CPTR title slide. Daniela M Cirillo San Raffaele Scientific Institute NDWG-Cochair

CPTR title slide Daniela M Cirillo San Raffaele Scientific Institute NDWG-Cochair

Outline The global threat of Drug Resistant TB Actions to control MDR-TB Barriers to implement universal screening for DR Potential and limitation of current molecular tools The need for a centralized database

Drug Resistance: a threat for TB control 9.6 MILLION estimated TB cases Facts: 9.6 million TB cases 1.5 million TB deaths

Drug Resistance: a threat for TB control 9.6 MILLION estimated TB cases Facts: 9.6 million TB cases 1.5 million TB deaths 3.6 million undiagnosed Up to 30% of cases diagnosed never get treated 123,000 MDR-TB cases diagnosed 6 MILLION new cases diagnosed Facts: 480 000 with MDR Only 12 % new + 58% prev. treated are diagnosed

MDR is transmitted more than acquired State of the art mechanistic mathematical modeling approach show that the VAST majority of MDRTB cases in high burden settings are due to TRANSMISSION rather than ACQUISITION during therapy Consequences: Addressing the management of sensitive TB doesn t control MDR Targeted screening of individuals with MDR is highly insufficient Decentralization of DRTB diagnosis and testing with patients/clinicians friendly diagnostics and lesser toxic drugs

Actions Universal screening for Drug Resistance Use drugs according to the drug resistance pattern Use only effective drugs in shorter regimens

Fundamental knowledge is still missing for many drugs: break points and ECOFF Critical concentration (or cut-off) It refers to a testing method It is the lowest drug concentration that inhibit growth of at least 95% of strains never exposed to the drug tested and that simultaneously does not suppress resistant strains ECOFF MIC value identifying the upper limit of the wild type population Lineage-related variability

DST Critical Concentration WHO, 2008 WHO, 2012

Banu S et al, JCM 2014 Concordance among different tests Complete concordance among phenotypic tests: 82% 77% 50% 51%

Phenotypic methods : challenges and limitations Phenotypic methods: Require a positive culture Require appropriate infrastructure Require technical capacity Require fast and temperature controlled referral of samples containing class 3 microorganisms SC LC time to DST time to DST Standardization issues: Media Critical concentration Mechanism of action non compatible with in vitro testing Cost Time to results Quality of results day 1 5 10 15 20 40 45 50 >60 Average contamination rate in low resources settings: 15-35% liquid culture 1-15 solid cultures

Potential of molecular diagnostics User-friendly molecular diagnostics will increase accessibility to proper diagnosis of DR Reducing inequality due to poor accessibility to DST Reducing cost and suffering due to side effects Increase accessibility to new drugs in a protected manner Decreasing direct transmission in community by achieving early sterilization Decreasing the generation of additional resistance due to improper treatment

Xpert MTB rif roll out: a successful story showing potential and limitations of molecular Current screening based on molecular detection of mutations in rpob hot spot as proxy for rifampicin resistance

Coverage of identified SNPs by Xpert MTB/RIF Region # of SNPs Xpert MTB/RIF RRDR 366 363/366 (99.2%) Outside RRDR within rpob 24 0/24 (0.0%) Non-resistance conferring mutations* 16 5/16 (31.3%) * Non-resistance conferring mutations in rpob gene are silent mutations because we do not have mutations clearly not associated with R. rpob RRDR spans from cod. 505 to cod. 537: Xpert MTB/RIF: F514F, L533L, T525T, R529R, L521L Courtesy of Paolo Miotto

Theoretical accuracy of molecular tests for RR detection in clinical isolates All strains with confirmed mutations* # of strains Genotype MTBDRplus NIPRO 11953 Sensitivity (95% CIs) 99.57 (99.39-99.71) Specificity (95% CIs) 99.92 (99.79-99.97) Sensitivity (95% CIs) 99.57 (99.39-99.71) Specificity (95% CIs) 99.92 (99.79-99.97) All strains with confirmed mutations* # of strains Xpert MTB/RIF Sensitivity (95% CIs) 11953 99.57 (99.39-99.71) Specificity (95% CIs) 99.92 (99.79-99.97) * Excludes strains for which there is uncertainty on how to classify the mutation (minimal confidence and indeterminate) but includes all strains with mutations within or outside RRDR and non-resistance conferring genetic variants Courtesy of Paolo Miotto

