What can we learn from the genetic code of TB? – Tim Walker

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What can we learn from the gene7c code of TB?

Timothy Walker

conditions and reduce inequity (Chisholm,1948; Rosen,1974). Afterthe second World War, a medically oriented TB control modelemerged (Amrith, 2002). Much hope was initially placed on massvaccination with BCG (Brimnes, 2007), hopes which were latershattered when it was demonstrated that the protective effect andepidemiological impact were limited (Rieder, 1999). When effectivechemotherapy for TB became available in the end of the 1940 andbeginning of 1950s, the control model switched to an almostcompletely curative focus. ‘‘Prevention starts with cure’’ becamea slogan for the global role out of effective treatments. It was pre-dicted that good coverage of effective treatment would result ina rapid decline in TB incidence (Styblo & Bumgarner, 1991).However, some recent observations have indicated that the impactof the present TB control strategy has been less than expected(WHO, 2008a). If these observations are confirmed, there may bea need to again broaden the strategy to include more preventiveefforts (Farmer, 1997; Jaramillo, 1999). One avenue for improved TBprevention is the ongoing quest for better TB vaccines and betterchemotherapy for preventive treatment. Another avenue leadsthrough actions to address the social determinants of TB, as well asthe more proximate risk factors (the physical and biomedicalfactors that directly influence the mechanisms that govern expo-sure to tuberculosis, risk of acquiring tuberculosis infection, andrisk of progression from tuberculosis infection to active tubercu-losis disease).

In order to assess the relevance and potential benefits of thelatter, a review was conducted to identify key social determinantsof TB and the possible causal pathways throughwhich they operate.We also reviewed the historical and recent progress in global TBcontrol with a view to assess the prospects of effectively controllingTB in the future with the current global strategy, and the potentialto increase epidemiological impact through adding actions onsocial determinants and risk factors.

Methods

A literature review was undertaken to identify historic andrecent trends in TB burden; social determinants of TB; and themostimportant proximate TB risk factors. We searched PubMed, thesend-list ‘‘TB-Related News and Journal Items Weekly Update’’(Centre for Disease Control and Prevention, Atlanta, USA), anda private data-base on tuberculosis publications from the past 40years (created by Dr Hans Rieder). The analysis was carried out bythe Stop TB Department at WHO, in collaboration with other rele-vant WHO Departments, including those responsible for tobaccocontrol, nutrition, alcohol and substance abuse, environmentalhealth, diabetes, and HIV/AIDS. The Priority Public Health ConditionKnowledge Network of the CSDH provided technical support andfeedback.

Findings

History of TB epidemiology and social change in industrializedcountries

Epidemiological TB data before the 20th century is imprecise.However, some broad trends have been identified with a reason-able level of certainty. The conventional wisdom is that the inci-dence of TB increased in industrialized countries in the 17th to 18thcenturies, peaking at different times in different places from themiddle of the 1700s in Great Britain to the beginning of the 1900s inJapan. From these trends, a temporal association has been sug-gested between increased TB incidence and rapid industrializationand urbanisation. TB rates were often particularly high in urbanareas. A plausible explanation is that transmission increased due to

increased population density and crowded living conditions, whilepoor nutritional status and other risk factors increased the risk ofbreak-down from infection to active disease in vulnerable groups,such as among the urban poor (Aparicio, Capurro, & Castillo-Chavez, 2002; Grundy, 2005; Rieder, 1999; Shimao, 2005). At thepeak of the epidemic in Europe TB death rates were close to 1% peryear in some urban areas, several times higher than the currentrates in countries with high HIV prevalence (Fig. 1).

Throughout the 20th century, even before the introduction ofeffective chemotherapy, TB incidence declined steadily in mostindustrialized countries although it did increase temporarily duringthe twoWorldWars (Fig. 2). This was a period of economic growth,social reform, poverty reduction and improved living conditions aswell as important advances in medicine and public health. Therelative importance of the factors that may have contributed to thedecline in TB in the 20th century is still a matter of debate.McKeown and Record (1962) suggested that before the 1950s thedecline was due to improved nutritional status and to some extentimproved living conditions, while medical and public healthinterventions had only a marginal impact before chemotherapybecame available. Others have convincingly argued that the intro-duction of sanatoria and other mechanisms to isolate infectiouscases as well as pasteurization of milk also had a significant impacton trends in the incidence of TB (Fairchild & Oppenheimer, 1998;Grundy, 2005; Lienhardt, 2001; Wilson, 2005). Natural selectionmay also have played a role (Davies, Tocque, Bellis, Rimmington, &Davies, 1999).

