aeras schofield 21112013

Collaborating Institutions

PNG Institute of Medical Research

Kenya Medical Research Institute Mozambique

Centre for Clinical Health Research

The Walter and Eliza Hall Institute

of Medical Research

Malaria Immunology and Epidemiology studies in PNG

Understanding the targets and mechanisms of immunity to malaria to

rationalize the development of vaccines.

Examine both antibody and cellular compartments of the immune

response to the malaria.

Studies: Funders:

-Mugil study (2004) US Dept. Veterans Affairs

-Alexishafen pregnancy study (2006-11) MiP Consortium

-Ilaita (R03) mixed infection study (2007) NIH, HHMI Lab funds

-MALGEN severe malaria study (2006-10) Gates Grand Challenges, NH&MRC

-Cellex P. vivax study (2008) Cellex Foundation with CRESIB

-IPTi study (2008-2010) IPTi Consortium

-Albimana study (2009) Lab funds

-ICEMR study (2010-17) NIH






Studies: Funders:



-Ilaita (R03) mixed infection study (2007) Lab funds (HHMI)






Observational cohorts studies (n = ~ 500)






Studies: Funders:









Intervention studies (n = ~ 1500-2000)

Systems biology (‘omics’)

Biology and Clinical insight

Population platforms (field sites, cohort studies)

Population biology

Epidemiology

Stats

Malaria

Tuberculosis?

Population biology: platform for discovery

PNG Field Studies

2004-2013

Study villages

Longitudinal Study Design

0 days 30 60 90 120 150 180

Clinical examination 10mL blood taken

Immune cells purified

drug treatment

(baseline)

Baseline

Active case detection

-Clinical exam

-Blood films (LM)

-Finger prick (PCR)

-Symptomatic children

taken to Mugil Health Centre

Passive case detection 12 months

Parasitological and clinical outcomes

Michon et al., 2007

~95% of children were re-

infected with P. falciparum

~50% of children

experienced a clinical

episode of P. falciparum

Clinical episode: fever +

5000 parasites/μL

80

Pro

po

rtio

n u

nin

fect

ed

80

Pro

po

rtio

n u

nin

fect

ed

Moving beyond serology to define targets of naturally

acquired immunity

• Development of functional assays measuring relevant host/pathogen

interactions

– Growth inhibitory antibodies

– Opsonising antibodies

Anti-Rh5 antibodies associated with reduced risk of

high parasitemia

There Are Conflicting Reports as to the Cellular

Source of Innate IFNg in Humans

gd-T

CD

56

CD3

SS

C

SS

C

ab-TCR gd-TCR

NK

•A comprehensive phenotypic characterization of all innate IFNg producing cells

had not been done

NK cells also shown to be a major

source of innate IFNg (Artavanis-

Tsakonas & Riley, 2002)

gdT cells shown to be a major

source of innate IFNg (Hensmann

& Kwiatkowski, 2001)

Major Questions

• What cells produce IFNg in response to malaria in humans?

– Do they express NKC &/or KIR receptors?

• Is IFNg production by these cells associated with altered risk of disease in individuals living in malaria-endemic areas as it is in mice?

Malaria IFNg Elicitation Assay

Blood from

Purify

PBMC

P. falciparum

iRBC

Malaria

naive donors

16 hour incubation at 37ºC

Measure IFNg

in supernatants

by ELISA

Determine which

PBMC produce

IFNg by FACS

uRBC

or

IFNg

gdTCR

CD3

CD56

uRB

C

iRBC

IFNg

CD3

IFNg+ PBMC from 15

donors phenotypically

characterized

93% of

donors

gdT cells

7% of

donors

NK cells

D’Ombrain et al., 2007

gdT Cells Are The Predominant Source of IFNg in

93% of Donors

gdT Cells Are The Predominant Source of IFNg in

93% of donors NK cells

gdT cells

abT cells

other cells


0%

20%

40%

60%

80%

100%

H N G I L F K M D A E J B O C

Donors

% o

f T

ota

l IF

N- g

+ C

ells

•Cell frequency & the % contribution of each cell type were not associated with

heterogeneity in IFNg responsiveness


Depletion of gdT Cells Abrogates IFNg Production

CD3

CD56

gdTCR

abTC

R

97%

89%

96%

PBMC Depleted

PBMC

uRBC

iRBC

0

300

600

900

1200

1500

NK cell

depleted

gdT

depleted

abT

depleted

0

300

600

900

1200

1500

IFN

g (p

g/m

L)

