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Surendran A, Zhang H, Stamenkovic A, Ravandi A. Lipidomics and cardiovascular disease. Biochim Biophys Acta Mol Basis Dis 2025; 1871:167806. [PMID: 40122185 DOI: 10.1016/j.bbadis.2025.167806] [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: 01/13/2025] [Revised: 03/05/2025] [Accepted: 03/18/2025] [Indexed: 03/25/2025]
Abstract
Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, necessitating innovative approaches for early detection and personalized interventions. Lipidomics, leveraging advanced mass spectrometry techniques, has become instrumental in deciphering lipid-mediated mechanisms in CVDs. This review explores the application of lipidomics in identifying biomarkers for myocardial infarction, heart failure, stroke, and calcific aortic valve stenosis (CAVS). This review examines the technological advancements in shotgun lipidomics and LC/MS, which provide unparalleled insights into lipid composition and function. Key lipid biomarkers, including ceramides and lysophospholipids, have been linked to disease progression and therapeutic outcomes. Integrating lipidomics with genomic and proteomic data reveals the molecular underpinnings of CVDs, enhancing risk prediction and intervention strategies. This review positions lipidomics as a transformative tool in reshaping cardiovascular research and clinical practice.
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Affiliation(s)
- Arun Surendran
- Mass Spectrometry Core Facility, BRIC-Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala, India
| | - Hannah Zhang
- Cardiovascular Lipidomics Laboratory, St. Boniface Hospital, Albrechtsen Research Centre, Manitoba, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Manitoba, Canada; Precision Cardiovascular Medicine Group, St. Boniface Hospital Research, Manitoba, Canada
| | - Aleksandra Stamenkovic
- Cardiovascular Lipidomics Laboratory, St. Boniface Hospital, Albrechtsen Research Centre, Manitoba, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Manitoba, Canada; Precision Cardiovascular Medicine Group, St. Boniface Hospital Research, Manitoba, Canada
| | - Amir Ravandi
- Cardiovascular Lipidomics Laboratory, St. Boniface Hospital, Albrechtsen Research Centre, Manitoba, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Manitoba, Canada; Precision Cardiovascular Medicine Group, St. Boniface Hospital Research, Manitoba, Canada.
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Hirsch S, Porat Z, Dror I, Shilo Y, Berkowitz B. Characterizing the particulate content of urine in healthy humans using flow cytometry. PLoS One 2025; 20:e0324271. [PMID: 40403029 PMCID: PMC12097575 DOI: 10.1371/journal.pone.0324271] [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] [Received: 01/27/2025] [Accepted: 04/22/2025] [Indexed: 05/24/2025] Open
Abstract
There is a notable scarcity of information concerning particulate matter in urine. This study presents an initial investigation that uses flow cytometry to determine the particulate content in the urine of healthy individuals, focusing on particles within a diameter range of 0.33-70 µm. Imaging flow cytometry was combined with fluorescent tagging and a birefringence technique to characterize particulate matter in terms of concentration, type, and size. This method enabled the identification and quantification of total particles within a sample, as well as the characterization of specific subtypes, including lipid-associated particles, protein aggregates, lipid-protein complexes, particles containing calcium (such as calcium oxalate crystals), DNA-containing particles (including cells and bacteria), and crystalline structures. Benchmark ranges for particulate matter present in urine were categorized according to subgroups that account for the influence of age, gender, and time of sampling, yielding valuable insights into the total number of particles traversing the human urinary tract daily. Significantly, the analysis here suggests that approximately 320 × 106 particles may pass through the urinary tract each day. Examination of a range of potential correlations among samples indicated that the total particle concentrations remained statistically similar. More specifically, there were no significant concentration differences in urine samples relative to sampling time, gender, or age. These findings provide valuable insights into the variability of urinary particulate matter and lay the groundwork for future, larger-scale studies. Ultimately, this research contributes to understanding urinary tract function and may potentially lead to identifying novel markers for various health conditions.
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Affiliation(s)
- Sigal Hirsch
- Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Ziv Porat
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel
| | - Ishai Dror
- Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Yaniv Shilo
- Department of Urology, Kaplan Medical Center, Affiliated with the Hebrew University, Rehovot, Israel
| | - Brian Berkowitz
- Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
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3
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Gautam P, Yadav R, Vishwakarma RK, Pathak A, Singh C. Metabolic dysregulation in amyotrophic lateral sclerosis: insights from 1H NMR-based metabolomics in a tertiary care center in India. Metab Brain Dis 2025; 40:196. [PMID: 40310505 DOI: 10.1007/s11011-025-01616-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2024] [Accepted: 04/15/2025] [Indexed: 05/02/2025]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by motor neuron loss, leading to severe physical impairment and mortality. Despite available treatments like Riluzole and Edaravone, their limited efficacy highlights the need for improved understanding of ALS pathology. This study has explored metabolic alterations in North Indian ALS patients using 1H Nuclear Magnetic Resonance (NMR)-based metabolomics. A case-control study, involving 45 ALS patients and 30 healthy controls (HCs) was performed. Serum samples were analyzed using 600-MHz NMR spectrometer, revealing significant metabolic differences between ALS and HC groups. Multivariate analyses identified nine dysregulated metabolites-pyruvate, glutamine, histidine, isoleucine, leucine, imidazole, arginine, creatinine, and choline-with ROC analysis showing isoleucine as a promising biomarker (AUC 83%). Pathway enrichment analysis highlighted disruptions in key metabolic pathways, including the Glucose-Alanine Cycle, Urea Cycle, Ammonia Recycling, and the Warburg Effect, suggesting potential links to neuroinflammatory and mitochondrial dysfunction in ALS pathogenesis. This pilot study provides insight into ALS-specific metabolic alterations in Indian cohort and demonstrates the potential of these metabolites as diagnostic biomarkers. Our findings identify potential biomarkers that require validation in larger, multi-centric cohorts to support diagnosis, prognosis, and improved management of ALS.
