA Class I

817 B alleles

263 C alleles

486 A alleles

Experimental Design

• Subjects– HIV-infected Zulu/Xhosa (n=706)

• Methods– High resolution HLA typing– Viral load determination

p < 0.0001

p = 0.0006

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

HLA B-association with control of HIV

B*57

B*5801

B*5802

B*1801 p < 0.0001p = 0.0008

p = 0.0014

B*8101

Kiepiela et al, Nature, 2004

p = 0.0006

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

HLA-association with control of HIV

B*5801

B*5802p < 0.0001

Kiepiela et al, Nature, 2004

Marked differences in HLA associations: B*5801 and B*5802

p< 0.0001

n = 93 n = 259 n = 722

Median= 14, 650

Median= 75, 200

Median= 33, 000

B5801 B5802 Neither-10

100

1000

10000

100000

1000000

10000000

Vir

al lo

ad

(RN

A C

op

ies/

ml)

Ngumbela et al, ARHR 2008

p< 0.0001 p< 0.0001

n = 93 n = 259 n = 722

Median= 14, 650

Median= 75, 200

Median= 33, 000

B5801 B5802 Neither10

100

1000

10000

100000

1000000

10000000

Vir

al lo

ad

(RN

A C

op

ies/

ml)

Ngumbela et al, ARHR 2008

Marked differences in HLA associations: B*5801 and B*5802

HLA B*5802 is deleterious?

Conclusions I

• HLA B alleles influence viral load

• Certain alleles are associated with protection, and others with progression

CTL

How do HLA alleles influence viral load?

HLA Class I

BPocket

FPocket

Infected cell

HLA Class I

BPocket

FPocket

Viral Peptide

Infected cell

HLA Class I

BPocket

FPocket

T Cell Receptor

Infected cell

Experimental Design

• Subjects– HIV infected treatment naïve Zulu/Xhosa

• Methods– Determine the dominant protein targeted by CD8 T

cells by ICS using pooled peptides (61 subjects)

– Determine breadth of CD8 T cell responses by Elispot, using individual overlapping peptides spanning all HIV proteins (578 subjects)

– Correlate to viral load

A dominant CD8 Gag-specific response is associated with lower

viremia

Ramduth, Chetty, Mngquandaniso et al, JID 2005

r=-0.25p<0.0001

p<0.0001

102

103

104

105

106

107

0 1 2 3 >3

Number of Gag responses

Vir

al L

oad

A p<0.0001

p<0.0001

GAG

The breadth of the Gag-specific CD8 response is associated with lower viral load

Kiepiela, Leslie, Honeyborne et al, Nature Medicine 2007

21,000

94,000

102

103

104

105

106

107

p=0.0163p=0.0072

r=0.17p<0.0001

ENV

0 1 2 3 >3

Number of Env responses

Vir

al L

oad

Bp=0.0155

p=0.0456

The breadth of the Env-specific CD8 response is associated with higher viral load

220,000

29,000

Kiepiela, Leslie, Honeyborne et al, Nature Medicine 2007

p = 0.0006

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

HLA-association with control of HIV

B*5801

B*5802p < 0.0001

Kiepiela et al, Nature, 2004

Gag-specific CD8 responses are minimal to undetectable in the first 6

months after vertical transmission

0-2 mo 4mo 6mo 2-12 yrs0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

p=0.0531

ns

ns

% C

D8

IFN

- R

esp

on

ses

(A)

Thobakgale et al, JV 2007

Are there functional differences in HIV-specific immune responses?

Experimental Design

• Subjects selected from a cohort of 288 persons with chronic HIV infection– 13 high Gag-specific CD8 T cell responses

• Mean breadth 8+2.6

• Mean magnitude 3380+1304 SFC/10^6 PBMC

– 13 low Gag-specific CD8 T cell responses • Mean breadth 0.64+0.6

• Mean magnitude 808.8+1038 SFC/106 PBMC

Subjects matched for CD4 count and overall Elispot responses

High Gag responder Low Gag responder0

100

200

300

400

500

600

700

800

900p=0.153

High Gag responder Low Gag responder0

10000

20000

30000

40000

50000p=0.161

No difference in terms of CD4 cell counts or total elispot responses

in high vs low Gag responders

Julg, Williams, Reddy et al, unpublished

Experimental Design

• Methods– Measure the ability of freshly isolated CD8

T cells to• Inhibit a heterologous strain of virus in

autologous CD4 cells• Proliferate in response to HIV peptides• Secrete cytokines in response to HIV

peptides

High Gag responders have significantly lower viral loads

High Gag responder Low Gag responder0

1

2

3

4

5

6

7p=0.002

Julg, Williams, Reddy et al, unpublished

0 1 2 3 4 5 6 7 8 9 10 11 12 131

10

100

1000

10000

100000

1000000

CD4 uninfected

CD4 infected withHIV-1 (X4) MOI 0.1

Day

p2

4 p

g/m

l

0 1 2 3 4 5 6 7 8 9 10 11 12 131

10

100

1000

10000

100000

1000000

CD8 Cells added

CD4 uninfected

CD4 infected withHIV-1 (X4) MOI 0.1

Day

p2

4 p

g/m

l

Julg, Williams, Reddy et al, unpublished

High Gag responder Low Gag responder0.0

0.5

1.0

1.5

2.0

2.5p<0.003

High Gag-responders inhibit virus replication better

Julg, Williams, Reddy et al, unpublished

Conclusions II

• Broader Gag-specific CD8 T cell responses are associated with lower viral loads

