Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019

Liu, Hui; Lin, Shu‐Fang; Ao, Xiulan; Gong, Xin; Liu, Chunyun; De-sheng, XU; Huang, Yumei; Liu, Zhiqiang; Zhao, Bixing; Liu, Xiaolong; Xiao, Han; Ye, Hanhui

doi:10.1016/j.csbj.2020.12.010

Cited by 6 publications

(4 citation statements)

References 45 publications

(34 reference statements)

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“…Rhodiola rosea L. (Golden root) has great immunoregulatory action and attenuates inflammatory harm since it regulates the differentiation of immune cells, activates inflammatory signaling pathways and secretes inflammatory factors [ 38 ]. Andrographis paniculata (Bitter weed) inhibits the augmented NOD-like receptor protein 3 (NLRP3), caspase-1 and interleukin-1β (IL-1β) particles which are strongly implicated in SARS-CoV [ 39 ].…”

Section: Medicinal Plants and Their Metabolites Used In Case Of Covid-19mentioning

confidence: 99%

Role of Diet and Nutrients in SARS-CoV-2 Infection: Incidence on Oxidative Stress, Inflammatory Status and Viral Production

et al. 2022

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Coronavirus illness (COVID-19) is an infectious pathology generated by intense severe respiratory syndrome coronavirus 2 (SARS-CoV-2). This infectious disease has emerged in 2019. The COVID-19-associated pandemic has considerably affected the way of life and the economy in the world. It is consequently crucial to find solutions allowing remedying or alleviating the effects of this infectious disease. Natural products have been in perpetual application from immemorial time given that they are attested to be efficient towards several illnesses without major side effects. Various studies have shown that plant extracts or purified molecules have a promising inhibiting impact towards coronavirus. In addition, it is substantial to understand the characteristics, susceptibility and impact of diet on patients infected with COVID-19. In this review, we recapitulate the influence of extracts or pure molecules from medicinal plants on COVID-19. We approach the possibilities of plant treatment/co-treatment and feeding applied to COVID-19. We also show coronavirus susceptibility and complications associated with nutrient deficiencies and then discuss the major food groups efficient on COVID-19 pathogenesis. Then, we covered emerging technologies using plant-based SARS-CoV-2 vaccine. We conclude by giving nutrient and plants curative therapy recommendations which are of potential interest in the COVID-19 infection and could pave the way for pharmacological treatments or co-treatments of COVID-19.

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Section: Medicinal Plants and Their Metabolites Used In Case Of Covid-19mentioning

confidence: 99%

Role of Diet and Nutrients in SARS-CoV-2 Infection: Incidence on Oxidative Stress, Inflammatory Status and Viral Production

et al. 2022

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“…During SARS-CoV-2 infection, glycolysis-associated genes are upregulated in monocytes of patients [176] , such as 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) [193] , [194] . In addition to this, the replication of SARS-CoV-2 is supported and maintained when the switch from OXPHOS to aerobic glycolysis occurs [176] .…”

Section: Immunological Responses In Covid-19mentioning

confidence: 99%

Drug delivery systems as immunomodulators for therapy of infectious disease: Relevance to COVID-19

Brain

Plant-Hately

Heaton

et al. 2021

Advanced Drug Delivery Reviews

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“…Therefore, several approaches for meta-analysis of transcriptome expression studies have been considered in order to achieve increased power and thus increased scientific evidence of findings [ 31 , 41 , 53 ]. In the context of infectious diseases, such methods have for example been applied for meta-analysis of transcriptome expression data from West Nile virus infected [ 20 ] or SARS-CoV2 infected samples [ 28 ]. Furthermore, meta-analysis can increase the reproducibility of gene expression analysis [ 49 ], and can increase the generalizability of results when data is taken from a variety of sources [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Network meta-analysis of transcriptome expression changes in different manifestations of dengue virus infection

et al. 2022

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Background Several studies have been performed to study transcriptome profiles after dengue virus infections with partly different results. Due to slightly different settings of the individual studies, different genes and enriched gene sets are reported in these studies. The main aim of this network meta-analysis was to aggregate a selection of these studies to identify genes and gene sets that are more generally associated with dengue virus infection, i.e. with less dependence on the individual study settings. Methods We performed network meta-analysis by different approaches using publicly available gene expression data of five selected studies from the Gene Expression Omnibus database. The study network includes dengue fever (DF), hemorrhagic fever (DHF), shock syndrome (DSS) patients as well as convalescent and healthy control individuals. After data merging and missing value imputation, study-specific batch effects were removed. Pairwise differential expression analysis and subsequent gene-set enrichment analysis were performed between the five study groups. Furthermore, mutual information networks were derived from the top genes of each group comparison, and the separability between the three patient groups was studied by machine learning models. Results From the 10 possible pairwise group comparisons in the study network, six genes (IFI27, TPX2, CDT1, DTL, KCTD14 and CDCA3) occur with a noticeable frequency among the top listed genes of each comparison. Thus, there is an increased evidence that these genes play a general role in dengue virus infections. IFI27 and TPX2 have also been highlighted in the context of dengue virus infection by other studies. A few of the identified gene sets from the network meta-analysis overlap with findings from the original studies. Mutual information networks yield additional genes for which the observed pairwise correlation is different between the patient groups. Machine learning analysis shows a moderate separability of samples from the DF, DHF and DSS groups (accuracy about 80%). Conclusions Due to an increased sample size, the network meta-analysis could reveal additional genes which are called differentially expressed between the studied groups and that may help to better understand the molecular basis of this disease.

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Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019

Cited by 6 publications

References 45 publications

Role of Diet and Nutrients in SARS-CoV-2 Infection: Incidence on Oxidative Stress, Inflammatory Status and Viral Production

Role of Diet and Nutrients in SARS-CoV-2 Infection: Incidence on Oxidative Stress, Inflammatory Status and Viral Production

Drug delivery systems as immunomodulators for therapy of infectious disease: Relevance to COVID-19

Network meta-analysis of transcriptome expression changes in different manifestations of dengue virus infection

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