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Xu R, Zhang S, Li J, Zhu J. Plasma and serum metabolic analysis of healthy adults shows characteristic profiles by subjects' sex and age. Metabolomics 2024; 20:43. [PMID: 38491253 PMCID: PMC10943143 DOI: 10.1007/s11306-024-02108-z] [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: 09/16/2023] [Accepted: 03/03/2024] [Indexed: 03/18/2024]
Abstract
INTRODUCTION Pre-analytical factors like sex, age, and blood processing methods introduce variability and bias, compromising data integrity, and thus deserve close attention. OBJECTIVES This study aimed to explore the influence of participant characteristics (age and sex) and blood processing methods on the metabolic profile. METHOD A Thermo UPLC-TSQ-Quantiva-QQQ Mass Spectrometer was used to analyze 175 metabolites across 9 classes in 208 paired serum and lithium heparin plasma samples from 51 females and 53 males. RESULTS Comparing paired serum and plasma samples from the same cohort, out of the 13 metabolites that showed significant changes, 4 compounds related to amino acids and derivatives had lower levels in plasma, and 5 other compounds had higher levels in plasma. Sex-based analysis revealed 12 significantly different metabolites, among which most amino acids and derivatives and nitrogen-containing compounds were higher in males, and other compounds were elevated in females. Interestingly, the volcano plot also confirms the similar patterns of amino acids and derivatives higher in males. The age-based analysis suggested that metabolites may undergo substantial alterations during the 25-35-year age range, indicating a potential metabolic turning point associated with the age group. Moreover, a more distinct difference between the 25-35 and above 35 age groups compared to the below 25 and 25-35 age groups was observed, with the most significant compound decreased in the above 35 age groups. CONCLUSION These findings may contribute to the development of comprehensive metabolomics analyses with confounding factor-based adjustment and enhance the reliability and interpretability of future large-scale investigations.
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Affiliation(s)
- Rui Xu
- Human Nutrition Program, Department of Human Sciences, The Ohio State University, Columbus, OH, 43210, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA
| | - Shiqi Zhang
- Human Nutrition Program, Department of Human Sciences, The Ohio State University, Columbus, OH, 43210, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA
| | - Jieli Li
- Department of Pathology, The Ohio State University, Columbus, OH, 43210, USA.
| | - Jiangjiang Zhu
- Human Nutrition Program, Department of Human Sciences, The Ohio State University, Columbus, OH, 43210, USA.
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA.
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Willency JA, Lin Y, Pirro V. Targeted metabolomics in human and animal biofluids and tissues using liquid chromatography coupled with tandem mass spectrometry. STAR Protoc 2024; 5:102884. [PMID: 38367229 PMCID: PMC10882138 DOI: 10.1016/j.xpro.2024.102884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 08/07/2023] [Accepted: 01/26/2024] [Indexed: 02/19/2024] Open
Abstract
Here, we present a targeted polar metabolomics protocol for the analysis of biofluids and frozen tissue biopsies using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We describe steps for sample pretreatment, liquid-liquid extraction, and isolation of polar metabolites. We then detail procedures for target LC-MS/MS analysis. In this protocol, we focus on the analysis of plasma and serum samples. We also provide brief instructions on how to process other biological matrices as supplemental information. For complete details on the use and execution of this protocol, please refer to Coskun et al. (2022).1.
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Affiliation(s)
- Jill A Willency
- Technologies and Operations Group, Eli Lilly and Company, Indianapolis, IN 46225, USA
| | - Yanzhu Lin
- Discovery Statistics, Eli Lilly and Company, Indianapolis, IN 46225, USA
| | - Valentina Pirro
- Technologies and Operations Group, Eli Lilly and Company, Indianapolis, IN 46225, USA.
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Weber DG, Casjens S, Wichert K, Lehnert M, Taeger D, Rihs HP, Brüning T, Johnen G. Tasks and Experiences of the Prospective, Longitudinal, Multicenter MoMar (Molecular Markers) Study for the Early Detection of Mesothelioma in Individuals Formerly Exposed to Asbestos Using Liquid Biopsies. Cancers (Basel) 2023; 15:5896. [PMID: 38136442 PMCID: PMC10742125 DOI: 10.3390/cancers15245896] [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: 08/23/2023] [Revised: 11/07/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
Mesothelioma is an aggressive cancer, strongly associated with prior exposure to asbestos. Commonly, tumors are detected at late stages of the disease. Detection at early stages might be meaningful, because therapies might be more effective when the tumor burden is relatively low and the tumor has not spread to distant sites. Circulating biomarkers in blood might be a promising tool to improve the early detection of mesothelioma, but for screening in asymptomatic subjects, candidate biomarkers need to be validated in appropriate studies. This study was conducted to assess the performance of biomarkers in liquid biopsies to detect mesothelioma at early stages. Over a period of 10 years, 2769 volunteers formerly exposed to asbestos were annually examined and liquid biopsies were collected. A follow-up was completed 17 months after the last blood collection. The article provides a detailed overview of our lessons learned and experiences of conducting a prospective, longitudinal, multicenter study. The existing cohort of individuals at risk is highly suitable for the validation of blood-based biomarkers for the early detection of mesothelioma as well as lung cancer.
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Affiliation(s)
- Daniel Gilbert Weber
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, 44801 Bochum, Germany
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Heng B, Pires AS, Chow S, Krishnamurthy S, Bonnell B, Bustamante S, Guillemin GJ. Stability Studies of Kynurenine Pathway Metabolites in Blood Components Define Optimal Blood Processing Conditions. Int J Tryptophan Res 2023; 16:11786469231213521. [PMID: 38106464 PMCID: PMC10725091 DOI: 10.1177/11786469231213521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/25/2023] [Indexed: 12/19/2023] Open
Abstract
The kynurenine pathway (KP) is the main pathway of tryptophan (TRP) metabolism that generates energy for multiple cellular processes. The activity of this pathway has been shown to be dysregulated in multiple human diseases. The resultant modulation of metabolites has been suggested to comprise biomarkers to track disease progression or could identify new therapeutic targets. While metabolite changes can be measured readily in blood, there is limited knowledge on the effect of blood matrices and sample processing time may have on the stability of KP metabolites. Understanding the stability of KP metabolites in blood is integral to obtaining accurate KP data to correlate with clinical pathology. Hence, the aim of this study was to assess the concentration of KP metabolites in matched whole blood, plasma and serum. The impact of pre-analytical sample processing time in the various blood matrices was also analysed. Serum and plasma had the higher concentration of KP metabolites compared to whole blood. Furthermore, concentrations of KP metabolites declined when the collected blood was processed after 24 hours storage at 4°C. Our study shows that that type of blood matrix and the time to processing have an impact on the stability of the KP metabolites. Serum or plasma are the preferred choice of matrix and the isolation of these matrices from whole blood is best performed immediately after collection for optimal analytical KP data.
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Affiliation(s)
- Benjamin Heng
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Ananda Staats Pires
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Sharron Chow
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Shivani Krishnamurthy
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Brooke Bonnell
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Sonia Bustamante
- Bioanalytical Mass Spectrometry Facility, University of New South Wales, Sydney, Australia
| | - Gilles J Guillemin
- Macquarie Medical School, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
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Kempa S, Buechler C, Föh B, Felthaus O, Prantl L, Günther UL, Müller M, Derer-Petersen S, Sina C, Schmelter F, Tews HC. Serum Metabolomic Profiling of Patients with Lipedema. Int J Mol Sci 2023; 24:17437. [PMID: 38139266 PMCID: PMC10743543 DOI: 10.3390/ijms242417437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 11/30/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Lipedema is a chronic condition characterized by disproportionate and symmetrical enlargement of adipose tissue, predominantly affecting the lower limbs of women. This study investigated the use of metabolomics in lipedema research, with the objective of identifying complex metabolic disturbances and potential biomarkers for early detection, prognosis, and treatment strategies. The study group (n = 25) comprised women diagnosed with lipedema. The controls were 25 lean women and 25 obese females, both matched for age. In the patients with lipedema, there were notable changes in the metabolite parameters. Specifically, lower levels of histidine and phenylalanine were observed, whereas pyruvic acid was elevated compared with the weight controls. The receiver operating characteristic (ROC) curves for the diagnostic accuracy of histidine, phenylalanine, and pyruvic acid concentrations in distinguishing between patients with lipedema and those with obesity but without lipedema revealed good diagnostic ability for all parameters, with pyruvic acid being the most promising (area under the curve (AUC): 0.9992). Subgroup analysis within matched body mass index (BMI) ranges (30.0 to 39.9 kg/m2) further revealed that differences in pyruvic acid, phenylalanine, and histidine levels are likely linked to lipedema pathology rather than BMI variations. Changes in low-density lipoprotein (LDL)-6 TG levels and significant reductions in various LDL-2-carried lipids of patients with lipedema, compared with the lean controls, were observed. However, these lipids were similar between the lipedema patients and the obese controls, suggesting that these alterations are related to adiposity. Metabolomics is a valuable tool for investigating lipedema, offering a comprehensive view of metabolic changes and insights into lipedema's underlying mechanisms.
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Affiliation(s)
- Sally Kempa
- Department of Plastic, Hand, and Reconstructive Surgery, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Christa Buechler
- Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology, and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Bandik Föh
- Institute of Nutritional Medicine, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
- Department of Medicine I, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
| | - Oliver Felthaus
- Department of Plastic, Hand, and Reconstructive Surgery, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Lukas Prantl
- Department of Plastic, Hand, and Reconstructive Surgery, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Ulrich L. Günther
- Institute of Chemistry and Metabolomics, University of Lübeck, 23562 Lübeck, Germany
| | - Martina Müller
- Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology, and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Stefanie Derer-Petersen
- Institute of Nutritional Medicine, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
| | - Christian Sina
- Institute of Nutritional Medicine, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
- Department of Medicine I, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
- Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering (IMTE), 23562 Lübeck, Germany
| | - Franziska Schmelter
- Institute of Nutritional Medicine, University Medical Center Schleswig-Holstein, Campus Lübeck, 23538 Lübeck, Germany
| | - Hauke C. Tews
- Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology, and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
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Ghini V, Meoni G, Vignoli A, Di Cesare F, Tenori L, Turano P, Luchinat C. Fingerprinting and profiling in metabolomics of biosamples. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:105-135. [PMID: 38065666 DOI: 10.1016/j.pnmrs.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 12/18/2023]
Abstract
This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.
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Affiliation(s)
- Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy.
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy; Giotto Biotech S.r.l., Sesto Fiorentino, Italy.
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7
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Clarke ED, Ferguson JJ, Stanford J, Collins CE. Dietary Assessment and Metabolomic Methodologies in Human Feeding Studies: A Scoping Review. Adv Nutr 2023; 14:1453-1465. [PMID: 37604308 PMCID: PMC10721540 DOI: 10.1016/j.advnut.2023.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 05/01/2023] [Accepted: 08/16/2023] [Indexed: 08/23/2023] Open
Abstract
Dietary metabolomics is a relatively objective approach to identifying new biomarkers of dietary intake and for use alongside traditional methods. However, methods used across dietary feeding studies vary, thus making it challenging to compare results. The objective of this study was to synthesize methodological components of controlled human feeding studies designed to quantify the diet-related metabolome in biospecimens, including plasma, serum, and urine after dietary interventions. Six electronic databases were searched. Included studies were as follows: 1) conducted in healthy adults; 2) intervention studies; 3) feeding studies focusing on dietary patterns; and 4) measured the dietary metabolome. From 12,425 texts, 50 met all inclusion criteria. Interventions were primarily crossover (n = 25) and parallel randomized controlled trials (n = 22), with between 8 and 395 participants. Seventeen different dietary patterns were tested, with the most common being the "High versus Low-Glycemic Index/Load" pattern (n = 11) and "Typical Country Intake" (n = 11); with 32 providing all or the majority (90%) of food, 16 providing some food, and 2 providing no food. Metabolites were identified in urine (n = 31) and plasma/serum (n = 30). Metabolites were quantified using liquid chromatography, mass spectroscopy (n = 31) and used untargeted metabolomics (n = 37). There was extensive variability in the methods used in controlled human feeding studies examining the metabolome, including dietary patterns tested, biospecimen sample collection, and metabolomic analysis techniques. To improve the comparability and reproducibility of controlled human feeding studies examining the metabolome, it is important to provide detailed information about the dietary interventions being tested, including information about included or restricted foods, food groups, and meal plans provided. Strategies to control for individual variability, such as a crossover study design, statistical adjustment methods, dietary-controlled run-in periods, or providing standardized meals or test foods throughout the study should also be considered. The protocol for this review has been registered at Open Science Framework (https://doi.org/10.17605/OSF.IO/DAHGS).
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Affiliation(s)
- Erin D Clarke
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jessica Ja Ferguson
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jordan Stanford
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Clare E Collins
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
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Astarita G, Kelly RS, Lasky-Su J. Metabolomics and lipidomics strategies in modern drug discovery and development. Drug Discov Today 2023; 28:103751. [PMID: 37640150 PMCID: PMC10543515 DOI: 10.1016/j.drudis.2023.103751] [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] [Received: 06/27/2023] [Revised: 08/09/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023]
Abstract
Metabolomics and lipidomics have an increasingly pivotal role in drug discovery and development. In the context of drug discovery, monitoring changes in the levels or composition of metabolites and lipids relative to genetic variations yields functional insights, bolstering human genetics and (meta)genomic methodologies. This approach also sheds light on potential novel targets for therapeutic intervention. In the context of drug development, metabolite and lipid biomarkers contribute to enhanced success rates, promising a transformative impact on precision medicine. In this review, we deviate from analytical chemist-focused perspectives, offering an overview tailored to drug discovery. We provide introductory insight into state-of-the-art mass spectrometry (MS)-based metabolomics and lipidomics techniques utilized in drug discovery and development, drawing from the collective expertise of our research teams. We comprehensively outline the application of metabolomics and lipidomics in advancing drug discovery and development, spanning fundamental research, target identification, mechanisms of action, and the exploration of biomarkers.
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Affiliation(s)
- Giuseppe Astarita
- Georgetown University, Washington, DC, USA; Arkuda Therapeutics, Watertown, MA, USA.
| | - Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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Liu H, Tang Q, Yan X, Wang L, Wang J, Yang Q, Wei B, Li J, Qi J, Hu J, Hu B, Han C, Wang J, Li L. Mass spectrometry-based metabolic profiling for identification of biomarkers related to footpad dermatitis in ducks. Br Poult Sci 2023; 64:577-585. [PMID: 37254666 DOI: 10.1080/00071668.2023.2214884] [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: 04/04/2022] [Revised: 03/02/2023] [Accepted: 04/04/2023] [Indexed: 06/01/2023]
Abstract
1. A new assessment method for duck footpad dermatitis (FPD) evaluation was developed, combining visual and histological characters using the images and sections of 400 ducks' feet at 340 d of age. All ducks were graded as G0 (healthy), G1 (mild), G2 (moderate) and G3 (severe) according to the degree of FPD.2. To reveal the potential biomarkers in serum related to duck FPD, non-targeted metabolomics and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to explore differential metabolites in each group.3. There were 57, 91 and 210 annotated differential metabolites in groups G1, G2 and G3 compared with G0, which meant that the severity of FPD increased in line with the number of metabolites. Four metabolites, L-phenylalanine, L-arginine, L-leucine and L-lysine, were considered potential biomarkers related to FPD.4. KEGG enrichment analysis showed that the FPD was mainly involved in glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway and amino acid metabolism. These are related to production metabolism and can affect the physiological activities of ducks, which might explain the decrease in production performance.
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Affiliation(s)
- H Liu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Q Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - X Yan
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - L Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Q Yang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - B Wei
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Qi
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Hu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - B Hu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - C Han
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - J Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - L Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
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Killilea DW, Schultz K. Pre-analytical variables influence zinc measurement in blood samples. PLoS One 2023; 18:e0286073. [PMID: 37713369 PMCID: PMC10503700 DOI: 10.1371/journal.pone.0286073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 05/08/2023] [Indexed: 09/17/2023] Open
Abstract
Zinc deficiency continues to be a major concern for global public health. The zinc status of a target population is typically estimated by measuring circulating zinc levels, but the sampling procedures are not standardized and thus may result in analytical discrepancies. To examine this, we designed a study that controlled most of the technical parameters in order to focus on five pre-analytical variables reported to influence the measurement of zinc in blood samples, including (1) blood draw site (capillary or venous), (2) blood sample matrix (plasma or serum), (3) blood collection tube manufacturer (Becton, Dickinson and Company or Sarstedt AG & Co), (4) blood processing time (0, 4, or 24 hours), and (5) blood holding temperatures (4°C, 20°C, or 37°C). A diverse cohort of 60 healthy adults were recruited to provide sequential capillary and venous blood samples, which were carefully processed under a single chain of custody and measured for zinc content using inductively coupled plasma optical emission spectrometry. When comparing blood draw sites, the mean zinc content of capillary samples was 0.054 mg/L (8%; p<0.0001) higher than venous blood from the same donors. When comparing blood sample matrices, the mean zinc content of serum samples was 0.029 mg/L (5%; p<0.0001) higher than plasma samples from the same donors. When comparing blood collection tube manufacturer, the mean zinc content from venous blood samples did not differ between venders, but the mean zinc content from BD capillary plasma was 0.036 mg/L (6%; p<0.0001) higher than Sarstedt capillary plasma from the same donors. When comparing processing times, the mean zinc content of plasma and serum samples was 5-12% higher (p<0.0001) in samples processed 4-24 hour after collection. When comparing holding temperatures, the mean zinc content of plasma and serum samples was 0.5-7% higher (p = 0.0007 or p = 0.0061, respectively) in samples temporarily held at 20°C or 37°C after collection. Thus even with the same donors and blood draws, significant differences in zinc content were observed with different draw sites, tube types, and processing procedures, demonstrating that key pre-analytic variables can have an impact on zinc measurement, and subsequent classification of zinc status. Minimizing these pre-analytical variables is important for generating best practice guidelines for assessment of zinc status.
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Affiliation(s)
- David W. Killilea
- Office of Research, University of California San Francisco, San Francisco, California, United States of America
| | - Kathleen Schultz
- Office of Research, University of California San Francisco, San Francisco, California, United States of America
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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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12
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Badillo-Sanchez D, Serrano Ruber M, Davies-Barrett A, Jones DJ, Hansen M, Inskip S. Metabolomics in archaeological science: A review of their advances and present requirements. SCIENCE ADVANCES 2023; 9:eadh0485. [PMID: 37566664 PMCID: PMC10421062 DOI: 10.1126/sciadv.adh0485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/11/2023] [Indexed: 08/13/2023]
Abstract
Metabolomics, the study of metabolites (small molecules of <1500 daltons), has been posited as a potential tool to explore the past in a comparable manner to other omics, e.g., genomics or proteomics. Archaeologists have used metabolomic approaches for a decade or so, mainly applied to organic residues adhering to archaeological materials. Because of advances in sensitivity, resolution, and the increased availability of different analytical platforms, combined with the low mass/volume required for analysis, metabolomics is now becoming a more feasible choice in the archaeological sector. Additional approaches, as presented by our group, show the versatility of metabolomics as a source of knowledge about the human past when using human osteoarchaeological remains. There is tremendous potential for metabolomics within archaeology, but further efforts are required to position it as a routine technique.
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Affiliation(s)
| | - Maria Serrano Ruber
- School of Archaeology and Ancient History, University of Leicester, Leicester, UK
| | - Anna Davies-Barrett
- School of Archaeology and Ancient History, University of Leicester, Leicester, UK
| | - Donald J. L. Jones
- Leicester Cancer Research Centre, RKCSB, University of Leicester, Leicester, UK
- The Leicester van Geest MultiOmics Facility, University of Leicester, Leicester, UK
| | - Martin Hansen
- Environmental Metabolomics Lab, Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Sarah Inskip
- School of Archaeology and Ancient History, University of Leicester, Leicester, UK
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13
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Lista S, González-Domínguez R, López-Ortiz S, González-Domínguez Á, Menéndez H, Martín-Hernández J, Lucia A, Emanuele E, Centonze D, Imbimbo BP, Triaca V, Lionetto L, Simmaco M, Cuperlovic-Culf M, Mill J, Li L, Mapstone M, Santos-Lozano A, Nisticò R. Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives. Ageing Res Rev 2023; 89:101987. [PMID: 37343679 DOI: 10.1016/j.arr.2023.101987] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/12/2023] [Accepted: 06/15/2023] [Indexed: 06/23/2023]
Abstract
Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.
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Affiliation(s)
- Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain.
| | - Raúl González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz, Spain
| | - Susana López-Ortiz
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Álvaro González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz, Spain
| | - Héctor Menéndez
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Juan Martín-Hernández
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Alejandro Lucia
- Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid, Spain; Faculty of Sport Sciences, European University of Madrid, Villaviciosa de Odón, Madrid, Spain; CIBER of Frailty and Healthy Ageing (CIBERFES), Madrid, Spain
| | | | - Diego Centonze
- Department of Systems Medicine, Tor Vergata University, Rome, Italy; Unit of Neurology, IRCCS Neuromed, Pozzilli, IS, Italy
| | - Bruno P Imbimbo
- Department of Research and Development, Chiesi Farmaceutici, Parma, Italy
| | - Viviana Triaca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Rome, Italy
| | - Luana Lionetto
- Clinical Biochemistry, Mass Spectrometry Section, Sant'Andrea University Hospital, Rome, Italy; Department of Neuroscience, Mental Health and Sensory Organs, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Maurizio Simmaco
- Clinical Biochemistry, Mass Spectrometry Section, Sant'Andrea University Hospital, Rome, Italy; Department of Neuroscience, Mental Health and Sensory Organs, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Miroslava Cuperlovic-Culf
- Digital Technologies Research Center, National Research Council, Ottawa, Canada; Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Jericha Mill
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA; School of Pharmacy, University of Wisconsin-Madison, Madison, WI, USA
| | - Mark Mapstone
- Department of Neurology, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Alejandro Santos-Lozano
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain; Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid, Spain
| | - Robert Nisticò
- School of Pharmacy, University of Rome "Tor Vergata", Rome, Italy; Laboratory of Pharmacology of Synaptic Plasticity, EBRI Rita Levi-Montalcini Foundation, Rome, Italy
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14
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Wang W, Rong Z, Wang G, Hou Y, Yang F, Qiu M. Cancer metabolites: promising biomarkers for cancer liquid biopsy. Biomark Res 2023; 11:66. [PMID: 37391812 DOI: 10.1186/s40364-023-00507-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 05/27/2023] [Indexed: 07/02/2023] Open
Abstract
Cancer exerts a multitude of effects on metabolism, including the reprogramming of cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation of cancer cells and adaptation to the tumor microenvironment. There is a growing body of evidence suggesting that aberrant metabolites play pivotal roles in tumorigenesis and metastasis, and have the potential to serve as biomarkers for personalized cancer therapy. Importantly, high-throughput metabolomics detection techniques and machine learning approaches offer tremendous potential for clinical oncology by enabling the identification of cancer-specific metabolites. Emerging research indicates that circulating metabolites have great promise as noninvasive biomarkers for cancer detection. Therefore, this review summarizes reported abnormal cancer-related metabolites in the last decade and highlights the application of metabolomics in liquid biopsy, including detection specimens, technologies, methods, and challenges. The review provides insights into cancer metabolites as a promising tool for clinical applications.
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Affiliation(s)
- Wenxiang Wang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China
| | - Zhiwei Rong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, 100191, China
| | - Guangxi Wang
- Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yan Hou
- Department of Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Clinical Research Center, Peking University, Beijing, 100191, China
| | - Fan Yang
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China.
| | - Mantang Qiu
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
- Peking University People's Hospital Thoracic Oncology Institute, Beijing, 100044, China.
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15
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Liu Y, Wu Z, Armstrong DW, Wolosker H, Zheng Y. Detection and analysis of chiral molecules as disease biomarkers. Nat Rev Chem 2023; 7:355-373. [PMID: 37117811 PMCID: PMC10175202 DOI: 10.1038/s41570-023-00476-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2023] [Indexed: 04/30/2023]
Abstract
The chirality of small metabolic molecules is important in controlling physiological processes and indicating the health status of humans. Abnormal enantiomeric ratios of chiral molecules in biofluids and tissues occur in many diseases, including cancers and kidney and brain diseases. Thus, chiral small molecules are promising biomarkers for disease diagnosis, prognosis, adverse drug-effect monitoring, pharmacodynamic studies and personalized medicine. However, it remains difficult to achieve cost-effective and reliable analysis of small chiral molecules in clinical procedures, in part owing to their large variety and low concentration. In this Review, we describe current and emerging techniques that detect and quantify small-molecule enantiomers and their biological importance.
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Affiliation(s)
- Yaoran Liu
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Zilong Wu
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA.
- Texas Materials Institute, The University of Texas at Austin, Austin, TX, USA.
| | - Daniel W Armstrong
- Department of Chemistry & Biochemistry, University of Texas at Arlington, Arlington, TX, USA.
| | - Herman Wolosker
- Department of Biochemistry, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
| | - Yuebing Zheng
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA.
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA.
- Texas Materials Institute, The University of Texas at Austin, Austin, TX, USA.
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
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16
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Najafova T, Dagdeviren G, Kasikci M, Sahin D, Yucel A, Ozyuncu O, Gurler M. Segmental hair metabolomics analysis in pregnant women with pregnancy complications. Metabolomics 2023; 19:45. [PMID: 37084096 DOI: 10.1007/s11306-023-02009-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
INTRODUCTION Pregnancy complications, as preeclampsia (PE) and HELLP syndrome, occurring with similar pathophysiological mechanisms, have adverse effects on the health of both mother and fetus during pregnancy and thereafter, they are leading causes of maternal and fetal morbidity and mortality. The hair metabolome has been recognized as a valuable source of information in pregnancy research, as it provides stable metabolite information to be able to assist with studying biomarkers or metabolic mechanisms of pregnancy and its complications. OBJECTIVE The aim of this study was to investigate the hair metabolome profile of pregnant women with PE, HELLP syndrome and healthy women. METHOD Hair samples of new-borns' mothers (patients and controls) were investigated segmentally relevant to each trimester using a proper sample preparation and gas chromatography-mass spectrometry (GC-MS) to identify robust biomarkers that can be useful for screening, early detection, follow-up and treatment of PE and HELLP syndrome, the etiology of which are still unknown. RESULTS The results showed a significant change in the metabolome profiles of the patient and control groups regarding the trimesters. A striking decrease was observed in all 100 metabolites investigated in the patient group (p < 0.000). The metabolic pathways associated with significant metabolites have also been investigated, and the most affected pathways were observed to be the urea cycle, glycine, serine, aspartate, methionine and purine metabolism, ammonia cycle, and phosphatidylethanolamine biosynthesis. CONCLUSION The found metabolites provide us with extensive data on the ability to establish biomarkers for predicting, early detection and monitoring of PE.
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Affiliation(s)
- Tahmina Najafova
- Department of Medical Biochemistry, Faculty of Medicine, Hacettepe University, Sıhhiye, 06100, Ankara, Turkey.
| | - Gulsah Dagdeviren
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Merve Kasikci
- Department of Biostatistics, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Dilek Sahin
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Aykan Yucel
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Ozgur Ozyuncu
- Department of Gynaecology and Obstetrics, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Mukaddes Gurler
- Department of Medical Biochemistry, Faculty of Medicine, Hacettepe University, Sıhhiye, 06100, Ankara, Turkey
- Department of Medical Biochemistry and Forensic Medicine, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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17
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Eggertsen PP, Hansen J, Andersen ML, Nielsen JF, Olsen RKJ, Palmfeldt J. Simultaneous measurement of kynurenine metabolites and explorative metabolomics using liquid chromatography-mass spectrometry: A novel accurate method applied to serum and plasma samples from a large healthy cohort. J Pharm Biomed Anal 2023; 227:115304. [PMID: 36827735 DOI: 10.1016/j.jpba.2023.115304] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/14/2023] [Accepted: 02/15/2023] [Indexed: 02/18/2023]
Abstract
Kynurenine metabolites are emerging as promising clinical biomarkers in several diseases, especially within psychiatry. Unfortunately, they are difficult to detect, particularly the challenging neurotoxic metabolite quinolinic acid (QUIN). The aim of this study was twofold: First, to develop a liquid chromatography-mass spectrometry method (LC-MS) for simultaneous targeted quantification of key kynurenine metabolites together with untargeted metabolomics, and second, to demonstrate the feasibility of the method by exploring serum/plasma and gender differences in 120 healthy young adults between 18 and 30 years of age. A range of analytical columns (C18 and biphenyl columns) and mobile phases (acidic and alkaline) were systematically evaluated. The optimized LC-MS method was based on a biphenyl column, a water-methanol gradient with 0.2% formic acid, and authentic isotope-labeled standards for each kynurenine metabolite. Precision and accuracy of targeted quantification of the key kynurenine metabolites tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), and QUIN were excellent, far exceeding the acceptance criteria specified by international guidelines. Median inter- and intra-day precision were < 6% in serum and plasma; the median accuracy was 2.4% in serum and 8% in plasma. Serum concentrations were ≤ 10% different from the corresponding concentrations in plasma for all kynurenine metabolites in healthy young adults. Men had higher levels (8-18%) of TRP, KYN, and KYNA than women (p ≤ 0.009), while no differences were observed for 3-HK and QUIN (p > 0.70). Incurred sample reanalysis of 10% of the samples yielded a median difference < 5% from the initial measurement, demonstrating the robustness of the method. Besides the targeted quantification of key kynurenine metabolites, our method was found to be suitable for simultaneous untargeted metabolomics analyses of hundreds of metabolites. A range of compound classes could be detected including amino acids, nucleic acids, dipeptides, antioxidants, and acylcarnitines, making explorative studies highly feasible. For example, we identified an additional kynurenine metabolite, 2-Quinolinecarboxylic acid, which was 47% higher in males than females (adjusted p-value = 0.001). In conclusion, in this study, we present a reliable and robust LC-MS method for simultaneous targeted and untargeted metabolomics ready for both research and clinical use. We show that both serum and plasma can be used for kynurenine studies, and the reported gender differences are in accordance with the literature. Future studies should consider using biphenyl-based LC-MS columns to successfully detect QUIN.
