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Metabolites
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Biofluid-Based Metabolomics for Biomarker Discovery
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Biofluid-Based Metabolomics for Biomarker Discovery

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Integrative Metabolomics".

Deadline for manuscript submissions: closed (15 May 2023) | Viewed by 15800

Special Issue Editor

Dr. Kévin Contrepois

E-Mail Website
Guest Editor
Integrated Bioanalysis, Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, South San Francisco, CA 94080, USA
Interests: biomarker discovery; multi-omics; systems biology; mass spectrometry

Special Issue Information

Dear Colleagues,

Nowadays, advancements in omics technologies allow the routine generation of high-quality and high-content data from any biological sample, among which metabolomics has quickly become a major screening tool in the field of biomarker discovery due to being the product of gene expression and protein activity and, thus, closest to the phenotype. Both precision health and precision medicine strategies rely on biomarkers to assess disease risk, detect early preclinical conditions, assess disease progression and monitor treatment response.

This Special Issue of Metabolites is devoted to biomarker discovery in biofluids using metabolomics technologies, topics covered including, but not limited to, the exploration of novel biological matrixes and sampling procedures, methodological development (sample preparation and data acquisition), the improvement of analysis workflows (data annotation and machine learning approaches) as well as advances in biomarker prioritization, both clinical and translational studies being equally desirable. Herein, the definition of metabolites is broad and includes xenobiotics, complex lipids and lipid mediators.

Dr. Kévin Contrepois
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
  • biomarker discovery and validation
  • biofluid
  • mass spectrometry
  • NMR
  • precision medicine
  • precision health

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Published Papers (6 papers)

