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Lee J, Ji BG, Hong EJ, Jeon JP. Association of Serum Metabolites with Serum Indices and Preanalytical Factors of Biobanked Serum Samples. Biopreserv Biobank 2024. [PMID: 38975777 DOI: 10.1089/bio.2023.0130] [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: 07/09/2024] Open
Abstract
Background: Serum indices (hemolysis, icterus, and lipemia; HIL) are known to impact clinical chemistry assay results. This study aimed to investigate the impact of HIL indices on serum metabolite profiles and the association of serum metabolite levels with pre-analytical factors of serum samples. Methods: A cohort of serum samples (n = 12,196) from the Korean Genome and Epidemiology Study (KoGES) was analyzed for HIL indices and the pre-analytical variables (SPRECs) which were generated in the process of serum collection. We further performed targeted metabolomics on a subset comprising hemolyzed (n = 60), icteric (n = 60), lipemic (n = 60) groups, and a common control group of non-HIL samples (n = 60) using the Absolute IDQ p180 kit. Results: We found 22 clinical chemistry analytes significantly associated with hemolysis, 25 with icterus, and 24 with lipemia (p < 0.0001). Serum metabolites (n = 27) were associated with all of hemolysis, icterus, and lipemia (p < 0.05). The PC ae C36 2 had exhibited a significant association with pre-analytical factors corresponding to the third (pre-centrifugation delay between processing) and sixth (post-centrifugation) elements of the SPREC. Conclusions: This study showed the association of the serum index and pre-analytical factors with serum metabolite profiles. In addition, the association of pre-analytical factors with serum metabolite concentrations would corroborate the utility of SPRECs for the quality control of biobanked serum samples.
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Affiliation(s)
- Juyoung Lee
- Division of Biobank, National Biobank of Korea, National Institute of Health, Cheongju, Korea
| | - Byeong-Gon Ji
- Division of Biobank, National Biobank of Korea, National Institute of Health, Cheongju, Korea
| | - Eun-Jung Hong
- Division of Biobank, National Biobank of Korea, National Institute of Health, Cheongju, Korea
| | - Jae-Pil Jeon
- Division of Biobank, National Biobank of Korea, National Institute of Health, Cheongju, Korea
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2
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Xue W, Li F, Li X, Liu Y. A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize. Molecules 2024; 29:3026. [PMID: 38998975 PMCID: PMC11243018 DOI: 10.3390/molecules29133026] [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: 05/08/2024] [Revised: 06/15/2024] [Accepted: 06/19/2024] [Indexed: 07/14/2024] Open
Abstract
The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non-targeted screening method for P&VDs for their comprehensive risk assessment. In this study, a modified support vector machine (SVM)-assisted metabolomics approach by screening eligible variables to represent marker compounds of 124 multi-class P&VDs in maize was developed based on the results of high-performance liquid chromatography-tandem mass spectrometry. Principal component analysis and orthogonal partial least squares discriminant analysis indicate the existence of variables with obvious inter-group differences, which were further investigated by S-plot plots, permutation tests, and variable importance in projection to obtain eligible variables. Meanwhile, SVM recursive feature elimination under the radial basis function was employed to obtain the weight-squared values of all the variables ranging from large to small for the screening of eligible variables as well. Pairwise t-tests and fold changes of concentration were further employed to confirm these eligible variables to represent marker compounds. The results indicate that 120 out of 124 P&VDs can be identified by the SVM-assisted metabolomics method, while only 109 P&VDs can be found by the metabolomics method alone, implying that SVM can promote the screening accuracy of the metabolomics method. In addition, the method's practicability was validated by the real contaminated maize samples, which provide a bright application prospect in non-targeted screening of contaminants. The limits of detection for 120 P&VDs in maize samples were calculated to be 0.3~1.5 µg/kg.
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Affiliation(s)
- Weifeng Xue
- Technology Centre of Dalian Customs, Dalian 116000, China
| | - Fang Li
- Technology Centre of Dalian Customs, Dalian 116000, China
| | - Xuemei Li
- Technology Centre of Dalian Customs, Dalian 116000, China
| | - Ying Liu
- Technology Centre of Dalian Customs, Dalian 116000, China
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3
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Li S, Looby N, Chandran V, Kulasingam V. Challenges in the Metabolomics-Based Biomarker Validation Pipeline. Metabolites 2024; 14:200. [PMID: 38668328 PMCID: PMC11051909 DOI: 10.3390/metabo14040200] [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: 03/01/2024] [Revised: 03/27/2024] [Accepted: 03/31/2024] [Indexed: 04/28/2024] Open
Abstract
As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.
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Affiliation(s)
- Shenghan Li
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Nikita Looby
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Division of Orthopaedic Surgery, Osteoarthritis Research Program, Schroeder Arthritis Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Vinod Chandran
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Division of Rheumatology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Vathany Kulasingam
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Division of Clinical Biochemistry, Laboratory Medicine Program, University Health Network, Toronto, ON M5G 2C4, Canada
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Yu M, Wen W, Wang Y, Shan X, Yi X, Zhu W, Aa J, Wang G. Plasma metabolomics reveals risk factors for lung adenocarcinoma. Front Oncol 2024; 14:1277206. [PMID: 38567154 PMCID: PMC10985191 DOI: 10.3389/fonc.2024.1277206] [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: 08/14/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
Background Metabolic reprogramming plays a significant role in the advancement of lung adenocarcinoma (LUAD), yet the precise metabolic changes remain incompletely understood. This study aims to uncover metabolic indicators associated with the progression of LUAD. Methods A total of 1083 subjects were recruited, including 670 LUAD, 135 benign lung nodules (BLN) and 278 healthy controls (HC). Gas chromatography-mass spectrometry (GC/MS) was used to identify and quantify plasma metabolites. Odds ratios (ORs) were calculated to determine LUAD risk factors, and machine learning algorithms were utilized to differentiate LUAD from BLN. Results High levels of oxalate, glycolate, glycine, glyceric acid, aminomalonic acid, and creatinine were identified as risk factors for LUAD (adjusted ORs>1.2, P<0.03). Remarkably, oxalate emerged as a distinctive metabolic risk factor exhibiting a strong correlation with the progression of LUAD (adjusted OR=5.107, P<0.001; advanced-stage vs. early-stage). The Random Forest (RF) model demonstrated a high degree of efficacy in distinguishing between LUAD and BLN (accuracy = 1.00 and 0.73, F1-score= 1.00 and 0.79, and AUC = 1.00 and 0.76 in the training and validation sets, respectively). TCGA and GTEx gene expression data have shown that lactate dehydrogenase A (LDHA), a crucial enzyme involved in oxalate metabolism, is increasingly expressed in the progression of LUAD. High LDHA expression levels in LUAD patients are also linked to poor prognoses (HR=1.66, 95% CI=1.34-2.07, P<0.001). Conclusions This study reveals risk factors associated with LUAD.
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Affiliation(s)
- Mengjie Yu
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu, China
| | - Wei Wen
- Department of Thoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yue Wang
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu, China
| | - Xia Shan
- Department of Respiration, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xin Yi
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu, China
| | - Wei Zhu
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiye Aa
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu, China
| | - Guangji Wang
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu, China
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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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6
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Nishiumi S, Yokoyama T, Ojima N. User-friendly relative quantification procedure for gas chromatography/mass spectrometry-based plasma metabolome analysis. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2024; 38:e9683. [PMID: 38212648 DOI: 10.1002/rcm.9683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/20/2023] [Accepted: 11/27/2023] [Indexed: 01/13/2024]
Abstract
RATIONALE Recently, metabolome analysis has been applied to a variety of research fields, but differences between batches or facilities can cause discrepancies in the results of such analyses. To resolve these issues using comprehensive metabolome analysis, in which it is difficult to perform quantitative analyses of all detected metabolites, internal standard compounds are used to obtain relative metabolite levels. This study investigated gas chromatography/mass spectrometry-based plasma metabolome analysis methods that are superior to relative quantification using internal standard compounds. METHODS In experiment I, four analyses were performed under different analytical conditions at one facility, and then the data from the four analyses were compared. In experiment II, the same samples were analyzed at three facilities, and then the data from the three facilities were compared. RESULTS Regarding the relative values obtained through comparisons with the internal standard compound, differences in the analytical results were observed among the four analytical conditions in experiment I and among the three facilities in experiment II, and the differences observed among the three facilities (experiment II) were larger. When correction was performed using plasma as a quality control, which is the procedure suggested in this study, these differences were markedly ameliorated. CONCLUSION The suggested procedure involves the analysis of a plasma standard as a quality control for each batch and the calculation of relative target plasma to quality-control plasma values for each metabolite. This is an easy and low-cost method and could be readily employed by researchers during comprehensive plasma metabolome analysis.
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Affiliation(s)
- Shin Nishiumi
- Department of Omics Medicine, Hyogo Medical University, Nishinomiya, Japan
- Department of Biosphere Sciences, School of Human Sciences, Kobe College, Nishinomiya, Japan
| | - Tomonori Yokoyama
- Department of Omics Medicine, Hyogo Medical University, Nishinomiya, Japan
- Analytical and Measuring Instruments Division, Shimadzu Corporation, Kyoto, Japan
| | - Noriyuki Ojima
- Department of Omics Medicine, Hyogo Medical University, Nishinomiya, Japan
- Analytical and Measuring Instruments Division, Shimadzu Corporation, Kyoto, Japan
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7
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Wang S, He T, Wang H. Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker. J Pharm Biomed Anal 2024; 239:115869. [PMID: 38064771 DOI: 10.1016/j.jpba.2023.115869] [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: 09/26/2023] [Revised: 11/06/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024]
Abstract
Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.
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Affiliation(s)
- Shufeng Wang
- Keystonobel Biotechnologies and Pharmaceuticals (Beijing) Co., Ltd, Beijing 100176, PR China
| | - Tingting He
- Department of Hepatology Medicine of Traditional Chinese Medicine, the Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, PR China
| | - Hongxia Wang
- Institute of Mass Spectrometry, Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Ningbo University, Ningbo 315211, PR China; School of Material Science and Chemical Engineering Ningbo University, Ningbo 315211, PR China; Ningbo Zhenhai Institute of Mass Spectrometry, Ningbo 315206, PR China.
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8
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Xiong W, Anthony DC, Anthony S, Ho TBT, Louis E, Satsangi J, Radford-Smith DE. Sodium fluoride preserves blood metabolite integrity for biomarker discovery in large-scale, multi-site metabolomics investigations. Analyst 2024; 149:1238-1249. [PMID: 38224241 DOI: 10.1039/d3an01359f] [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: 01/16/2024]
Abstract
Background: Metabolite profiling of blood by nuclear magnetic resonance (NMR) is invaluable to clinical biomarker discovery. To ensure robustness, biomarkers require validation in large cohorts and across multiple centres. However, collection procedures are known to impact on the stability of biofluids that may, in turn, degrade biomarker signals. We trialled three blood collection tubes with the aim of solving technical challenges due to preanalytical variation in blood metabolite levels that are common in cohort studies. Methods: We first investigated global NMR-based metabolite variability between biobanks, including the large-scale UK Biobank and TwinsUK biobank of the general UK population, and more targeted biobanks derived from multicentre clinical trials relating to inflammatory bowel disease. We then compared the blood metabolome of 12 healthy adult volunteers when collected into either sodium fluoride/potassium oxalate, lithium heparin, or serum blood tubes using different pre-processing parameters. Results: Preanalytical variation in the method of blood collection strongly influences metabolite composition within and between biobanks. This variability can largely be attributed to glucose and lactate. In the healthy control cohort, the fluoride oxalate collection tube prevented fluctuation in glucose and lactate levels for 24 hours at either 4 °C or room temperature (20 °C). Conclusions: Blood collection into a fluoride oxalate collection tube appears to preserve the blood metabolome with delayed processing up to 24 hours at 4 °C. This method may be considered as an alternative when rapid processing is not feasible.
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Affiliation(s)
- Wenzheng Xiong
- Department of Chemistry, University of Oxford, Oxford, UK.
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Daniel C Anthony
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Suzie Anthony
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Thi Bao Tien Ho
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Edouard Louis
- Department of Gastroenterology, University Hospital CHU of Liège, Liège, Belgium
| | - Jack Satsangi
- Translational Gastroenterology Unit, Nuffield Department of Experimental Medicine, University of Oxford, Oxford, UK
| | - Daniel E Radford-Smith
- Department of Chemistry, University of Oxford, Oxford, UK.
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
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Roach J, Mital R, Haffner JJ, Colwell N, Coats R, Palacios HM, Liu Z, Godinho JLP, Ness M, Peramuna T, McCall LI. Microbiome metabolite quantification methods enabling insights into human health and disease. Methods 2024; 222:81-99. [PMID: 38185226 DOI: 10.1016/j.ymeth.2023.12.007] [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: 07/07/2023] [Revised: 10/27/2023] [Accepted: 12/13/2023] [Indexed: 01/09/2024] Open
Abstract
Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin. We further discuss techniques used to quantify common microbial metabolites, including short-chain fatty acids (SCFA), secondary bile acids (BAs), tryptophan derivatives, N-acyl amides and trimethylamine N-oxide (TMAO). Lastly, we conclude with challenges and future directions for the field.
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Affiliation(s)
- Jarrod Roach
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Rohit Mital
- Department of Biology, University of Oklahoma
| | - Jacob J Haffner
- Department of Anthropology, University of Oklahoma; Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma
| | - Nathan Colwell
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Randy Coats
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Horvey M Palacios
- Department of Anthropology, University of Oklahoma; Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma
| | - Zongyuan Liu
- Department of Chemistry and Biochemistry, University of Oklahoma
| | | | - Monica Ness
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Thilini Peramuna
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma; Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma; Department of Chemistry and Biochemistry, San Diego State University.
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10
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González-Domínguez Á, Estanyol-Torres N, Brunius C, Landberg R, González-Domínguez R. QC omics: Recommendations and Guidelines for Robust, Easily Implementable and Reportable Quality Control of Metabolomics Data. Anal Chem 2024; 96:1064-1072. [PMID: 38179935 PMCID: PMC10809278 DOI: 10.1021/acs.analchem.3c03660] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/03/2023] [Accepted: 12/21/2023] [Indexed: 01/06/2024]
Abstract
The implementation of quality control strategies is crucial to ensure the reproducibility, accuracy, and meaningfulness of metabolomics data. However, this pivotal step is often overlooked within the metabolomics workflow and frequently relies on the use of nonstandardized and poorly reported protocols. To address current limitations in this respect, we have developed QComics, a robust, easily implementable and reportable method for monitoring and controlling data quality. The protocol operates in various sequential steps aimed to (i) correct for background noise and carryover, (ii) detect signal drifts and "out-of-control" observations, (iii) deal with missing data, (iv) remove outliers, (v) monitor quality markers to identify samples affected by improper collection, preprocessing, or storage, and (vi) assess overall data quality in terms of precision and accuracy. Notably, this tool considers important issues often neglected along quality control, such as the need of separately handling missing values and truly absent data to avoid losing relevant biological information, as well as the large impact that preanalytical factors may elicit on metabolomics results. Altogether, the guidelines compiled in QComics might contribute to establishing gold standard recommendations and best practices for quality control within the metabolomics community.
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Affiliation(s)
- Álvaro González-Domínguez
- Instituto
de Investigación e Innovación Biomédica de Cádiz
(INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz 11009, Spain
| | - Núria Estanyol-Torres
- Division
of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology,SE-412 96Gothenburg ,Sweden
| | - Carl Brunius
- Division
of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology,SE-412 96Gothenburg ,Sweden
| | - Rikard Landberg
- Division
of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology,SE-412 96Gothenburg ,Sweden
| | - Raúl González-Domínguez
- Instituto
de Investigación e Innovación Biomédica de Cádiz
(INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz 11009, Spain
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11
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Chen Y, Li H, Kong T, Shan L, Hao L, Wang F. The low ratio of ghrelin in plasma and cerebrospinal fluid might be beneficial to sleep. Pharmacol Biochem Behav 2023; 233:173672. [PMID: 37944671 DOI: 10.1016/j.pbb.2023.173672] [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: 09/06/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023]
Abstract
OBJECTIVE Ghrelin is physiologically important for maintaining sleep rhythm. Cigarette smoking has been demonstrated to significantly increase the risk of insufficient sleep by regulating ghrelin at the central and peripheral levels. No research has been published to study the relationship between active smoking and sleep via ghrelin level in cerebrospinal fluid (CSF). METHODS A total of 139 Chinese males were recruited and divided into active smokers (n = 77) and non-smokers (n = 62). The levels of CSF and plasma ghrelin were measured. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep. RESULTS Non-smokers had lower PSQI scores (1.71 ± 1.93) than active smokers (3.70 ± 1.78). Non-smokers have significantly lower plasma ghrelin levels and lower plasma/CSF ghrelin ratio but higher CSF ghrelin than active smokers. Among non-smokers, plasma ghrelin levels were not correlated with PSQI scores (all p > 0.05), CSF ghrelin levels were positively correlated with PSQI scores (r = 0.309, p = 0.019), and the plasma/CSF ghrelin ratio was negatively correlated with PSQI scores (r = -0.346, p = 0.008). CONCLUSIONS This study is the first to reveal the relationship between cigarette smoking, high CSF ghrelin levels and insufficient sleep, suggesting that maintaining a normal plasma/CSF ghrelin ratio may be the physiological mechanism of healthy sleep, and the insufficient sleep population must quit smoking.
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Affiliation(s)
- Yuanyuan Chen
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot 010110, China
| | - Hui Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
| | - Tiantian Kong
- Xinjiang Key Laboratory of Neurological Disorder Research, the Second Affiliated Hospital of Xinjiang Medical University, Urumqi 830063, China
| | - Ligang Shan
- Department of Anesthesiology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China
| | - Lei Hao
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot 010110, China.
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing 100096, China.
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12
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Zhang T, Gao H, Fan Y, Chen S, Li Y, Liu R, Li T, Yin C. Gut microbiota disorder induces liver dysfunction in polycystic ovary syndrome rats' model by regulating metabolite rosmarinic acid. Life Sci 2023; 330:121912. [PMID: 37423380 DOI: 10.1016/j.lfs.2023.121912] [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: 05/12/2023] [Revised: 06/20/2023] [Accepted: 07/03/2023] [Indexed: 07/11/2023]
Abstract
AIMS The present study aims to investigate the impact of the gut microbiota and serum metabolites on the regulation of liver dysfunction in PCOS. MATERIALS AND METHODS PCOS rat models were established by treating Sprague Dawley (SD) rats with DHEA (an androgen, 60 mg/kg) and LET (a nonsteroidal aromatase inhibitor, 1 mg/kg) for 90 days. Hematoxylin and eosin staining (H&E), Western blotting, and radioimmunoassay were employed to test ovarian and liver functions. Gut microbiome and serum metabolites were assessed using 16S rRNA amplicon sequencing and non-targeted metabolomics, respectively. The association between gut microbiota and serum metabolites was examined using Spearman analysis. Finally, using HepG2 cells to investigate the function of the serum metabolite rosmarinic acid (RA). KEY FINDINGS Both Dehydroepiandrosterone (DHEA) and letrozole (LET) treatments induced a PCOS phenotype and liver dysfunction. However, LET resulted in more severe lipid accumulation and liver cell apoptosis than DHEA. 16S rRNA sequencing and non-targeted metabolomics analysis revealed significant differences in beta diversity and serum metabolite profiles among the three groups. Furthermore, among the significantly changed metabolites, RA was found to have a significant correlation with the levels of serum aspartate transaminase (AST) and lactate dehydrogenase (LDH) and could promote HepG2 cell apoptosis. SIGNIFICANCE Restoring gut microbiota, altering serum metabolites and/or decreasing RA may provide a new insight to treat this complication.
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Affiliation(s)
- Tingting Zhang
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Huimin Gao
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Yali Fan
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Shuya Chen
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Yingying Li
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Ruixia Liu
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Tianhe Li
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China.
| | - Chenghong Yin
- Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China.
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13
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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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14
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Liang K, Li Q, Song Z, Zhao K, Su R, Huang S, Guo X, Li Y. Endogenous Plasma Peptides Modulated by Protease in a Time-Dependent Manner as Effective Biomarkers for Preanalytical Quality Control. J Proteome Res 2023; 22:3029-3039. [PMID: 37530177 DOI: 10.1021/acs.jproteome.3c00335] [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: 08/03/2023]
Abstract
Non-cryopreservation temperature exposure (NCE) is a vital preanalytical factor for assessing plasma quality. NCE can introduce undesirable errors in clinical diagnosis or when developing biomarkers of diseases. Biomarkers that can effectively indicate the changes in sample quality caused by long-term NCE (0-several days) are limited. Low-molecular-weight (LMW) peptides in the plasma are modulated by endogenous proteases. These protease activities are significantly correlated with NCE temperatures and duration, indicating a potential link of these protease reactions with the preanalytical quality of plasma samples. In this study, two groups of plasma samples were aged at room temperature (RT, 57 samples) and 4 °C (69 samples) for different durations (0, 1, 2, 5, and 10 days), and LMW peptidomics were analyzed through nanopore-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The analysis revealed 10 peptides that consistently exhibited time-dependent changes, which were used to develop multiple-variable models for predicting the changes in sample quality resulting from extended NCE. These biomarker models exhibited outstanding performance in distinguishing poor-quality samples aged at both RT and 4 °C. To validate the findings, tests on samples from validation sets were conducted by analysts who were blinded to the detailed conditions, which revealed a high specificity (94.3-96.9%) and sensitivity (90.5-99.3%). These results indicate the potential of these peptides as novel biomarkers of quality control.
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Affiliation(s)
- Kai Liang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Western Institute of Health Data Science, Chongqin 400050, China
| | - Qianqian Li
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhijing Song
- Western Institute of Health Data Science, Chongqin 400050, China
| | - Keli Zhao
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Rong Su
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Shengchun Huang
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Xueyan Guo
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Yan Li
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Western Institute of Health Data Science, Chongqin 400050, China
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15
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Gowda GAN, Pascua V, Raftery D. Anomalous Dynamics of Labile Metabolites in Cold Human Blood Detected Using 1H NMR Spectroscopy. Anal Chem 2023; 95:12923-12930. [PMID: 37582233 PMCID: PMC10528060 DOI: 10.1021/acs.analchem.3c02478] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
Recent efforts in our laboratory have enabled access to an unprecedented number (∼90) of quantifiable metabolites in human blood by a simple nuclear magnetic resonance (NMR) spectroscopy method, which includes energy coenzymes, redox coenzymes, and antioxidants that are fundamental to cellular functions [ J. Magn. Reson. Open 2022, 12-13, 100082]. The coenzymes and antioxidants, however, are notoriously labile and are extremely sensitive to specimen harvesting, extraction, and measurement conditions. This problem is largely underappreciated and carries the risk of grossly inaccurate measurements and incorrect study outcomes. As a part of addressing this challenge, in this study, human blood specimens were comprehensively and quantitatively investigated using 1H NMR spectroscopy. Freshly drawn human blood specimens were treated or not treated with methanol, ethanol, or a mixture of methanol and chloroform, and stored on ice or on bench, at room temperature for different time periods from 0 to 24 h, prior to storing at -80 °C. Interestingly, the labile metabolite levels were stable in blood treated with an organic solvent. However, their levels in blood in untreated samples increased or decreased by factors of up to 5 or more within 3 h. Further, surprisingly, and contrary to the current knowledge about metabolite stability, the variation of coenzyme levels was more dramatic in blood stored on ice than on bench, at room temperature. In addition, unlike the generally observed phenomenon of oxidation of redox coenzymes, reduction was observed in untreated blood. Such preanalytical dynamics of the labile metabolites potentially arises from the active cellular metabolism. From the metabolomics perspective, the massive variation of the labile metabolite levels even in blood stored on ice is alarming and stresses the critical need to immediately quench the cellular metabolism for reliable analyses. Overall, the results provide compelling evidence that warrants a paradigm shift in the sample collection protocol for blood metabolomics involving labile metabolites.
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, University of Washington, Seattle, WA 98109
- Mitochondria and Metabolism Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109
| | - Vadim Pascua
- Northwest Metabolomics Research Center, University of Washington, Seattle, WA 98109
| | - Daniel Raftery
- Northwest Metabolomics Research Center, University of Washington, Seattle, WA 98109
- Mitochondria and Metabolism Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109
- Fred Hutchinson Cancer Center, Seattle, WA 98109
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16
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Zachariah JP, Pena S, Lupo PJ, Putluri N, Penny DJ, Richard MA. Effect of exogenous l-carnitine on aortic stiffness in dyslipidemic adolescents: Design of a quadruple-blind, randomized, controlled interventional trial. Contemp Clin Trials Commun 2023; 34:101174. [PMID: 37448910 PMCID: PMC10338141 DOI: 10.1016/j.conctc.2023.101174] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/22/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023] Open
Abstract
Background Atherosclerotic cardiovascular disease (ASCVD) risk factors including vascular remodeling leading to hypertension and dyslipidemia are prevalent among children and adolescents. Conflicting observational and Mendelian randomization data suggest endogenous carnitine may affect arterial stiffness and lipid traits. Because of this, we developed a study to evaluate the causal role for carnitine in arterial stiffness at a point when the lifecourse trajectory to hypertension can be modified. Methods This study is a mechanistic, double-blinded, randomized control trial (RCT) in 166 adolescents with dyslipidemia for the effect of 6 months of maximum dose 3 g daily oral l-carnitine supplementation (CS+) versus placebo (CS-) on aortic stiffness measured as carotid-femoral pulse wave velocity (CFPWV) and pulse pressure (PP); lipid concentrations (total cholesterol, HDL-C, triglycerides, and LDL-C) and serum fatty acid oxidation biomarkers by metabolomic analysis. Conclusions The simultaneous evaluation of endogenous carnitine genetic effects and exogenous l-carnitine supplementation may facilitate future therapies for youth with cardiometabolic derangement to arrest atherosclerotic changes.
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Affiliation(s)
- Justin P. Zachariah
- Section of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Sandra Pena
- Section of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Philip J. Lupo
- Section of Hematology-Oncology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Nagireddy Putluri
- Department of Molecular and Cellular Biology, Dan L. Duncan Comprehensive Cancer Center, Advanced Technology Core, Alkek Center for Molecular Discovery, Baylor College of Medicine, Houston, TX, USA
| | - Daniel J. Penny
- Section of Pediatric Cardiology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Melissa A. Richard
- Section of Hematology-Oncology, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
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17
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Wang Q, Hoene M, Hu C, Fritsche L, Ahrends R, Liebisch G, Ekroos K, Fritsche A, Birkenfeld AL, Liu X, Zhao X, Li Q, Su B, Peter A, Xu G, Lehmann R. Ex vivo instability of lipids in whole blood: preanalytical recommendations for clinical lipidomics studies. J Lipid Res 2023; 64:100378. [PMID: 37087100 PMCID: PMC10208886 DOI: 10.1016/j.jlr.2023.100378] [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: 02/01/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 04/24/2023] Open
Abstract
Reliability, robustness, and interlaboratory comparability of quantitative measurements is critical for clinical lipidomics studies. Lipids' different ex vivo stability in blood bears the risk of misinterpretation of data. Clear recommendations for the process of blood sample collection are required. We studied by UHPLC-high resolution mass spectrometry, as part of the "Preanalytics interest group" of the International Lipidomics Society, the stability of 417 lipid species in EDTA whole blood after exposure to either 4°C, 21°C, or 30°C at six different time points (0.5 h-24 h) to cover common daily routine conditions in clinical settings. In total, >800 samples were analyzed. 325 and 288 robust lipid species resisted 24 h exposure of EDTA whole blood to 21°C or 30°C, respectively. Most significant instabilities were detected for FA, LPE, and LPC. Based on our data, we recommend cooling whole blood at once and permanent. Plasma should be separated within 4 h, unless the focus is solely on robust lipids. Lists are provided to check the ex vivo (in)stability of distinct lipids and potential biomarkers of interest in whole blood. To conclude, our results contribute to the international efforts towards reliable and comparable clinical lipidomics data paving the way to the proper diagnostic application of distinct lipid patterns or lipid profiles in the future.
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Affiliation(s)
- Qingqing Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China; University of Chinese Academy of Sciences, Beijing, China
| | - Miriam Hoene
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
| | - Chunxiu Hu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Louise Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Robert Ahrends
- Department of Analytical Chemistry, University of Vienna, Vienna, Austria
| | - Gerhard Liebisch
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Kim Ekroos
- Lipidomics Consulting Ltd., Espoo, Finland
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas L Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Qi Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Benzhe Su
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
| | - Andreas Peter
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China.
| | - Rainer Lehmann
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany.
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18
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Safari F, Kehelpannala C, Safarchi A, Batarseh AM, Vafaee F. Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis. Cancers (Basel) 2023; 15:2780. [PMID: 37345117 DOI: 10.3390/cancers15102780] [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: 02/24/2023] [Revised: 05/02/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023] Open
Abstract
Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.
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Affiliation(s)
- Fatemeh Safari
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
| | - Cheka Kehelpannala
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Azadeh Safarchi
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- Microbiomes for One Systems Health, Health and Biosecurity, CSIRO, Westmead, NSW 2145, Australia
| | - Amani M Batarseh
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- UNSW Data Science Hub (uDASH), University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- OmniOmics.ai Pty Ltd., Sydney, NSW 2035, Australia
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19
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Jin N, Yu M, Du X, Wu Z, Zhai C, Pan H, Gu J, Xie B. Identification of potential serum biomarkers for congenital heart disease children with pulmonary arterial hypertension by metabonomics. BMC Cardiovasc Disord 2023; 23:167. [PMID: 36991345 PMCID: PMC10061882 DOI: 10.1186/s12872-023-03171-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 03/06/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Pulmonary arterial hypertension is a common complication in patients with congenital heart disease. In the absence of early diagnosis and treatment, pediatric patients with PAH has a poor survival rate. Here, we explore serum biomarkers for distinguishing children with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) from CHD. METHODS Samples were analyzed by nuclear magnetic resonance spectroscopy-based metabolomics and 22 metabolites were further quantified by ultra-high-performance liquid chromatography-tandem mass spectroscopy. RESULTS Serum levels of betaine, choline, S-Adenosyl methionine (SAM), acetylcholine, xanthosine, guanosine, inosine and guanine were significantly altered between CHD and PAH-CHD. Logistic regression analysis showed that combination of serum SAM, guanine and N-terminal pro-brain natriuretic peptide (NT-proBNP), yielded the predictive accuracy of 157 cases was 92.70% with area under the curve of the receiver operating characteristic curve value of 0.9455. CONCLUSION We demonstrated that a panel of serum SAM, guanine and NT-proBNP is potential serum biomarkers for screening PAH-CHD from CHD.
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Affiliation(s)
- Nan Jin
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Zhejiang, China
| | - Mengjie Yu
- Key laboratory of medical electronics and digital health of Zhejiang Province, Medical College of Jiaxing University, Jiaxing University, Jiaxing, China
- The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China
| | - Xiaoyue Du
- Key laboratory of medical electronics and digital health of Zhejiang Province, Medical College of Jiaxing University, Jiaxing University, Jiaxing, China
| | - Zhiguo Wu
- The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China
| | - Changlin Zhai
- Department of Cardiovascular Diseases, Institute of Atherosclerosis, the Affiliated hospital of Jiaxing University, Jiaxing, China
| | - Haihua Pan
- Department of Cardiovascular Diseases, Institute of Atherosclerosis, the Affiliated hospital of Jiaxing University, Jiaxing, China
| | - Jinping Gu
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Zhejiang, China.
| | - Baogang Xie
- College of Pharmaceutical Sciences, Zhejiang University of Technology, Zhejiang, China.
- Key laboratory of medical electronics and digital health of Zhejiang Province, Medical College of Jiaxing University, Jiaxing University, Jiaxing, China.
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20
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Garwolińska D, Kot-Wasik A, Hewelt-Belka W. Pre-analytical aspects in metabolomics of human biofluids - sample collection, handling, transport, and storage. Mol Omics 2023; 19:95-104. [PMID: 36524542 DOI: 10.1039/d2mo00212d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).
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Affiliation(s)
- Dorota Garwolińska
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
| | - Agata Kot-Wasik
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
| | - Weronika Hewelt-Belka
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
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21
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Isolated Effects of Plasma Freezing versus Thawing on Metabolite Stability. Metabolites 2022; 12:metabo12111098. [DOI: 10.3390/metabo12111098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/02/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
Freezing and thawing plasma samples is known to perturb metabolite stability. However, no study has systematically tested how different freezing and thawing methods affect plasma metabolite levels. The objective of this study was to isolate the effects of freezing from thawing on mouse plasma metabolite levels, by comparing a matrix of freezing and thawing conditions through 10 freeze–thaw cycles. We tested freezing with liquid nitrogen (LN2), at −80 °C, or at −20 °C, and thawing quickly in room temperature water or slowly on ice. Plasma samples were extracted and the relative abundance of 87 metabolites was obtained via liquid chromatography–mass spectrometry (LC–MS). Observed changes in metabolite abundance by treatment group correlated with the amount of time it took for samples to freeze or thaw. Thus, snap-freezing with LN2 and quick-thawing with water led to minimal changes in metabolite levels. Conversely, samples frozen at −20 °C exhibited the most changes in metabolite levels, likely because freezing required about 4 h, versus freezing instantaneously in LN2. Overall, our results show that plasma samples subjected to up to 10 cycles of LN2 snap-freezing with room temperature water quick-thawing exhibit remarkable metabolomic stability.
