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Vignoli A, Gori AM, Berteotti M, Cesari F, Giusti B, Bertelli A, Kura A, Sticchi E, Salvadori E, Barbato C, Formelli B, Pescini F, Marcucci R, Tenori L, Poggesi A. The serum metabolomic profiles of atrial fibrillation patients treated with direct oral anticoagulants or vitamin K antagonists. Life Sci 2024; 351:122796. [PMID: 38852797 DOI: 10.1016/j.lfs.2024.122796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/03/2024] [Accepted: 06/04/2024] [Indexed: 06/11/2024]
Abstract
AIMS Long-term oral anticoagulation is the primary therapy for preventing ischemic stroke in patients with atrial fibrillation (AF). Different types of oral anticoagulant drugs can have specific effects on the metabolism of patients. Here we characterize, for the first time, the serum metabolomic and lipoproteomic profiles of AF patients treated with anticoagulants: vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs). MATERIALS AND METHODS Serum samples of 167 AF patients (median age 78 years, 62 % males, 70 % on DOACs treatment) were analyzed via high resolution 1H nuclear magnetic resonance (NMR) spectroscopy. Data on 25 metabolites and 112 lipoprotein-related fractions were quantified and analyzed with multivariate and univariate statistical approaches. KEY FINDINGS Our data provide evidence that patients treated with VKAs and DOACs present significant differences in their profiles: lower levels of alanine and lactate (odds ratio: 1.72 and 1.84), free cholesterol VLDL-4 subfraction (OR: 1.75), triglycerides LDL-1 subfraction (OR: 1.80) and 4 IDL cholesterol fractions (ORs ∼ 1.80), as well as higher levels of HDL cholesterol (OR: 0.48), apolipoprotein A1 (OR: 0.42) and 7 HDL cholesterol fractions/subfractions (ORs: 0.40-0.51) are characteristic of serum profile of patients on DOACs' therapy. SIGNIFICANCE Our results support the usefulness of NMR-based metabolomics for the description of the effects of oral anticoagulants on AF patient circulating metabolites and lipoproteins. The higher serum levels of HDL cholesterol observed in patients on DOACs could contribute to explaining their reduced cardiovascular risk, suggesting the need of further studies in this direction to fully understand possible clinical implications.
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Affiliation(s)
- Alessia Vignoli
- Department of Chemistry "Ugo Schiff", University of Florence, 50019 Sesto Fiorentino, Italy; Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
| | - Anna Maria Gori
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Martina Berteotti
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Francesca Cesari
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Betti Giusti
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Alessia Bertelli
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Ada Kura
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Elena Sticchi
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Emilia Salvadori
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy
| | - Carmen Barbato
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy
| | | | | | - Rossella Marcucci
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Leonardo Tenori
- Department of Chemistry "Ugo Schiff", University of Florence, 50019 Sesto Fiorentino, Italy; Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy.
| | - Anna Poggesi
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy; Stroke Unit, AOU Careggi, 50134, Florence, Italy.
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Coskun A, Ertaylan G, Pusparum M, Van Hoof R, Kaya ZZ, Khosravi A, Zarrabi A. Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy. Biochim Biophys Acta Mol Basis Dis 2024:167339. [PMID: 38986819 DOI: 10.1016/j.bbadis.2024.167339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/25/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.
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Affiliation(s)
- Abdurrahman Coskun
- Acibadem University, School of Medicine, Department of Medical Biochemistry, Istanbul, Turkey.
| | - Gökhan Ertaylan
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium
| | - Murih Pusparum
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium; I-Biostat, Data Science Institute, Hasselt University, Hasselt 3500, Belgium
| | - Rebekka Van Hoof
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium
| | - Zelal Zuhal Kaya
- Nisantasi University, School of Medicine, Department of Medical Biochemistry, Istanbul, Turkey
| | - Arezoo Khosravi
- Department of Genetics and Bioengineering, Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul 34959, Turkey
| | - Ali Zarrabi
- Department of Biomedical Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul 34396, Turkey; Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600 077, India
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3
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Singh D, Ham D, Kim SA, Kothari D, Park YJ, Joung H, Lee CH. Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress and inflammation: a randomized controlled crossover trial. Sci Rep 2024; 14:15277. [PMID: 38961128 PMCID: PMC11222465 DOI: 10.1038/s41598-024-65742-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 06/24/2024] [Indexed: 07/05/2024] Open
Abstract
Dietary biomarkers in urine remain elusive when evaluating diet-induced oxidative stress and inflammation. In our previous study, we conducted a randomized controlled crossover trial to compare the short-term (4-weeks) effects of the balanced Korean diet (BKD) with Western diets, including the 2010 dietary guidelines for Americans (2010 DGA) and typical American diet (TAD), on various metabolic indices in obese Korean adults. Building on this work, the current research focuses on the impact of these dietary interventions on oxidative stress (d-ROMs and BAP) and inflammation (CRP, TNF-α, IL-6, IL-1β, MCP-1) biomarkers in serum, and the concurrent urine metabolomes. Each dietary regimen was in silico and experimentally examined for their antioxidant levels using ABTS, DPPH, and FRAP assays, as well as total flavonoid (TFC) and total phenolic (TPC) contents. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants (n = 48, average age: 41 years). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD (p < 0.05). Butanol extracts from recommended diets (BKD and 2010 DGA) showed significantly higher antioxidant activity compared to TAD in ABTS (p < 0.01), DPPH, and FRAP (p < 0.05) assays. Consistent results were observed in total phenolic and flavonoid contents, mirroring their respective antioxidant activities. Following the intervention period, oxidative stress & inflammation markers in serum varied marginally, however, the urine metabolite profiles were clearly demarcated for the BKD and Western dietary groups (PC1 = 5.41%). For BKD group, the pre- and post-intervention urine metabolite profiles were clearly segregated (PLS2 = 2.93%). Compared to TAD, urine extracts from the recommended dietary group showed higher abundance of benzoic acid & phenolic derivatives (VIP > 0.7, p < 0.05). Metabolites associated with oxidative stress were observed higher in the urine samples from Western dietary groups compared to BKD. Urine metabolomics data delineated the post-intervention effects of three dietary interventions which corroborates the respective findings for their effects on metabolic indices.
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Affiliation(s)
- Digar Singh
- Department of Botany and Microbiology, Hemvati Nandan Bahuguna Garhwal University, Srinagar (Garhwal), Uttarakhand, 246174, India
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, 05029, Republic of Korea
| | - Dongwoo Ham
- Institute of Health and Environment, Seoul National University, Seoul, 08826, Republic of Korea
| | - Seong-Ah Kim
- Division of Strategic Research, The Seoul Institute, Seoul, 06756, Republic of Korea
| | - Damini Kothari
- Department of Biochemistry, Hemvati Nandan Bahuguna Garhwal University, Srinagar (Garhwal), Uttarakhand, 246174, India
| | - Yu Jin Park
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, 05029, Republic of Korea
| | - Hyojee Joung
- Institute of Health and Environment, Seoul National University, Seoul, 08826, Republic of Korea.
- Department of Public Health, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea.
| | - Choong Hwan Lee
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, 05029, Republic of Korea.
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Li Y, Qiao X, Feng Y, Zhou R, Zhang K, Pan Y, Yan T, Yan L, Yang S, Wei X, Li P, Xu C, Lv Z, Tian Z. Characterization of the gut microbiota and fecal metabolome in the osteosarcoma mouse model. Aging (Albany NY) 2024; 16:205951. [PMID: 38967635 DOI: 10.18632/aging.205951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 05/21/2024] [Indexed: 07/06/2024]
Abstract
Previous studies have reported the correlation between gut microbiota (GM), GM-derived metabolites, and various intestinal and extra-intestinal cancers. However, limited studies have investigated the correlation between GM, GM-derived metabolites, and osteosarcoma (OS). This study successfully established a female BALB/c nude mouse model of OS. Mice (n = 14) were divided into the following two groups (n = 7/group): OS group named OG, injected with Saos-2 OS cells; normal control group named NCG, injected with Matrigel. The GM composition and metabolites were characterized using 16S rDNA sequencing and untargeted metabolomics, respectively. Bioinformatics analysis revealed that amino acid metabolism was dysregulated in OS. The abundances of bone metabolism-related genera Alloprevotella, Rikenellaceae_RC9_gut_group, and Muribaculum were correlated with amino acid metabolism, especially histidine metabolism. These findings suggest the correlation between GM, GM-derived metabolites, and OS pathogenesis. Clinical significance: The currently used standard therapeutic strategies for OS, including surgery, chemotherapy, and radiation, are not efficacious. The findings of this study provided novel insights for developing therapeutic, diagnostic, and prognostic strategies for OS.
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Affiliation(s)
- Yuan Li
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Xiaochen Qiao
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Yi Feng
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Ruhao Zhou
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Kun Zhang
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Yongchun Pan
- Department of Orthopedics, Third People's Hospital of Datong City, Datong 037006, Shanxi, P.R. China
| | - Ting Yan
- Translational Medicine Center, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
| | - Lei Yan
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Sen Yang
- Department of Orthopedics, The Second People's Hospital of Changzhi, Changzhi 046000, Shanxi, P.R. China
| | - Xiaochun Wei
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Pengcui Li
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Chaojian Xu
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Zhi Lv
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
| | - Zhi Tian
- Second Clinical Medical College, Shanxi Medical University, Taiyuan 030001, Shanxi, P.R. China
- Department of Orthopedics, The Second Hospital of Shanxi Medical University, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Taiyuan 030001, Shanxi, P.R. China
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Taylor GS, Smith K, Scragg J, McDonald TJ, Shaw JA, West DJ, Roberts LD. The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes. Diabetologia 2024; 67:1413-1428. [PMID: 38662134 PMCID: PMC11153288 DOI: 10.1007/s00125-024-06153-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/07/2024] [Indexed: 04/26/2024]
Abstract
AIMS/HYPOTHESIS Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined byV ˙ O 2peak . METHODS Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3-200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed byV ˙ O 2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60%V ˙ O 2peak ) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity (V ˙ O 2peak ) during exercise in health and type 1 diabetes. RESULTS Maximal aerobic capacity (V ˙ O 2peak ) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23×10-5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity (V ˙ O 2peak ) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). CONCLUSIONS/INTERPRETATION The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes.
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Affiliation(s)
- Guy S Taylor
- Human Nutrition & Exercise Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Kieran Smith
- Human Nutrition & Exercise Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
- The Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Oxford, UK
| | - Jadine Scragg
- Human Nutrition & Exercise Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - James A Shaw
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Daniel J West
- Human Nutrition & Exercise Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.
| | - Lee D Roberts
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
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Gao J, Xiang X, Yan Q, Ding Y. CDCS-TCM: A framework based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine. JOURNAL OF ETHNOPHARMACOLOGY 2024; 328:118100. [PMID: 38537843 DOI: 10.1016/j.jep.2024.118100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/08/2024] [Accepted: 03/21/2024] [Indexed: 04/14/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Traditional Chinese medicine, with the feature of synergistic effects of multi-component, multi-pathway and multi-target, plays an important role in the treatment of cancer, cardiovascular and cerebrovascular diseases, etc. However, chemical components in traditional Chinese medicine are complex and most of the pharmacological mechanisms remain unclear, especially the relationships of chemical components change during the metabolic process. AIM OF STUDY Our aim is to provide a method based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine. MATERIALS AND METHODS We proposed a framework named CDCS-TCM to analyze the causality and dynamic correlation between substances in the metabolic process of traditional Chinese medicine. Our method mainly consists two parts. The first part is to discover the local and global causality by the causality network. The second part is to investigate the dynamic correlations and identify the essential substance by dynamic substance correlation network. RESULTS We developed a CDCS-TCM method to analyze the causality and dynamic correlation of substances. Using the XiangDan Injection for ischemic stroke as an example, we have identified the important substances in the metabolic process including substance pairs with strong causality and the dynamic changes of the core effector substance clusters. CONCLUSION The proposed framework will be useful for exploring the correlations of active ingredients in traditional Chinese medicine more effectively and will provide a new perspective for the elucidation of drug action mechanisms and the new drug discovery.
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Affiliation(s)
- Jiaxuan Gao
- School of Science, Jiangnan University, Wuxi, Jiangsu, PR China.
| | - Xiaoyang Xiang
- School of Science, Jiangnan University, Wuxi, Jiangsu, PR China.
| | - Qunfang Yan
- School of Science, Jiangnan University, Wuxi, Jiangsu, PR China.
| | - Yanrui Ding
- School of Science, Jiangnan University, Wuxi, Jiangsu, PR China.
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Fux E, Lenski M, Bendt AK, Otvos JD, Ivanisevic J, De Bruyne S, Cavalier E, Friedecký D. A global perspective on the status of clinical metabolomics in laboratory medicine - a survey by the IFCC metabolomics working group. Clin Chem Lab Med 2024; 0:cclm-2024-0550. [PMID: 38915248 DOI: 10.1515/cclm-2024-0550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 06/15/2024] [Indexed: 06/26/2024]
Abstract
OBJECTIVES Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.
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Affiliation(s)
- Elie Fux
- Roche Diagnostics GmbH, Penzberg, Germany
| | - Marie Lenski
- ULR 4483, IMPECS - IMPact de l'Environnement Chimique sur la Santé humaine, Univ. Lille, Institut Pasteur de Lille et Unité Fonctionnelle de Toxicologie, CHU Lille, Lille, France
| | - Anne K Bendt
- Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - James D Otvos
- Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Julijana Ivanisevic
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Sander De Bruyne
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Etienne Cavalier
- Department of Clinical Chemistry, CIRM, University of Liège, CHU de Liège, Liège, Belgium
| | - David Friedecký
- Department of Clinical Biochemistry, University Hospital Olomouc, Olomouc, Czechia
- Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic
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8
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Yang H, Suh DH, Jung ES, Lee Y, Liu KH, Do IG, Lee CH, Park CY. Ezetimibe, Niemann-Pick C1 like 1 inhibitor, modulates hepatic phospholipid metabolism to alleviate fat accumulation. Front Pharmacol 2024; 15:1406493. [PMID: 38953111 PMCID: PMC11215075 DOI: 10.3389/fphar.2024.1406493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 05/13/2024] [Indexed: 07/03/2024] Open
Abstract
Background Ezetimibe, which lowers cholesterol by blocking the intestinal cholesterol transporter Niemann-Pick C1 like 1, is reported to reduce hepatic steatosis in humans and animals. Here, we demonstrate the changes in hepatic metabolites and lipids and explain the underlying mechanism of ezetimibe in hepatic steatosis. Methods We fed Otsuka Long-Evans Tokushima Fatty (OLETF) rats a high-fat diet (60 kcal % fat) with or vehicle (control) or ezetimibe (10 mg kg-1) via stomach gavage for 12 weeks and performed comprehensive metabolomic and lipidomic profiling of liver tissue. We used rat liver tissues, HepG2 hepatoma cell lines, and siRNA to explore the underlying mechanism. Results In OLETF rats on a high-fat diet, ezetimibe showed improvements in metabolic parameters and reduction in hepatic fat accumulation. The comprehensive metabolomic and lipidomic profiling revealed significant changes in phospholipids, particularly phosphatidylcholines (PC), and alterations in the fatty acyl-chain composition in hepatic PCs. Further analyses involving gene expression and triglyceride assessments in rat liver tissues, HepG2 hepatoma cell lines, and siRNA experiments unveiled that ezetimibe's mechanism involves the upregulation of key phospholipid biosynthesis genes, CTP:phosphocholine cytidylyltransferase alpha and phosphatidylethanolamine N-methyl-transferase, and the phospholipid remodeling gene lysophosphatidylcholine acyltransferase 3. Conclusion This study demonstrate that ezetimibe improves metabolic parameters and reduces hepatic fat accumulation by influencing the composition and levels of phospholipids, specifically phosphatidylcholines, and by upregulating genes related to phospholipid biosynthesis and remodeling. These findings provide valuable insights into the molecular pathways through which ezetimibe mitigates hepatic fat accumulation, emphasizing the role of phospholipid metabolism.
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Affiliation(s)
- Hyekyung Yang
- Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dong Ho Suh
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea
| | - Eun Sung Jung
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea
| | - Yoonjin Lee
- Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kwang-Hyeon Liu
- College of Pharmacy and Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea
| | - In-Gu Do
- Department of Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Choong Hwan Lee
- Department of Bioscience and Biotechnology, Konkuk University, Seoul, Republic of Korea
| | - Cheol-Young Park
- Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Zhang Q, Feng Y, Wu D, Xie Y, Wu G, Wu W, Wang H, Liu X, Fan L, Xiang B, Sun Q, Li Y, Wang Y, Ye H. Serum Metabolomic and Lipidomic Profiling Reveals the Signature for Postoperative Obesity among Adult-Onset Craniopharyngioma. Metabolites 2024; 14:338. [PMID: 38921473 PMCID: PMC11205291 DOI: 10.3390/metabo14060338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 06/13/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
Craniopharyngioma patients often suffer from a diminished quality of life after surgery, which is usually associated with metabolic disorders and hypothalamic obesity. However, the precise etiology of these conditions remains elusive. To identify the metabolic changes after surgery, we conducted a cross-sectional study using metabolomic and lipidomic analysis to profile metabolic alterations in adult-onset craniopharyngioma patients with postoperative obesity. A cohort of 120 craniopharyngioma patients who had undergone surgery were examined. Differential analyses, including clinical characteristics, serum metabolome, and lipidome, were conducted across distinct body mass index (BMI) groups. Our findings indicated no statistically significant differences in age, sex, and fasting blood glucose among postoperative craniopharyngioma patients when stratified by BMI. However, a noteworthy difference was observed in uric acid and blood lipid levels. Further investigation revealed that alterations in metabolites and lipids were evidently correlated with increased BMI, indicating that postoperative obesity of craniopharyngioma patients affected their whole-body metabolism. Additionally, the multi-omics analysis identified specific metabolites and lipids, including uric acid and DG(18:2/20:4), as contributors to the metabolic disorders associated with postoperative obesity of craniopharyngioma patients. This work provides valuable insight into the involvement of metabolites and lipids in metabolic disorders subsequent to craniopharyngioma surgery.
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Affiliation(s)
- Qiongyue Zhang
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Yonghao Feng
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
- Department of Endocrinology, Jinshan Hospital, Fudan University, Shanghai 201508, China
| | - Dou Wu
- Department of Ultrasonography, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - Yinyin Xie
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Guoming Wu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Wei Wu
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Hui Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xiaoyu Liu
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
- College of Life Sciences, Inner Mongolia University, Hohhot 010021, China
| | - Linling Fan
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Boni Xiang
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Quanya Sun
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Yiming Li
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
| | - Yongfei Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
| | - Hongying Ye
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China (Y.X.); (W.W.)
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10
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Pflieger T, Venkatesh R, Dachtler M, Cooke K, Laufer S, Lunter D. Influence of design parameters on sustained drug release properties of 3D-printed theophylline tablets. Int J Pharm 2024; 658:124207. [PMID: 38718971 DOI: 10.1016/j.ijpharm.2024.124207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/03/2024] [Accepted: 05/04/2024] [Indexed: 05/14/2024]
Abstract
The application of three-dimensional printing (3DP) in the pharmaceutical industry brings a broad spectrum of benefits to patients by addressing individual needs and improve treatment success. This study investigates the sustained release properties of 3DP tablets containing Theophylline (TPH), which is commonly used to treat respiratory diseases and recently having a comeback due to its potential in the treatment of conditions like Covid-19. Since TPH is a narrow therapeutic window (NTW) drug with serious side effects in the event of overdose, the release properties must be observed particularly closely. We employed a state-of-the-art single screw extrusion 3D printer, which is fed with granules containing the drug. By employing a Taguchi orthogonal array design of experiments (DOE), tablet design parameters and factor related process stability were sought to be evaluated fundamentally. Following this, examinations regarding tailored TPH dosages were undertaken and a relationship between the real printed dose of selected tablet designs and their sustained drug release was established. The release profiles were analyzed using different mathematical model fits and compared in terms of mean dissolution times (MDT). Finally, in-vivo/in-vitro correlation (IVIVC) and physiologically based pharmacokinetic (PBPK) modeling showed that a paradigm patient group could be covered with the dosage forms produced.
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Affiliation(s)
- Thomas Pflieger
- DiHeSys Digital Health Systems GmbH, Marie-Curie-Strasse 19, 73529 Schwaebisch Gmuend, Germany; Chair of Pharmaceutical Technology, Eberhard Karls University, Auf der Morgenstelle 8, 72074 Tuebingen, Germany
| | - Rakesh Venkatesh
- DiHeSys Digital Health Systems GmbH, Marie-Curie-Strasse 19, 73529 Schwaebisch Gmuend, Germany
| | - Markus Dachtler
- DiHeSys Digital Health Systems GmbH, Marie-Curie-Strasse 19, 73529 Schwaebisch Gmuend, Germany
| | - Karin Cooke
- Gen-Plus GmbH & Co. KG, Staffelseestrasse 6, 81477 Munich, Germany
| | - Stefan Laufer
- Chair of Pharmaceutical Chemistry, Eberhard Karls University, Auf der Morgenstelle 8, 72074 Tuebingen, Germany
| | - Dominique Lunter
- Chair of Pharmaceutical Technology, Eberhard Karls University, Auf der Morgenstelle 8, 72074 Tuebingen, Germany.
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11
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Cheng T, Yun Z, Fan S, Wang H, Xue W, Zhang X, Jia B, Hu Y. Causal association between blood metabolites and risk of hypertension: a Mendelian randomization study. Front Cardiovasc Med 2024; 11:1373480. [PMID: 38911515 PMCID: PMC11190327 DOI: 10.3389/fcvm.2024.1373480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/28/2024] [Indexed: 06/25/2024] Open
Abstract
Background Previous studies have indicated a strong link between blood metabolites and hypertension, however the causality of metabolites and hypertension is unknown. Methods Two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between 486 blood metabolites and essential hypertension (EHT). Blood metabolite GWAS data was utilized as the exposure, with EHT GWAS data as the outcome. To further verify the results, another different source of EHT GWAS data was repeatedly analyzed. The major MR analytic approach used to determine causality was inverse variance weighted (IVW), with MR-Egger, Weighted Median, and MR-PRESSO models serving as supplements. We used the Cochran Q test to examine heterogeneity. Horizontal pleiotropy was examined using MR-Egger intercept and MR-PRESSO global test. The MR Steiger test confirmed the causal relationship between blood metabolites and EHT. Results In this study, nine blood metabolites associated with EHT were preliminarily identified by MR analysis, including four known metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid, creatine, hexadecanedioate) and five unknown metabolites. Then another source of EHT GWAS data was repeatedly analyzed for further verification, and two overlapped metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid) were found. There was a negative correlation between N-acetylornithine and EHT (OR = 0.987, 95% CI = 0.980-0.993, P = 1.01 × 10-4), Cochran's Q test suggested there was no heterogeneity (Q = 31.7586, P = 0.1331), MR-Egger intercept and MR-PRESSO global test suggested there was no horizontal pleiotropy (P > 0.05), Leave-one-out analysis indicated that no single single-nucleotide polymorphism (SNP) had a significant effect on the results, and MR Steiger test confirmed that the direction of causality was correct (P < 0.001). There was a negative correlation between X-12510-2-aminooctanoic acid and EHT (OR = 0.982, 95% CI = 0.972-0.993, P = 0.0017), and there was no evidence of heterogeneity or pleiotropy in multiple sensitivity analyses. Conclusion The study discovered some blood metabolites causally linked to EHT, which might lead to new understandings of the pathophysiology of hypertension.
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Affiliation(s)
- Tao Cheng
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
- Clinical Medical College, Beijing University of Chinese Medicine, Beijing, China
| | - Zhangjun Yun
- Clinical Medical College, Beijing University of Chinese Medicine, Beijing, China
| | - Shaowei Fan
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
| | - Huan Wang
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
| | - Wenjing Xue
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
- Clinical Medical College, Beijing University of Chinese Medicine, Beijing, China
| | - Xuesong Zhang
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
| | - Bochao Jia
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
- Clinical Medical College, Beijing University of Chinese Medicine, Beijing, China
| | - Yuanhui Hu
- Department of Cardiological Medicine, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China
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12
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Dong Y, Malitsky S. MetaboReport: from metabolomics data analysis to comprehensive reporting. Bioinformatics 2024; 40:btae373. [PMID: 38885410 PMCID: PMC11209541 DOI: 10.1093/bioinformatics/btae373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/30/2024] [Accepted: 06/13/2024] [Indexed: 06/20/2024] Open
Abstract
MOTIVATION Metabolomics, as an essential tool in systems biology, is now widely accessible to researchers of all levels. Yet challenges remain in data analysis and result interpretation. To address these challenges, we introduced MetaboReport, a versatile and interactive web app that simplifies metabolomics experiment design, data preprocessing, exploration, statistical analysis, visualization, and reporting. RESULTS MetaboReport produces a comprehensive HTML report, including project details, an introduction, interactive plots and tables, statistical results and an in-depth explanations and interpretation of the results. MetaboReport is particularly tailored for research labs and metabolomics core facilities that provide metabolomics services, allowing them to efficiently manage and document different metabolomics projects, and effectively report the metabolomics results to users. AVAILABILITY AND IMPLEMENTATION MetaboReport is freely accessible on https://metaboreport.com, with source code available on GitHub (https://github.com/YonghuiDong/MetReport). Alternatively, users can install MetaboReport as a standalone desktop app (https://metaboreport.sourceforge.io).
