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Dasgupta S. Systems Biology and Machine Learning Identify Genetic Overlaps Between Lung Cancer and Gastroesophageal Reflux Disease. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:492-503. [PMID: 39269895 DOI: 10.1089/omi.2024.0150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/15/2024]
Abstract
One Health and planetary health place emphasis on the common molecular mechanisms that connect several complex human diseases as well as human and planetary ecosystem health. For example, not only lung cancer (LC) and gastroesophageal reflux disease (GERD) pose a significant burden on planetary health, but also the coexistence of GERD in patients with LC is often associated with a poor prognosis. This study reports on the genetic overlaps between these two conditions using systems biology-driven bioinformatics and machine learning-based algorithms. A total of nine hub genes including IGHV1-3, COL3A1, ITGA11, COL1A1, MS4A1, SPP1, MMP9, MMP7, and LOC102723407 were found to be significantly altered in both LC and GERD as compared with controls and with pathway analyses suggesting a significant association with the matrix remodeling pathway. The expression of these genes was validated in two additional datasets. Random forest and K-nearest neighbor, two machine learning-based algorithms, achieved accuracies of 89% and 85% for distinguishing LC and GERD, respectively, from controls using these hub genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of doxycycline to matrix metalloproteinase 7 (binding affinity: -6.8 kcal/mol). The present study is the first of its kind that combines in silico and machine learning algorithms to identify the gene signatures that relate to both LC and GERD and promising drug candidates that warrant further research in relation to therapeutic innovation in LC and GERD. Finally, this study also suggests upstream regulators, including microRNAs and transcription factors, that can inform future mechanistic research on LC and GERD.
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Affiliation(s)
- Sanjukta Dasgupta
- Department of Biotechnology, Center for Multidisciplinary Research and Innovations, Brainware University, Barasat, India
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2
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Xiao X, Wang Q, Chai X, Zhang X, Jiang B, Liu M. Using neural networks to obtain NMR spectra of both small and macromolecules from blood samples in a single experiment. Commun Chem 2024; 7:167. [PMID: 39079950 PMCID: PMC11289489 DOI: 10.1038/s42004-024-01251-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/22/2024] [Indexed: 08/02/2024] Open
Abstract
Metabolomics plays a crucial role in understanding metabolic processes within biological systems. Using specific pulse sequences, NMR-based metabolomics detects small and macromolecular metabolites that are altered in blood samples. Here we proposed a method called spectral editing neural network, which can effectively edit and separate the spectral signals of small and macromolecules in 1H NMR spectra of serum and plasma based on the linewidth of the peaks. We applied the model to process the 1H NMR spectra of plasma and serum. The extracted small and macromolecular spectra were then compared with experimentally obtained relaxation-edited and diffusion-edited spectra. Correlation analysis demonstrated the quantitative capability of the model in the extracted small molecule signals from 1H NMR spectra. The principal component analysis showed that the spectra extracted by the model and those obtained by NMR spectral editing methods reveal similar group information, demonstrating the effectiveness of the model in signal extraction.
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Affiliation(s)
- Xiongjie Xiao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Qianqian Wang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Xin Chai
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Xu Zhang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
- Optics Valley Laboratory, Wuhan, China
| | - Bin Jiang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Optics Valley Laboratory, Wuhan, China.
| | - Maili Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan National Laboratory for Optoelectronics, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Optics Valley Laboratory, Wuhan, China.
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3
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Dasgupta S. Thinking Beyond Disease Silos: Dysregulated Genes Common in Tuberculosis and Lung Cancer as Identified by Systems Biology and Machine Learning. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:347-356. [PMID: 38856681 DOI: 10.1089/omi.2024.0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
The traditional way of thinking about human diseases across clinical and narrow phenomics silos often masks the underlying shared molecular substrates across human diseases. One Health and planetary health fields particularly address such complexities and invite us to think across the conventional disease nosologies. For example, tuberculosis (TB) and lung cancer (LC) are major pulmonary diseases with significant planetary health implications. Despite distinct etiologies, they can coexist in a given community or patient. This is both a challenge and an opportunity for preventive medicine, diagnostics, and therapeutics innovation. This study reports a bioinformatics analysis of publicly available gene expression data, identifying overlapping dysregulated genes, downstream regulators, and pathways in TB and LC. Analysis of NCBI-GEO datasets (GSE83456 and GSE103888) unveiled differential expression of CEACAM6, MUC1, ADM, DYSF, PLOD2, and GAS6 genes in both diseases, with pathway analysis indicating association with lysine degradation pathway. Random forest, a machine-learning-based classification, achieved accuracies of 84% for distinguishing TB from controls and 83% for discriminating LC from controls using these specific genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of warfarin to GAS6. Taken together, the present study speaks of the pressing need to rethink clinical diagnostic categories of human diseases and that TB and LC might potentially share molecular substrates. Going forward, planetary health and One Health scholarship are poised to cultivate new ways of thinking about diseases not only across medicine and ecology but also across traditional diagnostic conventions.
