Dataset Information

Multi-omic Analyses of Plasma Cytokines, Lipidomics, and Transcriptomics Distinguish Treatment Outcomes in Cutaneous Leishmaniasis.

ABSTRACT: Leishmania braziliensis infection frequently results in cutaneous leishmaniasis (CL). An increase in incidence of drug-resistant CL leading to treatment failure has been reported. Identification of reliable predictors of treatment outcomes is necessary to optimize patient care. Here, we performed a prospective case-control study in which plasma levels of cytokines and lipid mediators were assessed at different time points during antileishmanial therapy in patients with CL from Brazil. Multidimensional analyses were employed to describe a combination of biomarkers able to predict and characterize treatment failure. We found a biosignature influenced mainly by plasma levels of lipid mediators that accurately predicted treatment failure. Furthermore, transcriptomic analysis of a publicly available data set revealed that expression levels of genes related to lipid metabolism measured in skin lesions could distinguish treatment outcomes in CL. Thus, activation of pathways linked to lipid biosynthesis predicts treatment failure in CL. The biomarkers identified may be further explored as therapeutic targets.

SUBMITTER: Malta-Santos H

PROVIDER: S-EPMC7721649 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-omic Analyses of Plasma Cytokines, Lipidomics, and Transcriptomics Distinguish Treatment Outcomes in Cutaneous Leishmaniasis.

Malta-Santos Hayna H Fukutani Kiyoshi F KF Sorgi Carlos A CA Queiroz Artur T L ATL Nardini Viviane V Silva Juliana J Lago Alex A Carvalho Lucas P LP Machado Paulo L R PLR Bozza Patrícia T PT França-Costa Jaqueline J Faccioli Lucia H LH Carvalho Edgar M EM Andrade Bruno B BB Borges Valéria M VM

iScience 20201123 12

<i>Leishmania braziliensis</i> infection frequently results in cutaneous leishmaniasis (CL). An increase in incidence of drug-resistant CL leading to treatment failure has been reported. Identification of reliable predictors of treatment outcomes is necessary to optimize patient care. Here, we performed a prospective case-control study in which plasma levels of cytokines and lipid mediators were assessed at different time points during antileishmanial therapy in patients with CL from Brazil. Mul ...[more]

PMID: 33313489

Similar Datasets

Project description:Rationale: Children usually develop less severe symptoms responding to Coronavirus Disease 2019 (COVID-19) than adults. However, little is known about the molecular alterations and pathogenesis of COVID-19 in children. Methods: We conducted plasma proteomic and metabolomic profilings of the blood samples of a cohort containing 18 COVID-19-children with mild symptoms and 12 healthy children, which were enrolled from hospital admissions and outpatients, respectively. Statistical analyses were performed to identify molecules specifically altered in COVID-19-children. We also developed a machine learning-based pipeline named inference of biomolecular combinations with minimal bias (iBM) to prioritize proteins and metabolites strongly altered in COVID-19-children, and experimentally validated the predictions. Results: By comparing to the multi-omic data in adults, we identified 44 proteins and 249 metabolites differentially altered in COVID-19-children against healthy children or COVID-19-adults. Further analyses demonstrated that both deteriorative immune response/inflammation processes and protective antioxidant or anti-inflammatory processes were markedly induced in COVID-19-children. Using iBM, we prioritized two combinations that contained 5 proteins and 5 metabolites, respectively, each exhibiting a total area under curve (AUC) value of 100% to accurately distinguish COVID-19-children from healthy children or COVID-19-adults. Further experiments validated that all the 5 proteins were up-regulated upon coronavirus infection. Interestingly, we found that the prioritized metabolites inhibited the expression of pro-inflammatory factors, and two of them, methylmalonic acid (MMA) and mannitol, also suppressed coronaviral replication, implying a protective role of these metabolites in COVID-19-children. Conclusion: The finding of a strong antagonism of deteriorative and protective effects provided new insights on the mechanism and pathogenesis of COVID-19 in children that mostly underwent mild symptoms. The identified metabolites strongly altered in COVID-19-children could serve as potential therapeutic agents of COVID-19.

Dataset Information

Multi-omic Analyses of Plasma Cytokines, Lipidomics, and Transcriptomics Distinguish Treatment Outcomes in Cutaneous Leishmaniasis.

Publications

Multi-omic Analyses of Plasma Cytokines, Lipidomics, and Transcriptomics Distinguish Treatment Outcomes in Cutaneous Leishmaniasis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure