Last data update: Apr 18, 2025. (Total: 49119 publications since 2009)
Records 1-3 (of 3 Records) |
Query Trace: Hall PJ[original query] |
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The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis
Walker TM , Fowler PW , Knaggs J , Hunt M , Peto TE , Walker AS , Crook DW , Walker TM , Miotto P , Cirillo DM , Kser CU , Knaggs J , Iqbal Z , Hunt M , Chindelevitch L , Farhat MR , Comas I , Comas I , Posey J , Omar SV , Peto TE , Walker AS , Crook DW , Suresh A , Uplekar S , Laurent S , Colman RE , Rodwell TC , Nathanson CM , Zignol M , Ismail N , Rodwell TC , Walker AS , Steyn AJC , Lalvani A , Baulard A , Christoffels A , Mendoza-Ticona A , Trovato A , Skrahina A , Lachapelle AS , Brankin A , Piatek A , GibertoniCruz A , Koch A , Cabibbe AM , Spitaleri A , Brandao AP , Chaiprasert A , Suresh A , Barbova A , VanRie A , Ghodousi A , Bainomugisa A , Mandal A , Roohi A , Javid B , Zhu B , Letcher B , Rodrigues C , Nimmo C , Nathanson CM , Duncan C , Coulter C , Utpatel C , Liu C , Grazian C , Kong C , Kser CU , Wilson DJ , Cirillo DM , Matias D , Jorgensen D , Zimenkov D , Chetty D , Moore DA , Clifton DA , Crook DW , vanSoolingen D , Liu D , Kohlerschmidt D , Barreira D , Ngcamu D , SantosLazaro ED , Kelly E , Borroni E , Roycroft E , Andre E , Bttger EC , Robinson E , Menardo F , Mendes FF , Jamieson FB , Coll F , Gao GF , Kasule GW , Rossolini GM , Rodger G , Smith EG , Meintjes G , Thwaites G , Hoffmann H , Albert H , Cox H , Laurenson IF , Comas I , Arandjelovic I , Barilar I , Robledo J , Millard J , Johnston J , Posey J , Andrews JR , Knaggs J , Gardy J , Guthrie J , Taylor J , Werngren J , Metcalfe J , Coronel J , Shea J , Carter J , Pinhata JM , Kus JV , Todt K , Holt K , Nilgiriwala KS , Ghisi KT , Malone KM , Faksri K , Musser KA , Joseph L , Rigouts L , Chindelevitch L , Jarrett L , Grandjean L , Ferrazoli L , Rodrigues M , Farhat M , Schito M , Fitzgibbon MM , Loemb MM , Wijkander M , Ballif M , Rabodoarivelo MS , Mihalic M , Wilcox M , Hunt M , Zignol M , Merker M , Egger M , O'Donnell M , Caws M , Wu MH , Whitfield MG , Inouye M , Mansj M , DangThi MH , Joloba M , Kamal SM , Okozi N , Ismail N , Mistry N , Hoang NN , Rakotosamimanana N , Paton NI , Rancoita PMV , Miotto P , Lapierre P , Hall PJ , Tang P , Claxton P , Wintringer P , Keller PM , Thai PVK , Fowler PW , Supply P , Srilohasin P , Suriyaphol P , Rathod P , Kambli P , Groenheit R , Colman RE , Ong RTH , Warren RM , Wilkinson RJ , Diel R , Oliveira RS , Khot R , Jou R , Tahseen S , Laurent S , Gharbia S , Kouchaki S , Shah S , Plesnik S , Earle SG , Dunstan S , Hoosdally SJ , Mitarai S , Gagneux S , Omar SV , Yao SY , GrandjeanLapierre S , Battaglia S , Niemann S , Pandey S , Uplekar S , Halse TA , Cohen T , Cortes T , Prammananan T , Kohl TA , Thuong NTT , Teo TY , Peto TEA , Rodwell TC , William T , Walker TM , Rogers TR , Surve U , Mathys V , Furi V , Cook V , Vijay S , Escuyer V , Dreyer V , Sintchenko V , Saphonn V , Solano W , Lin WH , vanGemert W , He W , Yang Y , Zhao Y , Qin Y , Xiao YX , Hasan Z , Iqbal Z , Puyen ZM , CryPticConsortium theSeq , Treat Consortium . Lancet Microbe 2022 3 (4) e265-e273 Background: Molecular diagnostics are considered the most promising route to achievement of rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO-endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: In this systematic analysis, we used a candidate gene approach to identify mutations associated with resistance or consistent with susceptibility for 13 WHO-endorsed antituberculosis drugs. We collected existing worldwide MTBC whole-genome sequencing data and phenotypic data from academic groups and consortia, reference laboratories, public health organisations, and published literature. We categorised phenotypes as follows: methods and critical concentrations currently endorsed by WHO (category 1); critical concentrations previously endorsed by WHO for those methods (category 2); methods or critical concentrations not currently endorsed by WHO (category 3). For each mutation, we used a contingency table of binary phenotypes and presence or absence of the mutation to compute positive predictive value, and we used Fisher's exact tests to generate odds ratios and Benjamini-Hochberg corrected p values. Mutations were graded as associated with resistance if present in at least five isolates, if the odds ratio was more than 1 with a statistically significant corrected p value, and if the lower bound of the 95% CI on the positive predictive value for phenotypic resistance was greater than 25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: We analysed 41 137 MTBC isolates with phenotypic and whole-genome sequencing data from 45 countries. 