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Affiliation(s)
- Yonghui Dong
- FAFU-UCR Joint Center for Horticultural Biology and Metabolomics, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Life Science Core Facilities, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Sergey Malitsky
- Life Science Core Facilities, Weizmann Institute of Science, Rehovot, 76100, Israel
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13
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Xu M, Qian K, Shao H, Yao Y, Nair V, Ye J, Qin A. Metabolomics analysis of CEF cells infected with avian leukosis virus subgroup J based on UHPLC-QE-MS. Poult Sci 2024; 103:103693. [PMID: 38598912 PMCID: PMC11017069 DOI: 10.1016/j.psj.2024.103693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/21/2024] [Accepted: 03/24/2024] [Indexed: 04/12/2024] Open
Abstract
Avian leukosis virus subgroup J (ALV-J) is a retrovirus that can cause immunosuppression and tumors in chicken. However, relative pathogenesis is still not clear. At present, metabolomics has shown great potential in the screening of tumor metabolic markers, prognostic evaluation, and drug target design. In this study, we utilize an untargeted metabolomics approach based on ultrahigh-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS) to analyze the metabolic changes in chicken embryo fibroblast (CEF) cells infected by ALV-J. We found that ALV-J infection significantly altered a wealth of metabolites compared with control group. Additionally, most of the differentially expressed metabolites belonged to lipid metabolism, purine nucleotide metabolism and amino acid metabolism. Among them, the proportion of lipid metabolites account for the highest proportion (around 31%). Results suggest that these changes may be conductive to the formation of virion, thereby promoting the replication of ALV-J. These data provided metabolic evidence and potential biomarkers for the cellular metabolic changes induced by ALV-J, and provided important insight for further understanding the replication needs and pathogenesis of ALV-J.
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Affiliation(s)
- Menglu Xu
- Ministry of Education Key Lab for Avian Preventive Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, P.R. China
| | - Kun Qian
- Ministry of Education Key Lab for Avian Preventive Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, P.R. China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, Jiangsu, 225009, P.R. China
| | - Hongxia Shao
- Ministry of Education Key Lab for Avian Preventive Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, P.R. China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, Jiangsu, 225009, P.R. China
| | - Yongxiu Yao
- The Pirbright Institute & UK-China Centre of Excellence on Avian Disease Research, Pirbright, Surrey, GU24 0NF, United Kingdom
| | - Venugopal Nair
- The Pirbright Institute & UK-China Centre of Excellence on Avian Disease Research, Pirbright, Surrey, GU24 0NF, United Kingdom
| | - Jianqiang Ye
- Ministry of Education Key Lab for Avian Preventive Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, P.R. China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, Jiangsu, 225009, P.R. China
| | - Aijian Qin
- Ministry of Education Key Lab for Avian Preventive Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, P.R. China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou, Jiangsu, 225009, P.R. China.
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14
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Cui P, Li X, Huang C, Lin D. Metabolomics-driven discovery of therapeutic targets for cancer cachexia. J Cachexia Sarcopenia Muscle 2024; 15:781-793. [PMID: 38644205 PMCID: PMC11154780 DOI: 10.1002/jcsm.13465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 12/07/2023] [Accepted: 01/09/2024] [Indexed: 04/23/2024] Open
Abstract
Cancer cachexia (CC) is a devastating metabolic syndrome characterized by skeletal muscle wasting and body weight loss, posing a significant burden on the health and survival of cancer patients. Despite ongoing efforts, effective treatments for CC are still lacking. Metabolomics, an advanced omics technique, offers a comprehensive analysis of small-molecule metabolites involved in cellular metabolism. In CC research, metabolomics has emerged as a valuable tool for identifying diagnostic biomarkers, unravelling molecular mechanisms and discovering potential therapeutic targets. A comprehensive search strategy was implemented to retrieve relevant articles from primary databases, including Web of Science, Google Scholar, Scopus and PubMed, for CC and metabolomics. Recent advancements in metabolomics have deepened our understanding of CC by uncovering key metabolic signatures and elucidating underlying mechanisms. By targeting crucial metabolic pathways including glucose metabolism, amino acid metabolism, fatty acid metabolism, bile acid metabolism, ketone body metabolism, steroid metabolism and mitochondrial energy metabolism, it becomes possible to restore metabolic balance and alleviate CC symptoms. This review provides a comprehensive summary of metabolomics studies in CC, focusing on the discovery of potential therapeutic targets and the evaluation of modulating specific metabolic pathways for CC treatment. By harnessing the insights derived from metabolomics, novel interventions for CC can be developed, leading to improved patient outcomes and enhanced quality of life.
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Affiliation(s)
- Pengfei Cui
- College of Food and PharmacyXuchang UniversityXuchangChina
| | - Xiaoyi Li
- Xuchang Central HospitalXuchangChina
| | - Caihua Huang
- Research and Communication Center of Exercise and HealthXiamen University of TechnologyXiamenChina
| | - Donghai Lin
- Key Laboratory for Chemical Biology of Fujian Province, MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, College of Chemistry and Chemical EngineeringXiamen UniversityXiamenChina
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15
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Hou Y, Xiao Z, Zhu Y, Li Y, Liu Q, Wang Z. Blood metabolites and chronic kidney disease: a Mendelian randomization study. BMC Med Genomics 2024; 17:147. [PMID: 38807172 PMCID: PMC11131213 DOI: 10.1186/s12920-024-01918-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/20/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Human blood metabolites have demonstrated close associations with chronic kidney disease (CKD) in observational studies. Nonetheless, the causal relationship between metabolites and CKD is still unclear. This study aimed to assess the associations between metabolites and CKD risk. METHODS We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 1400 blood metabolites and eight phenotypes (outcomes) (CKD, estimated glomerular filtration rate(eGFR), urine albumin to creatinine ratio, rapid progress to CKD, rapid decline of eGFR, membranous nephropathy, immunoglobulin A nephropathy, and diabetic nephropathy). The inverse variance weighted (IVW), MR-Egger, and weighted median were used to investigate the causal relationship. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, MR-PRESSO Global test, and leave-one-out analysis. Bonferroni correction was used to test the strength of the causal relationship. RESULTS Through the MR analysis of 1400 metabolites and eight clinical phenotypes, a total of 48 metabolites were found to be associated with various outcomes. Among them, N-acetylleucine (OR = 0.923, 95%CI: 0.89-0.957, PIVW = 1.450 × 10-5) has a strong causal relationship with lower risk of CKD after the Bonferroni-corrected test, whereas Glycine to alanine ratio has a strong causal relationship with higher risk of CKD (OR = 1.106, 95%CI: 1.063-1.151, PIVW = 5.850 × 10-7). No horizontal pleiotropy and heterogeneity were detected. CONCLUSION Our study offers groundbreaking insights into the integration of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for CKD. It underscores 48 metabolites as potential causal candidates, meriting further investigation.
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Affiliation(s)
- Yawei Hou
- Institute of Chinese Medical Literature and Culture, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhenwei Xiao
- Department of Nephrology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yushuo Zhu
- Department of Emergency and Critical Care Medicine, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yameng Li
- The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Qinglin Liu
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhenguo Wang
- Institute of Chinese Medical Literature and Culture, Shandong University of Traditional Chinese Medicine, Jinan, China.
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16
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Zheng R, Su R, Fan Y, Xing F, Huang K, Yan F, Chen H, Liu B, Fang L, Du Y, Zhou F, Wang D, Feng S. Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures. Anal Chem 2024; 96:8772-8781. [PMID: 38743842 DOI: 10.1021/acs.analchem.4c01171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.
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Affiliation(s)
- Ran Zheng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Rui Su
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Yusi Fan
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Software, Jilin University, Changchun 130021, China
| | - Fan Xing
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Keke Huang
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Fei Yan
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Huanwen Chen
- School of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Botong Liu
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Laiping Fang
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
| | - Yechao Du
- Department of General Surgery Center, First Hospital of Jilin University, 1 Xinmin Street Changchun, Jilin 130012, China
| | - Fengfeng Zhou
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Software, Jilin University, Changchun 130021, China
| | - Daguang Wang
- Department of Gastric Colorectal and Anal Surgery, First Hospital of Jilin University, 1 Xinmin Street Changchun, Jilin 130012, China
| | - Shouhua Feng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130021, China
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17
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Du Y, Wijaya WA, Liu WH. Advancements in metabolomics research in benign gallbladder diseases: A review. Medicine (Baltimore) 2024; 103:e38126. [PMID: 38788004 PMCID: PMC11124670 DOI: 10.1097/md.0000000000038126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 04/12/2024] [Indexed: 05/26/2024] Open
Abstract
The burgeoning field of metabolomics has piqued the interest of researchers in the context of benign gallbladder diseases, which include conditions such as gallbladder polyps, gallstones, and cholecystitis, which are common digestive system disorders. As metabolomics continues to advance, researchers have increasingly focused their attention on its applicability in the study of benign gallbladder diseases to provide new perspectives for diagnostic, therapeutic, and prognostic evaluation. This comprehensive review primarily describes the techniques of liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance and their respective applications in the study of benign gallbladder disease. Metabolomics has made remarkable progress in various aspects of these diseases, ranging from early diagnosis, etiological research, assessment of disease progression and prognosis, and optimization of therapeutic strategies. However, challenges remain in the field of metabolomics in the study of benign gallbladder diseases. These include issues related to data processing and analysis, biomarker discovery and validation, interdisciplinary research integration, and the advancement of personalized medicine. This article attempts to summarize research findings to date, highlight future research directions, and provide a reference point for metabolomics research in benign gallbladder disease.
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Affiliation(s)
- Yanzhang Du
- Department of Gastroenterology, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Wennie A. Wijaya
- West China Hospital School of Medicine, Sichuan University, Chengdu, China
| | - Wei Hui Liu
- Department of Gastroenterology, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
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18
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Hristova-Panusheva K, Xenodochidis C, Georgieva M, Krasteva N. Nanoparticle-Mediated Drug Delivery Systems for Precision Targeting in Oncology. Pharmaceuticals (Basel) 2024; 17:677. [PMID: 38931344 PMCID: PMC11206252 DOI: 10.3390/ph17060677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 06/28/2024] Open
Abstract
Nanotechnology has emerged as a transformative force in oncology, facilitating advancements in site-specific cancer therapy and personalized oncomedicine. The development of nanomedicines explicitly targeted to cancer cells represents a pivotal breakthrough, allowing the development of precise interventions. These cancer-cell-targeted nanomedicines operate within the intricate milieu of the tumour microenvironment, further enhancing their therapeutic efficacy. This comprehensive review provides a contemporary perspective on precision cancer medicine and underscores the critical role of nanotechnology in advancing site-specific cancer therapy and personalized oncomedicine. It explores the categorization of nanoparticle types, distinguishing between organic and inorganic variants, and examines their significance in the targeted delivery of anticancer drugs. Current insights into the strategies for developing actively targeted nanomedicines across various cancer types are also provided, thus addressing relevant challenges associated with drug delivery barriers. Promising future directions in personalized cancer nanomedicine approaches are delivered, emphasising the imperative for continued optimization of nanocarriers in precision cancer medicine. The discussion underscores translational research's need to enhance cancer patients' outcomes by refining nanocarrier technologies in nanotechnology-driven, site-specific cancer therapy.
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Affiliation(s)
- Kamelia Hristova-Panusheva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. Georgi Bonchev” Str., Bl. 21, 1113 Sofia, Bulgaria; (K.H.-P.); (C.X.)
| | - Charilaos Xenodochidis
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. Georgi Bonchev” Str., Bl. 21, 1113 Sofia, Bulgaria; (K.H.-P.); (C.X.)
| | - Milena Georgieva
- Institute of Molecular Biology “Acad. R. Tsanev”, Bulgarian Academy of Sciences, “Acad. Georgi Bonchev” Str., Bl. 21, 1113 Sofia, Bulgaria;
| | - Natalia Krasteva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. Georgi Bonchev” Str., Bl. 21, 1113 Sofia, Bulgaria; (K.H.-P.); (C.X.)
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Li H, Li L, Huang QQ, Yang SY, Zou JJ, Xiao F, Xiang Q, Liu X, Yu R. Global status and trends of metabolomics in diabetes: A literature visualization knowledge graph study. World J Diabetes 2024; 15:1021-1044. [PMID: 38766424 PMCID: PMC11099375 DOI: 10.4239/wjd.v15.i5.1021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 01/28/2024] [Accepted: 03/18/2024] [Indexed: 05/10/2024] Open
Abstract
BACKGROUND Diabetes is a metabolic disease characterized by hyperglycemia, which has increased the global medical burden and is also the main cause of death in most countries. AIM To understand the knowledge structure of global development status, research focus, and future trend of the relationship between diabetes and metabolomics in the past 20 years. METHODS The articles about the relationship between diabetes and metabolomics in the Web of Science Core Collection were retrieved from 2002 to October 23, 2023, and the relevant information was analyzed using CiteSpace6.2.2R (CiteSpace), VOSviewer6.1.18 (VOSviewer), and Bibliometrix software under R language. RESULTS A total of 3123 publications were included from 2002 to 2022. In the past two decades, the number of publications and citations in this field has continued to increase. The United States, China, Germany, the United Kingdom, and other relevant funds, institutions, and authors have significantly contributed to this field. Scientific Reports and PLoS One are the journals with the most publications and the most citations. Through keyword co-occurrence and cluster analysis, the closely related keywords are "insulin resistance", "risk", "obesity", "oxidative stress", "metabolomics", "metabolites" and "biomarkers". Keyword clustering included cardiovascular disease, gut microbiota, metabonomics, diabetic nephropathy, molecular docking, gestational diabetes mellitus, oxidative stress, and insulin resistance. Burst detection analysis of keyword depicted that "Gene", "microbiota", "validation", "kidney disease", "antioxidant activity", "untargeted metabolomics", "management", and "accumulation" are knowledge frontiers in recent years. CONCLUSION The relationship between metabolomics and diabetes is receiving extensive attention. Diabetic nephropathy, diabetic cardiovascular disease, and kidney disease are key diseases for future research in this field. Gut microbiota, molecular docking, and untargeted metabolomics are key research directions in the future. Antioxidant activity, gene, validation, mass spectrometry, management, and accumulation are at the forefront of knowledge frontiers in this field.
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Affiliation(s)
- Hong Li
- College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Liu Li
- College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Qiu-Qing Huang
- College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Si-Yao Yang
- College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Jun-Ju Zou
- College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Fan Xiao
- College of International Education, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Qin Xiang
- Department of Science and Technology, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Xiu Liu
- Hunan Key Laboratory of TCM Prescription and Syndromes Translational Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
| | - Rong Yu
- Hunan Key Laboratory of TCM Prescription and Syndromes Translational Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan Province, China
- College of Graduate, Hunan University of Chinese Medicine, Hunan Changsha, Hunan Province, China
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Henriquez JE, Badwaik VD, Bianchi E, Chen W, Corvaro M, LaRocca J, Lunsman TD, Zu C, Johnson KJ. From Pipeline to Plant Protection Products: Using New Approach Methodologies (NAMs) in Agrochemical Safety Assessment. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:10710-10724. [PMID: 38688008 DOI: 10.1021/acs.jafc.4c00958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
The human population will be approximately 9.7 billion by 2050, and food security has been identified as one of the key issues facing the global population. Agrochemicals are an important tool available to farmers that enable high crop yields and continued access to healthy foods, but the average new agrochemical active ingredient takes more than ten years, 350 million dollars, and 20,000 animals to develop and register. The time, monetary, and animal costs incentivize the use of New Approach Methodologies (NAMs) in early-stage screening to prioritize chemical candidates. This review outlines NAMs that are currently available or can be adapted for use in early-stage screening agrochemical programs. It covers new in vitro screens that are on the horizon in key areas of regulatory concern. Overall, early-stage screening with NAMs enables the prioritization of development for agrochemicals without human and environmental health concerns through a more directed, agile, and iterative development program before animal-based regulatory testing is even considered.
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Affiliation(s)
| | - Vivek D Badwaik
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Enrica Bianchi
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Jessica LaRocca
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Chengli Zu
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Kamin J Johnson
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
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21
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Li B, Zhao X, Xie W, Hong Z, Cao Y, Ding Y, Zhang Y. Causal association of circulating metabolites with diabetic retinopathy: a bidirectional Mendelian randomization analysis. Front Endocrinol (Lausanne) 2024; 15:1359502. [PMID: 38800471 PMCID: PMC11116606 DOI: 10.3389/fendo.2024.1359502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 04/24/2024] [Indexed: 05/29/2024] Open
Abstract
Introduction The retina is a highly metabolically active tissue, and there is a lack of clarity about the relationship between metabolites and diabetic retinopathy (DR). This study used two-sample bidirectional Mendelian randomization (MR) analyses to identify causal relationships between metabolites and DR. Methods Genetic variants were selected from the open-access Genome-Wide Association Studies (GWAS) summary database as proxies for the 1400 most recently published metabolites. MR analysis was performed to examine associations between these metabolite traits and DR. Single nucleotide polymorphism (SNP) data that were significantly associated with exposure were screened through association analysis. Validated instrumental variables (IVs) were obtained by removing SNPs with linkage disequilibrium (LD) and F-statistic values below 10. MR analyses were performed using the inverse variance weighted (IVW) method as the primary approach. The robustness of the results was verified by sensitivity analyses, including assessments of heterogeneity, horizontal pleiotropy, and the leave-one-out method. Results In the IVW approach and in the primary analysis of several sensitivity analyses, genetically determined glycolithocholate sulfate levels, androstenediol (3 beta, 17 beta) monosulfate (1) levels, 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4) levels, 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels, 1-oleoyl-2-linoleoyl-GPE (18:1/18:2) levels, X-26109 levels, N6-methyllysine levels, (N6,N6-dimethyllysine levels), and (N2-acetyl,N6,N6-dimethyllysine levels) were negatively associated with the risk of DR. 5-hydroxymethyl-2-furoylcarnitine levels and the glutamate-to-alanine ratio were positively associated with the risk of DR. No reverse causal association was found between DR and metabolites. Discussion This MR study suggests that nine metabolites may have a protective effect in DR, while two metabolites may be associated with an increased risk of DR. However, further research is needed to confirm these findings. Supplementation with beneficial metabolites may reduce DR risk and could potentially be a novel therapeutic approach to DR treatment.
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Affiliation(s)
- Bo Li
- Department of Endocrinology, Quanzhou First Hospital, Affiliated to Fujian Medical University, Quanzhou, Fujian, China
- Hubei Key Laboratory of Embryonic Stem Cell Research, Biomedical Research Institute, Hubei University of Medicine, Shiyan, Hubei, China
| | - Xu Zhao
- Emergency and Critical Care Center, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Wanrun Xie
- Department of Endocrinology, Quanzhou First Hospital, Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Zhenzhen Hong
- Department of Endocrinology, Quanzhou First Hospital, Affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Ye Cao
- Department of Cardiology, Fujian Provincial Hospital, Shengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- Department of Cardiology, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yan Ding
- Hubei Key Laboratory of Embryonic Stem Cell Research, Biomedical Research Institute, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yi Zhang
- Department of Endocrinology, Quanzhou First Hospital, Affiliated to Fujian Medical University, Quanzhou, Fujian, China
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Steuer AE, Wartmann Y, Schellenberg R, Mantinieks D, Glowacki LL, Gerostamoulos D, Kraemer T, Brockbals L. Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning? Metabolomics 2024; 20:51. [PMID: 38722380 PMCID: PMC11081988 DOI: 10.1007/s11306-024-02117-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/20/2024] [Indexed: 05/12/2024]
Abstract
INTRODUCTION The (un)targeted analysis of endogenous compounds has gained interest in the field of forensic postmortem investigations. The blood metabolome is influenced by many factors, and postmortem specimens are considered particularly challenging due to unpredictable decomposition processes. OBJECTIVES This study aimed to systematically investigate the influence of the time since death on endogenous compounds and its relevance in designing postmortem metabolome studies. METHODS Femoral blood samples of 427 authentic postmortem cases, were collected at two time points after death (854 samples in total; t1: admission to the institute, 1.3-290 h; t2: autopsy, 11-478 h; median ∆t = 71 h). All samples were analyzed using an untargeted metabolome approach, and peak areas were determined for 38 compounds (acylcarnitines, amino acids, phospholipids, and others). Differences between t2 and t1 were assessed by Wilcoxon signed-ranked test (p < 0.05). Moreover, all samples (n = 854) were binned into time groups (6 h, 12 h, or 24 h intervals) and compared by Kruskal-Wallis/Dunn's multiple comparison tests (p < 0.05 each) to investigate the effect of the estimated time since death. RESULTS Except for serine, threonine, and PC 34:1, all tested analytes revealed statistically significant changes between t1 and t2 (highest median increase 166%). Unpaired analysis of all 854 blood samples in-between groups indicated similar results. Significant differences were typically observed between blood samples collected within the first and later than 48 h after death, respectively. CONCLUSIONS To improve the consistency of comprehensive data evaluation in postmortem metabolome studies, it seems advisable to only include specimens collected within the first 2 days after death.
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Affiliation(s)
- Andrea E Steuer
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland.
| | - Yannick Wartmann
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland
| | - Rena Schellenberg
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland
| | - Dylan Mantinieks
- Department of Forensic Medicine, Monash University, Victoria, Australia
- Victorian Institute of Forensic Medicine, Victoria, Australia
| | | | - Dimitri Gerostamoulos
- Department of Forensic Medicine, Monash University, Victoria, Australia
- Victorian Institute of Forensic Medicine, Victoria, Australia
| | - Thomas Kraemer
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland
| | - Lana Brockbals
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057, Zurich, Switzerland
- Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Sydney, Australia
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23
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Laus F, Bazzano M, Spaterna A, Laghi L, Marchegiani A. Nuclear Magnetic Resonance (NMR) Metabolomics: Current Applications in Equine Health Assessment. Metabolites 2024; 14:269. [PMID: 38786746 PMCID: PMC11123227 DOI: 10.3390/metabo14050269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/29/2024] [Accepted: 04/30/2024] [Indexed: 05/25/2024] Open
Abstract
Metabolomics can allow for the comprehensive identification of metabolites within biological systems, at given time points, in physiological and pathological conditions. In the last few years, metabolomic analysis has gained popularity both in human and in veterinary medicine, showing great potential for novel applications in clinical activity. The aim of applying metabolomics in clinical practice is understanding the mechanisms underlying pathological conditions and the influence of certain stimuli (i.e., drugs, nutrition, exercise) on body systems, in the attempt of identifying biomarkers that can help in the diagnosis of diseases. Proton Nuclear Magnetic Resonance spectroscopy (1H-NMR) is well tailored to be used as an analytical platform for metabolites' detection at the base of metabolomics studies, due to minimal sample preparation and high reproducibility. In this mini-review article, the scientific production of NMR metabolomic applications to equine medicine is examined. The research works are very different in methodology and difficult to compare. Studies are mainly focused on exercise, reproduction, and nutrition, other than respiratory and musculoskeletal diseases. The available information on this topic is still scant, but a greater collection of data could allow researchers to define new reliable markers to be used in clinical practice for diagnostic and therapeutical purposes.
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Affiliation(s)
- Fulvio Laus
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione, 93/95, 62024 Matelica, Italy; (F.L.); (A.S.); (A.M.)
| | - Marilena Bazzano
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione, 93/95, 62024 Matelica, Italy; (F.L.); (A.S.); (A.M.)
| | - Andrea Spaterna
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione, 93/95, 62024 Matelica, Italy; (F.L.); (A.S.); (A.M.)
| | - Luca Laghi
- Department of Agricultural and Food Sciences, University of Bologna, 47521 Cesena, Italy;
| | - Andrea Marchegiani
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione, 93/95, 62024 Matelica, Italy; (F.L.); (A.S.); (A.M.)
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Virgens GS, Oliveira J, Cardoso MIO, Teodoro JA, Amaral DT. BioProtIS: Streamlining protein-ligand interaction pipeline for analysis in genomic and transcriptomic exploration. J Mol Graph Model 2024; 128:108721. [PMID: 38308972 DOI: 10.1016/j.jmgm.2024.108721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/22/2024] [Accepted: 01/24/2024] [Indexed: 02/05/2024]
Abstract
The identification of protein-ligand interactions plays a pivotal role in elucidating biological processes and discovering potential bioproducts. Harnessing the capabilities of computational methods in drug discovery, we introduce an innovative Inverted Virtual Screening (IVS) pipeline. This pipeline Integrated molecular dynamics and docking analyses to ensure that protein structures are not only energetically favorable but also representative of stable conformations. The primary objective of this pipeline is to automate and streamline the analysis of protein-ligand interactions at both genomic and transcriptomic scales. In the contemporary post-genomic era, high-throughput computational screening for bioproducts, biological systems, and therapeutic drugs has become a cornerstone practice. This approach offers the promise of cost-effectiveness, time efficiency, and optimization of laboratory work. Nevertheless, a notable deficiency persists in the availability of efficient pipelines capable of automating the virtual screening process, seamlessly integrating input and output, and leveraging the full potential of open-source tools. To bridge this critical gap, we have developed a versatile pipeline known as BioProtIS. This tool seamlessly integrates a suite of state-of-the-art tools, including Modeller, AlphaFold, Gromacs, FPOCKET, and AutoDock Vina, thus facilitating the streamlined docking of ligands with an expansive repertoire of proteins sourced from genomes and transcriptomes, and substrates. To assess the pipeline's performance, we employed the transcriptomes of Cereus jamacaru (a cactus species) and Aspisoma lineatum (firefly), along with the genome of Homo sapiens. This integration not only improves the accuracy of ligand-protein interactions by minimizing replicability deviations but also optimizes the discovery process by enabling the simultaneous evaluation of multiple substrates. Furthermore, our pipeline accommodates distinct testing scenarios, such as blind docking or site-specific targeting, which are invaluable in applications ranging from drug repositioning to the exploration of new allosteric binding sites and toxicity assessments. BioProtIS has been designed with modularity at its core. This inherent flexibility empowers users to make custom modifications directly within the source code, tailoring the pipeline to their specific research needs. Moreover, it lays the foundation for seamless integration of diverse docking algorithms in future iterations, promising ongoing advancements in the field of computational biology. This pipeline is available for free distribution and can be download at: https://github.com/BBMDO/BioProtIS.
