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Chang CW, Hsu JY, Hsiao PZ, Sung PS, Liao PC. Optimized analytical strategy based on high-resolution mass spectrometry for unveiling associations between long-term chemical exposome in hair and Alzheimer's disease. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116955. [PMID: 39213755 DOI: 10.1016/j.ecoenv.2024.116955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 08/24/2024] [Accepted: 08/25/2024] [Indexed: 09/04/2024]
Abstract
Exposure to environmental pollutants or contaminants is correlated with detrimental effects on human health, such as neurodegenerative diseases. Adopting hair as a biological matrix for biomonitoring is a significant innovation, since it can reflect the long-term chemical exposome, spanning months to years. However, only a limited number of studies have developed analytical strategies for profiling the chemical exposome in this heterogeneous biological matrix. In this study, a systematic investigation of the chemical extraction procedure from human hair was conducted, using a design of experiments and a high-resolution mass spectrometry (HRMS)-based suspect screening approach. The PlackettBurman (PB) design was applied to identify the significant variables influencing the number of detected features. Then, a central composite design was implemented to optimize the levels of each identified significant variable. Under the optimal conditions-15-minute pulverization, 25 mg of hair weight, 40 min of sonication, and a sonication temperature of 35 °C-approximately 32,000 and 15,000 aligned features were detected in positive and negative ion modes, respectively. This optimized analytical procedure was applied to hair samples from patients with Alzheimer's disease (AD) and individuals with normal cognitive function. Overall, 307 chemicals were identified using the suspect screening approach, with 37 chemicals differentiating patients with AD from controls. This study not only optimized an analytical procedure for characterizing the long-term chemical exposome in human hair but also explored the associations between AD and environmental factors.
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Affiliation(s)
- Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Ping-Zu Hsiao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Pi-Shan Sung
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan; Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
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Nagano E, Saito H, Mannari T, Kuge M, Odake K, Shimma S. Analysis of the Correlation between Cholesterol Levels in Blood Using Clinical Data and Hair Using Mass Spectrometry Imaging. Mass Spectrom (Tokyo) 2024; 13:A0149. [PMID: 39076408 PMCID: PMC11284271 DOI: 10.5702/massspectrometry.a0149] [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: 06/17/2024] [Accepted: 07/08/2024] [Indexed: 07/31/2024] Open
Abstract
Mass spectrometry imaging (MSI) is a technique that visualizes the distribution of molecules by ionizing the components on the surface of a sample and directly detecting them. Previously, MSI using hair has primarily been used in the forensic field to detect illegal drugs. On the other hand, there are few examples of using this technology for health monitoring. In this study, hair and clinical data were collected from 24 subjects, and the correlation between blood cholesterol levels and cholesterol detected from cross-sectional hair slices was analyzed. As a result, a positive correlation with a correlation coefficient of 0.43 was observed between blood cholesterol and cholesterol detected from hair. Furthermore, when comparing the results of fluorescence staining (FS) of hair cholesterol with Filipin III and the MSI results, it was found that while FS could visualize detailed hair structures, there were cases where the results differed from MSI, possibly due to some cholesterol loss during the staining process. In the future, if various disease biomarkers can be detected using hair MSI, it could potentially become a non-invasive diagnostic method.
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Affiliation(s)
- Erika Nagano
- Miruion Inc., 7–7–20 Asagi, Saito, Suita, Osaka 567–0085, Japan
| | - Hiromi Saito
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Osaka, Japan
| | - Tetsuya Mannari
- Cosmetic Research and Development Department, Takara Belmont Corp., Shiga, Japan
| | - Munekazu Kuge
- Cosmetic Research and Development Department, Takara Belmont Corp., Shiga, Japan
| | - Kazuki Odake
- Miruion Inc., 7–7–20 Asagi, Saito, Suita, Osaka 567–0085, Japan
| | - Shuichi Shimma
- Miruion Inc., 7–7–20 Asagi, Saito, Suita, Osaka 567–0085, Japan
- Department of Biotechnology, Graduate School of Engineering, Osaka University, Osaka, Japan
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Miller HA, Suliman S, Frieboes HB. Pulmonary Fibrosis Diagnosis and Disease Progression Detected Via Hair Metabolome Analysis. Lung 2024:10.1007/s00408-024-00712-3. [PMID: 38861171 DOI: 10.1007/s00408-024-00712-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 05/30/2024] [Indexed: 06/12/2024]
Abstract
BACKGROUND Fibrotic interstitial lung disease is often identified late due to non-specific symptoms, inadequate access to specialist care, and clinical unawareness precluding proper and timely treatment. Biopsy histological analysis is definitive but rarely performed due to its invasiveness. Diagnosis typically relies on high-resolution computed tomography, while disease progression is evaluated via frequent pulmonary function testing. This study tested the hypothesis that pulmonary fibrosis diagnosis and progression could be non-invasively and accurately evaluated from the hair metabolome, with the longer-term goal to minimize patient discomfort. METHODS Hair specimens collected from pulmonary fibrosis patients (n = 56) and healthy subjects (n = 14) were processed for metabolite extraction using 2DLC/MS-MS, and data were analyzed via machine learning. Metabolomic data were used to train machine learning classification models tuned via a rigorous combination of cross validation, feature selection, and testing with a hold-out dataset to evaluate classifications of diseased vs. healthy subjects and stable vs. progressed disease. RESULTS Prediction of pulmonary fibrosis vs. healthy achieved AUROCTRAIN = 0.888 (0.794-0.982) and AUROCTEST = 0.908, while prediction of stable vs. progressed disease achieved AUROCTRAIN = 0.833 (0.784 - 0.882) and AUROCTEST = 0. 799. Top metabolites for diagnosis included ornithine, 4-(methylnitrosamino)-1-3-pyridyl-N-oxide-1-butanol, Thr-Phe, desthiobiotin, and proline. Top metabolites for progression included azelaic acid, Thr-Phe, Ala-Tyr, indoleacetyl glutamic acid, and cytidine. CONCLUSION This study provides novel evidence that pulmonary fibrosis diagnosis and progression may in principle be evaluated from the hair metabolome. Longer term, this approach may facilitate non-invasive and accurate detection and monitoring of fibrotic lung diseases.
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Affiliation(s)
- Hunter A Miller
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40292, USA
| | - Sally Suliman
- Division of Pulmonary Medicine, University of Louisville, Louisville, KY, USA
- University of Arizona Medical Center Phoenix, Phoenix, AZ, USA
| | - Hermann B Frieboes
- Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40292, USA.
- UofL Health - Brown Cancer Center, University of Louisville, Louisville, KY, USA.
- Center for Predictive Medicine, University of Louisville, Louisville, KY, USA.
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Chang CW, Hsu JY, Lo YT, Liu YH, Mee-inta O, Lee HT, Kuo YM, Liao PC. Characterization of Hair Metabolome in 5xFAD Mice and Patients with Alzheimer's Disease Using Mass Spectrometry-Based Metabolomics. ACS Chem Neurosci 2024; 15:527-538. [PMID: 38269400 PMCID: PMC10853927 DOI: 10.1021/acschemneuro.3c00587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/11/2024] [Accepted: 01/11/2024] [Indexed: 01/26/2024] Open
Abstract
Hair emerged as a biospecimen for long-term investigation of endogenous metabolic perturbations, reflecting the chemical composition circulating in the blood over the past months. Despite its potential, the use of human hair for metabolomics in Alzheimer's disease (AD) research remains limited. Here, we performed both untargeted and targeted metabolomic approaches to profile the key metabolic pathways in the hair of 5xFAD mice, a widely used AD mouse model. Furthermore, we applied the discovered metabolites to human subjects. Hair samples were collected from 6-month-old 5xFAD mice, a stage marked by widespread accumulation of amyloid plaques in the brain, followed by sample preparation and high-resolution mass spectrometry analysis. Forty-five discriminatory metabolites were discovered in the hair of 6-month-old 5xFAD mice compared to wild-type control mice. Enrichment analysis revealed three key metabolic pathways: arachidonic acid metabolism, sphingolipid metabolism, and alanine, aspartate, and glutamate metabolism. Among these pathways, six metabolites demonstrated significant differences in the hair of 2-month-old 5xFAD mice, a stage prior to the onset of amyloid plaque deposition. These findings suggest their potential involvement in the early stages of AD pathogenesis. When evaluating 45 discriminatory metabolites for distinguishing patients with AD from nondemented controls, a combination of l-valine and arachidonic acid significantly differentiated these two groups, achieving a 0.88 area under the curve. Taken together, these findings highlight the potential of hair metabolomics in identifying disease-specific metabolic alterations and developing biomarkers for improving disease detection and monitoring.
