scholarly journals Estimation of country-specific tuberculosis antibiograms using genomic data

2021 ◽  
Author(s):  
Avika Dixit ◽  
Luca Freschi ◽  
Roger Vargas ◽  
Matthias I Groeschel ◽  
Sabira Tahseen ◽  
...  
Keyword(s):  
South Asia ◽  
Model Performance ◽  
Quality Criteria ◽  
Genotypic Resistance ◽  
Phenotypic Resistance ◽  
Country Level ◽  
Mdr Tb ◽  
Resistance Prediction ◽  
Resistance Rates ◽  
Sequence Quality

Background: Global tuberculosis (TB) drug resistance (DR) surveillance is largely focused on the drug rifampicin. We leveraged public and surveillance M. tuberculosis (Mtb) whole genome sequencing (WGS) data, to generate more comprehensive 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 twelve drugs and bias-corrected for model performance, outbreak sampling, and resistance oversampling. We validated our estimates using a national DR survey conducted in South Africa. Results: Mtb isolates from 29 countries (n=19,149) met sequence quality criteria. Marginal genotypic resistance estimates overlapped with the South African DR survey for all drugs except isoniazid and second-line injectables that were underestimated (n=3,134); among multi-drug resistant (MDR) TB, estimates overlapped for pyrazinamide and the fluoroquinolones. Globally, mono-resistance to isoniazid was estimated at 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). Rates of resistance discordance between isoniazid and ethionamide were high with 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=3,964). 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. Our results raise concerns about the empiric use of short-course fluoroquinolone regimens for drug susceptible TB in South Asia and suggest that ethionamide is an under-utilized drug in MDR treatment.

scholarly journals Molecular Evaluation of Fluoroquinolone Resistance in Serial Mycobacterium tuberculosis Isolates from Individuals Diagnosed with Multidrug-Resistant Tuberculosis

2020 ◽  
Vol 65 (1) ◽  
pp. e01663-20
Author(s):  
Melisa Willby ◽  
Paige Chopra ◽  
Darrin Lemmer ◽  
Katherine Klein ◽  
Tracy L. Dalton ◽  
...  
Keyword(s):  
Treatment Success ◽  
Multidrug Resistant ◽  
Fluoroquinolone Resistance ◽  
Personal Genome ◽  
Genotypic Resistance ◽  
Phenotypic Resistance ◽  
Tb Treatment ◽  
Resistant Tuberculosis ◽  
Multidrug Resistant Tuberculosis ◽  
Mdr Tb

ABSTRACTFluoroquinolones (FQ) are crucial components of multidrug-resistant tuberculosis (MDR TB) treatment. Differing levels of resistance are associated with specific mutations within the quinolone-resistance-determining region (QRDR) of gyrA. We sequenced the QRDR from serial isolates of MDR TB patients in the Preserving Effective TB Treatment Study (PETTS) with baseline FQ resistance (FQR) or acquired FQ resistance (FQACQR) using an Ion Torrent Personal Genome Machine (PGM) to a depth of 10,000× and reported single nucleotide polymorphisms in ≥1% of reads. FQR isolates harbored 15 distinct alleles with 1.3 (maximum = 6) on average per isolate. Eighteen alleles were identified in FQACQR isolates with an average of 1.6 (maximum = 9) per isolate. Isolates from 78% of FQACQR individuals had mutant alleles identified within 6 months of treatment initiation. Asp94Gly was the predominant allele in the initial FQ-resistant isolates followed by Ala90Val. Seventy-seven percent (36/47) of FQACQR group patients had isolates with FQ resistance alleles prior to changes to the FQ component of their treatment. Unlike the individuals treated initially with other FQs, none of the 21 individuals treated initially with levofloxacin developed genotypic or phenotypic FQ resistance, although country of residence was likely a contributing factor since 69% of these individuals were from a single country. Initial detection of phenotypic resistance and genotypic resistance occurred simultaneously for most; however, phenotypic resistance occurred earlier in isolates harboring mixtures of alleles of very low abundance (<1% of reads), whereas genotypic resistance often occurred earlier for alleles associated with low-level resistance. Understanding factors influencing acquisition and evolution of FQ resistance could reveal strategies for improved treatment success.

scholarly journals Deep Learning for Monitoring Agricultural Drought in South Asia Using Remote Sensing Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1715
Author(s):  
Foyez Ahmed Prodhan ◽  
Jiahua Zhang ◽  
Fengmei Yao ◽  
Lamei Shi ◽  
Til Prasad Pangali Sharma ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
South Asia ◽  
Model Performance ◽  
Remote Sensing Data ◽  
Agricultural Drought ◽  
Gradient Boosting ◽  
Complex Nature ◽  
Sensing Data

