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Perea L, Faner R, Chalmers JD, Sibila O. Pathophysiology and genomics of bronchiectasis. Eur Respir Rev 2024; 33:240055. [PMID: 38960613 PMCID: PMC11220622 DOI: 10.1183/16000617.0055-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/02/2024] [Indexed: 07/05/2024] Open
Abstract
Bronchiectasis is a complex and heterogeneous inflammatory chronic respiratory disease with an unknown cause in around 30-40% of patients. The presence of airway infection together with chronic inflammation, airway mucociliary dysfunction and lung damage are key components of the vicious vortex model that better describes its pathophysiology. Although bronchiectasis research has significantly increased over the past years and different endotypes have been identified, there are still major gaps in the understanding of the pathophysiology. Genomic approaches may help to identify new endotypes, as has been shown in other chronic airway diseases, such as COPD.Different studies have started to work in this direction, and significant contributions to the understanding of the microbiome and proteome diversity have been made in bronchiectasis in recent years. However, the systematic application of omics approaches to identify new molecular insights into the pathophysiology of bronchiectasis (endotypes) is still limited compared with other respiratory diseases.Given the complexity and diversity of these technologies, this review describes the key components of the pathophysiology of bronchiectasis and how genomics can be applied to increase our knowledge, including the study of new techniques such as proteomics, metabolomics and epigenomics. Furthermore, we propose that the novel concept of trained innate immunity, which is driven by microbiome exposures leading to epigenetic modifications, can complement our current understanding of the vicious vortex. Finally, we discuss the challenges, opportunities and implications of genomics application in clinical practice for better patient stratification into new therapies.
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Affiliation(s)
- Lidia Perea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Rosa Faner
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias M.P. (CIBERES), Barcelona, Spain
| | - James D Chalmers
- Division of Molecular and Clinical Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Oriol Sibila
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias M.P. (CIBERES), Barcelona, Spain
- Respiratory Department, Hospital Clínic, University of Barcelona, Barcelona, Spain
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2
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Buschur KL, Pottinger TD, Vogel-Claussen J, Powell CA, Aguet F, Allen NB, Ardlie K, Bluemke DA, Durda P, Hermann EA, Hoffman EA, Lima JA, Liu Y, Malinsky D, Manichaikul A, Motahari A, Post WS, Prince MR, Rich SS, Rotter JI, Smith BM, Tracy RP, Watson K, Winther HB, Lappalainen T, Barr RG. Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc 2024; 21:884-894. [PMID: 38335160 PMCID: PMC11160125 DOI: 10.1513/annalsats.202305-417oc] [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: 05/08/2023] [Accepted: 02/09/2024] [Indexed: 02/12/2024] Open
Abstract
Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.
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Affiliation(s)
| | | | - Jens Vogel-Claussen
- Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | | | - Francois Aguet
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Norrina B. Allen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Kristin Ardlie
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - David A. Bluemke
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, Vermont
| | | | - Eric A. Hoffman
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - João A.C. Lima
- Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Baltimore, Maryland
| | - Yongmei Liu
- Department of Medicine, Duke University Medical Center, Durham, North Carolina
| | | | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Amin Motahari
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Baltimore, Maryland
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Benjamin M. Smith
- Department of Medicine
- Research Institute, McGill University Health Center, Montreal, Québec, Canada
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, Vermont
| | - Karol Watson
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California; and
| | - Hinrich B. Winther
- Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Tuuli Lappalainen
- Department of Biostatistics
- Department of Systems Biology, Columbia University Medical Center, New York, New York
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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3
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Shen XR, Liu YY, Qian RQ, Zhang WY, Huang JA, Zhang XQ, Zeng DX. Circular RNA Expression of Peripheral Blood Mononuclear Cells Associated with Risk of Acute Exacerbation in Smoking Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis 2024; 19:789-797. [PMID: 38524397 PMCID: PMC10961080 DOI: 10.2147/copd.s448759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/13/2024] [Indexed: 03/26/2024] Open
Abstract
Purpose Circular RNAs (circRNAs) are newly identified endogenous non-coding RNAs that function as crucial gene modulators in the development of several diseases. By assessing the expression levels of circRNAs in peripheral blood mononuclear cells (PBMCs) from patients with chronic obstructive pulmonary disease (COPD), this study attempted to find new biomarkers for COPD screening. Patients and Methods We confirmed altered circRNA expression in PBMCs of COPD (n=41) vs controls (n=29). Further analysis focused on the highest and lowest circRNA expression levels. The T-test is used to assess the statistical variances in circRNAs among COPD patients in the smoking and non-smoking cohorts. Additionally, among smokers, the Spearman correlation test assesses the association between circRNAs and clinical indicators. Results Two circRNAs, hsa_circ_0042590 and hsa_circ_0049875, that were highly upregulated and downregulated in PBMCs from COPD patients were identified and verified. Smokers with COPD had lower hsa_circ_0042590 and higher hsa_circ_0049875, in comparison to non-smokers. There was a significant correlation (r=0.52, P<0.01) between the number of acute exacerbations (AEs) that smokers with COPD experienced in the previous year and the following year (r=0.67, P<0.001). Moreover, hsa_circ_0049875 was connected to the quantity of AEs in the year prior (r=0.68, P<0.0001) as well as the year after (r=0.72, P<0.0001). AUC: 0.79, 95% CI: 0.1210-0.3209, P<0.0001) for hsa_circ_0049875 showed a strong diagnostic value for COPD, according to ROC curve analysis. Hsa_circ_0042590 showed a close second with an AUC of 0.83 and 95% CI: -0.1972--0.0739 (P <0.0001). Conclusion This research identified a strong correlation between smoking and hsa_circ_0049875 and hsa_circ_0042590 in COPD PBMCs. The number of AEs in the preceding and succeeding years was substantially linked with the existence of hsa_circ_0042590 and hsa_circ_0049875 in COPD patients who smoke. Additionally, according to our research, hsa_circ_0049875 and hsa_circ_0042590 may be valuable biomarkers for COPD diagnosis.
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Affiliation(s)
- Xu-Rui Shen
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Jiangsu, People’s Republic of China
| | - Ying-Ying Liu
- Department of Pulmonary and Critical Care Medicine, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, People’s Republic of China
| | - Rui-Qi Qian
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Jiangsu, People’s Republic of China
| | - Wei-Yun Zhang
- Department of Pulmonary and Critical Care Medicine, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, People’s Republic of China
| | - Jian-An Huang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Jiangsu, People’s Republic of China
| | - Xiu-Qin Zhang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Jiangsu, People’s Republic of China
| | - Da-Xiong Zeng
- Department of Pulmonary and Critical Care Medicine, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, People’s Republic of China
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4
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Huang W, Luo T, Lan M, Zhou W, Zhang M, Wu L, Lu Z, Fan L. Identification and Characterization of a ceRNA Regulatory Network Involving LINC00482 and PRRC2B in Peripheral Blood Mononuclear Cells: Implications for COPD Pathogenesis and Diagnosis. Int J Chron Obstruct Pulmon Dis 2024; 19:419-430. [PMID: 38348310 PMCID: PMC10860591 DOI: 10.2147/copd.s437046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 02/01/2024] [Indexed: 02/15/2024] Open
Abstract
Purpose Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, characterized by intense lung infiltrations of immune cells (macrophages and monocytes). While existing studies have highlighted the crucial role of the competitive endogenous RNA (ceRNA) regulatory network in COPD development, the complexity and characteristics of the ceRNA network in monocytes remain unexplored. Methods We downloaded messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) microarray data from GSE146560, GSE102915, and GSE71220 in the Gene Expression Omnibus (GEO) database. This data was used to identify differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs). Predicted miRNAs that bind to DElncRNAs were intersected with DEmiRNAs, forming a set of intersecting miRNAs. This set was then used to predict potential binding mRNAs, intersected with DEmRNAs, and underwent functional enrichment analysis using R software and the STRING database. The resulting triple regulatory network and hub genes were constructed using Cytoscape. Comparative Toxicomics Database (CTD) was utilized for disease correlation predictions, and ROC curve analysis assessed diagnostic accuracy. Results Our study identified 5 lncRNAs, 4 miRNAs, and 149 mRNAs as differentially expressed. A lncRNA-miRNA-mRNA regulatory network was constructed, and hub genes were selected through hub analysis. Enrichment analysis highlighted terms related to cell movement and gene expression regulation. We established a LINC00482-has-miR-6088-PRRC2B ceRNA network with diagnostic relevance for COPD. ROC analysis demonstrated the diagnostic value of these genes. Moreover, a positive correlation between LINC00482 and PRRC2B expression was observed in COPD PBMCs. The CTD database indicated their involvement in inflammatory responses. Conclusion In summary, our study not only identified pivotal hub genes in peripheral blood mononuclear cells (PBMCs) of COPD but also constructed a ceRNA regulatory network. This contributes to understanding the pathophysiological processes of COPD through bioinformatics analysis, expanding our knowledge of COPD, and providing a foundation for potential diagnostic and therapeutic targets for COPD.
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Affiliation(s)
- Wenjie Huang
- Department of Reproductive Medicine, Guangzhou Women and Children’s Medical Center Liuzhou Hospital, Liuzhou, Guangxi, 545616, People’s Republic of China
- Department of Reproductive Medicine, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, Guangxi, 545001, People’s Republic of China
| | - Ting Luo
- Department of Reproductive Medicine, Guangzhou Women and Children’s Medical Center Liuzhou Hospital, Liuzhou, Guangxi, 545616, People’s Republic of China
- Department of Reproductive Medicine, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, Guangxi, 545001, People’s Republic of China
| | - Mengqiu Lan
- Clinical Laboratory Science, Liuzhou Municipal Liutie Central Hospital, Liuzhou, Guangxi, 545007, People’s Republic of China
| | - Wenting Zhou
- Department of Reproductive Medicine, Guangzhou Women and Children’s Medical Center Liuzhou Hospital, Liuzhou, Guangxi, 545616, People’s Republic of China
- Department of Reproductive Medicine, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, Guangxi, 545001, People’s Republic of China
| | - Ming Zhang
- Department of Reproductive Medicine, Guangzhou Women and Children’s Medical Center Liuzhou Hospital, Liuzhou, Guangxi, 545616, People’s Republic of China
- Department of Reproductive Medicine, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, Guangxi, 545001, People’s Republic of China
| | - Lihong Wu
- Clinical Laboratory Science, Liuzhou Municipal Liutie Central Hospital, Liuzhou, Guangxi, 545007, People’s Republic of China
| | - Zhenni Lu
- Clinical Laboratory Science, Liuzhou Municipal Liutie Central Hospital, Liuzhou, Guangxi, 545007, People’s Republic of China
| | - Li Fan
- Department of Reproductive Medicine, Guangzhou Women and Children’s Medical Center Liuzhou Hospital, Liuzhou, Guangxi, 545616, People’s Republic of China
- Department of Reproductive Medicine, Liuzhou Maternity and Child Healthcare Hospital, Liuzhou, Guangxi, 545001, People’s Republic of China
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5
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Maiorino E, De Marzio M, Xu Z, Yun JH, Chase RP, Hersh CP, Weiss ST, Silverman EK, Castaldi PJ, Glass K. Joint clinical and molecular subtyping of COPD with variational autoencoders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.19.23294298. [PMID: 38260473 PMCID: PMC10802661 DOI: 10.1101/2023.08.19.23294298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a complex, heterogeneous disease. Traditional subtyping methods generally focus on either the clinical manifestations or the molecular endotypes of the disease, resulting in classifications that do not fully capture the disease's complexity. Here, we bridge this gap by introducing a subtyping pipeline that integrates clinical and gene expression data with variational autoencoders. We apply this methodology to the COPDGene study, a large study of current and former smoking individuals with and without COPD. Our approach generates a set of vector embeddings, called Personalized Integrated Profiles (PIPs), that recapitulate the joint clinical and molecular state of the subjects in the study. Prediction experiments show that the PIPs have a predictive accuracy comparable to or better than other embedding approaches. Using trajectory learning approaches, we analyze the main trajectories of variation in the PIP space and identify five well-separated subtypes with distinct clinical phenotypes, expression signatures, and disease outcomes. Notably, these subtypes are more robust to data resampling compared to those identified using traditional clustering approaches. Overall, our findings provide new avenues to establish fine-grained associations between the clinical characteristics, molecular processes, and disease outcomes of COPD.
