ABSTRACT
Radiology may better define tuberculosis (TB) severity and guide duration of treatment. We aimed to systematically study baseline chest X-rays (CXR) and their association with TB treatment outcome using real-world data. We used logistic regression to associate TB treatment outcomes with CXR findings, including percent of lung involved in disease (PLI), cavitation, and Timika score, alone or in combination with other clinical characteristics, stratifying by drug resistance status and HIV (n = 2,809). We fine-tuned convolutional neural nets (CNN) to automate PLI measurement from the CXR DICOM images (n = 5,261). PLI is the only CXR finding associated with unfavorable outcome across drug resistance and HIV subgroups [Rifampicin-susceptible disease without HIV, adjusted odds ratio (aOR) 1·11 (1·01, 1·22), P-value 0·025]. The most informed model of baseline characteristics tested predicts outcome with a validation mean area under the curve (AUC) of 0·769. PLI and Timika (AUC 0·656 and 0·655 respectively) predict unfavorable outcomes better than cavitary information (best AUC 0·591). The addition of PLI improves prediction compared to sex and age alone (AUC 0·680 and 0·627, respectively).PLI>25% provides a better separation of favorable and unfavorable outcomes compared to PLI>50%. The best performing ensemble of CNNs has an AUC 0·850 for PLI>25% and mean absolute error of 11·7% for the PLI value. PLI is better than cavitation for predicting unfavorable treatment outcome in pulmonary TB in non-clinical trial settings and it can be accurately and automatically predicted with CNNs. One Sentence Summary: The percent of lung involved in disease improves prediction of unfavorable outcomes in pulmonary tuberculosis when added to clinical characteristics.
ABSTRACT
Several human-adapted Mycobacterium tuberculosis complex (Mtbc) lineages exhibit a restricted geographical distribution globally. These lineages are hypothesized to transmit more effectively among sympatric hosts, that is, those that share the same geographical area, though this is yet to be confirmed while controlling for exposure, social networks and disease risk after exposure. Using pathogen genomic and contact tracing data from 2,279 tuberculosis cases linked to 12,749 contacts from three low-incidence cities, we show that geographically restricted Mtbc lineages were less transmissible than lineages that have a widespread global distribution. Allopatric host-pathogen exposure, in which the restricted pathogen and host are from non-overlapping areas, had a 38% decrease in the odds of infection among contacts compared with sympatric exposures. We measure tenfold lower uptake of geographically restricted lineage 6 strains compared with widespread lineage 4 strains in allopatric macrophage infections. We conclude that Mtbc strain-human long-term coexistence has resulted in differential transmissibility of Mtbc lineages and that this differs by human population.
Subject(s)
Host-Pathogen Interactions , Mycobacterium tuberculosis , Sympatry , Tuberculosis , Humans , Mycobacterium tuberculosis/genetics , Mycobacterium tuberculosis/classification , Tuberculosis/transmission , Tuberculosis/microbiology , Tuberculosis/epidemiology , Contact Tracing , Female , Adult , Male , Macrophages/microbiology , Incidence , PhylogenySubject(s)
Antitubercular Agents , Diarylquinolines , Microbial Sensitivity Tests , Mycobacterium tuberculosis , Reference Standards , Diarylquinolines/therapeutic use , Diarylquinolines/pharmacology , Humans , Mycobacterium tuberculosis/drug effects , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/microbiologyABSTRACT
BACKGROUND: The antibiotic bedaquiline is a key component of new WHO regimens for drug-resistant tuberculosis; however, predicting bedaquiline resistance from bacterial genotypes remains challenging. We aimed to understand the genetic mechanisms of bedaquiline resistance by analysing Mycobacterium tuberculosis isolates from South Africa. METHODS: For this genomic analysis, we conducted whole-genome sequencing of Mycobacterium tuberculosis samples collected at two referral laboratories in Cape Town and Johannesburg, covering regions of South Africa with a high prevalence of tuberculosis. We used the tool ARIBA to measure the status of predefined genes that are associated with bedaquiline resistance. To produce a broad genetic landscape of M tuberculosis in South Africa, we extended our analysis to include all publicly available isolates from the European Nucleotide Archive, including isolates obtained by the CRyPTIC consortium, for which minimum inhibitory concentrations of bedaquiline were available. FINDINGS: Between Jan 10, 2019, and July, 22, 2020, we sequenced 505 M tuberculosis isolates from 461 patients. Of the 64 isolates with mutations within the mmpR5 regulatory gene, we found 53 (83%) had independent acquisition of 31 different