Skip to content
naulon
Not checkedNot checked for notices yet.

Dysglycemia is associated with Mycobacterium tuberculosis lineages in tuberculosis patients of North Lima-Peru.

Kattya Lopez, María B Arriaga, Juan G Aliaga and 9 more

PLoS ONE · 2021

doi:10.1371/journal.pone.0243184 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

This study was performed to investigate the role of dysglycemia on the genetic diversity of Mycobacterium tuberculosis (MTB) among pulmonary tuberculosis (TB) patients to build scientific evidence about the possible mechanisms of TB transmission. MTB isolates obtained of patients affected by pulmonary tuberculosis from health care facilities of North Lima-Peru, were analyzed using whole genome sequencing and 24-locus mycobacterial interspersed repetitive-unit -variable-number tandem repeats (MIRU-VNTR). Subsequently, clinical and epidemiological characteristics were associated with clustering, lineages and comorbid conditions. The analysis carried out 112 pulmonary TB patients from various health centers in North Lima, 17 (15%) had diabetes mellitus (DM) and 33 (29%) had pre-diabetes (PDM). Latin American-Mediterranean, Haarlem and Beijing were the most frequent MTB lineages found in those patients. Previous TB (adjusted odds ratio [aOR] = 3.65; 95%CI: 1.32-17.81), age (aOR = 1.12; 95%CI: 1.03-1.45) and Beijing lineage (aOR = 3.53; 95%CI: 1.08-13.2) were associated with TB-DM comorbidity. Alcoholism (aOR = 2.92; 95%CI: 1.10-8.28), age (aOR = 1.05; 95%CI: 1.03-1.12) and Haarlem lineage (aOR = 2.54; 95%CI: 1.04-6.51) were associated with TB-PDM comorbidity. Beijing and Haarlem lineages were independently associated with TB-DM and TB-PDM comorbidities, respectively. Although these findings may be surprising, we must be cautious to suggest that dysglycemia could be associated with a highly clustering and predisposition of MTB lineages related to a serious impact on the severity of TB disease, which requires further research.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.