The discovery of the TB bacillus in 1882 was an outstandingadvance in the understanding of transmissible diseases, andmarked the beginning of the germ theory era. As a result of thisdiscovery, a TB control paradigm based mostly on the biologicalunderstanding of the disease gradually emerged. It received a finalboost with the discovery in the 1940s and 1950s of drugs that couldcure the disease (Amrith, 2002). The expanded pharmacopeia ofanti-TB drugs in the 1950s and 1960s helped to sustain and perhapsaccelerate the decline in TB incidence (Fig. 2). But this was not onlya period of rapid medical and health care advances. It was alsoa time of both rapid economic growth and accelerated welfarereforms in many industrialized countries (Navarro et al., 2006).Progress in TB control in the industrialized countries over the pastcenturies was thus brought about by advances on several fronts atthe same time – medical, public health, economic and social.

The evolution of the WHO’s TB control strategy

After decades of TB control neglect, with sustained high TBburden in many low- and middle income countries and a resur-gence of TB in several high-income countries in the 1980s, global

Fig. 1. Modelled tuberculosis deaths rates or selected European cities 1750–1950(source: Rieder, 1999).

K. Lonnroth et al. / Social Science & Medicine 68 (2009) 2240–2246 2241

Drivers of tuberculosis epidemics: The role of risk factors and social determinants

Knut Lonnroth*, Ernesto Jaramillo, Brian G. Williams, Christopher Dye, Mario RaviglioneWorld Health Organization, Geneva, Switzerland

a r t i c l e i n f o

Article history:Available online 23 April 2009

Keywords:TuberculosisDisease controlSocial determinantsRisk factorsReviewEpidemiologyWHO

a b s t r a c t

The main thrust of the World Health Organization’s global tuberculosis (TB) control strategy is to ensureeffective and equitable delivery of quality assured diagnosis and treatment of TB. Options for includingpreventive efforts have not yet been fully considered. This paper presents a narrative review of thehistorical and recent progress in TB control and the role of TB risk factors and social determinants. Thereview was conducted with a view to assess the prospects of effectively controlling TB under the currentstrategy, and the potential to increase epidemiological impact through additional preventive interven-tions. The review suggests that, while the current strategy is effective in curing patients and saving lives,the epidemiological impact has so far been less than predicted. In order to reach long-term epidemio-logical targets for global TB control, additional interventions to reduce peoples’ vulnerability for TB maytherefore be required. Risk factors that seem to be of importance at the population level include poorliving and working conditions associated with high risk of TB transmission, and factors that impair thehost’s defence against TB infection and disease, such as HIV infection, malnutrition, smoking, diabetes,alcohol abuse, and indoor air pollution. Preventive interventions may target these factors directly or viatheir underlying social determinants. The identification of risk groups also helps to target strategies forearly detection of people in need of TB treatment. More research is needed on the suitability, feasibilityand cost-effectiveness of these intervention options.

! 2009 Elsevier Ltd. All rights reserved.

Introduction

The Commission on Social Determinants for Health (CSDH), setup by the World Health Organization (WHO) in 2005, hasattempted to revitalize the debate and actions to improve healththrough addressing the ‘‘causes of the causes’’ of ill health. Thecommission has developed action frameworks in several fields toaddress the social determinants of health including early childhooddevelopment, globalization, urbanisation, employment conditions,social exclusion, etc. A key message from the CSDH is that publichealth achievements will largely depend on actions outside thehealth care sector (CSDH, 2008).

The work of the commission builds on a long social medicinetradition, from Virchow and the public health oriented social andenvironmental interventions that he and others inspired from themid-19th century onwards (Rosen, 1974), through the social modelof health adopted byWHO in the late 1940s (Chisholm,1948), to theHealth for All concept in the 1970s (WHO, 1978). It has not alwaysbeen easy to keep the social medicine concepts and action

frameworks alive (Amrith, 2002; Rosen, 1974). Several countrieshave tried consistently to pursue social policies aimed to promoteequity in health, some with a great deal of success (CSDH, 2008).However, in most countries, little of the social model of healthadvocated by WHO and others was translated into practice. Asa consequence, much preventable ill health and health inequityprevails today (CSDH, 2008).