mutations, with a particular enrichment of truncated MmpR5 in bedaquiline-resistant isolates resulting from either frameshift mutations or the introduction of an insertion element. Truncation occurred across three M tuberculosis lineages, and were present in 66% of bedaquiline-resistant isolates. Although the distributions overlapped, the median minimum inhibitory concentration of bedaquiline was 0·25 mg/L (IQR 0·12-0·25) in mmpR5-disrupted isolates, compared with 0·06 mg/L (0·03-0·06) in wild-type M tuberculosis. INTERPRETATION: Reduction in the susceptibility of M tuberculosis to bedaquiline has evolved repeatedly across the phylogeny. In our data, we see no evidence that this reduction has led to the spread of a successful strain in South Africa. Binary phenotyping based on the bedaquiline breakpoint might be inappropriate to monitor resistance to this drug. We recommend the use of minimum inhibitory concentrations in addition to MmpR5 truncation screening to identify moderate increases in resistance to bedaquiline. FUNDING: US Centers for Disease Control and Prevention.
Subject(s)
Antitubercular Agents , Bacterial Proteins , Diarylquinolines , Microbial Sensitivity Tests , Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Mycobacterium tuberculosis/genetics , Mycobacterium tuberculosis/drug effects , South Africa/epidemiology , Diarylquinolines/pharmacology , Humans , Antitubercular Agents/pharmacology , Tuberculosis, Multidrug-Resistant/microbiology , Tuberculosis, Multidrug-Resistant/genetics , Tuberculosis, Multidrug-Resistant/epidemiology , Bacterial Proteins/genetics , Whole Genome Sequencing , Mutation , Genomics , Drug Resistance, Bacterial/geneticsABSTRACT
BACKGROUND: Bacterial diversity could contribute to the diversity of tuberculosis infection and treatment outcomes observed clinically, but the biological basis of this association is poorly understood. The aim of this study was to identify associations between phenogenomic variation in Mycobacterium tuberculosis and tuberculosis clinical features. METHODS: We developed a high-throughput platform to define phenotype-genotype relationships in M tuberculosis clinical isolates, which we tested on a set of 158 drug-sensitive M tuberculosis strains sampled from a large tuberculosis clinical study in Ho Chi Minh City, Viet Nam. We tagged the strains with unique genetic barcodes in multiplicate, allowing us to pool the strains for in-vitro competitive fitness assays across 16 host-relevant antibiotic and metabolic conditions. Relative fitness was quantified by deep sequencing, enumerating output barcode read counts relative to input normalised values. We performed a genome-wide association study to identify phylogenetically linked and monogenic mutations associated with the in-vitro fitness phenotypes. These genetic determinants were further associated with relevant clinical outcomes (cavitary disease and treatment failure) by calculating odds ratios (ORs) with binomial logistic regressions. We also assessed the population-level transmission of strains associated with cavitary disease and treatment failure using terminal branch length analysis of the phylogenetic data. FINDINGS: M tuberculosis clinical strains had diverse growth characteristics in host-like metabolic and drug conditions. These fitness phenotypes were highly heritable, and we identified monogenic and phylogenetically linked variants associated with the fitness phenotypes. These data enabled us to define two genetic features that were associated with clinical outcomes. First, mutations in Rv1339, a phosphodiesterase, which were associated with slow growth in glycerol, were further associated with treatment failure (OR 5·34, 95% CI 1·21-23·58, p=0·027). Second, we identified a phenotypically distinct slow-growing subclade of lineage 1 strains (L1.1.1.1) that was associated with cavitary disease (OR 2·49, 1·11-5·59, p=0·027) and treatment failure (OR 4·76, 1·53-14·78, p=0·0069), and which had shorter terminal branch lengths on the phylogenetic tree, suggesting increased transmission. INTERPRETATION: Slow growth under various antibiotic and metabolic conditions served as in-vitro intermediate phenotypes underlying the association between M tuberculosis monogenic and phylogenetically linked mutations and outcomes such as cavitary disease, treatment failure, and transmission potential. These data suggest that M tuberculosis growth regulation is an adaptive advantage for bacterial success in human populations, at least in some circumstances. These data further suggest markers for the underlying bacterial processes that contribute to these clinical outcomes. FUNDING: National Health and Medical Research Council/A∗STAR, National Institutes of Allergy and Infectious Diseases, National Institute of Child Health and Human Development, and the Wellcome Trust Fellowship in Public Health and Tropical Medicine.
