Molecular Epidemiology ofTuberculosis

Kathy DeRiemer, PhD, MPHSchool of Medicine

University of California, Davis

Overview

• TB transmission and pathogenesis• Genotyping methods• Genotyping for clinical management• Genotyping for TB Control Programs• Future applications of genotyping

Mycobacterium tuberculosis isinfectious and spreads through the air

Coughing, sneezing, talking, shouting, singing . . . . .

Mycobacterium tuberculosis

Clonal organism, but some progeny lose chunks of DNA and become different

Thick, lipid-richcell wall and membrane

Restriction fragment lengthpolymorphism (RFLP) analysis

Barnes PF, Cave MD. New Engl J Med 2003; 349:1149-56

MIRU-based genotyping

IS6110 RFLP genotyping

Variable number tandem repeats(VNTR), 21-635 bp

Sputgiesz RS, et al. J Clin Microbiol 2003; 41:4224-30

MIRU = mycobacterial interspersed repeat units

MLVA = multiple locus VNTR analysis

Spoligotyping

Spacer

H37Rv

IS6110DR locus

X

BCGH37Rv

X

Barnes PF, Cave MD. New Engl J Med 2003; 349:1149-56

Comparison of Genotyping Systems

Kremer et al., 1999. J Clin Micro (37), 2609-2618

Recent infection and rapid progression to disease

Reactivated disease

Who is Infected and Diseased?

Latency,Latent TB infection (LTBI)

Infection . . .

Transmission and pathogenesis

IS6110 RFLP of M. tuberculosis

Identify unsuspected transmission

Strain 4 – Unsuspected transmission among Southeast Asian personsStrain 5 – Unsuspected transmission among US born persons

“DNA fingerprints”

Clustered: Recent transmission

Outbreak in a facility for AIDS patients

Restriction fragment length polymorphisms (IS6110 RFLP)

Each vertical lane is an isolate of M. tuberculosis from a different TB patient

Unique: Reactivation of latent

TB infection

MIRU-VNTR

Advantages• Almost as discriminatory as IS6110 RFLP• Automated high throughput analysis of many

isolates• Digital results, easy to establish and compare

databases• New loci identified for strains in specific

geographical regions

Genotyping for Clinical Management

1. Confirm cross-contamination in thelaboratory• ~ 3% of patients do not have TB• Cross contamination = sputum smears are negative and only one specimen is culture positive

Genotyping for Clinical Management

2. Evaluate recurrent tuberculosis• Relapse of disease, caused by the

same strain that caused the firstepisode

• Relapse represents treatment failure• Reinfection, with a different strain of M. tuberculosis

Genotyping for Clinical Management

MIRU-VNTR

IS6110 RFLP

Exogenous reinfection was common (61.5%) Shen G, et al. Emerg Infect Dis 2006; 12:1776-8

Genotyping for Clinical Management

3. Evaluate isolates with differentpatterns of drug susceptibility• Cross contamination• Original organism developed drug

resistance during or after anti-tuberculosis therapy

• Transmission of a drug-resistant strain

Li X, et al. J Infect Dis 2007; 195: 864-9

Transmissionof drug-resistanttuberculosis in Shanghai

84% (27/32)of treated patientshad primaryresistance

Genotyping for Clinical Management

4. Evaluate mixed infections• Mixed infections: Shanghai, VNTR-7 loci• Estimated rate: 5.6% (95% CI 3.1-9.2%)

3.5%Beijing strains12.5%Non-Beijing strains4.1%New cases

15.7%Retreatment cases

Fang R, et al. Tuberculosis (Edinb.) 2008; in press

p < 0.05

p < 0.05

Genotyping for TB Control Programs

5. Evaluate chains of transmission

• Outbreak versus coincidentaloccurrence of a large number ofcases

• Guide public health measures toreduce transmission of M.tuberculosis

Genotyping for TB Control Programs

6. Identification of groups at increasedrisk for tuberculosis

Homelessshelters

Genotyping for TB Control Programs

Prisoners

Genotyping for TB Control Programs

Schools and day care centers

Genotyping for TB Control Programs

Residences for the elderly

Genotyping for TB Control Programs

M. tuberculosis Acute diseaseinfection (30%) (10% life, HIV+ 5-10% /yr)

ReactivationLatent (10% life, HIV+ 80%)

