High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain.

BACKGROUND: Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened. METHODS AND FINDINGS: We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02-1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region. CONCLUSIONS: In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.

Vitamin D status and risk of incident tuberculosis disease: A nested case-control study, systematic review, and individual-participant data meta-analysis.

BACKGROUND: Few studies have evaluated the association between preexisting vitamin D deficiency and incident tuberculosis (TB). We assessed the impact of baseline vitamins D levels on TB disease risk. METHODS AND FINDINGS: We assessed the association between baseline vitamin D and incident TB in a prospective cohort of 6,751 HIV-negative household contacts of TB patients enrolled between September 1, 2009, and August 29, 2012, in Lima, Peru. We screened for TB disease at 2, 6, and 12 months after enrollment. We defined cases as household contacts who developed TB disease at least 15 days after enrollment of the index patient. For each case, we randomly selected four controls from among contacts who did not develop TB disease, matching on gender and year of age. We also conducted a one-stage individual-participant data (IPD) meta-analysis searching PubMed and Embase to identify prospective studies of vitamin D and TB disease until June 8, 2019. We included studies that assessed vitamin D before TB diagnosis. In the primary analysis, we defined vitamin D deficiency as 25-(OH)D < 50 nmol/L, insufficiency as 50-75 nmol/L, and sufficiency as >75nmol/L. We estimated the association between baseline vitamin D status and incident TB using conditional logistic regression in the Lima cohort and generalized linear mixed models in the meta-analysis. We further defined severe vitamin D deficiency as 25-(OH)D < 25 nmol/L and performed stratified analyses by HIV status in the IPD meta-analysis. In the Lima cohort, we analyzed 180 cases and 709 matched controls. The adjusted odds ratio (aOR) for TB risk among participants with baseline vitamin D deficiency compared to sufficient vitamin D was 1.63 (95% CI 0.75-3.52; p = 0.22). We included seven published studies in the meta-analysis and analyzed 3,544 participants. In the pooled analysis, the aOR was 1.48 (95% CI 1.04-2.10; p = 0.03). The aOR for severe vitamin D deficiency was 2.05 (95% CI 0.87-4.87; p trend for decreasing 25-(OH)D levels from sufficient vitamin D to severe deficiency = 0.02). Among 1,576 HIV-positive patients, vitamin D deficiency conferred a 2-fold (aOR 2.18, 95% CI 1.22-3.90; p = 0.01) increased risk of TB, and the aOR for severe vitamin D deficiency compared to sufficient vitamin D was 4.28 (95% CI 0.85-21.45; p = 0.08). Our Lima cohort study is limited by the short duration of follow-up, and the IPD meta-analysis is limited by the number of possible confounding covariates available across all studies. CONCLUSION: Our findings suggest vitamin D predicts TB disease risk in a dose-dependent manner and that the risk of TB disease is highest among HIV-positive individuals with severe vitamin D deficiency. Randomized control trials are needed to evaluate the possible role of vitamin D supplementation on reducing TB disease risk.

Role of the first WHO mutation catalogue in the diagnosis of antibiotic resistance in Mycobacterium tuberculosis in the Valencia Region, Spain: a retrospective genomic analysis.

BACKGROUND: In June, 2021, WHO published the most complete catalogue to date of resistance-conferring mutations in Mycobacterium tuberculosis. Here, we aimed to assess the performance of genome-based antimicrobial resistance prediction using the catalogue and its potential for improving diagnostics in a real low-burden setting. METHODS: In this retrospective population-based genomic study M tuberculosis isolates were collected from 25 clinical laboratories in the low-burden setting of the Valencia Region, Spain. Culture-positive tuberculosis cases reported by regional public health authorities between Jan 1, 2014, and Dec 31, 2016, were included. The drug resistance profiles of these isolates were predicted by the genomic identification, via whole-genome sequencing (WGS), of the high-confidence resistance-causing variants included in the catalogue and compared with the phenotype. We determined the minimum inhibitory concentration (MIC) of the isolates with discordant resistance profiles using the resazurin microtitre assay. FINDINGS: WGS was performed on 785 M tuberculosis complex culture-positive isolates, and the WGS resistance prediction sensitivities were: 85·4% (95% CI 70·8-94·4) for isoniazid, 73·3% (44·9-92·2) for rifampicin, 50·0% (21·1-78·9) for ethambutol, and 57·1% (34·0-78·2) for pyrazinamide; all specificities were more than 99·6%. Sensitivity values were lower than previously reported, but the overall pan-susceptibility accuracy was 96·4%. Genotypic analysis revealed that four phenotypically susceptible isolates carried mutations (rpoB Leu430Pro and rpoB Ile491Phe for rifampicin and fabG1 Leu203Leu for isoniazid) known to give borderline resistance in standard phenotypic tests. Additionally, we identified three putative resistance-associated mutations (inhA Ser94Ala, katG Leu48Pro, and katG Gly273Arg for isoniazid) in samples with substantially higher MICs than those of susceptible isolates. Combining both genomic and phenotypic data, in accordance with the WHO diagnostic guidelines, we could detect two new multidrug-resistant cases. Additionally, we detected 11 (1·6%) of 706 isolates to be monoresistant to fluoroquinolone, which had been previously undetected. INTERPRETATION: We showed that the WHO catalogue enables the detection of resistant cases missed in phenotypic testing in a low-burden region, thus allowing for better patient-tailored treatment. We also identified mutations not included in the catalogue, relevant at the local level. Evidence from this study, together with future updates of the catalogue, will probably lead in the future to the partial replacement of culture testing with WGS-based drug susceptibility testing in our setting. FUNDING: European Research Council and the Spanish Ministerio de Ciencia.