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Affiliation(s)
- Graziela Sória Virgens
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil
| | - Júlia Oliveira
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil
| | | | - João Alfredo Teodoro
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil
| | - Danilo T Amaral
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, São Paulo, Brazil.
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25
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Ji G, Zhang J, Feng X, Sheng H, Hu H, Li F, Ma Y, Hu Y, Na R, Yang W, Ma Y. Analysis of blood biochemistry and non-targeted metabolomics of endometritis in dairy cows. Anim Reprod Sci 2024; 264:107460. [PMID: 38564886 DOI: 10.1016/j.anireprosci.2024.107460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 02/11/2024] [Accepted: 03/21/2024] [Indexed: 04/04/2024]
Abstract
The incidence of bovine endometritis, which has a negative impact on the reproduction of dairy cows, has been recently increasing. In this study, the differential markers and metabolites of healthy cows and cows with endometritis were analyzed by measuring blood biochemical indicators and immune factors using biochemical and enzyme-linked immunosorbent assay kits combined with nontargeted metabolomics. The LC-QTOF platform was used to evaluate the serum metabolomics of healthy cows and cows with endometritis after 21-27 days of calving. The results showed that glucose, free fatty acid, calcium, sodium, albumin, and alanine aminotransferase levels were significantly lower in the serum of cows with endometritis than in healthy cows (P < 0.05). However, the serum potassium, interleukin-1, interleukin-6, and tumor necrosis factor levels were significantly higher in cows with endometritis (P < 0.05). In addition, the serum metabolome data analysis of the two groups showed that the expression of 468 metabolites was significantly different (P < 0.05), of which 291 were upregulated and 177 were downregulated. These metabolites were involved in 78 metabolic pathways, including amino acid, nucleotide, carbohydrate, lipid, and vitamin metabolism pathways; signal transduction pathways, and other biological pathways. Taken together, negative energy balance and immune activation, which are related to local abnormalities in amino acid, lipid, and carbohydrate metabolism, were the important causes of endometritis in dairy cows. Metabolites such as glucose, carnosine, dehydroascorbic acid, L-malic acid, tetrahydrofolic acid, and UDP-glucose may be used as key indicators in the hematological diagnosis and treatment of endometritis in dairy cows.
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Affiliation(s)
- Guoshang Ji
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Junxing Zhang
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Xue Feng
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Hui Sheng
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Honghong Hu
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Fen Li
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Yanfen Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Yamei Hu
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Rina Na
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Wenfei Yang
- Ningxia Xin' ao Agriculture and Animal Husbandry Co., Ltd., Lingwu 750406, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China.
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Monyela S, Kayoka PN, Ngezimana W, Nemadodzi LE. Evaluating the Metabolomic Profile and Anti-Pathogenic Properties of Cannabis Species. Metabolites 2024; 14:253. [PMID: 38786730 PMCID: PMC11122914 DOI: 10.3390/metabo14050253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
The Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven to present a highly diverse metabolomic profile with a pool of bioactive metabolites used for numerous pharmacological purposes ranging from anti-inflammatory to antimicrobial. Cannabis sativa has since been an extensive subject of investigation, monopolizing the research. Hence, there are fewer studies with a comprehensive understanding of the composition of bioactive metabolites grown in different environmental conditions, especially C. indica and a few other Cannabis strains. These pharmacological properties are mostly attributed to a few phytocannabinoids and some phytochemicals such as terpenoids or essential oils which have been tested for antimicrobial properties. Many other discovered compounds are yet to be tested for antimicrobial properties. These phytochemicals have a series of useful properties including anti-insecticidal, anti-acaricidal, anti-nematicidal, anti-bacterial, anti-fungal, and anti-viral properties. Research studies have reported excellent antibacterial activity against Gram-positive and Gram-negative multidrug-resistant bacteria as well as methicillin-resistant Staphylococcus aureus (MRSA). Although there has been an extensive investigation on the antimicrobial properties of Cannabis, the antimicrobial properties of Cannabis on phytopathogens and aquatic animal pathogens, mostly those affecting fish, remain under-researched. Therefore, the current review intends to investigate the existing body of research on metabolomic profile and anti-microbial properties whilst trying to expand the scope of the properties of the Cannabis plant to benefit the health of other animal species and plant crops, particularly in agriculture.
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Affiliation(s)
- Shadrack Monyela
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
| | - Prudence Ngalula Kayoka
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
| | - Wonder Ngezimana
- Department of Horticulture, Faculty of Plant and Animal Sciences and Technology, Marondera University of Agricultural Sciences and Technology, Marondera P.O. Box 35, Zimbabwe
| | - Lufuno Ethel Nemadodzi
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
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Dong X, Qu Y, Sheng T, Fan Y, Chen S, Yuan Q, Ma G, Ge Y. HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers. Aging (Albany NY) 2024; 16:7487-7504. [PMID: 38683118 PMCID: PMC11087094 DOI: 10.18632/aging.205779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/03/2024] [Indexed: 05/01/2024]
Abstract
Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.
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Affiliation(s)
- Xun Dong
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Yaoyao Qu
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Tongtong Sheng
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuanming Fan
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Silu Chen
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qinbo Yuan
- Department of Urology, Wuxi Fifth People’s Hospital, Wuxi, China
| | - Gaoxiang Ma
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
- The Clinical Metabolomics Center, China Pharmaceutical University, Nanjing, China
- Deparment of Oncology, Pukou Hospital of Chinese Medicine affiliated to China Pharmaceutical University, Nanjing, China
| | - Yuqiu Ge
- Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, China
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Yarahmadi A, Zare M, Aghayari M, Afkhami H, Jafari GA. Therapeutic bacteria and viruses to combat cancer: double-edged sword in cancer therapy: new insights for future. Cell Commun Signal 2024; 22:239. [PMID: 38654309 PMCID: PMC11040964 DOI: 10.1186/s12964-024-01622-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 04/17/2024] [Indexed: 04/25/2024] Open
Abstract
Cancer, ranked as the second leading cause of mortality worldwide, leads to the death of approximately seven million people annually, establishing itself as one of the most significant health challenges globally. The discovery and identification of new anti-cancer drugs that kill or inactivate cancer cells without harming normal and healthy cells and reduce adverse effects on the immune system is a potential challenge in medicine and a fundamental goal in Many studies. Therapeutic bacteria and viruses have become a dual-faceted instrument in cancer therapy. They provide a promising avenue for cancer treatment, but at the same time, they also create significant obstacles and complications that contribute to cancer growth and development. This review article explores the role of bacteria and viruses in cancer treatment, examining their potential benefits and drawbacks. By amalgamating established knowledge and perspectives, this review offers an in-depth examination of the present research landscape within this domain and identifies avenues for future investigation.
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Affiliation(s)
- Aref Yarahmadi
- Department of Biology, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran
| | - Mitra Zare
- Department of Microbiology, Faculty of Sciences, Kerman Branch, Islamic Azad University, Kerman, Iran
| | - Masoomeh Aghayari
- Department of Microbiology, Faculty of Sciences, Urmia Branch, Islamic Azad University, Urmia, Iran
| | - Hamed Afkhami
- Nervous System Stem Cells Research Center, Semnan University of Medical Sciences, Semnan, Iran.
- Cellular and Molecular Research Center, Qom University of Medical Sciences, Qom, Iran.
- Department of Medical Microbiology, Faculty of Medicine, Shahed University, Tehran, Iran.
| | - Gholam Ali Jafari
- Cellular and Molecular Research Center, Qom University of Medical Sciences, Qom, Iran.
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Guo X, Ou T, Yang X, Song Q, Zhu L, Mi S, Zhang J, Zhang Y, Chen W, Guo J. Untargeted metabolomics based on ultra-high performance liquid chromatography-mass spectrometry/MS reveals the lipid-lowering mechanism of taurine in hyperlipidemia mice. Front Nutr 2024; 11:1367589. [PMID: 38706565 PMCID: PMC11066166 DOI: 10.3389/fnut.2024.1367589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/03/2024] [Indexed: 05/07/2024] Open
Abstract
Introduction Taurine has a prominent lipid-lowering effect on hyperlipidemia. However, a comprehensive analysis of the effects of taurine on endogenous metabolites in hyperlipidemia has not been documented. This study aimed to explore the impact of taurine on multiple metabolites associated with hyperlipidemia. Methods The hyperlipidemic mouse model was induced by high-fat diet (HFD). Taurine was administered via oral gavage at doses of 700 mg/kg/day for 14 weeks. Evaluation of body weight, serum lipid levels, and histopathology of the liver and adipose tissue was performed to confirm the lipid-lowering effect of taurine. Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS)-based metabonomics analyses of serum, urine, feces, and liver, coupled with multivariate data analysis, were conducted to assess changes in the endogenous metabolites. Results and discussion Biochemical and histological examinations demonstrated that taurine administration prevented weight gain and dyslipidemia, and alleviated lipid deposition in the liver and adipose tissue in hyperlipidemic mice. A total of 76 differential metabolites were identified by UPLC-MS-based metabolomics approach, mainly involving BAs, GPs, SMs, DGs, TGs, PUFAs and amino acids. Taurine was found to partially prevent HFDinduced abnormalities in the aforementioned metabolites. Using KEGG database and MetaboAnalyst software, it was determined that taurine effectively alleviates metabolic abnormalities caused by HFD, including fatty acid metabolism, sphingolipid metabolism, glycerophospholipid metabolism, diacylglycerol metabolism, amino acid metabolism, bile acid and taurine metabolism, taurine and hypotaurine metabolism. Moreover, DGs, GPs and SMs, and taurine itself may serve as active metabolites in facilitating various anti-hyperlipidemia signal pathways associated with taurine. This study provides new evidence for taurine to prevent hyperlipidemia.
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Affiliation(s)
- Xinzhe Guo
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Tong Ou
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Xinyu Yang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Qi Song
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Lin Zhu
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Shengquan Mi
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Jing Zhang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Yanzhen Zhang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Wen Chen
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Junxia Guo
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
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Chen Y, Lin J, Tao M. Association between cheese and fish consumption and the occurrence of depression based on European population: mediating role of metabolites. Front Nutr 2024; 11:1322254. [PMID: 38694223 PMCID: PMC11061354 DOI: 10.3389/fnut.2024.1322254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 03/28/2024] [Indexed: 05/04/2024] Open
Abstract
Background The consumption of cheese and fish has been linked to the onset of depression. However, the connection between consuming cheese, consuming fish, experiencing depression, and the pathways that mediate this relationship remains unclear. The purpose of this research was to investigate the potential association between the consumption of cheese and fish and the occurrence of depression. Moreover, it is important to identify any metabolites that might be involved and understand their respective roles and functions. Methods A two-step, two-sample Mendelian randomization (MR) study was conducted using genome-wide association study (GWAS) data on cheese, non-oily fish, and oily fish consumption and depression, along with 12 alternate mediators. The study included a total of 451,486 participants in the cheese consumption group, 460,880 in the non-oily fish consumption group, 460,443 in the oily fish consumption group, and 322,580 with a diagnosis of depression. The single nucleotide polymorphism (SNP) estimates were pooled using inverse-variance weighted, weighted median, MR-Egger, simple mode, and weighted mode. Results The data we collected suggested that consuming more cheese correlated with a lower likelihood of experiencing depression (OR: 0.95; 95% CI: 0.92 to 0.98). Neither non-oily fish nor oily fish consumption was directly linked to depression onset (p = 0.08, p = 0.78, respectively). Although there was a direct causal relationship with depression, the mediating relationship of triglycerides (TG), total cholesterol in large HDL, cholesterol to total lipids ratio in large HDL, free cholesterol to total lipids ratio in large HDL, glycine, and phospholipids to total lipids ratio in very large HDL of cheese intake on depression risk were - 0.002 (95% CI: -0.023 - 0.020), -0.002 (95% CI: -0.049 - 0.045), -0.001 (95% CI: -0.033 - 0.031), -0.001 (95% CI: -0.018 - 0.015), 0.001 (95% CI: -0.035 - 0.037), and - 0.001 (95% CI: -0.024 - 0.021), respectively. The mediating relationship of uridine, free cholesterol to total lipids ratio in large HDL, total cholesterol in large HDL, acetoacetate, and 3-hydroxybutyrate (3-HB) between non-oily fish consumption and depression risk were 0.016 (95% CI: -0.008 - 0.040), 0.011 (95% CI: -1.269 - 1.290), 0.010 (95% CI: -1.316 - 1.335), 0.011 (95% CI: -0.089 - 0.110), and 0.008 (95% CI: -0.051 - 0.068), respectively. The mediation effect of uridine and free cholesterol to total lipids ratio in large HDL between intake of oily fish and the risk of depression was found to be 0.006 (95% CI: -0.015 - 0.028) and - 0.002 (95% CI: -0.020 - 0.017), respectively. The correlation between eating cheese and experiencing depression persisted even when adjusting for other variables like Indian snacks, mango consumption, sushi consumption, and unsalted peanuts using multivariable MR. Conclusion The consumption of cheese and fish influenced the likelihood of experiencing depression, and this may be mediated by certain metabolites in the body. Our study provided a new perspective on the clinical treatment of depression.
