InTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis.
ABSTRACT: BACKGROUND: Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data. RESULTS: We developed inTB, a web-based system for integrated warehousing and analysis of clinical, socio-demographic and molecular data for Mycobacterium sp. isolates. As a database it can organize and display data from any of the standard genotyping methods (SNP, MIRU-VNTR, RFLP and spoligotype), as well as an extensive array of clinical and socio-demographic variables that are used in multiple countries to characterize the disease. Through the inTB interface it is possible to insert and download data, browse the database and search specific parameters. New isolates are automatically classified into strains according to an internal reference, and data uploaded or typed in is checked for internal consistency. As an analysis framework, the system provides simple, point and click analysis tools that allow multiple types of data plotting, as well as simple ways to download data for external analysis. Individual trees for each genotyping method are available, as well as a super tree combining all of them. The integrative nature of inTB grants the user the ability to generate trees for filtered subsets of data crossing molecular and clinical/socio-demografic information. inTB is built on open source software, can be easily installed locally and easily adapted to other diseases. Its design allows for use by research laboratories, hospitals or public health authorities. The full source code as well as ready to use packages is available at http://www.evocell.org/inTB. CONCLUSIONS: To the best of our knowledge, this is the only system capable of integrating different types of molecular data with clinical and socio-demographic data, empowering researchers and clinicians with easy to use analysis tools that were not possible before.
Project description:The comparison of Mycobacterium tuberculosis bacterial genotypes with phenotypic, demographic, geospatial and clinical data improves our understanding of how strain lineage influences the development of drug-resistance and the spread of tuberculosis.To investigate the association of Mycobacterium tuberculosis bacterial genotype with drug-resistance. Drug susceptibility testing together with genotyping using both 15-loci MIRU-typing and spoligotyping, was performed on 2,139 culture positive isolates, each from a different patient in Lima, Peru. Demographic, geospatial and socio-economic data were collected using questionnaires, global positioning equipment and the latest national census.The Latin American Mediterranean (LAM) clade (OR 2.4, p<0.001) was significantly associated with drug-resistance and alone accounted for more than half of all drug resistance in the region. Previously treated patients, prisoners and genetically clustered cases were also significantly associated with drug-resistance (OR's 2.5, 2.4 and 1.8, p<0.001, p<0.05, p<0.001 respectively).Tuberculosis disease caused by the LAM clade was more likely to be drug resistant independent of important clinical, genetic and socio-economic confounding factors. Explanations for this include; the preferential co-evolution of LAM strains in a Latin American population, a LAM strain bacterial genetic background that favors drug-resistance or the "founder effect" from pre-existing LAM strains disproportionately exposed to drugs.
Project description:Extrapulmonary Tuberculosis (EPTB) and Human Immunodeficiency Virus (HIV) infection are interrelated as a result of immune depression. The aim of this study was to determine the prevalence of Mycobacterium tuberculosis complex isolates and the burden of HIV co-infection among EPTB suspected patients.An institution based cross-sectional study was conducted among EPTB suspected patients at the University of Gondar Hospital. Socio-demographic characteristics and other clinical data were collected using a pretested questionnaire. GeneXpert MTB/RIF assay was performed to diagnosis Mycobacterium tuberculosis complex and Rifampicin resistance. All samples were also investigated by cytology and culture. The HIV statuses of all patients were screened initially by KHB, and all positive cases were further re-tested by STAT-pack. Data was analyzed using SPSS version 20 computer software and a P-value of < 0.05 was taken as statistically significant.A total of 141 extrapulmonary suspected patients were enrolled in this study. The overall prevalence of culture confirmed extrapulmonary tuberculosis infection was 29.8%, but the GeneXpert result showed a 26.2% prevalence of Mycobacterium tuberculosis complex infection. The 78.4% prevalence of extrapulmonary tuberculosis infection was found to be higher among the adult population. The prevalence of HIV infection among EPTB suspected patients was 14.1%, while it was 32.4% among GeneXpert-confirmed extrapulmonary TB cases (12/37). Tuberculosis lymphadenitis was the predominant (78.4%) type of EPTB infection followed by tuberculosis cold abscess (10.7%). Adult hood, previous history of contact with known pulmonary tuberculosis patients, and HIV co-infection showed a statistically significant association with extrapulmonary tuberculosis infection (P<0.013).The prevalence of culture confirmed-EPTB infection was high, and a higher EPTB-HIV co-infection was also observed.
