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Shi C, Cheng L, Yu Y, Chen S, Dai Y, Yang J, Zhang H, Chen J, Geng N. Multi-omics integration analysis: Tools and applications in environmental toxicology. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 360:124675. [PMID: 39103035 DOI: 10.1016/j.envpol.2024.124675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 07/08/2024] [Accepted: 08/03/2024] [Indexed: 08/07/2024]
Abstract
Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.
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Affiliation(s)
- Chengcheng Shi
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Lin Cheng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ying Yu
- College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Shuangshuang Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Yubing Dai
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiajia Yang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Materials Science and Engineering, Hebei University of Engineering, Handan, 056038, China
| | - Haijun Zhang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiping Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ningbo Geng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
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2
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Dowrick JM, Roy NC, Bayer S, Frampton CMA, Talley NJ, Gearry RB, Angeli-Gordon TR. Unsupervised machine learning highlights the challenges of subtyping disorders of gut-brain interaction. Neurogastroenterol Motil 2024:e14898. [PMID: 39119757 DOI: 10.1111/nmo.14898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/17/2024] [Accepted: 07/31/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Unsupervised machine learning describes a collection of powerful techniques that seek to identify hidden patterns in unlabeled data. These techniques can be broadly categorized into dimension reduction, which transforms and combines the original set of measurements to simplify data, and cluster analysis, which seeks to group subjects based on some measure of similarity. Unsupervised machine learning can be used to explore alternative subtyping of disorders of gut-brain interaction (DGBI) compared to the existing gastrointestinal symptom-based definitions of Rome IV. PURPOSE This present review aims to familiarize the reader with fundamental concepts of unsupervised machine learning using accessible definitions and provide a critical summary of their application to the evaluation of DGBI subtyping. By considering the overlap between Rome IV clinical definitions and identified clusters, along with clinical and physiological insights, this paper speculates on the possible implications for DGBI. Also considered are algorithmic developments in the unsupervised machine learning community that may help leverage increasingly available omics data to explore biologically informed definitions. Unsupervised machine learning challenges the modern subtyping of DGBI and, with the necessary clinical validation, has the potential to enhance future iterations of the Rome criteria to identify more homogeneous, diagnosable, and treatable patient populations.
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Affiliation(s)
- Jarrah M Dowrick
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
| | - Nicole C Roy
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- Department of Human Nutrition, University of Otago, Dunedin, New Zealand
- Riddet Institute, Massey University, Palmerston North, New Zealand
| | - Simone Bayer
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Chris M A Frampton
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Nicholas J Talley
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Richard B Gearry
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Timothy R Angeli-Gordon
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- High-Value Nutrition National Science Challenge, Auckland, New Zealand
- Riddet Institute, Massey University, Palmerston North, New Zealand
- Department of Surgery, University of Auckland, Auckland, New Zealand
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3
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Sharma S, Gerber AN, Kraft M, Wenzel SE. Asthma Pathogenesis: Phenotypes, Therapies, and Gaps: Summary of the Aspen Lung Conference 2023. Am J Respir Cell Mol Biol 2024; 71:154-168. [PMID: 38635858 PMCID: PMC11299090 DOI: 10.1165/rcmb.2024-0082ws] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 04/17/2024] [Indexed: 04/20/2024] Open
Abstract
Although substantial progress has been made in our understanding of asthma pathogenesis and phenotypes over the nearly 60-year history of the Aspen Lung Conferences on asthma, many ongoing challenges exist in our understanding of the clinical and molecular heterogeneity of the disease and an individual patient's response to therapy. This report summarizes the proceedings of the 2023 Aspen Lung Conference, which was organized to review the clinical and molecular heterogeneity of asthma and to better understand the impact of genetic, environmental, cellular, and molecular influences on disease susceptibility, heterogeneity, and severity. The goals of the conference were to review new information about asthma phenotypes, cellular processes, and cellular signatures underlying disease heterogeneity and treatment response. The report concludes with ongoing gaps in our understanding of asthma pathobiology and provides some recommendations for future research to better understand the clinical and basic mechanisms underlying disease heterogeneity in asthma and to advance the development of new treatments for this growing public health problem.
