{"id":1839,"date":"2018-12-31T00:00:10","date_gmt":"2018-12-30T17:00:10","guid":{"rendered":"https:\/\/www.hivnat.org\/en\/?p=1839"},"modified":"2018-12-31T00:00:10","modified_gmt":"2018-12-30T17:00:10","slug":"impact-of-hiv-infection-on-the-population-genomics-of-drug-resistant-mycobacterium-tuberculosis-insights-from-macro-evolutionary-analyses","status":"publish","type":"post","link":"https:\/\/www.hivnat.org\/en\/studies\/1839\/","title":{"rendered":"Impact of HIV infection on the population genomics of drug-resistant Mycobacterium tuberculosis: insights from macro-evolutionary analyses"},"content":{"rendered":"\n\t\t\t\t\n<p class=\"wp-block-paragraph\"><strong>Project no.: <\/strong>HIV-NAT 188\/IeDEA TB genomics<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This study\nwill investigate the macroevolution of drug-resistant <em>M. tuberculosis.<\/em><strong><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Brief Summary: <\/strong>The gold standard for drug susceptibility testing (DST) in <em>Mycobacterium tuberculosis<\/em> involves\ntime-consuming assessments of bacterial growth at defined drug concentrations.\nWhole genome sequencing allows rapid detection of drug-resistant <em>M. tuberculosis<\/em> isolates. However,\nhigh-quality data linking quantitative phenotypic DST and genomic data has thus\nfar been lacking.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We determined drug resistance profiles of 177\ngenetically diverse clinical <em>M.\ntuberculosis <\/em>isolates from Democratic Republic of the Congo, Ivory Coast,\nPeru, Thailand, South Africa and Switzerland by semi-quantitative and\nquantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC\nMGIT 960 system and 7H11 agar dilution. We compared phenotypic drug\nsusceptibility results with predicted drug resistance profiles inferred by\nwhole genome sequencing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Both phenotypic DST methods identically\nclassified the strains into resistant\/susceptible in 73-99% of the cases,\ndepending on the drug. Increased minimal inhibitory concentrations (MICs) could\nbe explained by mutations identified by whole genome sequencing. The overall\nsensitivity and specificity of predicting drug resistance based on whole genome\nsequences were 87.5% and 82.1%, respectively. Wild type and mutant MIC\ndistributions overlapped partially due to mutational combinations, but this had\nno clinical implications.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Whole genome sequencing has high predictive\npower to infer resistance profiles without the need for time-consuming phenotypic\nmethods.<strong><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Results: <\/strong>We included 738 TB patients; median age\nwas 34 years (interquartile range [IQR]: 27-43); 269 (36%) female; 304 (41%)\nHIV-positive (median CD4 count at TB diagnosis: 192 cells\/\u00b5l; IQR: 80-369) and\n175 (57%) were on ART at TB treatment start. The NRC identified 460 (62%)\npansusceptible TB cases, 43 (6%) mono-resistance, 205 (28%) multidrug\nresistance (MDR), and 30 (4%) pre-extensive drug resistance (pre-XDR) or XDR\ncases. Local clinics diagnosed drug resistances using Xpert MTB\/RIF (276 cases,\n37%), culture (259, 35%), line-probe assay (LPA, 15, 2%), a combination of the\nabove (99, 13%), and unknown method (89, 12%). In 590 cases (80%), NRC\nconfirmed drug resistance profiles obtained at clinics. Among the 148 (20%)\ndiscrepant profiles, 56 (38%) were initially tested with Xpert MTB\/RIF, 60\n(40%) with culture, 4 (3%) with LPA, and 28 (19%) with combined tests. Among\ncases with discrepant resistance profiles, 10 (7%) were under-treated, 21 (14%)\nwere over-treated, and the remaining 117 (79%) cases were appropriately\ntreated. Mortality was loweramong\npatients whose resistance profiles were concordant or discrepant and leading to\nover-treatment, compared to patients with discrepant results leading to\nunder-treatment: 39 (7%), 4 (6%), and 15 (19%) deaths, respectively\n(p&lt;0.001). There was no evidence for an association between HIV status and\naccuracy of drug resistance profiles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">634 tuberculosis patients\nwere included; median age was 33.2 years, 239 (37.7%) were female, 272 (42.9%)\nHIV-positive and 69 (10.9%) patients died. Based on the reference laboratory\nDST, 394 (62.2%) strains were pan-susceptible, 45 (7.1%) mono-resistant, 163\n(25.7%) multidrug-resistant (MDR-TB), and 30 (4.7%) had pre-extensive or\nextensive drug resistance (pre-XDR\/XDR-TB). Results of reference and local laboratories\nwere discordant in 121 (19.1%) cases, corresponding to a sensitivity of 84.3%\nand a specificity of 90.8%. In patients with drug-resistant tuberculosis, discordant results were associated with increased mortality (risk ratio\n1.81; 95% CI 1.07-3.07). In logistic regression, compared to adequately treated\npatients with pan-susceptible strains, the adjusted odds ratio for death was\n4.23 (95% CI 2.16-8.29) for adequately treated patients with drug-resistant strains\nand 21.54 (95% CI 3.36-138.1) for inadequately treated patients with\ndrug-resistant strains. HIV status was not associated with mortality.<\/p>\n\t\t","protected":false},"excerpt":{"rendered":"<p>\t\t\t\tThis study will investigate the macroevolution of drug-resistant M. tuberculosis.\t\t<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[24],"tags":[],"class_list":["post-1839","post","type-post","status-publish","format-standard","hentry","category-studies"],"_links":{"self":[{"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/posts\/1839","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/comments?post=1839"}],"version-history":[{"count":0,"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/posts\/1839\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/media?parent=1839"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/categories?post=1839"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hivnat.org\/en\/wp-json\/wp\/v2\/tags?post=1839"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}