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Affiliation(s)
- Enrico Maiorino
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Margherita De Marzio
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Zhonghui Xu
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Jeong H. Yun
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Robert P. Chase
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School
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6
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Imamoto T, Kawasaki T, Sato H, Tatsumi K, Ishii D, Yoshioka K, Hasegawa Y, Ohara O, Suzuki T. Different Transcriptome Features of Peripheral Blood Mononuclear Cells in Non-Emphysematous Chronic Obstructive Pulmonary Disease. Int J Mol Sci 2023; 25:66. [PMID: 38203236 PMCID: PMC10779039 DOI: 10.3390/ijms25010066] [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: 11/16/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
Non-emphysematous chronic obstructive pulmonary disease (COPD), which is defined based on chest computed tomography findings, presented different transcriptome features of peripheral blood mononuclear cells (PBMCs) compared with emphysematous COPD. Enrichment analysis of transcriptomic data in COPD demonstrated that the "Hematopoietic cell lineage" pathway in Kyoto Encyclopedia of Genes and Genomes pathway analysis was highly upregulated, suggesting that cellular dynamic dysregulation in COPD lungs is affected by pathologically modified PBMCs. The differentially expressed genes (DEGs) upregulated in PBMCs reflected the disease state of non-emphysematous COPD. Upregulated DEGs such as XCL1, PRKCZ, TMEM102, CD200R1, and AQP1 activate T lymphocytes and eosinophils. Upregulating keratan sulfate biosynthesis and metabolic processes is associated with protection against the destruction of the distal airways. ITGA3 upregulation augments interactions with extracellular matrix proteins, and COL6A1 augments the profibrotic mast cell phenotype during alveolar collagen VI deposition. Upregulating HSPG2, PDGFRB, and PAK4 contributes to the thickening of the airway wall, and upregulating SERPINF1 expression explains the better-preserved vascular bed. Therefore, gene expression and pathway analysis in PBMCs in patients with non-emphysematous COPD represented type 2 immune responses and airway remodeling features. Therefore, these patients have asthmatic potential despite no clinical signs of asthma, in contrast to those with emphysematous COPD.
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Affiliation(s)
- Takuro Imamoto
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Takeshi Kawasaki
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Hironori Sato
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Koichiro Tatsumi
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Daisuke Ishii
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Keiichiro Yoshioka
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
| | - Yoshinori Hasegawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Chiba 292-0818, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Chiba 292-0818, Japan
| | - Takuji Suzuki
- Department of Respirology, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
- Synergy Institute for Futuristic Mucosal Vaccine Research and Development, Chiba University, Chiba 260-8670, Japan
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7
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Kapellos TS, Baßler K, Fujii W, Nalkurthi C, Schaar AC, Bonaguro L, Pecht T, Galvao I, Agrawal S, Saglam A, Dudkin E, Frishberg A, de Domenico E, Horne A, Donovan C, Kim RY, Gallego-Ortega D, Gillett TE, Ansari M, Schulte-Schrepping J, Offermann N, Antignano I, Sivri B, Lu W, Eapen MS, van Uelft M, Osei-Sarpong C, van den Berge M, Donker HC, Groen HJM, Sohal SS, Klein J, Schreiber T, Feißt A, Yildirim AÖ, Schiller HB, Nawijn MC, Becker M, Händler K, Beyer M, Capasso M, Ulas T, Hasenauer J, Pizarro C, Theis FJ, Hansbro PM, Skowasch D, Schultze JL. Systemic alterations in neutrophils and their precursors in early-stage chronic obstructive pulmonary disease. Cell Rep 2023; 42:112525. [PMID: 37243592 PMCID: PMC10320832 DOI: 10.1016/j.celrep.2023.112525] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/18/2023] [Accepted: 05/01/2023] [Indexed: 05/29/2023] Open
Abstract
Systemic inflammation is established as part of late-stage severe lung disease, but molecular, functional, and phenotypic changes in peripheral immune cells in early disease stages remain ill defined. Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small-airway inflammation, emphysema, and severe breathing difficulties. Using single-cell analyses we demonstrate that blood neutrophils are already increased in early-stage COPD, and changes in molecular and functional neutrophil states correlate with lung function decline. Assessing neutrophils and their bone marrow precursors in a murine cigarette smoke exposure model identified similar molecular changes in blood neutrophils and precursor populations that also occur in the blood and lung. Our study shows that systemic molecular alterations in neutrophils and their precursors are part of early-stage COPD, a finding to be further explored for potential therapeutic targets and biomarkers for early diagnosis and patient stratification.
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Affiliation(s)
- Theodore S Kapellos
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Kevin Baßler
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Wataru Fujii
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Christina Nalkurthi
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Anna C Schaar
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Lorenzo Bonaguro
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Tal Pecht
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Izabela Galvao
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Shobhit Agrawal
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Adem Saglam
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Erica Dudkin
- Computational Life Sciences, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Amit Frishberg
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Elena de Domenico
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Arik Horne
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Chantal Donovan
- University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; Immune Health, Hunter Medical Research Institute, New Lambton and The University of Newcastle, Newcastle, NSW 2305, Australia
| | - Richard Y Kim
- University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; Immune Health, Hunter Medical Research Institute, New Lambton and The University of Newcastle, Newcastle, NSW 2305, Australia
| | - David Gallego-Ortega
- School of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, Garvan Institute of Medical Research, and St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW 2010, Australia
| | - Tessa E Gillett
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; GRIAC Research Institute, University Medical Center Groningen, 9700 RB Groningen, the Netherlands
| | - Meshal Ansari
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Jonas Schulte-Schrepping
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Nina Offermann
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Ignazio Antignano
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Burcu Sivri
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Wenying Lu
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Mathew S Eapen
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Martina van Uelft
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Collins Osei-Sarpong
- Immunogenomics & Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Maarten van den Berge
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Hylke C Donker
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Harry J M Groen
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Sukhwinder S Sohal
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Johanna Klein
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Tina Schreiber
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Andreas Feißt
- University Clinics for Radiology, University Hospital Bonn, 53127 Bonn, Germany
| | - Ali Önder Yildirim
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Herbert B Schiller
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Martijn C Nawijn
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; GRIAC Research Institute, University Medical Center Groningen, 9700 RB Groningen, the Netherlands
| | - Matthias Becker
- Modular HPC and AI, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Kristian Händler
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany; Institute of Human Genetics, University of Lübeck, 23562 Lübeck, Germany
| | - Marc Beyer
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany; Immunogenomics & Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Melania Capasso
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Thomas Ulas
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Jan Hasenauer
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany; Computational Life Sciences, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Carmen Pizarro
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Fabian J Theis
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Philip M Hansbro
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Dirk Skowasch
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Joachim L Schultze
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany.
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8
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Jiang J, Shang J. Feature Screening for High-Dimensional Variable Selection in Generalized Linear Models. ENTROPY (BASEL, SWITZERLAND) 2023; 25:851. [PMID: 37372195 DOI: 10.3390/e25060851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 04/20/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023]
Abstract
The two-stage feature screening method for linear models applies dimension reduction at first stage to screen out nuisance features and dramatically reduce the dimension to a moderate size; at the second stage, penalized methods such as LASSO and SCAD could be applied for feature selection. A majority of subsequent works on the sure independent screening methods have focused mainly on the linear model. This motivates us to extend the independence screening method to generalized linear models, and particularly with binary response by using the point-biserial correlation. We develop a two-stage feature screening method called point-biserial sure independence screening (PB-SIS) for high-dimensional generalized linear models, aiming for high selection accuracy and low computational cost. We demonstrate that PB-SIS is a feature screening method with high efficiency. The PB-SIS method possesses the sure independence property under certain regularity conditions. A set of simulation studies are conducted and confirm the sure independence property and the accuracy and efficiency of PB-SIS. Finally we apply PB-SIS to one real data example to show its effectiveness.
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Affiliation(s)
- Jinzhu Jiang
- Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403, USA
| | - Junfeng Shang
- Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403, USA
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9
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Zhang J, Cheng H, Di Narzo A, Zhu Y, Xie S, Shao X, Zhang Z, Chung SK, Hao K. Profiling Microbiota from Multiple Sites in the Respiratory Tract to Identify a Biomarker for PM 2.5 Nitrate Exposure-Induced Pulmonary Damages. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:7346-7357. [PMID: 37133311 DOI: 10.1021/acs.est.2c08807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The microbiota present in the respiratory tract (RT) responds to environmental stimuli and engages in a continuous interaction with the host immune system to maintain homeostasis. A total of 40 C57BL/6 mice were divided into four groups and exposed to varying concentrations of PM2.5 nitrate aerosol and clean air. After 10 weeks of exposure, assessments were conducted on the lung and airway microbiome, lung functions, and pulmonary inflammation. Additionally, we analyzed data from both mouse and human respiratory tract (RT) microbiomes to identify possible biomarkers for PM2.5 exposure-induced pulmonary damages. On average, 1.5 and 13.5% inter-individual microbiome variations in the lung and airway were explained by exposure, respectively. In the airway, among the 60 bacterial OTUs (operational taxonomic units) > 0.05% proportion, 40 OTUs were significantly affected by PM2.5 exposure (FDR ≤ 10%). Further, the airway microbiome was associated with peak expiratory flow (PEF) (p = 0.003), pulmonary neutrophil counts (p = 0.01), and alveolar 8-OHdG oxidative lesions (p = 0.0078). The Clostridiales order bacteria showed the strongest signals. For example, the o_Clostridiales;f_;g_ OTU was elevated by PM2.5 nitrate exposure (p = 4.98 × 10-5) and negatively correlated with PEF (r = -0.585 and p = 2.4 × 10-4). It was also associated with the higher pulmonary neutrophil count (p = 8.47 × 10-5) and oxidative lesion (p = 7.17 × 10-3). In human data, we confirmed the association of airway Clostridiales order bacteria with PM2.5 exposure and lung function. For the first time, this study characterizes the impact of PM2.5 exposure on the microbiome of multiple sites in the respiratory tract (RT) and its relevance to airflow obstructive diseases. By analyzing data from both humans and mice, we have identified bacteria belonging to the Clostridiales order as a promising biomarker for PM2.5 exposure-induced decline in pulmonary function and inflammation.
