Small molecule metabolites: discovery of biomarkers and therapeutic targets.

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Exploring Potential Biomarkers and Molecular Mechanisms of Ischemic Cardiomyopathy and COVID-19 Comorbidity Based on Bioinformatics and Systems Biology.

Cardiovascular complications combined with COVID-19 (SARS-CoV-2) lead to a poor prognosis in patients. The common pathogenesis of ischemic cardiomyopathy (ICM) and COVID-19 is still unclear. Here, we explored potential molecular mechanisms and biomarkers for ICM and COVID-19. Common differentially expressed genes (DEGs) of ICM (GSE5406) and COVID-19 (GSE164805) were identified using GEO2R. We performed enrichment and protein-protein interaction analyses and screened key genes. To confirm the diagnostic performance for these hub genes, we used external datasets (GSE116250 and GSE211979) and plotted ROC curves. Transcription factor and microRNA regulatory networks were constructed for the validated hub genes. Finally, drug prediction and molecular docking validation were performed using cMAP. We identified 81 common DEGs, many of which were enriched in terms of their relation to angiogenesis. Three DEGs were identified as key hub genes (HSP90AA1, HSPA9, and SRSF1) in the protein-protein interaction analysis. These hub genes had high diagnostic performance in the four datasets (AUC > 0.7). Mir-16-5p and KLF9 transcription factor co-regulated these hub genes. The drugs vindesine and ON-01910 showed good binding performance to the hub genes. We identified HSP90AA1, HSPA9, and SRSF1 as markers for the co-pathogenesis of ICM and COVID-19, and showed that co-pathogenesis of ICM and COVID-19 may be related to angiogenesis. Vindesine and ON-01910 were predicted as potential therapeutic agents. Our findings will contribute to a deeper understanding of the comorbidity of ICM with COVID-19.

Efficacy and safety of mesenchymal stem cells for the treatment of patients infected with COVID-19: a systematic review and meta-analysis protocol.

INTRODUCTION: To date, no specific antivirus drugs or vaccines have been available to prevent or treat the COVID-19 pandemic. Mesenchymal stem cell (MSC) therapy may be a promising therapeutic approach that reduces the high mortality in critical cases. This protocol is proposed for a systematic review and meta-analysis that aims to evaluate the efficacy and safety of MSC therapy on patients with COVID-19. METHODS AND ANALYSIS: Ten databases including PubMed, EMBASE, Cochrane Library, CINAHL, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database (VIP), Wanfang database, China Biomedical Literature Database (CBM) and Chinese Biomedical Literature Service System (SinoMed) will be searched from inception to 1 December 2020. All published randomised controlled trials, clinical controlled trials and case series that meet the prespecified eligibility criteria will be included. The primary outcomes include mortality, incidence and severity of adverse events, respiratory improvement, days from ventilator, duration of fever, progression rate from mild or moderate to severe, improvement of such serious symptoms as difficulty breathing or shortness of breath, chest pain or pressure, and loss of speech or movement, biomarkers of laboratory examination and changes in CT. The secondary outcomes include dexamethasone doses and quality of life. Two reviewers will independently perform study selection, data extraction and assessment of bias risk. Data synthesis will be conducted using RevMan software (V.5.3.5). If necessary, subgroup and sensitivity analysis will be performed. Grading of Recommendations Assessment, Development and Evaluation system will be used to assess the strength of evidence. ETHICS AND DISSEMINATION: Ethical approval is not necessary since no individual patient or privacy data have been collected. The results of this review will be disseminated in a peer-reviewed journal or an academic conference presentation. PROSPERO REGISTRATION NUMBER: CRD42020190079.

Efficacy of integrative Traditional Chinese and Western medicine for the treatment of patients infected with 2019 novel coronavirus (COVID-19): A protocol for systematic review and meta analysis.

BACKGROUND: No specific anti-virus drugs or vaccines have been available for the treatment of COVID-19. Integrative traditional Chinese and western medicine has been proposed as a therapeutic option with substantial applications in China. This protocol is proposed for a systematic review and meta-analysis that aims to evaluate the efficacy of integrative traditional Chinese and western medicine treatment on patients with COVID-19. METHODS: Ten databases including PubMed, EMBASE, Cochrane Library, CIHAHL, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database (VIP), Wanfang database, China Biomedical Literature Database (CBM) and Chinese Biomedical Literature Service System (SinoMed) will be searched. All published randomized controlled trials, clinical controlled trials, case-control, and case series that meet the pre-specified eligibility criteria will be included. Primary outcome measures include mortality, clinical recovery rate, duration of fever, progression rate from mild or moderate to severe, improvement of symptoms, biomarkers of laboratory examination and changes in computed tomography. Secondary outcomes include dosage of hormonotherapy, incidence and severity of adverse events and quality of life. Study selection, data extraction and assessment of bias risk will be conducted by 2 reviewers independently. RevMan software (V.5.3.5) will be used to perform data synthesis. Subgroup and sensitivity analysis will be performed when necessary. The strength of evidence will be assessed by the GRADE system. RESULTS: This study will provide a well-reported and high-quality synthesis on the efficacy of integrative traditional Chinese and western medicine treatment on patients with COVID-19. CONCLUSION: This systematic review protocol will be helpful for providing evidence of whether integrative traditional Chinese and western medicine treatment is an effective therapeutic approach for patients with COVID-19. ETHICS AND DISSEMINATION: Ethical approval is unnecessary as no individual patient or privacy data is collected. The results of this study will be disseminated in a peer-reviewed scientific journal and/or conference presentation. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020167205.