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Special Issue Editor

Special Issue Information

Dear Colleagues,

We are calling for the submission of systematic reviews and meta-analyses on any topic related to metabolites and disease risk. In recent years, there has been a massive expansion of research output related to metabolomics. Therefore, there is an urgent need to synthesize and summarize the findings to take stock of what we know so far. Systematic review refers to the summary of published findings and meta-analysis is a statistical analysis of the results of independent studies. They involve a set of methods to systematically search for and synthesize evidence from published studies. They are useful for reconciling inconsistencies across studies, allowing the integration and synthesis of existing knowledge, highlighting research gaps, and guiding subsequent research. We welcome systematic reviews and meta-analyses on topics within the domain of metabolite studies, as well as in related fields, which may include but are not limited to the following areas:

Diseases
Microbiome
Environmental/lifestyle factors

Dr. Wei Jie Seow
Guest Editor

Manuscript Submission Information

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Keywords

Systematic review
Meta-analysis
Metabolites

Published Papers (2 papers)

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Research

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14 pages, 2833 KiB

Open AccessArticle

Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets

by Zhiqiang Pang, Guangyan Zhou, Jasmine Chong and Jianguo Xia

Metabolites 2021, 11(1), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11010044 - 09 Jan 2021

Cited by 64 | Viewed by 12421

Abstract

The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather than the viral load or its genetic variations. A growing number of omics studies have been conducted to characterize the host immune and metabolic responses underlying the disease progression. Meta-analyses of these datasets have great potential to identify robust molecular signatures to inform clinical care and to facilitate therapeutics development. In this study, we performed a comprehensive meta-analysis of publicly available global metabolomics datasets obtained from three countries (United States, China and Brazil). To overcome high heterogeneity inherent in these datasets, we have (a) implemented a computational pipeline to perform consistent raw spectra processing; (b) conducted meta-analyses at pathway levels instead of individual feature levels; and (c) performed visual data mining on consistent patterns of change between disease severities for individual studies. Our analyses have yielded several key metabolic signatures characterizing disease progression and clinical outcomes. Their biological interpretations were discussed within the context of the current literature. To the best of our knowledge, this is the first comprehensive meta-analysis of global metabolomics datasets of COVID-19. Full article

(This article belongs to the Special Issue Systematic Reviews and Meta-Analyses (SR-MA) of Metabolites and Disease Risk)

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Graphical abstract

Review

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15 pages, 1799 KiB

Open AccessReview

Urinary Volatile Organic Compound Analysis for the Diagnosis of Cancer: A Systematic Literature Review and Quality Assessment

by Qing Wen, Piers Boshier, Antonis Myridakis, Ilaria Belluomo and George B. Hanna

Metabolites 2021, 11(1), 17; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11010017 - 29 Dec 2020

Cited by 39 | Viewed by 4759

Abstract

The analysis of urinary volatile organic compounds (VOCs) is a promising field of research with the potential to discover new biomarkers for cancer early detection. This systematic review aims to summarise the published literature concerning cancer-associated urinary VOCs. A systematic online literature search was conducted to identify studies reporting urinary VOC biomarkers of cancers in accordance with the recommendations of the Cochrane Library and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Thirteen studies comprising 1266 participants in total were included in the review. Studies reported urinary VOC profiles of five cancer subtypes: prostate cancer, gastrointestinal cancer, leukaemia/lymphoma, lung cancer, and bladder cancer. Forty-eight urinary VOCs belonging to eleven chemical classes were identified with high diagnostic performance. VOC profiles were distinctive for each cancer type with limited cross-over. The metabolic analysis suggested distinctive phenotypes for prostate and gastrointestinal cancers. The heterogenicity of study design, methodological and reporting quality may have contributed to inconsistencies between studies. Urinary VOC analysis has shown promising performance for non-invasive diagnosis of cancer. However, limitations in study design have resulted in inconsistencies between studies. These limitations are summarised and discussed in order to support future studies. Full article

(This article belongs to the Special Issue Systematic Reviews and Meta-Analyses (SR-MA) of Metabolites and Disease Risk)

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