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Affiliation(s)
- Yan Chen
- Second Clinical Medical School, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jixin Lin
- Second Clinical Medical School, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ming Tao
- Second Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, China
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Predescu E, Vaidean T, Rapciuc AM, Sipos R. Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review. Int J Mol Sci 2024; 25:4385. [PMID: 38673970 PMCID: PMC11050195 DOI: 10.3390/ijms25084385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.
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Affiliation(s)
- Elena Predescu
- Department of Neuroscience, Psychiatry and Pediatric Psychiatry, “Iuliu Hatieganu” University of Medicine and Pharmacy, 57 Republicii Street, 400489 Cluj-Napoca, Romania;
| | - Tudor Vaidean
- Clinic of Pediatric Psychiatry and Addiction, Clinical Emergency Hospital for Children, 57 Republicii Street, 400489 Cluj-Napoca, Romania;
| | - Andreea-Marlena Rapciuc
- Clinical Department of Nephrology, County Emergency Clinical Hospital Cluj, 3-5 Clinicilor Street, 400006 Cluj-Napoca, Romania;
| | - Roxana Sipos
- Department of Neuroscience, Psychiatry and Pediatric Psychiatry, “Iuliu Hatieganu” University of Medicine and Pharmacy, 57 Republicii Street, 400489 Cluj-Napoca, Romania;
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Tang H, Huang Y, Yuan D, Liu J. Atherosclerosis, gut microbiome, and exercise in a meta-omics perspective: a literature review. PeerJ 2024; 12:e17185. [PMID: 38584937 PMCID: PMC10999153 DOI: 10.7717/peerj.17185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/11/2024] [Indexed: 04/09/2024] Open
Abstract
Background Cardiovascular diseases are the leading cause of death worldwide, significantly impacting public health. Atherosclerotic cardiovascular diseases account for the majority of these deaths, with atherosclerosis marking the initial and most critical phase of their pathophysiological progression. There is a complex relationship between atherosclerosis, the gut microbiome's composition and function, and the potential mediating role of exercise. The adaptability of the gut microbiome and the feasibility of exercise interventions present novel opportunities for therapeutic and preventative approaches. Methodology We conducted a comprehensive literature review using professional databases such as PubMed and Web of Science. This review focuses on the application of meta-omics techniques, particularly metagenomics and metabolomics, in studying the effects of exercise interventions on the gut microbiome and atherosclerosis. Results Meta-omics technologies offer unparalleled capabilities to explore the intricate connections between exercise, the microbiome, the metabolome, and cardiometabolic health. This review highlights the advancements in metagenomics and metabolomics, their applications in research, and examines how exercise influences the gut microbiome. We delve into the mechanisms connecting these elements from a metabolic perspective. Metagenomics provides insight into changes in microbial strains post-exercise, while metabolomics sheds light on the shifts in metabolites. Together, these approaches offer a comprehensive understanding of how exercise impacts atherosclerosis through specific mechanisms. Conclusions Exercise significantly influences atherosclerosis, with the gut microbiome serving as a critical intermediary. Meta-omics technology holds substantial promise for investigating the gut microbiome; however, its methodologies require further refinement. Additionally, there is a pressing need for more extensive cohort studies to enhance our comprehension of the connection among these element.
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Affiliation(s)
- Haotian Tang
- Department of Histology and Embryology, School of Basic Medical Sciences, Central South University, Changsha, Hunan, China
| | - Yanqing Huang
- Department of Histology and Embryology, School of Basic Medical Sciences, Central South University, Changsha, Hunan, China
| | - Didi Yuan
- Department of Histology and Embryology, School of Basic Medical Sciences, Central South University, Changsha, Hunan, China
| | - Junwen Liu
- Department of Histology and Embryology, School of Basic Medical Sciences, Central South University, Changsha, Hunan, China
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Lu J, Wu Y, Zhan S, Zhong Y, Guo Y, Gao J, Zhang B, Dong X, Che J, Xu Y. A Microenvironment-responsive small-molecule probe and application in quick acute myocardial infarction imaging. Talanta 2024; 270:125571. [PMID: 38154354 DOI: 10.1016/j.talanta.2023.125571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/04/2023] [Accepted: 12/18/2023] [Indexed: 12/30/2023]
Abstract
Acute myocardial infarction (AMI) patients are at an elevated risk for life-threatening myocardial ischemia/reperfusion injury. Early-stage nonradioactive and noninvasive diagnosis of AMI is imperative for the subsequent disease treatment, yet it presents substantial challenges. After AMI, the myocardium typically exhibits elevated levels of peroxynitrite (ONOO-), constituting a distinct microenvironmental feature. In this context, the near-infrared imaging probe (BBEB) is employed to precisely delineate the boundaries of AMI lesions with a high level of sensitivity and specificity by monitoring endogenous ONOO-. This probe allows for the early detection of myocardial damage at cellular and animal levels, providing exceptional temporal and spatial resolution. Notably, BBEB enables visualization of ONOO- level alterations during AMI treatment incorporating antioxidant drugs. Overall, BBEB can rapidly and accurately visualize myocardial injury, particularly in the early stages, and can further facilitate antioxidant drug screening.
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Affiliation(s)
- Jialiang Lu
- Hangzhou Institute of Innovative Medicine, Institute of Drug Discovery and Design, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yirong Wu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang, 310006, China
| | - Siyao Zhan
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang, 310006, China
| | - Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang, 310006, China
| | - Yu Guo
- Hangzhou Institute of Innovative Medicine, Institute of Drug Discovery and Design, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Jian Gao
- Hangzhou Institute of Innovative Medicine, Institute of Drug Discovery and Design, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Bo Zhang
- Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China
| | - Xiaowu Dong
- Hangzhou Institute of Innovative Medicine, Institute of Drug Discovery and Design, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China; Department of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Jinxin Che
- Hangzhou Institute of Innovative Medicine, Institute of Drug Discovery and Design, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
| | - Yizhou Xu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang, 310006, China.
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Chen G, Zhang W, Li D, Song J, Dong M. Testosterone synthesis was inhibited in the testis metabolomics of a depression mouse model. J Affect Disord 2024; 350:627-635. [PMID: 38244803 DOI: 10.1016/j.jad.2024.01.143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 01/09/2024] [Accepted: 01/14/2024] [Indexed: 01/22/2024]
Abstract
INTRODUCTION Depression is a common emotional disorder. Previous studies have suggested that depression is associated with the central nervous system. Recent studies have suggested that reduced testosterone level is the core inducement of depression. Testis is the vital organ for the synthesis of testosterone. How does testis mediate depression is still unknown. OBJECTIVES We adopted a classical depression model of mouse caused through chronic mild stress (CMS). The metabolomics liquid chromatography-mass spectrometry was adopted to analyse the influence of CMS on testis metabolism. Then we confirmed the possible abnormal metabolism of the testis in depression mice by pathway analysis and molecular biological technique. RESULTS Compared with control mice, 16 differential metabolites were found in CMS mice by multivariate statistical analysis. In comparison with control mice, CMS mice showed higher levels for campesterol, ribitol, citric acid, platelet activating factor, guanosine, cytosine and xanthine and lower levels for docosahexaenoic acid, hippuric acid, creatine, testosterone, dehydroepiandrosterone, progesterone, l-carnitine, acetyl carnitine and propionyl carnitine. The pathway analysis indicated that these differential metabolites are associated with steroid hormone synthesis, purine metabolism and phenylalanine metabolism. In addition, we also first discovered that testicular morphology in depression mice was damaged and steroid hormone synthetases (including steroidogenic acute regulatory protein and P450 cholesterol side chain cleavage) were inhibited. CONCLUSION These findings may be helpful to parse molecular mechanisms of pathophysiology of depression. It also pointed out the direction to search for potential therapy schedules for male depression and provide novel insights into exploring the pathogenesis of male depression.
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Affiliation(s)
- Guanghui Chen
- Department of Pharmacy, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Wenbin Zhang
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Dongyan Li
- Department of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jian Song
- Department of Pharmacy, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Meixue Dong
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
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Gong X, Fu Y, Zhou L, Wei A, Pan C, Zhu T, Li H. Decoding chronic rhinosinusitis: A metabolomics-based approach. Int Forum Allergy Rhinol 2024; 14:828-840. [PMID: 38343156 DOI: 10.1002/alr.23331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/10/2024] [Accepted: 01/15/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Chronic rhinosinusitis (CRS) is a common and intractable disease in otorhinolaryngology, laying a heavy burden on healthcare systems. The worldwide researchers are making efforts to find solutions to this disease. Metabolomics has recently gained more and more traction, and might become a promising tool to unravel the complexity of CRS. This paper provides an overview of current studies on the metabolomics of various CRS subtypes. METHODS We conducted a comprehensive literature search in PubMed, Web of Science, EMBASE, Google Scholar, and Cochrane Library, up to May 25, 2023. Search strategies incorporated key terms such as "chronic rhinosinusitis" and "metabolomics" with relevant synonyms and MeSH terms. Titles and abstracts of 86 screened articles were assessed for relevance to CRS and metabolomics. Methodological robustness, data reliability, and relevance were considered for shortlisted articles. RESULTS After the refined process, a total of 26 articles were included in this study and sorted out by research themes, methodology and pivotal discoveries. These included studies identified the metabolic pathways and markers related to the pathophysiology in each subtype of CRS. CONCLUSIONS Metabolomics helps to shed light on the complexity of CRS. The mentioned findings highlight the importance of specific metabolic pathways and markers in understanding the pathophysiology of CRS. Despite that, challenges and future directions in metabolomics research for CRS would be worth being further explored.
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Affiliation(s)
- Xinru Gong
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yijie Fu
- School of Preclinical Medicine, Chengdu University, Chengdu, Sichuan, China
| | - Lei Zhou
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Aiming Wei
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Chongsheng Pan
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Tianmin Zhu
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Hui Li
- School of Preclinical Medicine, Chengdu University, Chengdu, Sichuan, China
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Hagn G, Meier-Menches SM, Plessl-Walder G, Mitra G, Mohr T, Preindl K, Schlatter A, Schmidl D, Gerner C, Garhöfer G, Bileck A. Plasma Instead of Serum Avoids Critical Confounding of Clinical Metabolomics Studies by Platelets. J Proteome Res 2024. [PMID: 38520676 DOI: 10.1021/acs.jproteome.3c00761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2024]
Abstract
Metabolomics is an emerging and powerful bioanalytical method supporting clinical investigations. Serum and plasma are commonly used without rational prioritization. Serum is collected after blood coagulation, a complex biochemical process involving active platelet metabolism. This may affect the metabolome and increase the variance, as platelet counts and function may vary substantially in individuals. A multiomics approach systematically investigating the suitability of serum and plasma for clinical studies demonstrated that metabolites correlated well (n = 461, R2 = 0.991), whereas lipid mediators (n = 83, R2 = 0.906) and proteins (n = 322, R2 = 0.860) differed substantially between specimen. Independently, analysis of platelet releasates identified most biomolecules significantly enriched in serum compared to plasma. A prospective, randomized, controlled parallel group metabolomics trial with acetylsalicylic acid administered for 7 days demonstrated that the apparent drug effects significantly differ depending on the analyzed specimen. Only serum analyses of healthy individuals suggested a significant downregulation of TXB2 and 12-HETE, which were specifically formed during coagulation in vitro. Plasma analyses reliably identified acetylsalicylic acid effects on metabolites and lipids occurring in vivo such as an increase in serotonin, 15-deoxy-PGJ2 and sphingosine-1-phosphate and a decrease in polyunsaturated fatty acids. The present data suggest that plasma should be preferred above serum for clinical metabolomics studies as the serum metabolome may be substantially confounded by platelets.