• Broader Env-specific CD8 T cell responses are associated with higher viral loads

• Broad Gag-specific CD8 T cell responses are associated with enhanced ability to neutralize infectious HIV and greater functionality

CTL

Virus

CTL

Viral Epitope

S W

HLA B5801

TSTLQEQIAW

Rapid selection for mutation in the B5801-restricted TW10 epitope

--N-------

Wild type

T242N

Wild-type virus outgrows mutant T242N

0 10 20 30 40 50 600

20

40

60

80

100

NL4-3/T242N

NL4-3

days post-infection

% v

iral v

aria

nt

0 10 20 30 40 50 600

20

40

60

80

100

Child T242N

Child WT

days post-infection

% v

iral v

aria

nt

A B

NL4-3 NL4-3/T242N Child WT Child T242N0

2

4

6

8

10

12

14

% G

FP+

cells

C D

% v

iral

var

iant

% v

iral

var

iant

% G

FP

+ c

ells

0 100 200 300 400 500 600012

34567

Age (days)

ART

Viral Load

% T242N

100%

80%

60%

40%

20%

0%

log

vira

l loa

dL

og v

iral

load

Days post-infection Days post-infection

Figure1

% v

iral

var

ian

t

% v

iral

var

ian

t

days post infection

Martinez-Picado, J Virol, 2006

Number of HLA-B-associated Gag mutationscorrelated with median viral load for each allele

0 1 2 3 4 5 6

10000

100000 r = -0.56p = 0.0034

B*5703

B*5702B*8101

B*5801

B*3910B*1401B*4403B*0702B*3501B*1510

B*41

B*1516B*5301B*1302B*4201B*4501B*1503B*0801B*5802B*1402B*1801B*0705B*4202B*51B*4901

50000

Number of HLA-B Gag mutations

Vir

al L

oad

Matthews, Prendergast et

al, J Virol, 2008

Conclusions III

• Gag-specific CD8 T cell responses select for fitness mutants that cripple HIV

CTL

What is this epitope-specific immune pressure doing at a population level?

• Subjects– 2800 persons with chronic HIV infection– 9 cohorts, 5 continents

• Methods– HLA typing– Virus sequencing in Gag– Analyze the relationship between HLA

prevalence and detection of escape mutationsY Kawashima et al, Nature 2009

Global CTL Escape Collaboration

London

% I

135X

var

ian

t in

pop

ulat

ion

75

50

25

00 10 20

% HLA-B51 Prevalence

p=0.0001Kumamoto

VancouverPerth

Oxford

Barbados

LusakaDurban

Gaberone

Percent escape mutant in theentire

population

Y Kawashima et al, Nature in press

% I

135X

var

ian

tin

HL

A-m

ism

atch

ed75

50

25

00 10 20

% HLA-B51 Prevalence

p=0.0006Percent escape mutant

in persons NOT

expressing HLA B51

Y Kawashima et al, Nature in press

Conclusions IV

• HIV is being shaped by the immune response on a global level, and some protective epitopes are being lost

Do host genetics affect transmission?

Impact of Protective HLA alleles on HIV Transmission

0

5

10

15

20

25

30

35

Non-Transmitters Transmitters

Percent mothers expressing

protective HLA alleles

N=236 N=61

P = 0.05

Thobakgale et al, JV in press

Impact of Protective HLA alleles on disease progression in infants

0

10

20

30

40

50

60

Slow Progressor Progressor

Percent mother or child expressing

protective HLA alleles

N=17 N=44

P = 0.047

Thobakgale et al, JV in press

Conclusions V

• HLA is impacting transmission

• Protective HLA alleles should increase in the population as the epidemic progresses

What else can international partnerships and local leadership

achieve?

KwaZulu Natal Research Institute for TB and HIV (K-RITH)

Given where we are now, what should the priorities be moving forward?

0

0

25

50

75

Female (15-49) Male (15-49) RSA antenatal clinics 2006PMMH March 2009

Age8 16 24 32 40 48 54 60

66%

%

By age 22, 66% of mothers are HIV infected(Durban, March 2009)

A vaccine for HIV is possible, but still a long way off

More efforts must turn to prevention

• Whizzkidsunited.com

Christina ThobakgaleKholiswa NgumbelaDanni RamduthKirebnashe NairBoris JulgKatie WilliamsIsobel HoneyborneMary Van der StockEshia MoodleyKaren BishopSharon ReddyFundi ChoncoWendy MphatsweSister Kesia

Zenele Mncube Nompumelelo Mkhwanazi Cheryl Day

Janet GiddyHenry SunpathHelga Holst

Thumbi Ndung’uJerry CoovadiaSalim Abdool KarimWilliam CarrVictoria Kasprowicz

Marcus AltfeldMarylyn AddoMark Brockman

Philip Goulder

Jill Conley

Marcus McGilvray