Drought, a climate-related disaster impacting a variety of sectors, poses challenges for millions of people in South Asia. Accurate and complete drought information with a proper monitoring system is very important in revealing the complex nature of drought and its associated factors. In this regard, deep learning is a very promising approach for delineating the non-linear characteristics of drought factors. Therefore, this study aims to monitor drought by employing a deep learning approach with remote sensing data over South Asia from 2001–2016. We considered the precipitation, vegetation, and soil factors for the deep forwarded neural network (DFNN) as model input parameters. The study evaluated agricultural drought using the soil moisture deficit index (SMDI) as a response variable during three crop phenology stages. For a better comparison of deep learning model performance, we adopted two machine learning models, distributed random forest (DRF) and gradient boosting machine (GBM). Results show that the DFNN model outperformed the other two models for SMDI prediction. Furthermore, the results indicated that DFNN captured the drought pattern with high spatial variability across three penology stages. Additionally, the DFNN model showed good stability with its cross-validated data in the training phase, and the estimated SMDI had high correlation coefficient R2 ranges from 0.57~0.90, 0.52~0.94, and 0.49~0.82 during the start of the season (SOS), length of the season (LOS), and end of the season (EOS) respectively. The comparison between inter-annual variability of estimated SMDI and in-situ SPEI (standardized precipitation evapotranspiration index) showed that the estimated SMDI was almost similar to in-situ SPEI. The DFNN model provides comprehensive drought information by producing a consistent spatial distribution of SMDI which establishes the applicability of the DFNN model for drought monitoring.

scholarly journals Assessment of SARS-CoV-2 genome sequencing: quality criteria and low frequency variants

2021 ◽  
Author(s):  
Damien Jacot ◽  
Trestan Pillonel ◽  
Gilbert Greub ◽  
Claire Bertelli
Keyword(s):  
Sample Selection ◽  
Low Frequency ◽  
Pcr Amplification ◽  
Quality Criterion ◽  
Quality Criteria ◽  
Sequencing Errors ◽  
Sequencing Quality ◽  
Quality Control Criteria ◽  
Control Criteria ◽  
Sequence Quality

Although many laboratories worldwide have developed their sequencing capacities in response to the need for SARS-CoV-2 genome-based surveillance of variants, only few reported some quality criteria to ensure sequence quality before lineage assignment and submission to public databases. Hence, we aimed here to provide simple quality control criteria for SARS-CoV-2 sequencing to prevent erroneous interpretation of low quality or contaminated data. We retrospectively investigated 647 SARS-CoV-2 genomes obtained over ten tiled amplicons sequencing runs. We extracted 26 potentially relevant metrics covering the entire workflow from sample selection to bioinformatics analysis. Based on data distribution, critical values were established for eleven selected metrics to prompt further quality investigations for problematic samples, in particular those with a low viral RNA quantity. Low frequency variants (<70% of supporting reads) can result from PCR amplification errors, sample cross contaminations or presence of distinct SARS-CoV2 genomes in the sample sequenced. The number and the prevalence of low frequency variants can be used as a robust quality criterion to identify possible sequencing errors or contaminations. Overall, we propose eleven metrics with fixed cutoff values as a simple tool to evaluate the quality of SARS-CoV-2 genomes, among which cycle thresholds, mean depth, proportion of genome covered at least 10x and the number of low frequency variants combined with mutation prevalence data.

scholarly journals Understanding the social determinants of TB and HIV in South Asia

2014 ◽  
Author(s):  
Bishwajit Ghose ◽  
Cheng Zhaohui ◽  
He Zhifei
Keyword(s):  
South Asia ◽  
Healthcare System ◽  
Social Determinants ◽  
Social Life ◽  
Public Health Problem ◽  
Asian Population ◽  
Major Public Health Problem ◽  
South Asian Population ◽  
Wide Range ◽  
Mdr Tb

South Asian population suffer a particularly wide range of infectious diseases among which TB and HIV appear to produce most profound influence across various dimensions of social life, healthcare and the economy. Although the countries in this region have a relatively lower prevalence of HIV/AIDS compared to other developing regions until now, the future looks rather bleak in terms of preparedness for emerging healthcare realities. Tuberculosis on the other hand, has always been a major public health problem plaguing the healthcare system and the economy for decades. Moreover, the emergence of the drug resistant (MDR-TB & XDR-TB) strains are making the existing intervention and prevention strategies less effective and posing ever-growing threats to the underdeveloped healthcare infrastructure. Understanding the underlying social-determinants of these diseases can prove crucial to design more comprehensive intervention approaches. This article aims to clarify why the healthcare system in South Asia needs to adopt a social-determinants-of-health (SDOH) approach as a long-term strategy for more efficient prevention and control of TB and HIV infection.

scholarly journals Genotypic Resistance inHelicobacter pyloriStrains Correlates with Susceptibility Test and Treatment Outcomes after Levofloxacin- and Clarithromycin-Based Therapies

2010 ◽  
Vol 55 (3) ◽  
pp. 1123-1129 ◽  
Author(s):  
Jyh-Ming Liou ◽  
Chi-Yang Chang ◽  
Wang-Huei Sheng ◽  
Yu-Chi Wang ◽  
Mei-Jyh Chen ◽  
...  
Keyword(s):  
Treatment Outcomes ◽  
Triple Therapy ◽  
Direct Sequencing ◽  
Point Mutations ◽  
Kappa Coefficient ◽  
23S Rrna ◽  
Genotypic Resistance ◽  
Phenotypic Resistance ◽  
Therapeutic Outcomes ◽  
H Pylori