Comparison of three statistical methods for establishing tentative wild-type population and epidemiological cutoff values for echinocandins, amphotericin B, flucytosine, and six Candida species as determined by the colorimetric Sensititre YeastOne method.

The Sensititre YeastOne (SYO) method is a widely used method to determine the susceptibility of Candida spp. to antifungal agents. CLSI clinical breakpoints (CBP) have been reported for antifungals, but not using this method. In the absence of CBP, epidemiological cutoff values (ECVs) are useful to separate wild-type (WT) isolates (those without mechanisms of resistance) from non-WT isolates (those that can harbor some resistance mechanisms), which is the goal of any susceptibility test. The ECVs for five agents, obtained using the MIC distributions determined by the SYO test, were calculated and contrasted with those for three statistical methods and the MIC(50) and modal MIC, both plus 2-fold dilutions. The median ECVs (in mg/liter) (% of isolates inhibited by MICs equal to or less than the ECV; number of isolates tested) of the five methods for anidulafungin, micafungin, caspofungin, amphotericin B, and flucytosine, respectively, were as follows: 0.25 (98.5%; 656), 0.06 (95.1%; 659), 0.25 (98.7%; 747), 2 (100%; 923), and 1 (98.5%; 915) for Candida albicans; 8 (100%; 352), 4 (99.2%; 392), 2 (99.2%; 480), 1 (99.8%; 603), and 0.5 (97.9%; 635) for C. parapsilosis; 1 (99.2%; 123), 0.12 (99.2%; 121), 0.25 (99.2%; 138), 2 (100%; 171), and 0.5 (97.2%; 175) for C. tropicalis; 0.12 (96.6%; 174), 0.06 (96%; 176), 0.25 (98.4%; 188), 2 (100%; 209), and 0.25 (97.6%; 208) for C. glabrata; 0.25 (97%; 33), 0.5 (93.9%; 33), 1 (91.9%; 37), 4 (100%; 51), and 32 (100%; 53) for C. krusei; and 4 (100%; 33), 2 (100%; 33), 2 (100%; 54), 1 (100%; 90), and 0.25 (93.4%; 91) for C. orthopsilosis. The three statistical methods gave similar ECVs (within one dilution) and included ≥ 95% of isolates. These tentative ECVs would be useful for monitoring the emergence of isolates with reduced susceptibility by use of the SYO method.

Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics.

Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

[Extended spectrum beta-lactamase producing Escherichia coli in a tertiary hospital. Is there an increase of resistances to beta lactams?] / Infecciones urinarias por Escherichia coli productor de betalactamasas de espectro extendido en un hospital terciario ¿existe un aumento de las resistencias a los betalactámicos?

OBJECTIVE: The increase of isolation of beta-lactamase resistant Escherichia coli (BREC) strains makes treatment difficult. The objective of this study is to evaluate the situation in our environment. METHODS: Retrospective study including patients who presented positive urine cultures for E. coli in the Department of Health of Castellon between January 2012 and December 2015. We analyzed variables such as age, gender, patient`s origin (outpatient or hospital) and other risk factors. We performed a descriptive analysis to study the prevalence of BREC. RESULTS: 9113 cultures were positive for E Coli, 273(2.9%) of them were BREC. The annual percentage of BREC ranged from 1.7% to 3,4% with no increase over the last years. Mean age was 70 years, without gender differences. 247 cultures came from outpatient patients (90%), being 96% of them women. The factors most frequently associated with BREC were to present UTI over the last year and have received antibiotic treatment the previous 3 months; 50% of these received a beta lactam. CONCLUSIONS: In our environment, the isolation of BREC is similar to other series. Most patients come from the outpatient environment, were previously treated with antibiotics and had recurrent UTIs.