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Affiliation(s)
- Gerhard Hagn
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Waehringer Str. 42, 1090 Vienna, Austria
| | - Samuel M Meier-Menches
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Günter Plessl-Walder
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Gaurav Mitra
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Thomas Mohr
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
| | - Karin Preindl
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
- Department of Laboratory Medicine, Medical University of Vienna, Waehringer Gürtel 18-20, 1090 Vienna, Austria
| | - Andreas Schlatter
- Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - Doreen Schmidl
- Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - Christopher Gerner
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Gerhard Garhöfer
- Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - Andrea Bileck
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint Metabolome Facility, University and Medical University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
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Xia J, He X, Yang W, Song H, Yang J, Zhang G, Yang Z, Chen H, Liang Z, Kollie L, Abozeid A, Zhang X, Li Z, Yang D. Unveiling the distribution of chemical constituents at different body parts and maturity stages of Ganoderma lingzhi by combining metabolomics with desorption electrospray ionization mass spectrometry imaging (DESI). Food Chem 2024; 436:137737. [PMID: 37857205 DOI: 10.1016/j.foodchem.2023.137737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/24/2023] [Accepted: 10/10/2023] [Indexed: 10/21/2023]
Abstract
Ganoderma lingzhi is an important medicinal fungus, which is widely used as dietary supplement and for pharmaceutical industries. However, the spatial distribution and dynamic accumulation pattern of active components such as ganoderic acids (GAs) among different parts of G. lingzhi fruiting body are still unclear. In this study, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) with untargeted metabolomics analysis was applied to investigate the metabolites distribution within G. lingzhi fruiting body at four different maturity stages (squaring, opening, maturation and harvesting stage). A total of 132 metabolites were characterized from G. lingzhi, including 115 triterpenoids, 11 fatty acids and other component. Most of the GAs content in the cap was significantly higher than that in the stipe, with six components such as ganoderic acid B being extremely significant. GAs in the cap was mainly present in the bottom edge of the mediostratum layer, such as ganoderic A-I and ganoderic GS-1, while in the stipe, they were mainly distributed in the shell layer and the context layer, such as ganoderic A-F. Most ganoderic acids content in both the stipe and the cap of G. lingzhi was gradually decreased with the development of G. lingzhi. The GAs in the stipe was gradually transferred from the shell layer to the content layer, while the distribution of GAs among different tissues of the cap was not significantly changed. In addition, linoleic acid, 9-HODE, 9-KODE and other fatty acids were mainly accumulated in the opening and maturing stage of the caps. This study further clarifies the spatial dynamic distribution of GAs in G. lingzhi fruiting body at four different maturity stages (squaring, opening, maturation and harvesting stage), which provides a basis for the rational utilization of the medicinal parts of G. lingzhi. Furthermore, mass spectrometry imaging combined with non-target metabolome analysis provides a powerful tool for the spatial distribution of active substances in the different regions of the medicinal edible fungi.
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Affiliation(s)
- Jie Xia
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Xinyu He
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Wan Yang
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Hongyan Song
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Jihong Yang
- Zhejiang Shouxiangu Botanical Drug Institute Co., Ltd, Hangzhou, China
| | - Guoliang Zhang
- Zhejiang Shouxiangu Botanical Drug Institute Co., Ltd, Hangzhou, China
| | - Zongqi Yang
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Haimin Chen
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Zongsuo Liang
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China; Shaoxing Academy of Biomedicne Co., Ltd of Zhejiang Sci-Tech University, Zhejiang Engineering Research Center for the Development Technology of Medicinal and Edible Health Food, Shaoxing, China
| | - Larwubah Kollie
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China
| | - Ann Abozeid
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China; Botany and Microbiology Department, Faculty of Science, Menoufia University, Shebin Elkoom, Egypt
| | - Xiaodan Zhang
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China.
| | - Zhenhao Li
- Zhejiang Shouxiangu Botanical Drug Institute Co., Ltd, Hangzhou, China.
| | - Dongfeng Yang
- College of Life Sciences and Medicine, Key Laboratory of Plant Secondary Metabolism and Regulation of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, China; Shaoxing Academy of Biomedicne Co., Ltd of Zhejiang Sci-Tech University, Zhejiang Engineering Research Center for the Development Technology of Medicinal and Edible Health Food, Shaoxing, China.
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Mizuno S, Wagata M, Nagaie S, Ishikuro M, Obara T, Tamiya G, Kuriyama S, Tanaka H, Yaegashi N, Yamamoto M, Sugawara J, Ogishima S. Development of phenotyping algorithms for hypertensive disorders of pregnancy (HDP) and their application in more than 22,000 pregnant women. Sci Rep 2024; 14:6292. [PMID: 38491024 PMCID: PMC10943000 DOI: 10.1038/s41598-024-55914-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 02/28/2024] [Indexed: 03/18/2024] Open
Abstract
Recently, many phenotyping algorithms for high-throughput cohort identification have been developed. Prospective genome cohort studies are critical resources for precision medicine, but there are many hurdles in the precise cohort identification. Consequently, it is important to develop phenotyping algorithms for cohort data collection. Hypertensive disorders of pregnancy (HDP) is a leading cause of maternal morbidity and mortality. In this study, we developed, applied, and validated rule-based phenotyping algorithms of HDP. Two phenotyping algorithms, algorithms 1 and 2, were developed according to American and Japanese guidelines, and applied into 22,452 pregnant women in the Birth and Three-Generation Cohort Study of the Tohoku Medical Megabank project. To precise cohort identification, we analyzed both structured data (e.g., laboratory and physiological tests) and unstructured clinical notes. The identified subtypes of HDP were validated against reference standards. Algorithms 1 and 2 identified 7.93% and 8.08% of the subjects as having HDP, respectively, along with their HDP subtypes. Our algorithms were high performing with high positive predictive values (0.96 and 0.90 for algorithms 1 and 2, respectively). Overcoming the hurdle of precise cohort identification from large-scale cohort data collection, we achieved both developed and implemented phenotyping algorithms, and precisely identified HDP patients and their subtypes from large-scale cohort data collection.
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Affiliation(s)
- Satoshi Mizuno
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Maiko Wagata
- Department of Feto-Maternal Medical Science, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Satoshi Nagaie
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Mami Ishikuro
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Taku Obara
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Gen Tamiya
- Department of Statistical Genetics and Genomics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Shinichi Kuriyama
- Department of Molecular Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | | | - Nobuo Yaegashi
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
| | - Masayuki Yamamoto
- Department of Biochemistry and Molecular Biology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Junichi Sugawara
- Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Tohoku University, Miyagi, Japan
- Suzuki Memorial Hospital, 3-5-5, Satonomori, Iwanumashi, Miyagi, Japan
| | - Soichi Ogishima
- Department of Informatics for Genomic Medicine, Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan.
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, Miyagi, Japan.
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Willency JA, Lin Y, Pirro V. Targeted metabolomics in human and animal biofluids and tissues using liquid chromatography coupled with tandem mass spectrometry. STAR Protoc 2024; 5:102884. [PMID: 38367229 PMCID: PMC10882138 DOI: 10.1016/j.xpro.2024.102884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 08/07/2023] [Accepted: 01/26/2024] [Indexed: 02/19/2024] Open
Abstract
Here, we present a targeted polar metabolomics protocol for the analysis of biofluids and frozen tissue biopsies using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We describe steps for sample pretreatment, liquid-liquid extraction, and isolation of polar metabolites. We then detail procedures for target LC-MS/MS analysis. In this protocol, we focus on the analysis of plasma and serum samples. We also provide brief instructions on how to process other biological matrices as supplemental information. For complete details on the use and execution of this protocol, please refer to Coskun et al. (2022).1.
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Affiliation(s)
- Jill A Willency
- Technologies and Operations Group, Eli Lilly and Company, Indianapolis, IN 46225, USA
| | - Yanzhu Lin
- Discovery Statistics, Eli Lilly and Company, Indianapolis, IN 46225, USA
| | - Valentina Pirro
- Technologies and Operations Group, Eli Lilly and Company, Indianapolis, IN 46225, USA.
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40
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Jeppe K, Ftouni S, Nijagal B, Grant LK, Lockley SW, Rajaratnam SMW, Phillips AJK, McConville MJ, Tull D, Anderson C. Accurate detection of acute sleep deprivation using a metabolomic biomarker-A machine learning approach. SCIENCE ADVANCES 2024; 10:eadj6834. [PMID: 38457492 PMCID: PMC11094653 DOI: 10.1126/sciadv.adj6834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/02/2024] [Indexed: 03/10/2024]
Abstract
Sleep deprivation enhances risk for serious injury and fatality on the roads and in workplaces. To facilitate future management of these risks through advanced detection, we developed and validated a metabolomic biomarker of sleep deprivation in healthy, young participants, across three experiments. Bi-hourly plasma samples from 2 × 40-hour extended wake protocols (for train/test models) and 1 × 40-hour protocol with an 8-hour overnight sleep interval were analyzed by untargeted liquid chromatography-mass spectrometry. Using a knowledge-based machine learning approach, five consistently important variables were used to build predictive models. Sleep deprivation (24 to 38 hours awake) was predicted accurately in classification models [versus well-rested (0 to 16 hours)] (accuracy = 94.7%/AUC 99.2%, 79.3%/AUC 89.1%) and to a lesser extent in regression (R2 = 86.1 and 47.8%) models for within- and between-participant models, respectively. Metabolites were identified for replicability/future deployment. This approach for detecting acute sleep deprivation offers potential to reduce accidents through "fitness for duty" or "post-accident analysis" assessments.
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Affiliation(s)
- Katherine Jeppe
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
| | - Suzanne Ftouni
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
| | - Brunda Nijagal
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, Parkville, Australia
| | - Leilah K. Grant
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Steven W. Lockley
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Shantha M. W. Rajaratnam
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Andrew J. K. Phillips
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Malcolm J. McConville
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, Parkville, Australia
| | - Dedreia Tull
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, Parkville, Australia
| | - Clare Anderson
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
- Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, UK
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Zhu P, Dubbelman AC, Hunter C, Genangeli M, Karu N, Harms A, Hankemeier T. Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:590-602. [PMID: 38379502 PMCID: PMC10921459 DOI: 10.1021/jasms.3c00418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024]
Abstract
Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.
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Affiliation(s)
- Pingping Zhu
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Anne-Charlotte Dubbelman
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht 3584 CM, The Netherlands
| | | | - Michele Genangeli
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Naama Karu
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Amy Harms
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands
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42
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Xiao Z, Yu S, Zhang D, Li C. UHPLC-qTOF-MS-Based Nontargeted Metabolomics to Characterize the Effects of Capsaicin on Plasma and Skin Metabolic Profiles of C57BL/6 Mice-An In vivo Experimental Study. Drug Des Devel Ther 2024; 18:719-729. [PMID: 38476205 PMCID: PMC10929253 DOI: 10.2147/dddt.s423974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Background Capsaicin is the main compound found in chili pepper and has complex pharmacologic effects. This study aimed to elucidate the mechanism of the effect of capsaicin on physiological processes by analyzing changes in metabolites and metabolic pathways. Methods Female C57BL/6 mice were divided into two groups(n = 10/group) and fed with capsaicin-soybean oil solution(group T) or soybean oil(group C) for 6 weeks. Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-qTOF-MS) based metabolomics was undertaken to assess plasma and skin metabolic profile changes and identify differential metabolites through multivariate analysis. Results According to the OPLS-DA score plots, the plasma and skin metabolic profiles in the group T and group C were significantly separated. In plasma, 38 significant differential metabolites were identified. KEGG pathway enrichment analysis revealed that the most significant plasma metabolic pathways included pyruvate metabolism and ABC transporters. In skin, seven significant differential metabolites were found. Four metabolic pathways with p values < 0.05 were detected, including sphingolipid metabolism, sphingolipid signaling pathway, apoptosis, and necroptosis. Conclusion These findings will provide metabolomic insights to assess the physiological functions of capsaicin and contribute to a better understanding of the potential effects of a capsaicin-rich diet on health.