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Affiliation(s)
- Peter Preben Eggertsen
- Department of Clinical Medicine, Aarhus University, Denmark; Research Unit for Molecular Medicine, Aarhus University and Aarhus University Hospital, Denmark; Hammel Neurorehabilitation Centre and University Research Clinic, Denmark.
| | - Jakob Hansen
- Department of Forensic Medicine, Aarhus University, Denmark
| | - Malene Lundfold Andersen
- Department of Clinical Medicine, Aarhus University, Denmark; Research Unit for Molecular Medicine, Aarhus University and Aarhus University Hospital, Denmark
| | - Jørgen Feldbæk Nielsen
- Department of Clinical Medicine, Aarhus University, Denmark; Hammel Neurorehabilitation Centre and University Research Clinic, Denmark
| | - Rikke Katrine Jentoft Olsen
- Department of Clinical Medicine, Aarhus University, Denmark; Research Unit for Molecular Medicine, Aarhus University and Aarhus University Hospital, Denmark
| | - Johan Palmfeldt
- Department of Clinical Medicine, Aarhus University, Denmark; Research Unit for Molecular Medicine, Aarhus University and Aarhus University Hospital, Denmark.
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18
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Sens A, Rischke S, Hahnefeld L, Dorochow E, Schäfer SMG, Thomas D, Köhm M, Geisslinger G, Behrens F, Gurke R. Pre-analytical sample handling standardization for reliable measurement of metabolites and lipids in LC-MS-based clinical research. J Mass Spectrom Adv Clin Lab 2023; 28:35-46. [PMID: 36872954 PMCID: PMC9975683 DOI: 10.1016/j.jmsacl.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 02/09/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
The emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.
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Key Words
- 1-AG, 1-arachidonoyl glycerol
- 1-LG, 1-linoleoyl glycerol
- 2-AG, 2-arachidonoyl glycerol
- 2-LG, 2- linoleoyl glycerol
- ACN, acetonitrile
- AEA, arachidonoyl ethanolamide
- BHT, 2,6-di-tert-butyl-4-methylphenol
- CAR, carnitine
- EC, endocannabinoid
- FC, fold change
- FT, freezing temperature/storage in ice water
- HETE, hydroxyeicosatetraenoate
- HRMS, high-resolution mass spectrometry
- IRB, Institutional Review Board
- IS, internal standard
- K3EDTA plasma sampling
- K3EDTA, tripotassium ethylenediaminetetraacetic acid
- LC, liquid chromatography
- LEA, linoleoyl ethanolamide
- LLE, liquid–liquid extraction
- LLOQ, lowest limit of quantification
- LPA, lysophosphatidic acid
- LPC O, lysophosphatidylcholine-ether
- LPC, lysophosphatidylcholine
- LPE, lysophosphatidylethanolamine
- LPG, lysophosphatidylglycerol
- LPI, lysophosphatic inositol
- Lipidomics
- MS/MS, tandem mass spectrometry
- MTBE, methyl tertiary-butyl ether
- MeOH, methanol
- Metabolomics
- OEA, oleoyl ethanolamide
- PBS, phosphate-buffered saline
- PC, phohsphatidylcholine
- PE, phosphotidylethanolamine
- PEA, palmitoyl ethanolamide
- PI, phosphatidylinositol
- Pre-analytics
- QC, quality control
- REC, Research Ethics Committee
- RT, room temperature
- Ref, reference sample
- SEA, stearoyl ethanolamide
- SPE, solid-phase extraction
- STD, calibration standard
- Sampling protocol
- VEA, vaccenic acid ethanolamid
- WB, whole blood
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Affiliation(s)
- A Sens
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - S Rischke
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - L Hahnefeld
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - E Dorochow
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - S M G Schäfer
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - D Thomas
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - M Köhm
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany.,Rheumatology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - G Geisslinger
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - F Behrens
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany.,Rheumatology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - R Gurke
- Pharmazentrum Frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
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19
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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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20
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Teruya T, Sunagawa S, Mori A, Masuzaki H, Yanagida M. Markers for obese and non-obese Type 2 diabetes identified using whole blood metabolomics. Sci Rep 2023; 13:2460. [PMID: 36774491 PMCID: PMC9922320 DOI: 10.1038/s41598-023-29619-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 02/07/2023] [Indexed: 02/13/2023] Open
Abstract
Definitive differences in blood metabolite profiles between obese and non-obese Type 2 diabetes (T2D) have not been established. We performed an LC-MS-based non-targeted metabolomic analysis of whole blood samples collected from subjects classified into 4 types, based on the presence or absence of obesity and T2D. Of the 125 compounds identified, 20, comprising mainly nucleobases and glucose metabolites, showed significant increases or decreases in the T2D group. These included cytidine, UDP-glucuronate, UMP, 6-phosphogluconate, and pentose-phosphate. Among those 20 compounds, 11 enriched in red blood cells (RBCs) have rarely been studied in the context of diabetes, indicating that RBC metabolism is more extensively disrupted than previously known. Correlation analysis revealed that these T2D markers include 15 HbA1c-associated and 5 irrelevant compounds that may reflect diabetic conditions by a different mechanism than that of HbA1c. In the obese group, enhanced protein and fatty acid catabolism causes increases in 13 compounds, including methylated or acetylated amino acids and short-chain carnitines. Our study, which may be considered a pilot investigation, suggests that changes in blood metabolism due to obesity and diabetes are large, but essentially independent.
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Affiliation(s)
- Takayuki Teruya
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
- R&D Cluster Programs Section, Technology Development and Innovation Center, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
| | - Sumito Sunagawa
- Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Ayaka Mori
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
- Cell Division Dynamics Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
| | - Hiroaki Masuzaki
- Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Mitsuhiro Yanagida
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan.
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21
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Fritz J, Huang T, Depner CM, Zeleznik OA, Cespedes Feliciano EM, Li W, Stone KL, Manson JE, Clish C, Sofer T, Schernhammer E, Rexrode K, Redline S, Wright KP, Vetter C. Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women. Sleep 2023; 46:zsac226. [PMID: 36130143 PMCID: PMC9832513 DOI: 10.1093/sleep/zsac226] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/08/2022] [Indexed: 01/16/2023] Open
Abstract
Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.
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Affiliation(s)
- Josef Fritz
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
- Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Innsbruck, Austria
| | - Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Christopher M Depner
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA
| | - Oana A Zeleznik
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Wenjun Li
- Department of Public Health, School of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA
| | - Katie L Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Clary Clish
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA
| | - Eva Schernhammer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
| | - Kathryn Rexrode
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Kenneth P Wright
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Céline Vetter
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
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22
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Bizkarguenaga M, Gil-Redondo R, Bruzzone C, Bernardo-Seisdedos G, Laín A, González-Valle B, Embade N, Mato JM, Millet O. Prospective Metabolomic Studies in Precision Medicine: The AKRIBEA Project. Handb Exp Pharmacol 2023; 277:275-297. [PMID: 36253553 DOI: 10.1007/164_2022_610] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
For a long time, conventional medicine has analysed biomolecules to diagnose diseases. Yet, this approach has proven valid only for a limited number of metabolites and often through a bijective relationship with the disease (i.e. glucose relationship with diabetes), ultimately offering incomplete diagnostic value. Nowadays, precision medicine emerges as an option to improve the prevention and/or treatment of numerous pathologies, focusing on the molecular mechanisms, acting in a patient-specific dimension, and leveraging multiple contributing factors such as genetic, environmental, or lifestyle. Metabolomics grasps the required subcellular complexity while being sensitive to all these factors, which results in a most suitable technique for precision medicine. The aim of this chapter is to describe how NMR-based metabolomics can be integrated in the design of a precision medicine strategy, using the Precision Medicine Initiative of the Basque Country (the AKRIBEA project) as a case study. To that end, we will illustrate the procedures to be followed when conducting an NMR-based metabolomics study with a large cohort of individuals, emphasizing the critical points. The chapter will conclude with the discussion of some relevant biomedical applications.
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Affiliation(s)
- Maider Bizkarguenaga
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Rubén Gil-Redondo
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Chiara Bruzzone
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Ganeko Bernardo-Seisdedos
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Ana Laín
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Beatriz González-Valle
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - José M Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance, Bizkaia Science and Technology Park, Derio, Bizkaia, Spain.
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23
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Gegner HM, Naake T, Dugourd A, Müller T, Czernilofsky F, Kliewer G, Jäger E, Helm B, Kunze-Rohrbach N, Klingmüller U, Hopf C, Müller-Tidow C, Dietrich S, Saez-Rodriguez J, Huber W, Hell R, Poschet G, Krijgsveld J. Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis. Front Mol Biosci 2022; 9:961448. [PMID: 36605986 PMCID: PMC9808085 DOI: 10.3389/fmolb.2022.961448] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 11/28/2022] [Indexed: 01/07/2023] Open
Abstract
Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.