Subject(s)
Antitubercular Agents , Mycobacterium tuberculosis , Tuberculosis , Humans , Mycobacterium tuberculosis/genetics , Mycobacterium tuberculosis/drug effects , Tuberculosis/drug therapy , Tuberculosis/microbiology , Vietnam/epidemiology , Antitubercular Agents/therapeutic use , Antitubercular Agents/pharmacology , Genome-Wide Association Study , Treatment Outcome , Phenotype , Phylogeny , Mutation , Phenomics , Genotype , Female , Adult , MaleABSTRACT
Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.
ABSTRACT
Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.
ABSTRACT
Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in Mycobacterium tuberculosis (Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3-24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76-1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57-0.90 and 0.87-1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.
Subject(s)
Mycobacterium tuberculosis , Transcriptome , Mycobacterium tuberculosis/drug effects , Mycobacterium tuberculosis/genetics , Transcriptome/genetics , Gene Expression Regulation, Bacterial/drug effects , Microbial Sensitivity Tests , Anti-Bacterial Agents/pharmacology , Gene Expression Profiling/methods , Antitubercular Agents/pharmacology , HumansABSTRACT
BACKGROUND: Global tuberculosis (TB) drug resistance (DR) surveillance focuses on rifampicin. We examined the potential of public and surveillance Mycobacterium tuberculosis (Mtb) whole-genome sequencing (WGS) data, to generate expanded country-level resistance prevalence estimates (antibiograms) using in silico resistance prediction. METHODS: We curated and quality-controlled Mtb WGS data. We used a validated random forest model to predict phenotypic resistance to 12 drugs and bias-corrected for model performance, outbreak sampling and rifampicin resistance oversampling. Validation leveraged a national DR survey conducted in South Africa. RESULTS: Mtb isolates from 29 countries (n=19 149) met sequence quality criteria. Global marginal genotypic resistance among mono-resistant TB estimates overlapped with the South African DR survey, except for isoniazid, ethionamide and second-line injectables, which were underestimated (n=3134). Among multidrug resistant (MDR) TB (n=268), estimates overlapped for the fluoroquinolones but overestimated other drugs. Globally pooled mono-resistance to isoniazid was 10.9% (95% CI: 10.2-11.7%, n=14 012). Mono-levofloxacin resistance rates were highest in South Asia (Pakistan 3.4% (0.1-11%), n=111 and India 2.8% (0.08-9.4%), n=114). Given the recent interest in drugs enhancing ethionamide activity and their expected activity against isolates with resistance discordance between isoniazid and ethionamide, we measured this rate and found it to be high at 74.4% (IQR: 64.5-79.7%) of isoniazid-resistant isolates predicted to be ethionamide susceptible. The global susceptibility rate to pyrazinamide and levofloxacin among MDR was 15.1% (95% CI: 10.2-19.9%, n=3964). CONCLUSIONS: This is the first attempt at global Mtb antibiogram estimation. DR prevalence in Mtb can be reliably estimated using public WGS and phenotypic resistance prediction for key antibiotics, but public WGS data demonstrates oversampling of isolates with higher resistance levels than MDR. Nevertheless, our results raise concerns about the empiric use of short-course fluoroquinolone regimens for drug-susceptible TB in South Asia and indicate underutilisation of ethionamide in MDR treatment.
