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间日疟原虫疟疾期间的细胞因子/趋化因子网络:理解该疾病的新见解

On the cytokine/chemokine network during Plasmodium vivax malaria: new insights to understand the disease.

作者信息

Hojo-Souza Natália Satchiko, Pereira Dhelio Batista, de Souza Fernanda Sumika Hojo, de Oliveira Mendes Tiago Antônio, Cardoso Mariana Santos, Tada Mauro Shugiro, Zanini Graziela Maria, Bartholomeu Daniella Castanheira, Fujiwara Ricardo Toshio, Bueno Lilian Lacerda

机构信息

Departamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Centro de Pesquisa em Medicina Tropical, Porto, Velho, Rondônia, Brazil.

出版信息

Malar J. 2017 Jan 24;16(1):42. doi: 10.1186/s12936-017-1683-5.

DOI:10.1186/s12936-017-1683-5
PMID:28118834
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5260126/
Abstract

BACKGROUND

The clinical outcome of malaria depends on the delicate balance between pro-inflammatory and immunomodulatory cytokine responses triggered during infection. Despite the numerous reports on characterization of plasma levels of cytokines/chemokines, there is no consensus on the profile of these mediators during blood stage malaria. The identification of acute phase biomarkers might contribute to a better understanding of the disease, allowing the use of more effective therapeutic approaches to prevent the progression towards severe disease. In the present study, the plasma levels of cytokines and chemokines and their association with parasitaemia and number of previous malaria episodes were evaluated in Plasmodium vivax-infected patients during acute and convalescence phase, as well as in healthy donors.

METHODS

Samples of plasma were obtained from peripheral blood samples from four different groups: P. vivax-infected, P. vivax-treated, endemic control and malaria-naïve control. The cytokine (IL-6, IL-10, IL-17, IL-27, TGF-β, IFN-γ and TNF) and chemokine (MCP-1/CCL2, IP-10/CXCL10 and RANTES/CCL5) plasma levels were measured by CBA or ELISA. The network analysis was performed using Spearman correlation coefficient.

RESULTS

Plasmodium vivax infection induced a pro-inflammatory response driven by IL-6 and IL-17 associated with an immunomodulatory profile mediated by IL-10 and TGF-β. In addition, a reduction was observed of IFN-γ plasma levels in P. vivax group. A lower level of IL-27 was observed in endemic control group in comparison to malaria-naïve control group. No significant results were found for IL-12p40 and TNF. It was also observed that P. vivax infection promoted higher levels of MCP-1/CCL2 and IP-10/CXCL10 and lower levels of RANTES/CCL5. The plasma level of IL-10 was elevated in patients with high parasitaemia and with more than five previous malaria episodes. Furthermore, association profile between cytokine and chemokine levels were observed by correlation network analysis indicating signature patterns associated with different parasitaemia levels.

CONCLUSIONS

The P. vivax infection triggers a balanced immune response mediated by IL-6 and MCP-1/CCL2, which is modulated by IL-10. In addition, the results indicated that IL-10 plasma levels are influenced by parasitaemia and number of previous malaria episodes.

摘要

背景

疟疾的临床结局取决于感染期间引发的促炎和免疫调节细胞因子反应之间的微妙平衡。尽管有大量关于细胞因子/趋化因子血浆水平特征的报道,但对于血源性疟疾期间这些介质的概况尚无共识。急性期生物标志物的鉴定可能有助于更好地理解该疾病,从而采用更有效的治疗方法来预防疾病进展为重症。在本研究中,评估了间日疟原虫感染患者急性期和恢复期以及健康供体血浆中细胞因子和趋化因子的水平及其与寄生虫血症和既往疟疾发作次数的关系。

方法

从四个不同组的外周血样本中获取血浆样本:间日疟原虫感染组、间日疟原虫治疗组、地方性对照组和未感染疟疾对照组。通过CBA或ELISA测量细胞因子(IL-6、IL-10、IL-17、IL-27、TGF-β、IFN-γ和TNF)和趋化因子(MCP-1/CCL2、IP-10/CXCL10和RANTES/CCL5)的血浆水平。使用Spearman相关系数进行网络分析。

结果

间日疟原虫感染引发了由IL-6和IL-17驱动的促炎反应,并伴有由IL-10和TGF-β介导的免疫调节特征。此外,间日疟原虫组中IFN-γ血浆水平降低。与未感染疟疾对照组相比,地方性对照组中IL-27水平较低。未发现IL-12p40和TNF有显著结果。还观察到间日疟原虫感染促进了更高水平的MCP-1/CCL2和IP-10/CXCL10以及更低水平的RANTES/CCL5。寄生虫血症高且既往疟疾发作超过五次的患者血浆中IL-10水平升高。此外,通过相关网络分析观察到细胞因子和趋化因子水平之间的关联特征,表明与不同寄生虫血症水平相关的特征模式。

结论

间日疟原虫感染引发了由IL-6和MCP-1/CCL2介导的平衡免疫反应,该反应由IL-10调节。此外,结果表明IL-10血浆水平受寄生虫血症和既往疟疾发作次数的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/787086f41452/12936_2017_1683_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/29bf335a8d15/12936_2017_1683_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/23042d505374/12936_2017_1683_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/f9a08346776f/12936_2017_1683_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/4a47ab38af78/12936_2017_1683_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/787086f41452/12936_2017_1683_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/29bf335a8d15/12936_2017_1683_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/12aec8cb1824/12936_2017_1683_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/23042d505374/12936_2017_1683_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/f9a08346776f/12936_2017_1683_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/4a47ab38af78/12936_2017_1683_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fd9/5260126/787086f41452/12936_2017_1683_Fig6_HTML.jpg

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