The last 2–3 decades have seen reinvigorated attempts to fightdiseases with medical technologies alone. Key concepts in today’sdiscourse on disease control include: evidence-based medicine;health systems strengthening; and community involvement. Thelatter two focuses mainly on the capacity to deliver medical tech-nologies effectively. Meanwhile, social medicine has often beenreduced to actions to identify risk groups that need to be targetedwith medical interventions and attempts to influence individuals’risk behaviour (Porter, 2006).

The current global tuberculosis (TB) control paradigm mainlyfocuses on cutting transmission through early case detection andeffective treatment. Medical interventions are at the core of theglobal strategy (Lonnroth & Raviglione, 2008; WHO, 2006).However, historically, TB has been used as a prime example ofa ‘‘social disease’’, the control of which requires social, economicand environmental interventions. Furthermore, the need to controlTB has often been used as an argument for improving living

* Corresponding author. World Health Organization, Stop TB Department, 20Avenue Appia, CH-1211 Geneva, Switzerland. Tel.: þ41 22 7911628, fax: þ41 227914199.

E-mail address: [email protected] (K. Lonnroth).

Contents lists available at ScienceDirect

Social Science & Medicine

journal homepage: www.elsevier .com/locate/socscimed

0277-9536/$ – see front matter ! 2009 Elsevier Ltd. All rights reserved.doi:10.1016/j.socscimed.2009.03.041

Social Science & Medicine 68 (2009) 2240–2246

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9.4 million new cases of TB globally in 2009 80% of these in just 22 countries

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The M. tuberculosis genome -‐  Circular genome -‐  4.4 million base pairs long -‐  4000 genes -‐  Evolves by descent (no

horizontal gene transfer)

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Microbiology COMPASS: COMplete PAthogen Sequencing Solution

Articles

www.thelancet.com/infection Published online November 15, 2012 http://dx.doi.org/10.1016/S1473-3099(12)70277-3 5

within the variation we recorded, some rates were con-sistent with latent infection. All longitudinally sampled patients received antituberculosis drug treatment. HIV testing was not systematically done until 2011 (only eight results were available, all negative); however, UK rates of co-infection are fairly low, declining steadily from 9·0% in 2003, to 4·9% in 2010.28 We recorded weak evidence that the initial genetic diversity and rate of change in DNA sequences might vary be tween household outbreaks and longitudinally sampled individuals (joint vs separate models, p=0·08). However, the mu tation rate was lower in individuals followed up longitudinally (0·3 SNPs per genome per year [95% CI 0–0·6]) than in those in household outbreaks (0·6 SNPs per genome per year [0·3–0·9]), and the initial diversity was higher (1·2 SNPs [0·3–1·9] vs 0·2 SNPs [0·008–0·7]).

We used these results to construct two thresholds against which to assess the MIRU-VNTR-based community clusters. We expected epidemiological link-age consistent with transmission to exist between isolates diff ering by fi ve or fewer SNPs, and not to exist between isolates diff ering by more than 12 SNPs. We deemed pairs diff ering by six to 12 SNPs to be indeterminate.

The 11 community clusters were defi ned by their MIRU-VNTR profi le (or up to two locus mismatches; table). Starting from the fi rst case in each cluster, we constructed 11 networks (one for each cluster), accounting for 157 potential transmissions (edges; appendix). Within the three clusters centred on schools, 17 (85%) of 20 patients

could be epidemiologically linked (table), with no link confi rmed in three MIRU-VNTR-matched community isolates (the community-based case in cluster three was 35 SNPs away from the school isolates). In clusters six and seven, 27 (79%) of 34 patients could also be

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Figure 2: Genetic diversity of related isolates of Mycobacterium tuberculosis(A) Time-unadjusted pairwise genetic distances in SNPs. 22 of the 38 links within the 25 household clusters also occur within community clusters (ie, known linkage) but are shown with household isolates and not with community isolates. Top horizontal dashed line indicates the threshold above which direct transmission can be judged to be unlikely; bottom horizontal dashed line indicates the threshold below which transmission should be investigated. (B) Rate of change in DNA sequences estimated by coalescent-based maximum likelihood from the fi rst and last isolates from individuals with persistent open tuberculosis and from households. SNP=single nucleotide polymorphism. MIRU-VNTR=mycobacterial interspersed repetitive-unit–variable-number tandem-repeat.*Isolates had substantially diff erent MIRU-VNTR profi les. †Pair of Mycobacterium africanum isolates are represented two SNPs apart.

