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Nam H, Kim D, Jin X, Park S. Metabolic determinants of leukemia onset variability in genetically homogeneous AKR mice. Biochem Biophys Res Commun 2024; 725:150257. [PMID: 38901226 DOI: 10.1016/j.bbrc.2024.150257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 06/22/2024]
Abstract
Leukemia is a complex disease shaped by the intricate interplay of genetic and environmental factors. Given our preliminary data showing different leukemia incidence in genetically homogenous AKR mice harboring the spontaneous leukemia-inducing mutation Rmcfs, we sought to unravel the role of metabolites and gut microbiota in the leukemia penetrance. Our metabolomic analysis revealed distinct serum metabolite profiles between mice that developed leukemia and those that did not. We discovered that linoleic acid (LA), an essential ω-6 polyunsaturated fatty acid, was significantly decreased in the leukemia group, with the lower levels observed starting from 25 weeks before the onset. A predictive model based on LA levels demonstrated high accuracy in predicting leukemia development (area under curve 0.82). In vitro experiment confirmed LA's cytotoxic effects against leukemia cells, and in vivo study showed that a diet enriched with LA prolonged survival in AKR mice. Furthermore, gut microbiome analysis identified specific Lachnospiraceae species, that affect host lipid metabolism, are exclusively present in the leukemia group, suggesting their potential influence on LA metabolism and leukemia development. These findings shed light on the complex relationship between metabolites, gut microbiota, and leukemia development, providing valuable insights into the role of non-genetic factors in leukemia penetrance and potential strategies for leukemia prevention.
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Affiliation(s)
- Hoonsik Nam
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Doyeon Kim
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Xing Jin
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea.
| | - Sunghyouk Park
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea.
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2
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González-Domínguez Á, González-Domínguez R. How far are we from reliable metabolomics-based biomarkers? The often-overlooked importance of addressing inter-individual variability factors. Biochim Biophys Acta Mol Basis Dis 2024; 1870:166910. [PMID: 37802155 DOI: 10.1016/j.bbadis.2023.166910] [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: 08/08/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/08/2023]
Abstract
Metabolomics has proven great potential to unravel the molecular basis of diseases. However, most attempts aimed at identifying reliable metabolomics-based biomarkers for diagnosis, prediction, and prognosis of diseases have repeatedly failed because of inconsistent results and unsatisfactory replication in independent cohorts. This review article explores the possible causes behind this reproducibility crisis, with special focus on the role that inter-individual variability factors play in modulating the susceptibility to disease development. Furthermore, we provide future perspectives on the applicability of metabolomics in biomedical research and its translatability into clinical practice.
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Affiliation(s)
- Álvaro González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, 11009 Cádiz, Spain
| | - Raúl González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, 11009 Cádiz, Spain.
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3
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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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4
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Lista S, González-Domínguez R, López-Ortiz S, González-Domínguez Á, Menéndez H, Martín-Hernández J, Lucia A, Emanuele E, Centonze D, Imbimbo BP, Triaca V, Lionetto L, Simmaco M, Cuperlovic-Culf M, Mill J, Li L, Mapstone M, Santos-Lozano A, Nisticò R. Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives. Ageing Res Rev 2023; 89:101987. [PMID: 37343679 DOI: 10.1016/j.arr.2023.101987] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/12/2023] [Accepted: 06/15/2023] [Indexed: 06/23/2023]
Abstract
Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.
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Affiliation(s)
- Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain.
| | - Raúl González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz, Spain
| | - Susana López-Ortiz
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Álvaro González-Domínguez
- Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz, Spain
| | - Héctor Menéndez
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Juan Martín-Hernández
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Alejandro Lucia
- Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid, Spain; Faculty of Sport Sciences, European University of Madrid, Villaviciosa de Odón, Madrid, Spain; CIBER of Frailty and Healthy Ageing (CIBERFES), Madrid, Spain
| | | | - Diego Centonze
- Department of Systems Medicine, Tor Vergata University, Rome, Italy; Unit of Neurology, IRCCS Neuromed, Pozzilli, IS, Italy
| | - Bruno P Imbimbo
- Department of Research and Development, Chiesi Farmaceutici, Parma, Italy
| | - Viviana Triaca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Rome, Italy
| | - Luana Lionetto
- Clinical Biochemistry, Mass Spectrometry Section, Sant'Andrea University Hospital, Rome, Italy; Department of Neuroscience, Mental Health and Sensory Organs, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Maurizio Simmaco
- Clinical Biochemistry, Mass Spectrometry Section, Sant'Andrea University Hospital, Rome, Italy; Department of Neuroscience, Mental Health and Sensory Organs, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Miroslava Cuperlovic-Culf
- Digital Technologies Research Center, National Research Council, Ottawa, Canada; Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON, Canada
| | - Jericha Mill
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA; School of Pharmacy, University of Wisconsin-Madison, Madison, WI, USA
| | - Mark Mapstone
- Department of Neurology, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Alejandro Santos-Lozano
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain; Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid, Spain
| | - Robert Nisticò
- School of Pharmacy, University of Rome "Tor Vergata", Rome, Italy; Laboratory of Pharmacology of Synaptic Plasticity, EBRI Rita Levi-Montalcini Foundation, Rome, Italy
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5
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Green RE, Lord J, Scelsi MA, Xu J, Wong A, Naomi-James S, Handy A, Gilchrist L, Williams DM, Parker TD, Lane CA, Malone IB, Cash DM, Sudre CH, Coath W, Thomas DL, Keuss S, Dobson R, Legido-Quigley C, Fox NC, Schott JM, Richards M, Proitsi P. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease. Alzheimers Res Ther 2023; 15:38. [PMID: 36814324 PMCID: PMC9945600 DOI: 10.1186/s13195-023-01184-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 02/08/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß = - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß = - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.