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Affiliation(s)
- Jushan Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai 200072, China
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
- College of Environmental Science and Engineering, Tongji University, Shanghai 200072, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029-6574, United States
| | - Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029-6574, United States
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Shuanshuan Xie
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Xiaowen Shao
- Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029-6574, United States
| | - Sookja Kim Chung
- Medical Faculty, Macau University of Science and Technology, Taipa, Macau SAR 999078, China
| | - Ke Hao
- College of Environmental Science and Engineering, Tongji University, Shanghai 200072, China
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029-6574, United States
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10
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Matson SM, Sundar IK. The Promise of Liquid Biopsies: Extracellular Vesicle microRNAs Open the Door to Future Study in Lung Disease. Am J Respir Crit Care Med 2023; 207:7-9. [PMID: 36044703 PMCID: PMC9952863 DOI: 10.1164/rccm.202208-1592ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Affiliation(s)
- Scott M. Matson
- Department of Internal MedicineUniversity of Kansas Medical CenterKansas City, Kansas
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11
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Negewo NA, Gibson PG, Simpson JL, McDonald VM, Baines KJ. Severity of Lung Function Impairment Drives Transcriptional Phenotypes of COPD and Relates to Immune and Metabolic Processes. Int J Chron Obstruct Pulmon Dis 2023; 18:273-287. [PMID: 36942279 PMCID: PMC10024507 DOI: 10.2147/copd.s388297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 02/15/2023] [Indexed: 03/16/2023] Open
Abstract
Purpose This study sought to characterize transcriptional phenotypes of COPD through unsupervised clustering of sputum gene expression profiles, and further investigate mechanisms underlying the characteristics of these clusters. Patients and methods Induced sputum samples were collected from patients with stable COPD (n = 72) and healthy controls (n = 15). Induced sputum was collected for inflammatory cell counts, and RNA extracted. Transcriptional profiles were generated (Illumina Humanref-8 V2) and analyzed by GeneSpring GX14.9.1. Unsupervised hierarchical clustering and differential gene expression analysis were performed, and gene alterations validated in the ECLIPSE dataset (GSE22148). Results We identified 2 main clusters (Cluster 1 [n = 35] and Cluster 2 [n = 37]), which further divided into 4 sub-clusters (Sub-clusters 1.1 [n = 14], 1.2 [n = 21], 2.1 [n = 20] and 2.2 [n = 17]). Compared with Cluster 1, Cluster 2 was associated with significantly lower lung function (p = 0.014), more severe disease (p = 0.009) and breathlessness (p = 0.035), and increased sputum neutrophils (p = 0.031). Sub-cluster 1.1 had significantly higher proportion of people with comorbid cardiovascular disease compared to the other 3 sub-clusters (92.5% vs 57.1%, 50% and 52.9%, p < 0.013). Through supervised analysis we determined that degree of airflow limitation (GOLD stage) was the predominant factor driving gene expression differences in our transcriptional clusters. There were 452 genes (adjusted p < 0.05 and ≥2 fold) altered in GOLD stage 3 and 4 versus 1 and 2, of which 281 (62%) were also found to be significantly expressed between these GOLD stages in the ECLIPSE data set (GSE22148). Differentially expressed genes were largely downregulated in GOLD stages 3 and 4 and connected in 5 networks relating to lipoprotein and cholesterol metabolism; metabolic processes in oxidation/reduction and mitochondrial function; antigen processing and presentation; regulation of complement activation and innate immune responses; and immune and metabolic processes. Conclusion Severity of lung function drives 2 distinct transcriptional phenotypes of COPD and relates to immune and metabolic processes.
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Affiliation(s)
- Netsanet A Negewo
- Immune Health Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Peter G Gibson
- Centre of Excellence in Treatable Traits, University of Newcastle, New Lambton Heights, NSW, Australia
- Department of Respiratory and Sleep Medicine, John Hunter Hospital, Newcastle, NSW, Australia
- Asthma and Breathing Research Centre, Hunter Medical Research Centre, New Lambton Heights, NSW, Australia
| | - Jodie L Simpson
- Immune Health Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Vanessa M McDonald
- Centre of Excellence in Treatable Traits, University of Newcastle, New Lambton Heights, NSW, Australia
- Department of Respiratory and Sleep Medicine, John Hunter Hospital, Newcastle, NSW, Australia
- Asthma and Breathing Research Centre, Hunter Medical Research Centre, New Lambton Heights, NSW, Australia
- School of Nursing and Midwifery, The University of Newcastle, Callaghan, NSW, Australia
| | - Katherine J Baines
- Immune Health Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Correspondence: Katherine J Baines, Hunter Medical Research Institute, Level 2 East Wing, Locked Bag 1000, New Lambton Heights, NSW, 2305, Australia, Tel +61 2 40420090, Fax +61 2 40420046, Email
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12
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Liu S, Li Y, Wei X, Adi D, Wang YT, Han M, Liu F, Chen BD, Li XM, Yang YN, Fu ZY, Ma YT. Genetic analysis of DNA methylation in dyslipidemia: a case-control study. PeerJ 2022; 10:e14590. [PMID: 36570009 PMCID: PMC9774006 DOI: 10.7717/peerj.14590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Coronary heart disease has become the leading cause of death in developed countries, and dyslipidemia is closely associated with the risk of cardiovascular disease. Dyslipidemia is caused by the abnormal regulation of several genes and signaling pathways, and dyslipidemia is influenced mainly by genetic variation. AMFR, FBXW7, INSIG1, INSIG2, and MBTPS1 genes are associated with lipid metabolism. In a recent GWAS study, the GRINA gene has been reported to be associated with dyslipidemia, but its molecular mechanism has not been thoroughly investigated. The correlation between the DNA methylation of these genes and lipid metabolism has not been studied. This study aimed to examine the relationship between the DNA methylation of these genes and the risk of dyslipidemia by comparing the methylation levels of dyslipidemia and control samples. Methods A case-control research method was used in this study. The patient's blood samples were collected at the Heart Center of the First Affiliated Hospital of Xinjiang Medical University. In the Xinjiang Han population, 100 cases of hyperlipidemia and 80 cases of the control group were selected. The two groups were age and gender-matched. Quantitative methylation analysis of CpG sites in the gene promoter regions of six genes was performed by Solexa high-throughput sequencing. Results The DNA methylation levels of 23 CpG sites in six genes were shown to be associated with hyperlipidemia, and a total of 20 DNA methylation haplotypes showed statistically significant differences between the two groups. When compared with the control group, the dyslipidemia group had significantly higher levels of methylation in the GRINA gene (2.68 vs 2.36, P = 0.04). Additionally, we also discovered a significant methylation haplotype of GRINA (P = 0.017). Conclusion The findings of this study reveal that the DNA methylation of GRINA increases the risk for dyslipidemia in humans.
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Affiliation(s)
- Shuai Liu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yang Li
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Xian Wei
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Dilare Adi
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yong-Tao Wang
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Min Han
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Fen Liu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Bang-Dang Chen
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Xiao-Mei Li
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yi-Ning Yang
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Zhen-Yan Fu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yi-Tong Ma
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
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Zhu Y, Han Y, Almuntashiri S, Dutta S, Wang X, Owen CA, Zhang D. Dysregulation of miR-103a Mediates Cigarette Smoking-induced Lipid-laden Macrophage Formation. Am J Respir Cell Mol Biol 2022; 67:695-707. [PMID: 36066909 PMCID: PMC9743184 DOI: 10.1165/rcmb.2022-0202oc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 09/02/2022] [Indexed: 12/15/2022] Open
Abstract
Cigarette smoke (CS) is considered a major risk factor for chronic obstructive pulmonary disease (COPD) that is currently the third leading cause of death in the United States. Studies have indicated that patients with COPD have elevated blood low-density lipoprotein levels, which may contribute to the dysregulation of lipid metabolism. Accumulating data show that microRNAs (miRNAs) are involved in various human diseases. However, the role of microRNAs in the pathogenesis of COPD remains poorly defined. In this study, we found that miR-103a expression was significantly reduced in alveolar macrophages from smokers and patients with COPD versus that in alveolar macrophages from nonsmokers. Our data indicated that reactive oxygen species negatively regulate miR-103a in macrophages. Functionally, miR-103a modulates the expressions of genes involved in lipid metabolism and directly targets low-density lipoprotein receptors in macrophages. Furthermore, overexpression of miR-103a suppressed the accumulation of lipid droplets and reduced the reactive oxygen species, both in vitro and in vivo. Taken together, our findings indicate that downregulation of miR-103a contributes to cigarette smoke-induced lipid-laden macrophage formation and plays a critical role in lipid homeostasis in lung macrophages in the pathogenesis of COPD.
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Affiliation(s)
- Yin Zhu
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
| | - Yohan Han
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
| | - Sultan Almuntashiri
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
- Department of Clinical Pharmacy, College of Pharmacy, University of Hail, Hail, Saudi Arabia
| | - Saugata Dutta
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
| | - Xiaoyun Wang
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
| | - Caroline A. Owen
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and
| | - Duo Zhang
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood Veterans Affairs Medical Center, Augusta, Georgia
- Department of Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia
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14
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Zhang J, Cheng H, Di Narzo A, Zhu Y, Shan M, Zhang Z, Shao X, Chen J, Wang C, Hao K. Within- and cross-tissue gene regulations were disrupted by PM 2.5 nitrate exposure and associated with respiratory functions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 850:157977. [PMID: 35964746 DOI: 10.1016/j.scitotenv.2022.157977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 07/25/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Pathogenesis of complex diseases often involves multiple organs/tissue-types. To date, the PM2.5 exposure's toxic effects and induced disease risks were not studied at multi-tissue level. METHODS C57BL/6 mice (n = 40) were exposed to PM2.5 NO3- and clean air, respectively, and afterwards assessed respiratory functions and transcriptome in relevant tissues: blood and lung. We constructed within- and cross-tissue gene regulation networks and identified network modules associated with exposure and respiratory functions. RESULTS PM2.5 NO3- exposure elevated naïve B cells proportion in blood (p = 0.0028). Among the 6000 highest expressed genes in blood, 18.8 % (1133 genes) were altered by exposure at p ≤ 0.05 level, among which 763 genes were also associated with respiratory function (enrichment folds = 7.63, p = 2.7E-189). The exposure disrupted blood genes were primarily in the immunoregulation pathways. Both within- and cross-tissue gene network modules were perturbed by exposure and associated with respiratory function. An immunodeficiency related cross-tissue module of 555 genes was affected by exposure (p = 0.0023) and strongly correlated with FEV0.05/FVC (r = 0.61 and p = 3E-5). CONCLUSIONS This study aims to fill in a major knowledge gap and investigated the effect of PM2.5 exposure simultaneously in multiple tissues. We provided novel evidence that PM2.5 NO3- exposure profoundly perturbed within- and cross-tissue gene regulations, and highlighted their roles in the etiology of respiratory decline.
