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Metabolites
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Metabolomics in Disease Mechanisms and Drug Targets
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Metabolomics in Disease Mechanisms and Drug Targets

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Metabolomic Profiling Technology".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 5373

Special Issue Editor

Dr. Kefeng Li

E-Mail Website
Guest Editor
Faculty of Applied Sciences, Macao Polytechnic University, Macau SAR 999074, China
Interests: artificial intelligence-empowered metabolomics; exposomics analysis; application in understanding complex diseases and identifying novel drug targets
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics, a distinct and comprehensive top–down methodology, offers profound insights into intricate systems, with its profiles encapsulating the phenotypic manifestations of cellular reactions to physiological, pathophysiological stimuli, and epigenetic alterations. Through quantitative profiling of the metabolome, we can glean mechanistic insights into a myriad of biological functions and processes. Recent advancements in metabolomic analysis have propelled us towards a fresh understanding of the intricate mechanisms underlying complex metabolic diseases. Furthermore, metabolomics can illuminate potential new targets for therapeutic intervention by pinpointing pathological metabolic shifts, particularly those involving enzymes that exhibit increased flux during disease progression. The successful clinical development of therapies targeting these novel entities has heightened interest and appreciation of the value of metabolomics as a strategy for drug target identification. However, numerous challenges remain to be addressed, including understanding the connectivity and interactions among metabolites, elucidating complex disease mechanisms, and pinpointing appropriate drug targets.

In light of these considerations, this Special Issue is dedicated to the exploration of metabolomics in the context of disease mechanisms and drug target identification. We invite original research articles and comprehensive reviews that illuminate the role of metabolomics in disease mechanism elucidation and drug target discovery, with a particular focus on innovative strategies and methodologies to overcome existing challenges.

Dr. Kefeng Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • metabolomics
  • disease mechanism
  • drug target
  • biomarker
  • disease prediction

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Published Papers (2 papers)

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Review

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19 pages, 2507 KiB  
Review
Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases
by Weiyu Meng, Hongxin Pan, Yuyang Sha, Xiaobing Zhai, Abao Xing, Sai Sachin Lingampelly, Srinivasa R. Sripathi, Yuefei Wang and Kefeng Li
Metabolites 2024, 14(2), 93; https://doi.org/10.3390/metabo14020093 - 26 Jan 2024
Cited by 5 | Viewed by 3216
Abstract
The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. [...] Read more.
The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism’s phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications. Full article
(This article belongs to the Special Issue Metabolomics in Disease Mechanisms and Drug Targets)
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Other

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24 pages, 1235 KiB  
Systematic Review
Peripheral Lipid Signatures, Metabolic Dysfunction, and Pathophysiology in Schizophrenia Spectrum Disorders
by Sally Wu, Kristoffer J. Panganiban, Jiwon Lee, Dan Li, Emily C.C. Smith, Kateryna Maksyutynska, Bailey Humber, Tariq Ahmed, Sri Mahavir Agarwal, Kristen Ward and Margaret Hahn
Metabolites 2024, 14(9), 475; https://doi.org/10.3390/metabo14090475 - 28 Aug 2024
Cited by 1 | Viewed by 1441
Abstract
Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and [...] Read more.
Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and AP-induced metabolic dysfunction are unknown, but dysregulated lipid metabolism may play a role. Lipidomics, which detects lipid metabolites in a biological sample, represents an analytical tool to examine lipid metabolism. This systematic review aims to determine peripheral lipid signatures that are dysregulated among individuals with SSDs (1) with minimal exposure to APs and (2) during AP treatment. To accomplish this goal, we searched MEDLINE, Embase, and PsychINFO databases in February 2024 to identify all full-text articles written in English where the authors conducted lipidomics in SSDs. Lipid signatures reported to significantly differ in SSDs compared to controls or in relation to AP treatment and the direction of dysregulation were extracted as outcomes. We identified 46 studies that met our inclusion criteria. Most of the lipid metabolites that significantly differed in minimally AP-treated patients vs. controls comprised glycerophospholipids, which were mostly downregulated. In the AP-treated group vs. controls, the significantly different metabolites were primarily fatty acyls, which were dysregulated in conflicting directions between studies. In the pre-to-post AP-treated patients, the most impacted metabolites were glycerophospholipids and fatty acyls, which were found to be primarily upregulated and conflicting, respectively. These lipid metabolites may contribute to SSD pathophysiology and metabolic dysfunction through various mechanisms, including the modulation of inflammation, cellular membrane permeability, and metabolic signaling pathways. Full article
(This article belongs to the Special Issue Metabolomics in Disease Mechanisms and Drug Targets)
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