PBMC

*

Vg9 54.2 45.8

CD8 29.9 70.1

Vd2 83.6 16.4

CD4 4.7 95.3

Vd1 9.5 90.5

+

Malaria Responsive gdT Cells Are Mainly of

the Vg9Vd2 Subset

iRBC

gdTCR+ & IFNg+ PBMC

phenotypically characterised

gdTCR

iRBC

IFNg

iRBC


NKG2A

68.2 31.8

NKG2D

83.2 16.8

CD94 89.4 10.6

CD161 73.5 26.5

+ iRBC

gdTCR+ & IFNg+ PBMC

phenotypically characterised

gdTCR

iRBC

IFNg

iRBC

The Majority of Malaria Responsive gdT Cells

Express NKC Receptors


NKC & KIR Receptors Are Differentially

Expressed on IFNg+ & IFNg- gdT Cells

+ iRBC

gdTCR+ & IFNg- or IFNg+

PBMC compared by

Wilcoxon Signed-Rank

Tests

gdTCR IFNg

0%

25%

50%

75%

100%

E F G D K H I

NKG2A p<0.01

Donors

% I

FN

g- &

IF

Ng+

gdT

cel

ls

expre

ssin

g N

KG

2A


IFN-g- gdT cells IFN-g+ gdT cells

iRBC iRBC

0%

10%

20%

30%

E F G D K H I

KIR2DL1 p<0.01

Donors

% I

FN

g- &

IF

Ng+

gdT

cel

ls

expre

ssin

g K

IR2D

L1

Summary: PART 1

There is heterogeneity among donors in the innate IFNg response to iRBC

gdT cells that express NK receptors, not NK cells, are the major cellular source of IFNg

NK receptors are differentially expressed on IFNg+ & IFNg- gdT cells

Are gdT cell involved in risk of disease?

0

2000

4000

6000

8000

10000

12000

14000

14

3

10

9

23

1

41

40

1

50

10

8

13

8

14

6

56

12

1

40 9

30

3

42

5

21

0

22

2

30

2

14

14

1

30

7

41

3

20

5

24

3

42

7

24

5

24

4

42

1 6

31

High

Medium

Low

Heterogeneity in IFNg Responses Among Semi-

immune PNG Children

IFN

g (p

g/m

L)

PNG Children

Heterogeneity in IFNg Responses is Malaria

Specific

≤ ≤

iRBC PHA

High IFNg Responses Are Associated With a Lower

Risk of High Density Infections

No change

in risk

Higher risk

(pathogenic)

Lower risk

(protective)

Haz

ard

Rat

io

Hazard Ratio: Ratio of hazard of having a P. falciparum

infection to high IFNg responsiveness

(clinical) low density

infections high density

infections

A case-control study of severe malaria in PNG

Severe Malaria

n=202

Uncomplicated malaria controls

n=174

Healthy community controls

n=164

• >1000 P.f./μL

• WHO (2000) definition of severe

malaria

• Admitted to Modilon Hospital

• >1000 P.f./μL

• No severe disease

• Health / immunization clinics

• No acute illness

• No severe malaria within 2 weeks

• Immunization clinics

Groups matched by age, sex, and province

of parent’s birth

Cases Controls

Cytokine responses to pRBC are associated with disease

severity

Cytokine responses to pRBC are associated

with disease severity

Cytokine responses are associated with

specific severe malaria syndromes

Respiratory distress Deep coma Hyperlactataemia

gd T cells in severe malaria produce TNF and monokines

Vg9Vd2 T Cells

•Evidence for 2 mechanisms of activation:

phospho-

antigens

APC

Expansion

•Vg9Vd2T cells are activated by phosphoantigens

1. Vg9Vd2TCR can function as a PRR

2. Vg9Vd2TCR can also be MHC

IFNg

Vg9Vd2TCR

restricted






Studies: Funders:









Observational cohorts studies (n = ~ 500)






Studies: Funders:









Intervention studies (n = ~ 1500-2000)

Cohort study questions

• How do malaria-specific CD4+ T cell and gd T cell responses differ in phenotype, frequencies and function in relation to age, parasitological and clinical outcomes?

• What responses are associated with differential clinical and parasitological risk i.e correlates of immunity or susceptibility?

• Are CD4+ ab T cell and gd T cell responses correlated?

• How do CD4+ T cell responses to EBV and CMV differ to malaria-specific CD4+ T cell responses?