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Seyfinejad B, Nemutlu E, Taghizadieh A, Khoubnasabjafari M, Ozkan SA, Jouyban A. Biomarkers in exhaled breath condensate as fingerprints of asthma, chronic obstructive pulmonary disease and asthma-chronic obstructive pulmonary disease overlap: a critical review. Biomark Med 2023; 17:811-837. [PMID: 38179966 DOI: 10.2217/bmm-2023-0420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024] Open
Abstract
Asthma, chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap are the third leading cause of mortality around the world. They share some common features, which can lead to misdiagnosis. To properly manage these conditions, reliable markers for early and accurate diagnosis are needed. Over the past 20 years, many molecules have been investigated in the exhaled breath condensate to better understand inflammation pathways and mechanisms related to these disorders. Recently, more advanced techniques, such as sensitive metabolomic and proteomic profiling, have been used to obtain a more comprehensive understanding. This article reviews the use of targeted and untargeted metabolomic methodology to study asthma, COPD and asthma-COPD overlap.
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Affiliation(s)
- Behrouz Seyfinejad
- Pharmaceutical Analysis Research Center & Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Emirhan Nemutlu
- Department of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara, 06100, Turkiye
| | - Ali Taghizadieh
- Tuberculosis & Lung Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Internal Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Maryam Khoubnasabjafari
- Tuberculosis & Lung Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Anesthesiology & Intensive Care, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sibel A Ozkan
- Ankara University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, 06560, Turkiye
| | - Abolghasem Jouyban
- Pharmaceutical Analysis Research Center & Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
- Faculty of Pharmacy, Near East University, PO Box 99138 Nicosia, North Cyprus, Mersin 10, Turkiye
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5
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Gea J, Enríquez-Rodríguez CJ, Agranovich B, Pascual-Guardia S. Update on metabolomic findings in COPD patients. ERJ Open Res 2023; 9:00180-2023. [PMID: 37908399 PMCID: PMC10613990 DOI: 10.1183/23120541.00180-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 08/15/2023] [Indexed: 11/02/2023] Open
Abstract
COPD is a heterogeneous disorder that shows diverse clinical presentations (phenotypes and "treatable traits") and biological mechanisms (endotypes). This heterogeneity implies that to carry out a more personalised clinical management, it is necessary to classify each patient accurately. With this objective, and in addition to clinical features, it would be very useful to have well-defined biological markers. The search for these markers may either be done through more conventional laboratory and hypothesis-driven techniques or relatively blind high-throughput methods, with the omics approaches being suitable for the latter. Metabolomics is the science that studies biological processes through their metabolites, using various techniques such as gas and liquid chromatography, mass spectrometry and nuclear magnetic resonance. The most relevant metabolomics studies carried out in COPD highlight the importance of metabolites involved in pathways directly related to proteins (peptides and amino acids), nucleic acids (nitrogenous bases and nucleosides), and lipids and their derivatives (especially fatty acids, phospholipids, ceramides and eicosanoids). These findings indicate the relevance of inflammatory-immune processes, oxidative stress, increased catabolism and alterations in the energy production. However, some specific findings have also been reported for different COPD phenotypes, demographic characteristics of the patients, disease progression profiles, exacerbations, systemic manifestations and even diverse treatments. Unfortunately, the studies carried out to date have some limitations and shortcomings and there is still a need to define clear metabolomic profiles with clinical utility for the management of COPD and its implicit heterogeneity.