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Affiliation(s)
- Rebecca E Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Marzia A Scelsi
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,Institute of Pharmaceutical Science, King's College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK
| | - Sarah Naomi-James
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Alex Handy
- University College London, Institute of Health Informatics, London, UK
| | - Lachlan Gilchrist
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Department of Brain Sciences, Imperial College London, London, W12 0NN, UK.,UK DRI Centre for Care Research and Technology, Imperial College London, London, W12 0BZ, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Carole H Sudre
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK.,MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK.,University College London, Institute of Health Informatics, London, UK.,Health Data Research UK London, University College London, London, UK.,NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK.,Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.
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6
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Hristova J, Svinarov D. Enhancing precision medicine through clinical mass spectrometry platform. BIOTECHNOL BIOTEC EQ 2022. [DOI: 10.1080/13102818.2022.2053342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Affiliation(s)
- Julieta Hristova
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
| | - Dobrin Svinarov
- Alexander University Hospital, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
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7
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Hertzog A, Selvanathan A, Devanapalli B, Ho G, Bhattacharya K, Tolun AA. A narrative review of metabolomics in the era of "-omics": integration into clinical practice for inborn errors of metabolism. Transl Pediatr 2022; 11:1704-1716. [PMID: 36345452 PMCID: PMC9636448 DOI: 10.21037/tp-22-105] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 08/23/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND OBJECTIVE Traditional targeted metabolomic investigations identify a pre-defined list of analytes in samples and have been widely used for decades in the diagnosis and monitoring of inborn errors of metabolism (IEMs). Recent technological advances have resulted in the development and maturation of untargeted metabolomics: a holistic, unbiased, analytical approach to detecting metabolic disturbances in human disease. We aim to provide a summary of untargeted metabolomics [focusing on tandem mass spectrometry (MS-MS)] and its application in the field of IEMs. METHODS Data for this review was identified through a literature search using PubMed, Google Scholar, and personal repositories of articles collected by the authors. Findings are presented within several sections describing the metabolome, the current use of targeted metabolomics in the diagnostic pathway of patients with IEMs, the more recent integration of untargeted metabolomics into clinical care, and the limitations of this newly employed analytical technique. KEY CONTENT AND FINDINGS Untargeted metabolomic investigations are increasingly utilized in screening for rare disorders, improving understanding of cellular and subcellular physiology, discovering novel biomarkers, monitoring therapy, and functionally validating genomic variants. Although the untargeted metabolomic approach has some limitations, this "next generation metabolic screening" platform is becoming increasingly affordable and accessible. CONCLUSIONS When used in conjunction with genomics and the other promising "-omic" technologies, untargeted metabolomics has the potential to revolutionize the diagnostics of IEMs (and other rare disorders), improving both clinical and health economic outcomes.
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Affiliation(s)
- Ashley Hertzog
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Arthavan Selvanathan
- Genetic Metabolic Disorders Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Beena Devanapalli
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Gladys Ho
- Sydney Genome Diagnostics, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Kaustuv Bhattacharya
- Genetic Metabolic Disorders Service, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Adviye Ayper Tolun
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
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8
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Zhu Z, Camargo CA, Raita Y, Freishtat RJ, Fujiogi M, Hahn A, Mansbach JM, Spergel JM, Pérez-Losada M, Hasegawa K. Nasopharyngeal airway dual-transcriptome of infants with severe bronchiolitis and risk of childhood asthma: A multicenter prospective study. J Allergy Clin Immunol 2022; 150:806-816. [PMID: 35483507 PMCID: PMC9547815 DOI: 10.1016/j.jaci.2022.04.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 03/26/2022] [Accepted: 04/08/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND Severe bronchiolitis (ie, bronchiolitis requiring hospitalization) during infancy is a major risk factor for childhood asthma. However, the exact mechanism linking these common conditions remains unclear. OBJECTIVES This study sought to examine the integrated role of airway microbiome (both taxonomy and function) and host response in asthma development in this high-risk population. METHODS This multicenter prospective cohort study of 244 infants with severe bronchiolitis (median age, 3 months) examined the infants' nasopharyngeal metatranscriptomes (microbiomes) and transcriptomes (hosts), as well as metabolomes at hospitalization. The longitudinal relationships investigated include (1) major bacterial species (Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis), (2) microbial function, and (3) host response with risks of developing asthma by age 6 years. RESULTS First, the abundance of S pneumoniae was associated with greater risks of asthma (P = .01), particularly in infants with nonrhinovirus infection (Pinteraction = .04). Second, of 328 microbial functional pathways that are differentially enriched by asthma development, the top pathways (eg, fatty acid and glycolysis pathways; false discovery rate [FDR] < 1 × 10-12) were driven by these 3 major species (eg, positive association of S pneumoniae with glycolysis; FDR < 0.001). These microbial functional pathways were validated with the parallel metabolome data. Third, 104 transcriptome pathways were differentially enriched (FDR < .05)-for example, downregulated interferon-α and -γ and upregulated T-cell activation pathways. S pneumoniae was associated with most differentially expressed transcripts (eg, DAGLB; FDR < 0.05). CONCLUSIONS By applying metatranscriptomic, transcriptomic, and metabolomic approaches to a multicenter cohort of infants with bronchiolitis, this study found an interplay between major bacterial species, their function, and host response in the airway, and their longitudinal relationship with asthma development.
