Use of correlates of immunity in vaccinology Adam Penn-Nicholson - - PowerPoint PPT Presentation

Use of correlates of immunity in vaccinology

Adam Penn-Nicholson South African Tuberculosis Vaccine Initiative 11th November 2014 10th Annual African Vaccinology Course (AAVC): Developing Vaccinology Expertise for Africa

What is the point of vaccination?

• Protection from disease
• Immunogenicity ≠ protection

Characteristics of Different Types

• f Vaccines
• Live

attenuated

• Whole Killed /

Inactivated

• Subunit

– Recombinant protein, peptide – Polysaccharid e

• Viral Vector
• DNA Vaccines

Currently licensed vaccines

Vaccines Vaccine type Serum IgG Mucosal IgG Mucosal IgA T cells Diphtheria toxoid Toxoid ++ (+) Hepatitis A Killed ++ Hepatitis B (HBsAg) Protein ++ Hib PS PS ++ (+) Hib glycoconjugates PS-protein ++ ++ Influenza Killed, subunit ++ (+) Influenza intranasal Live attenuated ++ + + + (CD8+) Japanese encephalitis Killed ++ Measles Live attenuated ++ + (CD8+) Meningococcal PS PS ++ (+) Meningococcal conjugates PS-protein ++ ++ Mumps Live attenuated ++ Papillomavirus (human) VLPs ++ ++ Pertussis, whole cell Killed ++ Pertussis, acellular Protein ++ +?(CD4+) Pneumococcal PS PS ++ (+) Pneumococcal conjugates PS-protein ++ ++ Polio Sabin Live attenuated ++ ++ ++ Polio Salk Killed ++ + Rabies Killed ++ Rotavirus VLPs (+) (+) ++ Rubella Live attenuated ++ Tetanus toxoid Toxoid ++ Tuberculosis (BCG) Live mycobacteria ++(CD4+) Typhoid PS PS + (+) Varicella (chickenpox) Live attenuated ++ +?(CD4+) Varicella (zoster) Live attenuated ++(CD4+) Yellow fever Live attenuated ++

Modified from Vaccines (6th Ed.), Plotkin

Evolution of vaccine development

Rappuoli R, Aderem A. A 2020 vision for vaccines against HIV, tuberculosis and malaria. Nature 2011;473:463–469.

Technologies for vaccine development

Rappuoli R, Mandl CW, Black S, De Gregorio E. Vaccines for the twenty-first century society. Nat Rev Immunol 2011;11:865–872.

Correlates of Vaccine Induced Immunity

Vaccines Vaccine type Serum IgG Mucosal IgG Mucosal IgA T cells Diphtheria toxoid Toxoid ++ (+) Hepatitis A Killed ++ Hepatitis B (HBsAg) Protein ++ Hib PS PS ++ (+) Hib glycoconjugates PS-protein ++ ++ Influenza Killed, subunit ++ (+) Influenza intranasal Live attenuated ++ + + + (CD8+) Japanese encephalitis Killed ++ Measles Live attenuated ++ + (CD8+) Meningococcal PS PS ++ (+) Meningococcal conjugates PS-protein ++ ++ Mumps Live attenuated ++ Papillomavirus (human) VLPs ++ ++ Pertussis, whole cell Killed ++ Pertussis, acellular Protein ++ +?(CD4+) Pneumococcal PS PS ++ (+) Pneumococcal conjugates PS-protein ++ ++ Polio Sabin Live attenuated ++ ++ ++ Polio Salk Killed ++ + Rabies Killed ++ Rotavirus VLPs (+) (+) ++ Rubella Live attenuated ++ Tetanus toxoid Toxoid ++ Tuberculosis (BCG) Live mycobacteria ++(CD4+) Typhoid PS PS + (+) Varicella (chickenpox) Live attenuated ++ +?(CD4+) Varicella (zoster) Live attenuated ++(CD4+) Yellow fever Live attenuated ++

Modified from Vaccines (6th Ed.), Plotkin Ab response accounts for protection elicited by most current vaccines

Correlates of Protective Immunity Immunity

Rappuoli R, Aderem A. A 2020 vision for vaccines against HIV, tuberculosis and malaria. Nature 2011;473:463–469.

A preparation of antibodies that neutralizes a pathogen and is administered before or around the time of known or potential exposure.

Passive Vaccine

Not all antibodies are equal

Plotkin SA. Vaccines: Correlates of Vaccine‐Induced Immunity. Clinical Infectious Diseases 2008;47:401–409.

