TY - JOUR
T1 - Serum Biomarker Profile Including CCL1, CXCL10, VEGF, and Adenosine Deaminase Activity Distinguishes Active From Remotely Acquired Latent Tuberculosis
AU - Delemarre, Eveline M.
AU - van Hoorn, Laura
AU - Bossink, Aik W.J.
AU - Drylewicz, Julia
AU - Joosten, Simone A.
AU - Ottenhoff, Tom H.M.
AU - Akkerman, Onno W.
AU - Goletti, Delia
AU - Petruccioli, Elisa
AU - Navarra, Assunta
AU - van den Broek, Brigitte T.A.
AU - Paardekooper, Sanne P.A.
AU - van Haeften, Ineke
AU - Koenderman, Leo
AU - Lammers, Jan Willem J.
AU - Thijsen, Steven F.T.
AU - Hofland, Regina W.
AU - Nierkens, Stefan
N1 - Publisher Copyright:
© Copyright © 2021 Delemarre, van Hoorn, Bossink, Drylewicz, Joosten, Ottenhoff, Akkerman, Goletti, Petruccioli, Navarra, van den Broek, Paardekooper, van Haeften, Koenderman, Lammers, Thijsen, Hofland and Nierkens.
PY - 2021/10/7
Y1 - 2021/10/7
N2 - Introduction: There is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures. Materials and Methods: The discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation. Results: sPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants. Conclusion: The biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals.
AB - Introduction: There is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures. Materials and Methods: The discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation. Results: sPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants. Conclusion: The biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals.
UR - http://www.scopus.com/inward/record.url?scp=85117572280&partnerID=8YFLogxK
U2 - 10.3389/fimmu.2021.725447
DO - 10.3389/fimmu.2021.725447
M3 - Article
C2 - 34691031
AN - SCOPUS:85117572280
SN - 1664-3224
VL - 12
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 725447
ER -