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Affiliation(s)
- Zhaozhong Zhu
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass.
| | - Carlos A Camargo
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass
| | - Yoshihiko Raita
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass
| | - Robert J Freishtat
- Center for Genetic Medicine Research, Children's National Hospital, Washington, DC; Division of Emergency Medicine, Children's National Hospital, Washington, DC; Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC
| | - Michimasa Fujiogi
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass
| | - Andrea Hahn
- Center for Genetic Medicine Research, Children's National Hospital, Washington, DC; Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC; Division of Infectious Diseases, Children's National Hospital, Washington, DC
| | - Jonathan M Mansbach
- Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, Mass
| | - Jonathan M Spergel
- Division of Allergy and Immunology, Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, Pa
| | - Marcos Pérez-Losada
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, George Washington University School of Medicine and Health Sciences, Washington, DC; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão, Portugal
| | - Kohei Hasegawa
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass
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9
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Castellano-Escuder P, González-Domínguez R, Vaillant MF, Casas-Agustench P, Hidalgo-Liberona N, Estanyol-Torres N, Wilson T, Beckmann M, Lloyd AJ, Oberli M, Moinard C, Pison C, Borel JC, Joyeux-Faure M, Sicard M, Artemova S, Terrisse H, Dancer P, Draper J, Sánchez-Pla A, Andres-Lacueva C. Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome: Results From a European Two-Center Study. Front Nutr 2022; 9:880770. [PMID: 35757242 PMCID: PMC9219016 DOI: 10.3389/fnut.2022.880770] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Background Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits. Objectives The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010). Design We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time. Results Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0). Conclusion We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits. Clinical Trail Registration www.ClinicalTrials.gov, Identifier: NCT03169088.
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Affiliation(s)
- Pol Castellano-Escuder
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain.,Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Raúl González-Domínguez
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Marie-France Vaillant
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,Service Hospitalier Universitaire Pneumologie Physiologie, CHU Grenoble Alpes, Grenoble, France
| | - Patricia Casas-Agustench
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Nicole Hidalgo-Liberona
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Núria Estanyol-Torres
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
| | - Thomas Wilson
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Amanda J Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | | | - Christophe Moinard
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France
| | - Christophe Pison
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,Service Hospitalier Universitaire Pneumologie Physiologie, CHU Grenoble Alpes, Grenoble, France.,Université Grenoble Alpes, Grenoble, France
| | - Jean-Christian Borel
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France
| | | | | | | | - Hugo Terrisse
- Laboratory of Fundamental and Applied Bioenergetics, Inserm1055, Grenoble, France.,TIMC-MESP Laboratory, University of Grenoble Alpes, Grenoble, France
| | | | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Alex Sánchez-Pla
- CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain.,Statistics and Bioinformatics Research Group, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Cristina Andres-Lacueva
- Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XIA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, Spain
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10
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Green R, Lord J, Xu J, Maddock J, Kim M, Dobson R, Legido-Quigley C, Wong A, Richards M, Proitsi P. Metabolic correlates of late midlife cognitive outcomes: findings from the 1946 British Birth Cohort. Brain Commun 2021; 4:fcab291. [PMID: 35187482 PMCID: PMC8853724 DOI: 10.1093/braincomms/fcab291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 09/17/2021] [Accepted: 12/10/2021] [Indexed: 11/14/2022] Open
Abstract
Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanisms relevant to early dementia. Here, we systematically explored the metabolic correlates of cognitive outcomes measured across the seventh decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites profiled by liquid chromatography-mass spectrometry (age 60-64), we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N = 1740). We additionally conducted pathway and network analyses to allow for greater insight into potential mechanisms, and sequentially adjusted for life course factors across four models, including sex and blood collection (Model 1), Model 1 + body mass index and lipid medication (Model 2), Model 2 + social factors and childhood cognition (Model 3) and Model 3 + lifestyle influences (Model 4). After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules were associated with cognitive outcomes. Of the 155, 35 metabolites were highly connected in their network module (termed 'hub' metabolites), presenting as promising marker candidates. Notably, we report relationships between a module comprised of acylcarnitines and processing speed which remained robust to life course adjustment, revealing palmitoylcarnitine (C16) as a hub (Model 4: β = -0.10, 95% confidence interval = -0.15 to -0.052, P = 5.99 × 10-5). Most associations were sensitive to adjustment for social factors and childhood cognition; in the final model, four metabolites remained after multiple testing correction, and 80 at P < 0.05. Two modules demonstrated associations that were partly or largely attenuated by life course factors: one enriched in modified nucleosides and amino acids (overall attenuation = 39.2-55.5%), and another in vitamin A and C metabolites (overall attenuation = 68.6-92.6%). Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors, particularly childhood cognition and education. Using a large birth cohort study with information across the life course, we highlighted potential metabolic mechanisms associated with cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.