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Affiliation(s)
- Chih-Wei Chang
- Department
of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Jen-Yi Hsu
- Department
of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Yu-Tai Lo
- Department
of Geriatrics and Gerontology, National Cheng Kung University Hospital,
College of Medicine, National Cheng Kung
University, Tainan 704, Taiwan
- Department
of Public Health, College of Medicine, National
Cheng Kung University, Tainan 704, Taiwan
| | - Yu-Hsuan Liu
- Department
of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Onanong Mee-inta
- Institute
of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Hsueh-Te Lee
- Institute
of Anatomy and Cell Biology, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Yu-Min Kuo
- Institute
of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
- Department
of Cell Biology and Anatomy, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Pao-Chi Liao
- Department
of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department
of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
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Yin N, Jiang X, Yu M, Yang Y, Ge H, Han TL, Qi H. The maternal hair metabolome is capable of discriminating intrahepatic cholestasis of pregnancy from uncomplicated pregnancy. Front Endocrinol (Lausanne) 2024; 14:1280833. [PMID: 38260149 PMCID: PMC10801165 DOI: 10.3389/fendo.2023.1280833] [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: 08/21/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disease associated with elevated bile acids in the blood. Diagnosis typically only occurs after the manifestation of clinical symptoms and the metabolic mechanisms underlying its development remain unclear. The aim of this study was to investigate potential specific metabolites and the underlying metabolic changes occurring during the development of ICP in the maternal plasma and hair metabolomes of women diagnosed with either ICP or having a healthy pregnancy. Methods A total of 35 Chinese women with ICP and 42 healthy pregnancies were enrolled in our study. Plasma and hair samples, total bile acid levels (TBA), alanine transaminase levels (ALT), aspartate aminotransferase levels (AST), and additional clinical information were collected during the third trimester. Metabolites from maternal plasma and hair segments collected pre-conception and analyzed using gas chromatography-mass spectrometry (GC-MS). Results Three plasma metabolites (p < 0.05, q < 0.38) and 21 hair metabolites (p < 0.05, q < 0.05) were significantly different between ICP and healthy pregnancies. A combination of the eight most significant hair metabolites in a multivariate receiver operating characteristic curve model showed the best area under the curve (AUC) was 0.885, whereas the highest AUC using metabolites from plasma samples was only 0.74. Metabolic pathway analysis revealed 32 pathways were significantly (p and q values < 0.05) affected in the hair samples of patients with ICP. Pathways associated with glutathione metabolism and ABC transporters were affected. No metabolic pathways were significantly affected in plasma. Discussion Overall, this study showed that the hair metabolome could be more useful than the plasma metabolome for distinguishing ICP from normal pregnancy.
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Affiliation(s)
- Nanlin Yin
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Center for Reproductive Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiuping Jiang
- Center for Reproductive Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Muhua Yu
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yang Yang
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Huisheng Ge
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Ting-Li Han
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Hongbo Qi
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
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de Souza HMR, Pereira TTP, de Sá HC, Alves MA, Garrett R, Canuto GAB. Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens. Metabolites 2024; 14:36. [PMID: 38248839 PMCID: PMC10819689 DOI: 10.3390/metabo14010036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/23/2024] Open
Abstract
This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.
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Affiliation(s)
- Hygor M. R. de Souza
- Instituto de Química, Universidade Federal do Rio de Janeiro, LabMeta—LADETEC, Rio de Janeiro 21941-598, Brazil;
| | - Tássia T. P. Pereira
- Departamento de Genética, Ecologia e Evolucao, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil;
- Departamento de Biodiversidade, Evolução e Meio Ambiente, Universidade Federal de Ouro Preto, Ouro Preto 35400-000, Brazil
| | - Hanna C. de Sá
- Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia, Salvador 40170-115, Brazil;
| | - Marina A. Alves
- Instituto de Pesquisa de Produtos Naturais Walter Mors, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-599, Brazil;
| | - Rafael Garrett
- Instituto de Química, Universidade Federal do Rio de Janeiro, LabMeta—LADETEC, Rio de Janeiro 21941-598, Brazil;
- Department of Laboratory Medicine, Boston Children’s Hospital—Harvard Medical School, Boston, MA 02115, USA
| | - Gisele A. B. Canuto
- Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia, Salvador 40170-115, Brazil;
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Chen CJ, Lee DY, Yu J, Lin YN, Lin TM. Recent advances in LC-MS-based metabolomics for clinical biomarker discovery. MASS SPECTROMETRY REVIEWS 2023; 42:2349-2378. [PMID: 35645144 DOI: 10.1002/mas.21785] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/14/2021] [Accepted: 11/18/2021] [Indexed: 06/15/2023]
Abstract
The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.
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Affiliation(s)
- Chao-Jung Chen
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan
- Proteomics Core Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Der-Yen Lee
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Jiaxin Yu
- AI Innovation Center, China Medical University Hospital, Taichung, Taiwan
| | - Yu-Ning Lin
- Proteomics Core Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Tsung-Min Lin
- Proteomics Core Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
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Xia YY, de Seymour JV, Yang XJ, Zhou LW, Liu Y, Yang Y, Beck KL, Conlon CA, Mansell T, Novakovic B, Saffery R, Han TL, Zhang H, Baker PN. Hair and cord blood element levels and their relationship with air pollution, dietary intake, gestational diabetes mellitus, and infant neurodevelopment. Clin Nutr 2023; 42:1875-1888. [PMID: 37625317 DOI: 10.1016/j.clnu.2023.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 07/30/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023]
Abstract
BACKGROUND & AIMS Exposure to a range of elements, air pollution, and specific dietary components in pregnancy has variously been associated with gestational diabetes mellitus (GDM) risk or infant neurodevelopmental problems. We measured a range of pregnancy exposures in maternal hair and/or infant cord serum and tested their relationship to GDM and infant neurodevelopment. METHODS A total of 843 pregnant women (GDM = 224, Non-GDM = 619) were selected from the Complex Lipids in Mothers and Babies cohort study. Forty-eight elements in hair and cord serum were quantified using inductively coupled plasma-mass spectrometry analysis. Binary logistic regression was used to estimate the associations between hair element concentrations and GDM risk, while multiple linear regression was performed to analyze the relationship between hair/cord serum elements and air pollutants, diet exposures, and Bayley Scales of infant neurodevelopment at 12 months of age. RESULTS After adjusting for maternal age, BMI, and primiparity, we observed that fourteen elements in maternal hair were associated with a significantly increased risk of GDM, particularly Ta (OR = 9.49, 95% CI: 6.71, 13.42), Re (OR = 5.21, 95% CI: 3.84, 7.07), and Se (OR = 5.37, 95% CI: 3.48, 8.28). In the adjusted linear regression model, three elements (Rb, Er, and Tm) in maternal hair and infant cord serum were negatively associated with Mental Development Index scores. For dietary exposures, elements were positively associated with noodles (Nb), sweetened beverages (Rb), poultry (Cs), oils and condiments (Ca), and other seafood (Gd). In addition, air pollutants PM2.5 (LUR) and PM10 were negatively associated with Ta and Re in maternal hair. CONCLUSIONS Our findings highlight the potential influence of maternal element exposure on GDM risk and infant neurodevelopment. We identified links between levels of these elements in both maternal hair and infant cord serum related to air pollutants and dietary factors.
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Affiliation(s)
- Yin-Yin Xia
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Department of Occupational and Environmental Hygiene, School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China; Mass Spectrometry Center of Maternal Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Jamie V de Seymour
- School of Sport, Exercise and Nutrition, College of Health, Massey University, Auckland, New Zealand
| | - Xiao-Jia Yang
- Department of Occupational and Environmental Hygiene, School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Lin-Wei Zhou
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yue Liu
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Department of Occupational and Environmental Hygiene, School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China; Mass Spectrometry Center of Maternal Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Yang Yang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Mass Spectrometry Center of Maternal Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Kathryn L Beck
- School of Sport, Exercise and Nutrition, College of Health, Massey University, Auckland, New Zealand
| | - Cathryn A Conlon
- School of Sport, Exercise and Nutrition, College of Health, Massey University, Auckland, New Zealand
| | - Toby Mansell
- Molecular Immunity, Murdoch Children's Research Institute, Melbourne, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Boris Novakovic
- Molecular Immunity, Murdoch Children's Research Institute, Melbourne, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Richard Saffery
- Molecular Immunity, Murdoch Children's Research Institute, Melbourne, VIC, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Ting-Li Han
- Mass Spectrometry Center of Maternal Fetal Medicine, Chongqing Medical University, Chongqing, China; Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China; Institute of Life Sciences, Chongqing Medical University, Chongqing, China.
| | - Hua Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Mass Spectrometry Center of Maternal Fetal Medicine, Chongqing Medical University, Chongqing, China.
| | - Philip N Baker
- College of Life Sciences, University of Leicester, Leicester, United Kingdom
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Tan TH, Li SW, Chang CW, Chen YC, Liu YH, Ma JT, Chang CP, Liao PC. Rat Hair Metabolomics Analysis Reveals Perturbations of Unsaturated Fatty Acid Biosynthesis, Phenylalanine, and Arachidonic Acid Metabolism Pathways Are Associated with Amyloid-β-Induced Cognitive Deficits. Mol Neurobiol 2023; 60:4373-4395. [PMID: 37095368 PMCID: PMC10293421 DOI: 10.1007/s12035-023-03343-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 04/04/2023] [Indexed: 04/26/2023]
Abstract
Hair is a noninvasive valuable biospecimen for the long-term assessment of endogenous metabolic disturbance. Whether the hair is suitable for identifying biomarkers of the Alzheimer's disease (AD) process remains unknown. We aim to investigate the metabolism changes in hair after β-amyloid (Aβ1-42) exposure in rats using ultra-high-performance liquid chromatography-high-resolution mass spectrometry-based untargeted and targeted methods. Thirty-five days after Aβ1-42 induction, rats displayed significant cognitive deficits, and forty metabolites were changed, of which twenty belonged to three perturbed pathways: (1) phenylalanine metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis-L-phenylalanine, phenylpyruvate, ortho-hydroxyphenylacetic acid, and phenyllactic acid are up-regulated; (2) arachidonic acid (ARA) metabolism-leukotriene B4 (LTB4), arachidonyl carnitine, and 5(S)-HPETE are upregulation, but ARA, 14,15-DiHETrE, 5(S)-HETE, and PGB2 are opposite; and (3) unsaturated fatty acid biosynthesis- eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), FA 18:3 + 1O, and FA 18:3 + 2O are downregulated. Linoleic acid metabolism belonging to the biosynthesis of unsaturated fatty acid includes the upregulation of 8-hydroxy-9,10-epoxystearic acid, 13-oxoODE, and FA 18:2 + 4O, and downregulation of 9(S)-HPODE and dihomo-γ-linolenic acid. In addition, cortisone and dehydroepiandrosterone belonging to steroid hormone biosynthesis are upregulated. These three perturbed metabolic pathways also correlate with cognitive impairment after Aβ1-42 stimulation. Furthermore, ARA, DHA, EPA, L-phenylalanine, and cortisone have been previously implicated in the cerebrospinal fluid of AD patients and show a similar changing trend in Aβ1-42 rats' hair. These data suggest hair can be a useful biospecimen that well reflects the expression of non-polar molecules under Aβ1-42 stimulation, and the five metabolites have the potential to serve as novel AD biomarkers.
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Affiliation(s)
- Tian-Hoe Tan
- Department of Emergency Medicine, Chi Mei Medical Center, Tainan, 710, Taiwan
- Department of Senior Services, Southern Taiwan University of Science and Technology, No.1, Nantai St., Yungkang Dist., Tainan, 710, Taiwan
| | - Shih-Wen Li
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan, 70428, Taiwan
| | - Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan, 70428, Taiwan
| | - Yuan-Chih Chen
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan, 70428, Taiwan
| | - Yu-Hsuan Liu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan, 70428, Taiwan
| | - Jui-Ti Ma
- Department of Medical Research, Chi Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan, 710, Taiwan
| | - Ching-Ping Chang
- Department of Medical Research, Chi Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan, 710, Taiwan.
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan, 70428, Taiwan.
- Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan.
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Yang Z, Luo X, Huang B, Jia X, Luan X, Shan N, An Z, Cao J, Qi H. Altered distribution of fatty acid exerting lipid metabolism and transport at the maternal-fetal interface in fetal growth restriction. Placenta 2023; 139:159-171. [PMID: 37406553 DOI: 10.1016/j.placenta.2023.05.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 05/17/2023] [Accepted: 05/31/2023] [Indexed: 07/07/2023]
Abstract
INTRODUCTION Fetal growth restriction (FGR) is a common complication of pregnancy. Lipid metabolism and distribution may contribute to the progression of FGR. However, the metabolism-related mechanisms of FGR remain unclear. The aim of this study was to identify metabolic profiles associated with FGR, as well as probable genes and signaling pathways. METHODS Metabolomic profiles at the maternal-fetal interface (including the placenta, maternal and fetal serum) from pregnant women with (n = 35) and without (n = 35) FGR were analyzed by gas chromatography-mass spectrometry (GC-MS). Combined with differentially expressed genes (DEGs) from the GSE35574 dataset, analysis was performed for differential metabolites, and identified by the Metabo Analyst dataset. Finally, the pathology and screened DEGs were further identified. RESULTS The results showed that fatty acids (FAs) accumulated in the placenta and decreased in fetal blood in FGR cases compared to controls. The linoleic acid metabolism was the focus of placental differential metabolites and genes enrichment analysis. In this pathway, phosphatidylcholine can interact with PLA2G2A and PLA2G4C, and 12(13)-EpOME can interact with CYP2J2. PLA2G2A and CYP2J2 were elevated, and PLA2G4C was decreased in the FGR placenta. DISCUSSION In conclusion, accumulation of FAs in the placental ischemic environments, may involve linoleic acid metabolism, which may be regulated by PLA2G2A, CYP2J2, and PLA2G4C. This study may contribute to understanding the underlying metabolic and molecular mechanisms of FGR.
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Affiliation(s)
- Zhongmei Yang
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; The Department of Obstetrics and Gynecology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China; Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China.
| | - Xiaofang Luo
- Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Biao Huang
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Xiaoyan Jia
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Xiaojin Luan
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Nan Shan
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Zhongling An
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Jinfeng Cao
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, 400016, China
| | - Hongbo Qi
- The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China; Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, 400016, China; Women and Children's Hospital of Chongqing Medical University, Chongqing, 401147, China.
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Chang CW, Hsu JY, Su YH, Chen YC, Hsiao PZ, Liao PC. Monitoring long-term chemical exposome by characterizing the hair metabolome using a high-resolution mass spectrometry-based suspect screening approach. CHEMOSPHERE 2023; 332:138864. [PMID: 37156292 DOI: 10.1016/j.chemosphere.2023.138864] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 03/20/2023] [Accepted: 05/05/2023] [Indexed: 05/10/2023]
Abstract
Hair has recently emerged as a biospecimen for characterizing the long-term chemical exposome in biomonitoring investigations spanning several months, as chemical compounds circulating in the bloodstream accumulate in hair. Although there has been interest in using human hair as a biospecimen for exposome studies, it has yet to be widely adopted compared to blood and urine. Here, we applied a high-resolution mass spectrometry (HRMS)-based suspect screening strategy to characterize the long-term chemical exposome in human hair. Hair samples were collected from 70 subjects and cut into 3 cm segments, which were then mixed to prepare pooled samples. The pooled hair samples underwent a sample preparation procedure, and the hair extracts were further analyzed using an HRMS-based suspect screening approach. An in-house chemical suspect list containing 1227 chemical entries from National Report on Human Exposure to Environmental Chemicals (Report) published by the U.S. CDC and the Exposome-Explorer 3.0 database developed by the WHO was subsequently used to screen and filter the suspect features against the HRMS dataset. Overall, we matched 587 suspect features in the HRMS dataset to 246 unique chemical formulas in the suspect list, and the structures of 167 chemicals were further identified through a fragmentation analysis. Among these, chemicals such as mono-2-ethylhexyl phthalate, methyl paraben, and 1-naphthol, which have been detected in the urine or blood for exposure assessment, were also identified in human hair. This suggests that hair reflects the accumulation of environmental compounds to which an individual is exposed. Exposure to exogenous chemicals may exert adverse effects on cognitive function, and we discovered 15 chemicals in human hair that may contribute to the pathogenesis of Alzheimer's disease. This finding suggests that human hair may be a promising biospecimen for monitoring long-term exposure to multiple environmental chemicals and perturbations in endogenous chemicals in biomonitoring investigations.
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Affiliation(s)
- Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Yu-Hsiang Su
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, 60002, Taiwan
| | - Yuan-Chih Chen
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ping-Zu Hsiao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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Najafova T, Dagdeviren G, Kasikci M, Sahin D, Yucel A, Ozyuncu O, Gurler M. Segmental hair metabolomics analysis in pregnant women with pregnancy complications. Metabolomics 2023; 19:45. [PMID: 37084096 DOI: 10.1007/s11306-023-02009-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
INTRODUCTION Pregnancy complications, as preeclampsia (PE) and HELLP syndrome, occurring with similar pathophysiological mechanisms, have adverse effects on the health of both mother and fetus during pregnancy and thereafter, they are leading causes of maternal and fetal morbidity and mortality. The hair metabolome has been recognized as a valuable source of information in pregnancy research, as it provides stable metabolite information to be able to assist with studying biomarkers or metabolic mechanisms of pregnancy and its complications. OBJECTIVE The aim of this study was to investigate the hair metabolome profile of pregnant women with PE, HELLP syndrome and healthy women. METHOD Hair samples of new-borns' mothers (patients and controls) were investigated segmentally relevant to each trimester using a proper sample preparation and gas chromatography-mass spectrometry (GC-MS) to identify robust biomarkers that can be useful for screening, early detection, follow-up and treatment of PE and HELLP syndrome, the etiology of which are still unknown. RESULTS The results showed a significant change in the metabolome profiles of the patient and control groups regarding the trimesters. A striking decrease was observed in all 100 metabolites investigated in the patient group (p < 0.000). The metabolic pathways associated with significant metabolites have also been investigated, and the most affected pathways were observed to be the urea cycle, glycine, serine, aspartate, methionine and purine metabolism, ammonia cycle, and phosphatidylethanolamine biosynthesis. CONCLUSION The found metabolites provide us with extensive data on the ability to establish biomarkers for predicting, early detection and monitoring of PE.