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Affiliation(s)
- Priyanka Gautam
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India
| | - Rahul Yadav
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India
| | - Ranjeet Kumar Vishwakarma
- Department of Physiology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India
| | - Abhishek Pathak
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India.
| | - Chandan Singh
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India.
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4
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Sedighikamal H, Mashayekhan S. Critical assessment of quenching and extraction/sample preparation methods for microorganisms in metabolomics. Metabolomics 2025; 21:40. [PMID: 40082321 DOI: 10.1007/s11306-025-02228-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 01/29/2025] [Indexed: 03/16/2025]
Abstract
BACKGROUND Advancements in the research of intracellular metabolome have the potential to affect our understanding of biological processes. The applications and findings of intracellular metabolome analysis are useful in understanding cellular pathways, microbial interactions, and the detection of secreted metabolites and their functions. AIM OF REVIEW This work focuses on the analysis of intracellular metabolomes in microorganisms. The techniques used for analyzing the intracellular metabolomes including metabolomics approaches such as mass spectrometry, nuclear magnetic resonance, liquid chromatography, and gas chromatography are discussed. KEY SCIENTIFIC CONCEPTS OF REVIEW Challenges such as sample preparation, data analysis, metabolite extraction, sample storage and collection, and processing techniques were investigated, as they can highlight emerging technologies and advancements in metabolome analysis, future applications in drug discovery, personalized medicine, systems biology, and the limitations and challenges in studying the metabolome of microorganisms.
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Affiliation(s)
- Hossein Sedighikamal
- Department of Chemical and Petroleum Engineering, Sharif University of Technology, PO Box: 11365-11155, Tehran, Iran
| | - Shohreh Mashayekhan
- Department of Chemical and Petroleum Engineering, Sharif University of Technology, PO Box: 11365-11155, Tehran, Iran.
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5
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Liu C, Chen H, Ma Y, Zhang L, Chen L, Huang J, Zhao Z, Jiang H, Kong J. Clinical metabolomics in type 2 diabetes mellitus: from pathogenesis to biomarkers. Front Endocrinol (Lausanne) 2025; 16:1501305. [PMID: 40070584 PMCID: PMC11893406 DOI: 10.3389/fendo.2025.1501305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 01/21/2025] [Indexed: 03/14/2025] Open
Abstract
As a multidimensional metabolic disorder, the disability and death rate of type 2 diabetes mellitus (T2DM) has increased over time. T2DM covers a wide range of pathological manifestations ranging from hyperglycemia to multi-organ failure, and it has the potential to evolve into acute complications, including ketosis and chronic complications such as peripheral neuropathy, retinopathy, and nephropathy. T2DM mainly occurs in microvascular and large vessels and thus it is restricted for the clinician to diagnose and prescribe. However, the pathological mechanism and clinical diagnosis are inadequate. High-throughput metabolomics, characterized by non-invasive diagnostic techniques to identify potential biomarkers and distinct stages of T2DM, has been increasingly recognized as a vigorous tool with latent capacity for clinical translation. The pathological stratification of T2DM can significantly reduce disability and mortality rates. By tracing the metabolome and associated pathways from impaired fasting blood glucose or impaired glucose tolerance to severe organ failure, the chief contributions of large, independent population-based cohorts are summarized herein. These results facilitate understanding the pathophysiology and mechanism and supports research in accurate diagnosis, risk prediction, curative effect, distinct stages, and prognosis judgment of T2DM.
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Affiliation(s)
- Chuanxin Liu
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Hetao Chen
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- Department of Clinical Laboratory, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Yujin Ma
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Lei Zhang
- Department of Integrative Medicine, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Lulu Chen
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- Department of Clinical Laboratory, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Jiarui Huang
- Department of Critical Care Medicine, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Zizhe Zhao
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Hongwei Jiang
- Luoyang Key Laboratory of Clinical Multiomics and Translational Medicine, Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
| | - Jiao Kong
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
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Altmann H, Barovic M, Straßburger K, Tschäpel M, Jonas S, Poitz DM, Belavgeni A, Chavakis T, Mirtschink P, Funk AM. Validating Centralized Biobanking Workflows for NMR Metabolomics Using the PRIMA Panel. Anal Chem 2025; 97:2762-2769. [PMID: 39873382 PMCID: PMC11822734 DOI: 10.1021/acs.analchem.4c04938] [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: 09/12/2024] [Revised: 01/06/2025] [Accepted: 01/08/2025] [Indexed: 01/30/2025]
Abstract
The quality of biological samples used in metabolomics research is significantly influenced by preanalytical factors, such as the timing of centrifugation and freezing. This study aimed to evaluate how preanalytical factors, like delays in centrifugation and freezing, affect metabolomics research. Blood samples, collected in various tube types, were subjected to controlled pre- and postcentrifugation delays. Metabolite levels were quantified using NMR spectroscopy and fitted in linear mixed models used to predict changes in metabolite concentrations over time. The results showed that some metabolites, such as lactic acid, were significantly affected by even short delays, while others remained stable for longer. The study introduced the concept of a "stability time point", marking when a metabolite's concentration changes by 20%. These predictive models were validated in a separate cohort. To apply these findings, the authors developed the PRIMA Panel, an open-source R Shiny tool. This tool allows researchers to assess the impact of preanalytical variations on their samples, predict metabolite stability, and generate performance reports. The PRIMA Panel was tested using samples from the Dresden Integrated Liquid Biobank, proving its utility in a real-world biobank setting. The study emphasizes the importance of tracking preanalytical factors to improve the reliability of metabolomics analyses. The PRIMA Panel is available online and for local deployment, providing a practical solution for quality control in metabolomics research. The results of the study underscore the importance of tracking preanalytical factors in biobanking. A versatile tool for assessing their impact on metabolic data is introduced, improving the reliability of future analyses.