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Affiliation(s)
- Rebecca Green
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Institute of Pharmaceutical Science, King’s College London, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Min Kim
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
- Health Data Research UK London, University College London, London, UK
- NIHR Biomedical Research Centre at University College London, Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King’s College London, London, UK
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
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11
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González-Domínguez R, Castellano-Escuder P, Carmona F, Lefèvre-Arbogast S, Low DY, Du Preez A, Ruigrok SR, Manach C, Urpi-Sarda M, Korosi A, Lucassen PJ, Aigner L, Pallàs M, Thuret S, Samieri C, Sánchez-Pla A, Andres-Lacueva C. Food and Microbiota Metabolites Associate with Cognitive Decline in Older Subjects: A 12-Year Prospective Study. Mol Nutr Food Res 2021; 65:e2100606. [PMID: 34661340 DOI: 10.1002/mnfr.202100606] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 10/11/2021] [Indexed: 12/17/2022]
Abstract
SCOPE Diet is considered an important modulator of cognitive decline and dementia, but the available evidence is, however, still fragmented and often inconsistent. METHODS AND RESULTS The article studies the long-term prospective Three-City Cohort, which consists of two separate nested case-control sample sets from different geographic regions (Bordeaux, n = 418; Dijon, n = 424). Cognitive decline is evaluated through five neuropsychological tests (Mini-Mental State Examination, Benton Visual Retention Test, Isaac's Set Test, Trail-Making Test part A, and Trail-Making Test part B). The food-related and microbiota-derived circulating metabolome is studied in participants free of dementia at baseline, by subjecting serum samples to large-scale quantitative metabolomics analysis. A protective association is found between metabolites derived from cocoa, coffee, mushrooms, red wine, the microbial metabolism of polyphenol-rich foods, and cognitive decline, as well as a negative association with metabolites related to unhealthy dietary components, such as artificial sweeteners and alcohol. CONCLUSION These results provide insight into the early metabolic events that are associated with the later risk to develop cognitive decline within the crosstalk between diet, gut microbiota and the endogenous metabolism, which can help identify potential targets for preventive and therapeutic strategies to preserve cognitive health.
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Affiliation(s)
- Raúl González-Domínguez
- Biomarkers and Nutrimetabolomics Laboratory, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain
| | - Pol Castellano-Escuder
- Biomarkers and Nutrimetabolomics Laboratory, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain.,Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Spain
| | - Francisco Carmona
- CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain.,Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Spain
| | - Sophie Lefèvre-Arbogast
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, F-33000, France
| | - Dorrain Y Low
- Université Clermont Auvergne, INRAE, UNH, Clermont, Ferrand, F-63000, France
| | - Andrea Du Preez
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9NU, UK
| | - Silvie R Ruigrok
- Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam, 1098 XH, The Netherlands
| | - Claudine Manach
- Université Clermont Auvergne, INRAE, UNH, Clermont, Ferrand, F-63000, France
| | - Mireia Urpi-Sarda
- Biomarkers and Nutrimetabolomics Laboratory, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain
| | - Aniko Korosi
- Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam, 1098 XH, The Netherlands
| | - Paul J Lucassen
- Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam, 1098 XH, The Netherlands
| | - Ludwig Aigner
- Institute of Molecular Regenerative Medicine, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, 5020, Austria
| | - Mercè Pallàs
- Pharmacology Section, Department of Pharmacology, Toxicology and Medicinal Chemistry, Faculty of Pharmacy and Food Sciences, and Institut de Neurociències, University of Barcelona, Barcelona, 08028, Spain
| | - Sandrine Thuret
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9NU, UK
| | - Cécilia Samieri
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, F-33000, France
| | - Alex Sánchez-Pla
- CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain.,Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Spain
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERfes), Instituto de Salud Carlos III, Madrid, 28029, Spain
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12
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Sarandi E, Kruger Krasagakis S, Tsoukalas D, Rudofsky G, Tsatsakis A. A Clinical Trial for the Identification of Metabolic Biomarkers in Hashimoto's Thyroiditis and in Psoriasis: Study Protocol. PATHOPHYSIOLOGY 2021; 28:291-306. [PMID: 35366263 PMCID: PMC8830459 DOI: 10.3390/pathophysiology28020019] [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: 05/13/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 11/17/2022] Open
Abstract
Hashimoto's thyroiditis and psoriasis are inflammatory disorders that significantly impact patients' quality of life, stressing the need for novel biomarkers of early diagnosis. This randomized clinical trial (NCT04693936) aims to identify Hashimoto's thyroiditis' and psoriasis' metabolic biomarkers and to investigate the effect of environmental factors on the disease-related metabolic imprint and quality of life. Patients with Hashimoto's thyroiditis, patients with psoriasis, and healthy individuals aged 18-60 will be recruited, enrolled according to eligibility criteria (medical history, clinical thyroid markers and the PASI score) and randomized to two groups. The intervention group will receive a combination of nutraceuticals for 6 months as part of a Mediterranean diet, and the control group will follow their usual diet. Data will be collected at baseline and the end of the study, including metabolite levels, lifestyle and anthropometric measurements, adherence to the Mediterranean diet (through the Mediterranean Diet Score) and disease-specific quality of life (through the Thyroid Patient Report Outcome for Hashimoto's group, and the Dermatology Life Quality Index for the psoriasis group). This study will investigate metabolic biomarkers and related changes in Hashimoto's thyroiditis and psoriasis and evaluate the association of metabolic changes with dietary factors and quality of life.