Limitations of current genotypic methods Commercially available for few drugs with variable diagnostic accuracy Targeting the most relevant genes (not all) and often only hot spots Difficulties in the interpretations of the results Overall not perceived as fully trustable

L430 Q432 D435 S441 H445 S450 L452 Limit of Xpert MTB/RIF: Swaziland WHO recommended first-line Dx test to identify MDR-TB 81 bp hotspot region within rpob (426-452) Majority of rifampicin mutations associated with DR 30% of MDR strains carried a I491F mutation Review of 2009 survey (1% prevalence of TB) 491 position not included in Xpert MTB/RIF 426 491 V65F V176F P206R Y314C H323Y R426H rifampicin resistance-determining region (RRDR) Sanchez-Padilla et al., 2015 NEJM

LPAs Tagliani et al JCM 2015

WGS Virulence determinants Identification Genotyping All-in-one Drug-resistance Evolution Phylogenesis Population structure

Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study Timothy M Walker, DrMRCP, Thomas A Kohl, PhD, Shaheed V Omar, MSc, Jessica Hedge, PhD, Carlos Del Ojo Elias, MSc, Phelim Bradley, MPhil, Zamin Iqbal, DPhil, Silke Feuerriegel, PhD, Katherine E Niehaus, MS, Daniel J Wilson, DPhil, David A Clifton, DPhil, Georgia Kapatai, PhD, Camilla L C Ip, PhD, Rory Bowden, PhD, Francis A Drobniewski, PhD, Caroline Allix-Béguec, PhD, Cyril Gaudin, PhD, Julian Parkhill, PhD, Roland Diel, PhD, Philip Supply, PhD, Derrick W Crook, FRCPath, E Grace Smith, FRCPath, A Sarah Walker, PhD, Nazir Ismail, FCPath, Stefan Niemann, PhD, Tim E A Peto, FRCP The Lancet Infectious Diseases DOI: 10.1016/S1473-3099(15)00062-6 The Lancet Infectious Diseases DOI: (10.1016/S1473-3099(15)00062-6) Copyright 2015 Walker et al. Open Access article distributed under the terms of CC-BY Terms and Conditions

Lesson learnt from diagnostic implementations Phenotypic methods are too slow and too demanding to be adopted as routine methods to start patients on appropriate therapy Implementation and maintenance of capacity for DST is more challenging that implementation of molecular diagnostics Liquid DST has limitations and it is highly challenged by the required infrastructure, cost, contamination rate, Performance of Molecular tests depends on strains circulating in a geographical area

Existing barriers to develop fully comprehensive molecular assays Lack of or incomplete knowledge associating SNPs to mechanisms of resistance and mic Resistance markers in multiple genes Unclear link between mutations and clinical outcomes Presence of mutations not associated to resistance Poor and inconsistent DST and mic data, unclear CC, Heteroresistance Geographic differences, clone spreading

Current hurdles Data sets scattered across a high number of studies Rare mutations under represented Different studies use different methods (liquid/solid, CCs, SNP detection approach...) Few studies correlating SNP to MICs, MICs in broth not always reliable Few studies correlating SNP with clinical outcome Few mutations supported by functional genetics Need to be comprehensive and based on common standards

The need for a database for TB Standardized Understand SNP-DST relationships (including MIC and cross-resistance) Understand SNP-clinical outcome relationships Standardize interpretation of SNPs more complex interactions Global Understand frequency of mutations Understand the geographical distribution of mutations Improve statistical power for rare mutations Evaluate the global picture taking into account strains diversity, evolution, compensatory mutations, more complex interactions

Multiple databases with global representation ( quality assessed) Standardized to CDISC investigational database Retain original data ownership and decide on level of access Incorporation of statistical and graphing analysis tools Experts driven process : experts includes different areas of expertise and represents different settings

Main differences with other existing databases

Collaborative efforts to produce high quality data

Conclusion If the statistical power required to cover the possible variants is met the following could be achieved: accurate genetic resistance prediction for existing and new TB drugs by WGS; superior design of near-to-patient amplification-based molecular drug-resistance tests as alternatives to WGSonly solutions; better, faster and finally individualized treatment of drugresistant TB with positive impact on treatment outcomes and transmission of the disease

Thank You! CDC DTBE and NIAID www.cptrinitiative.org