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Affiliation(s)
- Sunita Sharma
- Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Anthony N. Gerber
- Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- Department of Medicine, National Jewish Health, Denver, Colorado
| | - Monica Kraft
- Department of Medicine, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York; and
| | - Sally E. Wenzel
- Department of Environmental and Occupational Health, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
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4
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Bunyavanich S, Becker PM, Altman MC, Lasky-Su J, Ober C, Zengler K, Berdyshev E, Bonneau R, Chatila T, Chatterjee N, Chung KF, Cutcliffe C, Davidson W, Dong G, Fang G, Fulkerson P, Himes BE, Liang L, Mathias RA, Ogino S, Petrosino J, Price ND, Schadt E, Schofield J, Seibold MA, Steen H, Wheatley L, Zhang H, Togias A, Hasegawa K. Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop. J Allergy Clin Immunol 2024; 153:954-968. [PMID: 38295882 PMCID: PMC10999353 DOI: 10.1016/j.jaci.2024.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/29/2024]
Abstract
Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.
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Affiliation(s)
| | - Patrice M Becker
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | | | - Jessica Lasky-Su
- Brigham & Women's Hospital and Harvard Medical School, Boston, Mass
| | | | | | | | | | - Talal Chatila
- Boston Children's Hospital and Harvard Medical School, Boston, Mass
| | | | | | | | - Wendy Davidson
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Gang Dong
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Gang Fang
- Icahn School of Medicine at Mount Sinai, New York, NY
| | - Patricia Fulkerson
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | | | - Liming Liang
- Harvard T. H. Chan School of Public Health, Boston, Mass
| | | | - Shuji Ogino
- Brigham & Women's Hospital and Harvard Medical School, Boston, Mass; Harvard T. H. Chan School of Public Health, Boston, Mass; Broad Institute of MIT and Harvard, Boston, Mass
| | | | | | - Eric Schadt
- Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Max A Seibold
- National Jewish Health, Denver, Colo; University of Colorado School of Medicine, Aurora, Colo
| | - Hanno Steen
- Boston Children's Hospital and Harvard Medical School, Boston, Mass
| | - Lisa Wheatley
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Hongmei Zhang
- School of Public Health, University of Memphis, Memphis, Tenn
| | - Alkis Togias
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Kohei Hasegawa
- Massachusetts General Hospital and Harvard Medical School, Boston, Mass
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5
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Rai MF, Collins KH, Lang A, Maerz T, Geurts J, Ruiz-Romero C, June RK, Ramos Y, Rice SJ, Ali SA, Pastrello C, Jurisica I, Thomas Appleton C, Rockel JS, Kapoor M. Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies. Osteoarthritis Cartilage 2024; 32:385-397. [PMID: 38049029 DOI: 10.1016/j.joca.2023.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/22/2023] [Accepted: 11/29/2023] [Indexed: 12/06/2023]
Abstract
OBJECTIVE Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades. DESIGN We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease. RESULTS Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues. CONCLUSIONS Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.
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Affiliation(s)
- Muhammad Farooq Rai
- Department of Anatomy and Cellular Biology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Kelsey H Collins
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Annemarie Lang
- Departments of Orthopaedic Surgery and Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Tristan Maerz
- Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Jeroen Geurts
- Rheumatology, Department of Musculoskeletal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Cristina Ruiz-Romero
- Grupo de Investigación de Reumatología (GIR), Unidad de Proteómica, INIBIC -Hospital Universitario A Coruña, SERGAS, Spain
| | - Ronald K June
- Department of Mechanical & Industrial Engineering, Montana State University, Bozeman, MT, USA
| | - Yolande Ramos
- Dept. Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Sarah J Rice
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Shabana Amanda Ali
- Henry Ford Health + Michigan State University Health Sciences, Detroit, MI, USA
| | - Chiara Pastrello
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, ON, Canada
| | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, ON, Canada; Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, ON, Canada
| | - C Thomas Appleton
- Department of Medicine, University of Western Ontario, London, ON, Canada
| | - Jason S Rockel
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, ON, Canada
| | - Mohit Kapoor
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, ON, Canada.
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6
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van Breugel M, Fehrmann RSN, Bügel M, Rezwan FI, Holloway JW, Nawijn MC, Fontanella S, Custovic A, Koppelman GH. Current state and prospects of artificial intelligence in allergy. Allergy 2023; 78:2623-2643. [PMID: 37584170 DOI: 10.1111/all.15849] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/08/2023] [Accepted: 07/31/2023] [Indexed: 08/17/2023]
Abstract
The field of medicine is witnessing an exponential growth of interest in artificial intelligence (AI), which enables new research questions and the analysis of larger and new types of data. Nevertheless, applications that go beyond proof of concepts and deliver clinical value remain rare, especially in the field of allergy. This narrative review provides a fundamental understanding of the core concepts of AI and critically discusses its limitations and open challenges, such as data availability and bias, along with potential directions to surmount them. We provide a conceptual framework to structure AI applications within this field and discuss forefront case examples. Most of these applications of AI and machine learning in allergy concern supervised learning and unsupervised clustering, with a strong emphasis on diagnosis and subtyping. A perspective is shared on guidelines for good AI practice to guide readers in applying it effectively and safely, along with prospects of field advancement and initiatives to increase clinical impact. We anticipate that AI can further deepen our knowledge of disease mechanisms and contribute to precision medicine in allergy.
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Affiliation(s)
- Merlijn van Breugel
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- MIcompany, Amsterdam, the Netherlands
| | - Rudolf S N Fehrmann
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | | | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health and Care Research Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK
| | - Martijn C Nawijn
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sara Fontanella
- National Heart and Lung Institute, Imperial College London, London, UK
- National Institute for Health and Care Research Imperial Biomedical Research Centre (BRC), London, UK
| | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, UK
- National Institute for Health and Care Research Imperial Biomedical Research Centre (BRC), London, UK
| | - Gerard H Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
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7
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Kwoji ID, Aiyegoro OA, Okpeku M, Adeleke MA. 'Multi-omics' data integration: applications in probiotics studies. NPJ Sci Food 2023; 7:25. [PMID: 37277356 DOI: 10.1038/s41538-023-00199-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 05/22/2023] [Indexed: 06/07/2023] Open
Abstract
The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and the modulation of host immunity through the strengthening of the gut barrier and stimulation of antibodies. These benefits, combined with the need for improved nutraceuticals, have resulted in the extensive characterization of probiotics leading to an outburst of data generated using several 'omics' technologies. The recent development in system biology approaches to microbial science is paving the way for integrating data generated from different omics techniques for understanding the flow of molecular information from one 'omics' level to the other with clear information on regulatory features and phenotypes. The limitations and tendencies of a 'single omics' application to ignore the influence of other molecular processes justify the need for 'multi-omics' application in probiotics selections and understanding its action on the host. Different omics techniques, including genomics, transcriptomics, proteomics, metabolomics and lipidomics, used for studying probiotics and their influence on the host and the microbiome are discussed in this review. Furthermore, the rationale for 'multi-omics' and multi-omics data integration platforms supporting probiotics and microbiome analyses was also elucidated. This review showed that multi-omics application is useful in selecting probiotics and understanding their functions on the host microbiome. Hence, recommend a multi-omics approach for holistically understanding probiotics and the microbiome.
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Affiliation(s)
- Iliya Dauda Kwoji
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa
| | - Olayinka Ayobami Aiyegoro
- Unit for Environmental Sciences and Management, North-West University, Potchefstroom, Northwest, South Africa
| | - Moses Okpeku
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa
| | - Matthew Adekunle Adeleke
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa.
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8
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Garduno A, Cusack R, Leone M, Einav S, Martin-Loeches I. Multi-Omics Endotypes in ICU Sepsis-Induced Immunosuppression. Microorganisms 2023; 11:1119. [PMID: 37317092 DOI: 10.3390/microorganisms11051119] [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: 02/18/2023] [Revised: 04/03/2023] [Accepted: 04/21/2023] [Indexed: 06/16/2023] Open
Abstract
It is evident that the admission of some patients with sepsis and septic shock to hospitals is occurring late in their illness, which has contributed to the increase in poor outcomes and high fatalities worldwide across age groups. The current diagnostic and monitoring procedure relies on an inaccurate and often delayed identification by the clinician, who then decides the treatment upon interaction with the patient. Initiation of sepsis is accompanied by immune system paralysis following "cytokine storm". The unique immunological response of each patient is important to define in terms of subtyping for therapy. The immune system becomes activated in sepsis to produce interleukins, and endothelial cells express higher levels of adhesion molecules. The proportions of circulating immune cells change, reducing regulatory cells and increasing memory cells and killer cells, having long-term effects on the phenotype of CD8 T cells, HLA-DR, and dysregulation of microRNA. The current narrative review seeks to highlight the potential application of multi-omics data integration and immunological profiling at the single-cell level to define endotypes in sepsis and septic shock. The review will consider the parallels and immunoregulatory axis between cancer and immunosuppression, sepsis-induced cardiomyopathy, and endothelial damage. Second, the added value of transcriptomic-driven endotypes will be assessed through inferring regulatory interactions in recent clinical trials and studies reporting gene modular features that inform continuous metrics measuring clinical response in ICU, which can support the use of immunomodulating agents.