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Affiliation(s)
- Jushan Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | | | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xiaowen Shao
- Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Sema4, Stamford, CT, USA.
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15
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Banaganapalli B, Mallah B, Alghamdi KS, Albaqami WF, Alshaer DS, Alrayes N, Elango R, Shaik NA. Integrative weighted molecular network construction from transcriptomics and genome wide association data to identify shared genetic biomarkers for COPD and lung cancer. PLoS One 2022; 17:e0274629. [PMID: 36194576 PMCID: PMC9531836 DOI: 10.1371/journal.pone.0274629] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 09/01/2022] [Indexed: 11/05/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a multifactorial progressive airflow obstruction in the lungs, accounting for high morbidity and mortality across the world. This study aims to identify potential COPD blood-based biomarkers by analyzing the dysregulated gene expression patterns in blood and lung tissues with the help of robust computational approaches. The microarray gene expression datasets from blood (136 COPD and 6 controls) and lung tissues (16 COPD and 19 controls) were analyzed to detect shared differentially expressed genes (DEGs). Then these DEGs were used to construct COPD protein network-clusters and functionally enrich them against gene ontology annotation terms. The hub genes in the COPD network clusters were then queried in GWAS catalog and in several cancer expression databases to explore their pathogenic roles in lung cancers. The comparison of blood and lung tissue datasets revealed 63 shared DEGs. Of these DEGs, 12 COPD hub gene-network clusters (SREK1, TMEM67, IRAK2, MECOM, ASB4, C1QTNF2, CDC42BPA, DPF3, DET1, CCDC74B, KHK, and DDX3Y) connected to dysregulations of protein degradation, inflammatory cytokine production, airway remodeling, and immune cell activity were prioritized with the help of protein interactome and functional enrichment analysis. Interestingly, IRAK2 and MECOM hub genes from these COPD network clusters are known for their involvement in different pulmonary diseases. Additional COPD hub genes like SREK1, TMEM67, CDC42BPA, DPF3, and ASB4 were identified as prognostic markers in lung cancer, which is reported in 1% of COPD patients. This study identified 12 gene network- clusters as potential blood based genetic biomarkers for COPD diagnosis and prognosis.
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Affiliation(s)
- Babajan Banaganapalli
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- * E-mail: (BB); (NAS)
| | - Bayan Mallah
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Kawthar Saad Alghamdi
- Department of Biology, Faculty of Science, University of Hafr Al Batin, Hafr Al Batin, Saudi Arabia
| | - Walaa F. Albaqami
- Department of Science, Prince Sultan Military College of Health Sciences, Dhahran, Saudi Arabia
| | - Dalal Sameer Alshaer
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Nuha Alrayes
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ramu Elango
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Noor A. Shaik
- Department of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Princess Al-Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
- * E-mail: (BB); (NAS)
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Kim J, Suresh B, Lim MN, Hong SH, Kim KS, Song HE, Lee HY, Yoo HJ, Kim WJ. Metabolomics Reveals Dysregulated Sphingolipid and Amino Acid Metabolism Associated with Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis 2022; 17:2343-2353. [PMID: 36172036 PMCID: PMC9511892 DOI: 10.2147/copd.s376714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/09/2022] [Indexed: 11/25/2022] Open
Abstract
Purpose Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease presenting as multiple phenotypes, such as declining lung function, emphysema, or persistent airflow limitation caused by several risk factors, including cigarette smoking and air pollution. The inherent complexity of COPD phenotypes propounds difficulties for accurate diagnosis and prognosis. Although metabolomic profiles on COPD have been reported, the role of metabolism in COPD-related phenotypes is yet to be determined. In this study, we investigated the association between plasma sphingolipids and amino acids, and between COPD and COPD-related phenotypes in a Korean cohort. Patients and Methods Blood samples were collected from 120 patients with COPD and 80 control participants who underwent spirometry and quantitative computed tomography. The plasma metabolic profiling was carried out using LC-MS/MS analysis. Results Among the evaluated plasma sphingolipids, an increase in the metabolism of two specific sphingomyelins, SM (d18:1/24:0) and SM (d18:1/24:1) were significantly associated with COPD. There was no significant correlation between any of the SMs and the emphysema index, FVC and FEV1 in the COPD cohort. Meanwhile, Cer (d18:1/18:0) and Cer (d18:1/24:1) were significantly associated with reduced FEV1. Furthermore, the levels of several amino acids were altered in the COPD group compared to that in the non-COPD group; glutamate and alpha AAA were substantial associated with emphysema in COPD. Kynurenine was the only amino acid significantly associated with reduced FEV1 in COPD. In contrast, there was no correlation between FVC and the elevated metabolites. Conclusion Our results provide dysregulated plasma metabolites impacting COPD phenotypes, although more studies are needed to explore the underlying mechanism related to COPD pathogenesis.
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Affiliation(s)
- Jeeyoung Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Bharathi Suresh
- Graduate School of Biomedical Science and Engineering, Hanyang University, Seoul, South Korea
| | - Myoung Nam Lim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Seok-Ho Hong
- Department of Internal Medicine, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - Kye-Seong Kim
- Graduate School of Biomedical Science and Engineering, Hanyang University, Seoul, South Korea.,College of Medicine, Hanyang University, Seoul, South Korea
| | - Ha Eun Song
- Department of Convergence Medicine, Asan Medical Center, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Seoul, South Korea
| | - Hyo Yeong Lee
- Department of Convergence Medicine, Asan Medical Center, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Seoul, South Korea
| | - Hyun Ju Yoo
- Department of Convergence Medicine, Asan Medical Center, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Seoul, South Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
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17
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The Variation of Transcriptomic Perturbations is Associated with the Development and Progression of Various Diseases. DISEASE MARKERS 2022; 2022:2148627. [PMID: 36204511 PMCID: PMC9530920 DOI: 10.1155/2022/2148627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 08/31/2022] [Accepted: 09/07/2022] [Indexed: 11/28/2022]
Abstract
Background Although transcriptomic data have been widely applied to explore various diseases, few studies have investigated the association between transcriptomic perturbations and disease development in a wide variety of diseases. Methods Based on a previously developed algorithm for quantifying intratumor heterogeneity at the transcriptomic level, we defined the variation of transcriptomic perturbations (VTP) of a disease relative to the health status. Based on publicly available transcriptome datasets, we compared VTP values between the disease and health status and analyzed correlations between VTP values and disease progression or severity in various diseases, including neurological disorders, infectious diseases, cardiovascular diseases, respiratory diseases, liver diseases, kidney diseases, digestive diseases, and endocrine diseases. We also identified the genes and pathways whose expression perturbations correlated positively with VTP across diverse diseases. Results VTP values were upregulated in various diseases relative to their normal controls. VTP values were significantly greater in define than in possible or probable Alzheimer's disease. VTP values were significantly larger in intensive care unit (ICU) COVID-19 patients than in non-ICU patients, and in COVID-19 patients requiring mechanical ventilatory support (MVS) than in those not requiring MVS. VTP correlated positively with viral loads in acquired immune deficiency syndrome (AIDS) patients. Moreover, the AIDS patients treated with abacavir or zidovudine had lower VTP values than those without such therapies. In pulmonary tuberculosis (TB) patients, VTP values followed the pattern: active TB > latent TB > normal controls. VTP values were greater in clinically apparent than in presymptomatic malaria. VTP correlated negatively with the cardiac index of left ventricular ejection fraction (LVEF). In chronic obstructive pulmonary disease (COPD), VTP showed a negative correlation with forced expiratory volume in the first second (FEV1). VTP values increased with H. pylori infection and were upregulated in atrophic gastritis caused by H. pylori infection. The genes and pathways whose expression perturbations correlated positively with VTP scores across diseases were mainly involved in the regulation of immune, metabolic, and cellular activities. Conclusions VTP is upregulated in the disease versus health status, and its upregulation is associated with disease progression and severity in various diseases. Thus, VTP has potential clinical implications for disease diagnosis and prognosis.
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18
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Pei Y, Wei Y, Peng B, Wang M, Xu W, Chen Z, Ke X, Rong L. Combining single-cell RNA sequencing of peripheral blood mononuclear cells and exosomal transcriptome to reveal the cellular and genetic profiles in COPD. Respir Res 2022; 23:260. [PMID: 36127695 PMCID: PMC9490964 DOI: 10.1186/s12931-022-02182-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 09/09/2022] [Indexed: 11/30/2022] Open
Abstract
Background It has been a long-held consensus that immune reactions primarily mediate the pathology of chronic obstructive pulmonary disease (COPD), and that exosomes may participate in immune regulation in COPD. However, the relationship between exosomes and peripheral immune status in patients with COPD remains unclear. Methods In this study, we sequenced plasma exosomes and performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) from patients with COPD and healthy controls. Finally, we constructed competing endogenous RNA (ceRNA) and protein–protein interaction (PPI) networks to delineate the interactions between PBMCs and exosomes within COPD. Results We identified 135 mRNAs, 132 lncRNAs, and 359 circRNAs from exosomes that were differentially expressed in six patients with COPD compared with four healthy controls. Functional enrichment analyses revealed that many of these differentially expressed RNAs were involved in immune responses including defending viral infection and cytokine–cytokine receptor interaction. We also identified 18 distinct cell clusters of PBMCs in one patient and one control by using an unsupervised cluster analysis called uniform manifold approximation and projection (UMAP). According to resultant cell identification, it was likely that the proportions of monocytes, dendritic cells, and natural killer cells increased in the COPD patient we tested, meanwhile the proportions of B cells, CD4 + T cells, and naïve CD8 + T cells declined. Notably, CD8 + T effector memory CD45RA + (Temra) cell and CD8 + effector memory T (Tem) cell levels were elevated in patient with COPD, which were marked by their lower capacity to differentiate due to their terminal differentiation state and lower reactive capacity to viral pathogens. Conclusions We generated exosomal RNA profiling and single-cell transcriptomic profiling of PBMCs in COPD, described possible connection between impaired immune function and COPD development, and finally determined the possible role of exosomes in mediating local and systemic immune reactions. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-02182-8.
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Affiliation(s)
- Yanli Pei
- Respiratory Medicine Department, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Yuxi Wei
- Peking Union Medical College (PUMC), PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Boshizhang Peng
- Peking Union Medical College (PUMC), PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Mengqi Wang
- Peking Union Medical College (PUMC), PUMC and Chinese Academy of Medical Sciences, Beijing, China
| | - Wei Xu
- Respiratory Medicine Department, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Zhe Chen
- Laboratory of Cough, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, Jiangsu, China.
| | - Xindi Ke
- Peking Union Medical College (PUMC), PUMC and Chinese Academy of Medical Sciences, Beijing, China.
| | - Lei Rong
- Respiratory Medicine Department, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
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19
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Gregory A, Xu Z, Pratte K, Lee S, Liu C, Chase R, Yun J, Saferali A, Hersh CP, Bowler R, Silverman E, Castaldi PJ, Boueiz A. Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers. BMJ Open Respir Res 2022; 9:9/1/e001182. [PMID: 35999035 PMCID: PMC9403129 DOI: 10.1136/bmjresp-2021-001182] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 07/31/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiological measures to identify four COPD-related subtypes: ‘relatively resistant smokers (RRS)’, ‘mild upper lobe-predominant emphysema (ULE)’, ‘airway-predominant disease (AD)’ and ‘severe emphysema (SE)’. In the current study, we examined the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers. Methods We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster associations to 5-year prospective changes in spirometric and radiological measures and to gene expression and protein levels. We used Cox-proportional hazard test to test for cluster associations to prospective exacerbations, comorbidities and mortality. Results The RRS, ULE, AD and SE clusters represented 39%, 15%, 26% and 20% of the studied cohort at baseline, respectively. The SE cluster had the greatest 5-year FEV1 (forced expiratory volume in 1 s) and emphysema progression, and the highest risks of exacerbations, cardiovascular disease and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the SE cluster had an elevated respiratory mortality risk, while the ULE, AD and SE clusters had elevated all-cause mortality risks. These clusters also demonstrated differential protein and gene expression biomarker associations, mostly related to inflammatory and immune processes. Conclusion COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality and associations to transcriptomic and proteomic biomarkers. These findings emphasise the clinical and biological relevance of these subtypes, which call for more study for translation into clinical practice. Trail registration number NCT00608764.
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Affiliation(s)
- Andrew Gregory
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Zhonghui Xu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Katherine Pratte
- Department of Biostatistics, National Jewish Health, Denver, Colorado, USA
| | - Sool Lee
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Congjian Liu
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Robert Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Jeong Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Russell Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, Colorado, USA
| | - Edwin Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Adel Boueiz
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA .,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
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20
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Reed D, Kumar D, Kumar S, Raina K, Punia R, Kant R, Saba L, Cruickshank-Quinn C, Tabakoff B, Reisdorph N, Edwards MG, Wempe M, Agarwal C, Agarwal R. Transcriptome and metabolome changes induced by bitter melon ( Momordica charantia)- intake in a high-fat diet induced obesity model. J Tradit Complement Med 2022; 12:287-301. [PMID: 35493312 PMCID: PMC9039170 DOI: 10.1016/j.jtcme.2021.08.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 08/16/2021] [Accepted: 08/16/2021] [Indexed: 12/22/2022] Open
Abstract
Background and aim Metabolic syndrome (MetS) is a complex disease of physiological imbalances interrelated to abnormal metabolic conditions, such as abdominal obesity, type II diabetes, dyslipidemia and hypertension. In the present pilot study, we investigated the nutraceutical bitter melon (Momordica charantia L) -intake induced transcriptome and metabolome changes and the converging metabolic signaling networks underpinning its inhibitory effects against MetS-associated risk factors. Experimental procedure Metabolic effects of lyophilized bitter melon juice (BMJ) extract (oral gavage 200 mg/kg/body weight-daily for 40 days) intake were evaluated in diet-induced obese C57BL/6J male mice [fed-high fat diet (HFD), 60 kcal% fat]. Changes in a) serum levels of biochemical parameters, b) gene expression in the hepatic transcriptome (microarray analysis using Affymetrix Mouse Exon 1.0 ST arrays), and c) metabolite abundance levels in lipid-phase plasma [liquid chromatography mass spectrometry (LC-MS)-based metabolomics] after BMJ intervention were assessed. Results and conclusion BMJ-mediated changes showed a positive trend towards enhanced glucose homeostasis, vitamin D metabolism and suppression of glycerophospholipid metabolism. In the liver, nuclear peroxisome proliferator-activated receptor (PPAR) and circadian rhythm signaling, as well as bile acid biosynthesis and glycogen metabolism targets were modulated by BMJ (p < 0.05). Thus, our in-depth transcriptomics and metabolomics analysis suggests that BMJ-intake lowers susceptibility to the onset of high-fat diet associated MetS risk factors partly through modulation of PPAR signaling and its downstream targets in circadian rhythm processes to prevent excessive lipogenesis, maintain glucose homeostasis and modify immune responses signaling.
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Key Words
- AMPK, adenosine monophosphate-activated protein kinase
- BMJ, bitter melon juice
- Bitter melon
- DIO, diet-induced obese
- Diet intervention
- HDL, high density lipoprotein (cholesterol)
- HFD, high fat diet
- HMDB, Human Metabolome Database
- High fat diet-induced obesity
- KEGG, Kyoto Encyclopedia of Genes and Genomes
- LC-MS, liquid-chromatography mass spectrometry
- LDL, low density lipoprotein (cholesterol)
- MetS, Metabolic syndrome
- Metabolic syndrome
- Momordica charantia
- PC, phosphatidylcholine
- PE, phosphatidylethanolamine
- PPARs, Peroxisome proliferator-activated receptors
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Affiliation(s)
- Dominique Reed
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Dileep Kumar
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sushil Kumar
- Division of Critical Care Medicine and Cardiovascular Pulmonary Research, Departments of Pediatrics and Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Komal Raina
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, South Dakota State University, Brookings, SD, USA
| | - Reenu Punia
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rama Kant
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Laura Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Charmion Cruickshank-Quinn
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Boris Tabakoff
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Nichole Reisdorph
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Michael Wempe
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Chapla Agarwal
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rajesh Agarwal
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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21
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Wang L, Zhao H, Raman I, Yan M, Chen Q, Li QZ. Peripheral Blood Mononuclear Cell Gene Expression in Chronic Obstructive Pulmonary Disease: miRNA and mRNA Regulation. J Inflamm Res 2022; 15:2167-2180. [PMID: 35392023 PMCID: PMC8983057 DOI: 10.2147/jir.s337894] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 03/16/2022] [Indexed: 01/01/2023] Open
Affiliation(s)
- Lijing Wang
- Departments of Geriatrics, Respiratory Medicine, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People’s Republic of China
| | - Hongjun Zhao
- Department of Rheumatology and Immunology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People’s Republic of China
| | - Indu Raman
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Mei Yan
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Qiong Chen
- Departments of Geriatrics, Respiratory Medicine, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People’s Republic of China
| | - Quan-Zhen Li
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
- Correspondence: Quan-Zhen Li, Department of Immunology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA, Tel +1 214-645-6071, Fax +1 214-645-6074, Email
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22
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Huang HH, Liang Y. Integrating molecular interactions and gene expression to identify biomarkers and network modules of chronic obstructive pulmonary disease. Technol Health Care 2022; 30:135-142. [PMID: 35124591 PMCID: PMC9028746 DOI: 10.3233/thc-228013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) causes chronic obstructive conditions, chronic bronchitis, and emphysema, and is a major cause of death worldwide. Although several efforts for identifying biomarkers and pathways have been made, specific causal COPD mechanism remains unknown. OBJECTIVE: This study combined biological interaction data with gene expression data for a better understanding of the biological process and network module for COPD. METHODS: Using a sparse network-based method, we selected 49 genes from peripheral blood mononuclear cell expression data of 136 subjects, including 42 ex-smoking controls and 94 subjects with COPD. RESULTS: These 49 genes might influence biological processes and molecular functions related to COPD. For example, our result suggests that FoxO signaling may contribute to the atrophy of COPD peripheral muscle tissues via oxidative stress. CONCLUSIONS: Our approach enhances the existing understanding of COPD disease pathogenesis and predicts new genetic markers and pathways that may influence COPD pathogenesis.
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Affiliation(s)
- Hai-Hui Huang
- Faculty of Information Technology, Macau University of Science and Technology, Macau, China
- Macau Institute of Systems Engineering and Collaborative Laboratory of Intelligent Science and Systems, Macau University of Science and Technology, Macau, China
| | - Yong Liang
- Macau Institute of Systems Engineering and Collaborative Laboratory of Intelligent Science and Systems, Macau University of Science and Technology, Macau, China
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23
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Trivedi A, Bade G, Madan K, Ahmed Bhat M, Guleria R, Talwar A. Effect of Smoking and Its Cessation on the Transcript Profile of Peripheral Monocytes in COPD Patients. Int J Chron Obstruct Pulmon Dis 2022; 17:65-77. [PMID: 35027824 PMCID: PMC8749770 DOI: 10.2147/copd.s337635] [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: 09/13/2021] [Accepted: 12/13/2021] [Indexed: 11/23/2022] Open
Abstract
Rationale Smoking is the primary cause of chronic obstructive pulmonary disease (COPD); however, only 10–20% of smokers develop the disease suggesting possible genomic association in the causation of the disease. In the present study, we aimed to explore the whole genome transcriptomics of blood monocytes from COPD smokers (COPD-S), COPD Ex-smokers (COPD-ExS), Control smokers (CS), and Control Never-smokers (CNS) to understand the differential effects of smoking, COPD and that of smoking cessation. Methods Exploratory analyses in form of principal component analysis (PCA) and hierarchical component analysis (uHCA) were performed to evaluate the similarity in gene expression patterns, while differential expression analyses of different supervised groups of smokers and never smokers were performed to study the differential effect of smoking, COPD and smoking cessation. Differentially expressed genes among groups were subjected to post-hoc enrichment analysis. Candidate genes were subjected to external validation by quantitative RT-PCR experiments. Results CNS made a cluster completely segregated from the other three subgroups (CS, COPDS and COPD-ExS). About 550, 8 and 5 genes showed differential expression, respectively, between CNS and CS, between CS and COPD-S, and between COPD-S and COPD-ExS. Apoptosis, immune response, cell adhesion, and inflammation were the top process networks identified in enrichment analysis. Two candidate genes (CASP9 and TNFRSF1A) found to be integral to several pathways in enrichment analysis were validated in an external validation experiment. Conclusion Control never smokers had formed a cluster distinctively separated from all smokers (COPDS, COPD-ExS, and CS), while amongst all smokers, control smokers had aggregated in a separate cluster. Smoking cessation appeared beneficial if started at an early stage as many genes altered due to smoking started reverting towards the baseline, whereas only a few COPD-related genes showed reversal after smoking cessation.