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Affiliation(s)
- Tahmina Najafova
- Department of Medical Biochemistry, Faculty of Medicine, Hacettepe University, Sıhhiye, 06100, Ankara, Turkey.
| | - Gulsah Dagdeviren
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Merve Kasikci
- Department of Biostatistics, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Dilek Sahin
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Aykan Yucel
- Department of Perinatology, University of Health Sciences Etlik Zubeyde Hanım Women's Health Care, Training and Research Hospital, Ankara, Turkey
| | - Ozgur Ozyuncu
- Department of Gynaecology and Obstetrics, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Mukaddes Gurler
- Department of Medical Biochemistry, Faculty of Medicine, Hacettepe University, Sıhhiye, 06100, Ankara, Turkey
- Department of Medical Biochemistry and Forensic Medicine, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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Chang CW, Hsu JY, Hsiao PZ, Chen YC, Liao PC. Identifying Hair Biomarker Candidates for Alzheimer's Disease Using Three High Resolution Mass Spectrometry-Based Untargeted Metabolomics Strategies. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:550-561. [PMID: 36973238 DOI: 10.1021/jasms.2c00294] [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] [Indexed: 06/18/2023]
Abstract
High-resolution mass spectrometry (HRMS)-based untargeted metabolomics strategies have emerged as an effective tool for discovering biomarkers of Alzheimer's disease (AD). There are various HRMS-based untargeted metabolomics strategies for biomarker discovery, including the data-dependent acquisition (DDA) method, the combination of full scan and target MS/MS, and the all ion fragmentation (AIF) method. Hair has emerged as a potential biospecimen for biomarker discovery in clinical research since it might reflect the circulating metabolic profiles over several months, while the analytical performances of the different data acquisition methods for hair biomarker discovery have been rarely investigated. Here, the analytical performances of three data acquisition methods in HRMS-based untargeted metabolomics for hair biomarker discovery were evaluated. The human hair samples from AD patients (N = 23) and cognitively normal individuals (N = 23) were used as an example. The most significant number of discriminatory features was acquired using the full scan (407), which is approximately 10-fold higher than that using the DDA strategy (41) and 11% higher than that using the AIF strategy (366). Only 66% of discriminatory chemicals discovered in the DDA strategy were discriminatory features in the full scan dataset. Moreover, compared to the deconvoluted MS/MS spectra with coeluted and background ions from the AIF method, the MS/MS spectrum obtained from the targeted MS/MS approach is cleaner and purer. Therefore, an untargeted metabolomics strategy combining the full scan with the targeted MS/MS method could obtain most discriminatory features along with a high quality MS/MS spectrum for discovering the AD biomarkers.
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Affiliation(s)
- Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
| | - Ping-Zu Hsiao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
| | - Yuan-Chih Chen
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
- Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 704, Taiwan
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Su YH, Chang CW, Hsu JY, Li SW, Sung PS, Wang RH, Wu CH, Liao PC. Discovering Hair Biomarkers of Alzheimer's Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics. Molecules 2023; 28:molecules28052166. [PMID: 36903413 PMCID: PMC10004788 DOI: 10.3390/molecules28052166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/20/2023] [Accepted: 02/23/2023] [Indexed: 03/02/2023] Open
Abstract
Hair may be a potential biospecimen to discover biomarkers for Alzheimer's disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.
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Affiliation(s)
- Yu-Hsiang Su
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City 60002, Taiwan
| | - Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Shih-Wen Li
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Pi-Shan Sung
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Ru-Hsueh Wang
- Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Chih-Hsing Wu
- Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
- Correspondence:
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Ran R, Zhong X, Yang Y, Tang X, Shi M, Jiang X, Lin A, Gan X, Yu T, Hu L, Dong X, Han TL. Metabolomic profiling identifies hair as a robust biological sample for identifying women with cervical cancer. MEDICAL ONCOLOGY (NORTHWOOD, LONDON, ENGLAND) 2023; 40:75. [PMID: 36609777 DOI: 10.1007/s12032-022-01848-z] [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: 05/09/2022] [Accepted: 09/09/2022] [Indexed: 01/09/2023]
Abstract
Metabolomics serves as a useful tool for identifying biomarkers of disease and uncovering pathogenic mechanisms. However, most metabolomic studies use biological fluids such as blood and urine as biospecimens, which could be dramatically influenced by daily activities and dietary variation, resulting in measurement fluctuations. In contrast, hair may serve as a robust source of stable longitudinal metabolite information. Here, we conducted a pilot study to investigate the possibility of using hair as a biospecimen for the metabolomic analysis of cervical cancer. Hair, plasma, urine, and cervical tissue samples from cervical cancer and benign tumor patients were collected. Biospecimens were then tested using a gas chromatography-mass spectrometry-based metabolomic platform. The expressions of enzymatic genes related to metabolic changes were validated using qPCR. Statistical analyses were calculated via the R-console platform. Metabolite profiles in both hair and cervical tissue samples were significantly different between cancer and control groups, while no difference was observed in plasma and urine samples. Further analysis showed that most of the altered metabolites in hair were upregulated, and they had a negative correlation with those in the cervical tissue. Eight common metabolites showed an area under the Receiver Operating Characteristic curve greater than 0.95. These metabolites primarily participated in amino acid metabolism, cofactor synthesis, ferroptosis, and glycolysis. The gene expressions (IDH1, OGDH, GLUD1, ENO1, GSS, and GPX4) associated with the shortlisted metabolic pathways were also upregulated. Our study is the first to reveal metabolomic changes of hair in cervical cancer patients and demonstrates the potential for the hair metabolome to be used for biomarker identification in cervical cancer.
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Affiliation(s)
- Rui Ran
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaocui Zhong
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yang Yang
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400716, China
| | - Xianglan Tang
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Manlin Shi
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xingwei Jiang
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Anping Lin
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaoling Gan
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Tinghe Yu
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Lina Hu
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaojing Dong
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Ting-Li Han
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
- Liggins Institute, The University of Auckland, Auckland, 1023, New Zealand.
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Liu Y, Yang Y, Xia YY, de Seymour JV, Zhao DZ, Li YM, Zhang H, Han TL. An Evaluation of Different Digestion Methods for the Quantitation of Inorganic Elements in Human Hair Using ICP-MS. JOURNAL OF ANALYTICAL METHODS IN CHEMISTRY 2022; 2022:5742468. [PMID: 36507105 PMCID: PMC9731750 DOI: 10.1155/2022/5742468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/28/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
The inorganic elements have unique properties in biochemical processes in humans. An increasing number of pathologies have been associated with essential element ions, such as lead, mercury, and cadmium. Hair has become an attractive clinical specimen for studying the longitudinal exposure to elements from the external environment. Inductively coupled plasma-mass spectrometry (ICP-MS) coupled with nitric acid (HNO3) digestion is the most common approach for determining inorganic elements from human hair. This study aims to optimize the digestion method for the absolute quantitation of 52 elements using ICP-MS, for a large cohort study in human hair. Five different HNO3 (65%) digestion methods were investigated and evaluated for their internal standard solution stability, reproducibility, element coverage, and standard solution recovery efficiency, namely, room temperature for 24 h (RT), 90°C for 4 h (T90), ultrasonic-assisted digestion (UltraS), programmed digestion of microwave digestion (MicroD), and ordinary microwave oven digestion (O-MicroD). Our results demonstrated that O-MicroD, MicroD, and RT were the best performing digestion methods for coefficient of variation (CV) scores, coverage, and recovery efficiency, respectively. In particular, the O-MicroD method detected multiple elements in a small quantity of hair (3 mg), with minimum nitric acid usage (200 μl) and a short digestion time (30 min). The O-MicroD method had excellent reproducibility, as demonstrated by a continuous thousand injections of hair samples with three internal standards (CV: 103Rh = 3.59%, 115In = 3.61%, and 209Bi = 6.31%). Future studies of the elemental content of hair should carefully select their digestion method to meet the primary purpose of their study.
