Independent validation test of the vote-counting strategy used to rank biomarkers from published studies

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Alterations of the gut microbiota in patients with schizophrenia

Introduction

Schizophrenia is a complex psychiatric disorder, of which molecular pathogenesis remains largely unknown. Accumulating evidence suggest that gut microbiota may affect brain function via the complex gut-brain axis, which may be a potential contributor to schizophrenia. However, the alteration of gut microbiota showed high heterogeneity across different studies. Therefore, this study aims to identify the consistently altered gut microbial taxa associated with schizophrenia.

Methods

We conducted a systematic search and synthesis of the up-to-date human gut microbiome studies on schizophrenia, and performed vote counting analyses to identify consistently changed microbiota. Further, we investigated the effects of potential confounders on the alteration of gut microbiota.

Results

We obtained 30 available clinical studies, and found that there was no strong evidence to support significant differences in α-diversity and β-diversity between schizophrenic patients and healthy controls. Among 428 differential gut microbial taxa collected from original studies, we found that 8 gut microbial taxa were consistently up-regulated in schizophrenic patients, including Proteobacteria, Gammaproteobacteria, Lactobacillaceae, Enterobacteriaceae, Lactobacillus, Succinivibrio, Prevotella and Acidaminococcus. While 5 taxa were consistently down-regulated in schizophrenia, including Fusicatenibacter, Faecalibacterium, Roseburia, Coprococcus and Anaerostipes.

Discussion

These findings suggested that gut microbial changes in patients with schizophrenia were characterized by the depletion of anti-inflammatory butyrate-producing genera, and the enrichment of certain opportunistic bacteria genera and probiotics. This study contributes to further understanding the role of gut microbiota in schizophrenia, and developing microbiota-based diagnosis and therapy for schizophrenia.

Pattern of Expression of MicroRNA in Patients with Radiation-Induced Bladder Injury

INTRODUCTION

Bladder cancer (BC) is sensitive to radiation treatment and a subset of patients experience radiation-induced injuries including shrinkage of bladder due to bladder fibrosis.

METHODS

This study is a retrospective cohort study. Three Japanese BC patients were randomly selected. Using a microRNA (miRNA) array, comparing their samples with or without radiation-induced injuries, we have checked the clustering of miRNA expression.

RESULTS

Hsa-miR-130a, hsa-miR-200c, hsa-miR-141, and hsa-miR-96 were found to be highly expressed (>50 times) in patients with fibrotic bladder shrinkage (FBS) compared to those with intact bladder (IB) function. In patients with FBS, hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 were detected to have lesser than half expression to IB patients. We have analyzed the significance of these genes in relation to overall survival of 409 BC patients retrieved from the Cancer Genome Atlas data set. All available cutoff values between the lower and upper quartiles of expression are used for the selected genes, and false discovery rate using the Benjamini-Hochberg method is computed to correct for multiple hypothesis testing. We have run combined survival analysis of the mean expression of these four miRNAs highly expressed in FBS patients. 175 patients with high expression had a longer median survival of 98.47 months than 23.73 months in 233 patients with low expression (hazard ratio [HR]: 0.53; 0.39-0.72, log-rank p value: 7.3e-0.5). Combination analysis of all 8 genes including hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 showed the same HR for OS. Target scanning for these miRNAs matched specific cytokines known as an early biomarker to develop radiation-induced fibrosis.

CONCLUSIONS

BC patients with fibrotic radiation injury have specific miRNA expression profile targeting profibrotic cytokines and these miRNAs possibly render to favorable survival.

Metabolic signature for a dysbiotic microbiome in the female genital tract: A systematic review and meta-analysis

BACKGROUND

The vaginal microbiome (VMB) is a critical determinant of reproductive health, where a microbial shift towards a dysbiotic environment has implications for susceptibility to, and clinical presentation of sexually transmitted infections (STIs). Metabolomic profiling of the vaginal microenvironment has led to the identification of metabolic responses to clinical conditions of dysbiosis. However, no studies have examined metabolic markers that are common across conditions and can serve as a signature for vaginal dysbiosis.

METHOD OF STUDY

We have conducted a comprehensive systematic review and meta-analysis to identify consistently deregulated metabolites along with their impact on host and microbial metabolism during dysbiosis. We employed two complementary approaches including a vote counting analysis for all eligible studies identified in the systematic review, in addition to a meta-analysis for a subset of studies with sufficient available data. Significantly deregulated metabolites were then selected for pathway enrichment analysis.

RESULTS

Our results revealed a total of 502 altered metabolites reported across 10 dysbiotic conditions from 16 studies. Following a rigorous, collective analysis, six metabolites which were consistently downregulated and could be generalized to all dysbiotic conditions were identified. In addition, five downregulated and one upregulated metabolite was identified from a bacterial vaginosis (BV) focused sub-analysis. These metabolites have the potential to serve as a metabolic signature for vaginal dysbiosis. Their role in eight altered metabolic pathways indicates a disruption of amino acid, carbohydrate, and energy metabolism during dysbiosis.

CONCLUSION

Based on this analysis, we propose a schematic model outlining the common metabolic perturbations associated with vaginal dysbiosis, which can be potential targets for therapeutics and prophylaxis.

Altered neurometabolite levels in the brains of patients with depression: A systematic analysis of magnetic resonance spectroscopy studies

BACKGROUND

Numerous magnetic resonance spectroscopy (MRS) studies have reported metabolic abnormalities in the brains of patients with depression, although inconsistent results have been reported. The aim of this study was to explore changes in neurometabolite levels in patients with depression across large-scale MRS studies.

METHOD

A total of 307 differential metabolite entries associated with depression were retrieved from 180 MRS studies retrieved from the Metabolite Network of Depression Database. The vote-counting method was used to identify consistently altered metabolites in the whole brain and specific brain regions of patients with depression.

RESULTS

Only few differential neurometabolites showed a stable change trend. The levels of total choline (tCho) and the tCho/N-acetyl aspartate (NAA) ratio were consistently higher in the brains of patients with depression, and that the levels of NAA, glutamate and glutamine (Glx), and gamma-aminobutyric acid (GABA) were lower. For specific brain regions, we found lower Glx levels in the prefrontal cortex and lower GABA concentrations in the occipital cortex. We also found lower concentrations of NAA in the anterior cingulate cortex and prefrontal cortex. The levels of tCho were higher in the prefrontal cortex and putamen.

CONCLUSION

Our results revealed that most altered neurometabolites in previous studies lack of adequate reproducibility. Through vote-counting method with large-scale studies, downregulation of glutamatergic neurometabolites, impaired neuronal integrity, and disturbed membrane metabolism were found in the pathobiology of depression, which contribute to existing knowledge of neurometabolic changes in depression. Further studies based on a larger dataset are needed to confirm our findings.

Benefits of Participation in Clinical Trials: An Umbrella Review

Participation in randomised clinical trials (RCTs) entails taking part in the discovery of effects of health care interventions. The question of whether participants' outcomes are different to those of non-participants remains controversial. This umbrella review was aimed at assessing whether there are health benefits of participation in RCTs, compared to non-participation. After prospective registration (PROSPERO CRD42021287812), we searched the Medline, Scopus, Web of Science and Cochrane Library databases from inception to June 2022 to identify relevant systematic reviews with or without meta-analyses. Data extraction and study quality assessment (AMSTAR-2) were performed by two independent reviewers. Of 914 records, six systematic reviews summarising 380 comparisons of RCT participants with non-participants met the inclusion criteria. In two reviews, the majority of comparisons were in favour of participation in RCTs. Of the total of comparisons, 69 (18.7%) were in favour of participation, reporting statistically significant better outcomes for patients treated within RCTs, 264 (71.7%) comparisons were not statistically significant, and 35 (9.5%) comparisons were in favour of non-participation. None of the reviews found a harmful effect of participation in RCTs. Our findings suggest that taking part in RCTs may be beneficial compared to non-participation.