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Affiliation(s)
- Joaquim Gea
- Respiratory Medicine Department, Hospital del Mar – IMIM, Barcelona, Spain
- MELIS Department, Universitat Pompeu Fabra, Barcelona, Spain
- CIBERES, ISCIII, Barcelona, Spain
| | - César J. Enríquez-Rodríguez
- Respiratory Medicine Department, Hospital del Mar – IMIM, Barcelona, Spain
- MELIS Department, Universitat Pompeu Fabra, Barcelona, Spain
| | - Bella Agranovich
- Rappaport Institute for Research in the Medical Sciences, Technion University, Haifa, Israel
| | - Sergi Pascual-Guardia
- Respiratory Medicine Department, Hospital del Mar – IMIM, Barcelona, Spain
- MELIS Department, Universitat Pompeu Fabra, Barcelona, Spain
- CIBERES, ISCIII, Barcelona, Spain
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Yates DH. Physiology and Biomarkers for Surveillance of Occupational Lung Disease. Semin Respir Crit Care Med 2023; 44:349-361. [PMID: 37072024 DOI: 10.1055/s-0043-1766119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
Respiratory surveillance is the process whereby a group of exposed workers are regularly tested (or screened) for those lung diseases which occur as a result of a specific work exposure. Surveillance is performed by assessing various measures of biological or pathological processes (or biomarkers) for change over time. These traditionally include questionnaires, lung physiological assessments (especially spirometry), and imaging. Early detection of pathological processes or disease can enable removal of a worker from a potentially harmful exposure at an early stage. In this article, we summarize the physiological biomarkers currently used for respiratory surveillance, while commenting on differences in interpretative strategies between different professional groups. We also briefly review the many new techniques which are currently being assessed for respiratory surveillance in prospective research studies and which are likely to significantly broaden and enhance this field in the near future.
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Affiliation(s)
- Deborah H Yates
- Department of Thoracic Medicine, St. Vincent's Hospital, Darlinghurst, NSW, Australia
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Dasgupta S, Das SS, Patidar S, Kajaria V, Chowdhury SR, Chaudhury K. Identification of Common Dysregulated Genes in COVID-19 and Hypersensitivity Pneumonitis: A Systems Biology and Machine Learning Approach. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2023; 27:205-214. [PMID: 37062762 DOI: 10.1089/omi.2022.0171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
A comprehensive knowledge on systems biology of severe acute respiratory syndrome coronavirus 2 is crucial for differential diagnosis of COVID-19. Interestingly, the radiological and pathological features of COVID-19 mimic that of hypersensitivity pneumonitis (HP), another pulmonary fibrotic phenotype. This motivated us to explore the overlapping pathophysiology of COVID-19 and HP, if any, and using a systems biology approach. Two datasets were obtained from the Gene Expression Omnibus database (GSE147507 and GSE150910) and common differentially expressed genes (DEGs) for both diseases identified. Fourteen common DEGs, significantly altered in both diseases, were found to be implicated in complement activation and growth factor activity. A total of five microRNAs (hsa-miR-1-3p, hsa-miR-20a-5p, hsa-miR-107, hsa-miR-16-5p, and hsa-miR-34b-5p) and five transcription factors (KLF6, ZBTB7A, ELF1, NFIL3, and ZBT33) exhibited highest interaction with these common genes. Next, C3, CFB, MMP-9, and IL1A were identified as common hub genes for both COVID-19 and HP. Finally, these top-ranked genes (hub genes) were evaluated using random forest classifier to discriminate between the disease and control group (coronavirus disease 2019 [COVID-19] vs. controls, and HP vs. controls). This supervised machine learning approach demonstrated 100% and 87.6% accuracy in differentiating COVID-19 from controls, and HP from controls, respectively. These findings provide new molecular leads that inform COVID-19 and HP diagnostics and therapeutics research and innovation.