Subject(s)
Antitubercular Agents , Tuberculosis, Multidrug-Resistant , Humans , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Isoniazid/pharmacology , Isoniazid/therapeutic use , Ethionamide/therapeutic use , Rifampin/therapeutic use , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/epidemiology , Genomics , Microbial Sensitivity Tests , Machine LearningABSTRACT
BACKGROUND: Emerging resistance to bedaquiline (BDQ) threatens to undermine advances in the treatment of drug-resistant tuberculosis (DRTB). Characterizing serial Mycobacterium tuberculosis (Mtb) isolates collected during BDQ-based treatment can provide insights into the etiologies of BDQ resistance in this important group of DRTB patients. METHODS: We measured mycobacteria growth indicator tube (MGIT)-based BDQ minimum inhibitory concentrations (MICs) of Mtb isolates collected from 195 individuals with no prior BDQ exposure who were receiving BDQ-based treatment for DRTB. We conducted whole-genome sequencing on serial Mtb isolates from all participants who had any isolate with a BDQ MIC >1 collected before or after starting treatment (95 total Mtb isolates from 24 participants). RESULTS: Sixteen of 24 participants had BDQ-resistant TB (MGIT MIC ≥4â µg/mL) and 8 had BDQ-intermediate infections (MGIT MIC = 2 µg/mL). Participants with pre-existing resistance outnumbered those with resistance acquired during treatment, and 8 of 24 participants had polyclonal infections. BDQ resistance was observed across multiple Mtb strain types and involved a diverse catalog of mmpR5 (Rv0678) mutations, but no mutations in atpE or pepQ. Nine pairs of participants shared genetically similar isolates separated by <5 single nucleotide polymorphisms, concerning for potential transmitted BDQ resistance. CONCLUSIONS: BDQ-resistant TB can arise via multiple, overlapping processes, including transmission of strains with pre-existing resistance. Capturing the within-host diversity of these infections could potentially improve clinical diagnosis, population-level surveillance, and molecular diagnostic test development.
Subject(s)
Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Tuberculosis , Humans , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Diarylquinolines/pharmacology , Diarylquinolines/therapeutic use , Tuberculosis/drug therapy , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/microbiology , Genotype , Phenotype , Microbial Sensitivity TestsABSTRACT
Pathogenic microorganisms are in a perpetual struggle for survival in changing host environments, where host pressures necessitate changes in pathogen virulence, antibiotic resistance, or transmissibility. The genetic basis of phenotypic adaptation by pathogens is difficult to study in vivo. In this work, we develop a phylogenetic method to detect genetic dependencies that promote pathogen adaptation using 31,428 in vivo sampled Mycobacterium tuberculosis genomes, a globally prevalent bacterial pathogen with increasing levels of antibiotic resistance. We find that dependencies between mutations are enriched in antigenic and antibiotic resistance functions and discover 23 mutations that potentiate the development of antibiotic resistance. Between 11% and 92% of resistant strains harbor a dependent mutation acquired after a resistance-conferring variant. We demonstrate the pervasiveness of genetic dependency in adaptation of naturally evolving populations and the utility of the proposed computational approach.
