Patient characteristics associated with clustering of RFLP patterns in isolates of Mycobacterium tuberculosis callected from a non-outbreak setting

Abstract

With the rise in the number of cases of tuberculosis in the United States, techniques for strain typing of Mycobacterium tuberculosis have been developed to assist in the understanding of the epidemiology of the disease. Restriction Fragment Length Polymorphism (RFLP) is a valuable tool for exposing transmission of tuberculosis, with epidemiologically related strains exhibiting identical RFLP fingerprint patterns. In non-outbreak settings, RFLP analysis may reveal outbreaks of tuberculosis previously undetected by traditional contact tracing. In addition, RFLP may allow for distinction of cases due to exogenous transmission and endogenous reactivation, based upon similarity of patterns. Clinical isolates of Mycobacterium tuberculosis were collected over an eighteen month period from patients at the VA Hospital in Houston, Texas. A total of 61 isolates were collected and fingerprinted using IS6110 as, the target for RFLP analysis. The resulting fingerprint patterns were compared visually and categorized as clustered (identical to at least one other isolate in the study) or nonclustered (not identical to any other isolate). Computerized analysis was done to calculate similarities among all RFLP patterns. Demographic data (age, race, HIV status, drug and alcohol usage) collected on all patients was analyzed for an association with clustering of fingerprint patterns. The purpose of this study was to identify patients within this study population whose tuberculosis is the result of erogenous transmission, as evidenced by clustering of fingerprint patterns. Additionally, risk factors for clustering of patterns (inferring recent transmission) were identified for this study population. Of the 61 clinical isolates fingerprinted, 67% were identical to at least one other isolate in the study (therefore clustered). Patient risk factors for clustering identified by logistic regression analysis were younger age (less than 50 years of age,) and HIV status, with patients not infected with HIV at a higher risk for clustering of patterns. Therefore, erogenous transmission accounts for two-thirds of the cases in this study, with younger patients, and those HIV negative experiencing the highest rates.