Project description:Tuberculosis (TB) in humans is primarily caused by Mycobacterium tuberculosis (M. tuberculosis), with millions of infections and hundreds of thousands of deaths worldwide. It creates a substantial economic burden on the community. Unlike M. tuberculosis, Mycobacterium bovis infects cattle and causes bovine TB, also known as zoonotic TB. People can contract zoonotic TB after consumption of unpasteurized dairy products, handling the sick animals, and via occupational exposures. The association between the zoonotic TB in humans and cattle is not well known in Nepal. The study examined the associated risk factors, including exposure to infected cattle, that contribute to TB's development in human beings in Nepal. The study consists of human and animal subjects. Firstly, a retrospective matched case-control study was conducted at the National Tuberculosis Center (NTC), Bhaktapur, Nepal. A total of 290 people (equal numbers of TB cases and control subjects) were interviewed to obtain information on socio-demographic, behavioral, and occupational risks, including the history of cattle related exposures. Secondly, a cross-sectional study was performed among the cattle owned by the TB-confirmed patients. Comparative tuberculin skin test, rapid antibody test, and ELISA were used in parallel to detect M. bovis infection in cattle. The risk factors for the development of TB in humans were smokers (OR = 4.6, 95% CI: 2.1-10.0, p < 0.001), previous history of TB (OR = 7.9, 95% CI: 3.0-20.6, p < 0.001) and history of cattle exposures (OR = 3.9, 95% CI: 2.1-7.4, p = 0.001). Out of 123 cattle sampled, 12 cattle (9.76%, 95% CI: 5.37-16.76, p < 0.0001) were positive by the tuberculin test, 46 (37.4%, 95% CI: 28.97-46.62, p = 0.007) were tested positive by the rapid test, and 7 (5.7%, 95% CI: 2.52-11.80, p < 0.0001) by ELISA test. The inter-test agreement between the tuberculin and ELISA was very strong (? = 0.72, 95% CI: 0.48-0.95, p < 0.01). This study indicates that exposure to infected cattle and socio-demographic risk factors can contribute to the development of TB in human beings.
Project description:BACKGROUND:Tuberculosis (TB) represents a major global health problem. The prognosis of clinically active tuberculosis depends on the complex interactions between Mycobacterium tuberculosis (Mtb) and its host. In recent years, autophagy receives particular attention for its role in host defense against intracellular pathogens, including Mtb. In present study, we aim to investigate the relationship of autophagy induction by clinical isolates of Mtb with the clinical outcomes in patients with TB. METHODOLOGY/PRINCIPAL FINDINGS:We collected 185 clinical isolates of Mtb, and determined the effect of these Mtb isolates on autophagy induction in macrophages. It was found that most of clinical isolates of Mtb were able to induce autophagosome formation in macrophages, however, the autophagy-inducing ability varied significantly among different isolates. Of importance, our results revealed that patients infected by Mtb with poor autophagy-inducing ability displayed more severe radiographic extent of disease (p<0.001), and were more likely to have unfavorable treatment outcomes (p<0.001). No significant association was observed between the extent of Mtb-induced autophagy with some socio-demographic characteristics (such as gender, age and tobacco consumption), and some laboratory tests (such as hemoglobin, leukocyte count and erythrocyte sedimentation rate). Furthermore, results from logistic regression analysis demonstrated that the defect in autophagy induction by clinical isolates of Mtb was an independent risk factor for far-advanced radiographic disease (aOR 4.710 [1.93-11.50]) and unfavorable treatment outcomes (aOR 8.309 [2.22-28.97]) in TB. CONCLUSION/SIGNIFICANCE:These data indicated that the defect in autophagy induction by Mtb isolates increased the risk of poor clinical outcomes in TB patients, and detection of clinical isolates-induced autophagosome formation might help evaluate the TB outcomes.
