Dataset Information

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19

ABSTRACT: In March 2020, we performed a multicenter, randomized, double-blind phase II study of mesenchymal stem cells (MSCs) therapy in patients with severe COVID-19 (ClinicalTrials.gov: NCT04288102). Findings showed that MSC was a potentially effective therapeutic approach for patients with severe COVID-19, but not all patients responded well. To further understand the proteomic biomarkers of response to MSC therapy in patients with severe COVID-19, we characterize the proteomic profile of 58 patient pre-MSC treatment plasma samples (35 responders versus 23 non-responders) by using proteomics assays. The project aims to identify potential biomarkers for predicting response to MSC therapy by pre-MSC treatment plasma proteomic profile in severe COVID-19.

ORGANISM(S): Homo Sapiens

SUBMITTER: Fusheng Wang

PROVIDER: PXD042106 | iProX | Wed May 10 00:00:00 BST 2023

REPOSITORIES: iProX

ACCESS DATA

Publications

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19.

Li Tian-Tian TT Yao Wei-Qi WQ Dong Hai-Bo HB Wang Ze-Rui ZR Zhang Zi-Ying ZY Yuan Meng-Qi MQ Shi Lei L Wang Fu-Sheng FS

Stem cell research & therapy 20231210 1

<h4>Background</h4>The objective of this study was to identify potential biomarkers for predicting response to MSC therapy by pre-MSC treatment plasma proteomic profile in severe COVID-19 in order to optimize treatment choice.<h4>Methods</h4>A total of 58 patients selected from our previous RCT cohort were enrolled in this study. MSC responders (n = 35) were defined as whose resolution of lung consolidation ≥ 51.99% (the median value for resolution of lung consolidation) from pre-MSC to 28 days ...[more]

PMID: 38072927

Similar Datasets

Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.

Dataset Information

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19

Publications

Plasma proteomics-based biomarkers for predicting response to mesenchymal stem cell therapy in severe COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets