Plasma levels of C-reactive protein, matrix metalloproteinase-7 and lipopolysaccharide-binding protein distinguish active pulmonary or extrapulmonary tuberculosis from uninfected controls in children.

The immune profile associated with distinct clinical forms of tuberculosis (TB) has been extensively described for adult populations. Nevertheless, studies describing immune determinants of pulmonary or extrapulmonary TB (PTB or EPTB, respectively) in children are scarce. Here, we retrospectively assessed plasma levels of several mediators of inflammation in age and sex-matched children from South India presenting with PTB (n = 14) or EPTB (n = 22) as well as uninfected healthy controls (n = 19) to identify biomarkers that could accurately distinguish different TB clinical forms. Furthermore, we performed exploratory analyses testing the influence of sex on the systemic inflammatory profile. The analyses identified a biosignature of 10 biomarkers capable of distinguishing the three clinical groups simultaneously. Machine-learning decision trees indicated that C-reactive protein (CRP), matrix metalloproteinase (MMP)-7 and lipopolysaccharide-binding protein (LBP) were the markers that, when combined, displayed the highest accuracy in identifying the clinical groups. Additional exploratory analyses suggested that the disease signatures were highly influenced by sex. Therefore, sex differentially impacted status of systemic inflammation, immune activation and tissue remodeling in children with distinct clinical forms of TB. Regardless of such nuances related to biological sex, MMP-7, CRP and LBP were strong discriminators of active TB and thus could be considered as biomarkers useful in discrimination different TB clinical forms. These observations have implications on our understanding of the immunopathology of both clinical forms of TB in pediatric patients. If validated by other studies in the future, the combination of identified biomarkers may help development of point-of-care diagnostic or prognostic tools.

KEYWORDS: {{ getKeywords(articleDetailText.words) }}