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Affiliation(s)
- Heidi Altmann
- Medical
Clinic & Polyclinic 1, University Hospital
and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany
- National
Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany
| | - Marko Barovic
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Katrin Straßburger
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Maximilian Tschäpel
- Medical
Clinic & Polyclinic 1, University Hospital
and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden 01307, Germany
| | - Sophie Jonas
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - David M. Poitz
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Alexia Belavgeni
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Triantafyllos Chavakis
- National
Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Peter Mirtschink
- National
Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
| | - Alexander M. Funk
- National
Center for Tumor Diseases (NCT/UCC) Partner Site Dresden, Dresden 01307, Germany
- Institute
for Clinical Chemistry and Laboratory Medicine, University Hospital and Faculty of Medicine Carl Gustav Carus of
TU Dresden, Dresden 01307, Germany
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7
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Ma X, He Y, Lv D, Chen X, Hong Z, Chai Y, Liu Y. Optimization of metabolomics pretreatment method of cholangiocarcinoma cells based on ultrahigh performance liquid chromatography coupled with mass spectrometry. J Pharm Biomed Anal 2025; 252:116508. [PMID: 39426275 DOI: 10.1016/j.jpba.2024.116508] [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: 04/19/2024] [Revised: 10/03/2024] [Accepted: 10/05/2024] [Indexed: 10/21/2024]
Abstract
Metabolomics intends to maximize the quantity of available metabolites for the global metabolome, which largely depends on sample pretreatment protocols. However, there are few studies that comprehensively examined the effects of extraction and reconstitution solvents on metabolome coverage of adherent mammalian cells. In this study, the human cholangiocarcinoma TFK-1 cells were chosen as a cell model, and eight extraction solvents and five reconstitution solvents were used for the pretreatment based on ultrahigh performance liquid chromatography coupled with mass spectrometry (UPLC/MS). The coverage, reproducibility, and stability of the data were norms to evaluate the effectiveness of different extraction solvents and reconstitution solvents. Based on the number of metabolites, the mean Euclidean distance (EDMEAN) in the principal component analysis (PCA) 3D score plots and the relative standard deviation (RSD) distribution of metabolites, it was demonstrated that MeOH-CHCl3-H2O (8:1:1, v/v/v) was the optimal extraction solvent and MeOH-H2O (1:1, v/v) or H2O was superior to other reconstitution solvents for RP column analysis, and the extraction solvent MeOH-ACN-H2O (2:2:1, v/v/v) and the reconstitution solvents ACN-H2O (4:1, v/v) or MeOH-H2O (1:1, v/v) provide the best performance for HILIC column analysis. The optimized pretreatment methods explored in this study expand the coverage of polar and non-polar metabolites and improve the reproducibility and stability of the metabolic data, which can be applied to UPLC/MS-based global metabolomics study on cholangiocarcinoma cells, potentially providing better extraction solvents and reconstitution solvents for other adherent mammalian cells with similar chemical and physical properties.
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Affiliation(s)
- Xiaoyu Ma
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; School of Pharmacy, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China; State Key Laboratory of Shaanxi for Natural Medicines Research and Engineering, Xi'an 710061, China
| | - Yongping He
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; Department of Pharmacy, Chongzuo People's Hospital, Chongzuo 532200, China
| | - Diya Lv
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China
| | - Xiaofei Chen
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; Shanghai Key Laboratory for Pharmaceutical Metabolite Research, Shanghai 200433, China
| | - Zhanying Hong
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; Shanghai Key Laboratory for Pharmaceutical Metabolite Research, Shanghai 200433, China.
| | - Yifeng Chai
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; Shanghai Key Laboratory for Pharmaceutical Metabolite Research, Shanghai 200433, China.
| | - Yue Liu
- Department of Pharmacy, Naval Medical University (Second Military Medical University), Shanghai 200433, China; Shanghai Key Laboratory for Pharmaceutical Metabolite Research, Shanghai 200433, China.
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Bogusiewicz J, Kupcewicz B, Wnuk K, Gaca-Tabaszewska M, Furtak J, Harat M, Buszko K, Bojko B. The impact of sampling time point on the lipidome composition. J Pharm Biomed Anal 2024; 251:116429. [PMID: 39178482 DOI: 10.1016/j.jpba.2024.116429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 07/15/2024] [Accepted: 08/17/2024] [Indexed: 08/25/2024]
Abstract
Lipidomic profiling has been reported as an effective approach for characterizing and differentiating brain tumors. However, since lipids can undergo non-specific enzymatic and nonenzymatic reactions due to tissue disruption, it is critical to consider the preanalytical phase of the diagnostic process (e.g., optimizing the sampling time and sampling conditions). Thus, this study assesses the ways in which the time point of sampling impacts the lipidome composition of brain tumors. Two histologically distinct brain tumors-namely, meningiomas and gliomas-were sampled using solid-phase microextraction (SPME) fibers at two time points: on-site directly after removal, and after 12 months of storage at -30 °C. The samples were analyzed via HILIC chromatography coupled with HRMS, which enabled the detection of a wide range of features, including phospholipids and sphingolipids, as well as changes in the profiles of these compounds. The samples obtained from the stored tissues tended to have elevated levels of analytes with lower m/z values. In addition, the samples obtained from the fresh and stored tissues were easily distinguished based on their lipidome compositions, regardless of the histological tumor type. Notably, while storage did not affect the possibility of differentiating meningiomas and gliomas, the biological interpretation of the obtained results were prone to bias.
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Affiliation(s)
- Joanna Bogusiewicz
- Department of Pharmacodynamics and Molecular Pharmacology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-089, Poland
| | - Bogumiła Kupcewicz
- Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-089, Poland
| | - Kacper Wnuk
- Department of Biostatistics and Biomedical Systems Theory, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-067, Poland
| | - Magdalena Gaca-Tabaszewska
- Department of Pharmacodynamics and Molecular Pharmacology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-089, Poland
| | - Jacek Furtak
- Medical Faculty, University of Science and Technology in Bydgoszcz, Bydgoszcz 85-796, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, Bydgoszcz 85-681, Poland
| | - Marek Harat
- Medical Faculty, University of Science and Technology in Bydgoszcz, Bydgoszcz 85-796, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, Bydgoszcz 85-681, Poland
| | - Katarzyna Buszko
- Department of Biostatistics and Biomedical Systems Theory, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-067, Poland
| | - Barbara Bojko
- Department of Pharmacodynamics and Molecular Pharmacology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Bydgoszcz 85-089, Poland.
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Kremer S, Shakhnovich V, Riffel AK, Harvey L, Borges CR. Delta-S-Cys-Albumin as a Marker of Pediatric Biospecimen Integrity. Biopreserv Biobank 2024; 22:578-585. [PMID: 38651617 PMCID: PMC11656128 DOI: 10.1089/bio.2023.0121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024] Open
Abstract
Blood plasma storage is a crucial element of pediatric biobanking. Improperly stored or handled specimens (e.g., at > -30°C) can result in altered biomolecular compositions that no longer reflects in vivo reality. We report application of a previously developed assay in adults-the ΔS-Cys-Albumin assay, which facilitates estimation of plasma and serum exposure to thawed conditions-to a population of pediatric EDTA plasma samples from patients aged 3-18 years to determine the assay's applicability, estimate its reference range for pediatric samples, and assess the impact of pre-centrifugation delay at 0°C. In addition, the effect of plasma thawed-state exposure to a range of times at 23°C, 4°C, and -20°C on ΔS-Cys-Albumin was evaluated. Using 98 precollected and processed pediatric EDTA plasma specimens, no difference was found in ΔS-Cys-Albumin under conditions of pre-centrifugation delay for up to 10 hours at 0°C. This lack of change allowed us to estimate a pediatric reference range for ΔS-Cys-Albumin of 7.0%-22.5% (mean of 12.8%) with a modest Pearson correlation between ΔS-Cys-Albumin and age (p = 0.0037, R2 = 0.29). ΔS-Cys-Albumin stability in six specimens at 23°C, 4°C, and -20°C was also evaluated. Plateaus in the decay curves were reached by 1 day, 7 days, and 14-28 days at these respective temperatures. The estimated pediatric reference range observed in children was lower than that previously observed in 180 adults of 12.3%-30.6% (mean of 20.0%), and the slope of the age correlation in children was twice as steep as that from adults. ΔS-Cys-Albumin decay curves at 23°C, 4°C, and -20°C were similar to those previously observed in adults. The data reported here support the use of ΔS-Cys-Albumin in evaluating the integrity and overall exposure of pediatric EDTA plasma specimens to thawed conditions. In doing so, they add an important quality control tool to the biobanker's arsenal.
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Affiliation(s)
- Schuyler Kremer
- School of Molecular Sciences, Arizona State University, Tempe, Arizona, USA
- The Biodesign Institute at Arizona State University, Tempe, Arizona, USA
| | - Valentina Shakhnovich
- Children’s Mercy Hospital, Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
- Ironwood Pharmaceuticals, Boston, Massachusetts, USA
| | | | - Lisa Harvey
- Children’s Mercy Hospital, Kansas City, Missouri, USA
| | - Chad R. Borges
- School of Molecular Sciences, Arizona State University, Tempe, Arizona, USA
- The Biodesign Institute at Arizona State University, Tempe, Arizona, USA
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10
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Kvasnička A, Kotaška K, Friedecký D, Ježdíková K, Brumarová R, Hnát T, Kala P. Long-chain polyunsaturated fatty acid-containing phosphatidylcholines predict survival rate in patients after heart failure. Heliyon 2024; 10:e39979. [PMID: 39553601 PMCID: PMC11567051 DOI: 10.1016/j.heliyon.2024.e39979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/19/2024] [Accepted: 10/29/2024] [Indexed: 11/19/2024] Open
Abstract
Background Heart failure (HF) is becoming an increasingly prevalent issue, particularly among the elderly population. Lipids are closely associated with cardiovascular disease (CVD) pathology. Lipidomics as a comprehensive profiling tool is showing to be promising in the prediction of events and mortality due to CVD as well as identifying novel biomarkers. Materials and methods In this study, eicosanoids and lipid profiles were measured in order to predict survival in patients with de novo or acute decompensated HF. Our study included 50 patients (16 females, mean age 73 years and 34 males, mean age 71 years) with de novo or acute decompensated chronic HF with a median follow-up of 7 months. Lipids were semiquantified using targeted lipidomic liquid chromatography-mass spectrometry (LC-MS/MS) analysis. Eicosanoid concentrations were determined using a commercially available sandwich ELISA assay. Results From 736 lipids and 3 eicosanoids, 39 significant lipids were selected (by using the Mann-Whitney U test after Benjamini-Hochberg correction) with the highest number of representatives belonging to the polyunsaturated (PUFA) phosphatidylcholines (PC). PC 42:10 (p = 1.44 × 10-4) was found to be the most statistically significantly elevated in the surviving group with receiver operating characteristics of AUC = 0.84 (p = 3.24 × 10-7). A multivariate supervised discriminant analysis based on the aforementioned lipid panel enabled the classification of the groups of surviving and non-surviving patients with 90 % accuracy. Conclusions In the present study we describe a trend in PUFA esterified in PC that were systematically increased in surviving patients with HF. This trend in low-abundant and rarely identified PUFA PC (mainly very long chain PUFA containing PC such as PC 42:10 or PC 40:9 containing FA 22:6, FA 20:5 and FA 20:4) suggests candidate biomarkers.
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Affiliation(s)
- Aleš Kvasnička
- Laboratory for Inherited Metabolic Disorders, Department of Clinical Biochemistry, University Hospital, Olomouc, Czech Republic
- Faculty of Medicine and Dentistry, Palacký University in Olomouc, Czech Republic
| | - Karel Kotaška
- Department of Medical Chemistry and Clinical Biochemistry, 2nd Medical Faculty, University Hospital Motol, Prague, Czech Republic
| | - David Friedecký
- Laboratory for Inherited Metabolic Disorders, Department of Clinical Biochemistry, University Hospital, Olomouc, Czech Republic
- Faculty of Medicine and Dentistry, Palacký University in Olomouc, Czech Republic
| | - Karolína Ježdíková
- Department of Medical Chemistry and Clinical Biochemistry, 2nd Medical Faculty, University Hospital Motol, Prague, Czech Republic
| | - Radana Brumarová
- Faculty of Medicine and Dentistry, Palacký University in Olomouc, Czech Republic
| | - Tomáš Hnát
- Department of Cardiology, University Hospital Motol and 2nd Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petr Kala
- Department of Cardiology, University Hospital Motol and 2nd Faculty of Medicine, Charles University, Prague, Czech Republic
- Center of Experimental Medicine, Institute of Clinical and Experimental Medicine, Prague, Czech Republic
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11
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Sens A, Thomas D, Schäfer SMG, König A, Pinter A, Tegeder I, Geisslinger G, Gurke R. Endocannabinoid analysis in GlucoEXACT plasma: Method validation and sample handling recommendations. Talanta 2024; 278:126518. [PMID: 39018759 DOI: 10.1016/j.talanta.2024.126518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/02/2024] [Accepted: 07/04/2024] [Indexed: 07/19/2024]
Abstract
Endocannabinoids (ECs), such as anandamide and 2-arachidonyl glycerol (2-AG), contribute to the pathology of inflammatory, malignant, cardiovascular, metabolic and mental diseases. The reliability of quantitative analyses in biological fluids of ECs and endocannabinoid-like (EC-like) substances depends on pre-analytical conditions such as temperature and "time-to-centrifugation". Standardization of these parameters is critical for valid quantification and implementation in clinical research. In this study, we compared concentrations obtained with GlucoEXACT blood collection tubes versus K3EDTA tubes and employed the optimized procedure to assess ECs profiles in patients with inflammatory skin disease and healthy controls. A UHPLC-MS/MS method was validated for human plasma from GlucoEXACT blood collection tubes according to EMA and FDA guidelines, and pre-analytical conditions were systematically modified to assess analyte stability and optimize the procedures. The results showed significantly lower concentrations of ECs and EC-like substance concentrations with GlucoEXACT tubes compared with K3EDTA tubes, and GlucoEXACT extended the time window of stable concentrations. The strongest method-disagreement occurred for 1/2-AG suggesting that GlucoEXACT delayed ex vivo isomer rearrangement. Hence, GlucoExact tubes were superior in terms of stability and reliability. However, although absolute concentrations obtained with GlucoExact and K3EDTA differed, linear regression studies showed high agreement (except for 1/2-AG), and both methods showed similar EC profiles and similar disease-dependent pro-inflammatory patterns in dermatology patients. Hence, despite the obstacles in EC analyses, implementation of optimized pre-analytical blood collection and sample processing procedures provide reliable insight into peripheral ECs.
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Affiliation(s)
- A Sens
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - D Thomas
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - S M G Schäfer
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - A König
- Goethe University Frankfurt, University Hospital, Department of Dermatology, Venereology, and Allergology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - A Pinter
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Department of Dermatology, Venereology, and Allergology, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - I Tegeder
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - G Geisslinger
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - R Gurke
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590, Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany.
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12
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Rischke S, Schäfer SMG, König A, Ickelsheimer T, Köhm M, Hahnefeld L, Zaliani A, Scholich K, Pinter A, Geisslinger G, Behrens F, Gurke R. Metabolomic and lipidomic fingerprints in inflammatory skin diseases - Systemic illumination of atopic dermatitis, hidradenitis suppurativa and plaque psoriasis. Clin Immunol 2024; 265:110305. [PMID: 38972618 DOI: 10.1016/j.clim.2024.110305] [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: 11/14/2023] [Revised: 05/17/2024] [Accepted: 06/26/2024] [Indexed: 07/09/2024]
Abstract
Auto-inflammatory skin diseases place considerable symptomatic and emotional burden on the affected and put pressure on healthcare expenditures. Although most apparent symptoms manifest on the skin, the systemic inflammation merits a deeper analysis beyond the surface. We set out to identify systemic commonalities, as well as differences in the metabolome and lipidome when comparing between diseases and healthy controls. Lipidomic and metabolomic LC-MS profiling was applied, using plasma samples collected from patients suffering from atopic dermatitis, plaque-type psoriasis or hidradenitis suppurativa or healthy controls. Plasma profiles revealed a notable shift in the non-enzymatic anti-oxidant defense in all three inflammatory disorders, placing cysteine metabolism at the center of potential dysregulation. Lipid network enrichment additionally indicated the disease-specific provision of lipid mediators associated with key roles in inflammation signaling. These findings will help to disentangle the systemic components of autoimmune dermatological diseases, paving the way to individualized therapy and improved prognosis.
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Affiliation(s)
- S Rischke
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - S M G Schäfer
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - A König
- Goethe University Frankfurt, University Hospital, Department of Dermatology, Venereology, and Allergology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - T Ickelsheimer
- Goethe University Frankfurt, University Hospital, Department of Dermatology, Venereology, and Allergology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - M Köhm
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Division of Rheumatology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - L Hahnefeld
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - A Zaliani
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - K Scholich
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - A Pinter
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Department of Dermatology, Venereology, and Allergology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - G Geisslinger
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; 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), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Goethe University Frankfurt, University Hospital, Division of Rheumatology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - R Gurke
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany.