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22
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Mahajan UM, Oehrle B, Sirtl S, Alnatsha A, Goni E, Regel I, Beyer G, Vornhülz M, Vielhauer J, Chromik A, Bahra M, Klein F, Uhl W, Fahlbusch T, Distler M, Weitz J, Grützmann R, Pilarsky C, Weiss FU, Adam MG, Neoptolemos JP, Kalthoff H, Rad R, Christiansen N, Bethan B, Kamlage B, Lerch MM, Mayerle J. Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis. Gastroenterology 2022; 163:1407-1422. [PMID: 35870514 DOI: 10.1053/j.gastro.2022.07.047] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 06/28/2022] [Accepted: 07/14/2022] [Indexed: 12/19/2022]
Abstract
BACKGROUND & AIMS Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly lethal malignancy requiring efficient detection when the primary tumor is still resectable. We previously developed the MxPancreasScore comprising 9 analytes and serum carbohydrate antigen 19-9 (CA19-9), achieving an accuracy of 90.6%. The necessity for 5 different analytical platforms and multiple analytical runs, however, hindered clinical applicability. We therefore aimed to develop a simpler single-analytical run, single-platform diagnostic signature. METHODS We evaluated 941 patients (PDAC, 356; chronic pancreatitis [CP], 304; nonpancreatic disease, 281) in 3 multicenter independent tests, and identification (ID) and validation cohort 1 (VD1) and 2 (VD2) were evaluated. Targeted quantitative plasma metabolite analysis was performed on a liquid chromatography-tandem mass spectrometry platform. A machine learning-aided algorithm identified an improved (i-Metabolic) and minimalistic metabolic (m-Metabolic) signatures, and compared them for performance. RESULTS The i-Metabolic Signature, (12 analytes plus CA19-9) distinguished PDAC from CP with area under the curve (95% confidence interval) of 97.2% (97.1%-97.3%), 93.5% (93.4%-93.7%), and 92.2% (92.1%-92.3%) in the ID, VD1, and VD2 cohorts, respectively. In the VD2 cohort, the m-Metabolic signature (4 analytes plus CA19-9) discriminated PDAC from CP with a sensitivity of 77.3% and specificity of 89.6%, with an overall accuracy of 82.4%. For the subset of 45 patients with PDAC with resectable stages IA-IIB tumors, the sensitivity, specificity, and accuracy were 73.2%, 89.6%, and 82.7%, respectively; for those with detectable CA19-9 >2 U/mL, 81.6%, 88.7%, and 84.5%, respectively; and for those with CA19-9 <37 U/mL, 39.7%, 94.1%, and 76.3%, respectively. CONCLUSIONS The single-platform, single-run, m-Metabolic signature of just 4 metabolites used in combination with serum CA19-9 levels is an innovative accurate diagnostic tool for PDAC at the time of clinical presentation, warranting further large-scale evaluation.
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Affiliation(s)
- Ujjwal M Mahajan
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Bettina Oehrle
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Simon Sirtl
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Ahmed Alnatsha
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Elisabetta Goni
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Ivonne Regel
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Georg Beyer
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Marlies Vornhülz
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Jakob Vielhauer
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany
| | - Ansgar Chromik
- Department of General and Visceral Surgery, Asklepios Klinikum Hamburg, Hamburg, Germany
| | - Markus Bahra
- Zentrum für Onkologische Oberbauchchirurgie und Robotik, Krankenhaus Waldfriede, Berlin, Germany
| | - Fritz Klein
- Department of General, Visceral and Transplantation Surgery, Charité, Campus Virchow Klinikum, Berlin, Germany
| | - Waldemar Uhl
- Department of General and Visceral Surgery, Katholisches Klinikum Bochum, Bochum, Germany
| | - Tim Fahlbusch
- Department of General and Visceral Surgery, Katholisches Klinikum Bochum, Bochum, Germany
| | - Marius Distler
- Department for Visceral, Thoracic and Vascular Surgery, University Hospital, Technical University Dresden, Dresden, Germany
| | - Jürgen Weitz
- Department for Visceral, Thoracic and Vascular Surgery, University Hospital, Technical University Dresden, Dresden, Germany
| | - Robert Grützmann
- Department of Surgery, Erlangen University Hospital, Erlangen, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Erlangen, Germany
| | - Christian Pilarsky
- Department of Surgery, Erlangen University Hospital, Erlangen, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Erlangen, Germany
| | - Frank Ulrich Weiss
- Department of Medicine A, University Medicine Greifswald, Greifswald, Germany
| | - M Gordian Adam
- Metanomics Health GmbH, Berlin, Germany; biocrates life sciences ag, Innsbruck, Austria
| | - John P Neoptolemos
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Holger Kalthoff
- Section for Molecular Oncology, Institut for Experimental Cancer Research (IET), Universitätsklinikum Schleswig-Holstein, Kiel, Germany
| | - Roland Rad
- Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany; Institute of Molecular Oncology and Functional Genomics, TUM School of Medicine and Center for Translational Cancer Research (TranslaTUM), Technische Universität München, Munich, Germany
| | - Nicole Christiansen
- Metanomics Health GmbH, Berlin, Germany; TrinamiX GmbH, Ludwigshafen am Rhein, Rheinland-Pfalz, Germany
| | | | | | - Markus M Lerch
- Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany; Department of Medicine A, University Medicine Greifswald, Greifswald, Germany; Ludwig Maximilian University Klinikum, Munich, Germany
| | - Julia Mayerle
- Department of Medicine II, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany; Bavarian Centre for Cancer Research (Bayerisches Zentrum für Krebsforschung), Munich, Germany.
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He M, Huang Y, Wang Y, Liu J, Han M, Xiao Y, Zhang N, Gui H, Qiu H, Cao L, Jia W, Huang S. Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker. Front Immunol 2022; 13:954801. [PMID: 36248825 PMCID: PMC9554639 DOI: 10.3389/fimmu.2022.954801] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 09/12/2022] [Indexed: 11/25/2022] Open
Abstract
SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR < 0.05, absolute log2 fold change greater than 0.25, and VIP >1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What’s more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.
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Affiliation(s)
- Maozhang He
- Department of Microbiology, The Key Laboratory of Microbiology and Parasitology of Anhui Province, The Key Laboratory of Zoonoses of High Institutions in Anhui, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Yixuan Huang
- Department of Clinical Medicine, The First School of Clinical Medicine, Anhui Medical University, Hefei, China
| | - Yun Wang
- Department of Nosocomial Infection Control, Anhui No.2 Provincial People’s Hospital, Hefei, China
| | - Jiling Liu
- Department of Microbiology, The Key Laboratory of Microbiology and Parasitology of Anhui Province, The Key Laboratory of Zoonoses of High Institutions in Anhui, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Maozhen Han
- School of Life Sciences, Anhui Medical University, Hefei, China
| | - Yixuan Xiao
- Department of Microbiology, The Key Laboratory of Microbiology and Parasitology of Anhui Province, The Key Laboratory of Zoonoses of High Institutions in Anhui, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Na Zhang
- Department of Nosocomial Infection Control, Anhui No.2 Provincial People’s Hospital, Hefei, China
| | - Hongya Gui
- Department of Microbiology, The Key Laboratory of Microbiology and Parasitology of Anhui Province, The Key Laboratory of Zoonoses of High Institutions in Anhui, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Huan Qiu
- School of Nursing, Anhui Medical University, Hefei, China
| | - Liqing Cao
- School of Life Sciences, Anhui Medical University, Hefei, China
| | - Weihua Jia
- School of Life Sciences, Anhui Medical University, Hefei, China
- *Correspondence: Shenghai Huang, ; Weihua Jia,
| | - Shenghai Huang
- Department of Microbiology, The Key Laboratory of Microbiology and Parasitology of Anhui Province, The Key Laboratory of Zoonoses of High Institutions in Anhui, School of Basic Medical Sciences, Anhui Medical University, Hefei, China
- School of Life Sciences, Anhui Medical University, Hefei, China
- *Correspondence: Shenghai Huang, ; Weihua Jia,
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24
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Assessing the Impacts of Preanalytical Field Sampling Challenges on the Reliability of Serum Aflatoxin B1-Lysine Measurements by Use of LC-MS/MS. Toxins (Basel) 2022; 14:toxins14090612. [PMID: 36136549 PMCID: PMC9503385 DOI: 10.3390/toxins14090612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/15/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Aflatoxin exposure is endemic in developing countries with warm, humid climates that promote toxigenic mold growth on crops and foodstuffs. Estimating human aflatoxin exposure is key to identifying and abating contamination sources. Serum aflatoxin B1 bound to albumin lysine (AFB1-lys) is a preferred exposure biomarker, but field sample collection, processing, transportation, and storage logistics are challenging. We validated an improved LC-MS/MS method for serum AFB1-lys and applied it to three field sampling challenges: transportation/storage (elevated temperature); collection/processing (hemolysis); and sample type substitution (heparinized plasma). Our new LC-MS/MS method had a LOD of 0.03 ng/mL, accuracy (mean spike recovery) of 112%, total imprecision (replicate pool measurements) ≤5% at ≥0.2 ng/mL, and results that were 95.1% similar (mean percentage similarity) to an established method. AFB1-lys in human serum spiked with serum from aflatoxin-dosed rats was stable for 14 days at both ambient (22.5 °C) and elevated (38 °C) temperatures. Simulated hemolysis (adding 0.25–3 mg hemoglobin) did not affect AFB1-lys accuracy at ≥0.5 ng/mL but caused 10–25% signal suppression. Heparinized plasma AFB1-lys was 99.0% similar to serum but interfered with albumin measurements (bromocresol green) causing spurious low bias. Further investigation is warranted, but our findings suggest that AFB1-lys is pre-analytically robust.
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25
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Stability of Metabolomic Content during Sample Preparation: Blood and Brain Tissues. Metabolites 2022; 12:metabo12090811. [PMID: 36144215 PMCID: PMC9505456 DOI: 10.3390/metabo12090811] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 08/26/2022] [Accepted: 08/26/2022] [Indexed: 11/16/2022] Open
Abstract
Thermal and enzymatic reactions can significantly change the tissue metabolomic content during the sample preparation. In this work, we evaluated the stability of metabolites in human whole blood, serum, and rat brain, as well as in metabolomic extracts from these tissues. We measured the concentrations of 63 metabolites in brain and 52 metabolites in blood. We have shown that metabolites in the extracts from biological tissues are stable within 24 h at 4 °C. Serum and whole blood metabolomes are also rather stable, changes in metabolomic content of the whole blood homogenate become apparent only after 1–2 h of incubation at 4 °C, and become strong after 24 h. The most significant changes correspond to energy metabolites: the concentrations of ATP and ADP decrease fivefold, and the concentrations of NAD, NADH, and NADPH decrease below the detectable level. A statistically significant increase was observed for AMP, IMP, hypoxanthine, and nicotinamide. The brain tissue is much more metabolically active than human blood, and significant metabolomic changes occur already within the first several minutes during the brain harvest and sample homogenization. At a longer timescale (hours), noticeable changes were observed for all classes of compounds, including amino acids, organic acids, alcohols, amines, sugars, nitrogenous bases, nucleotides, and nucleosides.
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26
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Xue W, Yang C, Liu M, Lin X, Wang M, Wang X. Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize. Molecules 2022; 27:4711. [PMID: 35897888 PMCID: PMC9330060 DOI: 10.3390/molecules27154711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/14/2022] [Accepted: 07/18/2022] [Indexed: 11/29/2022] Open
Abstract
The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.
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Affiliation(s)
- Weifeng Xue
- Technical Center of Dalian Customs, Dalian 116000, China; (C.Y.); (M.L.); (X.L.); (M.W.); (X.W.)
