Distinct plasma chemokines and cytokines signatures in Leishmania guyanensis-infected patients with cutaneous leishmaniasis

Abstract

The immunopathology associated with Leishmaniasis is a consequence of inflammation. Upon infection with Leishmania, the type of host-immune response is determinant for the clinical manifestations that can lead to either self-healing or chronic disease. Multiple pathways may determine disease severity. A comparison of systemic immune profiles in patients with cutaneous leishmaniasis caused by L. guyanensis and healthy individuals with the same socio-epidemiological characteristics coming from the same endemic areas as the patients is performed to identify particular immune profile and pathways associated with the progression of disease development. Twenty-seven plasma soluble circulating factors were evaluated between the groups by univariate and multivariate analysis. The following biomarkers pairs IL-17/IL-9 (ρ=0,829), IL-17/IL-12 (ρ=0,786), IL-6/IL-1ra (ρ=0,785), IL-6/IL-12 (ρ=0,780), IL-1β/G-CSF (ρ=0,758) and IL-17/MIP-1β (ρ=0,754) showed the highest correlation mean among the patient while only INF-γ/IL-4 (ρ=0.740), 17/MIP-1β (ρ=0,712) and IL-17/IL-9 (ρ=0,707) exhibited positive correlation among the control group. The cytokine IL-17 and IL1β presented the greater number of positive pair correlation among the patients. The linear combinations of biomarkers displayed IP-10, IL-2 and RANTES as the variables with the higher discriminatory activity in the patient group compared to PDGF, IL-1ra and eotaxin among the control subjects. IP-10, IL-2, IL-1β, RANTES and IL-17 seem to be predictive value of progression to the development of disease among the Lg-infected individuals.

Keywords: Leishmania guyanensis; chemokines; cutaneous leishmaniasis; cytokines; growth factors.

Figure 1

Correlation matrices within chemokines, cytokines and growth factors among patients with cutaneous leishmaniasis (A) and healthy controls (B) groups. Increasing values are represented by colors codes: blue for positive correlation and red for negative correlation. Significance: p< 0.05.

Figure 2

Network of cytokine correlations in the patients with cutaneous leishmaniasis (A) and healthy controls (B) groups. Nodes symbolize cytokines and connecting lines represent a Spearman’s correlation between two biomarkers. Positive correlations are indicated by red lines, while blue lines represent negative correlations. The absolute value of the correlation is represented by the width of the lines. The thickness and saturation of the lines were proportional to the strength of correlation. Biomarkers were arranged based on the number of connections from minimum to maximum. The network diagram was constructed using Cytoscape software version 3.8.2.

Figure 3

Principal component analysis (PCA) and Linear discriminant analysis (LDA) of reciprocally expressed biomarkers. (A) Scatterplot of the first two principal components (Dim1 and Dim2) showing two main groups, comprising 60.1% of total variance. Biomarkers from patients with cutaneous leishmaniasis (red closed circles) and of healthy control group (green closed circles) clustered in two different groups with overlapping regions. Colored ellipses indicate regions with 95% confidence levels. (B). Separation of biomarkers within two studied groups based on its discrimination power.

Figure 4

Heat map showing relative expression of biomarkers levels patients with cutaneous leishmaniasis and in healthy controls. Biomarker levels are expressed by color codes. Green represents the lowest and red the highest cytokine levels in the color key on the left. The rows denote the cytokines and the columns the infection status. The cluster analysis demonstrates the level of correlation among the variables represented by dendrograms. The distance between the two clusters is represented by the height where the two clusters merge.