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Comparative Study
. 2021 Feb 26:12:633297.
doi: 10.3389/fimmu.2021.633297. eCollection 2021.

CXCL17 Is a Specific Diagnostic Biomarker for Severe Pandemic Influenza A(H1N1) That Predicts Poor Clinical Outcome

Affiliations
Comparative Study

CXCL17 Is a Specific Diagnostic Biomarker for Severe Pandemic Influenza A(H1N1) That Predicts Poor Clinical Outcome

Jose Alberto Choreño-Parra et al. Front Immunol. .

Erratum in

  • Corrigendum: CXCL17 Is a Specific Diagnostic Biomarker for Severe Pandemic Influenza A(H1N1) That Predicts Poor Clinical Outcome.
    Choreño-Parra JA, Jiménez-Álvarez LA, Ramírez-Martínez G, Sandoval-Vega M, Salinas-Lara C, Sánchez-Garibay C, Luna-Rivero C, Hernández-Montiel EM, Fernández-López LA, Cabrera-Cornejo MF, Choreño-Parra EM, Cruz-Lagunas A, Domínguez A, Márquez-García E, Cabello-Gutiérrez C, Bolaños-Morales FV, Mena-Hernández L, Delgado-Zaldivar D, Rebolledo-García D, Guadarrama-Ortiz P, Regino-Zamarripa NE, Mendoza-Milla C, García-Latorre EA, Rodríguez-Reyna TS, Cervántes-Rosete D, Hernández-Cárdenas CM, Khader SA, Zlotnik A, Zúñiga J. Choreño-Parra JA, et al. Front Immunol. 2021 May 13;12:700716. doi: 10.3389/fimmu.2021.700716. eCollection 2021. Front Immunol. 2021. PMID: 34054884 Free PMC article.

Abstract

The C-X-C motif chemokine ligand 17 (CXCL17) is chemotactic for myeloid cells, exhibits bactericidal activity, and exerts anti-viral functions. This chemokine is constitutively expressed in the respiratory tract, suggesting a role in lung defenses. However, little is known about the participation of CXCL17 against relevant respiratory pathogens in humans. Here, we evaluated the serum levels and lung tissue expression pattern of CXCL17 in a cohort of patients with severe pandemic influenza A(H1N1) from Mexico City. Peripheral blood samples obtained on admission and seven days after hospitalization were processed for determinations of serum CXCL17 levels by enzyme-linked immunosorbent assay (ELISA). The expression of CXCL17 was assessed by immunohistochemistry (IHQ) in lung autopsy specimens from patients that succumbed to the disease. Serum CXCL17 levels were also analyzed in two additional comparative cohorts of coronavirus disease 2019 (COVID-19) and pulmonary tuberculosis (TB) patients. Additionally, the expression of CXCL17 was tested in lung autopsy specimens from COVID-19 patients. A total of 122 patients were enrolled in the study, from which 68 had pandemic influenza A(H1N1), 24 had COVID-19, and 30 with PTB. CXCL17 was detected in post-mortem lung specimens from patients that died of pandemic influenza A(H1N1) and COVID-19. Interestingly, serum levels of CXCL17 were increased only in patients with pandemic influenza A(H1N1), but not COVID-19 and PTB. CXCL17 not only differentiated pandemic influenza A(H1N1) from other respiratory infections but showed prognostic value for influenza-associated mortality and renal failure in machine-learning algorithms and regression analyses. Using cell culture assays, we also identified that human alveolar A549 cells and peripheral blood monocyte-derived macrophages increase their CXCL17 production capacity after influenza A(H1N1) pdm09 virus infection. Our results for the first time demonstrate an induction of CXCL17 specifically during pandemic influenza A(H1N1), but not COVID-19 and PTB in humans. These findings could be of great utility to differentiate influenza and COVID-19 and to predict poor prognosis specially at settings of high incidence of pandemic A(H1N1). Future studies on the role of CXCL17 not only in severe pandemic influenza, but also in seasonal influenza, COVID-19, and PTB are required to validate our results.