Yellow Fever Vaccine YF-17D

The gold standard of vaccinology

gp120 trimeric structure

Adapted from Wyatt et al. NATURE VOL 393 18 JUNE 1998 pp. 705-711

View from target membrane perspective

Broadly Neutralizing Antibody Development Limitations:

From Wyatt et al. NATURE VOL 393 18 JUNE 1998 pp. 705-711

Monomeric gp120

Inner domain Outer domain

Most antibodies elicited are non-neutralizing

• r strain-specific

HIV Phase III Vaccine Trial RV144

31% protective efficacy

Correlates of protection: Non-neutralizing V1/V2 binding Abs and ADCC

Systems Immunology

Li S, Nakaya HI, Kazmin DA, Oh JZ, Pulendran B. Systems biological approaches to measure and understand vaccine immunity in humans. Semin Immunol 2013;25:209–218.

Need the right model

Need the right model

Need the right model

Need the right model

Mycobacterium tuberculosis (M.tb)

1/3 of global population is estimated to be M.tb infected 9 million develop TB disease / year 1.5 million deaths / year 25-50% of exposed individuals 90% latent infection

M.tb infected

10% active disease

M.tb uninfected

What distinguishes M.tb infected adolescents who progress to TB disease from the M.tb infected adolescents who do not?

M.tb containment in a granuloma

Holes in the lungs is exactly what M.tb needs to spread

Key transition stages of the TB timeline

TB treatment M.tb infection TB disease Exposure TB diagnosis Reinfection TB Exposure Relapse

1 2 3 4

Cure Risk of M.tb infection Risk of TB disease Treatment success Risk of recurrent TB

Validated biomarkers of protection against TB

G Poste. Nature 2011;459:156

IL-2 IL-17 IFN-γ TNF-α

Determinants of progression from infection to TB disease are unknown

• Classical Th1 responses do not associate

with risk of TB disease.

What distinguishes M.tb infected individuals who progress to TB disease from M.tb infected individuals who do not?

T cells are important

Different Approaches to TB Disease Biomarker Discovery

Biomarker discovery

Unbiased

“Validation” of candidates

Hypothesis- driven

Systems-level analyses have compared active TB to LTBI

Predictive Gene Expression Signatures

• Goal: Delineate and validate signatures of risk of TB

disease following natural infection with M.tb.

• Biomarkers for TB disease would:
• Facilitate screening of new TB vaccines
• Facilitate treatment to prevent disease
• Stimulate development of new vaccines and drugs
• Guide approaches to identify correlates of

protection

11 high schools in Worcester and surrounding towns 6,363 adolescents (age 12-18) enrolled

Adolescent Cohort Study

87 adolescents developed TB disease during the ACS 46 “per protocol” TB cases met inclusion criteria

Study design

No TB Disease (Controls)

TST+/QFN+

2 years Sample Collection Adolescents enrolled TB Disease (Cases)

TST+/QFN+, Microbiological confirmation + > 6 months

Carefully matched: Age, gender, ethnicity, school, prior episode of TB 46 Cases 107 Controls 364 PAXgene whole blood samples over 2 years of follow up All enrolled participants are healthy, M.tb-infected adolescents HIV negative

Controls Cases Training Set Test Set

RNA-Seq + qRT-PCR

Red = Higher expression Blue = Lower expression

2340 genes significant

Network visualization (Gene-level PCR classifier)

Examples of samples predicted case: Case case > 50% classifier votes Control

Samples Assays

Simple PCR Test for risk of TB

Fluidigm Dynamic Array System 96 x 96 = 9216 reactions per plate

Correlate of risk of TB disease helps us limit the number of participants recruited into trials

Model Sensitivity (%) Specificity (%) Clinical Enrichment PSVM1 70 61 1.79 PSVM2 43 89 3.91 Combined PSVM 38 89 3.45 Combined PR 52 80 2.60

THE BIOLOGY - Predicted innate immune response network associated with TB disease progression

Colors: Progressors vs. Non-progressors (0.5-0yrs before diagnosis)

Interactions

Systems Vaccinology

Pulendran B. Systems vaccinology: probing humanity's diverse immune systems with vaccines. Proc Natl Acad Sci USA 2014;111:12300–12306.

Pulendran B. Systems vaccinology: probing humanity's diverse immune systems with vaccines. Proc Natl Acad Sci USA 2014;111:12300–12306.

Thanks!