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Affiliation(s)
- Sanjukta Dasgupta
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Sankha Subhra Das
- Department of Human Genetics, University of California Los Angeles (UCLA), Los Angeles, California, USA
| | - Sankalp Patidar
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Vaibhav Kajaria
- Department of Pulmonology, Fortis Hospital Anandapur, Kolkata, India
| | | | - Koel Chaudhury
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
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8
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Dasgupta S, Ghosh N, Bhattacharyya P, Roy Chowdhury S, Chaudhury K. Metabolomics of asthma, COPD, and asthma-COPD overlap: an overview. Crit Rev Clin Lab Sci 2023; 60:153-170. [PMID: 36420874 DOI: 10.1080/10408363.2022.2140329] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The two common progressive lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are the leading causes of morbidity and mortality worldwide. Asthma-COPD overlap, referred to as ACO, is another complex pulmonary disease that manifests itself with features of both asthma and COPD. The disease has no clear diagnostic or therapeutic guidelines, thereby making both diagnosis and treatment challenging. Though a number of studies on ACO have been documented, gaps in knowledge regarding the pathophysiologic mechanism of this disorder exist. Addressing this issue is an urgent need for improved diagnostic and therapeutic management of the disease. Metabolomics, an increasingly popular technique, reveals the pathogenesis of complex diseases and holds promise in biomarker discovery. This comprehensive narrative review, comprising 99 original research articles in the last five years (2017-2022), summarizes the scientific advances in terms of metabolic alterations in patients with asthma, COPD, and ACO. The analytical tools, nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), commonly used to study the expression of the metabolome, are discussed. Challenges frequently encountered during metabolite identification and quality assessment are highlighted. Bridging the gap between phenotype and metabotype is envisioned in the future.
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Affiliation(s)
- Sanjukta Dasgupta
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Nilanjana Ghosh
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | | | | | - Koel Chaudhury
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
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9
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Understanding the Functional Role of the Microbiome and Metabolome in Asthma. Curr Allergy Asthma Rep 2023; 23:67-76. [PMID: 36525159 DOI: 10.1007/s11882-022-01056-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2022] [Indexed: 12/23/2022]
Abstract
PURPOSE OF REVIEW Asthma is a heterogenous respiratory disease characterized by airway inflammation and obstruction. However, the causes of asthma are unknown. Several studies have reported microbial and metabolomic dysbiosis in asthmatic patients; but, little is known about the functional role of the microbiota or the host-microbe metabolome in asthma pathophysiology. Current multi-omic studies are linking both the metabolome and microbiome in different organ systems to help identify the interactions involved in asthma, with the goal of better identifying endotypes/phenotypes, causal links, and potential targets of treatment. This review thus endeavors to explore the benefits of and current advances in studying microbiome-metabolome interactions in asthma. RECENT FINDINGS This is a narrative review of the current state of research surrounding the interaction between the microbiome and metabolome and their role in asthma. Associations with asthma onset, severity, and phenotype have been identified in both the microbiome and the metabolome, most frequently in the gut. More recently, studies have begun to investigate the role of the respiratory microbiome in airway disease and its association with the systemic metabolome, which has provided further insights into its role in asthma phenotypes. This review also identifies gaps in the field in understanding the direct link between respiratory microbiome and metabolome, hypothesizes the benefits for conducting such studies in the future for asthma treatment and prevention, and identifies current analytical limitations that need to be addressed to advance the field. This is a comprehensive review of the current state of research on the interaction between the microbiome and metabolome and their role in asthma.
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10
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Gea J, Enríquez-Rodríguez CJ, Pascual-Guardia S. Metabolomics in COPD. Arch Bronconeumol 2023; 59:311-321. [PMID: 36717301 DOI: 10.1016/j.arbres.2022.12.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/28/2022] [Accepted: 12/07/2022] [Indexed: 01/20/2023]
Abstract
The clinical presentation of chronic obstructive pulmonary disease (COPD) is highly heterogeneous. Attempts have been made to define subpopulations of patients who share clinical characteristics (phenotypes and treatable traits) and/or biological characteristics (endotypes), in order to offer more personalized care. Assigning a patient to any of these groups requires the identification of both clinical and biological markers. Ideally, biological markers should be easily obtained from blood or urine, but these may lack specificity. Biomarkers can be identified initially using conventional or more sophisticated techniques. However, the more sophisticated techniques should be simplified in the future if they are to have clinical utility. The -omics approach offers a methodology that can assist in the investigation and identification of useful markers in both targeted and blind searches. Specifically, metabolomics is the science that studies biological processes involving metabolites, which can be intermediate or final products. The metabolites associated with COPD and their specific phenotypic and endotypic features have been studied using various techniques. Several compounds of particular interest have emerged, namely, several types of lipids and derivatives (mainly phospholipids, but also ceramides, fatty acids and eicosanoids), amino acids, coagulation factors, and nucleic acid components, likely to be involved in their function, protein catabolism, energy production, oxidative stress, immune-inflammatory response and coagulation disorders. However, clear metabolomic profiles of the disease and its various manifestations that may already be applicable in clinical practice still need to be defined.