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Affiliation(s)
- Evangelia Sarandi
- Laboratory of Toxicology and Forensic Sciences, Medical School, University of Crete, 71003 Heraklion, Greece;
- Metabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases, 10674 Athens, Greece;
| | | | - Dimitris Tsoukalas
- Metabolomic Medicine, Health Clinics for Autoimmune and Chronic Diseases, 10674 Athens, Greece;
- European Institute of Nutritional Medicine, 00198 Rome, Italy
| | - Gottfried Rudofsky
- Clinic of Endocrinology and Metabolic Disorders, Cantonal Hospital Olten, Baslerstrasse 150, 4600 Olten, Switzerland;
| | - Aristides Tsatsakis
- Laboratory of Toxicology and Forensic Sciences, Medical School, University of Crete, 71003 Heraklion, Greece;
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13
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Integrated multi-omics uncovers reliable potential biomarkers and adverse effects of zinc deficiency. Clin Nutr 2021; 40:2683-2696. [PMID: 33933734 DOI: 10.1016/j.clnu.2021.03.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/18/2021] [Accepted: 03/12/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND Zinc deficiency is a worldwide public health problem. Currently, there are no established biomarkers available for the accurate diagnosis of zinc-deficiency in individuals. Additionally, a comprehensive view of the adverse effects of zinc deficiency is lacking. Our aim was to identify superior biomarkers of zinc deficiency and uncover the adverse effects of zinc deficiency. METHODS We performed multi-omics analysis using serum proteomics-metabolomics and liver proteomics on zinc-deficient rats to identify candidate biomarkers and reveal the associated adverse effects of zinc deficiency. Secondly, the candidate biomarkers were validated in two zinc-deficient populations and an RCT zinc supplementation trial on a zinc-deficient population. RESULTS Our integrated multi-omics approach revealed numerous biomarkers (>2000) and glutathione metabolism as the most important changed pathway in zinc deficiency. Three candidate biomarkers from glutathione metabolism were validated in repeated zinc-deficient rats by quantitative analysis. Only glutathione sulfotransferase omega-1 (GSTO1) (among 3 candidate biomarkers) was validated in the two zinc-deficient populations and zinc-supplemented population. Compared with serum zinc, serum GSTO1 yielded a better response to zinc supplementation and a higher correlation coefficient with zinc intake and the AUC value and has the potential for diagnosing zinc deficiency. By integrated multi-omics, we identified both established and novel adverse effects of zinc deficiency. CONCLUSIONS Our integrated multi-omics analysis revealed more complete information about zinc deficiency; GSTO1 was found to be a reliable potential biomarker for diagnosis of zinc deficiency. This trial is registered at http://www.chictr.org.cn/registry.aspx as ChiCTR1900028162.
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14
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Saorin A, Di Gregorio E, Miolo G, Steffan A, Corona G. Emerging Role of Metabolomics in Ovarian Cancer Diagnosis. Metabolites 2020; 10:E419. [PMID: 33086611 PMCID: PMC7603269 DOI: 10.3390/metabo10100419] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 01/20/2023] Open
Abstract
Ovarian cancer is considered a silent killer due to the lack of clear symptoms and efficient diagnostic tools that often lead to late diagnoses. Over recent years, the impelling need for proficient biomarkers has led researchers to consider metabolomics, an emerging omics science that deals with analyses of the entire set of small-molecules (≤1.5 kDa) present in biological systems. Metabolomics profiles, as a mirror of tumor-host interactions, have been found to be useful for the analysis and identification of specific cancer phenotypes. Cancer may cause significant metabolic alterations to sustain its growth, and metabolomics may highlight this, making it possible to detect cancer in an early phase of development. In the last decade, metabolomics has been widely applied to identify different metabolic signatures to improve ovarian cancer diagnosis. The aim of this review is to update the current status of the metabolomics research for the discovery of new diagnostic metabolomic biomarkers for ovarian cancer. The most promising metabolic alterations are discussed in view of their potential biological implications, underlying the issues that limit their effective clinical translation into ovarian cancer diagnostic tools.
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Affiliation(s)
- Asia Saorin
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
| | - Emanuela Di Gregorio
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
| | - Gianmaria Miolo
- Medical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy;
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
| | - Giuseppe Corona
- Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; (A.S.); (E.D.G.); (A.S.)
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15
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Wang X, Kadarmideen HN. Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs. Metabolites 2020; 10:E201. [PMID: 32429265 PMCID: PMC7281523 DOI: 10.3390/metabo10050201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/10/2020] [Accepted: 05/11/2020] [Indexed: 12/21/2022] Open
Abstract
Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs' feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10-6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.
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Affiliation(s)
| | - Haja N. Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, Building 324, 2800 Kongens Lyngby, Denmark;
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16
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Mapping Metabolite and ICD-10 Associations. Metabolites 2020; 10:metabo10050196. [PMID: 32423141 PMCID: PMC7281140 DOI: 10.3390/metabo10050196] [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: 04/15/2020] [Revised: 05/07/2020] [Accepted: 05/13/2020] [Indexed: 12/02/2022] Open
Abstract
The search for novel metabolic biomarkers is intense but has had limited practical outcomes for medicine. Part of the problem is that we lack knowledge of how different comorbidities influence biomarkers’ performance. In this study, 49 metabolites were measured by targeted LC/MS protocols in the serum of 1011 volunteers. Their performance as potential biomarkers was evaluated by the area under the curve of receiver operator characteristics (AUC-ROC) for 105 diagnosis codes or code groups from the 10th revision of the international classification of diseases (ICD-10). Additionally, the interferences between diagnosis codes were investigated. The highest AUC-ROC values for individual metabolites and ICD-10 code combinations reached a moderate (0.7) range. Most metabolites that were found to be potential markers remained so independently of the control group composition or comorbidities. The precise value of the AUC-ROC, however, could vary depending on the comorbidities. Moreover, networks of metabolite and disease associations were built in order to map diseases, which may interfere with metabolic biomarker research on other diseases.
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17
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Mahmud I, Kabir M, Haque R, Garrett TJ. Decoding the Metabolome and Lipidome of Child Malnutrition by Mass Spectrometric Techniques: Present Status and Future Perspectives. Anal Chem 2019; 91:14784-14791. [PMID: 31682425 DOI: 10.1021/acs.analchem.9b03338] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Child malnutrition (CM) is a global public health problem. It contributes to poor health in one in four children under five years worldwide and causes serious health problems in children, including stunted, wasted, and overweight growth. These serious public health issues lead to a higher chance of living in poverty in adulthood. Malnutrition is related with reduced economic productivity and increases the serious national and international burden. Currently, there is no meaningful therapeutic intervention of CM, and the use of different therapeutic foods has shown poor outcomes among supplemented malnourished children. The role of metabolites and lipids has been extensively recognized as early determinants of child health, but their contribution in CM and its pathobiology are poorly understood. This perspective provides a most recent update on these aspects. After briefly introducing the disciplines of metabolomics and lipidomics, we describe a mass spectrometry-based metabolic workflow for analysis of both metabolites and lipids and summarize several recent applications of metabolomics and lipidomics in CM. Finally, we discuss the future directions of the field toward the development of meaningful interventions for CM through metabolomics and lipidomics advances.
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Affiliation(s)
- Iqbal Mahmud
- Department of Pathology, Immunology, and Laboratory Medicine , University of Florida, College of Medicine , Gainesville , Florida 32608 , United States.,Southeast Center for Integrated Metabolomics (SECIM), Clinical and Translational Science Institute , University of Florida , Gainesville , Florida 32608 , United States
| | - Mamun Kabir
- Emerging Infections and Parasitology Laboratory, Infectious Disease Division , International Centre for Diarrheal Disease Research , Dhaka 1213 , Bangladesh
| | - Rashidul Haque
- Emerging Infections and Parasitology Laboratory, Infectious Disease Division , International Centre for Diarrheal Disease Research , Dhaka 1213 , Bangladesh
| | - Timothy J Garrett
- Department of Pathology, Immunology, and Laboratory Medicine , University of Florida, College of Medicine , Gainesville , Florida 32608 , United States.,Southeast Center for Integrated Metabolomics (SECIM), Clinical and Translational Science Institute , University of Florida , Gainesville , Florida 32608 , United States
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18
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Khizer Z, Akram MR, Sarfraz RM, Nirwan JS, Farhaj S, Yousaf M, Hussain T, Lou S, Timmins P, Conway BR, Ghori MU. Plasticiser-Free 3D Printed Hydrophilic Matrices: Quantitative 3D Surface Texture, Mechanical, Swelling, Erosion, Drug Release and Pharmacokinetic Studies. Polymers (Basel) 2019; 11:E1095. [PMID: 31261678 PMCID: PMC6680934 DOI: 10.3390/polym11071095] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 06/14/2019] [Accepted: 06/25/2019] [Indexed: 11/16/2022] Open
Abstract
Hydroxypropyl methyl cellulose, HPMC, a hydrophilic polymer, is widely used for the development of extended release hydrophilic matrices and it is also considered as a good contender for the fabrication of 3D printing of matrix tablets. It is often combined with plasticisers to enable extrusion. The aim of the current project was to develop plasticizer-free 3D printed hydrophilic matrices using drug loaded filaments prepared via HME to achieve an in vitro (swelling, erosion and drug release) and in vivo (drug absorption) performance which is analogous to hydrophilic matrix tablets developed through conventional approaches. Additionally, the morphology of the printed tablets was studied using quantitative 3D surface texture studies and the porosity calculated. Filaments were produced successfully and used to produce matrix tablets with acceptable drug loading (95-105%), mechanical and surface texture properties regardless of the employed HPMC grade. The viscosity of HPMC had a discernible impact on the swelling, erosion, HPMC dissolution, drug release and pharmacokinetic findings. The highest viscosity grade (K100M) results in higher degree of swelling, decreased HPMC dissolution, low matrix erosion, decreased drug release and extended drug absorption profile. Overall, this study demonstrated that the drug loaded (glipizide) filaments and matrix tablets of medium to high viscosity grades of HPMC, without the aid of plasticisers, can be successfully prepared. Furthermore, the in vitro and in vivo studies have revealed the successful fabrication of extended release matrices.
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Affiliation(s)
- Zara Khizer
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Muhammad R Akram
- College of Pharmacy, University of Sargodha, Sargodha 40100, Pakistan
| | - Rai M Sarfraz
- College of Pharmacy, University of Sargodha, Sargodha 40100, Pakistan
| | - Jorabar Singh Nirwan
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Samia Farhaj
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Maria Yousaf
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Tariq Hussain
- System Engineering Department, Military Technological College, Muscat 111, Oman
- The Wolfson Centre for Bulk Solid Handling Technology, University of Greenwich, London SE10 9LS, UK
| | - Shan Lou
- School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Peter Timmins
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Barbara R Conway
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK
| | - Muhammad Usman Ghori
- Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK.