OBJETIVO: El aumento de aislamiento de cepas Escherichia coli resistentes a las betalactamasas (ECRB) dificulta su tratamiento. El objetivo de este estudio es evaluar la situación en nuestro entorno. MATERIAL Y MÉTODO: Estudio retrospectivo entre enero 2012 y diciembre de 2015, incluyendo pacientes que presentaban cultivos de orina positivos para E. coli en el Departamento de Salud de Castellón. Analizamos variables como: edad, sexo, procedencia del paciente (medio ambulatorio u hospitalario) y otros factores de riesgo. Se ha realizado un análisis descriptivo para estudiar la prevalencia de ECRB. RESULTADOS: Se obtuvieron 9113 cultivos positivos para E. coli, de estos 273 (2,9%) fueron ECRB. El porcentaje por año de ECRB fue entre un 1,7% y un 3,4% sin observarse incremento en los últimos años. La edad media fue 70 años, sin diferencias entre sexos. 247 cultivos procedían de pacientes ambulatorios (90%), correspondiendo el 96% de estos a mujeres. Los factores de riesgo más asociados a ECBR fueron presentar ITU el último año y haber recibido tratamiento antibiótico en los 3 meses previos, de estos un 50% recibió un betalactámico. CONCLUSIONES: En nuestro medio el aislamiento de ECRB es similar a otras series. La mayoría de pacientes fueron procedentes de medio ambulatorio, tratados previamente con antibióticos y con episodios de ITU recurrentes.

Modelo predictivo clínico-radiológico para diagnosticar tuberculosis pulmonar activa / Predictive clinical-radiological model for diagnosing active pulmonary tuberculosis

Resumen: Introducción: El objetivo de este estudio fue desarrollar un modelo predictivo sobre la presencia de tuberculosis pulmonar activa utilizando datos clínico-epidemiológicos y hallazgos de radiografía simple (Rx) y tomografía computadorizada (TC) de tórax. Material y métodos: Se realizó un estudio observacional, retrospectivo, descriptivo y analítico, que recopiló 22 variables clínico-epidemiológicas, 11 hallazgos radiológicos en Rx de tórax y 23 en la TC, que se realizaron en pacientes con sospecha clínica de tuberculosis pulmonar durante un período de 10 años. Se aplicó un modelo de regresión logística multivariado a los predictores potenciales de cultivo positivo, obteniendo un modelo predictivo. Resultados: Se recogieron 1.540 pacientes con sospecha clínica de tuberculosis a los que se les realizó Rx y TC torácico. El cultivo fue positivo en 101 casos. Se utilizó un proceso de eliminación hacia atrás para obtener el mejor conjunto de variables predictivas. Se obtuvieron 24 variables que fueron significativas (6 clínicas, 5 de Rx y 13 de TC) y se les asignó una puntuación. A la suma de estas puntuaciones se restó la edad en años multiplicada por 0,03. El modelo sugiere el diagnóstico de tuberculosis pulmonar activa en pacientes con una puntuación superior a 1,845. Obtuvo una sensibilidad de 85,1%, especificidad de 83,6%, valor predictivo positivo de 26,6%, y valor predictivo negativo de 98,7%. El área bajo la curva ROC fue de 0,9163. Conclusión: Este sistema de puntuación basado en criterios clínico-epidemiológicos y hallazgos radiológicos puede ayudar a diagnosticar tuberculosis pulmonar activa en casos de sospecha diagnóstica.

Abstract:Introduction: The objective of this study was to develop a predictive model on the presence of active pulmonary tuberculosis using clinical-epidemiological data and findings of chest radiography and thoracic computed tomography (CT). Material and methods: An observational, retrospective, descriptive and analytical study was conducted, which collected 22 clinical and epidemiological variables, 11 radiological findings on chest x-ray and 23 on CT that were performed in patients with clinical suspicion of pulmonary tuberculosis during a period of 10 years. A multivariate logistic regression model was applied to the potential predictors of positive culture, obtaining a predictive model. Results: We collected 1,540 patients with clinical suspicion of tuberculosis who underwent radiography and thoracic CT. The culture was positive in 101 cases. A backward elimination process was used to obtain the best set of predictive variables. We obtained 24 variables that were significant (6 clinical, 5 of chest plain films and 13 of CT) and were assigned a score. The sum of these scores was subtracted from the age in years and multiplied by 0.03. The model suggests the diagnosis of active pulmonary tuberculosis in patients with a score higher than 1.845. The model obtained a sensitivity of 85.1%, specificity of 83.6%, positive predictive value of 26.6, and negative predictive value of 98.7%. The area under the ROC curve was 0.9163. Conclusion: This scoring system based on clinical-epidemiological criteria and radiological findings can help rule out active pulmonary tuberculosis in cases of diagnostic suspicion.