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Affiliation(s)
- Hagen M. Gegner
- Centre for Organismal Studies (COS), Metabolomics Core Technology Platform, University of Heidelberg, Heidelberg, Germany
| | - Thomas Naake
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Aurélien Dugourd
- Bioquant, Faculty of Medicine, Institute for Computational Biomedicine, University of Heidelberg and Heidelberg University Hospital, Heidelberg, Germany
| | - Torsten Müller
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany,Division Proteomics of Stem Cells and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Czernilofsky
- Department of Medicine V, Hematology, Oncology and Rheumatology, University of Heidelberg, Heidelberg, Germany
| | - Georg Kliewer
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany,Division Proteomics of Stem Cells and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Evelyn Jäger
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Barbara Helm
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Nina Kunze-Rohrbach
- Centre for Organismal Studies (COS), Metabolomics Core Technology Platform, University of Heidelberg, Heidelberg, Germany
| | - Ursula Klingmüller
- Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Carsten Müller-Tidow
- Department of Medicine V, Hematology, Oncology and Rheumatology, University of Heidelberg, Heidelberg, Germany
| | - Sascha Dietrich
- Department of Medicine V, Hematology, Oncology and Rheumatology, University of Heidelberg, Heidelberg, Germany
| | - Julio Saez-Rodriguez
- Bioquant, Faculty of Medicine, Institute for Computational Biomedicine, University of Heidelberg and Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Huber
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Rüdiger Hell
- Centre for Organismal Studies (COS), Metabolomics Core Technology Platform, University of Heidelberg, Heidelberg, Germany
| | - Gernot Poschet
- Centre for Organismal Studies (COS), Metabolomics Core Technology Platform, University of Heidelberg, Heidelberg, Germany,*Correspondence: Jeroen Krijgsveld, ; Gernot Poschet,
| | - Jeroen Krijgsveld
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany,Division Proteomics of Stem Cells and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany,*Correspondence: Jeroen Krijgsveld, ; Gernot Poschet,
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24
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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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25
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Timing of Blood Sample Processing Affects the Transcriptomic and Epigenomic Profiles in CD4+ T-cells of Atopic Subjects. Cells 2022; 11:cells11192958. [PMID: 36230920 PMCID: PMC9563434 DOI: 10.3390/cells11192958] [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: 07/04/2022] [Revised: 08/10/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022] Open
Abstract
Optimal pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4+ T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, CD4+ T-cells were isolated from the first blood sample within 2 h (immediate) or from the second blood sample after 24 h storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed CD4+ T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed CD4+ T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood CD4+ T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operation procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.
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26
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Rappold BA. Review of the Use of Liquid Chromatography-Tandem Mass Spectrometry in Clinical Laboratories: Part II-Operations. Ann Lab Med 2022; 42:531-557. [PMID: 35470272 PMCID: PMC9057814 DOI: 10.3343/alm.2022.42.5.531] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/08/2022] [Accepted: 04/13/2022] [Indexed: 11/19/2022] Open
Abstract
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is increasingly utilized in clinical laboratories because it has advantages in terms of specificity and sensitivity over other analytical technologies. These advantages come with additional responsibilities and challenges given that many assays and platforms are not provided to laboratories as a single kit or device. The skills, staff, and assays used in LC-MS/MS are internally developed by the laboratory, with relatively few exceptions. Hence, a laboratory that deploys LC-MS/MS assays must be conscientious of the practices and procedures adopted to overcome the challenges associated with the technology. This review discusses the post-development landscape of LC-MS/MS assays, including validation, quality assurance, operations, and troubleshooting. The content knowledge of LC-MS/MS users is quite broad and deep and spans multiple scientific fields, including biology, clinical chemistry, chromatography, engineering, and MS. However, there are no formal academic programs or specific literature to train laboratory staff on the fundamentals of LC-MS/MS beyond the reports on method development. Therefore, depending on their experience level, some readers may be familiar with aspects of the laboratory practices described herein, while others may be not. This review endeavors to assemble aspects of LC-MS/MS operations in the clinical laboratory to provide a framework for the thoughtful development and execution of LC-MS/MS applications.
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Affiliation(s)
- Brian A Rappold
- Laboratory Corporation of America Holdings, Research Triangle Park, NC, USA
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27
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Andresen C, Boch T, Gegner HM, Mechtel N, Narr A, Birgin E, Rasbach E, Rahbari N, Trumpp A, Poschet G, Hübschmann D. Comparison of extraction methods for intracellular metabolomics of human tissues. Front Mol Biosci 2022; 9:932261. [PMID: 36090025 PMCID: PMC9461704 DOI: 10.3389/fmolb.2022.932261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/12/2022] [Indexed: 11/16/2022] Open
Abstract
Analyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful extraction. We present a comprehensive study comparing ten extraction protocols in four human sample types (liver tissue, bone marrow, HL60, and HEK cells) aiming to detect and quantify up to 630 metabolites of different chemical classes. We show that the extraction efficiency and repeatability are highly variable across protocols, tissues, and chemical classes of metabolites. We used different quality metrics including the limit of detection and variability between replicates as well as the sum of concentrations as a global estimate of analytical repeatability of the extraction. The coverage of extracted metabolites depends on the used solvents, which has implications for the design of measurements of different sample types and metabolic compounds of interest. The benchmark dataset can be explored in an easy-to-use, interactive, and flexible online resource (R/shiny app MetaboExtract: http://www.metaboextract.shiny.dkfz.de) for context-specific selection of the optimal extraction method. Furthermore, data processing and conversion functionality underlying the shiny app are accessible as an R package: https://cran.r-project.org/package=MetAlyzer.
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Affiliation(s)
- Carolin Andresen
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Tobias Boch
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, Germany
- Division of Personalized Medical Oncology, German Cancer Research Center, Heidelberg, Germany
- Department of Personalized Oncology, University Hospital Mannheim, University of Heidelberg, Mannheim, Germany
- DKFZ-Hector Cancer Institute at the University Medical Center Mannheim, Mannheim, Germany
| | - Hagen M. Gegner
- Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Nils Mechtel
- Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Andreas Narr
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Emrullah Birgin
- Department of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, Germany
| | - Erik Rasbach
- Department of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, Germany
| | - Nuh Rahbari
- Department of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Trumpp
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Gernot Poschet
- Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Daniel Hübschmann
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
- Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany
- *Correspondence: Daniel Hübschmann,
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Advanced Microsamples: Current Applications and Considerations for Mass Spectrometry-Based Metabolic Phenotyping Pipelines. SEPARATIONS 2022. [DOI: 10.3390/separations9070175] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Microsamples are collections usually less than 50 µL, although all devices that we have captured as part of this review do not fit within this definition (as some can perform collections of up to 600 µL); however, they are considered microsamples that can be self-administered. These microsamples have been introduced in pre-clinical, clinical, and research settings to overcome obstacles in sampling via traditional venepuncture. However, venepuncture remains the sampling gold standard for the metabolic phenotyping of blood. This presents several challenges in metabolic phenotyping workflows: accessibility for individuals in rural and remote areas (due to the need for trained personnel), the unamenable nature to frequent sampling protocols in longitudinal research (for its invasive nature), and sample collection difficulty in the young and elderly. Furthermore, venous sample stability may be compromised when the temperate conditions necessary for cold-chain transport are beyond control. Alternatively, research utilising microsamples extends phenotyping possibilities to inborn errors of metabolism, therapeutic drug monitoring, nutrition, as well as sport and anti-doping. Although the application of microsamples in metabolic phenotyping exists, it is still in its infancy, with whole blood being overwhelmingly the primary biofluid collected through the collection method of dried blood spots. Research into the metabolic phenotyping of microsamples is limited; however, with advances in commercially available microsampling devices, common barriers such as volumetric inaccuracies and the ‘haematocrit effect’ in dried blood spot microsampling can be overcome. In this review, we provide an overview of the common uses and workflows for microsampling in metabolic phenotyping research. We discuss the advancements in technologies, highlighting key considerations and remaining knowledge gaps for the employment of microsamples in metabolic phenotyping research. This review supports the translation of research from the ‘bench to the community’.
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Ring Trial on Quantitative Assessment of Bile Acids Reveals a Method- and Analyte-Specific Accuracy and Reproducibility. Metabolites 2022; 12:metabo12070583. [PMID: 35888707 PMCID: PMC9319092 DOI: 10.3390/metabo12070583] [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: 05/19/2022] [Revised: 06/10/2022] [Accepted: 06/16/2022] [Indexed: 12/27/2022] Open
Abstract
(1) Background: Bile acids are a key mediator of the molecular microbiome-host interaction, and various mass spectrometry-based assays have been developed in the recent decade to quantify a wide range of bile acids. We compare existing methodologies to harmonize them. (2) Methods: Methodology for absolute quantification of bile acids from six laboratories in Europe were compared for the quantification of the primary bile acids cholic acid (CA) and chenodeoxycholic acid (CDCA) and conjugated products glycocholic acid (GCA) and taurocholic acid (TCA). For the bacterially modified secondary bile acids, the quantification of deoxycholic acid (DCA) and lithocholic acid (LCA) was compared. For the murine bile acids, we used the primary muricholic acids (α-MCA and, β-MCA) and the intestinally produced secondary bile acid muricholic (ω-MCA). The standards were spiked into methanol:water (1:1) mix as well as in human and murine serum at either low concentration range (150–3000 nM) or high concentration range (1500–40,000 nM). (3) Results: The precision was better for higher concentrations. Measurements for the hydrophobic unconjugated bile acids LCA and ω-MCA were the most challenging. (4) Conclusions: The quality assessments were generally very similar, and the comprehensive analyses demonstrated that data from chosen locations can be used for comparisons between studies.