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Affiliation(s)
- Yue Liu
- Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Occupational and Environmental Hygiene, School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Yang Yang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mass Spectrometry Center of Maternal-Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Yin-Yin Xia
- Department of Occupational and Environmental Hygiene, School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | | | - De-Zhang Zhao
- College of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Yang-Mei Li
- School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Hua Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mass Spectrometry Center of Maternal-Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Ting-Li Han
- Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Mass Spectrometry Center of Maternal-Fetal Medicine, Chongqing Medical University, Chongqing, China
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Yang Y, Yin Y, Tang X, Xia Y, Zhang J, Yan C, Zhang W, Zhang H, Han TL. Evaluating Different Extraction Approaches for GC-MS Based Metabolomics Analysis of the Giant Pandas' Fur. TOXICS 2022; 10:688. [PMID: 36422896 PMCID: PMC9696619 DOI: 10.3390/toxics10110688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/04/2022] [Accepted: 11/11/2022] [Indexed: 06/16/2023]
Abstract
Giant pandas in zoo captivity are situated in residential areas, where environmental pollutants and anthropogenic factors have an impact on their health. Hair metabolomics has been applied in numerous environmental toxicological studies. Therefore, the panda fur metabolome could be a reliable approach to reflect endogenous and exogenous metabolic changes related to environmental exposure. However, there is no established extraction protocol to study the fur metabolome of pandas. The aim of this research was to optimize the extraction of panda fur metabolome for high-throughput metabolomics analysis using gas chromatography-mass spectrometry. Fur samples were collected from five pandas. Eight different extraction methods were investigated and evaluated for their reproducibility, metabolite coverage, and extraction efficiency, particularly in relation to the biochemical compound classes such as amino acids, tricarboxylic acid cycle derivatives, fatty acids, and secondary metabolites. Our results demonstrated that HCl + ACN were the superior extraction solvents for amino acid and secondary metabolite extraction, and NaOH + MeOH was ideal for fatty acid extraction. Interestingly, the metabolomic analysis of panda fur was capable of discriminating the longitudinal metabolite profile between black and white furs. These extraction protocols can be used in future study protocols for the analysis of the fur metabolome in pandas.
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Affiliation(s)
- Yang Yang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
- Ministry of Education of China International Collaborative Joint Laboratory of Reproduction and Development, Chongqing Medical University, Chongqing 400000, China
- State Key Laboratory of Maternal and Fetal Medicine of Chongqing Municipality, Chongqing Medical University, Chongqing 400000, China
- Institute of Life Sciences, Chongqing Medical University, Chongqing 400000, China
| | | | - Xianglan Tang
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Yinyin Xia
- School of Public Health and Management, Chongqing Medical University, Chongqing 400000, China
| | - Jinya Zhang
- School of Clinical Medicine, Chongqing Medical University, Chongqing 400000, China
| | - Chun Yan
- School of Clinical Medicine, Chongqing Medical University, Chongqing 400000, China
| | - Weixuan Zhang
- School of Clinical Medicine, Chongqing Medical University, Chongqing 400000, China
| | - Hua Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
- Ministry of Education of China International Collaborative Joint Laboratory of Reproduction and Development, Chongqing Medical University, Chongqing 400000, China
- State Key Laboratory of Maternal and Fetal Medicine of Chongqing Municipality, Chongqing Medical University, Chongqing 400000, China
- Institute of Life Sciences, Chongqing Medical University, Chongqing 400000, China
| | - Ting-Li Han
- Ministry of Education of China International Collaborative Joint Laboratory of Reproduction and Development, Chongqing Medical University, Chongqing 400000, China
- State Key Laboratory of Maternal and Fetal Medicine of Chongqing Municipality, Chongqing Medical University, Chongqing 400000, China
- Institute of Life Sciences, Chongqing Medical University, Chongqing 400000, China
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
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Dai J, Boghossian NS, Sarzynski MA, Luo F, Sun X, Li J, Fiehn O, Liu J, Chen L. Metabolome-Wide Associations of Gestational Weight Gain in Pregnant Women with Overweight and Obesity. Metabolites 2022; 12:960. [PMID: 36295862 PMCID: PMC9609233 DOI: 10.3390/metabo12100960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 09/24/2022] [Accepted: 10/05/2022] [Indexed: 11/16/2022] Open
Abstract
Excessive gestational weight gain (GWG) is associated with adverse pregnancy outcomes. This metabolome-wide association study aimed to identify metabolomic markers for GWG. This longitudinal study included 39 Black and White pregnant women with a prepregnancy body mass index (BMI) of ≥ 25 kg/m2. Untargeted metabolomic profiling was performed using fasting plasma samples collected at baseline (mean: 12.1 weeks) and 32 weeks of gestation. The associations of metabolites at each time point and changes between the two time points with GWG were examined by linear and least absolute shrinkage and selection operator (LASSO) regression analyses. Pearson correlations between the identified metabolites and cardiometabolic biomarkers were examined. Of the 769 annotated metabolites, 88 metabolites at 32 weeks were individually associated with GWG, with four (phosphatidylcholine (PC) 34:4, triacylglycerol (TAG) 52:6, arachidonic acid, isoleucine) jointly associated with GWG (area under the receiver operating characteristic curve (AUC) for excessive GWG: 0.80, 95% CI: 0.67, 0.93). No correlations were observed between the 88 metabolites and insulin, C-peptide, and high-sensitivity C-reactive protein at 32 weeks. Twelve metabolites at baseline (AUC for excessive GWG: 0.80, 95% CI: 0.62, 0.99) and three metabolite changes (AUC for excessive GWG: 0.73, 95% CI: 0.44, 1.00) were jointly associated with GWG. We identified novel metabolites in the first and third trimesters associated with GWG, which may shed light on the pathophysiology of GWG.
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Affiliation(s)
- Jin Dai
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA
| | - Nansi S. Boghossian
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Mark A. Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Feng Luo
- School of Computing, Clemson University, Clemson, SC 29634, USA
| | - Xiaoqian Sun
- Department of Mathematical and Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Jian Li
- Department of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA
- School of Nursing, University of California, Los Angeles, CA 90095, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
| | - Jihong Liu
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Liwei Chen
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA
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The Exploration of Fetal Growth Restriction Based on Metabolomics: A Systematic Review. Metabolites 2022; 12:metabo12090860. [PMID: 36144264 PMCID: PMC9501562 DOI: 10.3390/metabo12090860] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/03/2022] [Accepted: 09/04/2022] [Indexed: 11/30/2022] Open
Abstract
Fetal growth restriction (FGR) is a common complication of pregnancy and a significant cause of neonatal morbidity and mortality. The adverse effects of FGR can last throughout the entire lifespan and increase the risks of various diseases in adulthood. However, the etiology and pathogenesis of FGR remain unclear. This study comprehensively reviewed metabolomics studies related with FGR in pregnancy to identify potential metabolic biomarkers and pathways. Relevant articles were searched through two online databases (PubMed and Web of Science) from January 2000 to July 2022. The reported metabolites were systematically compared. Pathway analysis was conducted through the online MetaboAnalyst 5.0 software. For humans, a total of 10 neonatal and 14 maternal studies were included in this review. Several amino acids, such as alanine, valine, and isoleucine, were high frequency metabolites in both neonatal and maternal studies. Meanwhile, several pathways were suggested to be involved in the development of FGR, such as arginine biosynthesis, arginine, and proline metabolism, glyoxylate and dicarboxylate metabolism, and alanine, aspartate, and glutamate metabolism. In addition, we also included 8 animal model studies, in which three frequently reported metabolites (glutamine, phenylalanine, and proline) were also present in human studies. In general, this study summarized several metabolites and metabolic pathways which may help us to better understand the underlying metabolic mechanisms of FGR.
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Xu Y, Cai W, Chen R, Zhang X, Bai Z, Zhang Y, Qin Y, Gu M, Sun Y, Wu Y, Wang Z. Metabolomic Analysis and MRM Verification of Coarse and Fine Skin Tissues of Liaoning Cashmere Goat. Molecules 2022; 27:molecules27175483. [PMID: 36080249 PMCID: PMC9457707 DOI: 10.3390/molecules27175483] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/17/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
One of the critical elements in evaluating the quality of cashmere is its fineness, but we still know little about how it is regulated at the metabolic level. In this paper, we use UHPLC–MS/MS detection and analysis technology to compare the difference in metabolites between coarse cashmere (CT_LCG) and fine cashmere (FT_LCG) skin of Liaoning cashmere goats. According to the data, under positive mode four metabolites were significantly up-regulated and seven were significantly down-regulated. In negative mode, seven metabolites were significantly up-regulated and fourteen metabolites were significantly down-regulated. The two groups’ most significant metabolites, Gly–Phe and taurochenodeoxycholate, may be crucial in controlling cashmere’s growth, development, and fineness. In addition, we enriched six KEGG pathways, of which cholesterol metabolism, primary bile acid biosynthesis, and bile secretion were enriched in positive and negative modes. These findings offer a new research idea for further study into the critical elements influencing cashmere’s fineness.