Subject(s)
Mycobacterium tuberculosis , Mycobacterium tuberculosis/genetics , Antitubercular Agents/therapeutic use , Phylogeny , Mutation , Virulence , Microbial Sensitivity TestsABSTRACT
Background: Combatting the tuberculosis (TB) epidemic caused by Mycobacterium tuberculosis ( Mtb ) necessitates a better understanding of the factors contributing to patient clinical outcomes and transmission. While host and environmental factors have been evaluated, the impact of Mtb genetic background and phenotypic diversity is underexplored. Previous work has made associations between Mtb genetic lineages and some clinical and epidemiological features, but the bacterial traits underlying these connections are largely unknown. Methods: We developed a high-throughput functional genomics platform for defining genotype-phenotype relationships across a panel of Mtb clinical isolates. These phenotypic fitness profiles function as intermediate traits which can be linked to Mtb genetic variants and associated with clinical and epidemiological outcomes. We applied this approach to a collection of 158 Mtb strains from a study of Mtb transmission in Ho Chi Minh City, Vietnam. Mtb strains were genetically tagged in multiplicate, which allowed us to pool the strains and assess in vitro competitive fitness using deep sequencing across a set of 14 host-relevant antibiotic and metabolic conditions. Phylogenetic and monogenic associations with these intermediate traits were identified and then associated with clinical outcomes. Findings: Mtb clinical strains have a broad range of growth and drug response dynamics that can be clustered by their phylogenetic relationships. We identified novel monogenic associations with Mtb fitness in various metabolic and antibiotic conditions. Among these, we find that mutations in Rv1339 , a phosphodiesterase, which were identified through their association with slow growth in glycerol, are further associated with treatment failure. We also identify a previously uncharacterized subclade of Lineage 1 strains (L1.1.1.1) that is phenotypically distinguished by slow growth under most antibiotic and metabolic stress conditions in vitro . This clade is associated with cavitary disease, treatment failure, and demonstrates increased transmission potential. Interpretation: High-throughput phenogenotyping of Mtb clinical strains enabled bacterial intermediate trait identification that can provide a mechanistic link between Mtb genetic variation and patient clinical outcomes. Mtb strains associated with cavitary disease, treatment failure, and transmission potential display intermediate phenotypes distinguished by slow growth under various antibiotic and metabolic conditions. These data suggest that Mtb growth regulation is an adaptive advantage for host bacterial success in human populations, in at least some circumstances. These data further suggest markers for the underlying bacterial processes that govern these clinical outcomes. Funding: National Institutes of Allergy and Infectious Diseases: P01 AI132130 (SS, SMF); P01 AI143575 (XW, SMF); U19 AI142793 (QL, SMF); 5T32AI132120-03 (SS); 5T32AI132120-04 (SS); 5T32AI049928-17 (SS) Wellcome Trust Fellowship in Public Health and Tropical Medicine: 097124/Z/11/Z (NTTT) National Health and Medical Research Council (NHMRC)/A*STAR joint call: APP1056689 (SJD) The funding sources had no involvement in study methodology, data collection, analysis, and interpretation nor in the writing or submission of the manuscript. Research in context: Evidence before this study: We used different combinations of the words mycobacterium tuberculosis, tuberculosis, clinical strains, intermediate phenotypes, genetic barcoding, phenogenomics, cavitary disease, treatment failure, and transmission to search the PubMed database for all studies published up until January 20 th , 2022. We only considered English language publications, which biases our search. Previous work linking Mtb determinants to clinical or epidemiological data has made associations between bacterial lineage, or less frequently, genetic polymorphisms to in vitro or in vivo models of pathogenesis, transmission, and clinical outcomes such as cavitary disease, treatment failure, delayed culture conversion, and severity. Many of these studies focus on the global pandemic Lineage 2 and Lineage 4 Mtb strains due in part to a deletion in a polyketide synthase implicated in host-pathogen interactions. There are a number of Mtb GWAS studies that have led to novel genetic determinants of in vitro drug resistance and tolerance. Previous Mtb GWAS analyses with clinical outcomes did not experimentally test any predicted phenotypes of the clinical strains. Published laboratory-based studies of Mtb clinical strains involve relatively small numbers of strains, do not identify the genetic basis of relevant phenotypes, or link findings to the corresponding clinical outcomes. There are two recent studies of other pathogens that describe phenogenomic analyses. One study of 331 M. abscessus clinical strains performed one-by-one phenotyping to identify bacterial features associated with clearance of infection and another details a competition experiment utilizing three barcoded Plasmodium falciparum clinical isolates to assay antimalarial fitness and resistance. Added value of this study: We developed