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Affiliation(s)
- Joaquim Gea
- Servicio de Neumología, Hospital del Mar - IMIM, Barcelona, Spain; Dpt. MELIS, Universitat Pompeu Fabra, Barcelona, Spain; CIBERES, ISCIII, Barcelona, Spain.
| | - César J Enríquez-Rodríguez
- Servicio de Neumología, Hospital del Mar - IMIM, Barcelona, Spain; Dpt. MELIS, Universitat Pompeu Fabra, Barcelona, Spain
| | - Sergi Pascual-Guardia
- Servicio de Neumología, Hospital del Mar - IMIM, Barcelona, Spain; Dpt. MELIS, Universitat Pompeu Fabra, Barcelona, Spain; CIBERES, ISCIII, Barcelona, Spain
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11
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Gruzieva O, Jeong A, He S, Yu Z, de Bont J, Pinho MGM, Eze IC, Kress S, Wheelock CE, Peters A, Vlaanderen J, de Hoogh K, Scalbert A, Chadeau-Hyam M, Vermeulen RCH, Gehring U, Probst-Hensch N, Melén E. Air pollution, metabolites and respiratory health across the life-course. Eur Respir Rev 2022; 31:220038. [PMID: 35948392 PMCID: PMC9724796 DOI: 10.1183/16000617.0038-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 06/09/2022] [Indexed: 11/05/2022] Open
Abstract
Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data.
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Affiliation(s)
- Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
- Both authors contributed equally to this article
| | - Ayoung Jeong
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Both authors contributed equally to this article
| | - Shizhen He
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Zhebin Yu
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jeroen de Bont
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria G M Pinho
- Dept of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
| | - Ikenna C Eze
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sara Kress
- IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Craig E Wheelock
- Unit of Integrative Metabolomics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Dept of Respiratory Medicine and Allergy, Karolinska University Hospital, Stockholm, Sweden
- Gunma University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Japan
| | - Annette Peters
- Institute of Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Jelle Vlaanderen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Augustin Scalbert
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Marc Chadeau-Hyam
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
- Imperial College London, London, UK
| | - Roel C H Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Ulrike Gehring
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
- These authors contributed equally to this article
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
- These authors contributed equally to this article
| | - Erik Melén
- Dept of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs Children's Hospital, Stockholm, Sweden
- These authors contributed equally to this article
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12
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Zhang L, Li X, Chen H, Wu Z, Hu M, Yao M. Haze Air Pollution Health Impacts of Breath-Borne VOCs. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:8541-8551. [PMID: 35559607 DOI: 10.1021/acs.est.2c01778] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Here, we investigated the use of breath-borne volatile organic compounds (VOCs) for rapid monitoring of air pollution health effects on humans. Forty-seven healthy college students were recruited, and their exhaled breath samples (n = 235) were collected and analyzed for VOCs before, on, and after two separate haze pollution episodes using gas chromatography-ion mobility spectrometry (GC-IMS). Using a paired t-test and machine learning model (Gradient Boosting Machine, GBM), six exhaled VOC species including propanol and isoprene were revealed to differ significantly among pre-, on-, and post-exposure in both haze episodes, while none was found between clean control days. The GBM model was shown capable of differentiating between pre- and on-exposure to haze pollution with a precision of 90-100% for both haze episodes. However, poor performance was detected for the same model between two different clean days. In addition to gender and particular haze occurrence influences, correlation analysis revealed that NH4+, NO3-, acetic acid, mesylate, CO, NO2, PM2.5, and O3 played important roles in the changes in breath-borne VOC fingerprints following haze air pollution exposure. This work has demonstrated direct evidence of human health impacts of haze pollution while identifying potential breath-borne VOC biomarkers such as propanol and isoprene for haze air pollution exposure.
