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Lim WW, Leung JH, Xie C, Cheng AWT, Su L, Lum LN, Toh A, Kong SC, Takano AM, Hausenloy DJ, Chua YC. Circulating Interleukins as Biomarkers in Non-Small Cell Lung Cancer Patients: A Pilot Study Compared to Normal Individuals. Diseases 2024; 12:221. [PMID: 39329890 DOI: 10.3390/diseases12090221] [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: 08/28/2024] [Revised: 09/17/2024] [Accepted: 09/17/2024] [Indexed: 09/28/2024] Open
Abstract
Identifying biomarkers in non-small cell lung cancer (NSCLC) can improve diagnosis and patient stratification. We evaluated plasmas and sera for interleukins (IL)-11, IL-6, IL-8, IL-17A, and IL-33 as biomarkers in primary NSCLC patients undergoing surgical treatment against normal volunteers. Exhaled-breath condensates (EBCs), a potential source without invasive procedures, were explored in normal individuals. Due to separate recruitment criteria and intrinsic cohort differences, the NSCLC and control cohorts were not well matched for age (median age: 65 vs. 40 years; p < 0.0001) and smoking status (p = 0.0058). Interleukins were first assessed through conventional ELISA. IL-11 was elevated in NSCLC plasma compared to controls (49.71 ± 16.90 vs. 27.67 ± 14.06 pg/mL, respectively, p < 0.0001) but undetectable in sera and EBCs by conventional ELISA. Therefore, high-sensitivity PCR-based IL-11 ELISA was repeated, albeit with concentration discrepancies. IL11 gene and protein upregulation by RT-qPCR and immunohistochemistry, respectively, were validated in NSCLC tumors. The lack of detection sensitivity across IL-6, IL-8, IL-17A, and IL-33 suggests the need for further, precise assays. Surprisingly, biomarker concentrations can be dissimilar across paired plasmas and sera. Our results identified a need to optimize detection limits for biomarker detection and caution against over-reliance on just one form of blood sample for biomarker assessment.
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Affiliation(s)
- Wei-Wen Lim
- National Heart Research Institute of Singapore, National Heart Center Singapore, Singapore 169609, Singapore
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
| | - Jason H Leung
- Department of Cardiothoracic Surgery, National Heart Center Singapore, Singapore 169609, Singapore
| | - Chen Xie
- National Heart Research Institute of Singapore, National Heart Center Singapore, Singapore 169609, Singapore
| | - Angelina W T Cheng
- National Heart Research Institute of Singapore, National Heart Center Singapore, Singapore 169609, Singapore
| | - Liping Su
- National Heart Research Institute of Singapore, National Heart Center Singapore, Singapore 169609, Singapore
| | - Luh-Nah Lum
- Clinical and Translational Research Office, National Heart Center Singapore, Singapore 169609, Singapore
| | - Aishah Toh
- Clinical and Translational Research Office, National Heart Center Singapore, Singapore 169609, Singapore
| | - Siew-Ching Kong
- Clinical and Translational Research Office, National Heart Center Singapore, Singapore 169609, Singapore
| | - Angela M Takano
- Department of Anatomical Pathology, Singapore General Hospital, Singapore 169608, Singapore
| | - Derek J Hausenloy
- National Heart Research Institute of Singapore, National Heart Center Singapore, Singapore 169609, Singapore
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore 169857, Singapore
- Yong Loo Lin School of Medicine, National University Singapore, Singapore 117597, Singapore
- The Hatter Cardiovascular Institute, University College London, London WC1E 6HX, UK
| | - Yang C Chua
- Department of Cardiothoracic Surgery, National Heart Center Singapore, Singapore 169609, Singapore
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2
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Thachil A, Wang L, Mandal R, Wishart D, Blydt-Hansen T. An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples. Metabolites 2024; 14:474. [PMID: 39330481 DOI: 10.3390/metabo14090474] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 08/10/2024] [Accepted: 08/12/2024] [Indexed: 09/28/2024] Open
Abstract
Discrepant sample processing remains a significant challenge within blood metabolomics research, introducing non-biological variation into the measured metabolome and biasing downstream results. Inconsistency during the pre-analytical phase can influence experimental processes, producing metabolome measurements that are non-representative of in vivo composition. To minimize variation, there is a need to create and adhere to standardized pre-analytical protocols for blood samples intended for use in metabolomics analyses. This will allow for reliable and reproducible findings within blood metabolomics research. In this review article, we provide an overview of the existing literature pertaining to pre-analytical factors that influence blood metabolite measurements. Pre-analytical factors including blood tube selection, pre- and post-processing time and temperature conditions, centrifugation conditions, freeze-thaw cycles, and long-term storage conditions are specifically discussed, with recommendations provided for best practices at each stage.
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Affiliation(s)
- Amy Thachil
- Department of Pediatrics, BC Children's Hospital, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Li Wang
- Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- BC Children's Hospital Research Institute, Vancouver, BC V5Z 4H4, Canada
| | - Rupasri Mandal
- Faculty of Science-Biological Sciences, The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - David Wishart
- Department of Laboratory Medicine & Pathology, Faculty of Science-Biological Sciences, The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Tom Blydt-Hansen
- Division of Nephrology, Department of Pediatrics, BC Children's Hospital, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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3
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Vignoli A, Gori AM, Berteotti M, Cesari F, Giusti B, Bertelli A, Kura A, Sticchi E, Salvadori E, Barbato C, Formelli B, Pescini F, Marcucci R, Tenori L, Poggesi A. The serum metabolomic profiles of atrial fibrillation patients treated with direct oral anticoagulants or vitamin K antagonists. Life Sci 2024; 351:122796. [PMID: 38852797 DOI: 10.1016/j.lfs.2024.122796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/03/2024] [Accepted: 06/04/2024] [Indexed: 06/11/2024]
Abstract
AIMS Long-term oral anticoagulation is the primary therapy for preventing ischemic stroke in patients with atrial fibrillation (AF). Different types of oral anticoagulant drugs can have specific effects on the metabolism of patients. Here we characterize, for the first time, the serum metabolomic and lipoproteomic profiles of AF patients treated with anticoagulants: vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs). MATERIALS AND METHODS Serum samples of 167 AF patients (median age 78 years, 62 % males, 70 % on DOACs treatment) were analyzed via high resolution 1H nuclear magnetic resonance (NMR) spectroscopy. Data on 25 metabolites and 112 lipoprotein-related fractions were quantified and analyzed with multivariate and univariate statistical approaches. KEY FINDINGS Our data provide evidence that patients treated with VKAs and DOACs present significant differences in their profiles: lower levels of alanine and lactate (odds ratio: 1.72 and 1.84), free cholesterol VLDL-4 subfraction (OR: 1.75), triglycerides LDL-1 subfraction (OR: 1.80) and 4 IDL cholesterol fractions (ORs ∼ 1.80), as well as higher levels of HDL cholesterol (OR: 0.48), apolipoprotein A1 (OR: 0.42) and 7 HDL cholesterol fractions/subfractions (ORs: 0.40-0.51) are characteristic of serum profile of patients on DOACs' therapy. SIGNIFICANCE Our results support the usefulness of NMR-based metabolomics for the description of the effects of oral anticoagulants on AF patient circulating metabolites and lipoproteins. The higher serum levels of HDL cholesterol observed in patients on DOACs could contribute to explaining their reduced cardiovascular risk, suggesting the need of further studies in this direction to fully understand possible clinical implications.
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Affiliation(s)
- Alessia Vignoli
- Department of Chemistry "Ugo Schiff", University of Florence, 50019 Sesto Fiorentino, Italy; Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy
| | - Anna Maria Gori
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Martina Berteotti
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Francesca Cesari
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Betti Giusti
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Alessia Bertelli
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Ada Kura
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Elena Sticchi
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Emilia Salvadori
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy
| | - Carmen Barbato
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy
| | | | | | - Rossella Marcucci
- Atherothrombotic Center, Department of Experimental and Clinical Medicine, University of Florence, AOU Careggi, 50134 Florence, Italy
| | - Leonardo Tenori
- Department of Chemistry "Ugo Schiff", University of Florence, 50019 Sesto Fiorentino, Italy; Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy.
| | - Anna Poggesi
- NEUROFARBA Department, University of Florence, 50139 Florence, Italy; Stroke Unit, AOU Careggi, 50134, Florence, Italy.
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Hagn G, Meier-Menches SM, Plessl-Walder G, Mitra G, Mohr T, Preindl K, Schlatter A, Schmidl D, Gerner C, Garhöfer G, Bileck A. Plasma Instead of Serum Avoids Critical Confounding of Clinical Metabolomics Studies by Platelets. J Proteome Res 2024; 23:3064-3075. [PMID: 38520676 PMCID: PMC11301681 DOI: 10.1021/acs.jproteome.3c00761] [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: 11/13/2023] [Revised: 02/14/2024] [Accepted: 03/13/2024] [Indexed: 03/25/2024]
Abstract
Metabolomics is an emerging and powerful bioanalytical method supporting clinical investigations. Serum and plasma are commonly used without rational prioritization. Serum is collected after blood coagulation, a complex biochemical process involving active platelet metabolism. This may affect the metabolome and increase the variance, as platelet counts and function may vary substantially in individuals. A multiomics approach systematically investigating the suitability of serum and plasma for clinical studies demonstrated that metabolites correlated well (n = 461, R2 = 0.991), whereas lipid mediators (n = 83, R2 = 0.906) and proteins (n = 322, R2 = 0.860) differed substantially between specimen. Independently, analysis of platelet releasates identified most biomolecules significantly enriched in serum compared to plasma. A prospective, randomized, controlled parallel group metabolomics trial with acetylsalicylic acid administered for 7 days demonstrated that the apparent drug effects significantly differ depending on the analyzed specimen. Only serum analyses of healthy individuals suggested a significant downregulation of TXB2 and 12-HETE, which were specifically formed during coagulation in vitro. Plasma analyses reliably identified acetylsalicylic acid effects on metabolites and lipids occurring in vivo such as an increase in serotonin, 15-deoxy-PGJ2 and sphingosine-1-phosphate and a decrease in polyunsaturated fatty acids. The present data suggest that plasma should be preferred above serum for clinical metabolomics studies as the serum metabolome may be substantially confounded by platelets.
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Affiliation(s)
- Gerhard Hagn
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Vienna
Doctoral School in Chemistry (DoSChem), University of Vienna, Waehringer Str. 42, 1090 Vienna, Austria
| | - Samuel M. Meier-Menches
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Günter Plessl-Walder
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Gaurav Mitra
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Thomas Mohr
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
| | - Karin Preindl
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
- Department
of Laboratory Medicine, Medical University
of Vienna, Waehringer
Gürtel 18-20, 1090 Vienna, Austria
| | - Andreas Schlatter
- Department
of Clinical Pharmacology, Medical University
of Vienna, 1090 Vienna, Austria
| | - Doreen Schmidl
- Department
of Clinical Pharmacology, Medical University
of Vienna, 1090 Vienna, Austria
| | - Christopher Gerner
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
| | - Gerhard Garhöfer
- Department
of Clinical Pharmacology, Medical University
of Vienna, 1090 Vienna, Austria
| | - Andrea Bileck
- Department
of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Straße 38, 1090 Vienna, Austria
- Joint
Metabolome Facility, University and Medical
University of Vienna, WaehringerStraße 38, 1090 Vienna, Austria
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5
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Lievanos-Ruiz FJ, Fenton-Navarro B. Enzymatic biomarkers of oxidative stress in patients with depressive disorders. A systematic review. Clin Biochem 2024; 130:110788. [PMID: 38969053 DOI: 10.1016/j.clinbiochem.2024.110788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Accepted: 06/30/2024] [Indexed: 07/07/2024]
Abstract
Oxidative stress (OS) results from the imbalance between the production of reactive oxygen species and the body's antioxidant mechanisms and is associated with various diseases, including depression. Antioxidants protect cells by neutralizing free radicals and include enzymatic components such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione reductase (GR), and glutathione S-transferase (GST). The concentration of these biomarkers can quantify OS. This research aimed to gather available information published in the last ten years about the concentration of enzymatic OS biomarkers in samples from patients with depressive disorders. METHOD A systematic review was conducted following the PRISMA guidelines, including original scientific articles that evaluated enzymatic OS biomarkers in participants with depressive disorders, using the keywords and boolean operators "superoxide dismutase" OR "catalase" OR "glutathione" AND "depress*" in the databases PubMed, SAGE Journals, DOAJ, Scielo, Dialnet, and Redalyc. RESULTS The initial search showed 614 results, with only 28 articles meeting the selection criteria. It was observed that all evaluated oxidative stress enzymatic markers showed a significant increase or decrease in patients with depressive disorders, due to a wide variability in the depressive disorders studied, the type of biological sample analyzed, and the techniques used. CONCLUSION There is evidence of the relationship between enzymatic OS biomarkers and depressive disorders, but additional studies are needed to clarify the nature of this relationship, particularly considering the different types of depressive disorders.
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Affiliation(s)
- F J Lievanos-Ruiz
- Laboratorio de Glicobiología y Farmacognosia, División de estudios de Posgrado, Facultad de Ciencias Médicas y Biológicas "Dr. Ignacio Chávez", Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia, Mexico.
| | - B Fenton-Navarro
- Laboratorio de Glicobiología y Farmacognosia, División de estudios de Posgrado, Facultad de Ciencias Médicas y Biológicas "Dr. Ignacio Chávez", Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia, Mexico.
