LATENCY: DOES IT EXIST?
JoAnne L. FlynnDepartment of Microbiology and Molecular Genetics
Department of ImmunologyCenter for Vaccine Research
University of Pittsburgh School of Medicine
National TB Lab Meeting 2011
Course of Mycobacterium tuberculosis infection
Activated MØ
Destroy bacillus
NO INFECTION
No initial destruction
Bacteria replicate
IL-12
IL-1
MØ
Bacterial
replication
and spread
Recruitment of
T cells and MØGRANULOMA
macrophage
T cell
LUNGSMØ
TNF
PRIMING
T CELLS
DC
LUNG
chemokines
airways
parenchyma
Lymph node
Granuloma
Control of replication
Latent TBinadequate control
of replication
ACTIVE TB
No disease
(control of replication
for lifetime)
Bacterial replication
Immunosuppression?
REACTIVATION
COURSE OF INFECTION
fibrosis
Tuberculosis from a clinical perspectiveA bimodal distribution of outcomes: latent or active
Primary TBLatent infection
No disease
Reactivation
90-95%
5-10%
5-10%
Active TB
P = pro-inflammatory A = anti-inflammatory
Can we define this spectrum by animal models and imaging?
Instead….M. tuberculosis infection may exist as a spectrum of outcomes
Lin and Flynn, JI, 2010
How can we assess the spectrum of M. tuberculosis infection?
Need a model with variable outcomes (like humans)
Need a model of latent M. tuberculosis infection
Need to be able to manipulate the model
Need to be able to study the infection serially and in real time
Animal models for tuberculosis research
Mouse: convenient, low variability, excellent reagents, well-characterizedbut no latent infection, pathology is different from humans
Guinea pigRabbit
Zebrafish: excellent genetic resources (M. marinum)
Non-human primates: close to humans, excellent reagentscons: cost, size, containment, animal-to-animal variability
Mimic some aspects of human pathologyLimited immunologic reagents
+ M. tbErdman25 cfuvia bronchoscope
Tuberculin Skin Test +Other immunologic tests +2-6 weeks
ACTIVE TB LATENT TB
6-8 months
Positive Chest x-ray Mycobacterial culture
•repeated + GA or BAL cultureClinical signs
•weight loss, •appetite loss•cough
No signs of disease CXR negative between 2-6 monthsMycobacterial culture
negative after 2 monthsClinical signs--none
Clinical definitions for classification of monkeys following Mtb infection
100%
Cynomolgus macaque
Progress to TB or remain stable
Reactivation
Spontaneousreactivation
Induced reactivation
(SHIV, SIV, TNF neutralization,CD8 or CD4 depletion)
stable
Active TB*N=69 (43%)
N=159 @ 6-8 months
Latent infectionN=83 (52%) Percolators
N=7 (4.4%)
Drug treatment
Outcome of low dose infection in cynomolgus macaques
*All manifestations of active TB seen in humans has been seen in macaques: Pott’s disease, cerebral TB, miliary TB, scrofula, cardiac TB, etc
Spectrum of granulomas in macaques
Caseous necrotic
Solid cellular Solid fibrotic
Suppurative necrotic
mineralized
Active vs latent monkeys: Clinical classifications validated by quantitative outcome measures at necropsy
*p=.001*p<.0001
*p=.0004 *p=.001
*Mann-Whitney, two tailed
Gross pathology CFU score
% positive tissue samples Sum of CFU/gram
PET/CT: Imaging modality for serial tracking of lesions and disease
BSL3 imaging suite Regional Biocontainment Lab (RBL)University of Pittsburgh
[18-F] FDG: fluorodeoxyglucose: incorporated into metabolically active cellsmarks areas of inflammation
Co-registration of PET/CT images: structural and functional map of disease
PET/CT in BSL3 facilityCT: structural map of lesions in organs
PET: functional map of lesions in organs
PET probe: specifically marks a cell with a particular property or function, probe is tagged with a positron emitter
University of Pittsburgh Jonathan Carney, Brian Lopresti, JoAnne Flynn, Jim Frye, and Jamie Tomko
Visualization of Small (1 mm) Tuberculous Lesions
Fusion of High Resolution microPET and Diagnostic Helical CT
1 cm 1 cm
SUV
Tuberculosis granulomas
PET CT
Fusion
Detection of small lesions (~1mm) in lungs
Not all lesions are FDG+
RLL 1 RLL 2
SUV max size CFU
RLL 1 4.6 2.7 mm 7000
RLL 2 3.4 1.7 mm 1333
The challenge: Matching lesions from scan to lesions at necropsy
Pre-treatment 1 Mo RIF 2 Mo RIF
PET/CT: track changes in lesions during drug treatment
21608
How does a drug affect a specific lesion over time?