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Figure 3: SNPs between MIRU-VNTR types by number of locus diff erencesComparison of all isolates with complete 24-locus MIRU-VNTR profi les. As each isolate was compared to each other isolate, the number of SNPs and MIRU-VNTR loci at which they diverge was recorded. Results are plotted on a log scale. Circle sizes are proportionate to the number of pairs diverging by a specifi c number of loci and SNPs. Dashed red box includes isolates that diff er by fi ve or fewer SNPs. SNP=single nucleotide polymorphism. MIRU-VNTR=mycobacterial interspersed repetitive-unit–variable-number tandem-repeat.

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Tuberculosis rates (per 100,000 population)Oxfordshire (2007-2012)

Map produced using PHEGIS. Contact GIS Team, ERD/MRA, Porton Down. 01980-616937 or [email protected]

© Crown copyright and database rights 2013 Ordnance Survey 100016969.4Born in a high-‐incidence country: 109/100000 popula7on

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Contact investigations for outbreaks of Mycobacterium tuberculosis:

advances through whole genome sequencing

T. M. Walker1, P. Monk2, E. Grace Smith3 and T. E. A. Peto1,4

1) Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, 2) East Midlands South Health Protection Unit, Leicester, 3) West

Midlands Public Health Laboratory, Health Protection Agency, Heart of England NHS Foundation Trust, Birmingham and 4) Oxford National Institute of Health

Research Biomedical Research Centre, John Radcliffe Hospital, Oxford, UK

Abstract

The control of tuberculosis depends on the identification and treatment of infectious patients and their contacts, who are currently identified

through a combined approach of genotyping and epidemiological investigation. However, epidemiological data are often challenging to obtain,

and genotyping data are difficult to interpret without them. Whole genome sequencing (WGS) technology is increasingly affordable, and

offers the prospect of identifying plausible transmission events between patients without prior recourse to epidemiological data. We discuss

the current approaches to tuberculosis control, and how WGS might advance public health efforts in the future.

Keywords: Contact investigation, outbreak, tuberculosis, whole genome sequencing

Clin Microbiol Infect

Corresponding author: T. M. Walker, Nuffield Department of

Medicine, University of Oxford, John Radcliffe Hospital, Headley Way,

Headington, Oxford, OX3 9DU, UK

E-mail: [email protected]

Introduction

The decline in tuberculosis incidence and mortality in western

Europe since the mid-18th century pre-dates the discovery of

the tubercle bacillus in 1882 and the development of drug

treatments in the 1940s. The reasons for this decline are

disputed, but hypotheses range from improvements in living

standards to the isolation of ‘consumptives’ in Poor Law

infirmaries and sanatoria. By 1990, this trend had been

reversed [1].

Historical trends in Africa, Asia and South America are less

well characterized, but historical and phylogeographical data

are consistent with the epidemics on these continents dating

back to the late 19th century, after the disease was probably

(re)-introduced by European colonizers [2,3]. Although this is

relatively late into the colonial period, in India the timing

coincides with a surge in British troop numbers after the 1857

mutiny, and the building of the railways that provided efficient

channels of transmission for disease [4]. The global burden of

disease is now felt most acutely on these continents, where

many of the world’s 2 billion people infected with latent or

active tuberculosis can be found [5].

Today, tuberculosis remains a disease of poverty in high-

income and low/middle-income countries alike. Without major

breakthroughs among experimental vaccines [6], available

control measures include contact tracing, active case-finding,

prophylaxis, and treatment. In high-income countries, contact

investigations have benefited from advances in genotyping

techniques over the past two decades. The arrival of rapid-

turn-around whole genome sequencing (WGS) technology has

the potential to guide public health teams in all settings with

unprecedented precision.