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6
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Castro NC, Bullock J, Haynesworth K, Loftus S, Metz J, North H, Kemp TJ, Pinto LA. Blood collection tube and anticoagulant influence on SARS-CoV-2 antibody and avidity levels. Heliyon 2024; 10:e34449. [PMID: 39114031 PMCID: PMC11305197 DOI: 10.1016/j.heliyon.2024.e34449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 07/09/2024] [Accepted: 07/09/2024] [Indexed: 08/10/2024] Open
Abstract
SARS-CoV-2 serology plays a crucial role in assessing COVID-19 vaccine immunogenicity and antibody responses to SARS-CoV-2 infection. Tube type and anticoagulant may influence serology results. Thus, understanding the influence of these variables in test results is key. We evaluated the influence of serum collection tube type and anticoagulant on anti-SARS-CoV-2 spike antibody levels detected by enzyme-linked immunosorbent assays (ELISAs) and Luminex multiplex assays (11-plex) in serum and plasma samples. Anti-spike IgG avidity was also evaluated in both sample types. No significant differences were found between serology assay results using different blood (serum) collection tube types. However, significantly lower antibody concentrations (p < 0.05) were observed in tubes with the anticoagulants sodium citrate and acid citrate dextrose (ACD) in the ELISA and Multiplex assays (n = 29), compared to expected concentrations. These differences mostly disappeared after adjusting for the dilution factor caused by the anticoagulant volume, indicating that anticoagulant does not significantly impact the assay results, while anticoagulant volume does. There was a significant difference (p < 0.05) in IgG avidity (M) of plasma samples (p < 0.05) compared to serum, but anticoagulant type had no effect. Overall, these findings indicate that the choice of collection tube may introduce subtle variations in assay results if the volumes of anticoagulants are not taken into consideration. Additionally, differences between serum and anticoagulant-treated plasma matrices were observed in avidity ELISAs, indicating that these samples are not interchangeable for these assays; a finding that requires further investigation.
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Affiliation(s)
- Nicholas C. Castro
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Jimmie Bullock
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Katarzyna Haynesworth
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Sarah Loftus
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Jordan Metz
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Hayley North
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Troy J. Kemp
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
| | - Ligia A. Pinto
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, 21702, USA
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7
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Chen Z, Fung E, Wong CK, Ling L, Lui G, Lai CKC, Ng RWY, Sze RKH, Ho WCS, Hui DSC, Chan PKS. Early Metabolomic and Immunologic Biomarkers as Prognostic Indicators for COVID-19. Metabolites 2024; 14:380. [PMID: 39057703 PMCID: PMC11278819 DOI: 10.3390/metabo14070380] [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: 06/18/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/28/2024] Open
Abstract
This prospective study in Hong Kong aimed at identifying prognostic metabolomic and immunologic biomarkers for Coronavirus Disease 2019 (COVID-19). We examined 327 patients, mean age 55 (19-89) years, in whom 33.6% were infected with Omicron and 66.4% were infected with earlier variants. The effect size of disease severity on metabolome outweighed others including age, gender, peak C-reactive protein (CRP), vitamin D and peak viral levels. Sixty-five metabolites demonstrated strong associations and the majority (54, 83.1%) were downregulated in severe disease (z score: -3.30 to -8.61). Ten cytokines/chemokines demonstrated strong associations (p < 0.001), and all were upregulated in severe disease. Multiple pairs of metabolomic/immunologic biomarkers showed significant correlations. Fourteen metabolites had the area under the receiver operating characteristic curve (AUC) > 0.8, suggesting a high predictive value. Three metabolites carried high sensitivity for severe disease: triglycerides in medium high-density lipoprotein (MHDL) (sensitivity: 0.94), free cholesterol-to-total lipids ratio in very small very-low-density lipoprotein (VLDL) (0.93), cholesteryl esters-to-total lipids ratio in chylomicrons and extremely large VLDL (0.92);whereas metabolites with the highest specificity were creatinine (specificity: 0.94), phospholipids in large VLDL (0.94) and triglycerides-to-total lipids ratio in large VLDL (0.93). Five cytokines/chemokines, namely, interleukin (IL)-6, IL-18, IL-10, macrophage inflammatory protein (MIP)-1b and tumour necrosis factor (TNF)-a, had AUC > 0.8. In conclusion, we demonstrated a tight interaction and prognostic potential of metabolomic and immunologic biomarkers enabling an outcome-based patient stratification.
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Affiliation(s)
- Zigui Chen
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
| | - Erik Fung
- Cardiovascular Science Center and Division of Cardiology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China;
- School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, White City, London SW7 2AZ, UK
| | - Chun-Kwok Wong
- Department of Chemical Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China;
| | - Lowell Ling
- Department of Anaesthesia and Intensive Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China;
| | - Grace Lui
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (G.L.); (D.S.C.H.)
| | - Christopher K. C. Lai
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
| | - Rita W. Y. Ng
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
| | - Ryan K. H. Sze
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
| | - Wendy C. S. Ho
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
| | - David S. C. Hui
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (G.L.); (D.S.C.H.)
| | - Paul K. S. Chan
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR 999077, China; (Z.C.); (C.K.C.L.); (R.W.Y.N.); (R.K.H.S.); (W.C.S.H.)
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8
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Daniels M, Margolis LM, Rood JC, Lieberman HR, Pasiakos SM, Karl JP. Comparative analysis of circulating metabolomic profiles identifies shared metabolic alterations across distinct multistressor military training exercises. Physiol Genomics 2024; 56:457-468. [PMID: 38738316 PMCID: PMC11368567 DOI: 10.1152/physiolgenomics.00008.2024] [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: 01/24/2024] [Revised: 03/26/2024] [Accepted: 05/03/2024] [Indexed: 05/14/2024] Open
Abstract
Military training provides insight into metabolic responses under unique physiological demands that can be comprehensively characterized by global metabolomic profiling to identify potential strategies for improving performance. This study identified shared changes in metabolomic profiles across three distinct military training exercises, varying in magnitude and type of stress. Blood samples collected before and after three real or simulated military training exercises were analyzed using the same untargeted metabolomic profiling platform. Exercises included a 2-wk survival training course (ST, n = 36), a 4-day cross-country ski march arctic training (AT, n = 24), and a 28-day controlled diet- and exercise-induced energy deficit (CED, n = 26). Log2-fold changes of greater than ±1 in 191, 121, and 64 metabolites were identified in the ST, AT, and CED datasets, respectively. Most metabolite changes were within the lipid (57-63%) and amino acid metabolism (18-19%) pathways and changes in 87 were shared across studies. The largest and most consistent increases in shared metabolites were found in the acylcarnitine, fatty acid, ketone, and glutathione metabolism pathways, whereas the largest decreases were in the diacylglycerol and urea cycle metabolism pathways. Multiple shared metabolites were consistently correlated with biomarkers of inflammation, tissue damage, and anabolic hormones across studies. These three studies of real and simulated military training revealed overlapping alterations in metabolomic profiles despite differences in environment and the stressors involved. Consistent changes in metabolites related to lipid metabolism, ketogenesis, and oxidative stress suggest a potential common metabolomic signature associated with inflammation, tissue damage, and suppression of anabolic signaling that may characterize the unique physiological demands of military training.NEW & NOTEWORTHY The extent to which metabolomic responses are shared across diverse military training environments is unknown. Global metabolomic profiling across three distinct military training exercises identified shared metabolic responses with the largest changes observed for metabolites related to fatty acids, acylcarnitines, ketone metabolism, and oxidative stress. These changes also correlated with alterations in markers of tissue damage, inflammation, and anabolic signaling and comprise a potential common metabolomic signature underlying the unique physiological demands of military training.