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19
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Kennedy AD, Wittmann BM, Evans AM, Miller LAD, Toal DR, Lonergan S, Elsea SH, Pappan KL. Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing. JOURNAL OF MASS SPECTROMETRY : JMS 2018; 53:1143-1154. [PMID: 30242936 DOI: 10.1002/jms.4292] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 09/10/2018] [Accepted: 09/17/2018] [Indexed: 06/08/2023]
Abstract
Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.
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Affiliation(s)
| | | | | | | | | | | | - Sarah H Elsea
- Department of Molecular and Human Genetics and Baylor Genetics, Baylor College of Medicine, Houston, TX, USA
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20
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Integration of the human exposome with the human genome to advance medicine. Biochimie 2018; 152:155-158. [DOI: 10.1016/j.biochi.2018.06.023] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 06/26/2018] [Indexed: 11/19/2022]
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Abstract
This commentary reviews the concept of experience-dependent epigenetic modifications in the CNS as a core mechanism underlying individuality and individuation at the behavioral level. I use the term individuation to refer to the underlying neurobiological processes that result in individuality, with the discussion focusing on individuality of cognitive, emotional, and behavioral repertoire. The review describes recent work supporting the concept of neuroepigenetic mechanisms underlying individuation, possible roles of transgenerational effects, and implications for precision medicine.
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Affiliation(s)
- J David Sweatt
- Department of Pharmacology, Vanderbilt University, Nashville, TN
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22
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Acosta-Vélez GF, Zhu TZ, Linsley CS, Wu BM. Photocurable poly(ethylene glycol) as a bioink for the inkjet 3D pharming of hydrophobic drugs. Int J Pharm 2018; 546:145-153. [PMID: 29705105 DOI: 10.1016/j.ijpharm.2018.04.056] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 04/10/2018] [Accepted: 04/25/2018] [Indexed: 11/26/2022]
Abstract
Binder jetting and material extrusion are the two most common additive manufacturing techniques used to create pharmaceutical tablets. However, their versatility is limited since the powder component is present throughout the dosage forms fabricated by binder jet 3D printing and material extrusion 3D printing requires high operating temperatures. Conversely, material jetting allows for compositional control at a voxel level and can dispense material at room temperature. Unfortunately, there are a limited number of materials that are both printable and biocompatible. Therefore, the aim of this study was to engineer photocurable bioinks that are suitable for hydrophobic active pharmaceutical ingredients and have rapid gelation times upon visible light exposure. The resulting bioinks were comprised of poly(ethylene glycol) diacrylate (250 Da) as the crosslinkable monomer, Eosin Y as the photoinitiator, and methoxide-poly(ethylene glycol)-amine as the coinitiator. Additionally, poly(ethylene glycol) (200 Da) was added as a plasticizer to modulate the drug release profiles, and Naproxen was used as the model drug due to its high hydrophobicity. Various bioink formulations were dispensed into the bottom half of blank preform tablets - made via direct compression - using a piezoelectric nozzle, photopolymerized, and capped with the top half of the preform tablet to complete the pharmaceutical dosage form. Results from the release studies showed that drug release can be modulated by both the percent of poly(ethylene glycol) diacrylate in the formulation and the light exposure time used to cure the bioinks. These bioinks have the potential to expand the library of materials available for creating pharmaceutical tablets via inkjet printing with personalized drug dosages.
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Affiliation(s)
- Giovanny F Acosta-Vélez
- Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, Room 5121, Engineering V, P.O. Box: 951600, Los Angeles, CA 90095, USA.
| | - Timothy Z Zhu
- Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, Room 5121, Engineering V, P.O. Box: 951600, Los Angeles, CA 90095, USA.
| | - Chase S Linsley
- Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, Room 5121, Engineering V, P.O. Box: 951600, Los Angeles, CA 90095, USA.
| | - Benjamin M Wu
- Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, Room 5121, Engineering V, P.O. Box: 951600, Los Angeles, CA 90095, USA; Division of Advanced Prosthodontics and the Weintraub Center for Reconstructive Biotechnology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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23
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Shields PG, Berman M, Brasky TM, Freudenheim JL, Mathe E, McElroy JP, Song MA, Wewers MD. A Review of Pulmonary Toxicity of Electronic Cigarettes in the Context of Smoking: A Focus on Inflammation. Cancer Epidemiol Biomarkers Prev 2017; 26:1175-1191. [PMID: 28642230 PMCID: PMC5614602 DOI: 10.1158/1055-9965.epi-17-0358] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2017] [Revised: 05/22/2017] [Accepted: 05/24/2017] [Indexed: 12/30/2022] Open
Abstract
The use of electronic cigarettes (e-cigs) is increasing rapidly, but their effects on lung toxicity are largely unknown. Smoking is a well-established cause of lung cancer and respiratory disease, in part through inflammation. It is plausible that e-cig use might affect similar inflammatory pathways. E-cigs are used by some smokers as an aid for quitting or smoking reduction, and by never smokers (e.g., adolescents and young adults). The relative effects for impacting disease risk may differ for these groups. Cell culture and experimental animal data indicate that e-cigs have the potential for inducing inflammation, albeit much less than smoking. Human studies show that e-cig use in smokers is associated with substantial reductions in blood or urinary biomarkers of tobacco toxicants when completely switching and somewhat for dual use. However, the extent to which these biomarkers are surrogates for potential lung toxicity remains unclear. The FDA now has regulatory authority over e-cigs and can regulate product and e-liquid design features, such as nicotine content and delivery, voltage, e-liquid formulations, and flavors. All of these factors may impact pulmonary toxicity. This review summarizes current data on pulmonary inflammation related to both smoking and e-cig use, with a focus on human lung biomarkers. Cancer Epidemiol Biomarkers Prev; 26(8); 1175-91. ©2017 AACR.