Epidemiology

Observations that patients with pulmonary tuberculosis often

do not lead to any secondary cases fuelled debate in the 19th

century about whether the disease was communicable at

all [7]. Although this issue was definitively settled by

Koch’s discovery, how a disease with a predominance of

ª2013 The Authors

Clinical Microbiology and Infection ª2013 European Society of Clinical Microbiology and Infectious Diseases

REVIEW 10.1111/1469-0691.12183

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6 www.thelancet.com/infection Published online November 15, 2012 http://dx.doi.org/10.1016/S1473-3099(12)70277-3

epidemiologically linked (table). However, in the remaining six clusters, including one associated with an African immigrant community (cluster ten), only 25 (24%) of 103 patients could be epidemiologically linked (table).

None of 69 epidemiologically linked and two (15%) of 13 possibly epidemiology linked patients were separated by more than fi ve SNPs (seven and 12 SNPs respectively); conversely, 13 (17%) of 75 epidemiologically un linked patients were separated by more than fi ve SNPs and seven (9%) by more than 12 SNPs (three-way comparison exact p<0·0001; table). However, 22 potential transmissions of the 69 known to be epidemiologically linked featured in both household and community outbreaks. Excluding

those, the number of epidemiologically linked patients diff ering by fi ve SNPs or fewer was 47 (p=0·003).

The ability to identify cryptic outbreaks was most evident in cluster four, in which fi ve SNPs or fewer separated 38 individuals with a background of substance misuse for whom contact tracing had been diffi cult (table). The ability to rule out transmission was par ticularly evident in cluster ten, in which more than 30 SNPs separated fi ve individuals from a recent immigrant community and one British-born individual from the next nearest patient. In this cluster, isolates from ten patients from two cities 45 miles apart, with no known epidemiological links, could be genetically linked by fi ve or fewer SNPs.

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Figure 4: Genetic distances within 11 community clustersGenetic distances estimated with maximum likelihood. Each blue circle represents a node of people who were infected with isolates separated by no SNPs. Each number within a circle is one patient, the number indicates at which year during the outbreak they were diagnosed (the fi rst infected is represented by 0). For patients with several isolates, the closest in SNPs to the next patient is included. Black circles are added when patients within blue circles are separated by more than one SNP; one black circle represents a diff erence of one SNP. Dashed lines in clusters three and ten show larger SNP distances (not to scale), with numbers representing the SNP diff erence. Arrows indicate the next closest isolate in the sequenced collection. Cluster fi ve has three red nodes that were sequenced after the blue nodes; the existence of the central red node was suggested by the constellation of surrounding blue nodes. SNP=single nucleotide polymorphism. *Two isolates from one patient.

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25/03/2014

16

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25/03/2014

17

Is it worth it?

Isoniazid Rifampicin Ethambutol Pyrazinamide Streptomycin Moxifloxacin Amikacin

WGS (2013) MulitDrug Resistant katG_S315T rpoB_S450L embB_M306V rpsL_K43R rrs_A1401G

Sample sequenced in one UK site - November 2013 Genetic code suggested resistance to five drugs

Is it worth it?




Within 7 SNPs (mutations) of a sample from other end of the country

25/03/2014

18

Is it worth it?




Reference lab (2010) XD Resistant R R R R R R


Is it worth it?




Reference lab (2010) XD Resistant R R R R R R


Fluoroquinolone resistance muta/on Reference 2010 variant gyrA_A90V GCG GTG

25/03/2014

19

“Return of the plague” – BBC4 / iplayer

Oxford: Derrick Crook Tim Peto Sarah Walker Helen Barker Tonya Vo7nseva Louise Pankhurst Chris Conlon Carlos Del Ojo Adam Giess Tanya Golubchik Ka7e Jeffery Ian Bowler Marcus Morgan Lynn Parker Karen Payne Sheila Churchill Noel McCarthy Luisa Saldana Sarah Lamble Leeds Mark Wilcox Deborah Gascoyne-‐Binzi Brighton John Paul Kevin Cole

Birmingham: Grace Smith Li Xu Tonya Collins East Midlands South: Philip Monk TB reference labs: Francis Drobniewski Agnieszka Broda John Magee Anne Barres Ian Laurenson Colindale: Ibrahim Abubakar Lucy Thomas Laura Anderson Maeve Lalore Jennifer Davidson

Acknowledgements

Documents

What can we learn from the genetic code of TB? – Tim Walker