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Affiliation(s)
- Michael Daniels
- Military Nutrition Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, United States
| | - Lee M Margolis
- Military Nutrition Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States
| | - Jennifer C Rood
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States
| | - Harris R Lieberman
- Military Nutrition Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States
| | - Stefan M Pasiakos
- Military Nutrition Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States
- Office of Dietary Supplements, National Institutes of Health, Bethesda, Maryland, United States
| | - J Philip Karl
- Military Nutrition Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States
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9
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Mun S, Kim JG, Lee SJ, Kim D, Lee J, Kang HG. Serum protein profiling reveals mechanism of activated thrombus formation in patients with stroke and atrial fibrillation. Sci Rep 2024; 14:13976. [PMID: 38886511 PMCID: PMC11183109 DOI: 10.1038/s41598-024-64750-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/12/2024] [Indexed: 06/20/2024] Open
Abstract
Stroke is an acute cerebrovascular disease in which blood flow to the brain is suddenly disrupted, causing damage to nerve cells. It involves complex and diverse pathophysiological processes and the treatment strategies are also diverse. The treatment for patients with stroke and atrial fibrillation (AF) is aimed at suppressing thrombus formation and migration. However, information regarding the protein networking involved in different thrombus formation pathways in patients with AF and stroke is insufficient. We performed protein profiling of patients with ischemic stroke with and without AF to investigate the mechanisms of thrombus formation and its pathophysiological association while providing helpful information for treating and managing patients with AF. These two groups were compared to identify the protein networks related to thrombus formation in AF. We observed that patients with ischemic stroke and AF had activated inflammatory responses induced by C-reactive protein, lipopolysaccharide-binding protein, and alpha-1-acid glycoprotein 1. In contrast, thyroid hormones were increased due to a decrease in transthyretin and retinol-binding protein 4 levels. The mechanism underlying enhanced cardiac activity, vasodilation, and the resulting thrombosis pathway were confirmed in AF. These findings will play an essential role in improving the prevention and treatment of AF-related stroke.
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Affiliation(s)
- Sora Mun
- Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam, 13135, Republic of Korea
| | - Jae Guk Kim
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, 35233, Republic of Korea
| | - Soo Joo Lee
- Department of Neurology, Daejeon Eulji Medical Center, Eulji University School of Medicine, Daejeon, 35233, Republic of Korea
| | - Doojin Kim
- Department of Hospital Business, Siotmedi Co., Ltd, Suwon, 16630, Republic of Korea
| | - Jiyeong Lee
- Department of Biomedical Laboratory Science, College of Health Science, Eulji University, Uijeongbu, 11759, Republic of Korea.
| | - Hee-Gyoo Kang
- Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam, 13135, Republic of Korea.
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10
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Benito S, Unceta N, Maciejczyk M, Sánchez-Ortega A, Taranta-Janusz K, Szulimowska J, Zalewska A, Andrade F, Gómez-Caballero A, Dubiela P, Barrio RJ. Revealing novel biomarkers for diagnosing chronic kidney disease in pediatric patients. Sci Rep 2024; 14:11549. [PMID: 38773318 PMCID: PMC11109104 DOI: 10.1038/s41598-024-62518-w] [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: 01/24/2024] [Accepted: 05/17/2024] [Indexed: 05/23/2024] Open
Abstract
Pediatric chronic kidney disease (CKD) is a clinical condition characterized by progressive renal function deterioration. CKD diagnosis is based on glomerular filtration rate, but its reliability is limited, especially at the early stages. New potential biomarkers (citrulline (CIT), symmetric dimethylarginine (SDMA), S-adenosylmethionine (SAM), n-butyrylcarnitine (nC4), cis-4-decenoylcarnitine, sphingosine-1-phosphate and bilirubin) in addition to creatinine (CNN) have been proposed for early diagnosis. To verify the clinical value of these biomarkers we performed a comprehensive targeted metabolomics study on a representative cohort of CKD and healthy pediatric patients. Sixty-seven children with CKD and forty-five healthy children have been enrolled in the study. Targeted metabolomics based on liquid chromatography-triple quadrupole mass spectrometry has been used for serum and plasma samples analysis. Univariate data analysis showed statistically significant differences (p < 0.05) in the concentration of CNN, CIT, SDMA, and nC4 among healthy and CKD pediatric patients. The predictive ability of the proposed biomarkers was also confirmed through specificity and sensitivity expressed in Receiver Operating Characteristic curves (AUC = 0.909). In the group of early CKD pediatric patients, AUC of 0.831 was obtained, improving the diagnostic reliability of CNN alone. Moreover, the models built on combined CIT, nC4, SDMA, and CNN allowed to distinguish CKD patients from healthy control regardless of blood matrix type (serum or plasma). Our data demonstrate potential biomarkers in the diagnosis of early CKD stages.
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Affiliation(s)
- Sandra Benito
- Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country (UPV/EHU), Paseo de La Universidad 7, 01006, Vitoria-Gasteiz, Spain
- i+Med, S.Coop Parque Tecnológico de Alava, Albert Einstein 15, 01510, Vitoria-Gasteiz, Álava, Spain
| | - Nora Unceta
- Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country (UPV/EHU), Paseo de La Universidad 7, 01006, Vitoria-Gasteiz, Spain
| | - Mateusz Maciejczyk
- Department of Hygiene, Medical University of Bialystok, 15-233, Białystok, Poland
| | - Alicia Sánchez-Ortega
- Central Service of Analysis (Sgiker), University of the Basque Country (UPV/EHU), Laskaray Ikergunea, Miguel de Unamuno 3, 01006, Vitoria-Gasteiz, Spain
| | | | - Julita Szulimowska
- Department of Pedodontics, Medical University of Bialystok, 15-274, Białystok, Poland
| | - Anna Zalewska
- Department of Conservative Dentistry, Medical University of Bialystok, 15-274, Białystok, Poland
| | - Fernando Andrade
- Metabolomics and Proteomics Platform, Biobizkaia Health Research Institute, 48903, Barakaldo, Bizkaia, Spain
| | - Alberto Gómez-Caballero
- Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country (UPV/EHU), Paseo de La Universidad 7, 01006, Vitoria-Gasteiz, Spain
| | - Pawel Dubiela
- Department of Regenerative Medicine and Immune Regulation, Medical University of Bialystok, 15-269, Białystok, Poland.
| | - Ramón J Barrio
- Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country (UPV/EHU), Paseo de La Universidad 7, 01006, Vitoria-Gasteiz, Spain
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11
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Saba L, Hanna C, Creo AL. Updates in hyponatremia and hypernatremia. Curr Opin Pediatr 2024; 36:219-227. [PMID: 38174733 DOI: 10.1097/mop.0000000000001324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
PURPOSE OF REVIEW Hyponatremia and hypernatremia are commonly encountered electrolyte abnormalities that require timely and careful intervention, as they can be associated with significant morbidity and mortality. RECENT FINDINGS This review article addresses the etiology, presentation, diagnosis, and management of both hyponatremia and hypernatremia, emphasizing the latest advancements and emerging trends in pediatric care. SUMMARY A methodical approach is needed to accurately assess and treat hyponatremia and hypernatremia. Both conditions continue to rely on serum and urine testing, however newer tests such as copeptin and stimulated testing may hold promise to further refine testing in the future.