a functional genomics platform to perform high-throughput phenotyping of Mtb clinical strains. We then used these phenotypes as intermediate traits to identify novel bacterial genetic features associated with clinical outcomes. We leveraged this platform with a sample of 158 Mtb clinical strains from a cross sectional study of Mtb transmission in Ho Chi Minh City, Vietnam. To enable high-throughput phenotyping of large numbers of Mtb clinical isolates, we applied a DNA barcoding approach that has not been previously utilized for the high-throughput analysis of Mtb clinical strains. This approach allowed us to perform pooled competitive fitness assays, tracking strain fitness using deep sequencing. We measured the replicative fitness of the clinical strains in multiplicate under 14 metabolic and antibiotic stress condition. To our knowledge, this is the largest phenotypic screen of Mtb clinical isolates to date. We performed bacterial GWAS to delineate the Mtb genetic variants associated with each fitness phenotype, identifying monogenic associations with several conditions. We then defined Mtb phenotypic and genetic features associated with clinical outcomes. We find that a subclade of Mtb strains, defined by variants largely involved in fatty acid metabolic pathways, share a universal slow growth phenotype that is associated with cavitary disease, treatment failure and increased transmission potential in Vietnam. We also find that mutations in Rv1339 , a poorly characterized phosphodiesterase, also associate with slow growth in vitro and with treatment failure in patients. Implications of all the available evidence: Phenogenomic profiling demonstrates that Mtb strains exhibit distinct growth characteristics under metabolic and antibiotic stress conditions. These fitness profiles can serve as intermediate traits for GWAS and association with clinical outcomes. Intermediate phenotyping allows us to examine potential processes by which bacterial strain differences contribute to clinical outcomes. Our study identifies clinical strains with slow growth phenotypes under in vitro models of antibiotic and host-like metabolic conditions that are associated with adverse clinical outcomes. It is possible that the bacterial intermediate phenotypes we identified are directly related to the mechanisms of these outcomes, or they may serve as markers for the causal yet unidentified bacterial determinants. Via the intermediate phenotyping, we also discovered a surprising diversity in Mtb responses to the new anti-mycobacterial drugs that target central metabolic processes, which will be important in considering roll-out of these new agents. Our study and others that have identified Mtb determinants of TB clinical and epidemiological phenotypes should inform efforts to improve diagnostics and drug regimen design.
ABSTRACT
Digital health technologies can help tackle challenges in global public health. Digital and AI-for-Health Challenges, controlled events whose goal is to generate solutions to a given problem in a defined period of time, are one way of catalysing innovation. This article proposes an expanded investment framework for Global Health AI and digitalhealth Innovation that goes beyond traditional factors such as return on investment. Instead, we propose non monetary and non GDP metrics, such as Disability Adjusted Life Years or achievement of universal health coverage. Furthermore, we suggest a venture building approach around global health, which includes filtering of participants to reduce opportunity cost, close integration of implementation scientists and an incubator for the long-term development of ideas resulting from the challenge. Finally, we emphasize the need to strengthen human capital across a range of areas in local innovation, implementation-science, and in health services.
ABSTRACT
Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-based methods being considered the gold standard for drug susceptibility testing, molecular methods provide rapid information about the Mycobacterium tuberculosis mutations associated with resistance to anti-tuberculosis drugs. This consensus document was developed on the basis of a comprehensive literature search, by the TBnet and RESIST-TB networks, about reporting standards for the clinical use of molecular drug susceptibility testing. Review and the search for evidence included hand-searching journals and searching electronic databases. The panel identified studies that linked mutations in genomic regions of M tuberculosis with treatment outcome data. Implementation of molecular testing for the prediction of drug resistance in M tuberculosis is key. Detection of mutations in clinical isolates has implications for the clinical management of patients with multidrug-resistant or rifampicin-resistant tuberculosis, especially in situations when phenotypic drug susceptibility testing is not available. A multidisciplinary team including clinicians, microbiologists, and laboratory scientists reached a consensus on key questions relevant to molecular prediction of drug susceptibility or resistance to M tuberculosis, and their implications for clinical practice. This consensus document should help clinicians in the management of patients with tuberculosis, providing guidance for the design of treatment regimens and optimising outcomes.