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27
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Niedermair T, Bhatt M, Babel M, Feustel M, Mamilos A, Schweikl H, Ferstl G, Hofman P, Brochhausen C. Interim Storage of Biospecimen at Satellite Collection Centers: Dewar and Cryotube Choice Are Important for Temporary Storage in Liquid Nitrogen. Biopreserv Biobank 2022; 21:149-157. [PMID: 35704045 DOI: 10.1089/bio.2022.0002] [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] [Indexed: 11/12/2022] Open
Abstract
One major goal of biobanks is to provide the best possible biospecimen quality for research use. This can be achieved, notably in accredited structures, by using standardized procedures for collection, processing, and storage of biosamples and associated data. Since tissue samples of a clinical biobank are commonly collected at surgical theaters in satellite locations or hospitals in remote areas, adequate temporary storage of the biosample is mandatory to maintain optimal sample quality. In cases where immediate snap freezing of the collected material is possible, interim storage of the samples in portable dewars filled with liquid nitrogen (LN2) is a widely used method. Therefore, the ideal dewar size and maximum storage time need to be considered to maintain an optimal biospecimen quality. In addition, the nature of the cryotube material is an important aspect for keeping the biosample safe while storing it in LN2. The objective of this study was to test different dewar vessels with respect to LN2 volume and consumption and to analyze the impact of LN2 contact on cryotube material through scanning electron microscopy.
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Affiliation(s)
- Tanja Niedermair
- Institute of Pathology, University Regensburg, University of Regensburg, Regensburg, Germany
- Central Biobank Regensburg, University Clinic and University of Regensburg, Regensburg, Germany
| | - Meet Bhatt
- Laboratory of Clinical and Experimental Pathology, FHU OncoAge, Nice Hospital Center, University Côte d'Azur, Nice, France
- Hospital-Integrated Biobank (BB-0033-00025), University Cote D'Azur, Nice, France
| | - Maximilian Babel
- Institute of Pathology, University Regensburg, University of Regensburg, Regensburg, Germany
- Central Biobank Regensburg, University Clinic and University of Regensburg, Regensburg, Germany
| | - Moritz Feustel
- Institute of Pathology, University Regensburg, University of Regensburg, Regensburg, Germany
- Central Biobank Regensburg, University Clinic and University of Regensburg, Regensburg, Germany
| | - Andreas Mamilos
- Institute of Pathology, University Regensburg, University of Regensburg, Regensburg, Germany
| | - Helmut Schweikl
- Department of Conservative Dentistry and Periodontology, University Hospital Regensburg, University of Regensburg, Regensburg, Germany
| | - Gerlinde Ferstl
- Department of Conservative Dentistry and Periodontology, University Hospital Regensburg, University of Regensburg, Regensburg, Germany
| | - Paul Hofman
- Laboratory of Clinical and Experimental Pathology, FHU OncoAge, Nice Hospital Center, University Côte d'Azur, Nice, France
- Hospital-Integrated Biobank (BB-0033-00025), University Cote D'Azur, Nice, France
| | - Christoph Brochhausen
- Institute of Pathology, University Regensburg, University of Regensburg, Regensburg, Germany
- Central Biobank Regensburg, University Clinic and University of Regensburg, Regensburg, Germany
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28
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Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women. Metabolites 2022; 12:metabo12050372. [PMID: 35629875 PMCID: PMC9147746 DOI: 10.3390/metabo12050372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 04/01/2022] [Accepted: 04/11/2022] [Indexed: 11/17/2022] Open
Abstract
In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups.
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29
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Study on the Effect of Crushed Rice-Lotus Seed Starch Reconstituted Rice on Lipid Metabolism Histology in Rats. J FOOD QUALITY 2022. [DOI: 10.1155/2022/9105936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The study investigated the changes of lipid metabolism histology in rats under the three groups of dietary modifications after dietary intervention in (Sprague-Dawley, SD) SD rats using lotus seed reconstituted rice, ordinary rice, and high-fat feed made from lotus seed starch-rice flour after extrusion and puffing. It was found that the high-fat feed could lead to the disorder of lipid metabolism in rats, and the accumulation of lipid metabolism substances caused by the high-fat feed was significantly increased; the intervention of ordinary rice and high-dose reconstituted rice revealed that the high-dose reconstituted rice could improve the disorder of lipid metabolism and the accumulation of lipid substances caused by the high-fat feed to a greater extent. The main lipid substances were PC, TAG, Cer, CE, SM, PE, LPC, Acar, DAG, FAHFA, OxPI, PI, SQDG, Cer/NS, GlcADG, HBMP, Cer/NDS, HexCer/NS, etc., and the study confirmed that the reconstituted rice made from lotus seeds in this experiment was better than ordinary rice, and the high-dose reconstituted rice obtained from the study has a better modulating effect on lipid metabolism disorders and organism damage caused by high-fat feed.
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30
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Lisitsyna A, Moritz F, Liu Y, Al Sadat L, Hauner H, Claussnitzer M, Schmitt-Kopplin P, Forcisi S. Feature Selection Pipelines with Classification for Non-targeted Metabolomics Combining the Neural Network and Genetic Algorithm. Anal Chem 2022; 94:5474-5482. [PMID: 35344349 DOI: 10.1021/acs.analchem.1c03237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Non-targeted metabolomics via high-resolution mass spectrometry methods, such as direct infusion Fourier transform-ion cyclotron resonance mass spectrometry (DI-FT-ICR MS), produces data sets with thousands of features. By contrast, the number of samples is in general substantially lower. This disparity presents challenges when analyzing non-targeted metabolomics data sets and often requires custom methods to uncover information not always accessible via classical statistical techniques. In this work, we present a pipeline that combines a convolutional neural network with traditional statistical approaches and an adaptation of a genetic algorithm. The developed method was applied to a lifestyle intervention cohort data set, where subjects at risk of type 2 diabetes underwent an oral glucose tolerance test. Feature selection is the final result of the pipeline, achieved through classification of the data set via a neural network, with a precision-recall score of over 0.9 on the test set. The features most relevant for the described classification were then chosen via a genetic algorithm. The output of the developed pipeline encompasses approximately 200 features with high predictive scores, providing a fingerprint of the metabolic changes in the prediabetic class on the data set. Our framework presents a new approach which allows to apply complex modeling based on convolutional neural networks for the analysis of high-resolution mass spectrometric data.
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Affiliation(s)
- Anna Lisitsyna
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,German Center for Diabetes Research (DZD), Neuherberg 85764, Germany
| | - Franco Moritz
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany
| | - Youzhong Liu
- Analytical Development, Small Molecule Development, Janssen Pharmaceutical Companies of Johnson and Johnson, Beerse 2340, Belgium
| | - Loubna Al Sadat
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich 80686, Germany
| | - Hans Hauner
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich 80686, Germany.,Else Kröner-Fresenius-Centre for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising 85354, Germany
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge 02141-2023 Massachusetts, United States.,Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02108, United States.,Harvard Medical School, Harvard University, Boston, Massachusetts 02108, United States
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,Chair of Analytical Food Chemistry, TUM School of Life Sciences, Technical University Munich, Munich 80686, Germany
| | - Sara Forcisi
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,German Center for Diabetes Research (DZD), Neuherberg 85764, Germany
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31
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Coppens V, Verkerk R, Morrens M. Tracking TRYCAT: A Critical Appraisal of Kynurenine Pathway Quantifications in Blood. Front Pharmacol 2022; 13:825948. [PMID: 35250576 PMCID: PMC8892384 DOI: 10.3389/fphar.2022.825948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/19/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Violette Coppens
- Faculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium.,Scientific Initiative of Neuropsychiatric and Psychopharmacological Studies (SINAPS), University Psychiatric Centre Duffel, Duffel, Belgium
| | - Robert Verkerk
- Laboratory of Medical Biochemistry, University of Antwerp, Antwerp, Belgium
| | - Manuel Morrens
- Faculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium.,Scientific Initiative of Neuropsychiatric and Psychopharmacological Studies (SINAPS), University Psychiatric Centre Duffel, Duffel, Belgium
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Yu M, Wen W, Yi X, Zhu W, Aa J, Wang G. Plasma Metabolomics Reveals Diagnostic Biomarkers and Risk Factors for Esophageal Squamous Cell Carcinoma. Front Oncol 2022; 12:829350. [PMID: 35198450 PMCID: PMC8859148 DOI: 10.3389/fonc.2022.829350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 01/19/2022] [Indexed: 01/15/2023] Open
Abstract
Esophageal squamous carcinoma (ESCC) has a high morbidity and mortality rate. Identifying risk metabolites associated with its progression is essential for the early prevention and treatment of ESCC. A total of 373 ESCC, 40 esophageal squamous dysplasia (ESD), and 218 healthy controls (HC) subjects were enrolled in this study. Gas chromatography-mass spectrometry (GC/MS) was used to acquire plasma metabolic profiles. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate the potential diagnosis and prediction ability markers. The levels of alpha-tocopherol and cysteine were progressively decreased, while the levels of aminomalonic acid were progressively increased during the various stages (from precancerous lesions to advanced-stage) of exacerbation in ESCC patients. Alpha-tocopherol performed well for the differential diagnosis of HC and ESD/ESCC (AUROC>0.90). OR calculations showed that a high level of aminomalonic acid was not only a risk factor for further development of ESD to ESCC (OR>13.0) but also a risk factor for lymphatic metastasis in ESCC patients (OR>3.0). A low level of alpha-tocopherol was a distinguished independent risk factor of ESCC (OR< 0.5). The panel constructed by glycolic acid, oxalic acid, glyceric acid, malate and alpha-tocopherol performed well in distinguishing between ESD/ESCC from HC in the training and validation set (AUROC>0.95). In conclusion, the oxidative stress function was impaired in ESCC patients, and improving the body’s antioxidant function may help reduce the early occurrence of ESCC.
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Affiliation(s)
- Mengjie Yu
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
| | - Wei Wen
- Department of Thoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xin Yi
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
| | - Wei Zhu
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Jiye Aa, ; Wei Zhu,
| | - Jiye Aa
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
- *Correspondence: Jiye Aa, ; Wei Zhu,
| | - Guangji Wang
- Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, China
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Xue W, Zhang H, Wang M, Liu Y, Liu M, Shen B. Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:233-240. [PMID: 34907408 DOI: 10.1039/d1ay01576a] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg-1 and 0.3-2.1 μg kg-1 in bovine and piscine muscle matrices, respectively.
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Affiliation(s)
- Weifeng Xue
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Haiqin Zhang
- School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China
| | - Mei Wang
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Ying Liu
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Mengyao Liu
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Baozhen Shen
- Technical Center of Dalian Customs, Dalian 116000, China.
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Liu Z, Jeffrey W, Rui B. Metabolomics as a promising tool for improving understanding of Multiple Sclerosis: a review of recent advances. Biomed J 2022; 45:594-606. [PMID: 35042018 PMCID: PMC9486246 DOI: 10.1016/j.bj.2022.01.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 12/29/2021] [Accepted: 01/10/2022] [Indexed: 12/23/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system that usually affects young adults. The development of MS is closely related to the changes in the metabolome. Metabolomics studies have been performed using biofluids or tissue samples from rodent models and human patients to reveal metabolic alterations associated with MS progression. This review aims to provide an overview of the applications of metabolomics that for the investigations of the perturbed metabolic pathways in MS and to reveal the potential of metabolomics in personalizing treatments. In conclusion, informative variations of metabolites can be potential biomarkers in advancing our understanding of MS pathogenesis for MS diagnosis, predicting the progression of the disease, and estimating drug effects. Metabolomics will be a promising technique for improving clinical care in MS.
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Affiliation(s)
- Zhicheng Liu
- Anhui Provincial laboratory of inflammatory and immunity disease, Anhui Institute of Innovative Drugs School of Pharmacy, Anhui Medical University, 81 Meishan Road, Hefei 230032, China.
| | - Waters Jeffrey
- Department of Neurology, Henry Ford Health System, Detroit, MI 48202, USA
| | - Bin Rui
- Department of Neurology, Henry Ford Health System, Detroit, MI 48202, USA.