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Affiliation(s)
- Alexis Garduno
- Department of Clinical Medicine, Trinity College, University of Dublin, D02 PN40 Dublin, Ireland
| | - Rachael Cusack
- Department of Intensive Care Medicine, St. James's Hospital, James's Street, D08 NHY1 Dublin, Ireland
| | - Marc Leone
- Department of Anesthesia, Intensive Care and Trauma Center, Nord University Hospital, Aix Marseille University, APHM, 13015 Marseille, France
| | - Sharon Einav
- General Intensive Care Unit, Shaare Zedek Medical Center, Jerusalem 23456, Israel
- Faculty of Medicine, Hebrew University, Jerusalem 23456, Israel
| | - Ignacio Martin-Loeches
- Department of Clinical Medicine, Trinity College, University of Dublin, D02 PN40 Dublin, Ireland
- Department of Intensive Care Medicine, St. James's Hospital, James's Street, D08 NHY1 Dublin, Ireland
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9
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Li J, Li L, You P, Wei Y, Xu B. Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer. Semin Cancer Biol 2023; 91:35-49. [PMID: 36868394 DOI: 10.1016/j.semcancer.2023.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 02/21/2023] [Accepted: 02/28/2023] [Indexed: 03/05/2023]
Abstract
Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed of tumor and stromal cellular components; at the genetic levels, they comprise genetically distinct tumor clones; at the phenotypic levels, cells in distinct microenvironmental niches acquire diverse phenotypic features. This heterogeneity affects almost every process of esophageal cancer progression from onset to metastases and recurrence, etc. Intertumoral and intratumoral heterogeneity are major obstacles in the treatment of esophageal cancer, but also offer the potential to manipulate the heterogeneity themselves as a new therapeutic strategy. The high-dimensional, multi-faceted characterization of genomics, epigenomics, transcriptomics, proteomics, metabonomics, etc. of esophageal cancer has opened novel horizons for dissecting tumor heterogeneity. Artificial intelligence especially machine learning and deep learning algorithms, are able to make decisive interpretations of data from multi-omics layers. To date, artificial intelligence has emerged as a promising computational tool for analyzing and dissecting esophageal patient-specific multi-omics data. This review provides a comprehensive review of tumor heterogeneity from a multi-omics perspective. Especially, we discuss the novel techniques single-cell sequencing and spatial transcriptomics, which have revolutionized our understanding of the cell compositions of esophageal cancer and allowed us to determine novel cell types. We focus on the latest advances in artificial intelligence in integrating multi-omics data of esophageal cancer. Artificial intelligence-based multi-omics data integration computational tools exert a key role in tumor heterogeneity assessment, which will potentially boost the development of precision oncology in esophageal cancer.
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Affiliation(s)
- Junyu Li
- Department of Radiation Oncology, Jiangxi Cancer Hospital, Nanchang 330029, Jiangxi, China; Jiangxi Health Committee Key (JHCK) Laboratory of Tumor Metastasis, Jiangxi Cancer Hospital, Nanchang 330029, Jiangxi, China
| | - Lin Li
- Department of Thoracic Oncology, Jiangxi Cancer Hospital, Nanchang 330029, Jiangxi, China
| | - Peimeng You
- Nanchang University, Department of Radiation Oncology, Jiangxi Cancer Hospital, Nanchang 330029, Jiangxi, China
| | - Yiping Wei
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China.
| | - Bin Xu
- Jiangxi Health Committee Key (JHCK) Laboratory of Tumor Metastasis, Jiangxi Cancer Hospital, Nanchang 330029, Jiangxi, China.
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10
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The Role of Systems Biology in Deciphering Asthma Heterogeneity. LIFE (BASEL, SWITZERLAND) 2022; 12:life12101562. [PMID: 36294997 PMCID: PMC9605413 DOI: 10.3390/life12101562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/28/2022] [Accepted: 10/04/2022] [Indexed: 11/17/2022]
Abstract
Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.
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11
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Logotheti M, Agioutantis P, Katsaounou P, Loutrari H. Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma. J Pers Med 2021; 11:jpm11121299. [PMID: 34945771 PMCID: PMC8707330 DOI: 10.3390/jpm11121299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/13/2021] [Accepted: 11/24/2021] [Indexed: 12/12/2022] Open
Abstract
Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients' classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes-endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota-host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.
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Affiliation(s)
- Marianthi Logotheti
- G.P. Livanos and M. Simou Laboratories, 1st Department of Critical Care Medicine & Pulmonary Services, Evangelismos Hospital, Medical School, National Kapodistrian University of Athens, 3 Ploutarchou Str., 10675 Athens, Greece; (M.L.); (P.A.)
