Dataset Information

Ethnicity and mycobacterial lineage as determinants of tuberculosis disease phenotype.

ABSTRACT: Emerging evidence suggests that Mycobacterium tuberculosis (Mtb) lineage and host ethnicity can determine tuberculosis (TB) clinical disease patterns but their relative importance and interaction are unknown.We evaluated prospectively collected TB surveillance and Mtb strain typing data in an ethnically heterogeneous UK population. Lineage assignment was denoted using 15-loci mycobacterial interspersed repetitive units containing variable numbers of tandem repeats (MIRU-VNTR) and MIRU-VNTRplus. Geographical and ethnic associations of the six global Mtb lineages were identified and the influence of lineage and demographic factors on clinical phenotype were assessed using multivariate logistic regression.Data were available for 1070 individuals with active TB which was pulmonary only, extrapulmonary only and concurrent pulmonary-extrapulmonary in 52.1%, 36.9% and 11.0% respectively. The most prevalent lineages were Euro-American (43.7%), East African Indian (30.2%), Indo-Oceanic (13.6%) and East Asian (12.2%) and were geo-ethnically restricted with, for example, Indian subcontinent ethnicity inversely associated with Euro-American lineage (OR 0.23; 95% CI 0.14 to 0.39) and positively associated with the East African-Indian lineage (OR 4.04; 95% CI 2.19 to 7.45). Disease phenotype was most strongly associated with ethnicity (OR for extrathoracic disease 21.14 (95% CI 6.08 to 73.48) for Indian subcontinent and 14.05 (3.97 to 49.65) for Afro-Caribbean), after adjusting for lineage. With East Asian lineage as the reference category, the Euro-American (OR 0.54; 95% CI 0.32 to 0.91) and East-African Indian (OR 0.50; 95% CI 0.29 to 0.86) lineages were negatively associated with extrathoracic disease, compared with pulmonary disease, after adjusting for ethnicity.Ethnicity is a powerful determinant of clinical TB phenotype independently of mycobacterial lineage and the role of ethnicity-associated factors in pathogenesis warrants investigation.

SUBMITTER: Pareek M

PROVIDER: S-EPMC5741171 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Ethnicity and mycobacterial lineage as determinants of tuberculosis disease phenotype.

Pareek Manish M Evans Jason J Innes John J Smith Grace G Hingley-Wilson Suzie S Lougheed Kathryn E KE Sridhar Saranya S Dedicoat Martin M Hawkey Peter P Lalvani Ajit A

Thorax 20120927 3

<h4>Background</h4>Emerging evidence suggests that Mycobacterium tuberculosis (Mtb) lineage and host ethnicity can determine tuberculosis (TB) clinical disease patterns but their relative importance and interaction are unknown.<h4>Methods</h4>We evaluated prospectively collected TB surveillance and Mtb strain typing data in an ethnically heterogeneous UK population. Lineage assignment was denoted using 15-loci mycobacterial interspersed repetitive units containing variable numbers of tandem repe ...[more]

PMID: 23019255

Similar Datasets

Project description:BackgroundTuberculosis (TB) is one of the world's most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM.MethodsBlood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins' functions and their contributions to biological pathways.ResultsMore than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an FDR < 0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, α-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P < 0.05; fold changes≥2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation.ConclusionPlasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.

Project description:AbstractNontuberculous mycobacteria (NTM) infection may interfere in the diagnosis and treatment of tuberculosis (TB) in TB-endemic regions. However, the population-based incidence of NTM disease and NTM-TB coinfection remains unclear.We used Taiwan's National Health Insurance Research Database to identify new diagnoses of NTM disease and TB from 2005 to 2013 and calculated the incidence rate and the proportion of NTM-TB coinfection. The patients with NTM disease or TB were determined by the use of disease codes from International Classification of Diseases, Ninth Revision, Clinical Modification, laboratory mycobacterium examination codes, and antimycobacterial therapy receipts.From 2005 to 2013, the age-adjusted incidence rate of NTM disease increased from 5.3 to 14.8 per 100,000 people per year and the age-adjusted incidence rate of NTM-TB coinfection was around 1.2 to 2.2 per 100,000 people per year. The proportion of NTM-TB coinfection among patients with confirmed TB was 2.8%. Male and older patients had a significantly higher incidence of NTM disease. The effects of urbanization and socioeconomic status (SES) on the incidences of TB and NTM disease were different. Rural living and lower SES were significantly associated with increasing the incidence of confirmed TB but not with that of NTM disease. For NTM disease, those living in the least urbanized area had significantly lower incidence rate ratio than in the highest urbanized area. The incidence of NTM-TB coinfection was higher in older patients and compared with patients aged < 45 years, the incidence rate ratio of the patients aged> 74 years was 12.5.In TB-endemic Taiwan, the incidence of NTM disease increased from 2005 to 2013. Male gender and old age were risk factors for high incidence of NTM disease. SES did not have a significant effect on the incidence of NTM disease, but rural living was associated with lower incidence of NTM disease. In TB-endemic areas, NTM-TB coinfection could disturb the diagnosis of TB and treatment, especially in elderly patients.

Dataset Information

Ethnicity and mycobacterial lineage as determinants of tuberculosis disease phenotype.

Publications

Ethnicity and mycobacterial lineage as determinants of tuberculosis disease phenotype.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets