scholarly journals Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome

2019 ◽  
Author(s):  
Yu-Han H. Hsu ◽  
Christina M. Astley ◽  
Joanne B. Cole ◽  
Sailaja Vedantam ◽  
Josep M. Mercader ◽  
...  
Keyword(s):  
Causal Inference ◽  
Pathway Analysis ◽  
Meta Analysis ◽  
Untargeted Metabolomics ◽  
Metabolic Disturbances ◽  
Major Health ◽  
Pathway Enrichment ◽  
Causal Connections ◽  
Sufficient Power ◽  
Unidentified Metabolite

ABSTRACTBackgroundObesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analyses to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals.MethodsWe expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify these metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS.ResultsWe identified 10 known metabolites that are more likely to be the causes (e.g. alpha-hydroxybutyrate) or effects (e.g. valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g. glycine). Importantly, we also identified about 5 times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms.ConclusionsThese findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

scholarly journals Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome

2020 ◽  
Vol 44 (7) ◽  
pp. 1596-1606
Author(s):  
Yu-Han H. Hsu ◽  
Christina M. Astley ◽  
Joanne B. Cole ◽  
Sailaja Vedantam ◽  
Josep M. Mercader ◽  
...  
Keyword(s):  
Causal Inference ◽  
Untargeted Metabolomics ◽  
Pathway Enrichment

scholarly journals Antibiotic prophylaxis for prevention against Lyme disease following tick bite: an updated systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guozhong Zhou ◽  
Xin Xu ◽  
Yu Zhang ◽  
Peng Yue ◽  
Shiqi Luo ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Antibiotic Prophylaxis ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
Tick Bite ◽  
Cochrane Library ◽  
Control Group ◽  
Sufficient Power ◽  
Detailed Assessment ◽  
Meta Analyses

Abstract Background In areas where Lyme disease is endemic, bites from ticks are common, but no vaccine is currently available against Lyme disease for humans. Therefore, the feasibility of using antibiotic prophylaxis to prevent Lyme disease after a tick bite is worth further exploration. Previous meta-analyses lack sufficient power to demonstrate the efficacy of about antibiotic prophylaxis for the prevention of Lyme disease following a tick bite. In this study, we explored more precise evidence and attempted to identify and update optimum treatment strategies. Methods We searched PubMed, Embase, and the Cochrane Library for studies until March 23, 2021. We included studies if the enrolled patients were randomly allocated to a treatment or control group within 72 h following a tick bite and had no clinical evidence of Lyme disease at enrolment. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines were followed for data abstraction. Two authors (GZZ and XX) independently reviewed the abstracts and identified articles for detailed assessment. We used a random-effects model to calculate the pooled results and reported the 95% confidence interval (CI). Study quality was assessed using a modified Jadad scale, and publication bias was assessed using Egger’s test. We calculated the risk ratio (RR) for the rates of unfavorable events in patients who received intervention versus the control group. This study is registered with PROSPERO, number CRD42021245002. Results Six studies (3,766 individuals) were included. The pooled rate of unfavorable events in persons receiving treatment and the control group were 0.4% (95%CI: 0.1–1.1%) and 2.2% (95%CI: 1.6–3.0%), respectively. The pooled RR was 0.38 (95%CI: 0.22–0.66). Subgroup analysis revealed that the pooled RR was 0.29 (95%CI: 0.14–0.60) in the single-use 200-mg doxycycline group; 0.28 (95%CI: 0.05–1.67) in a 10-day course group (Amoxicillin, Penicillin or tetracycline); and 0.73 (95%CI: 0.25–2.08) in a topical antibiotic treatment group (Azithromycin). Conclusions The available evidence supports the use of antibiotics for the prevention of Lyme disease, and reveals advantages of using single-dose; however, further confirmation is needed.

scholarly journals Is There a Relationship Between Psoriasis and Hepatitis C?: a Meta-analysis and Bioinformatics Investigation

2021 ◽  
Author(s):  
Yong Liu ◽  
Sheng Nan Cui ◽  
Meng Yao Duan ◽  
Zhi Li Dou ◽  
Yi Zhen Li ◽  
...  
Keyword(s):  
Hepatitis C ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Case Control ◽  
Cochrane Library ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Overlapping Genes ◽  
Cross Sectional ◽  
Pathway Enrichment

Abstract Background: The relationship between psoriasis and hepatitis C was previously controversial, so our purpose is to investigate this connection.Methods: We conducted a systematic review of the case-control, cross-sectional and cohort studies examining the association between psoriasis and hepatitis C in PubMed, EMBASE and Cochrane library databases and investigated the overlapping genes between psoriasis targets and hepatitis C targets using bioinformatics analysis. Based on overlapping genes and hub nodes, we also constructed the protein-protein interaction (PPI) network and module respectively, followed by the pathway enrichment analysis. Results: We included 11 publications that reported a total of 11 studies (8 cross-sectional and 3 case-control). The case–control and cross-sectional studies included 25,047 psoriasis patients and 4,091,631 controls in total. Psoriasis was associated with a significant increase of prevalent hepatitis C (OR 1.72; 95% confidence interval [CI] (1.17-2.52)). A total of 389 significant genes were common to both hepatitis C and psoriasis, which mainly involved IL6, TNF, IL10, ALB, STAT3 and CXCL8. The module and pathway enrichment analyses showed that the common genes had the potential to influence varieties of biological pathways, including the inflammatory response, cytokine activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, which play an important role in the pathogenesis of hepatitis C and psoriasis.Conclusion: Patients with psoriasis display increased prevalence of hepatitis C and the basic related mechanisms between hepatitis C and psoriasis had been preliminarily clarified.

scholarly journals Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

2021 ◽  
Vol 9 ◽  
Author(s):  
Moumita Mukherjee ◽  
Srikanta Goswami
Keyword(s):  
Pancreatic Cancer ◽  
Cell Migration ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein–protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

scholarly journals Chinese Herbal Medicine for Osteoporosis: A Systematic Review of Randomized Controlled Trails

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Zhi-qian Wang ◽  
Jin-long Li ◽  
Yue-li Sun ◽  
Min Yao ◽  
Jie Gao ◽  
...  
Keyword(s):  
Elderly Population ◽  
Meta Analysis ◽  
Chinese Herb ◽  
The Elderly ◽  
Chinese Herbs ◽  
Major Health Problem ◽  
Major Health ◽  
Pooled Data ◽  
Randomized Controlled ◽  
Chinese Medicine Treatment

Background. Osteoporosis is a major health problem for the elderly population. Chinese herb may be beneficial to osteoporosis due to its capability.Objectives. This study was designed to evaluate the effectiveness of Chinese medicine treatment on the patients with osteoporosis.Search Methods. Randomized controlled trials were retrieved from different 9 databases.Results. This meta analysis included 12 RCTs involving 1816 patients to compare Chinese herbs with placebo or standard anti-osteoporotic therapy in the treatment of bone loss. The pooled data showed that the percent change of increased BMD in the spine is higher with Chinese herb compared to placebo (lumber spine: WMD = 0.07, 95% CI: 0.01–0.04). In the femoral, Chinese herb showed significantly higher increments of BMD compared to placebo (femoral neck: WMD = 0.06, 95% CI: −0.02–0.13). Compared to the other standard anti-osteoporotic drugs, Chinese herbs also show advantage in BMD change (lumber spine: WMD = 0.03, 95% CI: −0.01–0.08; femoral: WMD = 0.01, 95% CI: −0.01–0.02).Conclusions. Our results demonstrated that Chinese herb significantly increased lumbar spine BMD as compared to the placebo or other standard anti-osteoporotic drugs.

MetENP/MetENPWeb: An R package and web application for metabolomics enrichment and pathway analysis in Metabolomics Workbench

2020 ◽  
Author(s):  
Kumari Sonal Choudhary ◽  
Eoin Fahy ◽  
Kevin Coakley ◽  
Manish Sud ◽  
Mano R Maurya ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Web Application ◽  
Enrichment Analysis ◽  
R Package ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Kegg Pathways ◽  
Link Type ◽  
Species Specific ◽  
User Friendly

ABSTRACTWith the advent of high throughput mass spectrometric methods, metabolomics has emerged as an essential area of research in biomedicine with the potential to provide deep biological insights into normal and diseased functions in physiology. However, to achieve the potential offered by metabolomics measures, there is a need for biologist-friendly integrative analysis tools that can transform data into mechanisms that relate to phenotypes. Here, we describe MetENP, an R package, and a user-friendly web application deployed at the Metabolomics Workbench site extending the metabolomics enrichment analysis to include species-specific pathway analysis, pathway enrichment scores, gene-enzyme information, and enzymatic activities of the significantly altered metabolites. MetENP provides a highly customizable workflow through various user-specified options and includes support for all metabolite species with available KEGG pathways. MetENPweb is a web application for calculating metabolite and pathway enrichment analysis.Availability and ImplementationThe MetENP package is freely available from Metabolomics Workbench GitHub: (https://github.com/metabolomicsworkbench/MetENP), the web application, is freely available at (https://www.metabolomicsworkbench.org/data/analyze.php)

Effects of Coenzyme Q10 Supplementation on Serum Adiponectin Levels: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

2020 ◽  
Vol 15 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Ali Nazary-Vannani ◽  
Ehsan Ghaedi ◽  
Shekoufeh Salamat ◽  
Afsaneh Sayyaf ◽  
Hamed K. Varkaneh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Serum Level ◽  
Coenzyme Q10 ◽  
Meta Analysis ◽  
Serum Adiponectin ◽  
Significant Heterogeneity ◽  
Metabolic Disturbances ◽  
Comprehensive Search ◽  
Coq10 Supplementation

Background: Adiponectin, a well-known adipokine plays a number of regulatory actions in human body metabolism. Decreased levels of adiponectin have been reported in type 2 diabetes mellitus, cardiovascular diseases, metabolic syndrome and hypertension. Coenzyme Q10 (Co Q10) is a fat-soluble antioxidant substance which has been reported to be effective in several metabolic disturbances such as insulin resistance and inflammation. Objective: Present systematic review and meta-analysis were performed to assess the effects of CoQ10 supplementation on adiponectin serum level. Methods: A comprehensive search was performed in electronic databases including EMBASE, Google scholar, and PubMed up to January 2018. A meta-analysis of eligible studies was performed using random effects model to estimate pooled effect size of CoQ10 supplementation on adiponectin. Results: A total of 209 subjects were recruited from 5 eligible studies. Meta-analysis did not suggest any significant effect of CoQ10 supplementation on adiponectin serum level (0.240 mg/dl, 95%CI: -0.216, 0.696, P= 0.303), without significant heterogeneity between included studies (I2= 40.9%, p= 0.149). Conclusion: Although present meta-analysis did not indicate any significant effects of CoQ10 supplementation on serum adiponectin levels but future long-term dose-response trials are needed before any firm conclusion.

Sign in / Sign up

Export Citation Format

Share Document