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13
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Salihovic S, Nyström N, Mathisen CBW, Kruse R, Olbjørn C, Andersen S, Noble AJ, Dorn-Rasmussen M, Bazov I, Perminow G, Opheim R, Detlie TE, Huppertz-Hauss G, Hedin CRH, Carlson M, Öhman L, Magnusson MK, Keita ÅV, Söderholm JD, D'Amato M, Orešič M, Wewer V, Satsangi J, Lindqvist CM, Burisch J, Uhlig HH, Repsilber D, Hyötyläinen T, Høivik ML, Halfvarson J. Identification and validation of a blood- based diagnostic lipidomic signature of pediatric inflammatory bowel disease. Nat Commun 2024; 15:4567. [PMID: 38830848 PMCID: PMC11148148 DOI: 10.1038/s41467-024-48763-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 04/30/2024] [Indexed: 06/05/2024] Open
Abstract
Improved biomarkers are needed for pediatric inflammatory bowel disease. Here we identify a diagnostic lipidomic signature for pediatric inflammatory bowel disease by analyzing blood samples from a discovery cohort of incident treatment-naïve pediatric patients and validating findings in an independent inception cohort. The lipidomic signature comprising of only lactosyl ceramide (d18:1/16:0) and phosphatidylcholine (18:0p/22:6) improves the diagnostic prediction compared with high-sensitivity C-reactive protein. Adding high-sensitivity C-reactive protein to the signature does not improve its performance. In patients providing a stool sample, the diagnostic performance of the lipidomic signature and fecal calprotectin, a marker of gastrointestinal inflammation, does not substantially differ. Upon investigation in a third pediatric cohort, the findings of increased lactosyl ceramide (d18:1/16:0) and decreased phosphatidylcholine (18:0p/22:6) absolute concentrations are confirmed. Translation of the lipidomic signature into a scalable diagnostic blood test for pediatric inflammatory bowel disease has the potential to support clinical decision making.
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Affiliation(s)
- Samira Salihovic
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Niklas Nyström
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Charlotte Bache-Wiig Mathisen
- Department of Gastroenterology, Oslo University Hospital, Oslo, Norway and Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Robert Kruse
- Department of Clinical Research Laboratory, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Christine Olbjørn
- Department of Pediatrics and Adolescent Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Svend Andersen
- Department of Pediatrics, Vestfold Hospital Trust, Tønsberg, Norway
| | - Alexandra J Noble
- Translational Gastroenterology Unit, Nuffield Department of Experimental Medicine, University of Oxford, Oxford, United Kingdom
- Biomedical Research Center, University of Oxford, Oxford, United Kingdom
| | - Maria Dorn-Rasmussen
- Department of Paediatric and Adolescence Medicine, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Copenhagen Center for Inflammatory Bowel Disease in Children, Adolescents and Adults, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Igor Bazov
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Gøri Perminow
- Department of Pediatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Randi Opheim
- Department of Gastroenterology, Oslo University Hospital, Oslo, Norway and Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Trond Espen Detlie
- Department of Gastroenterology, Akershus University Hospital, Lørenskog, Norway and Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Charlotte R H Hedin
- Karolinska Institutet, Department of Medicine Solna, Stockholm, Sweden
- Karolinska University Hospital, Gastroenterology unit, Department of Gastroenterology, Dermatovenereology and Rheumatology, Stockholm, Sweden
| | - Marie Carlson
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Lena Öhman
- Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Maria K Magnusson
- Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Åsa V Keita
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Johan D Söderholm
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Mauro D'Amato
- IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
- Gastrointestinal Genetics Lab, CIC bioGUNE - BRTA, Derio, Spain
- Department of Medicine & Surgery, LUM University, Casamassima, Italy
| | - Matej Orešič
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
| | - Vibeke Wewer
- Department of Paediatric and Adolescence Medicine, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Copenhagen Center for Inflammatory Bowel Disease in Children, Adolescents and Adults, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Jack Satsangi
- Translational Gastroenterology Unit, Nuffield Department of Experimental Medicine, University of Oxford, Oxford, United Kingdom
- Biomedical Research Center, University of Oxford, Oxford, United Kingdom
| | - Carl Mårten Lindqvist
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Johan Burisch
- Copenhagen Center for Inflammatory Bowel Disease in Children, Adolescents and Adults, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Gastrounit, medical division, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Holm H Uhlig
- Translational Gastroenterology Unit, Nuffield Department of Experimental Medicine, University of Oxford, Oxford, United Kingdom
- Biomedical Research Center, University of Oxford, Oxford, United Kingdom
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Dirk Repsilber
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | | | - Marte Lie Høivik
- Department of Gastroenterology, Oslo University Hospital, Oslo, Norway and Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Jonas Halfvarson
- Department of Gastroenterology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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14
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Rischke S, Gurke R, Bennett A, Behrens F, Geisslinger G, Hahnefeld L. ALISTER - Application for lipid stability evaluation and research. Clin Chim Acta 2024; 557:117858. [PMID: 38492658 DOI: 10.1016/j.cca.2024.117858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/30/2024] [Accepted: 03/03/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND AND AIMS In lipidomic and metabolomic studies, pre-analytical pitfalls enhance the risk of misusing resources such as time and money, as samples that are analyzed may not yield accurate or reliable data due to poor sample handling. Guidance and pre-analytic know-how are necessary for translation of omics technologies into routine clinical testing. The present work aims to enable decision making regarding sample stability in every phase of lipidomics- and metabolomics-centered studies. MATERIALS AND METHODS Data of multiple pre-analytic studies were aggregated into a database. Flexible approaches for evaluating these data were implemented in an RShiny-based web-application, tailored towards broad applicability in clinical and bioanalytic research. RESULTS Our "Application for lipid stability evaluation & research" - ALISTER facilitates decision making on blood sample stability during lipidomic and metabolomic studies, such as biomarker research, analysis of biobank samples and clinical testing. The interactive tool gives sampling recommendations when planning sample collection or aids in the assessment of sample quality of experiments retrospectively. CONCLUSION ALISTER is available for use under https://itmp.shinyapps.io/alister/. The application enables and simplifies data-driven decision making concerning pre-analytic blood sample handling and fits the needs of clinical investigations from multiple perspectives.