Subject(s)
Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Tuberculosis , Humans , Mycobacterium tuberculosis/genetics , Microbial Sensitivity Tests , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Tuberculosis, Multidrug-Resistant/diagnosis , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/microbiology , Tuberculosis/drug therapy , MutationABSTRACT
High throughput sequencing (HTS) can identify the presence of Mycobacterium tuberculosis DNA in a clinical sample while also providing information on drug susceptibility. Multiple studies have provided a context for exploring the clinical application of HTS for TB diagnosis. The workflow challenges, strengths and limitations of the various sequencing platforms, and tools used for analysis are presented to provide a framework for further innovations in the field.
ABSTRACT
Rationale: India is experiencing a regional increase in cases of multidrug-resistant tuberculosis (MDR-TB). Objectives: Given the complexity of MDR-TB diagnosis and care, we sought to address key knowledge gaps in MDR risk factors, care delays, and drivers of delay to help guide disease control. Methods: From January 2018 to September 2019, we conducted interviews with adults registered with the National TB Elimination Program for MDR (n = 128) and non-MDR-TB (n = 269) treatment to quantitatively and qualitatively study care pathways. We collected treatment records and GeneXpert-TB/RIF diagnostic reports. Measurements and Main Results: MDR-TB was associated with young age and crowded residence. GeneXpert rifampicin resistance diversity was measured at 72.5% Probe E. Median time from symptom onset to diagnosis of MDR was 90 days versus 60 days for non-MDR, Wilcoxon P < 0.01. Delay decreased by a median of 30 days among non-MDR patients with wider access to GeneXpert, Wilcoxon P = 0.02. Pathways to care were complex, with a median (interquartile range) of 4 (3-5) and 3 (2-4) encounters for MDR and non-MDR, respectively. Of patients with MDR-TB, 68% had their first encounter in the private sector, and this was associated with a larger number of subsequent healthcare encounters and catastrophic expenditure. Conclusions: The association of MDR with young age, crowding, and low genotypic diversity raises concerns of ongoing MDR transmission fueled by long delays in care. Delays are decreasing with GeneXpert use, suggesting the need for routine use in presumptive TB. Qualitatively, we identify the need to improve patient retention in the National TB Elimination Program and highlight patients' trust relationship with private providers.
Subject(s)
Antibiotics, Antitubercular/therapeutic use , Mycobacterium tuberculosis/drug effects , Rifampin/therapeutic use , Time-to-Treatment/statistics & numerical data , Tuberculosis, Multidrug-Resistant/diagnosis , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/transmission , Adolescent , Adult , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Humans , India/epidemiology , Male , Middle Aged , Risk Factors , Tuberculosis, Multidrug-Resistant/epidemiology , Young AdultABSTRACT
BACKGROUND: Clostridioides difficile infection (CDI) may be rising in severity in the US over the past decade and its treatment landscape is changing given the recent adoption of fecal microbiota transplantation (FMT) METHODS: We built a retrospective observational cohort using a database of a national care-plan containing medical claims of over 50 million individuals between 2008 and 2019. We used International Classification of Disease (ICD) and prescription data to identify patients with CDI. We estimated trends in disease burden and FMT use, and evaluated complications post FMT using a phenome-wide association approach. RESULTS: We identified 38,396 patients with CDI; the median age was 60 years (IQR 45-74) and 60% were female (n = 23,374). The rate of CDI increased from 33.4 to 69.46 cases per 100,000 person-years between 2008 and 2015, and stabilized from 2015 to 2019 (increase of 4.77 cases per 100,000 person-years per year, 95% CI 3.55-5.98 prior to 2015 vs. 2.01 95% CI - 10.16 to 14.18 after 2015). Of the 7715 patients with recurrent CDI, 407 patients (5%) underwent FMT. Gastrointestinal complications were increased within 1 month post FMT (OR 99.60, p < 0.001). Sepsis was identified in two individuals (0.49% 95% CI 0.05-1.7%) within the first month post FMT. The risk of CDI recurrence significantly decreased post FMT compared with anti-CDI antibiotics in the multivariable model (raw-recurrence rate 9.8% vs 36%, aOR = 0.21, 95% CI 0.12-0.53, p < 0.001). CONCLUSION: We show that FMT is strongly associated with a decrease in CDI recurrence compared with the usual care with generally mild complications for up to 2 years.