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Affiliation(s)
- Anjali Trivedi
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Geetanjali Bade
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Karan Madan
- Department of Pulmonary, Critical Care and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Muzaffer Ahmed Bhat
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Randeep Guleria
- Department of Pulmonary, Critical Care and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Anjana Talwar
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
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24
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Ho CH, Huang YJ, Lai YJ, Mukherjee R, Hsiao CK. The misuse of distributional assumptions in functional class scoring gene-set and pathway analysis. G3-GENES GENOMES GENETICS 2021; 12:6409857. [PMID: 34791175 PMCID: PMC8728032 DOI: 10.1093/g3journal/jkab365] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 10/14/2021] [Indexed: 12/14/2022]
Abstract
Gene-set analysis (GSA) is a standard procedure for exploring potential biological functions of a group of genes. The development of its methodology has been an active research topic in recent decades. Many GSA methods, when newly proposed, rely on simulation studies to evaluate their performance with an implicit assumption that the multivariate expression values are normally distributed. This assumption is commonly adopted in GSAs, particularly those in the group of functional class scoring (FCS) methods. The validity of the normality assumption, however, has been disputed in several studies, yet no systematic analysis has been carried out to assess the effect of this distributional assumption. Our goal in this study is not to propose a new GSA method but to first examine if the multi-dimensional gene expression data in gene sets follow a multivariate normal (MVN) distribution. Six statistical methods in three categories of MVN tests were considered and applied to a total of 24 RNA data sets. These RNA values were collected from cancer patients as well as normal subjects, and the values were derived from microarray experiments, RNA sequencing, and single-cell RNA sequencing. Our first finding suggests that the MVN assumption is not always satisfied. This assumption does not hold true in many applications tested here. In the second part of this research, we evaluated the influence of non-normality on the statistical power of current FCS methods, both parametric and nonparametric ones. Specifically, the scenario of mixture distributions representing more than one population for the RNA values was considered. This second investigation demonstrates that the non-normality distribution of the RNA values causes a loss in the statistical power of these GSA tests, especially when subtypes exist. Among the FCS GSA tools examined here and among the scenarios studied in this research, the N-statistics outperform the others. Based on the results from these two investigations, we conclude that the assumption of MVN should be used with caution when evaluating new GSA tools, since this assumption cannot be guaranteed and violation may lead to spurious results, loss of power, and incorrect comparison between methods. If a newly proposed GSA tool is to be evaluated, we recommend the incorporation of a wide range of multivariate non-normal distributions or sampling from large databases if available.
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Affiliation(s)
- Chi-Hsuan Ho
- Division of Biostatistics and Data Science, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Yu-Jyun Huang
- Division of Biostatistics and Data Science, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei 10055, Taiwan
| | - Ying-Ju Lai
- Division of Biostatistics and Data Science, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei 10055, Taiwan
| | | | - Chuhsing Kate Hsiao
- Division of Biostatistics and Data Science, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei 10055, Taiwan.,Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei 10055, Taiwan
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25
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Zhang J, Cheng H, Wang D, Zhu Y, Yang C, Shen Y, Yu J, Li Y, Xu S, Song X, Zhou Y, Chen J, Fan L, Jiang J, Wang C, Hao K. Revealing consensus gene pathways associated with respiratory functions and disrupted by PM2.5 nitrate exposure at bulk tissue and single cell resolution. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 280:116951. [PMID: 33780843 DOI: 10.1016/j.envpol.2021.116951] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/28/2021] [Accepted: 03/12/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Nitrate is a major pollutant component in ambient PM2.5. It is known that chronic exposure to PM2.5 NO3- damages respiratory functions. We aim to explore the underlying toxicological mechanism at single cell resolution. METHODS We systematically conducted exposure experiments on forty C57BL/6 mice, assessed respiratory functions, and profiled lung transcriptome. . Afterward, we estimated the cell type compositions from RNA-seq data using deconvolution analysis. The genes and pathways associated with respiratory function and dysregulated by to PM2.5 NO3- exposure were characterized at bulk-tissue and single-cell resolution. RESULTS PM2.5 NO3- exposure did not significantly modify the cell type composition in lung, but profoundly altered the gene expression within each cell type. At ambient concentration (22 μg/m3), exposure significantly (FDR<10%) altered 95 genes' expression. Among the genes associated with respiratory functions, a large fraction (74.6-91.7%) were significantly perturbed by PM2.5 NO3- exposure. For example, among the 764 genes associated with peak expiratory flow (PEF), 608 (79.6%) were affected by exposure (p = 1.92e-345). Pathways known to play role in lung disease pathogenesis, including circadian rhythms, sphingolipid metabolism, immune response and lysosome, were found significantly associated with respiratory functions and disrupted by PM2.5 NO3- exposure. CONCLUSIONS This study extended our knowledge of PM2.5 NO3- exposure's effect to the levels of lung gene expression, pathways, lung cell type composition and cell specific transcriptome. At single cell resolution, we provided insights in toxicological mechanism of PM2.5 NO3- exposure and subsequent pulmonary disease risks.
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Affiliation(s)
- Jushan Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dongbin Wang
- School of Environment, Tsinghua University, Beijing, China
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Chun Yang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Yuan Shen
- Department of Psychiatry, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jing Yu
- Department of Ophthalmology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Yuanyuan Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shunqing Xu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaolian Song
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Yang Zhou
- School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lihong Fan
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jingkun Jiang
- School of Environment, Tsinghua University, Beijing, China
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Ke Hao
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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26
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Gong M, Liu P, Sciurba FC, Stojanov P, Tao D, Tseng GC, Zhang K, Batmanghelich K. Unpaired data empowers association tests. Bioinformatics 2021; 37:785-792. [PMID: 33070196 PMCID: PMC8098021 DOI: 10.1093/bioinformatics/btaa886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 09/07/2020] [Accepted: 10/05/2020] [Indexed: 11/25/2022] Open
Abstract
Motivation There is growing interest in the biomedical research community to incorporate retrospective data, available in healthcare systems, to shed light on associations between different biomarkers. Understanding the association between various types of biomedical data, such as genetic, blood biomarkers, imaging, etc. can provide a holistic understanding of human diseases. To formally test a hypothesized association between two types of data in Electronic Health Records (EHRs), one requires a substantial sample size with both data modalities to achieve a reasonable power. Current association test methods only allow using data from individuals who have both data modalities. Hence, researchers cannot take advantage of much larger EHR samples that includes individuals with at least one of the data types, which limits the power of the association test. Results We present a new method called the Semi-paired Association Test (SAT) that makes use of both paired and unpaired data. In contrast to classical approaches, incorporating unpaired data allows SAT to produce better control of false discovery and to improve the power of the association test. We study the properties of the new test theoretically and empirically, through a series of simulations and by applying our method on real studies in the context of Chronic Obstructive Pulmonary Disease. We are able to identify an association between the high-dimensional characterization of Computed Tomography chest images and several blood biomarkers as well as the expression of dozens of genes involved in the immune system. Availability and implementation Code is available on https://github.com/batmanlab/Semi-paired-Association-Test. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mingming Gong
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA.,Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA.,School of Mathematics and Statistics, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Peng Liu
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Frank C Sciurba
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Petar Stojanov
- Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Dacheng Tao
- Australia School of Computer Science, The University of Sydney, Sydney, NSW 2006, Australia
| | - George C Tseng
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
| | - Kun Zhang
- Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kayhan Batmanghelich
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206, USA
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Lu HH, Zeng HH, Chen Y. Early chronic obstructive pulmonary disease: A new perspective. Chronic Dis Transl Med 2021; 7:79-87. [PMID: 34136767 PMCID: PMC8180470 DOI: 10.1016/j.cdtm.2021.02.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Indexed: 01/10/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a respiratory disease with a high incidence, mortality, and disability rate. Because there are few symptoms in the early stages of COPD, diagnosis and treatment are seriously insufficient. It is necessary to find effective clues for early COPD diagnosis and provide appropriate interventions. Several studies suggest that small airway disease is the earliest stage of COPD because it is correlated with subsequent development of airflow obstruction. However, there are currently no globally accepted criteria for defining early COPD. This study mainly introduced risk factors, definition, diagnosis, and treatment of early COPD from a new perspective.
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Affiliation(s)
- Huan-Huan Lu
- Department of Respiratory and Critical Care Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
- Research Unit of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
- Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
| | - Hui-Hui Zeng
- Department of Respiratory and Critical Care Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
- Research Unit of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
- Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
| | - Yan Chen
- Department of Respiratory and Critical Care Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
- Research Unit of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
- Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
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28
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Neto ABL, Vasconcelos NBR, Dos Santos TR, Duarte LEC, Assunção ML, de Sales-Marques C, Ferreira HDS. Prevalence of IGFBP3, NOS3 and TCF7L2 polymorphisms and their association with hypertension: a population-based study with Brazilian women of African descent. BMC Res Notes 2021; 14:186. [PMID: 34001234 PMCID: PMC8130172 DOI: 10.1186/s13104-021-05598-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 05/05/2021] [Indexed: 11/10/2022] Open
Abstract
Objective African ancestry seems to be a risk factor for hypertension; however, few genetic studies have addressed this issue. This study aimed to investigate the prevalence of polymorphisms NOS3; rs1799983, IGFBP3; rs11977526 and TCF7L2; rs7903146 in Brazilian women of African descent and their association with hypertension. Results The prevalences of the less frequent genotypes were 26.5% TT genotype of NOS3; rs1799983, 16.7% AA genotype of IGFBP3; rs11977526, and 18.3% TT genotype of TCF7L2; rs7903146. For these conditions, the prevalence of hypertension and PR (adjusted) relatively to the ancestral genotype were, respectively: 52.0% vs 24.5% (PR = 1.54; p < 0.001), 62.0% vs 24.1% (PR = 1.59; p < 0.001), and 38.9% vs 27.9% (PR = 0.86; p = 0.166). Associations with hypertension were statistically significant, except for the TCF7L2; rs7903146 polymorphism, after adjusted analysis. Brazilian Afro-descendant women with the TT genotype for the NOS3 gene and the AA genotype for the IGFBP3 gene are more susceptible to hypertension. The understanding of underlying mechanisms involving the pathogenesis of hypertension can motivate research for the development of new therapeutic targets related to nitric oxide metabolism and the management of oxidative stress. Supplementary Information The online version contains supplementary material available at 10.1186/s13104-021-05598-5.