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Handling unstable analytes: literature review and expert panel survey by Japan Bioanalysis Forum Discussion Group. Bioanalysis 2021; 14:169-185. [PMID: 34894755 DOI: 10.4155/bio-2021-0229] [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: 12/23/2022] Open
Abstract
Analyzing unstable small molecule drugs and metabolites in blood continues to be challenging for bioanalysis. Although scientific countermeasures such as immediate cooling, immediate freezing, addition of enzyme inhibitors, pH adjustment, dried blood spot or derivatization have been developed, selecting the best practices has become an issue in the pharmaceutical industry as the number of drugs with such problems is increasing, even for generic drugs. In this study, we conducted a comprehensive literature review and a questionnaire survey to determine a suitable practice for evaluating instability and implementing countermeasures. Three areas of focus, matrix selection, effect of hemolysis and selection of esterase inhibitors, are discussed.
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Evolution of the protein corona affects macrophage polarization. Int J Biol Macromol 2021; 191:192-200. [PMID: 34547310 DOI: 10.1016/j.ijbiomac.2021.09.081] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 08/19/2021] [Accepted: 09/13/2021] [Indexed: 01/14/2023]
Abstract
When nanoparticles (NPs) come into contact with bioenvironments, a protein corona forms on the NP surface. Previous reports showed that the constituents of the corona change with time. However, how different protein corona compositions influence cells, especially immune cells, has received less attention. Macrophages are important immune cells that can be polarized into a pro-inflammatory (M1) or anti-inflammatory (M2) phenotype. In this study, AuNPs were incubated with human plasma for different periods to obtain time-related AuNP-coronas, and the influences of time-related AuNP-coronas on macrophage polarization were investigated. The macrophage morphology, biomarkers, cytokine secretion studies show that the pristine AuNPs and 4 h-AuNP-corona induced macrophage cells into M2 phenotype, while the co-incubation of 12 h-AuNP-corona and macrophage cells result in M1 phenotype. Further proteomic analysis showed that the compositions of protein corona were changing constantly after AuNPs contacted with plasma. When the incubation time increased to 12 h, the immune proteins in protein corona were increased significantly, which play a key role in modulation of the different macrophages polarization. Our findings demonstrated that plasma incubation time is an important parameter that needs to be taken into account in the study of nano-immune interactions and safe use of NPs in biological systems. Moreover, our finding can be a new efficient strategy for activating inflammatory or anti-inflammatory in medical treatment.
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Yu M, Sun R, Zhao Y, Shao F, Zhu W, Aa J. Detection and verification of coexisting diagnostic markers in plasma and serum of patients with non-small-cell lung cancer. Future Oncol 2021; 17:4355-4369. [PMID: 34674559 DOI: 10.2217/fon-2021-0025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Aim: To screen and identify the potential biomarkers co-existing in plasma and serum of patients with non-small-cell lung cancer (NSCLC), and establish appropriate diagnostic models. Methods: A cohort of 195 plasma samples and 180 serum samples were obtained from healthy controls (HCs), adenocarcinoma (AdC) and squamous cell carcinoma (SqCC) patients enrolled from the First Affiliated Hospital of Nanjing Medical University. Metabolites in plasma and serum were analyzed by GC-MS. Results: Hypoxanthine was found to have good performance in the differential diagnosis of NSCLC (including AdC and SqCC) and HC (area under the receiver operating characteristic [AUROC] ≥0.85). Combinations of metabolites could be used for differential diagnosis of NSCLC and HC (AUROC >0.93), AdC and HC (AUROC >0.91), SqCC and HC (AUROC >0.95), AdC and SqCC (AUROC >0.72). Conclusions: Metabolomics based on GC-MS can screen and identify the differential metabolites coexisting in plasma and serum of patients with NSCLC, and prediction models established by this method can be used for the differential diagnosis of patients with NSCLC.
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Affiliation(s)
- Mengjie Yu
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
| | - Runbin Sun
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
| | - Yuqing Zhao
- Phase I Clinical Trial Unit, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Feng Shao
- Phase I Clinical Trial Unit, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Wei Zhu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Jiye Aa
- Key Laboratory of Drug Metabolism & Pharmacokinetics, China Pharmaceutical University, Nanjing, Jiangsu Province 210009, China
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Mohammad S, Bhattacharjee J, Vasanthan T, Harris CS, Bainbridge SA, Adamo KB. Metabolomics to understand placental biology: Where are we now? Tissue Cell 2021; 73:101663. [PMID: 34653888 DOI: 10.1016/j.tice.2021.101663] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/30/2021] [Accepted: 10/04/2021] [Indexed: 12/16/2022]
Abstract
Metabolomics, the application of analytical chemistry methodologies to survey the chemical composition of a biological system, is used to globally profile and compare metabolites in one or more groups of samples. Given that metabolites are the terminal end-products of cellular metabolic processes, or 'phenotype' of a cell, tissue, or organism, metabolomics is valuable to the study of the maternal-fetal interface as it has the potential to reveal nuanced complexities of a biological system as well as differences over time or between individuals. The placenta acts as the primary site of maternal-fetal exchange, the success of which is paramount to growth and development of offspring during pregnancy and beyond. Although the study of metabolomics has proven moderately useful for the screening, diagnosis, and understanding of the pathophysiology of pregnancy complications, the placental metabolome in the context of a healthy pregnancy remains poorly characterized and understood. Herein, we discuss the technical aspects of metabolomics and review the current literature describing the placental metabolome in human and animal models, in the context of health and disease. Finally, we highlight areas for future opportunities in the emerging field of placental metabolomics.
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Affiliation(s)
- S Mohammad
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada
| | - J Bhattacharjee
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada
| | - T Vasanthan
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada
| | - C S Harris
- Department of Biology & Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON, Canada
| | - S A Bainbridge
- Interdisciplinary School of Health Sciences, Faculty of Health Sciences, University of Ottawa, ON, Canada; Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, ON, Canada
| | - K B Adamo
- School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
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Zheng R, Brunius C, Shi L, Zafar H, Paulson L, Landberg R, Naluai ÅT. Prediction and evaluation of the effect of pre-centrifugation sample management on the measurable untargeted LC-MS plasma metabolome. Anal Chim Acta 2021; 1182:338968. [PMID: 34602206 DOI: 10.1016/j.aca.2021.338968] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 08/17/2021] [Accepted: 08/18/2021] [Indexed: 12/16/2022]
Abstract
Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics to predict and evaluate the influence of pre-centrifugation temperature and delayed time on plasma samples. Pre-centrifugation temperature (4, 25 and 37 °C; classification rate 87%) and time (5-210 min; Q2 = 0.82) were accurately predicted using Random Forest (RF). Metabolites uniquely reflecting temperature and temperature-time interactions were discovered using a combination of RF and generalized linear models. Time-related metabolite profiles suggested a perturbed stability of the metabolome at all temperatures in the investigated time period (5-210 min), and the variation at 4 °C was observed in particular before 90 min. Fourteen and eight metabolites were selected and validated for accurate prediction of pre-centrifugation temperature (classification rate 94%) and delay time (Q2 = 0.90), respectively. In summary, the metabolite profile was rapidly affected by pre-centrifugation delay at all temperatures and thus the pre-centrifugation delay should be as short as possible for metabolomics analysis. The metabolite panels provided accurate predictions of pre-centrifugation delay time and temperature in healthy individuals in a separate validation sample. Such predictions could potentially be useful for assessing legacy samples where relevant metadata is lacking. However, validation in larger populations and different phenotypes, including disease states, is needed.
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Affiliation(s)
- Rui Zheng
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Carl Brunius
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Chalmers Mass Spectrometry Infrastructure, Chalmers University of Technology, Gothenburg, Sweden
| | - Lin Shi
- Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi' an, China.
| | - Huma Zafar
- Biobank West, Sahlgrenska University Hospital, Region Västra Götaland, Sweden
| | - Linda Paulson
- Biobank West, Sahlgrenska University Hospital, Region Västra Götaland, Sweden
| | - Rikard Landberg
- Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Åsa Torinsson Naluai
- Biobank West, Sahlgrenska University Hospital, Region Västra Götaland, Sweden; Institute of Biomedicine, Biobank Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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Xue W, Zhang H, Liu M, Chen X, He S, Chu Y. Metabolomics-based screening analysis of PPCPs in water pretreated with five different SPE columns. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:4594-4603. [PMID: 34580678 DOI: 10.1039/d1ay01313k] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The selection of solid phase extraction (SPE) columns in the pretreatment process plays a decisive role in the screening and quantification of pharmaceutical and personal care products (PPCPs). As growing PPCPs have frequently been detected in the aquatic environment, it is a burdensome task through one-by-one recovery comparison to judge which column presents relatively ideal pretreatment results for PPCPs. In view of this, we developed a novel metabolomics-based screening method based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) results to accurately, rapidly and comprehensively choose a suitable column from 5 different kinds to handle 64 PPCPs in two water environments (50 μg L-1/pH ≅ 7.0/pure water and 1 μg L-1/pH ≅ 7.0/reservoir water) through seeking 'biomarkers', for which multivariate and univariate analyses were adopted. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) play a crucial role in multivariate analysis, and the pairwise t-test and fold change judgement in univariate analysis. Each column group was fully separated from the other 4 groups in PCA and OPLS-DA plots, laying a foundation to distinguish 'biomarkers' between groups. The S-Plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify 'biomarkers', which were further verified by a pairwise t-test and fold change judgement. Eventually, the 64 PPCPs as 'biomarkers' were divided into 5 groups, which correspond to 5 column groups, consistent with the findings of traditional PPCP recovery comparison, proving the validity of the metabolomics-based screening method. This novel method will exhibit greater superiority in choosing suitable SPE columns to handle a growing and larger number of PPCPs in water environments and beyond.
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Affiliation(s)
- Weifeng Xue
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Haiqin Zhang
- School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China
| | - Mengyao Liu
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Xi Chen
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Shuwen He
- Technical Center of Dalian Customs, Dalian 116000, China.
| | - Yingqian Chu
- Technical Center of Dalian Customs, Dalian 116000, China.
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Heiling S, Knutti N, Scherr F, Geiger J, Weikert J, Rose M, Jahns R, Ceglarek U, Scherag A, Kiehntopf M. Metabolite Ratios as Quality Indicators for Pre-Analytical Variation in Serum and EDTA Plasma. Metabolites 2021; 11:638. [PMID: 34564454 PMCID: PMC8465943 DOI: 10.3390/metabo11090638] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 12/18/2022] Open
Abstract
In clinical diagnostics and research, blood samples are one of the most frequently used materials. Nevertheless, exploring the chemical composition of human plasma and serum is challenging due to the highly dynamic influence of pre-analytical variation. A prominent example is the variability in pre-centrifugation delay (time-to-centrifugation; TTC). Quality indicators (QI) reflecting sample TTC are of utmost importance in assessing sample history and resulting sample quality, which is essential for accurate diagnostics and conclusive, reproducible research. In the present study, we subjected human blood to varying TTCs at room temperature prior to processing for plasma or serum preparation. Potential sample QIs were identified by Ultra high pressure liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) based metabolite profiling in samples from healthy volunteers (n = 10). Selected QIs were validated by a targeted MS/MS approach in two independent sets of samples from patients (n = 40 and n = 70). In serum, the hypoxanthine/guanosine (HG) and hypoxanthine/inosine (HI) ratios demonstrated high diagnostic performance (Sensitivity/Specificity > 80%) for the discrimination of samples with a TTC > 1 h. We identified several eicosanoids, such as 12-HETE, 15-(S)-HETE, 8-(S)-HETE, 12-oxo-HETE, (±)13-HODE and 12-(S)-HEPE as QIs for a pre-centrifugation delay > 2 h. 12-HETE, 12-oxo-HETE, 8-(S)-HETE, and 12-(S)-HEPE, and the HI- and HG-ratios could be validated in patient samples.