Keywords: COVID-19; CXCL17; SARS-CoV-2; chemokines; influenza A(H1N1); tuberculosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
CXCL17 in the lung and serum of influenza, COVID-19, and PTB patients. (A) Morphological changes observed in the lung of influenza and COVID-19 patients (n = 2 per group). H&E, ×400. The expression of CXCL17 was analyzed in lung autopsy specimens from influenza (left lower panel) and COVID-19 (right lower panel). IHQ, ×400. (B) Serum CXCL17 levels in healthy donors (HD; n = 30) patients with influenza (n = 68), COVID-19 subjects (n = 24), and PTB patients (n = 30). Kruskal–Wallis test and post hoc Dunn test (plots display medians with interquartile ranges; ****p ≤ 0.0001). (C) K-means clustering analysis of the clinical characteristics of influenza and COVID-19 patients. (D) Random forest algorithm showing the most important factors that differentiate influenza from COVID-19. The points represent the mean decrease Gini values, indicative of the importance of each variable with respect to the mean importance of the model (discontinuous vertical line). (E) Receiver operating characteristic (ROC) curve of the levels of CXCL17 in influenza and COVID-19 subjects. The graph displays area under the curve (AUC) and 95% CI interval values.
Figure 2
Figure 2
Dynamics and prognostic value of serum CXCL17 levels in influenza (A) Influenza patients (n = 68) were grouped according to their duration of symptoms on admission. Levels of CXCL17 were compared to healthy donors (HD; Kruskal–Wallis test and post hoc Dunn test; graph displays means and the standard error ( ± SE); *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001). (B) We obtained a second serum sample in 54 influenza subjects seven days (D7) after hospital admission (D0). Levels of CXCL17 at D0 and D7 were compared with the Mann–Whitney U test. (C) Longitudinal change in CXCL17 levels in survivor and deceased influenza patients (Wilcoxon test). (D) Initial serum CXCL17 levels in survivor (n = 52) and deceased (n = 16) influenza patients (Mann–Whitney U test; plots display medians and interquartile ranges). (E) Random forest algorithm showing the most important factors that impact on influenza-associated mortality. (F) Receiver operating characteristic (ROC) curve of the levels of CXCL17 in survivor and deceased influenza subjects. The graph displays area under the curve (AUC) and 95% CI interval values. (G) Survival curves of influenza patients grouped according to their serum CXCL17 levels were compared with the log-rank test.
Figure 3
Figure 3
Extended predictive value of serum CXCL17 levels in influenza patients and cellular sources. (A) Multiple correlation analysis of the clinical variables and serum CXCL17 levels of influenza patients (n = 68). The heat color map gradient was constructed using Spearman R values. (B) Serum CXCL17 levels in influenza patients according to the severity of their acute respiratory distress syndrome (ARDS) on admission (mild, PaO2/FiO2 >200, n = 3; moderate, PaO2/FiO2 100–200, n = 27; severe, PaO2/FiO2 <100, n = 38; Kruskal–Wallis test and post hoc Dunn test). (C) Comparison of the levels of CXCL17 between COVID-19 patients that survived (n = 14) or died (n = 10). Mann–Whitney U test. (D) Serum levels of CXCL17 were compared between influenza patients that developed acute kindly injury (AKIN, n = 19), and individuals with normal renal function (n = 49). (E) Differences in CXCL17 levels between influenza patients according to their need for renal replacement therapy (RRT; n = 52 vs 16). (BE) Plots display medians and interquartile ranges. Mann–Whitney U test. (F) Receiver operating characteristic (ROC) curve of the CXCL17 levels in influenza patients that developed AKIN and those that maintained normal renal function. The graph display area under the curve (AUC) and 95% CI interval values. (G) ROC curve analysis of the serum CXCL17 levels in patients requiring RRT. (H) Human A549 alveolar epithelial cells and (I) peripheral blood-monocyte derived macrophages were infected with a clinical isolate of the influenza A(H1N1) pdm09 virus for 24, 48, and 72 h n = 6–7 per group per time point). Levels of CXCL17 in supernatants from infected and uninfected cells were compared using the unpaired Student’s t test (n = 5 to 9 per group) at each time point. Values of p were corrected for multiple comparisons using the Holm–Sidak method. The data represent mean ( ± SE) values from 2 to 3 independent experiments per time point and experimental condition. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001.

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