Quantitative and qualitative profiles of circulating monocytes may help identifying tuberculosis infection and disease stages

Francesco Dieli, Antonio Cascio, Marco Pio La Manna, Nadia Rosalia Caccamo, Paola Di Carlo, Marco Pio La Manna, Valentina Orlando, Gilda Cuzzi, Francesco Dieli, Nadia Caccamo, Paola Di Carlo, Delia Goletti, Antonio Cascio, Fabrizio Palmieri, Valentina Orlando

Risultato della ricerca: Articlepeer review

58 Citazioni (Scopus)


Tuberculosis (TB) is one of the most important cause of morbidity and death among infectious diseases, and continuous efforts are needed to improve diagnostic tools and therapy. Previous published studies showed that the absolute cells number of monocytes or lymphocytes in peripheral blood or yet the ratio of monocytes to lymphocytes displayed the ability to predict the risk of active TB. In the present study we evaluated the ratio of monocytes to lymphocytes variation and we also analyzed the ex-vivo expression of CD64 on monocytes as tools to identify biomarkers for discriminating TB stages. Significant differences were found when the average ratio of monocytes to lymphocytes of active TB patients was compared with latent TB infection (LTBI) subjects, cured TB and healthy donors (HD). By the receiver operator characteristics (ROC) curve analysis the cut-off value of 0.285, allowed the discrimination of active TB from HD, with a sensitivity of 91.04% and a specificity of 93.55% (95% of confidence interval: 0.92-0.99). The ROC curve analysis comparing TB patients and LTBI groups, led to a sensitivity and the specificity of the assay of 85.07% and 85.71%, respectively (95% of confidence interval: 0.85 to 0.96). The upregulation of CD64 expression on circulating monocytes in active TB patients could represent an additional biomarker for diagnosis of active TB. In conclusion, we found that the ML ratio or monocyte absolute count or phenotypic measures show predictive value for active TB.
Lingua originaleEnglish
Numero di pagine15
RivistaPLoS One
Stato di pubblicazionePublished - 2017

All Science Journal Classification (ASJC) codes

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  • ???subjectarea.asjc.1100.1100???
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