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Affiliation(s)
- Sven Heiling
- Institute of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany; (N.K.); (F.S.); (M.R.)
| | - Nadine Knutti
- Institute of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany; (N.K.); (F.S.); (M.R.)
| | - Franziska Scherr
- Institute of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany; (N.K.); (F.S.); (M.R.)
| | - Jörg Geiger
- Interdisciplinary Bank of Biological Material and Data Würzburg (IBDW), Straubmühlweg 2a, Haus A9, 97078 Würzburg, Germany; (J.G.); (R.J.)
| | - Juliane Weikert
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.W.); (U.C.)
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, 04103 Leipzig, Germany
| | - Michael Rose
- Institute of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany; (N.K.); (F.S.); (M.R.)
| | - Roland Jahns
- Interdisciplinary Bank of Biological Material and Data Würzburg (IBDW), Straubmühlweg 2a, Haus A9, 97078 Würzburg, Germany; (J.G.); (R.J.)
| | - Uta Ceglarek
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.W.); (U.C.)
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, 04103 Leipzig, Germany
| | - André Scherag
- Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, Bachstrasse 18, 07743 Jena, Germany;
| | - Michael Kiehntopf
- Institute of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany; (N.K.); (F.S.); (M.R.)
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42
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McGranaghan P, Kirwan JA, Garcia-Rivera MA, Pieske B, Edelmann F, Blaschke F, Appunni S, Saxena A, Rubens M, Veledar E, Trippel TD. Lipid Metabolite Biomarkers in Cardiovascular Disease: Discovery and Biomechanism Translation from Human Studies. Metabolites 2021; 11:metabo11090621. [PMID: 34564437 PMCID: PMC8470800 DOI: 10.3390/metabo11090621] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/30/2021] [Accepted: 09/06/2021] [Indexed: 12/12/2022] Open
Abstract
Lipids represent a valuable target for metabolomic studies since altered lipid metabolism is known to drive the pathological changes in cardiovascular disease (CVD). Metabolomic technologies give us the ability to measure thousands of metabolites providing us with a metabolic fingerprint of individual patients. Metabolomic studies in humans have supported previous findings into the pathomechanisms of CVD, namely atherosclerosis, apoptosis, inflammation, oxidative stress, and insulin resistance. The most widely studied classes of lipid metabolite biomarkers in CVD are phospholipids, sphingolipids/ceramides, glycolipids, cholesterol esters, fatty acids, and acylcarnitines. Technological advancements have enabled novel strategies to discover individual biomarkers or panels that may aid in the diagnosis and prognosis of CVD, with sphingolipids/ceramides as the most promising class of biomarkers thus far. In this review, application of metabolomic profiling for biomarker discovery to aid in the diagnosis and prognosis of CVD as well as metabolic abnormalities in CVD will be discussed with particular emphasis on lipid metabolites.
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Affiliation(s)
- Peter McGranaghan
- Department of Internal Medicine and Cardiology, Charité Campus Virchow-Klinikum, 13353 Berlin, Germany; (P.M.); (B.P.); (F.E.); (F.B.)
- Baptist Health South Florida, Miami, FL 33143, USA; (A.S.); (M.R.); (E.V.)
| | - Jennifer A. Kirwan
- Metabolomics Platform, Berlin Institute of Health at Charité Universitätsmedizin Berlin, 13353 Berlin, Germany; (J.A.K.); (M.A.G.-R.)
- Max Delbrück Center for Molecular Research, 13125 Berlin, Germany
- School of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, UK
| | - Mariel A. Garcia-Rivera
- Metabolomics Platform, Berlin Institute of Health at Charité Universitätsmedizin Berlin, 13353 Berlin, Germany; (J.A.K.); (M.A.G.-R.)
- Max Delbrück Center for Molecular Research, 13125 Berlin, Germany
| | - Burkert Pieske
- Department of Internal Medicine and Cardiology, Charité Campus Virchow-Klinikum, 13353 Berlin, Germany; (P.M.); (B.P.); (F.E.); (F.B.)
- DZHK (German Centre for Cardiovascular Research), 13353 Berlin, Germany
- Berlin Institute of Health, 13353 Berlin, Germany
- German Heart Center Berlin, Department of Cardiology, 13353 Berlin, Germany
| | - Frank Edelmann
- Department of Internal Medicine and Cardiology, Charité Campus Virchow-Klinikum, 13353 Berlin, Germany; (P.M.); (B.P.); (F.E.); (F.B.)
- DZHK (German Centre for Cardiovascular Research), 13353 Berlin, Germany
- German Heart Center Berlin, Department of Cardiology, 13353 Berlin, Germany
| | - Florian Blaschke
- Department of Internal Medicine and Cardiology, Charité Campus Virchow-Klinikum, 13353 Berlin, Germany; (P.M.); (B.P.); (F.E.); (F.B.)
- DZHK (German Centre for Cardiovascular Research), 13353 Berlin, Germany
| | - Sandeep Appunni
- Department of Biochemistry, Government Medical College, Kozhikode, Kerala 673008, India;
| | - Anshul Saxena
- Baptist Health South Florida, Miami, FL 33143, USA; (A.S.); (M.R.); (E.V.)
| | - Muni Rubens
- Baptist Health South Florida, Miami, FL 33143, USA; (A.S.); (M.R.); (E.V.)
| | - Emir Veledar
- Baptist Health South Florida, Miami, FL 33143, USA; (A.S.); (M.R.); (E.V.)
- Department of Biostatistics, Florida International University, Miami, FL 33199, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Tobias Daniel Trippel
- Department of Internal Medicine and Cardiology, Charité Campus Virchow-Klinikum, 13353 Berlin, Germany; (P.M.); (B.P.); (F.E.); (F.B.)
- DZHK (German Centre for Cardiovascular Research), 13353 Berlin, Germany
- Correspondence: ; Tel.: +49-30-450-553765
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Sotelo-Orozco J, Chen SY, Hertz-Picciotto I, Slupsky CM. A Comparison of Serum and Plasma Blood Collection Tubes for the Integration of Epidemiological and Metabolomics Data. Front Mol Biosci 2021; 8:682134. [PMID: 34307452 PMCID: PMC8295687 DOI: 10.3389/fmolb.2021.682134] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/23/2021] [Indexed: 02/04/2023] Open
Abstract
Blood is a rich biological sample routinely collected in clinical and epidemiological studies. With advancements in high throughput -omics technology, such as metabolomics, epidemiology can now delve more deeply and comprehensively into biological mechanisms involved in the etiology of diseases. However, the impact of the blood collection tube matrix of samples collected needs to be carefully considered to obtain meaningful biological interpretations and understand how the metabolite signatures are affected by different tube types. In the present study, we investigated whether the metabolic profile of blood collected as serum differed from samples collected as ACD plasma, citrate plasma, EDTA plasma, fluoride plasma, or heparin plasma. We identified and quantified 50 metabolites present in all samples utilizing nuclear magnetic resonance (NMR) spectroscopy. The heparin plasma tubes performed the closest to serum, with only three metabolites showing significant differences, followed by EDTA which significantly differed for five metabolites, and fluoride tubes which differed in eleven of the fifty metabolites. Most of these metabolite differences were due to higher levels of amino acids in serum compared to heparin plasma, EDTA plasma, and fluoride plasma. In contrast, metabolite measurements from ACD and citrate plasma differed significantly for approximately half of the metabolites assessed. These metabolite differences in ACD and citrate plasma were largely due to significant interfering peaks from the anticoagulants themselves. Blood is one of the most banked samples and thus mining and comparing samples between studies requires understanding how the metabolite signature is affected by the different media and different tube types.
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Affiliation(s)
- Jennie Sotelo-Orozco
- Department of Public Health Sciences, University of California Davis, Davis, CA, United States
| | - Shin-Yu Chen
- Department of Food Science and Technology, University of California Davis, Davis, CA, United States
| | - Irva Hertz-Picciotto
- Department of Public Health Sciences, University of California Davis, Davis, CA, United States
| | - Carolyn M Slupsky
- Department of Food Science and Technology, University of California Davis, Davis, CA, United States.,Department of Nutrition, University of California Davis, Davis, CA, United States
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Shi B, Ding H, Wang L, Wang C, Tian X, Fu Z, Zhang L, Han L. Investigation on the stability in plant metabolomics with a special focus on freeze-thaw cycles: LC-MS and NMR analysis to Cassiae Semen (Cassia obtusifolia L.) seeds as a case study. J Pharm Biomed Anal 2021; 204:114243. [PMID: 34273658 DOI: 10.1016/j.jpba.2021.114243] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/27/2021] [Accepted: 07/03/2021] [Indexed: 01/16/2023]
Abstract
Metabolomics is a rapid and sensitive tool for the detection of dynamic metabolic compositions in the study of systemic metabolic consequences. However, it is also susceptible to a tiny variation of pre-analytical handling procedures. To provide reproducible results, specific knowledge on metabolites perturbance along with different freeze-thaw cycles (FTCs) is needed for further metabolomics studies. In this paper, five FTCs of germinated Cassiae Semen (CS) were chosen as a case study to investigate the influence of FTC effect based on UHPLC-Q-Orbitrap-MS and NMR technologies. A total of 108 metabolites were relatively quantified by LC-MS and NMR analyses. Principal component analysis (PCA) showed that the first and second FTC samples are welly separated from the other groups; however, the extent of FTC-induced effects are smaller after the third cycle. Upon five consecutive FTCs, alterations which consisted of decreased stachyose, sucrose, norrubrofusarin-6-O-β-d-glucopyranoside, and quercetin 3-(3″-acetylgalactoside), as well as increased phenylalanine, leucine, isoleucine, methionine, phenylalanine, mannose, gluconic acid, and valine, could be observed. FTC does not exert the same effect on all metabolites. Although a large number of secondary metabolites were stable when subjected to five FTCs, FTC effects may lead to false-positive in the discovery of biomarker. In the case of reusing plant seed samples, no more than three consecutive freeze-thaw cycles were found advisable. This work provides unique perspectives on the FTC effects, which may fill in some existing gaps in the knowledge of the stability of plant metabolites during sample pre-handling.
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Affiliation(s)
- Biru Shi
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Hui Ding
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Liming Wang
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Chenxi Wang
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Xiaoxuan Tian
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Zhifei Fu
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China
| | - Lihua Zhang
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China.
| | - Lifeng Han
- Tianjin State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China; Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, PR China.