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21
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Chen X, Zhao X, Jones MB, Harper A, de Seymour JV, Yang Y, Xia Y, Zhang T, Qi H, Gulliver J, Cannon RD, Saffery R, Zhang H, Han TL, Baker PN. The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester. Front Endocrinol (Lausanne) 2022; 13:1060309. [PMID: 36531491 PMCID: PMC9755849 DOI: 10.3389/fendo.2022.1060309] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort. METHODS A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites. RESULTS Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3. CONCLUSIONS This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.
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Affiliation(s)
- Xuyang Chen
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Xue Zhao
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Mary Beatrix Jones
- Department of Statistics, The University of Auckland, Auckland, New Zealand
| | - Alexander Harper
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | | | - Yang Yang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Yinyin Xia
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Ting Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Stomatological Hospital of Chongqing Medical University, Chongqing, China
| | - Hongbo Qi
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - John Gulliver
- Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, United Kingdom
| | - Richard D. Cannon
- Department of Oral Sciences, Sir John Walsh Research Institute, Faculty of Dentistry, University of Otago, Dunedin, New Zealand
| | - Richard Saffery
- Molecular Immunity, Murdoch Children’s Research Institute, Royal Children’s Hospital, Melbourne, VIC, Australia
| | - Hua Zhang
- Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Hua Zhang, ; Ting-Li Han,
| | - Ting-Li Han
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- Department of Obstetrics and Gynaecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Hua Zhang, ; Ting-Li Han,
| | - Philip N. Baker
- College of Life Sciences, University of Leicester, Leicester, United Kingdom
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22
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Chang WCW, Wang PH, Chang CW, Chen YC, Liao PC. Extraction strategies for tackling complete hair metabolome using LC-HRMS-based analysis. Talanta 2021; 223:121708. [PMID: 33303158 DOI: 10.1016/j.talanta.2020.121708] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 09/23/2020] [Accepted: 09/25/2020] [Indexed: 11/30/2022]
Abstract
Over recent years, metabolomics has been featured as the state-of-the-art technology that successfully opens the paths to understanding biological mechanisms and facilitating biomarker discovery. However, the inherent dynamic and sensitive nature of the metabolome have been challenging the accuracy of capturing the timepoints of interest while using biofluids such as urine and blood. Hair has thus emerged as a valuable analytical specimen for the long-term and retrospective determinations. Unfortunately, notwithstanding the apparent interest on global hair metabolomics, very few studies have engaged in the optimisation of the extraction strategy. In this study, we systemically investigated the extraction procedures for hair metabolome using a single factor experimental design. Three pH values (acidic, neutral, and basic) in aqueous solution, six extraction solvents (methanol, acetonitrile, acetone, phosphate-buffered saline, deionised water, and dichloromethane), different compositions of selected solvent mixtures and their sequential extraction, and a series of extraction times (15, 45, 60, 120, 240, and 480 min) were evaluated. The ideal condition for hair extraction is ultrasonic-assisted extraction with methanol:phosphate-buffered saline 50:50 (v/v) under +55 °C for 240 min. This strategy may secure the true composition of the metabolome, maximise the signal abundance, and guarantee a high coverage of wide-range metabolites in a straightforward approach. The optimised extraction strategy was then coupled with structure annotation tools for hair metabolome profiling. After a single RPLC-HRMS run, hair metabolite identification was achieved as the annotations of 171 probable structures and 853 tentative structures as well as the assignments of 414 unequivocal molecular formulae. In conclusion, we established an efficient extraction strategy for untargeted hair metabolomics, which the method is deliverable to any analytical laboratories and the sample can be directly profiled by means of a conventional RPLC-HRMS gradient.
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Affiliation(s)
- William Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 704, Taiwan
| | - Pin-Hsuan Wang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 704, Taiwan
| | - Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 704, Taiwan
| | - Yuan-Chih Chen
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 704, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, 704, Taiwan; Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan.
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23
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Petrick LM, Arora M, Niedzwiecki MM. Minimally Invasive Biospecimen Collection for Exposome Research in Children's Health. Curr Environ Health Rep 2021; 7:198-210. [PMID: 32535858 DOI: 10.1007/s40572-020-00277-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW The advent of low-volume biosampling and novel biomarker matrices offers non- or minimally invasive approaches to sampling in children. These new technologies, combined with advancements in mass spectrometry that provide high sensitivity, robust measurements of low-concentration exposures, facilitate the application of untargeted metabolomics in children's exposome research. Here, we review emerging sampling technologies for alternative biomatrices-dried capillary blood, interstitial fluid, saliva, teeth, and hair-and highlight recent applications of these samplers to drive discovery in population-based exposure research. RECENT FINDINGS Biosampling and biomarker technologies demonstrate potential to directly measure exposures during key developmental time periods. While saliva is the most traditional of the reported biomatrices, each technology has key advantages and disadvantages. For example, hair and teeth provide retrospective analysis of past exposures, and dried capillary blood provides quantitative measurements of systemic exposures that can be more readily compared with traditional venous blood measurements. Importantly, all technologies can or have the potential to be used at home, increasing the convenience and parental support for children's biosampling. This review describes emerging sample collection technologies that hold promise for children's exposome studies. While applications in metabolomics are still limited, these novel matrices are poised to facilitate longitudinal exposome studies to discover key exposures and windows of susceptibility affecting children's health.
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Affiliation(s)
- Lauren M Petrick
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Manish Arora
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Megan M Niedzwiecki
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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24
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Morillon AC, Leite DFB, Yakkundi S, Gethings LA, Thomas G, Baker PN, Kenny LC, English JA, McCarthy FP. Glycerophospholipid and detoxification pathways associated with small for gestation age pathophysiology: discovery metabolomics analysis in the SCOPE cohort. Metabolomics 2021; 17:5. [PMID: 33398476 PMCID: PMC7782411 DOI: 10.1007/s11306-020-01740-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 10/28/2020] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Small for gestational age (SGA) may be associated with neonatal morbidity and mortality. Our understanding of the molecular pathways implicated is poor. OBJECTIVES Our aim was to determine the metabolic pathways involved in the pathophysiology of SGA and examine their variation between maternal biofluid samples. METHODS Plasma (Cork) and urine (Cork, Auckland) samples were collected at 20 weeks' gestation from nulliparous low-risk pregnant women participating in the SCOPE study. Women who delivered an SGA infant (birthweight < 10th percentile) were matched to controls (uncomplicated pregnancies). Metabolomics (urine) and lipidomics (plasma) analyses were performed using ultra performance liquid chromatography-mass spectrometry. Features were ranked based on FDR adjusted p-values from empirical Bayes analysis, and significant features putatively identified. RESULTS Lipidomics plasma analysis revealed that 22 out of the 33 significantly altered lipids annotated were glycerophospholipids; all were detected in higher levels in SGA. Metabolomic analysis identified reduced expression of metabolites associated with detoxification (D-Glucuronic acid, Estriol-16-glucuronide), nutrient absorption and transport (Sulfolithocholic acid) pathways. CONCLUSIONS This study suggests higher levels of glycerophospholipids, and lower levels of specific urine metabolites are implicated in the pathophysiology of SGA. Further research is needed to confirm these findings in independent samples.
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Affiliation(s)
- Aude-Claire Morillon
- INFANT Research Centre, Cork University Hospital, Wilton, Cork, Ireland
- Department of Obstetrics and Gynecology, University College Cork, Cork, Ireland
| | - Debora F B Leite
- Federal University of Pernambuco, Pernambuco, Brazil
- Department of Tocogynecology, Campinas's State University, Sao Paulo, Brazil
| | - Shirish Yakkundi
- INFANT Research Centre, Cork University Hospital, Wilton, Cork, Ireland
- Department of Obstetrics and Gynecology, University College Cork, Cork, Ireland
| | - Lee A Gethings
- Waters Corporation, Wimslow, UK
- Manchester Institute of Biotechnology, Division of Infection and Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | | | - Philip N Baker
- College of Life Sciences, University of Leicester, Leicester, UK
| | - Louise C Kenny
- Department of Women's and Children's Health, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Jane A English
- INFANT Research Centre, Cork University Hospital, Wilton, Cork, Ireland
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
| | - Fergus P McCarthy
- INFANT Research Centre, Cork University Hospital, Wilton, Cork, Ireland.
- Department of Obstetrics and Gynecology, University College Cork, Cork, Ireland.
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25
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Towards Best Practice in Hair Metabolomic Studies: Systematic Investigation on the Impact of Hair Length and Color. Metabolites 2020; 10:metabo10100381. [PMID: 32993123 PMCID: PMC7601250 DOI: 10.3390/metabo10100381] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 09/23/2020] [Accepted: 09/25/2020] [Indexed: 11/16/2022] Open
Abstract
Untargeted metabolomic studies are used for large-scale analysis of endogenous compounds. Due to exceptional long detection windows of incorporated substances in hair, analysis of hair samples for retrospective monitoring of metabolome changes has recently been introduced. However, information on the general behavior of metabolites in hair samples is scarce, hampering correct data interpretation so far. The presented study aimed to investigate endogenous metabolites depending on hair color and along the hair strand and to propose recommendations for best practice in hair metabolomic studies. A metabolite selection was analyzed using untargeted data acquisition in genuine hair samples from different hair colors and after segmentation in 3 cm segments. Significant differences in metabolites among hair colors and segments were found. In conclusion, consideration of hair color and hair segments is necessary for hair metabolomic studies and, subsequently, recommendations for best practice in hair metabolomic studies were proposed.