Overall PET signals are reduced when drugs are working
pre-treatment 1 month HRM
1 mm 5 mm
0
5
10
15
20
25
30
35
40
45
0 5 10 15 20 25
PET
FD
G m
ax S
UV
(co
rre
cte
d)
Weeks PI
19608: Granulomas
RLL 2
LLL gran A
RLL 6
RLL 1
RLL 5
Scale
RLL 6'
Individual lesions are dynamic in monkeys with active TBIndependent changes in granulomas in a single monkey
PET
FD
G S
UV
max
Weeks PI
Can imaging be used to study latency and reactivation?
Latent TB: a spectrum of lesions in lungs (8 different monkeys)
54-CJK
58 - LJK
Humans with latent M. tuberculosis infection also have a spectrum of lesion types
Clif BarryRay Cho
Spectrum of latent infection as quantified by PET/CT imaging
28 latently infected monkeys: 18F-FDG PET/CT characteristics
Lung lesions
Mediastinal Lymph nodes
Total number of lung lesions/latent monkey
What happens during reactivation?
Where does reactivation start?
How does it spread?
Do all lung or lymph node granulomas reactivate?
Using PET/CT imaging to track reactivation
Lung lesion grows and is “hotter” following anti-TNF mediated reactivation
latent
2 Weeks anti-TNF Ab
4 Weeks anti-TNF Ab
Reactivation with anti-TNF: lymph nodes and dissemination
0
5
10
15
20
25
30
35
40
45
50
55
-1 0 1 2
PET
FD
G m
ax S
UV
(co
rre
cte
d)
Months anti-TNF
16606: Lymph Node
Carinal LN
0
5
10
15
20
25
30
35
40
-1 0 1 2
PET
FD
G m
ax S
UV
(co
rre
cte
d)
Months anti-TNF
16606: Granuloma
L1
SCALE
Baseline 3 WK anti-TNF 5 WK anti-TNF
CFU 2.2x104/gm
CFU 2.6x104/gm
Anti TNF Tx
CFU score 19.9% positive 23.8
0
5
10
15
20
25
30
35
40
-1 0 1 2
PET
FD
G m
ax S
UV
(co
rre
cte
d)
Months Humira
L3
L4
L1
L2
L5
SCALE
Granulomas
0
5
10
15
20
25
30
35
40
-1 0 1 2
PET
FD
G m
ax S
UV
(co
rre
cte
d)
Months anti-TNF
11108: Lymph Nodes
R Cranial Hilar LN
R Carinal LN
SCALE
Latent, anti-TNF reactivation : not all granulomas reactivate the same
CFU score 36.3% positive 33%
L5 8000 CFUL2 0 CFU
R carinal (red) CFU 708R cran HLN (blue) CFU 17500
Spectrum of M. tuberculosis infection: includes “percolators”
Fulminant (sepsis)
miliary
extrapulmonary
Pulmonary TB
Chronic TB
Low grade TB
Dormant infection
clearance
Subclinical infection
Active
TB
“percolating”
No signs of diseaseNormal chest x-rayOccasional positive BAL or GA culture
Is a percolator more likely to reactivate?
Higher on the spectrum of latency?
Represent “subclinical” disease?
Test this by depleting CD8 T cells in “true” latent vs percolator
Percolator monkeys (clinically latent but occasional + BAL or GA)
Mtb
8 months
antiCD8 antibody
Latent orpercolator Necropsy
Percolator monkeys reactivate when CD8 T cells are depleted.Latent monkeys do not.
p=.01p=.03
Percolators may have more “hot” lesions in lungs than “true latents”
Latent Lung Percolator Lung
Latent LN Percolator LN
N=28 latents N=4 percolators
Not all latent monkeys reactivate in response to anti-TNF AbPercolator monkeys reactivate
Percolator (reactivated)
Latent (reactivated)Latent (No reactivation)
Summary• Latent TB reflects a spectrum of infection
• PET/CT imaging can monitor infection in real-time and serially
• Reactivation can occur in lymph nodes or lung granulomas
• Not all lesions are equal when it comes to susceptibility to reactivation
• Not all reactivation triggers are equally effective– CD4 T cell depletion
– CD8 T cell depletion
– TNF neutralization
– SIV co-infection
• Spectrum may dictate risk of reactivation from any trigger—who is at risk?
• Challenge: Identify the persons most at risk so they can be treated—define in monkeys and humans with imaging and immunologic biomarkers
Acknowledgements• Chris Janssen• Brian Lopresti• Jaime Tomko• Mark Rodgers• Amy Myers
• Jim Frye• Melanie O’Malley• Paul Johnston• Dan Fillmore• Jim Mountz• Cathy Cochran• Lekneitah Smith• Carolyn Bigbee• Matt Bigbee• Jiayao Phuah• Angela Green• Tao Sun
GC11 groupDouglas Young (NIMR, Imperial)Clifton Barry, III (NIH)Rob Wilkinson (NIMR, UCT)
Ed Klein
P. Ling LinChildren’s Hospital
Teresa Coleman Chuck Scanga
Eoin Carney
FundingNIH NIAID/NHLBIBill and Melinda Gates Foundation Wellcome TrustEllison Foundation
Collin Diedrich
Josh Mattila
University of MichiganDenise Kirschner