Our more recent approaches

• Multiparameter flow cytometry consisting of:

Viability dye to exclude non-viable cells;

5 population markers to identify T cell populations

of interest and memory status;

3 markers to identify differentiation/antigen-

experience and immunosenescence;

4 markers to assess functional activity of cells and

polyfunctionality.

Immune regulation of gd T cell responses

• Rationale: Conventional T cells are tightly regulated by expression of receptors that suppresses cell activation. Prolonged and inappropriate expression of these receptors occur during chronic disease and immune exhaustion resulting in dysfunctional cell functions

• Study questions:

- Are gd T cell responses regulated in a similar manner as conventional T cells?

- How does expression of regulatory receptors on gd T cells effect functional capacity and cytokine profiles?

- How does expression of regulatory receptors on gd T cells relate to protective immunity during malaria?

Immune regulation: Programmed cell death-1 (PD-1)

• PD-1 is a cell surface receptor that suppresses activation of immune cells.

• PD-1 is expressed by dysfunctional cells in chronic diseases such as HIV and HCV. Porichis et al Blood 2011, Razziorrouh et al Gastroeneterology 2011

• Blocking of PD-1 interaction with it’s ligand results in restored cell function. Day et al Nature

2006

• In malaria blocking of PD-1 result in reduced parasite burden in an animal model. Butler

et al Nat Immunol 2012

gd T cell PD-1 expression

Immune regulation: and T-cell immunoglobulin and

mucin domain-containing protein 3 (Tim-3)

• Tim-3 engagement in mice result in apoptosis and loss of effector T cells.

• Zhu et al. Nat Immunol 2005

• In humans Tim-3 is associated with functional exhaustion.

• Jin et al PNAS 2010, Jones et al JEM 2008

• Blocking of Tim-3 partially reverse cell dysfunction.

• Sakuichi et al JEM 2010

• Very few studies have investigated Tim-3 on non-conventional T cells.

gd T cell Tim-3 expression

Innate lymphocytes – unexplored players in defense against

novel non-classical pathogen ligands?

Mucosa = largest exposed surface of the body – 1st barrier

Up to 1012 bacteria/cm3 – not all of which are friendly

humans exposed to multitude of organisms daily

250 m2 gut

70m2 lungs

The mucosal defense system – a central motor

Coordinates cross-talk among epithelium, immune system and

endogenous microflora of gut

Implicated in a wide range of diseases

Lung disease – asthma, TB

Autoimmune disease – mediated by ILC and alterations of gut

microbiota

Intestinal disease – inflammatory bowel disease,

Crohn’s disease

Innate lymphocytes – new players in lung defense

Diverse populations form an intricate innate

lymphocyte network

Spits et al. Nature Reviews Immunology 13, 145-149 (February 2013) | doi:10.1038/nri3365

ILC subsets, functions and disease associations

Highly conserved gene program between mice and man

Spits et al. Nature Reviews Immunology 13, 145-149 (February 2013) | doi:10.1038/nri3365

Bioinformatics at WEHI: world leading in transcriptomic statistics

Eliminating background noise by focusing on gene sets linked to cell populations or

processes of interest

Gene set testing is a powerful method to identify coordinated changes in genes

associated with a particular population or process of interest.

It is particularly useful in complex processes where the timing of up- and down-

regulation of genes can occur at different rates.

We successfully used Gordon Smyth’s rotational gene set testing (ROAST) and

competitive gene set testing (Camera) methods in Achtman et al. 2012 Effective

adjunctive therapy by an innate defense regulatory peptide in preclinical severe

malaria. Science Translational Medicine Sci Transl Med. 4 (135):135ra64. doi:

10.1126/scitranslmed.3003515.

Terry Speed

Gordon Smyth

Deconvolution of data based on additional information on population

sizes

The quanta unit of the immune system is the cell, yet analyzed samples are often heterogeneous

with respect to cell subsets - which can confound interpretation.

Experimentally, researchers face a difficult choice whether to profile heterogeneous samples with

the ensuing confounding effects, or a priori focus on a few cell subsets of interest, potentially

limiting new discoveries.

An attractive alternative solution is to extract cell subset-specific information directly from

heterogeneous samples via computational deconvolution techniques, thereby capturing both cell-

centered and whole system level context.

Our plan to define cellular immunity to P.falciparum Malaria

Study design Key Questions:

How do malaria-specific T cells phenotypes differ in relation to: (i) age; (ii) exposure; (iii) parasitological

outcomes; (iv) clinical outcomes; and (v) elicitation stimuli?