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30
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González O, Dubbelman AC, Hankemeier T. Postcolumn Infusion as a Quality Control Tool for LC-MS-Based Analysis. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:1077-1080. [PMID: 35483670 PMCID: PMC10443037 DOI: 10.1021/jasms.2c00022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Postcolumn infusion has been widely used to study the matrix effect of analytical methods based on liquid chromatography coupled to mass spectrometry (LC-MS). Nevertheless, this methodology is usually only applied during a method development or validation. With this application note, we aim to demonstrate that the continuous use of postcolumn infusion can be also a very useful tool to monitor the quality of LC-MS analyses and easily detect flaws in the analytical method performance. Here we propose a protocol that can be transferred to other LC-MS platforms, and we show some real situations in bioanalysis in which postcolumn infusion proved to be extremely helpful in, for example, the evaluation of a sample treatment or the detection of unexpected sources of the matrix effect.
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Affiliation(s)
| | - Anne-Charlotte Dubbelman
- Analytical BioSciences and
Metabolomics, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333
CC Leiden, The Netherlands
| | - Thomas Hankemeier
- Analytical BioSciences and
Metabolomics, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333
CC Leiden, The Netherlands
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31
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Huang T, Zeleznik OA, Roberts AL, Balasubramanian R, Clish CB, Eliassen AH, Rexrode KM, Tworoger SS, Hankinson SE, Koenen KC, Kubzansky LD. Plasma Metabolomic Signature of Early Abuse in Middle-Aged Women. Psychosom Med 2022; 84:536-546. [PMID: 35471987 PMCID: PMC9167800 DOI: 10.1097/psy.0000000000001088] [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] [Indexed: 10/18/2022]
Abstract
OBJECTIVE Metabolomic profiling may provide insights into biological mechanisms underlying the strong epidemiologic links observed between early abuse and cardiometabolic disorders in later life. METHODS We examined the associations between early abuse and midlife plasma metabolites in two nonoverlapping subsamples from the Nurses' Health Study II, comprising 803 (mean age = 40 years) and 211 women (mean age = 61 years). Liquid chromatography-tandem mass spectrometry assays were used to measure metabolomic profiles, with 283 metabolites consistently measured in both subsamples. Physical and sexual abuse before age 18 years was retrospectively assessed by validated questions integrating type/frequency of abuse. Analyses were conducted in each sample and pooled using meta-analysis, with multiple testing adjustment using the q value approach for controlling the positive false discovery rate. RESULTS After adjusting for age, race, menopausal status, body size at age 5 years, and childhood socioeconomic indicators, more severe early abuse was consistently associated with five metabolites at midlife (q value < 0.20 in both samples), including lower levels of serotonin and C38:3 phosphatidylethanolamine plasmalogen and higher levels of alanine, proline, and C40:6 phosphatidylethanolamine. Other metabolites potentially associated with early abuse (q value < 0.05 in the meta-analysis) included triglycerides, phosphatidylcholine plasmalogens, bile acids, tyrosine, glutamate, and cotinine. The association between early abuse and midlife metabolomic profiles was partly mediated by adulthood body mass index (32% mediated) and psychosocial distress (13%-26% mediated), but not by other life-style factors. CONCLUSIONS Early abuse was associated with distinct metabolomic profiles of multiple amino acids and lipids in middle-aged women. Body mass index and psychosocial factors in adulthood may be important intermediates for the observed association.
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Affiliation(s)
- Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Oana A. Zeleznik
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Andrea L. Roberts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
| | | | - A. Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Kathryn M. Rexrode
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Shelley S. Tworoger
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Susan E. Hankinson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA
| | - Karestan C. Koenen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Laura D. Kubzansky
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
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Rey-Stolle F, Dudzik D, Gonzalez-Riano C, Fernández-García M, Alonso-Herranz V, Rojo D, Barbas C, García A. Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial. Anal Chim Acta 2022; 1210:339043. [PMID: 35595356 DOI: 10.1016/j.aca.2021.339043] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/04/2021] [Accepted: 09/06/2021] [Indexed: 12/28/2022]
Abstract
GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.
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Affiliation(s)
- Fernanda Rey-Stolle
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - Danuta Dudzik
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain; Department of Biopharmaceutics and Pharmacodynamics, Faculty of Pharmacy, Medical University of Gdańsk, Poland
| | - Carolina Gonzalez-Riano
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - Miguel Fernández-García
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - Vanesa Alonso-Herranz
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - David Rojo
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - Coral Barbas
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain
| | - Antonia García
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad San Pablo CEU, CEU Universities. Campus Monteprincipe, Boadilla Del Monte, 28668, Madrid, Spain.
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Metabolomics in Bariatric and Metabolic Surgery Research and the Potential of Deep Learning in Bridging the Gap. Metabolites 2022; 12:metabo12050458. [PMID: 35629961 PMCID: PMC9143741 DOI: 10.3390/metabo12050458] [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: 04/23/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 02/01/2023] Open
Abstract
During the past several years, there has been a shift in terminology from bariatric surgery alone to bariatric and metabolic surgery (BMS). More than a change in name, this signifies a paradigm shift that incorporates the metabolic effects of operations performed for weight loss and the amelioration of related medical problems. Metabolomics is a relatively novel concept in the field of bariatrics, with some consistent changes in metabolite concentrations before and after weight loss. However, the abundance of metabolites is not easy to handle. This is where artificial intelligence, and more specifically deep learning, would aid in revealing hidden relationships and would help the clinician in the decision-making process of patient selection in an individualized way.
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Ding X, Yang F, Chen Y, Xu J, He J, Zhang R, Abliz Z. Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics. Anal Chem 2022; 94:7500-7509. [PMID: 35584098 DOI: 10.1021/acs.analchem.1c05502] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.
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Affiliation(s)
- Xian Ding
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, 100050 Beijing, China
| | - Fen Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Center of Drug Clinical Trial, Peking University Cancer Hospital and Institute, Beijing 100142, China
| | - Yanhua Chen
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics, Minzu University of China, State Ethnic Affairs Commission, 100081 Beijing, China.,Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, 100081 Beijing, China.,Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Jing Xu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, 100050 Beijing, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, 100050 Beijing, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, 100050 Beijing, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, 100050 Beijing, China.,Key Laboratory of Mass Spectrometry Imaging and Metabolomics, Minzu University of China, State Ethnic Affairs Commission, 100081 Beijing, China.,Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, 100081 Beijing, China.,Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
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Gegner HM, Mechtel N, Heidenreich E, Wirth A, Cortizo FG, Bennewitz K, Fleming T, Andresen C, Freichel M, Teleman AA, Kroll J, Hell R, Poschet G. Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms. Front Chem 2022; 10:869732. [PMID: 35548679 PMCID: PMC9083328 DOI: 10.3389/fchem.2022.869732] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 04/05/2022] [Indexed: 12/12/2022] Open
Abstract
Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer’s, Parkinson’s disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app “MetaboExtract”. Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.
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Affiliation(s)
- Hagen M. Gegner
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Nils Mechtel
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Elena Heidenreich
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Angela Wirth
- Institute of Pharmacology, Heidelberg University, Heidelberg, Germany
| | - Fabiola Garcia Cortizo
- Division of Signal Transduction in Cancer and Metabolism, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Katrin Bennewitz
- European Center for Angioscience (ECAS), Department of Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Thomas Fleming
- Department of Internal Medicine I and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany
| | - Carolin Andresen
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM GGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Marc Freichel
- Institute of Pharmacology, Heidelberg University, Heidelberg, Germany
| | - Aurelio A. Teleman
- Division of Signal Transduction in Cancer and Metabolism, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jens Kroll
- European Center for Angioscience (ECAS), Department of Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Rüdiger Hell
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Gernot Poschet
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
- *Correspondence: Gernot Poschet,
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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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Biagini D, Antoni S, Ghimenti S, Bonini A, Vivaldi F, Angelucci C, Riparbelli C, Cuttano A, Fuoco R, Di Francesco F, Lomonaco T. Methodological aspects of dried blood spot sampling for the determination of isoprostanoids and prostanoids. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107212] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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38
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Chen M, Hao Y, Chen S. A protocol for investigating lipidomic dysregulation and discovering lipid biomarkers from human serums. STAR Protoc 2022; 3:101125. [PMID: 35141563 PMCID: PMC8814823 DOI: 10.1016/j.xpro.2022.101125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Lipids play important roles in various human diseases. Disease-associated lipid dysregulation and biomarkers could provide molecular clues for diagnosis, pathogenesis, and therapy. This protocol provides a step-by-step workflow to investigate lipid dysregulation and discover biomarkers in human serum samples by liquid chromatography-mass spectrometry (LC-MS)-based lipidomics and machine learning analysis. The workflow includes project design, serum collection, sample preparation, data acquisition, data processing, and machine learning analysis. For complete details on the use and execution of this profile, please refer to Hao et al. (2021). LC-MS based lipidomics for large-scale profiling of human serum samples Identification and quantitation of serum lipids based on MS-DIAL An effective feature selection approach for discovery of biomarkers
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Affiliation(s)
- Moran Chen
- The Institute for Advanced Studies, Wuhan University, Wuhan, Hubei 430072, China
- Corresponding author
| | - Yanhong Hao
- The Institute for Advanced Studies, Wuhan University, Wuhan, Hubei 430072, China
| | - Suming Chen
- The Institute for Advanced Studies, Wuhan University, Wuhan, Hubei 430072, China
- Corresponding author
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Beuchel C, Dittrich J, Pott J, Henger S, Beutner F, Isermann B, Loeffler M, Thiery J, Ceglarek U, Scholz M. Whole Blood Metabolite Profiles Reflect Changes in Energy Metabolism in Heart Failure. Metabolites 2022; 12:metabo12030216. [PMID: 35323659 PMCID: PMC8949022 DOI: 10.3390/metabo12030216] [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: 12/23/2021] [Revised: 02/15/2022] [Accepted: 02/25/2022] [Indexed: 02/04/2023] Open
Abstract
A variety of atherosclerosis and cardiovascular disease (ASCVD) phenotypes are tightly linked to changes in the cardiac energy metabolism that can lead to a loss of metabolic flexibility and to unfavorable clinical outcomes. We conducted an association analysis of 31 ASCVD phenotypes and 97 whole blood amino acids, acylcarnitines and derived ratios in the LIFE-Adult (n = 9646) and LIFE-Heart (n = 5860) studies, respectively. In addition to hundreds of significant associations, a total of 62 associations of six phenotypes were found in both studies. Positive associations of various amino acids and a range of acylcarnitines with decreasing cardiovascular health indicate disruptions in mitochondrial, as well as peroxisomal fatty acid oxidation. We complemented our metabolite association analyses with whole blood and peripheral blood mononuclear cell (PBMC) gene-expression analyses of fatty acid oxidation and ketone-body metabolism related genes. This revealed several differential expressions for the heart failure biomarker N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in peripheral blood mononuclear cell (PBMC) gene expression. Finally, we constructed and compared three prediction models of significant stenosis in the LIFE-Heart study using (1) traditional risk factors only, (2) the metabolite panel only and (3) a combined model. Area under the receiver operating characteristic curve (AUC) comparison of these three models shows an improved prediction accuracy for the combined metabolite and classical risk factor model (AUC = 0.78, 95%-CI: 0.76–0.80). In conclusion, we improved our understanding of metabolic implications of ASCVD phenotypes by observing associations with metabolite concentrations and gene expression of the mitochondrial and peroxisomal fatty acid oxidation. Additionally, we demonstrated the predictive potential of the metabolite profile to improve classification of patients with significant stenosis.