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Affiliation(s)
- Abel Barbosa Lira Neto
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil. .,, Rua Costa Gama, 1160, Caçimbas, Arapiraca, Alagoas, 57038-430, Brazil.
| | - Nancy Borges Rodrigues Vasconcelos
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
| | - Tamara Rodrigues Dos Santos
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
| | - Luisa Elvira Cavazzani Duarte
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
| | - Monica Lopes Assunção
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
| | - Carolinne de Sales-Marques
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
| | - Haroldo da Silva Ferreira
- Federal University of Alagoas, Institute of Biological and Health Sciences, Postgraduate Program in Health Sciences, Campus A.C. Simões, Highway BR 104 North, Tabuleiro Do Martins, Maceió, Alagoas, 57072-970, Brazil
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Yu W, Ye T, Ding J, Huang Y, Peng Y, Xia Q, Cuntai Z. miR-4456/CCL3/CCR5 Pathway in the Pathogenesis of Tight Junction Impairment in Chronic Obstructive Pulmonary Disease. Front Pharmacol 2021; 12:551839. [PMID: 33953665 PMCID: PMC8089484 DOI: 10.3389/fphar.2021.551839] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 02/22/2021] [Indexed: 11/19/2022] Open
Abstract
Background: Cigarette smoke exposure (CSE) is a major cause of chronic obstructive pulmonary disease (COPD). The smoke disrupts cell-cell adhesion by inducing epithelial barrier damage to the tight junction (TJ) proteins. Even though the inflammatory mechanism of chemokine (C-C motif) ligand 3 (CCL3) in COPD has gained increasing attention in the research community, however, the underlying signaling pathway, remains unknown. Objectives: To identify the relationship of CCL3 in the pathogenesis of tight junction impairment in COPD and the pathway through which CSE causes damage to TJ in COPD via CCL3, both in vivo and in vitro. Methods: We screened the inflammatory factors in the peripheral blood mononuclear cells (PBMCs) from healthy controls and patients at each GOLD 1-4 stage of chronic obstructive pulmonary disease. RT-PCR, western blot, and ELISA were used to detect the levels of CCL3, ZO-1, and occludin after Cigarette smoke exposure. Immunofluorescence was applied to examine the impairment of the TJs in 16-HBE and A549 cells. The reverse assay was used to detect the effect of a CCR5 antagonist (DAPTA) in COPD. In the CSE-induced COPD mouse model, H&E staining and lung function tests were used to evaluate the pathological and physical states in each group. Immunofluorescence was used to assess the impairment of TJs in each group. ELISA and RT-PCR were used to examine the mRNA or protein expression of CCL3 or miR-4456 in each group. Results: The in vivo and in vitro results showed that CCL3 expression was increased in COPD compared with healthy controls. CCL3 caused significant injury to TJs through its C-C chemokine receptor type 5 (CCR5), while miR-4456 could suppress the effect of CCL3 on TJs by binding to the 3′-UTR of CCL3. Conclusion: miR-4456/CCL3/CCR5 pathway may be a potential target pathway for the treatment of COPD.
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Affiliation(s)
- Weiwei Yu
- Department of Geriatric Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ting Ye
- Department of Clinical Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jie Ding
- Urology Department of Xin Hua Hospital, Xin Hua Hospital Affliated to Shanghai Jiao Tong University, Shanghai, China
| | - Yi Huang
- Department of Geriatric Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Peng
- Department of Geriatric Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qin Xia
- Department of Geriatric Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhang Cuntai
- Department of Geriatric Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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30
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Integrative genomics analysis identifies five promising genes implicated in insomnia risk based on multiple omics datasets. Biosci Rep 2021; 40:226183. [PMID: 32830860 PMCID: PMC7468094 DOI: 10.1042/bsr20201084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 08/15/2020] [Accepted: 08/21/2020] [Indexed: 12/27/2022] Open
Abstract
In recent decades, many genome-wide association studies on insomnia have reported numerous genes harboring multiple risk variants. Nevertheless, the molecular functions of these risk variants conveying risk to insomnia are still ill-studied. In the present study, we integrated GWAS summary statistics (N=386,533) with two independent brain expression quantitative trait loci (eQTL) datasets (N=329) to determine whether expression-associated SNPs convey risk to insomnia. Furthermore, we applied numerous bioinformatics analyses to highlight promising genes associated with insomnia risk. By using Sherlock integrative analysis, we detected 449 significant insomnia-associated genes in the discovery stage. These identified genes were significantly overrepresented in six biological pathways including Huntington’s disease (P=5.58 × 10−5), Alzheimer’s disease (P=5.58 × 10−5), Parkinson’s disease (P=6.34 × 10−5), spliceosome (P=1.17 × 10−4), oxidative phosphorylation (P=1.09 × 10−4), and wnt signaling pathways (P=2.07 × 10−4). Further, five of these identified genes were replicated in an independent brain eQTL dataset. Through a PPI network analysis, we found that there existed highly functional interactions among these five identified genes. Three genes of LDHA (P=0.044), DALRD3 (P=5.0 × 10−5), and HEBP2 (P=0.032) showed significantly lower expression level in brain tissues of insomnic patients than that in controls. In addition, the expression levels of these five genes showed prominently dynamic changes across different time points between behavioral states of sleep and sleep deprivation in mice brain cortex. Together, the evidence of the present study strongly suggested that these five identified genes may represent candidate genes and contributed risk to the etiology of insomnia.
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31
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Zhong Y, Chen L, Li J, Yao Y, Liu Q, Niu K, Ma Y, Xu Y. Integration of summary data from GWAS and eQTL studies identified novel risk genes for coronary artery disease. Medicine (Baltimore) 2021; 100:e24769. [PMID: 33725943 PMCID: PMC7982177 DOI: 10.1097/md.0000000000024769] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/23/2021] [Indexed: 01/05/2023] Open
Abstract
Several genetic loci have been reported to be significantly associated with coronary artery disease (CAD) by multiple genome-wide association studies (GWAS). Nevertheless, the biological and functional effects of these genetic variants on CAD remain largely equivocal. In the current study, we performed an integrative genomics analysis by integrating large-scale GWAS data (N = 459,534) and 2 independent expression quantitative trait loci (eQTL) datasets (N = 1890) to determine whether CAD-associated risk single nucleotide polymorphisms (SNPs) exert regulatory effects on gene expression. By using Sherlock Bayesian, MAGMA gene-based, multidimensional scaling (MDS), functional enrichment, and in silico permutation analyses for independent technical and biological replications, we highlighted 4 susceptible genes (CHCHD1, TUBG1, LY6G6C, and MRPS17) associated with CAD risk. Based on the protein-protein interaction (PPI) network analysis, these 4 genes were found to interact with each other. We detected a remarkably altered co-expression pattern among these 4 genes between CAD patients and controls. In addition, 3 genes of CHCHD1 (P = .0013), TUBG1 (P = .004), and LY6G6C (P = .038) showed significantly different expressions between CAD patients and controls. Together, we provide evidence to support that these identified genes such as CHCHD1 and TUBG1 are indicative factors of CAD.
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Affiliation(s)
- Yigang Zhong
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
| | | | - Jingjing Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yinghao Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Qiang Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Kaimeng Niu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou
| | - Yunlong Ma
- Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yizhou Xu
- Department of Cardiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine
- Zhejiang Chinese Medical University
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32
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Zhang J, Cheng H, Wang D, Zhu Y, Yang C, Shen Y, Yu J, Li Y, Xu S, Zhang S, Song X, Zhou Y, Chen J, Jiang J, Fan L, Wang C, Hao K. Chronic Exposure to PM 2.5 Nitrate, Sulfate, and Ammonium Causes Respiratory System Impairments in Mice. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:3081-3090. [PMID: 33566583 DOI: 10.1021/acs.est.0c05814] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Water-soluble inorganic (WSI) ions are major components of ambient air PM2.5 (particulate matter of diameter ≤2.5 μm); however, their potential health effects are understudied. On C57BL/6 mice, we quantified the effect of three major PM2.5 WSIs (NO3-, SO42-, and NH4+) on respiratory systems. Exposure scenarios include different WSI types, concentrations, animal development stages (young vs adult), and sex. The exposure effects were comprehensively assessed, with special focus on the respiratory function and tissue/cell level changes. Chronic PM2.5 NO3- exposure produced significant respiratory function decline, mainly presented as airflow obstruction. The decline was more profound in young mice than in adult mice. In young mice, exposure to 22 μg/m3 PM2.5 NO3- reduced FEV0.05 (forced expiratory volume in 0.05 s) by 11.3% (p = 9.6 × 10-3) and increased pulmonary neutrophil infiltration by 7.9% (p = 7.1 × 10-3). Causality tests identified that neutrophil infiltration was involved in the biological mechanism underlying PM2.5 NO3- toxicity. In contrast, the effects of PM2.5 SO42- were considerably weaker than NO3-. PM2.5 NO3- exposure was 3.4 times more potent than PM2.5 SO42- in causing reduction of the peak expiratory flow. PM2.5 NH4+ exposure had no statistically significant effects on the respiratory function. In summary, this study provided strong evidence on the adverse impacts of PM2.5 WSIs, where the impacts were most profound in young mice exposed to PM2.5 NO3-. If confirmed in humans, toxicity of PM2.5 WSI will have broad implications in environment health and policy making.
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Affiliation(s)
- Jushan Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, New York, United States
| | - Dongbin Wang
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Chun Yang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Yuan Shen
- Department of Psychiatry, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200092, China
| | - Jing Yu
- Department of Ophthalmology, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200092, China
| | - Yuanyuan Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Shunqing Xu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
| | - Shumin Zhang
- School of Pharmacy, Binzhou Medical University, Yantai 264003, Shandong, China
| | - Xiaolian Song
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Yang Zhou
- School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York 10029, New York, United States
| | - Jingkun Jiang
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Lihong Fan
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
| | - Ke Hao
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai 200072, China
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, New York, United States
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Berdyshev EV, Serban KA, Schweitzer KS, Bronova IA, Mikosz A, Petrache I. Ceramide and sphingosine-1 phosphate in COPD lungs. Thorax 2021; 76:thoraxjnl-2020-215892. [PMID: 33514670 PMCID: PMC9004347 DOI: 10.1136/thoraxjnl-2020-215892] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 12/17/2020] [Accepted: 01/07/2021] [Indexed: 11/04/2022]
Abstract
Studies of chronic obstructive pulmonary disease (COPD) using animal models and patient plasma indicate dysregulation of sphingolipid metabolism, but data in COPD lungs are sparse. Mass spectrometric and immunostaining measurements of lungs from 69 COPD, 16 smokers without COPD and 13 subjects with interstitial lung disease identified decoupling of lung ceramide and sphingosine-1 phosphate (S1P) levels and decreased sphingosine kinase-1 (SphK1) activity in COPD. The correlation of ceramide abundance in distal COPD lungs with apoptosis and the inverse correlation between SphK1 activity and presence of emphysema suggest that disruption of ceramide-to-S1P metabolism is an important determinant of emphysema phenotype in COPD.
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Affiliation(s)
- Evgeny V Berdyshev
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
- Department of Medicine, University of Illinois Chicago, Chicago, Illinois, USA
| | - Karina A Serban
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
- School of Medicine, University of Colorado Denver, Aurora, Colorado, USA
| | - Kelly S Schweitzer
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Irina A Bronova
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
- Department of Medicine, University of Illinois Chicago, Chicago, Illinois, USA
| | - Andrew Mikosz
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Irina Petrache
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
- School of Medicine, University of Colorado Denver, Aurora, Colorado, USA
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Shaddox E, Peterson CB, Stingo FC, Hanania NA, Cruickshank-Quinn C, Kechris K, Bowler R, Vannucci M. Bayesian inference of networks across multiple sample groups and data types. Biostatistics 2020; 21:561-576. [PMID: 30590505 DOI: 10.1093/biostatistics/kxy078] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 10/22/2018] [Accepted: 10/28/2018] [Indexed: 01/06/2023] Open
Abstract
In this article, we develop a graphical modeling framework for the inference of networks across multiple sample groups and data types. In medical studies, this setting arises whenever a set of subjects, which may be heterogeneous due to differing disease stage or subtype, is profiled across multiple platforms, such as metabolomics, proteomics, or transcriptomics data. Our proposed Bayesian hierarchical model first links the network structures within each platform using a Markov random field prior to relate edge selection across sample groups, and then links the network similarity parameters across platforms. This enables joint estimation in a flexible manner, as we make no assumptions on the directionality of influence across the data types or the extent of network similarity across the sample groups and platforms. In addition, our model formulation allows the number of variables and number of subjects to differ across the data types, and only requires that we have data for the same set of groups. We illustrate the proposed approach through both simulation studies and an application to gene expression levels and metabolite abundances on subjects with varying severity levels of chronic obstructive pulmonary disease. Bayesian inference; Chronic obstructive pulmonary disease (COPD); Data integration; Gaussian graphical model; Markov random field prior; Spike and slab prior.