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26
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Kim S, Jang WJ, Yu H, Kim J, Lee SK, Jeong CH, Lee S. Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis. Int J Mol Sci 2020; 21:E6041. [PMID: 32839415 PMCID: PMC7503996 DOI: 10.3390/ijms21176041] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 12/13/2022] Open
Abstract
Methamphetamine (MA) is a highly addictive central nervous system stimulant. Drug addiction is not a static condition but rather a chronically relapsing disorder. Hair is a valuable and stable specimen for chronic toxicological monitoring as it retains toxicants and metabolites. The primary focus of this study was to discover the metabolic effects encompassing diverse pathological symptoms of MA addiction. Therefore, metabolic alterations were investigated in human hair following heavy MA abuse using both targeted and untargeted mass spectrometry and through integrated network analysis. The statistical analyses (t-test, variable importance on projection score, and receiver-operator characteristic curve) demonstrated that 32 metabolites (in targeted metabolomics) as well as 417 and 224 ion features (in positive and negative ionization modes of untargeted metabolomics, respectively) were critically dysregulated. The network analysis showed that the biosynthesis or metabolism of lipids, such as glycosphingolipids, sphingolipids, glycerophospholipids, and ether lipids, as well as the metabolism of amino acids (glycine, serine and threonine; cysteine and methionine) is affected by heavy MA abuse. These findings reveal crucial metabolic effects caused by MA addiction, with emphasis on the value of human hair as a diagnostic specimen for determining drug addiction, and will aid in identifying robust diagnostic markers and therapeutic targets.
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Affiliation(s)
- Suji Kim
- College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, Korea; (S.K.); (W.-J.J.); (H.Y.)
| | - Won-Jun Jang
- College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, Korea; (S.K.); (W.-J.J.); (H.Y.)
| | - Hyerim Yu
- College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, Korea; (S.K.); (W.-J.J.); (H.Y.)
| | - Jihyun Kim
- National Forensic Service, 10, Ipchun-ro, Wonju, Gangwon-do 26460, Korea; (J.K.); (S.-K.L.)
| | - Sang-Ki Lee
- National Forensic Service, 10, Ipchun-ro, Wonju, Gangwon-do 26460, Korea; (J.K.); (S.-K.L.)
| | - Chul-Ho Jeong
- College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, Korea; (S.K.); (W.-J.J.); (H.Y.)
| | - Sooyeun Lee
- College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, Korea; (S.K.); (W.-J.J.); (H.Y.)
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27
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Bardanzellu F, Puddu M, Fanos V. The Human Breast Milk Metabolome in Preeclampsia, Gestational Diabetes, and Intrauterine Growth Restriction: Implications for Child Growth and Development. J Pediatr 2020; 221S:S20-S28. [PMID: 32482230 DOI: 10.1016/j.jpeds.2020.01.049] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 01/16/2020] [Accepted: 01/21/2020] [Indexed: 02/07/2023]
Affiliation(s)
- Flaminia Bardanzellu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Italy.
| | - Melania Puddu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Italy
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU University of Cagliari, Italy
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28
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Abstract
BACKGROUND The development of liver transplantation (LT) is increasingly being limited by the unavailability of liver grafts. Unique regenerative capacity of liver in response to injuries makes living-donor liver transplantation (LDLT) a feasible strategy to meet clinical demands. Serine hydroxymethyl-transferase 2 (SHMT2) serves as the key enzyme in the biosynthesis of glycine. Glycine affects the activity of mammalian target of rapamycin (mTOR), which is important for cellular growth and proliferation. In this study, the effects of SHMT2 on mouse liver regeneration were investigated using a classical partial hepatectomy (PH) model. METHODS In vivo, PH was performed on mice with or without knockdown of SHMT2. In vitro, SHMT2 was overexpressed in primary hepatocytes, which were cultured in customized Dulbecco's modified eagle media and LY294002 (an Akt inhibitor). Relevant indexes of liver regeneration, cell proliferation, and Akt/mTOR signal pathways were analyzed. RESULTS After PH, the expression levels of SHMT2 fluctuated with time and knockdown of SHMT2 in vivo lowered the regenerative ability of liver, with reduced glycine levels compared to the scramble group. In addition, overexpression of SHMT2 in hepatocytes boosted glycine production while enhancing Akt/mTOR pathway activity. These results were validated by the application of LY294002 in vitro. CONCLUSIONS SHMT2 can contribute to liver regeneration after PH, and this is likely related to the activation of Akt/mTOR signaling pathway by its metabolic product, glycine, in hepatocytes. These results might have therapeutic implications for the prognosis of patients undergoing hepatic resection or transplantation.
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29
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Leite DFB, Morillon AC, Melo Júnior EF, Souza RT, McCarthy FP, Khashan A, Baker P, Kenny LC, Cecatti JG. Examining the predictive accuracy of metabolomics for small-for-gestational-age babies: a systematic review. BMJ Open 2019; 9:e031238. [PMID: 31401613 PMCID: PMC6701563 DOI: 10.1136/bmjopen-2019-031238] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 07/13/2019] [Accepted: 07/17/2019] [Indexed: 01/23/2023] Open
Abstract
INTRODUCTION To date, there is no robust enough test to predict small-for-gestational-age (SGA) infants, who are at increased lifelong risk of morbidity and mortality. OBJECTIVE To determine the accuracy of metabolomics in predicting SGA babies and elucidate which metabolites are predictive of this condition. DATA SOURCES Two independent researchers explored 11 electronic databases and grey literature in February 2018 and November 2018, covering publications from 1998 to 2018. Both researchers performed data extraction and quality assessment independently. A third researcher resolved discrepancies. STUDY ELIGIBILITY CRITERIA Cohort or nested case-control studies were included which investigated pregnant women and performed metabolomics analysis to evaluate SGA infants. The primary outcome was birth weight <10th centile-as a surrogate for fetal growth restriction-by population-based or customised charts. STUDY APPRAISAL AND SYNTHESIS METHODS Two independent researchers extracted data on study design, obstetric variables and sampling, metabolomics technique, chemical class of metabolites, and prediction accuracy measures. Authors were contacted to provide additional data when necessary. RESULTS A total of 9181 references were retrieved. Of these, 273 were duplicate, 8760 were removed by title or abstract, and 133 were excluded by full-text content. Thus, 15 studies were included. Only two studies used the fifth centile as a cut-off, and most reports sampled second-trimester pregnant women. Liquid chromatography coupled to mass spectrometry was the most common metabolomics approach. Untargeted studies in the second trimester provided the largest number of predictive metabolites, using maternal blood or hair. Fatty acids, phosphosphingolipids and amino acids were the most prevalent predictive chemical subclasses. CONCLUSIONS AND IMPLICATIONS Significant heterogeneity of participant characteristics and methods employed among studies precluded a meta-analysis. Compounds related to lipid metabolism should be validated up to the second trimester in different settings. PROSPERO REGISTRATION NUMBER CRD42018089985.
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Affiliation(s)
- Debora Farias Batista Leite
- Department of Tocogynecology, Campinas' State University, Campinas, Brazil
- Department of Maternal and Child Health, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil
| | - Aude-Claire Morillon
- Irish Centre for Fetal and Neonatal Translational Research (INFANT), University College Cork National University of Ireland, Cork, Ireland
| | | | - Renato T Souza
- Obstetrics and Gynecology, Universidade Estadual de Campinas, Campinas, Brazil
| | - Fergus P McCarthy
- Department of Gynaecology and Obstetrics, St Thomas Hospital, Cork, UK
| | - Ali Khashan
- Department of Epidemiology and Public Health, University College Cork, Cork, Ireland
| | - Philip Baker
- College of Medicine, University of Leicester, Leicester, UK
| | - Louise C Kenny
- Department of Women's and Children's Health, University of Liverpool School of Life Sciences, Liverpool, UK
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Deng L, Ismond K, Liu Z, Constable J, Wang H, Alatise OI, Weiser MR, Kingham TP, Chang D. Urinary Metabolomics to Identify a Unique Biomarker Panel for Detecting Colorectal Cancer: A Multicenter Study. Cancer Epidemiol Biomarkers Prev 2019; 28:1283-1291. [PMID: 31151939 PMCID: PMC6677589 DOI: 10.1158/1055-9965.epi-18-1291] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 03/29/2019] [Accepted: 05/28/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Population-based screening programs are credited with earlier colorectal cancer diagnoses and treatment initiation, which reduce mortality rates and improve patient health outcomes. However, recommended screening methods are unsatisfactory as they are invasive, are resource intensive, suffer from low uptake, or have poor diagnostic performance. Our goal was to identify a urine metabolomic-based biomarker panel for the detection of colorectal cancer that has the potential for global population-based screening. METHODS Prospective urine samples were collected from study participants. Based upon colonoscopy and histopathology results, 342 participants (colorectal cancer, 171; healthy controls, 171) from two study sites (Canada, United States) were included in the analyses. Targeted liquid chromatography-mass spectrometry (LC-MS) was performed to quantify 140 highly valuable metabolites in each urine sample. Potential biomarkers for colorectal cancer were identified by comparing the metabolomic profiles from colorectal cancer versus controls. Multiple models were constructed leading to a good separation of colorectal cancer from controls. RESULTS A panel of 17 metabolites was identified as possible biomarkers for colorectal cancer. Using only two of the selected metabolites, namely diacetylspermine and kynurenine, a predictor for detecting colorectal cancer was developed with an AUC of 0.864, a specificity of 80.0%, and a sensitivity of 80.0%. CONCLUSIONS We present a potentially "universal" metabolomic biomarker panel for colorectal cancer independent of cohort clinical features based on a North American population. Further research is needed to confirm the utility of the profile in a prospective, population-based colorectal cancer screening trial. IMPACT A urinary metabolomic biomarker panel was identified for colorectal cancer with the potential of clinical application.