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Affiliation(s)
- Peter G Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio.
| | - Micah Berman
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Public Health, Ohio
| | - Theodore M Brasky
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio
| | - Jo L Freudenheim
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York
| | - Ewy Mathe
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio
| | - Joseph P McElroy
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio
| | - Min-Ae Song
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, and College of Medicine, Columbus, Ohio
| | - Mark D Wewers
- Department of Internal Medicine, The Ohio State University, Columbus, Ohio
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25
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Contreras AV, Cocom-Chan B, Hernandez-Montes G, Portillo-Bobadilla T, Resendis-Antonio O. Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine. Front Physiol 2016; 7:606. [PMID: 28018236 PMCID: PMC5145879 DOI: 10.3389/fphys.2016.00606] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/21/2016] [Indexed: 12/19/2022] Open
Abstract
It has been experimentally shown that host-microbial interaction plays a major role in shaping the wellness or disease of the human body. Microorganisms coexisting in human tissues provide a variety of benefits that contribute to proper functional activity in the host through the modulation of fundamental processes such as signal transduction, immunity and metabolism. The unbalance of this microbial profile, or dysbiosis, has been correlated with the genesis and evolution of complex diseases such as cancer. Although this latter disease has been thoroughly studied using different high-throughput (HT) technologies, its heterogeneous nature makes its understanding and proper treatment in patients a remaining challenge in clinical settings. Notably, given the outstanding role of host-microbiome interactions, the ecological interactions with microorganisms have become a new significant aspect in the systems that can contribute to the diagnosis and potential treatment of solid cancers. As a part of expanding precision medicine in the area of cancer research, efforts aimed at effective treatments for various kinds of cancer based on the knowledge of genetics, biology of the disease and host-microbiome interactions might improve the prediction of disease risk and implement potential microbiota-directed therapeutics. In this review, we present the state of the art of sequencing and metabolome technologies, computational methods and schemes in systems biology that have addressed recent breakthroughs of uncovering relationships or associations between microorganisms and cancer. Together, microbiome studies extend the horizon of new personalized treatments against cancer from the perspective of precision medicine through a synergistic strategy integrating clinical knowledge, HT data, bioinformatics, and systems biology.
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Affiliation(s)
| | - Benjamin Cocom-Chan
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico
| | - Georgina Hernandez-Montes
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Tobias Portillo-Bobadilla
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Osbaldo Resendis-Antonio
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico; Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM)Mexico City, Mexico
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26
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Tebani A, Abily-Donval L, Afonso C, Marret S, Bekri S. Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era. Int J Mol Sci 2016; 17:ijms17071167. [PMID: 27447622 PMCID: PMC4964538 DOI: 10.3390/ijms17071167] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2016] [Revised: 07/12/2016] [Accepted: 07/15/2016] [Indexed: 12/29/2022] Open
Abstract
Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of “omic” technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent “omic” technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76031, France.
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, Rouen 76000, France.
| | - Lenaig Abily-Donval
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Department of Neonatal Pediatrics and Intensive Care, Rouen University Hospital, Rouen 76031, France.
| | - Carlos Afonso
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, Rouen 76000, France.
| | - Stéphane Marret
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Department of Neonatal Pediatrics and Intensive Care, Rouen University Hospital, Rouen 76031, France.
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76031, France.
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
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Metabolomics: Bridging the Gap between Pharmaceutical Development and Population Health. Metabolites 2016; 6:metabo6030020. [PMID: 27399792 PMCID: PMC5041119 DOI: 10.3390/metabo6030020] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 06/06/2016] [Accepted: 07/01/2016] [Indexed: 12/28/2022] Open
Abstract
Metabolomics has emerged as an essential tool for studying metabolic processes, stratification of patients, as well as illuminating the fundamental metabolic alterations in disease onset, progression, or response to therapeutic intervention. Metabolomics materialized within the pharmaceutical industry as a standalone assay in toxicology and disease pathology and eventually evolved towards aiding in drug discovery and pre-clinical studies via supporting pharmacokinetic and pharmacodynamic characterization of a drug or a candidate. Recent progress in the field is illustrated by coining of the new term—Pharmacometabolomics. Integration of data from metabolomics with large-scale omics along with clinical, molecular, environmental and behavioral analysis has demonstrated the enhanced utility of deconstructing the complexity of health, disease, and pharmaceutical intervention(s), which further highlight it as an essential component of systems medicine. This review presents the current state and trend of metabolomics applications in pharmaceutical development, and highlights the importance and potential of clinical metabolomics as an essential part of multi-omics protocols that are directed towards shaping precision medicine and population health.
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