Discovery of Synergistic Drug Combinations for Colorectal Cancer Driven by Tumor Barcode Derived from Metabolomics “Big Data”

The accumulation of cancer metabolomics data in the past decade provides exceptional opportunities for deeper investigations into cancer metabolism. However, integrating a large amount of heterogeneous metabolomics data to draw a full picture of the metabolic reprogramming and to discover oncometabolites of certain cancers remains challenging. In this study, a tumor barcode constructed based upon existing metabolomics “big data” using the Bayesian vote-counting method is proposed to identify oncometabolites in colorectal cancer (CRC). Specifically, a panel of oncometabolites of CRC was generated from 39 clinical studies with 3202 blood samples (1332 CRC vs. 1870 controls) and 990 tissue samples (495 CRC vs. 495 controls). Next, an oncometabolite-protein network was constructed by combining the tumor barcode and its involved proteins/enzymes. The effect of anti-cancer drugs or drug combinations was then mapped into this network by the random walk with restart process. Utilizing this network, potential Irinotecan (CPT-11)-sensitizing agents for CRC treatment were discovered by random forest and Xgboost. Finally, a compound named MK-2206 was highlighted and its synergy with CPT-11 was validated on two CRC cell lines. To summarize, we demonstrate in the present study that the metabolomics “big data”-based tumor barcodes and the subsequent network analyses are potentially useful for drug combination discovery or drug repositioning.

Effects of pharmacological treatment on metabolomic alterations in animal models of depression

Numerous studies have investigated metabolite alterations resulting from pharmacological treatment in depression models although few quantitative studies explored metabolites exhibiting constant alterations. This study aimed to identify consistently dysregulated metabolites across such studies using a knowledgebase-driven approach. This study was based on 157 studies that identified an assembly of 2757 differential metabolites in the brain, blood, urine, liver, and feces samples of depression models with pharmacological medication. The use of a vote-counting approach to identify consistently upregulated and downregulated metabolites showed that serotonin, dopamine, norepinephrine, gamma-aminobutyric acid, anandamide, tryptophan, hypoxanthine, and 3-methoxytyramine were upregulated in the brain, while quinolinic acid, glutamic acid, 5-hydroxyindoleacetic acid, myo-inositol, lactic acid, and the kynurenine/tryptophan ratio were downregulated. Circulating levels of trimethylamine N-oxide, isoleucine, leucine, tryptophan, creatine, serotonin, valine, betaine, and low-density lipoprotein were elevated. In contrast, levels of alpha-D-glucose, lactic acid, N-acetyl glycoprotein, glutamine, beta-D-glucose, corticosterone, alanine, phenylacetylglycine, glycine, high-density lipoprotein, arachidonic acid, myo-inositol, allantoin, and taurine were decreased. Moreover, 12 metabolites in urine and nine metabolites in the liver were dysregulated after treatment. Pharmacological treatment also increased fecal levels of butyric acid, acetic acid, propionic acid, and isovaleric acid. Collectively, metabolite disturbances induced by depression were reversed by pharmacological treatment. Pharmacological medication reversed the reduction of brain neurotransmitters caused by depression, modulated disturbance of the tryptophan-kynurenine pathway and inflammatory activation, and alleviated abnormalities of amino acid metabolism, energy metabolism, lipid metabolism, and gut microbiota-derived metabolites.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology’s potential, a set of transcriptomic datasets are meta-analyzed as an example.

Effect of gut microbiota modulation on feeding tolerance of enterally fed critically ill adult patients: a systematic review

PURPOSE

The objective of this systematic review was to evaluate the effect of pre-, pro-, and synbiotics on feeding tolerance of enterally fed critically ill adult patients.

METHODS

MEDLINE, Science Direct, Web of Knowledge, and the Cochrane Central Register of Controlled Trials were searched up to November 2019. English language randomized controlled trials reporting the effect of pre, pro or synbiotics on the feeding tolerance of enterally fed critically ill adult patients were included.

RESULTS

Overall, 15 papers were selected for review. Among six studies reporting the energy intake, only two studies showed significantly higher energy intake in the prebiotic-receiving groups. Among four RCTs reporting frequency or time to achieve the target calorie, only one found a significant effect of probiotics to reduce the time to achieve a target dose of calorie. About the prevalence or duration of diarrhea, 7 out of 12 RCTs reported a beneficial effect. All but one study found no beneficial effects for gut microbiota manipulation on clinical endpoints including length of stay (LOS) in hospital and intensive care unit (ICU).

CONCLUSION

It should be noticed that the heterogeneity in study designs, product format, and ICU patient populations makes it difficult to draw any general conclusion. Overall, it seems that pre, pro, or synbiotics have no significant beneficial effect on feeding tolerance and clinical endpoints in critically ill adults, but they may reduce the prevalence or duration of diarrhea.

A meta-analysis of microRNA expression profiling studies in heart failure

Heart failure (HF) is a major consequence of many cardiovascular diseases with high rate of morbidity and mortality. Early diagnosis and prevention are hampered by the lack of informative biomarkers. The aim of this study was to perform a meta-analysis of the miRNA expression profiling studies in HF to identify novel candidate biomarkers or/and therapeutic targets. A comprehensive literature search of the PubMed for miRNA expression studies related to HF was carried out. The vote counting and robust rank aggregation meta-analysis methods were used to identify significant meta-signatures of HF-miRs. The targets of HF-miRs were identified, and network construction and gene set enrichment analysis (GSEA) were performed to identify the genes and cognitive pathways most affected by the dysregulation of the miRNAs. The literature search identified forty-five miRNA expression studies related to CHF. Shared meta-signature was identified for 3 up-regulated (miR-21, miR-214, and miR-27b) and 13 down-regulated (miR-133a, miR-29a, miR-29b, miR-451, miR-185, miR-133b, miR-30e, miR-30b, miR-1, miR-150, miR-486, miR-149, and miR-16-5p) miRNAs. Network properties showed miR-29a, miR-21, miR-29b, miR-1, miR-16, miR-133a, and miR-133b have the most degree centrality. GESA identified functionally related sets of genes in signaling and community pathways in HF that are the targets of HF-miRs. The miRNA expression meta-analysis identified sixteen highly significant HF-miRs that are differentially expressed in HF. Further validation in large patient cohorts is required to confirm the significance of these miRs as HF biomarkers and therapeutic targets.

Metabolomic changes in animal models of depression: a systematic analysis

Extensive research has been carried out on the metabolomic changes in animal models of depression; however, there is no general agreement about which metabolites exhibit constant changes. Therefore, the aim of this study was to identify consistently altered metabolites in large-scale metabolomics studies of depression models. We performed vote counting analyses to identify consistently upregulated or downregulated metabolites in the brain, blood, and urine of animal models of depression based on 3743 differential metabolites from 241 animal metabolomics studies. We found that serotonin, dopamine, gamma-aminobutyric acid, norepinephrine, N-acetyl-L-aspartic acid, anandamide, and tryptophan were downregulated in the brain, while kynurenine, myo-inositol, hydroxykynurenine, and the kynurenine to tryptophan ratio were upregulated. Regarding blood metabolites, tryptophan, leucine, tyrosine, valine, trimethylamine N-oxide, proline, oleamide, pyruvic acid, and serotonin were downregulated, while N-acetyl glycoprotein, corticosterone, and glutamine were upregulated. Moreover, citric acid, oxoglutaric acid, proline, tryptophan, creatine, betaine, L-dopa, palmitic acid, and pimelic acid were downregulated, and hippuric acid was upregulated in urine. We also identified consistently altered metabolites in the hippocampus, prefrontal cortex, serum, and plasma. These findings suggested that metabolomic changes in depression models are characterized by decreased neurotransmitter and increased kynurenine metabolite levels in the brain, decreased amino acid and increased corticosterone levels in blood, and imbalanced energy metabolism and microbial metabolites in urine. This study contributes to existing knowledge of metabolomic changes in depression and revealed that the reproducibility of candidate metabolites was inadequate in previous studies.

Diagnostic value of microRNA panel in endometrial cancer: A systematic review

PURPOSE

We conducted a systematic review to evaluate the overall diagnostic accuracy of miRNAs in detecting endometrial cancer.

MATERIALS AND METHODS

A systematic search of Medline, Embase, Cinahl and the Cochrane Controlled Register of Trials was performed to identify studies reporting on the diagnostic value of miRNA in EC patients. Included were diagnostic studies looking at miRNA expression in women diagnosed with endometrial cancer. Two reviewers independently selected studies and assessed quality of studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) score system. Data extraction was completed and the vote-counting strategy was used to rank miRNAs.

RESULTS

26 studies were included with a total number of 1,400 EC patients reporting on 106 differentially expressed miRNAs. The most frequently found up-regulated miRNA was miR-205 followed by miR-200c, -223, -182, -183 and -200a. In addition, miR-135b, miR-429, miR-141 and miR-200b were also frequently up-regulated. There was less consensus on down-regulated miRNAs.

CONCLUSIONS

miRNAs yield a promising diagnostic biomarker potential in endometrial cancer, especially miR-205, the miR-200 family and miR-135b, -182, -183 and -223. However, no sufficient high quality data are available to draw hard conclusions. More research is needed to validate the diagnostic potential of these miRNAs in larger studies. In addition, the potential of urine as a non-invasive biofluid should be investigated in more detail.

Antibiotic therapy in neonates and impact on gut microbiota and antibiotic resistance development: a systematic review

Objectives

To systematically review the impact of antibiotic therapy in the neonatal period on changes in the gut microbiota and/or antibiotic resistance development.

Methods

Data sources were PubMed, Embase, Medline and the Cochrane Database, supplemented by manual searches of reference lists. Randomized controlled trials (RCTs) and observational studies were included if they provided data on different categories of antibiotic treatment (yes versus no, long versus short duration and/or broad- versus narrow-spectrum regimens) and subsequent changes in the gut microbiota and/or antibiotic resistance development. We evaluated risk of bias using the Cochrane Handbook, adapted to include observational studies. When appropriate, we used the vote-counting method to perform semi-quantitative meta-analyses. We applied the Grades of Recommendation, Assessment, Development and Evaluation approach to rate the quality of evidence (QoE). Study protocol registration: PROSPERO CRD42015026743.

Results

We included 48 studies, comprising 3 RCTs and 45 observational studies. Prolonged antibiotic treatment was associated with reduced gut microbial diversity in all three studies investigating this outcome (very low QoE). Antibiotic treatment was associated with reduced colonization rates of protective commensal anaerobic bacteria in four of five studies (very low QoE). However, all three categories of antibiotic treatment were associated with an increased risk of antibiotic resistance development, in particular MDR in Gram-negative bacteria, and we graded the QoE for these outcomes as moderate.

Conclusions

We are moderately confident that antibiotic treatment leads to antibiotic resistance development in neonates and it may also induce potentially disease-promoting gut microbiota alterations. Our findings emphasize the need to reduce unnecessary antibiotic treatment in neonates.

C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD)

The cardiovascular disease (C/VD) database is an integrated and clustered information resource that covers multi-omic studies (microRNA, genomics, proteomics and metabolomics) of cardiovascular-related traits with special emphasis on coronary artery disease (CAD). This resource was built by mining existing literature and public databases and thereafter manual biocuration was performed. To enable integration of omic data from distinct platforms and species, a specific ontology was applied to tie together and harmonise multi-level omic studies based on gene and protein clusters (CluSO) and mapping of orthologous genes (OMAP) across species. CAD continues to be a leading cause of death in the population worldwide, and it is generally thought to be an age-related disease. However, CAD incidence rates are now known to be highly influenced by environmental factors and interactions, in addition to genetic determinants. With the complexity of CAD aetiology, there is a difficulty in research studies to elucidate general elements compared to other cardiovascular diseases. Data from 92 studies, covering 13945 molecular entries (4353 unique molecules) is described, including data descriptors for experimental setup, study design, discovery-validation sample size and associated fold-changes of the differentially expressed molecular features (p-value<0.05). A dedicated interactive web interface, equipped with a multi-parametric search engine, data export and indexing menus are provided for a user-accessible browsing experience. The main aim of this work was the development of a data repository linking clinical information and molecular differential expression in several CVD-related traits from multi-omics studies (genomics, transcriptomics, proteomics and metabolomics). As an example case of how to query and identify data sets within the database framework and concomitantly demonstrate the database utility, we queried CAD-associated studies and performed a systems-level integrative analysis. URL: www.padb.org/cvd

Expression of atresia biomarkers in granulosa cells after ovarian stimulation in heifers

The use of younger gamete donors in dairy cattle genetic selection programs significantly accelerates genetic gains by decreasing the interval between generations. Ovarian stimulation (OS) and the practice of follicle-stimulating hormone (FSH) withdrawal, also known as coasting, are intensively used in pre-pubertal heifers without detrimental effects on subsequent reproductive performance but generally with lower embryo yields. However, recent data from embryo transfer programs showed similar embryo yields in younger and sexually mature animals but with a significant difference in the coasting period. The aim of the present study was to identify a set of granulosa cell biomarkers capable of distinguishing optimal follicle differentiation from late differentiation and atresia in order to assess the differences in coasting dynamics between pre- and post-pubertal donors. We integrated transcriptomic data sets from a public depository and used vote counting meta-analysis in order to elucidate the molecular changes occurring in granulosa cells during late follicle differentiation and atresia. The meta-analysis revealed the gene expression associated with follicle demise, and most importantly, identified potential biomarkers of that status in bovine granulosa cells. The comparison of the expression of six biomarkers between pre- and post-pubertal donors revealed that younger donors had more signs of atresia after the same period of coasting. We found different follicular dynamics following coasting in younger donors. It is possible that younger donors are less capable to sustain follicular survival most likely due to insufficient luteinizing hormone signaling. In summary, the pre-pubertal status influences follicular dynamics and reduces the oocyte developmental competence curve following OS and FSH withdrawal in heifers.

A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder

Introduction and Objectives

MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB.

Methods

To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients' samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups.

Results

Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p < 0.001).

Conclusions

The miRNA array identified nine dysregulated miRNAs from clinical samples. This panel of nine-miRNA signature provides predictive and prognostic value of patients with UCB.

MicroRNA meta-signature of oral cancer: evidence from a meta-analysis

AIM

It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients.

MATERIAL AND METHODS

Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis.

RESULTS

Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling.

CONCLUSIONS

The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.

Diagnostic value of microRNAs in asbestos exposure and malignant mesothelioma: systematic review and qualitative meta-analysis

Background

Asbestos is a harmful and exceptionally persistent natural material. Malignant mesothelioma (MM), an asbestos-related disease, is an insidious, lethal cancer that is poorly responsive to current treatments. Minimally invasive, specific, and sensitive biomarkers providing early and effective diagnosis in high-risk patients are urgently needed. MicroRNAs (miRNAs, miRs) are endogenous, non-coding, small RNAs with established diagnostic value in cancer and pollution exposure. A systematic review and a qualitative meta-analysis were conducted to identify high-confidence miRNAs that can serve as biomarkers of asbestos exposure and MM.

Methods

The major biomedical databases were systematically searched for miRNA expression signatures related to asbestos exposure and MM. The qualitative meta-analysis applied a novel vote-counting method that takes into account multiple parameters. The most significant miRNAs thus identified were then subjected to functional and bioinformatic analysis to assess their biomarker potential.

Results

A pool of deregulated circulating and tissue miRNAs with biomarker potential for MM was identified and designated as “mesomiRs” (MM-associated miRNAs). Comparison of data from asbestos-exposed and MM subjects found that the most promising candidates for a multimarker signature were circulating miR-126-3p, miR-103a-3p, and miR-625-3p in combination with mesothelin. The most consistently described tissue miRNAs, miR-16-5p, miR-126-3p, miR-143-3p, miR-145-5p, miR-192-5p, miR-193a-3p, miR-200b-3p, miR-203a-3p, and miR-652-3p, were also found to provide a diagnostic signature and should be further investigated as possible therapeutic targets.

Conclusion

The qualitative meta-analysis and functional investigation confirmed the early diagnostic value of two miRNA signatures for MM. Large-scale, standardized validation studies are needed to assess their clinical relevance, so as to move from the workbench to the clinic.

Seven-microRNA panel for lung adenocarcinoma early diagnosis in patients presenting with ground-glass nodules

Background

MicroRNA (miRNA) expression is correlated with tumor histology, differentiation, invasiveness and treatment outcome. We aimed to identify miRNAs whose differential expression might enable early diagnosis of lung adenocarcinoma in patients presenting with ground-glass nodules (GGNs).

Methods

To identify potential miRNAs of interest, we analyzed the miRNA expression profile of tumor and adjacent non-para-tumor tissue in three participants by next-generation sequencing (NGS). We then assessed the expression levels of the miRNAs of interest in 73 lung adenocarcinomas presenting with GGNs with matched adjacent non-tumor tissue by quantitative real-time polymerase chain reaction (qRT-PCR). We also detected the miRNA panel in 66 lung benign diseases and 66 lung adenocarcinomas presenting with GGN lesion tissues by qRT-PCR. Target genes of our selected miRNA panel were predicted using Miranda with default parameters.

Results

Twenty-three miRNAs showed differential expression between tumor and adjacent non-tumor tissue by NGS. Five miRNAs exhibited higher expression in tumor tissue compared to adjacent non-tumor tissue (P<0.05); 18 miRNAs demonstrated lower expression in tumor tissue versus adjacent non-tumor tissue (P<0.05). When qRT-PCR was performed for the 23 miRNAs identified by NGS in the pilot stage, seven were found to have statistically significant expression in tumor versus adjacent non-tumor tissue (P<0.05). The sensitivity and specificity of seven-miRNA panel were 86.4% and 60.6%, respectively.

Conclusion

The predicted targets of our miRNAs of interest are frequently associated with cancer signaling pathways. We developed a miRNA panel that could potentially predict the presence of lung adenocarcinoma in patients presenting with GGNs.

Return on investment in healthcare leadership development programs

Purpose Strong leadership has been shown to foster change, including loyalty, improved performance and decreased error rates, but there is a dearth of evidence on effectiveness of leadership development programs. To ensure a return on the huge investments made, evidence-based approaches are needed to assess the impact of leadership on health-care establishments. As a part of a pan-Canadian initiative to design an effective evaluative instrument, the purpose of this paper was to identify and summarize evidence on health-care outcomes/return on investment (ROI) indicators and metrics associated with leadership quality, leadership development programs and existing evaluative instruments. Design/methodology/approach The authors performed a scoping review using the Arksey and O'Malley framework, searching eight databases from 2006 through June 2016. Findings Of 11,868 citations screened, the authors included 223 studies reporting on health-care outcomes/ROI indicators and metrics associated with leadership quality (73 studies), leadership development programs (138 studies) and existing evaluative instruments (12 studies). The extracted ROI indicators and metrics have been summarized in detail. Originality/value This review provides a snapshot in time of the current evidence on ROI indicators and metrics associated with leadership. Summarized ROI indicators and metrics can be used to design an effective evaluative instrument to assess the impact of leadership on health-care organizations.