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Affiliation(s)
- Carl Beuchel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany; (J.P.); (S.H.); (M.L.)
- Correspondence: (C.B.); (U.C.); (M.S.)
| | - Julia Dittrich
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.D.); (B.I.); (J.T.)
| | - Janne Pott
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany; (J.P.); (S.H.); (M.L.)
- LIFE—Leipzig Research Center for Civilization Diseases, Leipzig University, 04103 Leipzig, Germany
| | - Sylvia Henger
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany; (J.P.); (S.H.); (M.L.)
- LIFE—Leipzig Research Center for Civilization Diseases, Leipzig University, 04103 Leipzig, Germany
| | | | - Berend Isermann
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.D.); (B.I.); (J.T.)
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany; (J.P.); (S.H.); (M.L.)
- LIFE—Leipzig Research Center for Civilization Diseases, Leipzig University, 04103 Leipzig, Germany
| | - Joachim Thiery
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.D.); (B.I.); (J.T.)
- Faculty of Medicine, Christian-Albrecht University of Kiel, 24118 Kiel, Germany
| | - Uta Ceglarek
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, 04103 Leipzig, Germany; (J.D.); (B.I.); (J.T.)
- LIFE—Leipzig Research Center for Civilization Diseases, Leipzig University, 04103 Leipzig, Germany
- Correspondence: (C.B.); (U.C.); (M.S.)
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany; (J.P.); (S.H.); (M.L.)
- LIFE—Leipzig Research Center for Civilization Diseases, Leipzig University, 04103 Leipzig, Germany
- IFB AdiposityDiseases, University Hospital Leipzig, 04103 Leipzig, Germany
- Correspondence: (C.B.); (U.C.); (M.S.)
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Cui P, Li X, Huang C, Li Q, Lin D. Metabolomics and its Applications in Cancer Cachexia. Front Mol Biosci 2022; 9:789889. [PMID: 35198602 PMCID: PMC8860494 DOI: 10.3389/fmolb.2022.789889] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/17/2022] [Indexed: 12/12/2022] Open
Abstract
Cancer cachexia (CC) is a complicated metabolic derangement and muscle wasting syndrome, affecting 50–80% cancer patients. So far, molecular mechanisms underlying CC remain elusive. Metabolomics techniques have been used to study metabolic shifts including changes of metabolite concentrations and disturbed metabolic pathways in the progression of CC, and expand further fundamental understanding of muscle loss. In this article, we aim to review the research progress and applications of metabolomics on CC in the past decade, and provide a theoretical basis for the study of prediction, early diagnosis, and therapy of CC.
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Affiliation(s)
- Pengfei Cui
- College of Food and Pharmacy, Xuchang University, Xuchang, China
| | - Xiaoyi Li
- Xuchang Central Hospital, Xuchang, China
| | - Caihua Huang
- Department of Physical Education, Xiamen University of Technology, Xiamen, China
| | - Qinxi Li
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Donghai Lin
- Key Laboratory for Chemical Biology of Fujian Province, MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China
- *Correspondence: Donghai Lin,
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Devi S, Pasanna RM, Nadiger N, Ghosh S, Kurpad AV, Mukhopadhyay A. Variability of human fasted venous plasma metabolomic profiles with tourniquet induced hemostasis. Sci Rep 2021; 11:24458. [PMID: 34961768 PMCID: PMC8712516 DOI: 10.1038/s41598-021-03665-2] [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: 09/02/2021] [Accepted: 12/08/2021] [Indexed: 11/17/2022] Open
Abstract
Venous plasma metabolomics is a potent and highly sensitive tool for identifying and measuring metabolites of interest in human health and disease. Accurate and reproducible insights from such metabolomic studies require extreme care in removing preanalytical confounders; one of these is the duration of tourniquet application when drawing the venous blood sample. Using an untargeted plasma metabolomics approach, we evaluated the effect of varying durations of tourniquet application on the variability in plasma metabolite concentrations in five healthy female subjects. Tourniquet application introduced appreciable variation in the metabolite abundances: 73% of the identified metabolites had higher temporal variation compared to interindividual variation [Intra-Class Correlation (ICC) > 0.50]. As such, we recommend tourniquet application for minimal duration and to wait for 5 min with the needle in situ after removing the tourniquet, to reduce hemostasis-induced variability and false flags in interpretation.
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Affiliation(s)
- Sarita Devi
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Sarjapur Road, Bangalore, 560034, India
| | - Roshni M Pasanna
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Sarjapur Road, Bangalore, 560034, India
| | - Nikhil Nadiger
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Sarjapur Road, Bangalore, 560034, India
| | - Santu Ghosh
- Department of Biostatistics, St. John's Medical College and Hospital, St. John's Research Institute, St. John's National Academy of Health Sciences, Bangalore, India
| | - Anura V Kurpad
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Sarjapur Road, Bangalore, 560034, India
| | - Arpita Mukhopadhyay
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Sarjapur Road, Bangalore, 560034, India.
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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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Gómez-Cebrián N, Vázquez Ferreiro P, Carrera Hueso FJ, Poveda Andrés JL, Puchades-Carrasco L, Pineda-Lucena A. Pharmacometabolomics by NMR in Oncology: A Systematic Review. Pharmaceuticals (Basel) 2021; 14:ph14101015. [PMID: 34681239 PMCID: PMC8539252 DOI: 10.3390/ph14101015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 12/14/2022] Open
Abstract
Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.
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Affiliation(s)
- Nuria Gómez-Cebrián
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain;
| | | | | | | | - Leonor Puchades-Carrasco
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain;
- Correspondence: (L.P.-C.); (A.P.-L.); Tel.: +34-963246713 (L.P.-C.)
| | - Antonio Pineda-Lucena
- Molecular Therapeutics Program, Centro de Investigación Médica Aplicada, 31008 Navarra, Spain
- Correspondence: (L.P.-C.); (A.P.-L.); Tel.: +34-963246713 (L.P.-C.)
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Perspectives and challenges in extracellular vesicles untargeted metabolomics analysis. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116382] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Giner MP, Christen S, Bartova S, Makarov MV, Migaud ME, Canto C, Moco S. A Method to Monitor the NAD + Metabolome-From Mechanistic to Clinical Applications. Int J Mol Sci 2021; 22:10598. [PMID: 34638936 PMCID: PMC8508997 DOI: 10.3390/ijms221910598] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 01/07/2023] Open
Abstract
Nicotinamide adenine dinucleotide (NAD+) and its reduced form (NADH) are coenzymes employed in hundreds of metabolic reactions. NAD+ also serves as a substrate for enzymes such as sirtuins, poly(ADP-ribose) polymerases (PARPs) and ADP-ribosyl cyclases. Given the pivotal role of NAD(H) in health and disease, studying NAD+ metabolism has become essential to monitor genetic- and/or drug-induced perturbations related to metabolic status and diseases (such as ageing, cancer or obesity), and its possible therapies. Here, we present a strategy based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), for the analysis of the NAD+ metabolome in biological samples. In this method, hydrophilic interaction chromatography (HILIC) was used to separate a total of 18 metabolites belonging to pathways leading to NAD+ biosynthesis, including precursors, intermediates and catabolites. As redox cofactors are known for their instability, a sample preparation procedure was developed to handle a variety of biological matrices: cell models, rodent tissues and biofluids, as well as human biofluids (urine, plasma, serum, whole blood). For clinical applications, quantitative LC-MS/MS for a subset of metabolites was demonstrated for the analysis of the human whole blood of nine volunteers. Using this developed workflow, our methodology allows studying NAD+ biology from mechanistic to clinical applications.
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Affiliation(s)
- Maria Pilar Giner
- Nestle Research, EPFL Innovation Park, H, 1015 Lausanne, Switzerland; (M.P.G.); (S.C.); (S.B.); (C.C.)
| | - Stefan Christen
- Nestle Research, EPFL Innovation Park, H, 1015 Lausanne, Switzerland; (M.P.G.); (S.C.); (S.B.); (C.C.)
| | - Simona Bartova
- Nestle Research, EPFL Innovation Park, H, 1015 Lausanne, Switzerland; (M.P.G.); (S.C.); (S.B.); (C.C.)
| | - Mikhail V. Makarov
- Mitchell Cancer Institute, University of South Alabama, 1660 Springhill Avenue, Mobile, AL 36604, USA; (M.V.M.); (M.E.M.)