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Affiliation(s)
- Lu Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xinyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Haoxuan Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zhijun Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Maosheng Yao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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Chen YC, Chang YP, Huang KT, Hsu PY, Hsiao CC, Lin MC. Unraveling the Pathogenesis of Asthma and Chronic Obstructive Pulmonary Disease Overlap: Focusing on Epigenetic Mechanisms. Cells 2022; 11:cells11111728. [PMID: 35681424 PMCID: PMC9179497 DOI: 10.3390/cells11111728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/05/2022] [Accepted: 05/21/2022] [Indexed: 12/10/2022] Open
Abstract
Asthma and COPD overlap (ACO) is characterized by patients presenting with persistent airflow limitation and features of both asthma and COPD. It is associated with a higher frequency and severity of exacerbations, a faster lung function decline, and a higher healthcare cost. Systemic inflammation in COPD and asthma is driven by type 1 T helper (Th1) and Th2 immune responses, respectively, both of which may contribute to airway remodeling in ACO. ACO-related biomarkers can be classified into four categories: neutrophil-mediated inflammation, Th2 cell responses, arachidonic acid-eicosanoids pathway, and metabolites. Gene–environment interactions are key contributors to the complexity of ACO and are regulated by epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNAs. Thus, this review focuses on the link between epigenetics and ACO, and outlines the following: (I) inheriting epigenotypes without change with environmental stimuli, or epigenetic changes in response to long-term exposure to inhaled particles plus intermittent exposure to specific allergens; (II) epigenetic markers distinguishing ACO from COPD and asthma; (III) potential epigenetic drugs that can reverse oxidative stress, glucocorticoid insensitivity, and cell injury. Improved understanding of the epigenetic regulations holds great value to give deeper insight into the mechanisms, and clarify their implications for biomedical research in ACO.
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Affiliation(s)
- Yung-Che Chen
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Department of Medicine, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
| | - Yu-Ping Chang
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Kuo-Tung Huang
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Po-Yuan Hsu
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Chang-Chun Hsiao
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
| | - Meng-Chih Lin
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
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Paris D, Palomba L, Tramice A, Motta L, Fuschillo S, Maniscalco M, Motta A. Identification of biomarkers in COPD by metabolomics of exhaled breath condensate and serum/plasma. Minerva Med 2022; 113:424-435. [PMID: 35191295 DOI: 10.23736/s0026-4806.22.07957-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is the third cause of death worldwide, presenting poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations because its pathophysiological determinants relate to tobacco smoke, genetic factors, alteration of several metabolic pathways, and oxidative stress. As a consequence, patients present different phenotypes even with comparable degrees of airflow limitation. Because of the increasing social and economic costs of COPD, a growing attention is currently payed to "omics" techniques for more personalized treatments and patient-tailored rehabilitation programs. In this regard, the systematic investigation of the metabolome (i.e., the whole set of endogenous molecules) in biomatrices, namely metabolomics, has become indispensable for phenotyping respiratory diseases. The metabolomic profiling of biological samples contains the small molecules produced during biological processes and their identification and quantification help in the diagnosis, comprehension of disease outcome and treatment response. Exhaled breath condensate (EBC), plasma and serum are biofluids readily available, with negligible invasiveness, and, therefore, suitable for metabolomics investigations. In this paper, we describe the latest advances on metabolomic profiling of EBC, plasma and serum in COPD patients.
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Affiliation(s)
- Debora Paris
- Institute of Biomolecular Chemistry, National Research Council, Pozzuoli, Napoli, Italy
| | - Letizia Palomba
- Department of Biomolecular Sciences, University Carlo Bo, Urbino, Italy
| | - Annabella Tramice
- Institute of Biomolecular Chemistry, National Research Council, Pozzuoli, Napoli, Italy
| | - Lorenzo Motta
- Section of Radiology, Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara, Italy
| | - Salvatore Fuschillo
- Pulmonary Rehabilitation Division of the Telese Terme Institute, Istituti Clinici Scientifici Maugeri IRCCS, Telese Terme, Benevento, Italy
| | - Mauro Maniscalco
- Pulmonary Rehabilitation Division of the Telese Terme Institute, Istituti Clinici Scientifici Maugeri IRCCS, Telese Terme, Benevento, Italy
| | - Andrea Motta
- Institute of Biomolecular Chemistry, National Research Council, Pozzuoli, Napoli, Italy -
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