Analyses:

Whole blood RNAseq transciptomes at base-line, clinical episode and convalesence

PBMC isolation, 16hr in vitro elicitation with whole parasites in presence/absence of autologous plasma.

Multiparameter flow cytometry for:

Surface Markers:

gd TCR

Live dead

CD3 (stained intracellularly)

CD4

CCR7 (memory marker)

CD45RA (memory marker)

CD27 (differentiation)

CD28 (differentiation)

Functional Markers:

IFNg (intracellular cytokine)

IL-2 (intracellular cytokine)

TNFa (intracellular cytokine)

CD154 (surface activation marker (stained in culture))

CD57 (surface exhaustion marker)

Post elicitation RNAseq transciptomes

Rotational gene set testing (ROAST) and competitive gene set testing (Camera), computational deconvolution.

Statistical model building, logistic regression, risk factor analysis.

ACKNOWLEDGMENTS

Schofield lab.

Krystal Evans

Ramin Mazhari

Ariel Achtman

Emily Eriksson

Marthe D’Ombrain

Leanne Robinson

Danika Hill

Stephanie Tan

Natalia Sampaio

Thuan Phuong

Amandine Carmagnac

Wasan Forsyth

Other WEHI labs.

Ivo Mueller

Diana Hansen

Marc Pelligrini

Gabrielle Belz

Bioinformatics

Terry Speed

Gordon Smyth

PNGIMR

Peter Siba

Inoni Betuela

Andrew Valleley

Suparat Phuanukoonnon

Queensland Mycobacterial Reference Laboratory

Chris Coulter

Swiss Tropical Public Health Institute

Marcel Tanner

Sebastian Gagneaux

Massachussetts Institute of Technology

Peter Seeberger

Mike Hewitt

Centers for Disease Control

John Barnwell

Ancora Pharmaceuticals Inc.

Stew Campbell

Merck Inc.

Jan ter Meulen

Craig Pryziecki

Mahidol University

Jetsumon Prachumsri

Australian Institute of Tropical Health

and Medicine

Brenda Govan

Natkuman Ketheesan CRESIB, Barcelona

Pedro Alonso

Carlota Dobano

Alfredo Mayor

Case Western Reserve University

Jim Kazura

Chris King

STUDY CHILDREN & GUARDIANS

Health Centre staff &

Teachers at Mugil and Megiar schools.

University of Melbourne

Stephen Rogerson

Louis Schofield, Director

AITHM - State and Federal Agreements

• Queensland Government $19.8 million – Oct. 2011

• Queensland Government $42.2 million – June 2013

• Federal Government $42.2 million (Sept 2013)

• Total $103 million

Budget breakdown

• State Government Budget $42 million

• 72% for Infrastructure – including equipment

• Infrastructure – AITHM Townsville

• Infrastructure – AITHM Torres Strait

• 28% for Operations and Research

• Federal Government Budget $42 million

• 62% for Infrastructure – including equipment

• Infrastructure – AITHM Cairns

• 38% for Operations and Research

Karkar

Balimo

Hiri

Wosera

Kikori

Torres Strait

Institutional Partnerships in our new TB program

• Papua New Guinea Institute of Medical Research (Peter Siba)

• Papua New Guinea Department of Health incl. Central Public Health Laboratory

• Australian Institute of Tropical Health and Medicine (Louis Schofield)

• The Walter and Eliza Hall Institute (Schofield, Mueller, Speed, Smyth, Belz)

• Queensland Health, including Local Health and Hospital Boards;

• Queensland Tropical Health Alliance (Louis Schofield);

• Swiss Tropical Public Health Institute (Marcel Tanner, Sebastian Gagneaux);

• Queensland Mycobacterial Reference Laboratory (Chris Coulter);

• International research institutions/agencies with a focus on tropical health;

• Key community groups and representatives.

Value proposition (for discussion)

Observational and interventional study designs in DSS, GPS

mapped, population-based longitudinal cohorts with nested clinical

case controls, in communities with v. high incidence of TB and

inadequate BCG coverage;

Integrated transcriptomic, multiparameter flow and statistical

analyses of diverse lymphoid lineages within intuitive conceptual

frameworks;

Collaborative ethos, community, institutional and political support.

Objectives:

Define natural and BCG-induced correlates of immunity and

susceptibility to TB

Improved public health tools and interventions

Vaccine trials

aeras schofield 21112013

Health & Medicine

ipti study

mugil study

albimana study

icemr study

vivax study

study villages

malgen severe malaria

alexishafen pregnancy