Subject(s)
Clostridioides difficile , Clostridium Infections , Clostridium Infections/epidemiology , Clostridium Infections/etiology , Clostridium Infections/therapy , Fecal Microbiota Transplantation/adverse effects , Female , Humans , Insurance, Health , Middle Aged , Recurrence , Retrospective Studies , Treatment Outcome , United States/epidemiologyABSTRACT
Antibiotic resistance among bacterial pathogens poses a major global health threat. Mycobacterium tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the low growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e., systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with an LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).
Subject(s)
Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Amikacin/pharmacology , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Clofazimine/pharmacology , Diarylquinolines , Drug Resistance, Multiple, Bacterial/genetics , Epistasis, Genetic , Humans , Kanamycin/pharmacology , Microbial Sensitivity Tests , Mutation , Mycobacterium tuberculosis/genetics , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/geneticsABSTRACT
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens. RESULTS: We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB's predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6-78.5%) and 75.4% (95% CI 74.5-76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4-75.3%) and Mykrobe at 71.9% (95% CI 70.9-72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5-97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants CONCLUSIONS: GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu , and the source code is available at https://github.com/farhat-lab/gentb-site .
Subject(s)
Computational Biology/methods , Drug Resistance, Bacterial , Machine Learning , Software , Tuberculosis, Multidrug-Resistant/diagnosis , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Databases, Genetic , Genome, Bacterial , Genomics/methods , Humans , Microbial Sensitivity Tests , ROC Curve , Reproducibility of Results , Web Browser , WorkflowABSTRACT
Importance: The familial aspect of acute appendicitis (AA) has been proposed, but its hereditary basis remains undetermined. Objective: To identify genomic variants associated with AA. Design, Setting, and Participants: This genome-wide association study, conducted from June 21, 2019, to February 4, 2020, used a multi-institutional biobank to retrospectively identify patients with AA across 8 single-nucleotide variation (SNV) genotyping batches. The study also examined differential gene expression in appendiceal tissue samples between patients with AA and controls using the GSE9579 data set in the National Institutes of Health's Gene Expression Omnibus repository. Statistical analysis was conducted from October 1, 2019, to February 4, 2020. Main Outcomes and Measures: Single-nucleotide variations with a minor allele frequency of 5% or higher were tested for association with AA using a linear mixed model. The significance threshold was set at P = 5 × 10-8. Results: A total of 29â¯706 patients (15â¯088 women [50.8%]; mean [SD] age at enrollment, 60.1 [17.0] years) were included, 1743 of whom had a history of AA. The genomic inflation factor for the cohort was 1.003. A previously unknown SNV at chromosome 18q was found to be associated with AA (rs9953918: odds ratio, 0.99; 95% CI, 0.98-1.00; P = 4.48 × 10-8). This SNV is located in an intron of the NEDD4L gene. The heritability of appendicitis was estimated at 30.1%. Gene expression data from appendiceal tissue donors identified NEDD4L to be among the most differentially expressed genes (14 of 22â¯216 genes; ß [SE] = -2.71 [0.44]; log fold change = -1.69; adjusted P = .04). Conclusions and Relevance: This study identified SNVs within the NEDD4L gene as being associated with AA. Nedd4l is involved in the ubiquitination of intestinal ion channels and decreased Nedd4l activity may be implicated in the pathogenesis of AA. These findings can improve the understanding of the genetic predisposition to and pathogenesis of AA.