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Affiliation(s)
- Leslie Saba
- Department of Pediatric and Adolescent Medicine, Mayo Clinic
| | - Christian Hanna
- Division of Pediatric Nephrology and Hypertension, Department of Pediatric and Adolescent Medicine, Mayo Clinic
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic
| | - Ana L Creo
- Division of Pediatric Endocrinology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA
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12
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Roberts J, Whiley L, Gray N, Gay M, Nitschke P, Masuda R, Holmes E, Nicholson JK, Wist J, Lawler NG. Rapid and Self-Administrable Capillary Blood Microsampling Demonstrates Statistical Equivalence with Standard Venous Collections in NMR-Based Lipoprotein Analysis. Anal Chem 2024; 96:4505-4513. [PMID: 38372289 PMCID: PMC10955515 DOI: 10.1021/acs.analchem.3c05152] [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: 11/14/2023] [Revised: 01/17/2024] [Accepted: 01/29/2024] [Indexed: 02/20/2024]
Abstract
We investigated plasma and serum blood derivatives from capillary blood microsamples (500 μL, MiniCollect tubes) and corresponding venous blood (10 mL vacutainers). Samples from 20 healthy participants were analyzed by 1H NMR, and 112 lipoprotein subfraction parameters; 3 supramolecular phospholipid composite (SPC) parameters from SPC1, SPC2, and SPC3 subfractions; 2 N-acetyl signals from α-1-acid glycoprotein (Glyc), GlycA, and GlycB; and 3 calculated parameters, SPC (total), SPC3/SPC2, and Glyc (total) were assessed. Using linear regression between capillary and venous collection sites, we explained that agreement (Adj. R2 ≥ 0.8, p < 0.001) was witnessed for 86% of plasma parameters (103/120) and 88% of serum parameters (106/120), indicating that capillary lipoprotein, SPC, and Glyc concentrations follow changes in venous concentrations. These results indicate that capillary blood microsamples are suitable for sampling in remote areas and for high-frequency longitudinal sampling of the majority of lipoproteins, SPCs, and Glycs.
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Affiliation(s)
- Jayden
Lee Roberts
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
| | - Luke Whiley
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
| | - Nicola Gray
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
| | - Melvin Gay
- Bruker
Pty Ltd., Preston, VIC 3072, Australia
| | - Philipp Nitschke
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
| | - Reika Masuda
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
| | - Elaine Holmes
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Department
of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Jeremy K. Nicholson
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Department
of Cardiology, Fiona Stanley Hospital, Medical School, University of Western Australia, Murdoch, WA 6150, Australia
- Institute
of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington, London SW7 2NA, U.K.
| | - Julien Wist
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Faculty
of Medicine, Department of Metabolism, Digestion and Reproduction,
Division of Digestive Diseases, Imperial
College, London SW7 2AZ, United Kingdom
- Chemistry
Department, Universidad del Valle, Melendez 76001, Cali, Colombia
| | - Nathan G. Lawler
- Australian
National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute,
Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Murdoch, WA 6150, Australia
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13
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Zhang Z, Cui X, Zhou N, Zhu L, Zhi Y, Zhang S. Influence of plasma collection tubes on N-glycome in human blood samples. Pract Lab Med 2024; 39:e00383. [PMID: 38463195 PMCID: PMC10924059 DOI: 10.1016/j.plabm.2024.e00383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/20/2024] [Accepted: 02/27/2024] [Indexed: 03/12/2024] Open
Abstract
Background and aims Quantitative analysis of plasma N-glycome is a promising method for identifying disease biomarkers. This study aimed to investigate the impact of using blood collection tubes with different anticoagulants on plasma N-glycome. Materials and methods We used a robust mass spectrometry method to profile plasma N-glycomes in two cohorts of healthy volunteers (cohort 1, n = 16; cohort 2, n = 53). The influence of three commonly used blood collection tubes on fully characterized N-glycomic profiles were explored. Results Principal component analysis revealed distinct clustering of blood samples based on the collection tubes. Pairwise comparisons demonstrated significant differences between EDTA and heparin plasma in 55 out of 82 quantified N-glycan traits, and between EDTA and citrate plasma in 62 out of 82 traits. These differences encompassed various N-glycan features, including glycan type, sialylation, galactosylation, fucosylation, and bisection. Trends in N-glycan variations in citrate and heparin plasma were largely consistent compared to EDTA plasma. In correlation analysis (EDTA vs. heparin; EDTA vs. citrate), Pearson's correlation coefficients were consistently higher than 0.7 for the majority of N-glycan traits. Conclusion Sample matrix variations impact plasma N-glycome measurements. Caution is crucial when comparing samples from different plasma collection tubes in glycomics projects.
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Affiliation(s)
- Zejian Zhang
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Xiangyi Cui
- Department of Allergy & Clinical Immunology, National Clinical Research Center for Immunologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Nan Zhou
- Department of Allergy & Clinical Immunology, National Clinical Research Center for Immunologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Lisi Zhu
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Yuxiang Zhi
- Department of Allergy & Clinical Immunology, National Clinical Research Center for Immunologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
| | - Shuyang Zhang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China
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14
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Wang HY, Lin WY, Zhou C, Yang ZA, Kalpana S, Lebowitz MS. Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review. Cancers (Basel) 2024; 16:862. [PMID: 38473224 DOI: 10.3390/cancers16050862] [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: 12/31/2023] [Revised: 02/08/2024] [Accepted: 02/16/2024] [Indexed: 03/14/2024] Open
Abstract
The concept and policies of multicancer early detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control studies or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation, are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumors, and addressing cancer-related information, such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarker detection, MCED AI training/validation, and the clinical application. This review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.