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From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids. Anal Bioanal Chem 2021; 413:5567-5585. [PMID: 34159398 PMCID: PMC8410705 DOI: 10.1007/s00216-021-03450-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 05/24/2021] [Accepted: 05/31/2021] [Indexed: 11/22/2022]
Abstract
The stability of lipids and other metabolites in human body fluids ranges from very stable over several days to very unstable within minutes after sample collection. Since the high-resolution analytics of metabolomics and lipidomics approaches comprise all these compounds, the handling of body fluid samples, and thus the pre-analytical phase, is of utmost importance to obtain valid profiling data. This phase consists of two parts, sample collection in the hospital (“bedside”) and sample processing in the laboratory (“bench”). For sample quality, the apparently simple steps in the hospital are much more critical than the “bench” side handling, where (bio)analytical chemists focus on highly standardized processing for high-resolution analysis under well-controlled conditions. This review discusses the most critical pre-analytical steps for sample quality from patient preparation; collection of body fluids (blood, urine, cerebrospinal fluid) to sample handling, transport, and storage in freezers; and subsequent thawing using current literature, as well as own investigations and practical experiences in the hospital. Furthermore, it provides guidance for (bio)analytical chemists to detect and prevent potential pre-analytical pitfalls at the “bedside,” and how to assess the quality of already collected body fluid samples. A knowledge base is provided allowing one to decide whether or not the sample quality is acceptable for its intended use in distinct profiling approaches and to select the most suitable samples for high-resolution metabolomics and lipidomics investigations.
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Gao P, Huang X, Fang XY, Zheng H, Cai SL, Sun AJ, Zhao L, Zhang Y. Application of metabolomics in clinical and laboratory gastrointestinal oncology. World J Gastrointest Oncol 2021; 13:536-549. [PMID: 34163571 PMCID: PMC8204353 DOI: 10.4251/wjgo.v13.i6.536] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/09/2021] [Accepted: 05/19/2021] [Indexed: 02/06/2023] Open
Abstract
Metabolites are versatile bioactive molecules. They are not only the substrates and/or the products of enzymatic reactions but also act as the regulators in the systemic metabolism. Metabolomics is a high-throughput analytical strategy to qualify or quantify as many metabolites as possible in the metabolomes. It is an indispensable part of systems biology. The leading techniques in this field are mainly based on mass spectrometry and nuclear magnetic resonance spectroscopy. The metabolomic analysis has gained wide use in bioscience fields. In the tumor research arena, metabolomics can be employed to identify biomarkers for prediction, diagnosis, and prognosis. Chemotherapeutic effect evaluation and personalized medicine decision-making can also benefit from metabolomic analysis of patient biofluid or biopsy samples. Many cell-level studies can help in disease exploration. In this review, the basic features and principles of varied metabolomic analysis are introduced. The value of metabolomics in clinical and laboratory gastrointestinal cancer studies is discussed, especially for mass spectrometry applications. Besides, combined use of metabolomics and other tools to solve problems in cancer practice is briefly illustrated. In summary, metabolomics paves a new way to explore cancerous diseases in the light of small molecules.
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Affiliation(s)
- Peng Gao
- Department ofClinical Laboratory, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Xin Huang
- Department of Internal Medicine, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Xue-Yan Fang
- Department of Nursing, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Hui Zheng
- Clinical Research Center, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Shu-Ling Cai
- Clinical Research Center, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Ai-Jun Sun
- Clinical Research Center, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Liang Zhao
- Department of Internal Medicine, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
| | - Yong Zhang
- Department of Surgery, Dalian Sixth People's Hospital, Dalian 116031, Liaoning Province, China
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Meregalli C, Bonomo R, Cavaletti G, Carozzi VA. Blood molecular biomarkers for chemotherapy-induced peripheral neuropathy: From preclinical models to clinical practice. Neurosci Lett 2021; 749:135739. [PMID: 33600907 DOI: 10.1016/j.neulet.2021.135739] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 02/04/2021] [Accepted: 02/09/2021] [Indexed: 12/26/2022]
Abstract
Chemotherapy-induced peripheral neuropathy (CIPN) has long been recognized as a clinically significant issue in patients treated with antineoplastic drugs. This common long-term toxic side-effect which negatively impacts the outcome of the disease can lead to disability and have detrimental effects on patients' quality of life. Since axonal injury is a prominent feature of CIPN, responsible for several sensory symptoms, including pain, sensory loss and hypersensitivity to mechanical and/or cold stimuli in the hands and feet, neurophysiological assessments remain the gold standard for clinical diagnosis of CIPN. Given the large impact of CIPN on cancer patients, there is increasing emphasis on biomarkers of adverse outcomes in safety assessment and translational research, to prevent permanent neuroaxonal damage. Since the results on reliable blood molecular markers for axonal degeneration are still controversial, here we provide a brief overview of blood molecular biomarkers used for assessing and/or predicting CIPN in preclinical and clinical settings.
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Affiliation(s)
- C Meregalli
- Experimental Neurology Unit, School of Medicine and Surgery, NeuroMI (Milan Center for Neuroscience), University of Milan Bicocca, Monza, Italy
| | - R Bonomo
- Experimental Neurology Unit, School of Medicine and Surgery, NeuroMI (Milan Center for Neuroscience), University of Milan Bicocca, Monza, Italy; PhD Program in Neuroscience, University of Milan Bicocca, Monza, Italy
| | - G Cavaletti
- Experimental Neurology Unit, School of Medicine and Surgery, NeuroMI (Milan Center for Neuroscience), University of Milan Bicocca, Monza, Italy
| | - V A Carozzi
- Experimental Neurology Unit, School of Medicine and Surgery, NeuroMI (Milan Center for Neuroscience), University of Milan Bicocca, Monza, Italy; Young Against Pain Group, Italy.
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48
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Claus RA, Graeler MH. Sphingolipidomics in Translational Sepsis Research-Biomedical Considerations and Perspectives. Front Med (Lausanne) 2021; 7:616578. [PMID: 33553212 PMCID: PMC7854573 DOI: 10.3389/fmed.2020.616578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 12/03/2020] [Indexed: 12/11/2022] Open
Abstract
Scientific Background: Sphingolipids are a highly diverse group of lipids with respect to physicochemical properties controlling either structure, distribution, or function, all of them regulating cellular response in health and disease. Mass spectrometry, on the other hand, is an analytical technique characterizing ionized molecules or fragments thereof by mass-to-charge ratios, which has been prosperingly developed for rapid and reliable qualitative and quantitative identification of lipid species. Parallel to best performance of in-depth chromatographical separation of lipid classes, preconditions of precise quantitation of unique molecular species by preprocessing of biological samples have to be fulfilled. As a consequence, “lipid profiles” across model systems and human individuals, esp. complex (clinical) samples, have become eminent over the last couple of years due to sensitivity, specificity, and discriminatory capability. Therefore, it is significance to consider the entire experimental strategy from sample collection and preparation, data acquisition, analysis, and interpretation. Areas Covered: In this review, we outline considerations with clinical (i.e., human) samples with special emphasis on sample handling, specific physicochemical properties, target measurements, and resulting profiling of sphingolipids in biomedicine and translational research to maximize sensitivity and specificity as well as to provide robust and reproducible results. A brief commentary is also provided regarding new insights of “clinical sphingolipidomics” in translational sepsis research. Expert Opinion: The role of mass spectrometry of sphingolipids and related species (“sphingolipidomics”) to investigate cellular and compartment-specific response to stress, e.g., in generalized infection and sepsis, is on the rise and the ability to integrate multiple datasets from diverse classes of biomolecules by mass spectrometry measurements and metabolomics will be crucial to fostering our understanding of human health as well as response to disease and treatment.
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Affiliation(s)
- Ralf A Claus
- Department for Anesthesiology and Intensive Care Medicine, Sepsis Research, Jena University Hospital, Jena, Germany
| | - Markus H Graeler
- Department for Anesthesiology and Intensive Care Medicine, Sepsis Research, Jena University Hospital, Jena, Germany.,Center for Sepsis Care & Control, Jena University Hospital, Jena, Germany.,Center for Molecular Biomedicine (CMB), Jena University Hospital, Jena, Germany
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Lucas S, Tencerova M, von der Weid B, Andersen TL, Attané C, Behler-Janbeck F, Cawthorn WP, Ivaska KK, Naveiras O, Podgorski I, Reagan MR, van der Eerden BCJ. Guidelines for Biobanking of Bone Marrow Adipose Tissue and Related Cell Types: Report of the Biobanking Working Group of the International Bone Marrow Adiposity Society. Front Endocrinol (Lausanne) 2021; 12:744527. [PMID: 34646237 PMCID: PMC8503265 DOI: 10.3389/fendo.2021.744527] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/24/2021] [Indexed: 12/19/2022] Open
Abstract
Over the last two decades, increased interest of scientists to study bone marrow adiposity (BMA) in relation to bone and adipose tissue physiology has expanded the number of publications using different sources of bone marrow adipose tissue (BMAT). However, each source of BMAT has its limitations in the number of downstream analyses for which it can be used. Based on this increased scientific demand, the International Bone Marrow Adiposity Society (BMAS) established a Biobanking Working Group to identify the challenges of biobanking for human BMA-related samples and to develop guidelines to advance establishment of biobanks for BMA research. BMA is a young, growing field with increased interest among many diverse scientific communities. These bring new perspectives and important biological questions on how to improve and build an international community with biobank databases that can be used and shared all over the world. However, to create internationally accessible biobanks, several practical and legislative issues must be addressed to create a general ethical protocol used in all institutes, to allow for exchange of biological material internationally. In this position paper, the BMAS Biobanking Working Group describes similarities and differences of patient information (PIF) and consent forms from different institutes and addresses a possibility to create uniform documents for BMA biobanking purposes. Further, based on discussion among Working Group members, we report an overview of the current isolation protocols for human bone marrow adipocytes (BMAds) and bone marrow stromal cells (BMSCs, formerly mesenchymal), highlighting the specific points crucial for effective isolation. Although we remain far from a unified BMAd isolation protocol and PIF, we have summarized all of these important aspects, which are needed to build a BMA biobank. In conclusion, we believe that harmonizing isolation protocols and PIF globally will help to build international collaborations and improve the quality and interpretation of BMA research outcomes.
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Affiliation(s)
- Stephanie Lucas
- Marrow Adiposity and Bone Lab-MABLab ULR4490, Univ. Littoral Côte d’Opale, Boulogne-sur-Mer, Univ. Lille, CHU Lille, Lille, France
| | - Michaela Tencerova
- Molecular Physiology of Bone, Institute of Physiology of the Czech Academy of Sciences, Prague, Czechia
| | - Benoit von der Weid
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Biomedical Sciences, Faculty of Biology and Medicine, Université de Lausanne, Lausanne, Switzerland
| | - Thomas Levin Andersen
- Clinical Cell Biology, Department of Pathology, Odense University Hospital, Odense, Denmark
- Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Molecular Medicine, University of Southern Denmark, Odense, Denmark
- Department of Forensic Medicine, Aarhus University, Aarhus, Denmark
| | - Camille Attané
- Institute of Pharmacology and Structural Biology, Université de Toulouse, CNRS UMR 5089, Toulouse, France
- Equipe labellisée Ligue contre le cancer, Toulouse, France
| | - Friederike Behler-Janbeck
- Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Orthopedics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - William P. Cawthorn
- British Heart Foundation Centre for Cardiovascular Science, The Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Kaisa K. Ivaska
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Olaia Naveiras
- Department of Biomedical Sciences, Faculty of Biology and Medicine, Université de Lausanne, Lausanne, Switzerland
- Hematology Service, Departments of Oncology and Laboratory Medicine, Lausanne University Hospital (CHUV), Université de Lausanne, Lausanne, Switzerland
| | - Izabela Podgorski
- Department of Pharmacology, Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, MI, United States
| | - Michaela R. Reagan
- Center for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, ME, United States
- Graduate School for Biomedical Science, Tufts University, Boston, MA, United States
| | - Bram C. J. van der Eerden
- Laboratory for Calcium and Bone Metabolism, Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
- *Correspondence: Bram C. J. van der Eerden,
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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