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13 pages, 16006 KiB  
Article
Quality Control of Targeted Plasma Lipids in a Large-Scale Cohort Study Using Liquid Chromatography–Tandem Mass Spectrometry
by Akiyoshi Hirayama, Takamasa Ishikawa, Haruka Takahashi, Sanae Yamanaka, Satsuki Ikeda, Aya Hirata, Sei Harada, Masahiro Sugimoto, Tomoyoshi Soga, Masaru Tomita and Toru Takebayashi
Metabolites 2023, 13(4), 558; https://doi.org/10.3390/metabo13040558 - 13 Apr 2023
Cited by 2 | Viewed by 1515
Abstract
High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography–mass spectrometry was used to analyze 10,833 samples in [...] Read more.
High-throughput metabolomics has enabled the development of large-scale cohort studies. Long-term studies require multiple batch-based measurements, which require sophisticated quality control (QC) to eliminate unexpected bias to obtain biologically meaningful quantified metabolomic profiles. Liquid chromatography–mass spectrometry was used to analyze 10,833 samples in 279 batch measurements. The quantified profile included 147 lipids including acylcarnitine, fatty acids, glucosylceramide, lactosylceramide, lysophosphatidic acid, and progesterone. Each batch included 40 samples, and 5 QC samples were measured for 10 samples of each. The quantified data from the QC samples were used to normalize the quantified profiles of the sample data. The intra- and inter-batch median coefficients of variation (CV) among the 147 lipids were 44.3% and 20.8%, respectively. After normalization, the CV values decreased by 42.0% and 14.7%, respectively. The effect of this normalization on the subsequent analyses was also evaluated. The demonstrated analyses will contribute to obtaining unbiased, quantified data for large-scale metabolomics. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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18 pages, 2106 KiB  
Article
Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach
by Xiangping Lin, Xinyu Liu, Mohamed N. Triba, Nadia Bouchemal, Zhicheng Liu, Douglas I. Walker, Tony Palama, Laurence Le Moyec, Marianne Ziol, Nada Helmy, Corinne Vons, Guowang Xu, Carina Prip-Buus and Philippe Savarin
Metabolites 2022, 12(11), 1081; https://doi.org/10.3390/metabo12111081 - 8 Nov 2022
Cited by 4 | Viewed by 3942
Abstract
Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the [...] Read more.
Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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13 pages, 4314 KiB  
Article
Congruence and Complementarity of Differential Mobility Spectrometry and NMR Spectroscopy for Plasma Lipidomics
by Mohan Ghorasaini, Konstantina Ismini Tsezou, Aswin Verhoeven, Yassene Mohammed, Panayiotis Vlachoyiannopoulos, Emmanuel Mikros and Martin Giera
Metabolites 2022, 12(11), 1030; https://doi.org/10.3390/metabo12111030 - 27 Oct 2022
Cited by 8 | Viewed by 2081
Abstract
The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid [...] Read more.
The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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12 pages, 3233 KiB  
Article
Simultaneous Determination of Methylated Nucleosides by HILIC–MS/MS Revealed Their Alterations in Urine from Breast Cancer Patients
by Zhihao Fang, Yiqiu Hu, Xiujuan Hong, Xiaoxiao Zhang, Tao Pan, Chi Pan, Shu Zheng and Cheng Guo
Metabolites 2022, 12(10), 973; https://doi.org/10.3390/metabo12100973 - 14 Oct 2022
Cited by 11 | Viewed by 2001
Abstract
RNA methylation plays a vital role in the pathogenesis of a variety of diseases including cancer, and aberrant levels of modified nucleosides in RNA were revealed to be related to cancer. Urine is a favored source for biomarker discovery due to the non-invasion [...] Read more.
RNA methylation plays a vital role in the pathogenesis of a variety of diseases including cancer, and aberrant levels of modified nucleosides in RNA were revealed to be related to cancer. Urine is a favored source for biomarker discovery due to the non-invasion to patients. Herein, we developed a sensitive hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC–MS/MS) method combined with stable isotope dilution for accurate quantification of methylated nucleosides in human urine. With this method, we successfully quantified ten methylated nucleosides in urine samples collected from healthy controls and breast cancer patients. We found N6-methyladenosine (m6A), 2′-O-methyladenosine (Am), N1-methyladenosine (m1A), N6,2′-O-dimethyladenosine (m6Am), N1-methylguanosine (m1G), 2′-O-methylguanosine (Gm), 5-methylcytidine (m5C) and 2′-O-methylcytidine (Cm) were all decreased in early-stage breast cancer patients, and a nomogram prediction model was constructed. Locally advanced breast cancer patients exhibited elevated levels of urinary 2′-O-methylated nucleosides in comparison to early-stage breast cancer patients. Together, we developed a robust method for the simultaneous determination of methylated nucleosides in human urine, and the results revealed an association between the contents of urinary methylated nucleosides and the occurrence of breast cancer, which may stimulate future studies about the regulatory roles of these methylated nucleosides in the initiation and progression of breast cancer. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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18 pages, 2287 KiB  
Article
The Metabolomic Profile in Amyotrophic Lateral Sclerosis Changes According to the Progression of the Disease: An Exploratory Study
by Carmen Marino, Manuela Grimaldi, Eduardo Maria Sommella, Tania Ciaglia, Angelo Santoro, Michela Buonocore, Emanuela Salviati, Francesca Trojsi, Arianna Polverino, Pierpaolo Sorrentino, Giuseppe Sorrentino, Pietro Campiglia and Anna Maria D’Ursi
Metabolites 2022, 12(9), 837; https://doi.org/10.3390/metabo12090837 - 4 Sep 2022
Cited by 6 | Viewed by 2425
Abstract
Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical [...] Read more.
Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical profile; however, no molecular biomarkers are used as diagnostic criteria to establish the ALS pathological staging. Using the source-reconstructed magnetoencephalography (MEG) approach, we demonstrated that global brain hyperconnectivity is associated with early and advanced clinical ALS stages. Using nuclear magnetic resonance (1H-NMR) and high resolution mass spectrometry (HRMS) spectroscopy, here we studied the metabolomic profile of ALS patients’ sera characterized by different stages of disease progression—namely early and advanced. Multivariate statistical analysis of the data integrated with the network analysis indicates that metabolites related to energy deficit, abnormal concentrations of neurotoxic metabolites and metabolites related to neurotransmitter production are pathognomonic of ALS in the advanced stage. Furthermore, analysis of the lipidomic profile indicates that advanced ALS patients report significant alteration of phosphocholine (PCs), lysophosphatidylcholine (LPCs), and sphingomyelin (SMs) metabolism, consistent with the exigency of lipid remodeling to repair advanced neuronal degeneration and inflammation. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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12 pages, 2111 KiB  
Brief Report
Changes in Plasma Metabolic Signature upon Acute and Chronic Morphine Administration in Morphine-Tolerant Mice
by Naseer A. Kutchy, Amelia Palermo, Rong Ma, Zhong Li, Alexandria Ulanov, Shannon Callen, Gary Siuzdak, Sabita Roy, Shilpa Buch and Guoku Hu
Metabolites 2023, 13(3), 434; https://doi.org/10.3390/metabo13030434 - 16 Mar 2023
Cited by 2 | Viewed by 2436
Abstract
Morphine administration causes system-level metabolic changes. Here, we show that morphine-tolerant mice exhibited distinct plasma metabolic signatures upon acute and chronic administration. We utilized a mouse model of morphine tolerance by exposing mice to increasing doses of the drug over 4 days. We [...] Read more.
Morphine administration causes system-level metabolic changes. Here, we show that morphine-tolerant mice exhibited distinct plasma metabolic signatures upon acute and chronic administration. We utilized a mouse model of morphine tolerance by exposing mice to increasing doses of the drug over 4 days. We collected plasma samples from mice undergoing acute or chronic morphine or saline injections and analyzed them using targeted GC–MS-based metabolomics to profile approximately 80 metabolites involved in the central carbon, amino acid, nucleotide, and lipid metabolism. Our findings reveal distinct alterations in plasma metabolite concentrations in response to acute or chronic morphine intake, and these changes were linked to the development of tolerance to morphine’s analgesic effects. We identified several metabolites that had been differentially affected by acute versus chronic morphine use, suggesting that metabolic changes may be mitigated by prolonged exposure to the drug. Morphine-tolerant mice showed a restoration of amino acid and glycolytic metabolites. Additionally, we conducted reconstructed metabolic network analysis on the first 30 VIP-ranked metabolites from the PLSDA of the saline, acute, and morphine-tolerant mice groups, which uncovered four interaction networks involving the amino acid metabolism, the TCA cycle, the glutamine-phenylalanine-tyrosine pathway, and glycolysis. These pathways were responsible for the metabolic differences observed following distinct morphine administration regimens. Overall, this study provides a valuable resource for future investigations into the role of metabolites in morphine-induced analgesia and associated effects following acute or chronic use in mice. Full article
(This article belongs to the Special Issue Biofluid-Based Metabolomics for Biomarker Discovery)
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