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Affiliation(s)
- Hsin-Yao Wang
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 33343, Taiwan
- School of Medicine, National Tsing Hua University, Hsinchu 300044, Taiwan
- 20/20 GeneSystems, Gaithersburg, MD 20877, USA
| | - Wan-Ying Lin
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 33343, Taiwan
| | | | - Zih-Ang Yang
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 33343, Taiwan
| | - Sriram Kalpana
- Department of Laboratory Medicine, Linkou Chang Gung Memorial Hospital, Taoyuan 33343, Taiwan
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15
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Xiong W, Anthony DC, Anthony S, Ho TBT, Louis E, Satsangi J, Radford-Smith DE. Sodium fluoride preserves blood metabolite integrity for biomarker discovery in large-scale, multi-site metabolomics investigations. Analyst 2024; 149:1238-1249. [PMID: 38224241 DOI: 10.1039/d3an01359f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Background: Metabolite profiling of blood by nuclear magnetic resonance (NMR) is invaluable to clinical biomarker discovery. To ensure robustness, biomarkers require validation in large cohorts and across multiple centres. However, collection procedures are known to impact on the stability of biofluids that may, in turn, degrade biomarker signals. We trialled three blood collection tubes with the aim of solving technical challenges due to preanalytical variation in blood metabolite levels that are common in cohort studies. Methods: We first investigated global NMR-based metabolite variability between biobanks, including the large-scale UK Biobank and TwinsUK biobank of the general UK population, and more targeted biobanks derived from multicentre clinical trials relating to inflammatory bowel disease. We then compared the blood metabolome of 12 healthy adult volunteers when collected into either sodium fluoride/potassium oxalate, lithium heparin, or serum blood tubes using different pre-processing parameters. Results: Preanalytical variation in the method of blood collection strongly influences metabolite composition within and between biobanks. This variability can largely be attributed to glucose and lactate. In the healthy control cohort, the fluoride oxalate collection tube prevented fluctuation in glucose and lactate levels for 24 hours at either 4 °C or room temperature (20 °C). Conclusions: Blood collection into a fluoride oxalate collection tube appears to preserve the blood metabolome with delayed processing up to 24 hours at 4 °C. This method may be considered as an alternative when rapid processing is not feasible.
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Affiliation(s)
- Wenzheng Xiong
- Department of Chemistry, University of Oxford, Oxford, UK.
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Daniel C Anthony
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Suzie Anthony
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Thi Bao Tien Ho
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Edouard Louis
- Department of Gastroenterology, University Hospital CHU of Liège, Liège, Belgium
| | - Jack Satsangi
- Translational Gastroenterology Unit, Nuffield Department of Experimental Medicine, University of Oxford, Oxford, UK
| | - Daniel E Radford-Smith
- Department of Chemistry, University of Oxford, Oxford, UK.
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, UK
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16
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Ghaffari MH, Daniel JB, Sadri H, Schuchardt S, Martín-Tereso J, Sauerwein H. Longitudinal characterization of the metabolome of dairy cows transitioning from one lactation to the next: Investigations in blood serum. J Dairy Sci 2024; 107:1263-1285. [PMID: 37777004 DOI: 10.3168/jds.2023-23841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/07/2023] [Indexed: 10/02/2023]
Abstract
The objective of this study was to characterize changes in the serum metabolome and various indicators of oxidative balance in dairy cows starting 2 wk before dry-off and continuing until wk 16 of lactation. Twelve Holstein dairy cows (body weight 745 ± 71 kg, body condition score 3.43 ± 0.66; mean ± SD) were housed in a tiestall barn from 10 wk before to 16 wk after parturition. Cows were dried off 6 wk before the expected calving date (mean dry period length = 42 d). From 8 wk before calving to 16 wk after calving, blood samples were taken weekly to study redox metabolism by determining antioxidant capacity, measured as the ferric-reducing ability of plasma, reactive oxidative metabolites, oxidative stress index, oxidative damage of lipids, measured as thiobarbituric acid reactive substances, and glutathione peroxidase activity. According to these results, dairy cows had the lowest serum antioxidant capacity and greater levels of oxidative stress during the dry-off period and the early postpartum period. For metabolomics, a subset of serum samples including wk -7 (before dry-off), -5 (after dry-off), -1, 1, 5, 10, and 15 relative to calving were used. A targeted metabolomics approach was performed using liquid chromatography and flow injection with electrospray ionization triple quadrupole mass spectrometry using the MxP Quant 500 kit (Biocrates Life Sciences AG). A total of 240 metabolites in serum were used in the final data analysis. Principal component analysis revealed a clear separation by days of sampling, indicating a remarkable shift in metabolic phenotype between the dry period and late and early lactation. Changes in many non-lipid metabolites associated with one-carbon metabolism, the tricarboxylic acid cycle, the urea cycle, and AA catabolism were observed in the study, with changes in AA serum concentrations likely related to factors such as energy and nitrogen balance, digestive efficiency, and changing diets. The study confirmed an extensive remodeling of the serum lipidome in peripartum dairy cows, highlighting the importance of changes in acylcarnitine (acylCN), phosphatidylcholines (PC), and triacylglycerols (TG), as they play a crucial role in lipid metabolism. Results showed that short-chain acylCN increased after dry-off and decreased thereafter, whereas lipid-derived acylCN increased around parturition, suggesting that more fatty acids could enter mitochondria. Phospholipids and sphingolipids in serum showed changes during lactation. In particular, concentrations of sphingomyelins, PC, and lysoPC decreased around calving but increased in mid- and late lactation. In contrast, concentrations of TG remained consistently low after parturition. The serum concentrations of bile acids fluctuated during the dry period and lactation, with glycocholic acid, cholic acid, glycodeoxycholic acid, and taurocholic acid showing the greatest concentrations. These changes are likely due to the interplay of diet, liver function, and the ability of the gut microbiota to convert primary to secondary bile acids. Overall, these descriptive results may aid in hypothesis generation and in the design and interpretation of future metabolite-based studies in dairy cows. Furthermore, they contribute to our understanding of the physiological ranges in serum metabolites relative to the lactation cycle of the dairy cow.
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Affiliation(s)
- M H Ghaffari
- Institute of Animal Science, Physiology Unit, University of Bonn, 53115 Bonn, Germany.
| | - J B Daniel
- Trouw Nutrition R&D, 3800 AG, Amersfoort, the Netherlands.
| | - H Sadri
- Department of Clinical Science, Faculty of Veterinary Medicine, University of Tabriz, 5166616471 Tabriz, Iran
| | - S Schuchardt
- Fraunhofer Institute for Toxicology and Experimental Medicine, 30625 Hannover, Germany
| | | | - H Sauerwein
- Institute of Animal Science, Physiology Unit, University of Bonn, 53115 Bonn, Germany
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17
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Liang S, Cao X, Wang Y, Leng P, Wen X, Xie G, Luo H, Yu R. Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types. Int J Med Sci 2024; 21:234-252. [PMID: 38169594 PMCID: PMC10758149 DOI: 10.7150/ijms.85704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 10/14/2023] [Indexed: 01/05/2024] Open
Abstract
Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.
