Recommendations for sample selection, collection and preparation for NMR-based metabolomics studies of blood DOI Creative Commons
Abdul‐Hamid Emwas, Helena U. Zacharias, Marcos Rodrigo Alborghetti

et al.

Metabolomics, Journal Year: 2025, Volume and Issue: 21(3)

Published: May 10, 2025

Metabolic profiling of blood metabolites, particularly in plasma and serum, is vital for studying human diseases, conditions, drug interventions toxicology. The clinical significance arises from its close ties to all cells facile accessibility. However, patient-specific variables such as age, sex, diet, lifestyle health status, along with pre-analytical conditions (sample handling, storage, etc.), can significantly affect metabolomic measurements whole blood, plasma, or serum studies. These factors, referred confounders, must be mitigated reveal genuine metabolic changes due illness intervention onset. This review aims aid metabolomics researchers collecting reliable, standardized datasets NMR-based (whole/serum/plasma) metabolomics. goal reduce the impact confounding factors enhance inter-laboratory comparability, enabling more meaningful outcomes outlines main affecting metabolite levels offers practical suggestions what measure expect, how mitigate properly prepare, handle store biosamples report data targeted studies serum.

Language: Английский

New software tools, databases, and resources in metabolomics: updates from 2020 DOI Open Access
Biswapriya B. Misra

Metabolomics, Journal Year: 2021, Volume and Issue: 17(5)

Published: May 1, 2021

Language: Английский

Citations

181
Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies DOI Creative Commons
Qiao Jin, Ronald C.W.

Cells, Journal Year: 2021, Volume and Issue: 10(11), P. 2832 - 2832

Published: Oct. 21, 2021

The increasing prevalence of diabetes and its complications, such as cardiovascular kidney disease, remains a huge burden globally. Identification biomarkers for the screening, diagnosis, prognosis complications better understanding molecular pathways involved in development progression can facilitate individualized prevention treatment. With advancement analytical techniques, metabolomics identify quantify multiple simultaneously high-throughput manner. Providing information on underlying metabolic pathways, further mechanisms progression. application epidemiological studies have identified novel type 2 (T2D) branched-chain amino acids, metabolites phenylalanine, energy metabolism, lipid metabolism. Metabolomics also been applied to explore potential modulated by medications. Investigating using systems biology approach integrating with other omics data, genetics, transcriptomics, proteomics, clinical data present comprehensive network causal inference. In this regard, deepen understanding, help therapeutic targets, improve management T2D complications. current review focused metabolomic disease from studies, will provide brief overview investigations T2D.

Language: Английский

Citations

162
NMR and Metabolomics—A Roadmap for the Future DOI Creative Commons
David S. Wishart, Leo L. Cheng, Valérie Copié

et al.

Metabolites, Journal Year: 2022, Volume and Issue: 12(8), P. 678 - 678

Published: July 23, 2022

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These changes are measured various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods becoming increasingly popular in the field of metabolomics (accounting for more than 70% published studies to date), there considerable benefits advantages NMR-based metabolomic studies. In fact, according PubMed, 926 papers on were 2021-the most ever a given year. This suggests that continues grow has plenty offer scientific community. perspective outlines growing applications NMR metabolomics, highlights several recent advances technologies provides roadmap future advancements.

Language: Английский

Citations

109
Advanced tandem mass spectrometry in metabolomics and lipidomics—methods and applications DOI Creative Commons
Sven Heiles

Analytical and Bioanalytical Chemistry, Journal Year: 2021, Volume and Issue: 413(24), P. 5927 - 5948

Published: June 18, 2021

Abstract Metabolomics and lipidomics are new drivers of the omics era as molecular signatures selected analytes allow phenotypic characterization serve biomarkers, respectively. The growing capabilities untargeted targeted workflows, which primarily rely on mass spectrometric platforms, enable extensive charting or identification bioactive metabolites lipids. Structural annotation these compounds is key in order to link specific entities defined biochemical functions phenotypes. Tandem spectrometry (MS), first foremost collision-induced dissociation (CID), method choice unveil structural details But CID fragment ions often not sufficient fully characterize analytes. Therefore, recent years have seen a surge alternative tandem MS methodologies that aim offer full In this article, principles, capabilities, drawbacks, applications “advanced spectrometry” strategies will be critically reviewed. This includes methods based electrons, photons, ion/molecule, well ion/ion reactions, combining with concepts from optical spectroscopy making use derivatization strategies. final sections review, combination liquid chromatography imaging highlighted future perspectives for research metabolomics discussed. Graphical abstract

Language: Английский

Citations

97
Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives DOI Creative Commons
Marine P. M. Letertre, Patrick Giraudeau, Pascal De Tullio

et al.