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Affiliation(s)
- Samuel Rischke
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Robert Gurke
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, 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
| | - Alexandre Bennett
- 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
| | - Frank Behrens
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, 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; Goethe University Frankfurt, University Hospital, Department of Rheumatology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Gerd Geisslinger
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, 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
| | - Lisa Hahnefeld
- Goethe University Frankfurt, Institute of Clinical Pharmacology, Faculty of Medicine, 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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15
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Xu D, Dai X, Zhang L, Cai Y, Chen K, Wu J, Dong L, Shen L, Yang J, Zhao J, Zhou Y, Mei Z, Wei W, Zhang Z, Xiong N. Mass spectrometry for biomarkers, disease mechanisms, and drug development in cerebrospinal fluid metabolomics. Trends Analyt Chem 2024; 173:117626. [DOI: 10.1016/j.trac.2024.117626] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
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16
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Saito K, Goda R, Arai K, Asahina K, Kawabata M, Uchiyama H, Andou T, Shimizu H, Takahara K, Kakehi M, Yamauchi S, Nitta SI, Suga T, Fujita H, Ishikawa R, Saito Y. Interlaboratory evaluation of LC-MS-based biomarker assays. Bioanalysis 2024; 16:389-402. [PMID: 38334082 DOI: 10.4155/bio-2023-0173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024] Open
Abstract
Validation of biomarker assays is crucial for effective drug development and clinical applications. Interlaboratory reproducibility is vital for reliable comparison and combination of data from different centers. This review summarizes interlaboratory studies of quantitative LC-MS-based biomarker assays using reference standards for calibration curves. The following points are discussed: trends in reports, reference and internal standards, evaluation of analytical validation parameters, study sample analysis and normalization of biomarker assay data. Full evaluation of these parameters in interlaboratory studies is limited, necessitating further research. Some reports suggest methods to address variations in biomarker assay data among laboratories, facilitating organized studies and data combination. Method validation across laboratories is crucial for reducing interlaboratory differences and reflecting target biomarker responses.
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Affiliation(s)
- Kosuke Saito
- National Institute of Health Sciences, Kanagawa, Japan
| | - Ryoya Goda
- Daiichi Sankyo Company Ltd, Tokyo, Japan
| | - Koji Arai
- LSI Medience Corporation, Tokyo, Japan
| | | | | | | | | | | | | | | | | | | | | | | | - Rika Ishikawa
- National Institute of Health Sciences, Kanagawa, Japan
| | - Yoshiro Saito
- National Institute of Health Sciences, Kanagawa, Japan
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17
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de Souza HMR, Pereira TTP, de Sá HC, Alves MA, Garrett R, Canuto GAB. Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens. Metabolites 2024; 14:36. [PMID: 38248839 PMCID: PMC10819689 DOI: 10.3390/metabo14010036] [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: 11/24/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/23/2024] Open
Abstract
This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.
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Affiliation(s)
- Hygor M. R. de Souza
- Instituto de Química, Universidade Federal do Rio de Janeiro, LabMeta—LADETEC, Rio de Janeiro 21941-598, Brazil;
| | - Tássia T. P. Pereira
- Departamento de Genética, Ecologia e Evolucao, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil;
- Departamento de Biodiversidade, Evolução e Meio Ambiente, Universidade Federal de Ouro Preto, Ouro Preto 35400-000, Brazil
| | - Hanna C. de Sá
- Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia, Salvador 40170-115, Brazil;
| | - Marina A. Alves
- Instituto de Pesquisa de Produtos Naturais Walter Mors, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-599, Brazil;
| | - Rafael Garrett
- Instituto de Química, Universidade Federal do Rio de Janeiro, LabMeta—LADETEC, Rio de Janeiro 21941-598, Brazil;
- Department of Laboratory Medicine, Boston Children’s Hospital—Harvard Medical School, Boston, MA 02115, USA
| | - Gisele A. B. Canuto
- Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia, Salvador 40170-115, Brazil;
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18
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Pausova Z, Sliz E. Large-Scale Population-Based Studies of Blood Metabolome and Brain Health. Curr Top Behav Neurosci 2024; 68:177-219. [PMID: 38509405 DOI: 10.1007/7854_2024_463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n > 50 metabolites) and brain health reported in large-scale studies (n > 500 individuals).
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Affiliation(s)
- Zdenka Pausova
- Centre hospitalier universitaire Sainte-Justine and Department of Pediatrics, University of Montreal, Montreal, QC, Canada
| | - Eeva Sliz
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland.
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19
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Sopic M, Vilne B, Gerdts E, Trindade F, Uchida S, Khatib S, Wettinger SB, Devaux Y, Magni P. Multiomics tools for improved atherosclerotic cardiovascular disease management. Trends Mol Med 2023; 29:983-995. [PMID: 37806854 DOI: 10.1016/j.molmed.2023.09.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/10/2023]
Abstract
Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.
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Affiliation(s)
- Miron Sopic
- Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg; Department of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, 11000, Serbia
| | - Baiba Vilne
- Bioinformatics Laboratory, Rīga Stradiņš University, Rīga, LV-1007, Latvia
| | - Eva Gerdts
- Center for Research on Cardiac Disease in Women, Department of Clinical Science, University of Bergen, Bergen, 5020, Norway
| | - Fábio Trindade
- Cardiovascular R&D Centre - UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, 4099-002, Portugal
| | - Shizuka Uchida
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, Copenhagen, SV, DK-2450, Denmark
| | - Soliman Khatib
- Natural Compounds and Analytical Chemistry Laboratory, MIGAL-Galilee Research Institute, Kiryat Shemona, 11016, Israel; Department of Biotechnology, Tel-Hai College, Upper Galilee 12210, Israel
| | - Stephanie Bezzina Wettinger
- Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, 2080, Malta
| | - Yvan Devaux
- Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
| | - Paolo Magni
- Department of Pharmacological and Biomolecular Sciences 'Rodolfo Paoletti', Università degli Studi di Milano, Via G. Balzaretti 9, 20133 Milano, Italy; IRCCS MultiMedica, Via Milanese 300, 20099 Sesto S. Giovanni, Milan, Italy.