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Affiliation(s)
- Simin Liang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Xiujun Cao
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Yingshuang Wang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Ping Leng
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Xiaoxia Wen
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Guojing Xie
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Huaichao Luo
- Department of Clinical Laboratory, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China (UESTC), Chengdu, China
| | - Rong Yu
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
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18
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Bovo S, Schiavo G, Galimberti G, Fanelli F, Bertolini F, Dall'Olio S, Pagotto U, Fontanesi L. Comparative targeted metabolomic profiles of porcine plasma and serum. Animal 2023; 17:101029. [PMID: 38064856 DOI: 10.1016/j.animal.2023.101029] [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: 07/07/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 12/23/2023] Open
Abstract
Metabolomics has been used to characterise many biological matrices and obtain detailed pictures of biological systems based on many metabolites. Plasma and serum are two blood-derived biofluids commonly used to assess and monitor the organismal metabolism and obtain information on the physiological and health conditions of an animal. Plasma is the supernatant that is separated from the cellular components after centrifugation of the blood that is first added with an anticoagulant. Serum is obtained after centrifugation of the blood that has been coagulated. The choice of one or the other biofluid for metabolomic analyses is related to specific analytical needs and technical issues, to problems derived by the collection and preparation steps, in particular when specimens are sampled from animals involved in field studies. Thus far, most of the metabolomic studies that compared plasma and serum have been carried out in humans and very little is known on the pigs. In this study, we used a targeted metabolomic platform that can detect about 180 metabolites of five biochemical classes to compare plasma and serum profiles of samples collected from 24 pigs. To also obtain a cross-species comparative metabolomic analysis, information for human plasma and serum derived from the same platform was retrieved from previous studies. Statistical analyses included univariate and multivariate approaches aimed at identifying stable and/or differentially abundant metabolites between the two porcine biofluids. A total of 154 (∼83%) metabolites passed the initial quality control, indicating a good repeatability of the analytical platform in pigs. Discarded metabolites included aspartate and biogenic amines that were already reported to be unstable in human studies. More than 80% of the metabolites had similar profiles in both porcine biofluids (average correlation was 0.75). Concentrations were usually higher in serum than in plasma, in agreement with what was already reported in humans. The univariate analysis identified 44 metabolites that had statistically different concentrations between porcine plasma and serum, of which 28 metabolites were also confirmed by the multivariate analysis. The obtained picture described similarities and differences between these two biofluids in pigs and the related human-pig comparisons. The obtained information can be useful for the choice of one or the other matrix for the implementation of metabolomic studies in this livestock species. The results can also provide useful hints to valuing the pig as animal model, in particular when metabolite-derived physiological states are relevant.
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Affiliation(s)
- Samuele Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy
| | - Giuseppina Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy
| | - Giuliano Galimberti
- Department of Statistical Sciences "Paolo Fortunati", University of Bologna, 40126 Bologna, Italy
| | - Flaminia Fanelli
- Department of Surgical and Medical Sciences, Endocrinology Unit, University of Bologna, 40138 Bologna, Italy
| | - Francesca Bertolini
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy
| | - Stefania Dall'Olio
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy
| | - Uberto Pagotto
- Department of Surgical and Medical Sciences, Endocrinology Unit, University of Bologna, 40138 Bologna, Italy
| | - Luca Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, 40127 Bologna, Italy.
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19
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Shastry A, Dunham-Snary K. Metabolomics and mitochondrial dysfunction in cardiometabolic disease. Life Sci 2023; 333:122137. [PMID: 37788764 DOI: 10.1016/j.lfs.2023.122137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/05/2023]
Abstract
Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.
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Affiliation(s)
- Abhishek Shastry
- Department of Medicine, Queen's University, Kingston, ON, Canada
| | - Kimberly Dunham-Snary
- Department of Medicine, Queen's University, Kingston, ON, Canada; Department of Biomedical & Molecular Sciences, Queen's University, Kingston, ON, Canada.
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20
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Ghini V, Meoni G, Vignoli A, Di Cesare F, Tenori L, Turano P, Luchinat C. Fingerprinting and profiling in metabolomics of biosamples. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:105-135. [PMID: 38065666 DOI: 10.1016/j.pnmrs.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 12/18/2023]
Abstract
This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.
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Affiliation(s)
- Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy.
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy; Giotto Biotech S.r.l., Sesto Fiorentino, Italy.
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21
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Yuan Y, Song H, Zhou J, Yin Y. Evaluation of Small Molecules in Blank EDTA Plasma Tubes and Optimization of Metabolomic Workflow for Biomarker Studies Using Plasma Samples. Anal Chem 2023; 95:10859-10863. [PMID: 37428854 DOI: 10.1021/acs.analchem.3c01864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
As the first step of metabolomic analysis in biomarker identification studies, various types of blood collection tubes are used in clinical practice. However, little attention is paid to potential contamination caused by the blank tube itself. Here, we evaluated small molecules in blank EDTA plasma tubes through LC-MS-based untargeted metabolomic analysis and identified small molecules with markedly varied levels among different production batches or specifications. Our data demonstrate possible contamination and data interference caused by blank EDTA plasma tubes when employing large clinical cohorts for biomarker identification. Therefore, we propose a workflow of filtering metabolites in blank tubes prior to statistical analysis to improve the fidelity of biomarker identification.
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Affiliation(s)
- Yuyao Yuan
- Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Huajie Song
- Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Juntuo Zhou
- Beijing Boyuan Precision Medicine, Beijing 102206, China
| | - Yuxin Yin
- Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing 100191, China
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22
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Munhoz AC, Serna JDC, Vilas-Boas EA, Caldeira da Silva CC, Santos TG, Mosele FC, Felisbino SL, Martins VR, Kowaltowski AJ. Adiponectin reverses β-Cell damage and impaired insulin secretion induced by obesity. Aging Cell 2023:e13827. [PMID: 37060190 DOI: 10.1111/acel.13827] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 03/11/2023] [Accepted: 03/14/2023] [Indexed: 04/16/2023] Open
Abstract
Obesity significantly decreases life expectancy and increases the incidence of age-related dysfunctions, including β-cell dysregulation leading to inadequate insulin secretion. Here, we show that diluted plasma from obese human donors acutely impairs β-cell integrity and insulin secretion relative to plasma from lean subjects. Similar results were observed with diluted sera from obese rats fed ad libitum, when compared to sera from lean, calorically restricted, animals. The damaging effects of obese circulating factors on β-cells occurs in the absence of nutrient overload, and mechanistically involves mitochondrial dysfunction, limiting glucose-supported oxidative phosphorylation and ATP production. We demonstrate that increased levels of adiponectin, as found in lean plasma, are the protective characteristic preserving β-cell function; indeed, sera from adiponectin knockout mice limits β-cell metabolic fluxes relative to controls. Furthermore, oxidative phosphorylation and glucose-sensitive insulin secretion, which are completely abrogated in the absence of this hormone, are restored by the presence of adiponectin alone, surprisingly even in the absence of other serological components, for both the insulin-secreting INS1 cell line and primary islets. The addition of adiponectin to cells treated with plasma from obese donors completely restored β-cell functional integrity, indicating the lack of this hormone was causative of the dysfunction. Overall, our results demonstrate that low circulating adiponectin is a key damaging element for β-cells, and suggest strong therapeutic potential for the modulation of the adiponectin signaling pathway in the prevention of age-related β-cell dysfunction.
