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Potential of DosR and Rpf antigens from Mycobacterium tuberculosis to discriminate between latent and active tuberculosis in a tuberculosis endemic population of Medellin Colombia

Overview of attention for article published in BMC Infectious Diseases, January 2018
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Title
Potential of DosR and Rpf antigens from Mycobacterium tuberculosis to discriminate between latent and active tuberculosis in a tuberculosis endemic population of Medellin Colombia
Published in
BMC Infectious Diseases, January 2018
DOI 10.1186/s12879-017-2929-0
Pubmed ID
Authors

Leonar Arroyo, Diana Marín, Kees L. M. C. Franken, Tom H. M. Ottenhoff, Luis F. Barrera

Abstract

Tuberculosis (TB) remains one of the most deadly infectious diseases. One-third to one-fourth of the human population is estimated to be infected with Mycobacterium tuberculosis (Mtb) without showing clinical symptoms, a condition called latent TB infection (LTBI). Diagnosis of Mtb infection is based on the immune response to a mixture of mycobacterial antigens (PPD) or to Mtb specific ESAT-6/CFP10 antigens (IGRA), highly expressed during the initial phase of infection. However, the immune response to PPD and IGRA antigens has a low power to discriminate between LTBI and PTB. The T-cell response to a group of so-called latency (DosR-regulon-encoded) and Resuscitation Promoting (Rpf) antigens of Mtb has been proved to be significantly higher in LTBI compared to active TB across many populations, suggesting their potential use as biomarkers to differentiate latent from active TB. PBMCs from a group LTBI (n = 20) and pulmonary TB patients (PTB, n = 21) from an endemic community for TB of the city of Medellín, Colombia, were in vitro stimulated for 7 days with DosR- (Rv1737c, Rv2029c, and Rv2628), Rpf- (Rv0867c and Rv2389c), the recombinant fusion protein ESAT-6-CFP10 (E6-C10)-, or PPD-antigen. The induced IFNγ levels detectable in the supernatants of the antigen-stimulated cells were then used to calculate specificity and sensitivity in discriminating LTBI from PTB, using different statistical approaches. IFNγ production in response to DosR and Rpf antigens was significantly higher in LTBI compared to PTB. ROC curve analyses of IFNγ production allowed differentiation of LTBI from PTB with areas under the curve higher than 0.70. Furthermore, Multiple Correspondence Analysis (MCA) revealed that LTBI is associated with higher levels of IFNγ in response to the different antigens compared to PTB. Analysis based on decision trees showed that the IFNγ levels produced in response to Rv2029c was the leading variable that best-classified disease status. Finally, logistic regression analysis predicted that IFNγ produced by PBMCs in response to E6-C10, Rv2029c, Rv0867c (RpfA) and Rv2389c (RpfA) antigens correlates best with the probability of being latently infected. The Mtb antigens E6-C10, Rv2029c (PfkB), Rv0867c (RpfA) and Rv2389c (RpfA), may be potential candidates to discriminate LTBI from PTB.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 18%
Researcher 9 13%
Student > Bachelor 8 12%
Student > Postgraduate 6 9%
Student > Ph. D. Student 5 7%
Other 10 15%
Unknown 18 26%
Readers by discipline Count As %
Immunology and Microbiology 14 21%
Medicine and Dentistry 9 13%
Biochemistry, Genetics and Molecular Biology 9 13%
Agricultural and Biological Sciences 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 6 9%
Unknown 25 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2018.
All research outputs
#15,487,739
of 23,015,156 outputs
Outputs from BMC Infectious Diseases
#4,533
of 7,723 outputs
Outputs of similar age
#270,239
of 442,237 outputs
Outputs of similar age from BMC Infectious Diseases
#88
of 162 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,723 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,237 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.