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20
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Wang Q, Hoene M, Hu C, Fritsche L, Ahrends R, Liebisch G, Ekroos K, Fritsche A, Birkenfeld AL, Liu X, Zhao X, Li Q, Su B, Peter A, Xu G, Lehmann R. Ex vivo instability of lipids in whole blood: preanalytical recommendations for clinical lipidomics studies. J Lipid Res 2023; 64:100378. [PMID: 37087100 PMCID: PMC10208886 DOI: 10.1016/j.jlr.2023.100378] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 04/24/2023] Open
Abstract
Reliability, robustness, and interlaboratory comparability of quantitative measurements is critical for clinical lipidomics studies. Lipids' different ex vivo stability in blood bears the risk of misinterpretation of data. Clear recommendations for the process of blood sample collection are required. We studied by UHPLC-high resolution mass spectrometry, as part of the "Preanalytics interest group" of the International Lipidomics Society, the stability of 417 lipid species in EDTA whole blood after exposure to either 4°C, 21°C, or 30°C at six different time points (0.5 h-24 h) to cover common daily routine conditions in clinical settings. In total, >800 samples were analyzed. 325 and 288 robust lipid species resisted 24 h exposure of EDTA whole blood to 21°C or 30°C, respectively. Most significant instabilities were detected for FA, LPE, and LPC. Based on our data, we recommend cooling whole blood at once and permanent. Plasma should be separated within 4 h, unless the focus is solely on robust lipids. Lists are provided to check the ex vivo (in)stability of distinct lipids and potential biomarkers of interest in whole blood. To conclude, our results contribute to the international efforts towards reliable and comparable clinical lipidomics data paving the way to the proper diagnostic application of distinct lipid patterns or lipid profiles in the future.
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Affiliation(s)
- Qingqing Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China; University of Chinese Academy of Sciences, Beijing, China
| | - Miriam Hoene
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
| | - Chunxiu Hu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Louise Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Robert Ahrends
- Department of Analytical Chemistry, University of Vienna, Vienna, Austria
| | - Gerhard Liebisch
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Kim Ekroos
- Lipidomics Consulting Ltd., Espoo, Finland
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas L Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany; Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Qi Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China
| | - Benzhe Su
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
| | - Andreas Peter
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), Dalian, China.
| | - Rainer Lehmann
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tübingen, Germany.
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21
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Safari F, Kehelpannala C, Safarchi A, Batarseh AM, Vafaee F. Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis. Cancers (Basel) 2023; 15:2780. [PMID: 37345117 DOI: 10.3390/cancers15102780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/02/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023] Open
Abstract
Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.
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Affiliation(s)
- Fatemeh Safari
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
| | - Cheka Kehelpannala
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Azadeh Safarchi
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- Microbiomes for One Systems Health, Health and Biosecurity, CSIRO, Westmead, NSW 2145, Australia
| | - Amani M Batarseh
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- UNSW Data Science Hub (uDASH), University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- OmniOmics.ai Pty Ltd., Sydney, NSW 2035, Australia
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22
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Rischke S, Hahnefeld L, Burla B, Behrens F, Gurke R, Garrett TJ. Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects. J Mass Spectrom Adv Clin Lab 2023; 28:47-55. [PMID: 36872952 PMCID: PMC9982001 DOI: 10.1016/j.jmsacl.2023.02.003] [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: 11/09/2022] [Revised: 02/14/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.
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Key Words
- (U)HPLC (Ultra-), High pressure liquid chromatography
- Biomarker Discovery Study
- HILIC, Hydrophilic interaction liquid chromatography
- HRMS, High resolution mass spectrometry
- LC-MS, Liquid chromatography – mass spectrometry
- LC-MS-Based Clinical Research
- Lipidomics
- MRM, Multiple reaction monitoring
- Metabolomics
- PCA, Principal component analysis
- QA, Quality assurance
- QC, Quality control
- RF, Random Forest
- RP, Reversed phase
- SVA, Support vector machine
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Affiliation(s)
- 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
| | - B Burla
- Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - 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.,Division of Rheumatology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60596 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
| | - T J Garrett
- Department of Pathology, Immunology and Laboratory Medicine and Southeast Center for Integrated Metabolomics, University of Florida, Gainesville, FL 32611, USA
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23
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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: 28] [Impact Index Per Article: 14.0] [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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24
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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: 4] [Impact Index Per Article: 2.0] [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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25
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Kartsova LA, Bessonova EA, Deev VA, Kolobova EA. Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis. Crit Rev Anal Chem 2023; 54:2110-2133. [PMID: 36625278 DOI: 10.1080/10408347.2022.2156770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.
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Affiliation(s)
| | | | | | - Ekaterina Alekseevna Kolobova
- Institute of Chemistry, St. Petersburg State University, St. Petersburg, Russia
- The Federal State Institute of Public Health 'The Nikiforov Russian Center of Emergency and Radiation Medicine', The Ministry of Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters, St. Petersburg, Russia
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26
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Ding J, Feng YQ. Mass spectrometry-based metabolomics for clinical study: Recent progresses and applications. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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27
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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: 18] [Impact Index Per Article: 6.0] [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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Toward building mass spectrometry-based metabolomics and lipidomics atlases for biological and clinical research. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Li Z, Zhang Y, Hoene M, Fritsche L, Zheng S, Birkenfeld A, Fritsche A, Peter A, Liu X, Zhao X, Zhou L, Luo P, Weigert C, Lin X, Xu G, Lehmann R. Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes. Front Endocrinol (Lausanne) 2022; 13:935016. [PMID: 35909528 PMCID: PMC9333093 DOI: 10.3389/fendo.2022.935016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/13/2022] [Indexed: 12/03/2022] Open
Abstract
AIMS/HYPOTHESIS Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites. METHODS Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA1c, and fasting insulin. RESULTS Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA1c, insulin, or a combination of FPG and HbA1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA1c. In comparison, the AUCs of FPG, HbA1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide). CONCLUSIONS/INTERPRETATION Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.
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Affiliation(s)
- Zaifang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Yanhui Zhang
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
| | - Miriam Hoene
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
| | - Louise Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Sijia Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Andreas Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Internal Medicine 4, University Hospital Tuebingen, Tuebingen, Germany
| | - Andreas Peter
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Ping Luo
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
| | - Cora Weigert
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Xiaohui Lin
- School of Computer Science & Technology, Dalian University of Technology, Dalian, China
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
| | - Rainer Lehmann
- Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- *Correspondence: Guowang Xu, ; Rainer Lehmann,
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