Network meta-analysis correlates with analysis of merged independent transcriptome expression data

Winter, Christine; Kosch, Robin; Ludlow, Martin; Osterhaus, Albert D. M. E.; Jung, Klaus

doi:10.1186/s12859-019-2705-9

Cited by 13 publications

(11 citation statements)

References 54 publications

(58 reference statements)

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“…We employed a network meta-analysis, which is widely used for aggregating results of clinical trials to make direct and indirect inferences about treatment effects. In contrast to traditional meta-analyses, which aggregate studies on the same study question, network meta-analyses also involve studies on different study questions which are linked by pairwise same-treatment groups [ 69 ]. Others share the limitations of the original studies.…”

Section: Discussionmentioning

confidence: 99%

Mitochondrial Consequences of Organ Preservation Techniques during Liver Transplantation

Horváth¹,

Jász²,

Baráth³

et al. 2021

IJMS

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Allograft ischemia during liver transplantation (LT) adversely affects the function of mitochondria, resulting in impairment of oxidative phosphorylation and compromised post-transplant recovery of the affected organ. Several preservation methods have been developed to improve donor organ quality; however, their effects on mitochondrial functions have not yet been compared. This study aimed to summarize the available data on mitochondrial effects of graft preservation methods in preclinical models of LT. Furthermore, a network meta-analysis was conducted to determine if any of these treatments provide a superior benefit, suggesting that they might be used on humans. A systematic search was conducted using electronic databases (EMBASE, MEDLINE (via PubMed), the Cochrane Central Register of Controlled Trials (CENTRAL) and Web of Science) for controlled animal studies using preservation methods for LT. The ATP content of the graft was the primary outcome, as this is an indicator overall mitochondrial function. Secondary outcomes were the respiratory activity of mitochondrial complexes, cytochrome c and aspartate aminotransferase (ALT) release. Both a random-effects model and the SYRCLE risk of bias analysis for animal studies were used. After a comprehensive search of the databases, 25 studies were enrolled in the analysis. Treatments that had the most significant protective effect on ATP content included hypothermic and subnormothermic machine perfusion (HMP and SNMP) (MD = −1.0, 95% CI: (−2.3, 0.3) and MD = −1.1, 95% CI: (−3.2, 1.02)), while the effects of warm ischemia (WI) without cold storage (WI) and normothermic machine perfusion (NMP) were less pronounced (MD = −1.8, 95% CI: (−2.9, −0.7) and MD = −2.1 MD; CI: (−4.6; 0.4)). The subgroup of static cold storage (SCS) with shorter preservation time (< 12 h) yielded better results than SCS ≥ 12 h, NMP and WI, in terms of ATP preservation and the respiratory capacity of complexes. HMP and SNMP stand out in terms of mitochondrial protection when compared to other treatments for LT in animals. The shorter storage time at lower temperatures, together with the dynamic preservation, provided superior protection for the grafts in terms of mitochondrial function. Additional clinical studies on human patients including marginal donors and longer ischemia times are needed to confirm any superiority of preservation methods with respect to mitochondrial function.

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Section: Discussionmentioning

confidence: 99%

Mitochondrial Consequences of Organ Preservation Techniques during Liver Transplantation

Horváth¹,

Jász²,

Baráth³

et al. 2021

IJMS

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“…Recently, a framework was published for partitioning the variation in gene expression due to a variety of molecular variables, including somatic mutations, transcription factors, microRNAs, copy number alternations, methylation and germ-line genetic variation [23]. Meta-analysis allows for expression data from various public repositories to be merged in order to make group comparisons that have not been considered before [24]. Recently, a web-based application was published which can be used to download, collect and manage gene expression data from public databases [25].…”

Section: Gene-expression Datamentioning

confidence: 99%

Open Data for Differential Network Analysis in Glioma

Jean-Quartier¹,

Jeanquartier²,

Holzinger³

2020

IJMS

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The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. By using selected exemplary tools and open-access resources for cancer research and differential network analysis, we highlight disturbed signaling components in brain cancer subtypes of glioma.

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“…To further explore whether polymorphisms in these four SNPs might predispose to HCC, additional research and quantitative statistical studies are required to resolve discrepancies ( 27 ). Network meta-analyses (NMA) can be used to summarize and compare studies on multiple interventions ( 28 ), and combine direct and indirect evidence thus produce a result more precise ( 29 ). We conducted this systematic review with a network meta-analysis to provide more comprehensive information on the polymorphisms of four selected miRNAs and their involvement in HCC susceptibility and interaction with HBV.…”

Section: Introductionmentioning

confidence: 99%

MiRNA Polymorphisms and Hepatocellular Carcinoma Susceptibility: A Systematic Review and Network Meta-Analysis

Zhang

et al. 2021

Front. Oncol.

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BackgroundHepatocellular carcinoma (HCC) is an intractable public health threat worldwide, representing the second leading cause of cancer-related mortality, with limited early detection and therapeutic options. Recent findings have revealed that the susceptibility of HCC is closely related to microRNA (miRNA). We performed this systematic review with a network meta-analysis to investigated four single nucleotide polymorphisms (SNPs) that most regularly reported in miRNAs, exploring their involvement in HCC susceptibility and interaction with hepatitis B virus (HBV).MethodsDatabases were reviewed for related studies published up to May 2019 to identify all studies that compared genotypes of miR-146a rs2910164, miR-149 rs2292832, miR-196a2 rs11614913, and miR-499 rs3746444 with no language and date restrictions. A pairwise meta-analysis was performed to estimate pooled odds ratios and 95% confidence intervals incorporating heterogeneity to assess the relationship between four miRNA polymorphisms and HCC. To further clarify the effect of polymorphisms on HCC, a Bayesian network meta-analysis was conducted to combine the effective sizes of direct and indirect comparisons. Calculations were performed by R version 3.6.1 and STATA 14.0. All steps were performed according to PRISMA guidelines.ResultsA total of 20 studies were enrolled in this network meta-analysis, providing 5,337 hepatocellular carcinoma cases and 6,585 controls. All included studies had an acceptable quality. Pairwise meta-analysis demonstrated that miR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, while the other three SNPs were not found to have a significant association. In the analysis of HCC patients under different HBV infection status, only miR-196a2 revealed correlation of threefold risk. The network results showed no significant difference in the distribution of genotype frequencies except for miR-196a2, which appeared to have the highest superiority index when comparing and ranking four SNPs.ConclusionMiR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, especially for HBV- related HCC, and that individuals with TC/CC were more susceptible. No significant association was found in the other three miRNA genes. MiR-196a2 could serve as the best predictor of susceptibility in HCC.

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Network meta-analysis correlates with analysis of merged independent transcriptome expression data

Cited by 13 publications

References 54 publications

Mitochondrial Consequences of Organ Preservation Techniques during Liver Transplantation

Mitochondrial Consequences of Organ Preservation Techniques during Liver Transplantation

Open Data for Differential Network Analysis in Glioma

MiRNA Polymorphisms and Hepatocellular Carcinoma Susceptibility: A Systematic Review and Network Meta-Analysis

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