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Affiliation(s)
- Ana Cláudia Munhoz
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | - Julian D C Serna
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
| | | | | | - Tiago G Santos
- Centro Internacional de Pesquisa (CIPE), A. C. Camargo Cancer Center, São Paulo, Brazil
| | - Francielle C Mosele
- Instituto de Biociências de Botucatu (IBB), Universidade Estadual Paulista (UNESP), Botucatu, Brazil
| | - Sergio L Felisbino
- Instituto de Biociências de Botucatu (IBB), Universidade Estadual Paulista (UNESP), Botucatu, Brazil
| | - Vilma Regina Martins
- Centro Internacional de Pesquisa (CIPE), A. C. Camargo Cancer Center, São Paulo, Brazil
| | - Alicia J Kowaltowski
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil
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23
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Milić N, Milanović M, Drljača J, Sudji J, Milošević N. Challenges in the Analytical Preparation of a Biological Matrix in Analyses of Endocrine-Disrupting Bisphenols. SEPARATIONS 2023. [DOI: 10.3390/separations10040226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023] Open
Abstract
Endocrine-disrupting chemicals (EDCs) are xenobiotics presented in a variety of everyday products that may disrupt the normal activity of hormones. Exposure to bisphenol A as EDC at trace and ultra-trace levels is associated with adverse health effects, and children are recognized as the most vulnerable group to EDCs exposure. In this review, a summary is presented of up-to-date sample preparation methods and instrumental techniques applied for the detection and quantification of bisphenol A and its structural analogues in various biological matrices. Biological matrices such as blood, cell-free blood products, urine, saliva, breast milk, cordial blood, amniotic and semen fluids, as well as sweat and hair, are very complex; therefore, the detection and later quantification of bisphenols at low levels present a real analytical challenge. The most popular analytical approaches include gas and liquid chromatography coupled with mass spectrometry, and their enhanced reliability and sensitivity finally allow the separation and detection of bisphenols in biological samples, even as ultra-traces. Liquid/liquid extraction (LLE) and solid-phase extraction (SPE) are still the most common methods for their extraction from biological matrices. However, many modern and environmentally safe microextraction techniques are currently under development. The complexity of biological matrices and low concentrations of analytes are the main issues for the limited identification, as well as understanding the adverse health effects caused by chronical and ubiquitous exposure to bisphenols and its analogues.
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).
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Affiliation(s)
- Dorota Garwolińska
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
| | - Agata Kot-Wasik
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
| | - Weronika Hewelt-Belka
- Department of Analytical Chemistry, Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
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25
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington
- Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington
- Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109
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26
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Risi E, Lisanti C, Vignoli A, Biagioni C, Paderi A, Cappadona S, Monte FD, Moretti E, Sanna G, Livraghi L, Malorni L, Benelli M, Puglisi F, Luchinat C, Tenori L, Biganzoli L. Risk assessment of disease recurrence in early breast cancer: A serum metabolomic study focused on elderly patients. Transl Oncol 2023; 27:101585. [PMID: 36403505 PMCID: PMC9676351 DOI: 10.1016/j.tranon.2022.101585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 10/28/2022] [Accepted: 11/08/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND We previously showed that metabolomics predicts relapse in early breast cancer (eBC) patients, unselected by age. This study aims to identify a "metabolic signature" that differentiates eBC from advanced breast cancer (aBC) patients, and to investigate its potential prognostic role in an elderly population. METHODS Serum samples from elderly breast cancer (BC) patients enrolled in 3 onco-geriatric trials, were retrospectively analyzed via proton nuclear magnetic resonance (1H NMR) spectroscopy. Three nuclear magnetic resonance (NMR) spectra were acquired for each serum sample: NOESY1D, CPMG, Diffusion-edited. Random Forest (RF) models to predict BC relapse were built on NMR spectra, and resulting RF risk scores were evaluated by Kaplan-Meier curves. RESULTS Serum samples from 140 eBC patients and 27 aBC were retrieved. In the eBC cohort, median age was 76 years; 77% of patients had luminal, 10% HER2-positive and 13% triple negative (TN) BC. Forty-two percent of patients had tumors >2 cm, 43% had positive axillary nodes. Using NOESY1D spectra, the RF classifier discriminated free-from-recurrence eBC from aBC with sensitivity, specificity and accuracy of 81%, 67% and 70% respectively. We tested the NOESY1D spectra of each eBC patient on the RF models already calculated. We found that patients classified as "high risk" had higher risk of disease recurrence (hazard ratio (HR) 3.42, 95% confidence interval (CI) 1.58-7.37) than patients at low-risk. CONCLUSIONS This analysis suggests that a "metabolic signature", identified employing NMR fingerprinting, is able to predict the risk of disease recurrence in elderly patients with eBC independently from standard clinicopathological features.
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Affiliation(s)
- Emanuela Risi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Camilla Lisanti
- Cro Aviano - National Cancer Institute - IRCCS, Medical Oncology and Cancer Prevention, Aviano, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | | | - Agnese Paderi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Silvia Cappadona
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Francesca Del Monte
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Erica Moretti
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Giuseppina Sanna
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Luca Livraghi
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | - Luca Malorni
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy
| | | | - Fabio Puglisi
- Cro Aviano - National Cancer Institute - IRCCS, Medical Oncology and Cancer Prevention, Aviano, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Laura Biganzoli
- Sandro Pitigliani Medical Oncology Department, Hospital of Prato, Prato, Italy.
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27
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Vignoli A, Meoni G, Ghini V, Di Cesare F, Tenori L, Luchinat C, Turano P. NMR-Based Metabolomics to Evaluate Individual Response to Treatments. Handb Exp Pharmacol 2023; 277:209-245. [PMID: 36318327 DOI: 10.1007/164_2022_618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy. .,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy. .,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy.
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28
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Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective. Metabolites 2022; 12:metabo12121244. [PMID: 36557282 PMCID: PMC9781488 DOI: 10.3390/metabo12121244] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/22/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.
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29
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Jian Q, Wu Y, Zhang F. Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress. Cells 2022; 11:cells11193005. [PMID: 36230967 PMCID: PMC9563658 DOI: 10.3390/cells11193005] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/22/2022] [Indexed: 11/18/2022] Open
Abstract
Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.
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Affiliation(s)
- Qizhi Jian
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yingjie Wu
- Institute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Liaoning Provence Key Laboratory of Genome Engineered Animal Models, Dalian Medical University, Dalian 116000, China
- Shandong Provincial Hospital, School of Laboratory Animal & Shandong Laboratory Animal Center, Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, China
- Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY 10010, USA
- Correspondence: (Y.W.); (F.Z.)
| | - Fang Zhang
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
- Correspondence: (Y.W.); (F.Z.)
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