- Olon Ricerca Bioscience, 7528 Auburn Road, Concord, OH 44077, USA
| | - Marie E. Migaud
- Mitchell Cancer Institute, University of South Alabama, 1660 Springhill Avenue, Mobile, AL 36604, USA; (M.V.M.); (M.E.M.)
| | - Carles Canto
- Nestle Research, EPFL Innovation Park, H, 1015 Lausanne, Switzerland; (M.P.G.); (S.C.); (S.B.); (C.C.)
| | - Sofia Moco
- Nestle Research, EPFL Innovation Park, H, 1015 Lausanne, Switzerland; (M.P.G.); (S.C.); (S.B.); (C.C.)
- Division of Molecular and Computational Toxicology, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute for Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
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Molsberry S, Bjornevik K, Hughes KC, Zhang ZJ, Jeanfavre S, Clish C, Healy B, Schwarzschild M, Ascherio A. Plasma Metabolomic Markers of Insulin Resistance and Diabetes and Rate of Incident Parkinson's Disease. JOURNAL OF PARKINSONS DISEASE 2021; 10:1011-1021. [PMID: 32250318 DOI: 10.3233/jpd-191896] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Although there is evidence of shared dysregulated pathways between diabetes and Parkinson's disease, epidemiologic research on an association between the two diseases has produced inconsistent results. OBJECTIVE We aimed to assess whether known metabolomic markers of insulin resistance and diabetes are also associated with Parkinson's disease development. METHODS We conducted a nested case-control study among Nurses' Health Study and Health Professionals Follow-up Study participants who had provided blood samples up to twenty years prior to Parkinson's diagnosis. Cases were matched to risk-set sampled controls by age, sex, fasting status, and time of blood collection. Participants provided covariate information via regularly collected cohort questionnaires. We used conditional logistic regression models to assess whether plasma levels of branched chain amino acids, acylcarnitines, glutamate, or glutamine were associated with incident development of Parkinson's disease. RESULTS A total of 349 case-control pairs were included in this analysis. In the primary analyses, none of the metabolites of interest were associated with Parkinson's disease development. In investigations of the association between each metabolite and Parkinson's disease at different time intervals prior to diagnosis, some metabolites showed marginally significant association but, after correction for multiple testing, only C18 : 2 acylcarnitine was significantly associated with Parkinson's disease among subjects for whom blood was collected less than 60 months prior to case diagnosis. CONCLUSIONS Plasma levels of diabetes-related metabolites did not contribute to predict risk of Parkinson's disease. Further investigation of the relationship between pre-diagnostic levels of diabetes-related metabolites and Parkinson's disease in other populations is needed to confirm these findings.
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Affiliation(s)
- Samantha Molsberry
- Population Health Sciences Program, Harvard University, Cambridge, MA, USA
| | - Kjetil Bjornevik
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine C Hughes
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhongli Joel Zhang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sarah Jeanfavre
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Clary Clish
- Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Brian Healy
- Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Alberto Ascherio
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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Dama E, Colangelo T, Fina E, Cremonesi M, Kallikourdis M, Veronesi G, Bianchi F. Biomarkers and Lung Cancer Early Detection: State of the Art. Cancers (Basel) 2021; 13:cancers13153919. [PMID: 34359818 PMCID: PMC8345487 DOI: 10.3390/cancers13153919] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/23/2021] [Accepted: 07/29/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Lung cancer is the leading cause of cancer death worldwide. Detecting lung malignancies promptly is essential for any anticancer treatment to reduce mortality and morbidity, especially in high-risk individuals. The use of liquid biopsy to detect circulating biomarkers such as RNA, microRNA, DNA, proteins, autoantibodies in the blood, as well as circulating tumor cells (CTCs), can substantially change the way we manage lung cancer patients by improving disease stratification using intrinsic molecular characteristics, identification of therapeutic targets and monitoring molecular residual disease. Here, we made an update on recent developments in liquid biopsy-based biomarkers for lung cancer early diagnosis, and we propose guidelines for an accurate study design, execution, and data interpretation for biomarker development. Abstract Lung cancer burden is increasing, with 2 million deaths/year worldwide. Current limitations in early detection impede lung cancer diagnosis when the disease is still localized and thus more curable by surgery or multimodality treatment. Liquid biopsy is emerging as an important tool for lung cancer early detection and for monitoring therapy response. Here, we reviewed recent advances in liquid biopsy for early diagnosis of lung cancer. We summarized DNA- or RNA-based biomarkers, proteins, autoantibodies circulating in the blood, as well as circulating tumor cells (CTCs), and compared the most promising studies in terms of biomarkers prediction performance. While we observed an overall good performance for the proposed biomarkers, we noticed some critical aspects which may complicate the successful translation of these biomarkers into the clinical setting. We, therefore, proposed a roadmap for successful development of lung cancer biomarkers during the discovery, prioritization, and clinical validation phase. The integration of innovative minimally invasive biomarkers in screening programs is highly demanded to augment lung cancer early detection.
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Affiliation(s)
- Elisa Dama
- Cancer Biomarkers Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy; (E.D.); (T.C.)
| | - Tommaso Colangelo
- Cancer Biomarkers Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy; (E.D.); (T.C.)
| | - Emanuela Fina
- Humanitas Research Center, IRCCS Humanitas Research Hospital, 20089 Rozzano, Milan, Italy;
| | - Marco Cremonesi
- Adaptive Immunity Laboratory, IRCCS Humanitas Research Hospital, 20089 Rozzano, Milan, Italy; (M.C.); (M.K.)
| | - Marinos Kallikourdis
- Adaptive Immunity Laboratory, IRCCS Humanitas Research Hospital, 20089 Rozzano, Milan, Italy; (M.C.); (M.K.)
- Department of Biomedical Sciences, Humanitas University, 20072 Pieve Emanuele, Italy
| | - Giulia Veronesi
- Division of Thoracic Surgery, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy;
| | - Fabrizio Bianchi
- Cancer Biomarkers Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo, Italy; (E.D.); (T.C.)
- Correspondence: ; Tel.: +39-08-8241-0954; Fax: +39-08-8220-4004
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Bjerkhaug AU, Granslo HN, Klingenberg C. Metabolic responses in neonatal sepsis-A systematic review of human metabolomic studies. Acta Paediatr 2021; 110:2316-2325. [PMID: 33851423 DOI: 10.1111/apa.15874] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/09/2021] [Indexed: 12/17/2022]
Abstract
AIM To systematically review human metabolomic studies investigating metabolic responses in septic neonates. METHODS A systematic literature search was performed in the databases MEDLINE, EMBASE and Cochrane library up to the 1st of January 2021. We included studies that assessed neonatal sepsis and the following outcomes; (1) change in the metabolism compared to healthy neonates and/or (2) metabolomics compared to traditional diagnostic tools of neonatal sepsis. The screened abstracts were independently considered for eligibility by two researchers. PROSPERO ID CRD42020164454. RESULTS The search identified in total 762 articles. Fifteen articles were assessed for eligibility. Four studies were included, with totally 78 neonates. The studies used different diagnostic criteria and had between 1 and 16 sepsis cases. All studies with bacterial sepsis found alterations in the glucose and lactate metabolism, reflecting possible redistribution of glucose consumption from mitochondrial oxidative phosphorylation to the lactate and pentose phosphate pathway. We also found signs of increased oxidative stress and fatty acid oxidation in sepsis cases. CONCLUSION We found signs of metabolomic signatures in neonatal sepsis. This may lead to better understanding of sepsis pathophysiology and detection of new candidate biomarkers. Results should be validated in large-scale multicentre studies.
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Affiliation(s)
- Aline U. Bjerkhaug
- Paediatric Research Group Faculty of Health Sciences UiT‐The Arctic University of Norway Tromsø Norway
| | - Hildegunn Norbakken Granslo
- Paediatric Research Group Faculty of Health Sciences UiT‐The Arctic University of Norway Tromsø Norway
- Department of Paediatrics and Adolescence Medicine University Hospital of North Norway Tromsø Norway
| | - Claus Klingenberg
- Paediatric Research Group Faculty of Health Sciences UiT‐The Arctic University of Norway Tromsø Norway
- Department of Paediatrics and Adolescence Medicine University Hospital of North Norway Tromsø Norway
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Gupta N, Ramakrishnan S, Wajid S. Emerging role of metabolomics in protein conformational disorders. Expert Rev Proteomics 2021; 18:395-410. [PMID: 34227444 DOI: 10.1080/14789450.2021.1948330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Introduction: Metabolomics focuses on interactions among different metabolites associated with various cellular functions in cells, tissues, and organs. In recent years, metabolomics has emerged as a powerful tool to identify perturbed metabolites, pathways influenced by the environment, for protein conformational diseases (PCDs) and also offers wide clinical application.Area Covered: This review provides a brief overview of recent advances in metabolomics as applied to identify metabolic variations in PCDs, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, prion disease, and cardiac amyloidosis. The 'PubMed' and 'Google Scholar' database search methods have been used to screen the published reports with key search terms: metabolomics, biomarkers, and protein conformational disorders.Expert opinion: Metabolomics is the large-scale study of metabolites and is deemed to overwhelm other omics. It plays a crucial role in finding variations in diseases due to protein conformational changes. However, many PCDs are yet to be identified. Metabolomics is still an emerging field; there is a need for new high-resolution analytical techniques and more studies need to be carried out to generate new information.
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Affiliation(s)
- Nimisha Gupta
- Department of Biotechnology, School of Chemical and Life Sciences, Jamia Hamdard, India
| | | | - Saima Wajid
- Department of Biotechnology, School of Chemical and Life Sciences, Jamia Hamdard, India
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