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Affiliation(s)
- Zhen Xiao
- Department of Dermatology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People’s Republic of China
- Department of Dermatology, Taiyuan Central Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
| | - Simin Yu
- Department of Dermatology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Deng Zhang
- Department of Dermatology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People’s Republic of China
| | - Chunming Li
- Department of Dermatology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People’s Republic of China
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Zhang Z, Yu H, Wong-Ma E, Dokouhaki P, Mostafa A, Shavadia JS, Wu F, Huan T. Reducing Quantitative Uncertainty Caused by Data Processing in Untargeted Metabolomics. Anal Chem 2024; 96:3727-3732. [PMID: 38395621 DOI: 10.1021/acs.analchem.3c04046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024]
Abstract
Processing liquid chromatography-mass spectrometry-based metabolomics data using computational programs often introduces additional quantitative uncertainty, termed computational variation in a previous work. This work develops a computational solution to automatically recognize metabolic features with computational variation in a metabolomics data set. This tool, AVIR (short for "Accurate eValuation of alIgnment and integRation"), is a support vector machine-based machine learning strategy (https://github.com/HuanLab/AVIR). The rationale is that metabolic features with computational variation have a poor correlation between chromatographic peak area and peak height-based quantifications across the samples in a study. AVIR was trained on a set of 696 manually curated metabolic features and achieved an accuracy of 94% in a 10-fold cross-validation. When tested on various external data sets from public metabolomics repositories, AVIR demonstrated an accuracy range of 84%-97%. Finally, tested on a large-scale metabolomics study, AVIR clearly indicated features with computational variation and thus guided us to manually correct them. Our results show that 75.3% of the samples with computational variation had a relative intensity difference of over 20% after correction. This demonstrates the critical role of AVIR in reducing computational variation to improve quantitative certainty in untargeted metabolomics analysis.
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Affiliation(s)
- Zixuan Zhang
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
| | - Huaxu Yu
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
| | - Ethan Wong-Ma
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
| | - Pouneh Dokouhaki
- Department of Pathology and Laboratory Medicine, University of Saskatchewan and Saskatchewan Health Authority, Saskatoon S7M 0Z9, SK, Canada
| | - Ahmed Mostafa
- Department of Pathology and Laboratory Medicine, University of Saskatchewan and Saskatchewan Health Authority, Saskatoon S7M 0Z9, SK, Canada
| | - Jay S Shavadia
- Division of Cardiology, College of Medicine, University of Saskatchewan, Saskatoon S7N 5E5, SK, Canada
| | - Fang Wu
- Department of Pathology and Laboratory Medicine, University of Saskatchewan and Saskatchewan Health Authority, Saskatoon S7M 0Z9, SK, Canada
| | - Tao Huan
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada
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Duan XP, Qin BD, Jiao XD, Liu K, Wang Z, Zang YS. New clinical trial design in precision medicine: discovery, development and direction. Signal Transduct Target Ther 2024; 9:57. [PMID: 38438349 PMCID: PMC10912713 DOI: 10.1038/s41392-024-01760-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 03/06/2024] Open
Abstract
In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.
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Affiliation(s)
- Xiao-Peng Duan
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Bao-Dong Qin
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Xiao-Dong Jiao
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Ke Liu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Zhan Wang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Yuan-Sheng Zang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China.
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45
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Yuan Y, Huang L, Yu L, Yan X, Chen S, Bi C, He J, Zhao Y, Yang L, Ning L, Jin H, Yang R, Li Y. Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls. Diabetes Metab Res Rev 2024; 40:e3789. [PMID: 38501707 DOI: 10.1002/dmrr.3789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 01/01/2024] [Accepted: 01/31/2024] [Indexed: 03/20/2024]
Abstract
AIMS Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.
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Affiliation(s)
- Yu Yuan
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Liping Huang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
- College of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lulu Yu
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xingxu Yan
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Siyu Chen
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Chenghao Bi
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Junjie He
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yiqing Zhao
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Liu Yang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Li Ning
- Department Clinical Laboratory, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Hua Jin
- College of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Rongrong Yang
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yubo Li
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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Chafai N, Bonizzi L, Botti S, Badaoui B. Emerging applications of machine learning in genomic medicine and healthcare. Crit Rev Clin Lab Sci 2024; 61:140-163. [PMID: 37815417 DOI: 10.1080/10408363.2023.2259466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 09/12/2023] [Indexed: 10/11/2023]
Abstract
The integration of artificial intelligence technologies has propelled the progress of clinical and genomic medicine in recent years. The significant increase in computing power has facilitated the ability of artificial intelligence models to analyze and extract features from extensive medical data and images, thereby contributing to the advancement of intelligent diagnostic tools. Artificial intelligence (AI) models have been utilized in the field of personalized medicine to integrate clinical data and genomic information of patients. This integration allows for the identification of customized treatment recommendations, ultimately leading to enhanced patient outcomes. Notwithstanding the notable advancements, the application of artificial intelligence (AI) in the field of medicine is impeded by various obstacles such as the limited availability of clinical and genomic data, the diversity of datasets, ethical implications, and the inconclusive interpretation of AI models' results. In this review, a comprehensive evaluation of multiple machine learning algorithms utilized in the fields of clinical and genomic medicine is conducted. Furthermore, we present an overview of the implementation of artificial intelligence (AI) in the fields of clinical medicine, drug discovery, and genomic medicine. Finally, a number of constraints pertaining to the implementation of artificial intelligence within the healthcare industry are examined.
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Affiliation(s)
- Narjice Chafai
- Laboratory of Biodiversity, Ecology, and Genome, Faculty of Sciences, Department of Biology, Mohammed V University in Rabat, Rabat, Morocco
| | - Luigi Bonizzi
- Department of Biomedical, Surgical and Dental Science, University of Milan, Milan, Italy
| | - Sara Botti
- PTP Science Park, Via Einstein - Loc. Cascina Codazza, Lodi, Italy
| | - Bouabid Badaoui
- Laboratory of Biodiversity, Ecology, and Genome, Faculty of Sciences, Department of Biology, Mohammed V University in Rabat, Rabat, Morocco
- African Sustainable Agriculture Research Institute (ASARI), Mohammed VI Polytechnic University (UM6P), Laâyoune, Morocco
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47
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Fei X, Du X, Wang J, Liu J, Gong Y, Zhao Z, Cao Z, Fu Q, Zhu Y, Dong L, Dong B, Pan J, Sun W, Xie S, Xue W. Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study. Int J Surg 2024; 110:1450-1462. [PMID: 38181121 PMCID: PMC10942223 DOI: 10.1097/js9.0000000000001033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 12/11/2023] [Indexed: 01/07/2024]
Abstract
OBJECTIVES Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making. METHODS Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models. RESULTS Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk. CONCLUSIONS Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.
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Affiliation(s)
| | | | | | | | | | - Zejun Zhao
- Department of Ultrasound, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
| | - Zhibin Cao
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong, People’s Republic of China
| | - Qibo Fu
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong, People’s Republic of China
| | | | | | | | | | - Wenshe Sun
- Department of Urology, Jiading District Central Hospital, Shanghai University of Medicine and Health Sciences, Shanghai
| | - Shaowei Xie
- Department of Ultrasound, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
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Liu X, Sun X, Guo C, Huang ZF, Chen YR, Feng FM, Wu LJ, Chen WX. Untargeted urine metabolomics and machine learning provide potential metabolic signatures in children with autism spectrum disorder. Front Psychiatry 2024; 15:1261617. [PMID: 38445087 PMCID: PMC10912307 DOI: 10.3389/fpsyt.2024.1261617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 01/19/2024] [Indexed: 03/07/2024] Open
Abstract
Background Complementary to traditional biostatistics, the integration of untargeted urine metabolomic profiling with Machine Learning (ML) has the potential to unveil metabolic profiles crucial for understanding diseases. However, the application of this approach in autism remains underexplored. Our objective was to delve into the metabolic profiles of autism utilizing a comprehensive untargeted metabolomics platform coupled with ML. Methods Untargeted metabolomics quantification (UHPLC/Q-TOF-MS) was performed for urine analysis. Feature selection was conducted using Lasso regression, and logistic regression, support vector machine, random forest, and extreme gradient boosting were utilized for significance stratification. Pathway enrichment analysis was performed to identify metabolic pathways associated with autism. Results A total of 52 autistic children and 40 typically developing children were enrolled. Lasso regression identified ninety-two urinary metabolites that significantly differed between the two groups. Distinct metabolites, such as prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, were revealed to be associated with autism through the application of four different ML methods (p<0.05). The alterations observed in the phosphatidylinositol and inositol phosphate metabolism pathways were linked to the pathophysiology of autism (p<0.05). Conclusion Significant urinary metabolites, including prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, exhibit associations with autism. Additionally, the involvement of the phosphatidylinositol and inositol phosphate pathways suggests their potential role in the pathophysiology of autism.
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Affiliation(s)
- Xian Liu
- Department of Children’s and Adolescent Health, College of Public Health, Harbin Medical University, Harbin, China
- Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Xin Sun
- Clinical Research and Innovation Center, Xinhua Hospital Affiliated with Shanghai Jiao Tong University, Shanghai, China
| | - Cheng Guo
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children’s Medical Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Zhi-Fang Huang
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children’s Medical Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Yi-Ru Chen
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children’s Medical Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Fang-Mei Feng
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children’s Medical Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Li-Jie Wu
- Department of Children’s and Adolescent Health, College of Public Health, Harbin Medical University, Harbin, China
| | - Wen-Xiong Chen
- The Assessment and Intervention Center for Autistic Children, Guangzhou Women and Children’s Medical Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Neurology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China
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Liu D, Nagana Gowda GA, Jiang Z, Alemdjrodo K, Zhang M, Zhang D, Raftery D. Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts. Proc Natl Acad Sci U S A 2024; 121:e2307430121. [PMID: 38359289 PMCID: PMC10895372 DOI: 10.1073/pnas.2307430121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 12/05/2023] [Indexed: 02/17/2024] Open
Abstract
Blood metabolite levels are affected by numerous factors, including preanalytical factors such as collection methods and geographical sites. These perturbations have caused deleterious consequences for many metabolomics studies and represent a major challenge in the metabolomics field. It is important to understand these factors and develop models to reduce their perturbations. However, to date, the lack of suitable mathematical models for blood metabolite levels under homeostasis has hindered progress. In this study, we develop quantitative models of blood metabolite levels in healthy adults based on multisite sample cohorts that mimic the current challenge. Five cohorts of samples obtained across four geographically distinct sites were investigated, focusing on approximately 50 metabolites that were quantified using 1H NMR spectroscopy. More than one-third of the variation in these metabolite profiles is due to cross-cohort variation. A dramatic reduction in the variation of metabolite levels (90%), especially their site-to-site variation (95%), was achieved by modeling each metabolite using demographic and clinical factors and especially other metabolites, as observed in the top principal components. The results also reveal that several metabolites contribute disproportionately to such variation, which could be explained by their association with biological pathways including biosynthesis and degradation. The study demonstrates an intriguing network effect of metabolites that can be utilized to better define homeostatic metabolite levels, which may have implications for improved health monitoring. As an example of the potential utility of the approach, we show that modeling gender-related metabolic differences retains the interesting variance while reducing unwanted (site-related) variance.
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Affiliation(s)
- Danni Liu
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - G. A. Nagana Gowda
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA98109
| | - Zhongli Jiang
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - Kangni Alemdjrodo
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - Min Zhang
- Department of Statistics, Purdue University, West Lafayette, IN47907
- Department of Epidemiology and Biostatistics, University of California, Irvine, CA92697
| | - Dabao Zhang
- Department of Statistics, Purdue University, West Lafayette, IN47907
- Department of Epidemiology and Biostatistics, University of California, Irvine, CA92697
| | - Daniel Raftery
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA98109
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Wang L, Li H, Zhang H, Song X, Jiang H, Wang D, Wang Y. Serum-based metabolomics reveals the mechanism of action of isorhynchophylline in the intervention of atherosclerosis in ApoE -/- mice. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:1083-1092. [PMID: 38284158 DOI: 10.1039/d3ay01803b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
Atherosclerosis (AS) is a chronic inflammatory disease with disorders of lipid metabolism. Metabolic disorders, inflammation and lipid deposition are prominent pathological features of atherosclerosis. Isorhynchophylline (IRN) has pharmacological effects such as protection of vascular endothelial cells, anti-inflammatory, anti-thrombotic, and anti-smooth muscle cell proliferation. However, it is unclear whether IRN is efficacious in atherosclerosis. In the present study, we verified the pharmacological efficacy and hepatoprotective effects of IRN in intervening in AS. LC-MS-based serum untargeted metabolomics was performed to search for potential biomarkers and related pathways in IRN-treated AS in ApoE-/- mice. Fifty-eight biomarkers were metabolically disturbed in the model mice compared to controls. Thirteen biomarkers showed optimal recovery methods after IRN-40 mg ml-1 intervention. We identified three metabolic pathways involved in IRN: glycerophospholipid metabolism, linoleic acid metabolism, and alpha-linolenic acid metabolism. These findings provide a research basis for the intervention of IRN in atherosclerosis.
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Affiliation(s)
- Lihua Wang
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Haichao Li
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Hao Zhang
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Xiayinan Song
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Haiqiang Jiang
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
- Key Laboratory of Traditional Chinese Medicine Classical Theory, Ministry of Education, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
- Shandong Provincial Key Laboratory of Traditional Chinese Medicine for Basic Research, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Danyang Wang
- Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China.
| | - Yu Wang
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250011, China.
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