38 215 MTBC isolates passed quality control steps and were included in the final analysis. 15 667 associations were computed for 13 211 unique mutations linked to one or more drugs. 1149 (73%) of 15 667 mutations were classified as associated with phenotypic resistance and 107 (07%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was more than 80%. Specificity was over 95% for all drugs except ethionamide (914%), moxifloxacin (916%) and ethambutol (933%). Only two resistance mutations were identified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: We present the first WHO-endorsed catalogue of molecular targets for MTBC drug susceptibility testing, which is intended to provide a global standard for resistance interpretation. The existence of this catalogue should encourage the implementation of molecular diagnostics by national tuberculosis programmes. Funding: Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation. 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license |
Whole-Genome Sequencing to Identify Missed Rifampicin and Isoniazid Resistance Among Tuberculosis Isolates-Chennai, India, 2013-2016.
Tamilzhalagan S , Shanmugam S , Selvaraj A , Suba S , Suganthi C , Moonan PK , Surie D , Sathyanarayanan MK , Gomathi NS , Jayabal L , Sachdeva KS , Selvaraju S , Swaminathan S , Tripathy SP , Hall PJ , Ranganathan UD . Front Microbiol 2021 12 720436 ![]() India has a high burden of drug-resistant tuberculosis (DR TB) and many cases go undetected by current drug susceptibility tests (DSTs). This study was conducted to identify rifampicin (RIF) and isoniazid (INH) resistance associated genetic mutations undetected by current clinical diagnostics amongst persons with DR TB in Chennai, India. Retrospectively stored 166 DR TB isolates during 2013-2016 were retrieved and cultured in Löwenstein-Jensen medium. Whole genome sequencing (WGS) and MGIT DST for RIF and INH were performed. Discordant genotypic and phenotypic sensitivity results were repeated for confirmation and the discrepant results considered final. Further, drug resistance-conferring mutations identified through WGS were analyzed for their presence as targets in current WHO-recommended molecular diagnostics. WGS detected additional mutations for rifampicin and isoniazid resistance than WHO-endorsed line probe assays. For RIF, WGS was able to identify an additional 10% (15/146) of rpoB mutant isolates associated with borderline rifampicin resistance compared to MGIT DST. WGS could detect additional DR TB cases than commercially available and WHO-endorsed molecular DST tests. WGS results reiterate the importance of the recent WHO revised critical concentrations of current MGIT DST to detect low-level resistance to rifampicin. WGS may help inform effective treatment selection for persons at risk of, or diagnosed with, DR TB. |
Systematic Review of Pooling Sputum as an Efficient Method for Xpert MTB/RIF Tuberculosis Testing during the COVID-19 Pandemic.
Cuevas LE , Santos VS , Lima Svma , Kontogianni K , Bimba JS , Iem V , Dominguez J , Adams E , Atienzar AC , Edwards T , Squire SB , Hall PJ , Creswell J . Emerg Infect Dis 2021 27 (3) 719-727 GeneXpert-based testing with Xpert MTB/RIF or Ultra assays is essential for tuberculosis diagnosis. However, testing may be affected by cartridge and staff shortages. More efficient testing strategies could help, especially during the coronavirus disease pandemic. We searched the literature to systematically review whether GeneXpert-based testing of pooled sputum samples achieves sensitivity and specificity similar to testing individual samples; this method could potentially save time and preserve the limited supply of cartridges. From 6 publications, we found 2-sample pools using Xpert MTB/RIF had 87.5% and 96.0% sensitivity (average sensitivity 94%; 95% CI 89.0%-98.0%) (2 studies). Four-sample pools averaged 91% sensitivity with Xpert MTB/RIF (2 studies) and 98% with Ultra (2 studies); combining >4 samples resulted in lower sensitivity. Two studies reported that pooling achieved 99%-100% specificity and 27%-31% in cartridge savings. Our results show that pooling may improve efficiency of GeneXpert-based testing. |
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