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Affiliation(s)
- Lu Deng
- Metabolomic Technologies Inc., Edmonton, Alberta, Canada.
| | - Kathleen Ismond
- Metabolomic Technologies Inc., Edmonton, Alberta, Canada
- Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Zhengjun Liu
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Jeremy Constable
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Haili Wang
- Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Olusegun I Alatise
- Department of Surgery, Obafemi Awolowo University and Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria
| | - Martin R Weiser
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - T P Kingham
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - David Chang
- Metabolomic Technologies Inc., Edmonton, Alberta, Canada
- Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
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Eshima J, Ong S, Davis TJ, Miranda C, Krishnamurthy D, Nachtsheim A, Stufken J, Plaisier C, Fricks J, Bean HD, Smith BS. Monitoring changes in the healthy female metabolome across the menstrual cycle using GC × GC-TOFMS. J Chromatogr B Analyt Technol Biomed Life Sci 2019; 1121:48-57. [DOI: 10.1016/j.jchromb.2019.04.046] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 04/16/2019] [Accepted: 04/23/2019] [Indexed: 01/22/2023]
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Hair Metabolomics in Animal Studies and Clinical Settings. Molecules 2019; 24:molecules24122195. [PMID: 31212725 PMCID: PMC6630908 DOI: 10.3390/molecules24122195] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 06/11/2019] [Accepted: 06/11/2019] [Indexed: 12/12/2022] Open
Abstract
Metabolomics is a powerful tool used to understand comprehensive changes in the metabolic response and to study the phenotype of an organism by instrumental analysis. It most commonly involves mass spectrometry followed by data mining and metabolite assignment. For the last few decades, hair has been used as a valuable analytical sample to investigate retrospective xenobiotic exposure as it provides a wider window of detection than other biological samples such as saliva, plasma, and urine. Hair contains functional metabolomes such as amino acids and lipids. Moreover, segmental analysis of hair based on its growth rate can provide information on metabolic changes over time. Therefore, it has great potential as a metabolomics sample to monitor chronic diseases, including drug addiction or abnormal conditions. In the current review, the latest applications of hair metabolomics in animal studies and clinical settings are highlighted. For this purpose, we review and discuss the characteristics of hair as a metabolomics sample, the analytical techniques employed in hair metabolomics and the consequence of hair metabolome alterations in recent studies. Through this, the value of hair as an alternative biological sample in metabolomics is highlighted.
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(Un)targeted hair metabolomics: first considerations and systematic evaluation on the impact of sample preparation. Anal Bioanal Chem 2019; 411:3963-3977. [DOI: 10.1007/s00216-019-01873-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 04/17/2019] [Accepted: 04/26/2019] [Indexed: 12/31/2022]
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Miranda J, Simões RV, Paules C, Cañueto D, Pardo-Cea MA, García-Martín ML, Crovetto F, Fuertes-Martin R, Domenech M, Gómez-Roig MD, Eixarch E, Estruch R, Hansson SR, Amigó N, Cañellas N, Crispi F, Gratacós E. Metabolic profiling and targeted lipidomics reveals a disturbed lipid profile in mothers and fetuses with intrauterine growth restriction. Sci Rep 2018; 8:13614. [PMID: 30206284 PMCID: PMC6134091 DOI: 10.1038/s41598-018-31832-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 08/13/2018] [Indexed: 12/11/2022] Open
Abstract
Fetal growth may be impaired by poor placental function or maternal conditions, each of which can influence the transfer of nutrients and oxygen from the mother to the developing fetus. Large-scale studies of metabolites (metabolomics) are key to understand cellular metabolism and pathophysiology of human conditions. Herein, maternal and cord blood plasma samples were used for NMR-based metabolic fingerprinting and profiling, including analysis of the enrichment of circulating lipid classes and subclasses, as well as the number of sub-fraction particles and their size. Changes in phosphatidylcholines and glycoproteins were prominent in growth-restricted fetuses indicating significant alterations in their abundance and biophysical properties. Lipoprotein profiles showed significantly lower plasma concentrations of cholesterol-intermediate density lipoprotein (IDL), triglycerides-IDL and high-density lipoprotein (HDL) in mothers of growth-restricted fetuses compared to controls (p < 0.05). In contrast, growth-restricted fetuses had significantly higher plasma concentrations of cholesterol and triglycerides transporting lipoproteins [LDL, IDL, and VLDL, (p < 0.005; all)], as well as increased VLDL particle types (large, medium and small). Significant changes in plasma concentrations of formate, histidine, isoleucine and citrate in growth-restricted fetuses were also observed. Comprehensive metabolic profiling reveals that both, mother and fetuses of pregnancies complicated with fetal growth restriction have a substantial disruption in lipid metabolism.
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Affiliation(s)
- Jezid Miranda
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Rui V Simões
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Cristina Paules
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Daniel Cañueto
- Metabolomics Platform, IISPV, DEEiA, Universidad Rovira i Virgili, Tarragona, Spain
| | | | - María L García-Martín
- BIONAND, Andalusian Centre for Nanomedicine and Biotechnology, Junta de Andalucía, Universidad de Málaga, Málaga, Spain
| | - Francesca Crovetto
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Rocio Fuertes-Martin
- Metabolomics Platform, IISPV, DEEiA, Universidad Rovira i Virgili, Tarragona, Spain
- Biosfer Teslab, Reus, Spain
| | - Monica Domenech
- Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - María D Gómez-Roig
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Elisenda Eixarch
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Ramon Estruch
- Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Stefan R Hansson
- Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Lund University, Sweden; Skåne University Hospital, Lund, Sweden
| | | | - Nicolau Cañellas
- Metabolomics Platform, IISPV, DEEiA, Universidad Rovira i Virgili, Tarragona, Spain
- CIBERDEM, Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders, Madrid, Spain
| | - Fatima Crispi
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.
| | - Eduard Gratacós
- Fetal i+D Fetal Medicine Research, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clinic de Ginecologia, Obstetricia i Neonatologia, IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
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Abstract
Once based mainly in paediatrics, inborn errors of metabolism (IEM), or inherited metabolic disorders (IMD) represent a growing adult medicine specialty. Individually rare these conditions have currently, a collective estimated prevalence of >1:800. Diagnosis has improved through expanded newborn screening programs, identification of potentially affected family members and greater awareness of symptomatic presentations in adolescence and in adulthood. Better survival and reduced mortality from previously lethal and debilitating conditions means greater numbers transition to adulthood. Pregnancy, once contraindicated for many, may represent a challenging but successful outcome. Successful pregnancies are now reported in a wide range of IEM. Significant challenges remain, given the biological stresses of pregnancy, parturition and the puerperium. Known diagnoses allow preventive and pre-emptive management. Unrecognized metabolic disorders especially, remain a preventable cause of maternal and neonatal mortality and morbidity. Increased awareness of these conditions amongst all clinicians is essential to expedite diagnosis and manage appropriately. This review aims to describe normal adaptations to pregnancy and discuss how various types of IEM may be affected. Relevant translational research and clinical experience will be reviewed with practical management aspects cited. Based on current literature, the impact of maternal IEM on mother and/or foetus, as well as how foetal IEM may affect the mother, will be considered. Insights gained from these rare disorders to more common conditions will be explored. Gaps in the literature, unanswered questions and steps to enhance further knowledge and systematically capture experience, such as establishment of an IEM-pregnancy registry, will be summarized.
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Affiliation(s)
- Gisela Wilcox
- School of Medical Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester, UK.
- The Mark Holland Metabolic Unit, Salford Royal Foundation NHS Trust, Salford, Greater Manchester, M6 8HD, UK.
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