ABSTRACTThe accuracy of genotypic resistance to levofloxacin (gyrAmutations) and its agreement with treatment outcomes after levofloxacin-based therapy have not been reported. We aimed to assess the correlation.Helicobacter pyloristrains isolated from patients who received levofloxacin-based and clarithromycin-based triple therapies in a previous randomized trial were analyzed for point mutations ingyrAand 23S rRNA. PCR followed by direct sequencing was used to assess thegyrAand 23S rRNA mutations. An agar dilution test was used to determine the MICs of clarithromycin and levofloxacin. We found that the agreement between genotypic and phenotypic resistance to levofloxacin was best when the MIC breakpoint was >1 μg/ml (kappa coefficient, 0.754). The eradication rates in patients with and withoutgyrAmutations were 41.7% and 82.7%, respectively (P= 0.003). The agreement between genotypic and phenotypic resistance to clarithromycin was best when the MIC breakpoint was >2 μg/ml (kappa, 0.694). The eradication rates in patients with and without 23S rRNA mutations were 7.7% and 93.5%, respectively (P< 0.001). The agreements (kappa coefficient) between therapeutic outcomes after clarithromycin-based triple therapy and genotypic and phenotypic resistance were 0.671 and 0.356, respectively. The agreements (kappa coefficient) between therapeutic outcomes after levofloxacin-based triple therapy and genotypic and phenotypic resistance were 0.244 and 0.190, respectively. In conclusion,gyrAand 23S rRNA mutations inH. pyloristrains appeared to be better markers than phenotypic resistance in the prediction of treatment outcomes. The optimal breakpoints for levofloxacin and clarithromycin resistance appeared to be >1 μg/ml and >2 μg/ml, respectively.

scholarly journals Predictive Genotypic Algorithm for Virologic Response to Lopinavir-Ritonavir in Protease Inhibitor-Experienced Patients

2007 ◽  
Vol 51 (9) ◽  
pp. 3067-3074 ◽  
Author(s):  
Martin S. King ◽  
Richard Rode ◽  
Isabelle Cohen-Codar ◽  
Vincent Calvez ◽  
Anne-Geneviève Marcelin ◽  
...  
Keyword(s):  
Protease Inhibitor ◽  
Optimal Algorithm ◽  
Virologic Response ◽  
Hiv Protease ◽  
Genotypic Resistance ◽  
Phenotypic Resistance ◽  
Response Data ◽  
Mutation Score ◽  
Antiviral Activities ◽  
Multivariable Analyses

ABSTRACT Several genotypic resistance algorithms have been proposed for quantitation of the degree of phenotypic resistance to the human immunodeficiency virus (HIV) protease inhibitor (PI) lopinavir (LPV), including the original LPV mutation score. In this study, we retrospectively evaluated 21 codons in HIV protease known to be associated with PI resistance in a large antiretroviral agent-experienced observational patient cohort, “Autorisation Temporaire d'Utilization” (ATU), to assess whether a more optimal algorithm could be derived by using virologic response data from patients treated with LPV in combination with ritonavir (LPV/r). Five of the 11 mutations constituting the LPV mutation score were not associated with a virologic response, while 4 additional mutations not included in this score demonstrated an association. Therefore, the LPV ATU score, which includes mutations at codons 10, 20, 24, 33, 36, 47, 48, 54, 82, and 84, was constructed and shown in two different types of multivariable analyses of the ATU cohort to be a better predictor of the virologic response than the LPV mutation score. The LPV ATU score was also more strongly associated with a virologic response when it was applied to independent clinical trial populations of PI-experienced patients receiving LPV/r. This study provides the basis for a new genotypic resistance algorithm that is useful for predicting the antiviral activities of LPV/r-based regimens in PI-experienced patients. The refined algorithm may be useful in making clinical treatment decisions and in refining genetic and pharmacologic methods for assessing the activity of LPV/r.

scholarly journals TO PIN POINT THE FLAWS IN TUBERCULOSIS TREATMENT THAT LEADS TO MDR-TB IN NISHTAR HOSPITAL MULTAN; PAKISTAN

2015 ◽  
Vol 7 ◽  
pp. 49
Author(s):  
Mohsin Ali Sindhu ◽  
Keyword(s):  
Developing Countries ◽  
South Asia ◽  
Patient Compliance ◽  
Statistical Data ◽  
Tuberculosis Treatment ◽  
Directly Observed Therapy ◽  
Mdr Tb ◽  
Poor Management

Tuberculosis is one of the major problems in developing countries. Can be treated but due to poor management of MDR-TB and multi-emerging now days. Nishtar Hospital Multan is one of the largest hospitals in South Asia. The purpose of this study was to point out the flaws in the case of treatment of tuberculosis, directly observed therapy and patient compliance, and tuberculosis. The study was conducted by researchers who have been associated with doctors and participants in the search, and when he visited the behavior in the hospital. And summarizes the data through the use of statistical data.

Sign in / Sign up

Export Citation Format

Share Document