Exposure infection Lifelong

No M. tuberculosis containmentinfection (70%) (90%)

Impact of HIV

Genotyping for TB Control Programs

Impact of HIV

Comparison of genotype clusters, San Francisco

DeRiemer K, et al. Am J Respir Crit Care Med 2007; 176:936-44

Genotyping for TB Control Programs

Cattamanchi A, et al. Int J Tuberc Lung Dis 2006; 10:297-304

Predictors of clustering in San Francisco

Genotyping for TB Control Programs

7. Improving case finding and contactinvestigations

• Identify locations TB patients use Household versus community sites• Determine who needs to be screened

-75Source: Population Action International 1994

Migrating Populations

Compared to 1960-75, four-fold increase in migration during 1990s

US Tourist exports drug-resistant TB

Wedding - Greece

Honeymoon – Greece, Italy, Czech Republic (7 airline flights)

Homecoming – New York to Denver

TB contact (wife) wearing protective N95 respirator

“World-famous” infectious TB patient

M. tuberculosis can transmit frominfectious source cases to theircontacts

Contact investigation

Index case

Contacts

Infectedcontacts

+

Concentric circle approach

Yield of contact investigations:active TB

6.5% (5.7-7.4%)9Adult contacts

8.5% (7.4-9.7%)6.0% (4.7-7.5%)7.0% (6.0-8.0%)

1368

Child contacts < 5 years 5-14 years < 15 years

Pooled yield(95% CI)

Totalstudies (n)

Morrison J, et al. Lancet Infect Dis 2008; in press

Yield of contact investigations:latent TB infection

64.6% (62.9-66.2%)7Adult contacts

30.4% (28.6-32.3%)47.9% (45.5-50.4%)40.4% (38.7-42.2%)

147

10

Child contacts < 5 years 5-14 years < 15 years

Pooled yield(95% CI)

Totalstudies (n)

Morrison J, et al. Lancet Infect Dis 2008; in press

Genotyping for TB Control Programs7. Evaluation of TB programs

Cattamanchi A, et al. Int J Tuberc Lung Dis 2006; 10:297-304

San Francisco, California

Genotyping for TB Control Programs7. Evaluation of TB programs

Cattamanchi A, et al. Int J Tuberc Lung Dis 2006; 10:297-304

San Francisco, California

Future Applications of Genotyping

• Surveillance genotyping: Real-timegenotyping

• Rapid identification of outbreaks• Evaluation of social networks

Genome of Mycobacterium tuberculosis

Cole ST, et al. Nature 1998

Ernst JD, et al. J Clin Invest 2007; 117:1738-45

RD = region of difference, genomic deletion

Proposed evolutionary pathwayof the tubercle bacilli

BCG

Global Population Structure of M. tuberculosis

Six main lineages, geographically structuredStable associations between host and pathogen

Gagneux S, Small PM. Lancet Infect Dis 2007; 7(5):328-37Gagneux S, DeRiemer K, Van T, PNAS 2006; 103:2869-73

New Paradigms:Interface of Several Fields

Molecular epidemiology

Microbial Pathogenesis

Functional Genomics

Acknowledgments• Shanghai CDC and Fudan University Dr. Jian Mei, Xin Shen, Dr. Qian Gao and many more

• Key Project of Chinese National Programsfor Fundamental Research & Development(973 Program 2005CB523102, 2002CB51284)

• Chinese National Programs B63(2006AA027423, 2006AA022328)

• Shanghai Key Medical Foundation(grant 5III029)

• Shanghai Municipal Sciences & TechnologyCommission (grants 05PJ14025, 05DZ22320)

Acknowledgments• Stanford University Peter Small Sebastien Gagneux Qian Gao Bouke de Jong Anthony Tsolaki

• University of California, Davis and San Francisco Phillip Hopewell, Charles Daley• National Institutes of Health• Wellcome Trust