Genetic variants and acute kidney injury: A review of the literature

PURPOSE

Limited data exists on potential genetic contributors to acute kidney injury. This review examines current knowledge of AKI genomics.

MATERIALS AND METHODS

32 studies were selected from PubMed and GWAS Catalog queries for original data studies of human AKI genetics. Hand search of references identified 3 additional manuscripts.

RESULTS

33 of 35 studies were hypothesis-driven investigations of candidate polymorphisms that either did not consistently replicate statistically significant findings, or obtained significant results only in few small-scale studies. Vote-counting meta-analysis of 9 variants examined in >1 candidate gene study showed ≥50% non-significant studies, with larger studies generally finding non-significant results. The remaining 2 studies were large-scale unbiased investigations: One examining 2,100 genes linked with cardiovascular, metabolic, and inflammatory syndromes identified BCL2, SERPINA4, and SIK3 variants, while a genome-wide association study (GWAS) identified variants in BBS9 and the GRM7|LMCD1-AS1 intergenic region. All studies had relatively small sample sizes (<2300 subjects). Study heterogeneity precluded candidate gene and GWA meta-analysis.

CONCLUSIONS

Most studies of AKI genetics involve hypothesis-driven (rather than hypothesis-generating) candidate gene investigations that have failed to identify contributory variants consistently. A limited number of unbiased, larger-scale studies have been carried out, but there remains a pressing need for additional GWA studies.

Effect of treadmill exercise on skeletal muscle autophagy in rats with obesity induced by a high-fat diet

[Purpose]

This study aimed to investigate the effects of treadmill exercise on body weight, blood biochemistry, and autophagy.

[Methods]

Triglyceride, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, insulin, and glucose levels were measured, the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) score was calculated, and the soleus muscle was analyzed for autophagy-related factors (Beclin-1, p62, LC3, Lamp-2) in rats with obesity induced by a high-fat diet. Eight-week-old Sprague Dawley rats were fed a high-fat diet for 35 weeks and then subjected to 10 weeks of treadmill exercise. The experimental group was divided into a Normal Diet-Sedentary (ND-SED, n=8) group, an (High-Fat Diet-Sedentary (HF-SED, n=8) group, and an High-Fat Diet + Treadmill Exercise (HF-TE, n=8) group. The intensity of treadmill exercise was set as 8 m/min for 5 min, 11 m/min for 5 min, 15 m/min for 20 min, and 11 m/min for the last 5 minutes. A glucose tolerance test was performed at the 2nd and 8th week of exercise by sampling of tail blood.

[Results]

With endurance exercise, the HFTE group showed a significant decrease in body weight, with improved blood biochemical indices and HOMA-IR scores, in comparison with the HF-SED group. However, there was no significant difference in Beclin-1, p62, LC3, and Lamp-2 proteins as measured by autophagic flux in the soleus muscle.

[Conclusion]

Treadmill exercise induced improvements in body weight, body fat, and biochemical indicators of obesity and Type 2 diabetes, but had no effect on autophagy in soleus muscle.

Meta-analysis of clinical metabolic profiling studies in cancer: challenges and opportunities

Cancer cell metabolism has received increasing attention. Despite a boost in the application of clinical metabolic profiling (CMP) in cancer patients, a meta‐analysis has not been performed. The primary goal of this study was to assess whether public accessibility of metabolomics data and identification and reporting of metabolites were sufficient to assess which metabolites were consistently altered in cancer patients. We therefore retrospectively curated data from CMP studies in cancer patients published during 5 recent years and used an established vote‐counting method to perform a semiquantitative meta‐analysis of metabolites in tumor tissue and blood. This analysis confirmed well‐known increases in glycolytic metabolites, but also unveiled unprecedented changes in other metabolites such as ketone bodies and amino acids (histidine, tryptophan). However, this study also highlighted that insufficient public accessibility of metabolomics data, and inadequate metabolite identification and reporting hamper the discovery potential of meta‐analyses of CMP studies, calling for improved standardization of metabolomics studies.