Project description:The sequencing of genomes of the pathogenic Mycobacterial species causing pulmonary and extrapulmonary tuberculosis, leprosy and other atypical mycobacterial infections, offer immense opportunities for discovering new therapeutics and identifying new vaccine candidates. Enhanced RV, which uses additional algorithms to Reverse Vaccinology (RV), has increased potential to reduce likelihood of undesirable features including allergenicity and immune cross reactivity to host. The starting point for MycobacRV database construction includes collection of known vaccine candidates and a set of predicted vaccine candidates identified from the whole genome sequences of 22 mycobacterium species and strains pathogenic to human and one non-pathogenic Mycobacterium tuberculosis H37Ra strain. These predicted vaccine candidates are the adhesins and adhesin-like proteins obtained using SPAAN at Pad > 0.6 and screening for putative extracellular or surface localization characteristics using PSORTb v.3.0 at very stringent cutoff. Subsequently, these protein sequences were analyzed through 21 publicly available algorithms to obtain Orthologs, Paralogs, BetaWrap Motifs, Transmembrane Domains, Signal Peptides, Conserved Domains, and similarity to human proteins, T cell epitopes, B cell epitopes, Discotopes and potential Allergens predictions. The Enhanced RV information was analysed in R platform through scripts following well structured decision trees to derive a set of nonredundant 233 most probable vaccine candidates. Additionally, the degree of conservation of potential epitopes across all orthologs has been obtained with reference to the M. tuberculosis H37Rv strain, the most commonly used strain in M. tuberculosis studies. Utilities for the vaccine candidate search and analysis of epitope conservation across the orthologs with reference to M. tuberculosis H37Rv strain are available in the mycobacrvR package in R platform accessible from the "Download" tab of MycobacRV webserver. MycobacRV an immunoinformatics database of known and predicted mycobacterial vaccine candidates has been developed and is freely available at http://mycobacteriarv.igib.res.in.
Project description:Systems-level approaches are increasingly common in both murine and human translational studies. These approaches employ multiple high information content assays. As a result, there is a need for tools to integrate heterogeneous types of laboratory and clinical/demographic data, and to allow the exploration of that data by aggregating and/or segregating results based on particular variables (e.g., mean cytokine levels by age and gender).Here we describe the application of standard data warehousing tools to create a novel environment for user-driven upload, integration, and exploration of heterogeneous data. The system presented here currently supports flow cytometry and immunoassays performed in the Stanford Human Immune Monitoring Center, but could be applied more generally.Users upload assay results contained in platform-specific spreadsheets of a defined format, and clinical and demographic data in spreadsheets of flexible format. Users then map sample IDs to connect the assay results with the metadata. An OLAP (on-line analytical processing) data exploration interface allows filtering and display of various dimensions (e.g., Luminex analytes in rows, treatment group in columns, filtered on a particular study). Statistics such as mean, median, and N can be displayed. The views can be expanded or contracted to aggregate or segregate data at various levels. Individual-level data is accessible with a single click. The result is a user-driven system that permits data integration and exploration in a variety of settings. We show how the system can be used to find gender-specific differences in serum cytokine levels, and compare them across experiments and assay types.We have used the tools and techniques of data warehousing, including open-source business intelligence software, to support investigator-driven data integration and mining of diverse immunological data.
