Correlations between major risk factors and closely related Mycobacterium tuberculosis isolates grouped by three current enotyping procedures: a population-based study in northeast Mexico

• Autor(a) principal: Peñuelas-Urquides,Katia
• Data de Publicação: 2014
• Outros Autores: Martínez-Rodríguez,Herminia Guadalupe, Enciso-Moreno,José Antonio, Molina-Salinas,Gloria María, Silva-Ramírez,Beatriz, Padilla-Rivas,Gerardo Raymundo, Vera-Cabrera,Lucio, Torres-de-la-Cruz,Víctor Manuel, Martínez-Martínez,Yazmin Berenice, Ortega-García,Jorge Luis, Garza-Treviño,Elsa Nancy, Enciso-Moreno,Leonor, Saucedo-Cárdenas,Odila, Becerril-Montes,Pola, Said-Fernández/,Salvador
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Memórias do Instituto Oswaldo Cruz
• Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762014000600814
• topic: Mycobacterium tuberculosis; MTB; genotyping; risk factors; tuberculosis transmission; population; based study

The characteristics of tuberculosis (TB) patients related to a chain of recent TB transmissions were investigated. Mycobacterium tuberculosis (MTB) isolates (120) were genotyped using the restriction fragment length polymorphism-IS6110 (R), spacer oligotyping (S) and mycobacterial interspersed repetitive units-variable number of tandem repeats (M) methods. The MTB isolates were clustered and the clusters were grouped according to the similarities of their genotypes. Spearman’s rank correlation coefficients between the groups of MTB isolates with similar genotypes and those patient characteristics indicating a risk for a pulmonary TB (PTB) chain transmission were ana- lysed. The isolates showing similar genotypes were distributed as follows: SMR (5%), SM (12.5%), SR (1.67%), MR (0%), S (46.67%), M (5%) and R (0%). The remaining 35 cases were orphans. SMR exhibited a significant correlation (p < 0.05) with visits to clinics, municipalities and comorbidities (primarily diabetes mellitus). S correlated with drug consumption and M with comorbidities. SMR is needed to identify a social network in metropolitan areas for PTB transmission and S and M are able to detect risk factors as secondary components of a transmission chain of TB.