Frontiers in Molecular Biosciences, Journal Year: 2021, Volume and Issue: 8

Published: Sept. 20, 2021

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize therapies and patient care based on individual characteristics. Its success highly depends way characterization of disease its evolution, patient’s classification, follow-up treatment could be optimized. Thus, personalized must combine innovative tools measure, integrate model data. Towards this goal, clinical metabolomics appears as ideally suited obtain relevant information. Indeed, signature brings crucial insight stratify patients according their responses a pathology and/or treatment, provide prognostic diagnostic biomarkers, improve therapeutic outcomes. However, translation from laboratory studies practice remains subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) mass spectrometry (MS) are two key platforms for measurement metabolome. NMR has several advantages features that essential metabolomics. inherently very robust, reproducible, unbiased, quantitative, informative at structural molecular level, requires little sample preparation reduced data processing. also well adapted large cohorts, multi-sites longitudinal studies. review focus potential context Starting with current status NMR-based level highlighting strengths, weaknesses challenges, article explores how, far initial “opposition” or “competition”, MS have been integrated demonstrated great complementarity, terms classification biomarker identification. Finally, perspective discussion provides into methodological developments significantly raise more resolutive, sensitive accessible tool applications point-of-care diagnosis. Thanks these advances, strong join other analytical currently used settings.

Language: Английский

Citations

75
Quantitative NMR spectroscopy of complex mixtures DOI
Patrick Giraudeau

Chemical Communications, Journal Year: 2023, Volume and Issue: 59(44), P. 6627 - 6642

Published: Jan. 1, 2023

The latest developments and applications in highly accurate quantitative NMR of complex mixtures.

Language: Английский

Citations

29
Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy DOI Creative Commons

Yurong Qin,

Miaozhe Huo, Xingwu Liu

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: March 8, 2024

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits minority of patients, underscoring the importance discovering reliable biomarkers can be used screen for beneficiaries and ultimately reduce risk overtreatment. Our comprehensive review focuses on latest advancements predictive ICI therapy, particularly emphasizing those enhance efficacy programmed cell death protein 1 (PD-1)/programmed death-ligand (PD-L1) inhibitors cytotoxic T-lymphocyte antigen-4 (CTLA-4) immunotherapies. We explore derived from various sources, including tumor cells, microenvironment (TIME), body fluids, gut microbes, metabolites. Among them, cells-derived include mutational burden (TMB) biomarker, neoantigen (TNB) microsatellite instability (MSI) PD-L1 expression mutated gene pathways, epigenetic biomarkers. TIME-derived landscape TIME biomarkers, inhibitory checkpoints repertoire also discuss techniques detect assess these detailing their respective datasets, strengths, weaknesses, evaluative metrics. Furthermore, we present computer models predicting response therapy. The knowledge-based mechanistic data-based machine learning (ML) models. are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) signal networks-based quantitative systems pharmacology (QSP) agent-based (ABMs). ML linear regression logistic support vector (SVM)/random forest/extra trees/k-nearest neighbors (KNN) artificial neural network (ANN) deep Additionally, there hybrid biology ML. summarized details outlining datasets they utilize, evaluation methods/metrics, strengths limitations. By summarizing major advances research therapeutic effect utility ICI, aim assist researchers choosing appropriate or exploration help clinicians conduct precision medicine by selecting best

Language: Английский

Citations

16
The potential new microbial hazard monitoring tool in food safety: Integration of metabolomics and artificial intelligence DOI
Ying Feng, Aswathi Soni, Gale Brightwell

et al.

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: 149, P. 104555 - 104555

Published: May 23, 2024

Language: Английский

Citations

11
Lipidomics-based natural products for chronic kidney disease treatment DOI Creative Commons
Ruiyan Zhang, Jingjing Wang,

Chenguang Wu

et al.

Heliyon, Journal Year: 2025, Volume and Issue: 11(1), P. e41620 - e41620

Published: Jan. 1, 2025

Chronic kidney disease (CKD) is by far the most prevalent in world and now a major global public health problem because of increase diabetes, hypertension obesity. Traditional biomarkers function lack sensitivity specificity for early detection monitoring CKD progression, necessitating more sensitive diagnostic intervention. Dyslipidemia hallmark CKD. Advancements mass spectrometry (MS)-based lipidomics platforms have facilitated comprehensive analysis lipids biological samples revealed changes lipidome that are associated with metabolic disorders, which can be used as new diseases. It also critical discovery therapeutic targets drugs. In this article, we focus on CKD, methodologies their applications Additionally, introduce novel identified through approaches natural products derived from treatment We believe our study makes significant contribution to literature demonstrating improve lipidomic perspective.

Language: Английский

Citations

1
Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms DOI Creative Commons
Cécile Martias, Nadine Baroukh, Sylvie Mavel

et al.

Molecules, Journal Year: 2021, Volume and Issue: 26(14), P. 4111 - 4111

Published: July 6, 2021

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use analytical platform, either NMR MS. Although some have already investigated data from multiple fluids, the information is limited to unique platform. On other hand, investigating human metabolome that combine multi-analytical platforms focused on biofluid. Combining types for one patient using multimodal approach (NMR MS) should extend coverage. Pre-analytical phases are time consuming. These steps need be improved order move into deal with large number samples. Our study describes standard operating procedure biological specimens (urine, blood, saliva, feces) (1H-NMR, RP-UHPLC-MS, HILIC-UHPLC-MS). Each follows preparation analysis multi-platform basis. method was evaluated its robustness able generate representative metabolic map.

Language: Английский

Citations

52