- Biotechnology Laboratory, School of Chemical Engineering, National Technical University of Athens, 5 Iroon Polytechniou Str., Zografou Campus, 15780 Athens, Greece
| | - Panagiotis Agioutantis
- G.P. Livanos and M. Simou Laboratories, 1st Department of Critical Care Medicine & Pulmonary Services, Evangelismos Hospital, Medical School, National Kapodistrian University of Athens, 3 Ploutarchou Str., 10675 Athens, Greece; (M.L.); (P.A.)
| | - Paraskevi Katsaounou
- Pulmonary Dept First ICU, Evangelismos Hospital, Medical School, National Kapodistrian University of Athens, Ipsilantou 45-7, 10675 Athens, Greece;
| | - Heleni Loutrari
- G.P. Livanos and M. Simou Laboratories, 1st Department of Critical Care Medicine & Pulmonary Services, Evangelismos Hospital, Medical School, National Kapodistrian University of Athens, 3 Ploutarchou Str., 10675 Athens, Greece; (M.L.); (P.A.)
- Correspondence:
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Abstract
PURPOSE OF REVIEW Asthma is the most common chronic disease of childhood. Investigations of the lower and upper airway microbiomes have significantly progressed over recent years, and their roles in pediatric asthma are becoming increasingly clear. RECENT FINDINGS Early studies identified the existence of upper and lower airway microbiomes, including imbalances in both associated with pediatric asthma. The infant airway microbiome may offer predictive value for the development of asthma in later childhood, and it may also be influenced by external factors such as respiratory viral illness. The airway microbiome has also been associated with the clinical course of asthma, including rates of exacerbation and level of control. Advances in -omics sciences have enabled improved identification of the airway microbiome's relationships with host response and function in children with asthma. Investigations are now moving toward the application of the above findings to explore risk modification and treatment options. SUMMARY The airway microbiome provides an intriguing window into pediatric asthma, offering insights into asthma diagnosis, clinical course, and perhaps treatment. Further investigation is needed to solidify these associations and translate research findings into clinical practice.
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Affiliation(s)
- Rhia Shah
- Division of Pulmonary Medicine, Department of Pediatrics,
Icahn School of Medicine at Mount Sinai, New York, NY
| | - Supinda Bunyavanich
- Division of Allergy and Immunology, Department of
Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Genetics and Genomic Sciences, Icahn School
of Medicine at Mount Sinai, New York, NY
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Agache I, Eguiluz‐Gracia I, Cojanu C, Laculiceanu A, Giacco S, Zemelka‐Wiacek M, Kosowska A, Akdis CA, Jutel M. Advances and highlights in asthma in 2021. Allergy 2021; 76:3390-3407. [PMID: 34392546 DOI: 10.1111/all.15054] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 08/09/2021] [Indexed: 12/12/2022]
Abstract
Last year brought a significant advance in asthma management, unyielding to the pressure of the pandemics. Novel key findings in asthma pathogenesis focus on the resident cell compartment, epigenetics and the innate immune system. The precision immunology unbiased approach was supplemented with novel tools and greatly facilitated by the use of artificial intelligence. Several randomised clinical trials and good quality real-world evidence shed new light on asthma treatment and supported the revision of several asthma guidelines (GINA, Expert Panel Report 3, ERS/ATS guidelines on severe asthma) and the conception of new ones (EAACI Guidelines for the use of biologicals in severe asthma). Integrating asthma management within the broader context of Planetary Health has been put forward. In this review, recently published articles and clinical trials are summarised and discussed with the goal to provide clinicians and researchers with a concise update on asthma research from a translational perspective.
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Affiliation(s)
- Ioana Agache
- Faculty of Medicine Transylvania University Brasov Romania
| | - Ibon Eguiluz‐Gracia
- Allergy Unit IBIMA‐Regional University Hospital of MalagaUMA, RETICS ARADyALBIONAND Malaga Spain
| | | | | | - Stefano Giacco
- Department of Medical Sciences and Public Health University of Cagliari Cagliari Italy
| | | | - Anna Kosowska
- Department of Clinical Immunology Wroclaw Medical University Wroclaw Poland
- All‐MED Medical Research Institute Wroclaw Poland
| | - Cezmi A. Akdis
- Swiss Institute of Allergy and Asthma Research (SIAF) University of Zurich Davos Switzerland
| | - Marek Jutel
- Department of Clinical Immunology Wroclaw Medical University Wroclaw Poland
- All‐MED Medical Research Institute Wroclaw Poland
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