Project description:Genetic tracking of Mycobacterium tuberculosis is a cornerstone of tuberculosis (TB) control programs. The RD(Rio) M. tuberculosis sublineage was previously associated with TB in Brazil. We investigated 3847 M. tuberculosis isolates and registry data from New York City (NYC) (2001-2005) to: (1) affirm the position of RD(Rio) strains within the M. tuberculosis phylogenetic structure, (2) determine its prevalence, and (3) define transmission, demographic, and clinical characteristics associated with RD(Rio) TB.Isolates classified as RD(Rio) or non-RD(Rio) M. tuberculosis by multiplex PCR were further classified as clustered (?2 isolates) or unique based primarily upon IS6110-RFLP patterns and lineage-specific cluster proportions were calculated. The secondary case rate of RD(Rio) was compared with other prevalent M. tuberculosis lineages. Genotype data were merged with the data from the NYC TB Registry to assess demographic and clinical characteristics.RD(Rio) strains were found to: (1) be restricted to the Latin American-Mediterranean family, (2) cause approximately 8% of TB cases in NYC, and (3) be associated with heightened transmission as shown by: (i) a higher cluster proportion compared to other prevalent lineages, (ii) a higher secondary case rate, and (iii) cases in children. Furthermore, RD(Rio) strains were significantly associated with US-born Black or Hispanic race, birth in Latin American and Caribbean countries, and isoniazid resistance.The RD(Rio) genotype is a single M. tuberculosis strain population that is emerging in NYC. The findings suggest that expanded RD(Rio) case and exposure identification could be of benefit due to its association with heightened transmission.
Project description:BACKGROUND:Multidrug drug-resistant tuberculosis (MDR-TB) is a major health problem and seriously threatens TB control and prevention efforts globally. Ethiopia is among the 30th highest TB burden countries for MDR-TB with 14% prevalence among previously treated cases. The focus of this study was on determining drug resistance patterns of Mycobacterium tuberculosis among MDR-TB suspected cases and associated risk factors. METHODS:A cross-sectional study was conducted in Addis Ababa from June 2015 to December 2016. Sputum samples and socio-demographic data were collected from 358 MDR-TB suspected cases. Samples were analyzed using Ziehl-Neelsen technique, GeneXpert MTB/RIF assay, and culture using Lowenstein-Jensen and Mycobacterial growth indicator tube. Data were analyzed using SPSS version 23. RESULTS:A total of 226 the study participants were culture positive for Mycobacterium tuberculosis, among them, 133 (58.8%) participants were males. Moreover, 162 (71.7%) had been previously treated for tuberculosis, while 128 (56.6%) were TB/HIV co-infected. A majority [122 (54%)] of the isolates were resistant to any first-line anti-TB drugs. Among the resistant isolates, 110 (48.7%) were determined to be resistant to isoniazid, 94 (41.6%) to streptomycin, 89 (39.4%) to rifampicin, 72 (31.9%) to ethambutol, and 70 (30.9%) to pyrazinamide. The prevalence of MDR-TB was 89 (39.4%), of which 52/89 (58.4%) isolates were resistance to all five first-line drugs. Risk factors such as TB/HIV co-infection (AOR = 5.59, p = 0.00), cigarette smoking (AOR = 3.52, p = 0.045), alcohol drinking (AOR = 5.14, p = 0.001) hospital admission (AOR = 3.49, p = 0.005) and visiting (AOR = 3.34, p = 0.044) were significantly associated with MDR-TB. CONCLUSIONS:The prevalence of MDR-TB in the study population was of a significantly high level among previously treated patients and age group of 25-34. TB/HIV coinfection, smoking of cigarette, alcohol drinking, hospital admission and health facility visiting were identified as risk factors for developing MDR-TB. Therefore, effective strategies should be designed considering the identified risk factors for control of MDR-TB.
Project description:Data warehousing is the most important technology to address recent advances in precision medicine. However, a generic clinical data warehouse does not address unstructured and insufficient data. In precision medicine, it is essential to develop a platform that can collect and utilize data. Data were collected from electronic medical records, genomic sequences, tumor biopsy specimens, and national cancer control initiative databases in the National Cancer Center (NCC), Korea. Data were de-identified and stored in a safe and independent space. Unstructured clinical data were standardized and incorporated into cancer registries and linked to cancer genome sequences and tumor biopsy specimens. Finally, national cancer control initiative data from the public domain were independently organized and linked to cancer registries. We constructed a system for integrating and providing various cancer data called the Korea Cancer Big Data Platform (K-CBP). Although the K-CBP could be used for cancer research, the legal and regulatory aspects of data distribution and usage need to be addressed first. Nonetheless, the system will continue collecting data from cancer-related resources that will hopefully facilitate precision-based research.