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Affiliation(s)
- Elin Shaddox
- Department of Statistics, Rice University, Houston, TX, USA
| | | | - Francesco C Stingo
- Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy
| | - Nicola A Hanania
- Department of Medicine-Pulmonary, Baylor College of Medicine, Houston, TX, USA
| | | | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado SPH, University of Colorado, Denver, CO, USA
| | - Russell Bowler
- Department of Medicine, National Jewish Health, Denver, CO, USA
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Zhang X, Song J, Shah BN, Nekhai S, Miasnikova G, Sergueeva A, Prchal JT, Gordeuk VR. Peripheral blood mononuclear cells show prominent gene expression by erythroid progenitors in diseases characterized by heightened erythropoiesis. Br J Haematol 2020; 190:e42-e45. [PMID: 32399971 DOI: 10.1111/bjh.16696] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 04/07/2020] [Indexed: 11/29/2022]
Affiliation(s)
- Xu Zhang
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Jihyun Song
- Hematology Division, University of Utah, Salt Lake City, UT, USA
| | - Binal N Shah
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Sergei Nekhai
- Center for Sickle Cell Disease, Howard University, Washington, DC, USA.,Chuvash Republic Clinical Hospital 2, Cheboksary, Russia
| | | | | | - Josef T Prchal
- Hematology Division, University of Utah, Salt Lake City, UT, USA
| | - Victor R Gordeuk
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
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Protective Effect of Ocotillol, the Derivate of Ocotillol-Type Saponins in Panax Genus, against Acetic Acid-Induced Gastric Ulcer in Rats Based on Untargeted Metabolomics. Int J Mol Sci 2020; 21:ijms21072577. [PMID: 32276345 PMCID: PMC7177626 DOI: 10.3390/ijms21072577] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 03/30/2020] [Accepted: 04/02/2020] [Indexed: 02/07/2023] Open
Abstract
Gastric ulcer (GU), a prevalent digestive disease, has a high incidence and is seriously harmful to human health. Finding a natural drug with a gastroprotective effect is needed. Ocotillol, the derivate of ocotillol-type saponins in the Panax genus, possesses good anti-inflammatory activity. The study aimed to investigate the gastroprotective effect of ocotillol on acetic acid-induced GU rats. The serum levels of endothelin-1 (ET-1) and nitric oxide (NO), the gastric mucosa levels of epidermal growth factor, superoxide dismutase and NO were assessed. Hematoxylin and eosin staining of gastric mucosa for pathological changes and immunohistochemical staining of ET-1, epidermal growth factor receptors and inducible nitric oxide synthase were evaluated. A UPLC-QTOF-MS-based serum metabolomics approach was applied to explore the latent mechanism. A total of 21 potential metabolites involved in 7 metabolic pathways were identified. The study helps us to understand the pathogenesis of GU and to provide a potential natural anti-ulcer agent.
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Regan EA, Hersh CP, Castaldi PJ, DeMeo DL, Silverman EK, Crapo JD, Bowler RP. Omics and the Search for Blood Biomarkers in Chronic Obstructive Pulmonary Disease. Insights from COPDGene. Am J Respir Cell Mol Biol 2020; 61:143-149. [PMID: 30874442 DOI: 10.1165/rcmb.2018-0245ps] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
There is an unmet need for blood biomarkers in diagnosis and prognosis of chronic obstructive pulmonary disease (COPD). The search for these biomarkers has been revolutionized by high-throughput sequencing techniques and multiplex platforms that can measure thousands of gene transcripts, proteins, or metabolites. We review COPDGene (Genetic Epidemiology of COPD) project publications that include DNA methylation, transcriptomic, proteomic, and metabolomic blood biomarkers and discuss their impact on COPD. Key contributions from COPDGene include identification of DNA methylation effects from smoking and genetic variation, new transcriptomic signatures in the blood, identification of protein biomarkers associated with severity and progression (e.g., sRAGE [soluble receptor for advanced glycosylation end products], inflammatory cytokines IL-6 and IL-8), and identification of small molecules (ceramides and sphingomyelin) that may be pathogenic. COPDGene studies have revealed that some of the COPD genome-wide association study polymorphisms are strongly associated with blood biomarkers (e.g., rs2070600 in AGER is a pQTL [protein quantitative trait locus] for sRAGE), underscoring the importance of combining omics results. Investigators have developed molecular networks identifying lower CD4+ resting memory cells associated with COPD. Genes, proteins, and metabolite networks are particularly important because the explanatory value of any single molecule is small (1-10%) compared with panels of multiple markers. COPDGene has been a useful resource in the identification and validation of multiple biomarkers for COPD. These biomarkers, either combined in multiple biomarker panels or integrated with other omics data types, may lead to novel diagnostic and prognostic tests for COPD phenotypes and may be relevant for assessing novel therapies.
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Affiliation(s)
- Elizabeth A Regan
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
| | - Craig P Hersh
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Peter J Castaldi
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Dawn L DeMeo
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Edwin K Silverman
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - James D Crapo
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
| | - Russell P Bowler
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
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Florez-Sampedro L, Soto-Gamez A, Poelarends GJ, Melgert BN. The role of MIF in chronic lung diseases: looking beyond inflammation. Am J Physiol Lung Cell Mol Physiol 2020; 318:L1183-L1197. [PMID: 32208924 DOI: 10.1152/ajplung.00521.2019] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine that has been associated with many diseases. Most studies found in literature describe MIF as a proinflammatory cytokine involved in chronic inflammatory conditions, but evidence from last years suggests that many of its key effects are not directly related to inflammation. In fact, MIF is constitutively expressed in most human tissues and in some cases in high levels, which does not reflect the pattern of expression of a classic proinflammatory cytokine. Moreover, MIF is highly expressed during embryonic development and decreases during adulthood, which point toward a more likely role as growth factor. Accordingly, MIF knockout mice develop age-related spontaneous emphysema, suggesting that MIF presence (e.g., in younger individuals and wild-type animals) is part of a healthy lung. In view of this new line of evidence, we aimed to review data on the role of MIF in the pathogenesis of chronic lung diseases.
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Affiliation(s)
- Laura Florez-Sampedro
- Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.,Department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Abel Soto-Gamez
- Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.,European Institute for the Biology of Aging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Gerrit J Poelarends
- Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Barbro N Melgert
- Department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Patel H, Iniesta R, Stahl D, Dobson RJ, Newhouse SJ. Working Towards a Blood-Derived Gene Expression Biomarker Specific for Alzheimer's Disease. J Alzheimers Dis 2020; 74:545-561. [PMID: 32065794 PMCID: PMC7175937 DOI: 10.3233/jad-191163] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2020] [Indexed: 11/15/2022]
Abstract
BACKGROUND The typical approach to identify blood-derived gene expression signatures as a biomarker for Alzheimer's disease (AD) have relied on training classification models using AD and healthy controls only. This may inadvertently result in the identification of markers for general illness rather than being disease-specific. OBJECTIVE Investigate whether incorporating additional related disorders in the classification model development process can lead to the discovery of an AD-specific gene expression signature. METHODS Two types of XGBoost classification models were developed. The first used 160 AD and 127 healthy controls and the second used the same 160 AD with 6,318 upsampled mixed controls consisting of Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, bipolar disorder, schizophrenia, coronary artery disease, rheumatoid arthritis, chronic obstructive pulmonary disease, and cognitively healthy subjects. Both classification models were evaluated in an independent cohort consisting of 127 AD and 687 mixed controls. RESULTS The AD versus healthy control models resulted in an average 48.7% sensitivity (95% CI = 34.7-64.6), 41.9% specificity (95% CI = 26.8-54.3), 13.6% PPV (95% CI = 9.9-18.5), and 81.1% NPV (95% CI = 73.3-87.7). In contrast, the mixed control models resulted in an average of 40.8% sensitivity (95% CI = 27.5-52.0), 95.3% specificity (95% CI = 93.3-97.1), 61.4% PPV (95% CI = 53.8-69.6), and 89.7% NPV (95% CI = 87.8-91.4). CONCLUSIONS This early work demonstrates the value of incorporating additional related disorders into the classification model developmental process, which can result in models with improved ability to distinguish AD from a heterogeneous aging population. However, further improvement to the sensitivity of the test is still required.
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Affiliation(s)
- Hamel Patel
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
| | - Raquel Iniesta
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Daniel Stahl
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Richard J.B. Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Stephen J. Newhouse
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
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Gene expression microarray public dataset reanalysis in chronic obstructive pulmonary disease. PLoS One 2019; 14:e0224750. [PMID: 31730674 PMCID: PMC6857915 DOI: 10.1371/journal.pone.0224750] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 10/21/2019] [Indexed: 12/20/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) was classified by the Centers for Disease Control and Prevention in 2014 as the 3rd leading cause of death in the United States (US). The main cause of COPD is exposure to tobacco smoke and air pollutants. Problems associated with COPD include under-diagnosis of the disease and an increase in the number of smokers worldwide. The goal of our study is to identify disease variability in the gene expression profiles of COPD subjects compared to controls, by reanalyzing pre-existing, publicly available microarray expression datasets. Our inclusion criteria for microarray datasets selected for smoking status, age and sex of blood donors reported. Our datasets used Affymetrix, Agilent microarray platforms (7 datasets, 1,262 samples). We re-analyzed the curated raw microarray expression data using R packages, and used Box-Cox power transformations to normalize datasets. To identify significant differentially expressed genes we used generalized least squares models with disease state, age, sex, smoking status and study as effects that also included binary interactions, followed by likelihood ratio tests (LRT). We found 3,315 statistically significant (Storey-adjusted q-value <0.05) differentially expressed genes with respect to disease state (COPD or control). We further filtered these genes for biological effect using results from LRT q-value <0.05 and model estimates’ 10% two-tailed quantiles of mean differences between COPD and control), to identify 679 genes. Through analysis of disease, sex, age, and also smoking status and disease interactions we identified differentially expressed genes involved in a variety of immune responses and cell processes in COPD. We also trained a logistic regression model using the common array genes as features, which enabled prediction of disease status with 81.7% accuracy. Our results give potential for improving the diagnosis of COPD through blood and highlight novel gene expression disease signatures.
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Pinto-Plata V, Casanova C, Divo M, Tesfaigzi Y, Calhoun V, Sui J, Polverino F, Priolo C, Petersen H, de Torres JP, Marin JM, Owen CA, Baz R, Cordova E, Celli B. Plasma metabolomics and clinical predictors of survival differences in COPD patients. Respir Res 2019; 20:219. [PMID: 31615518 PMCID: PMC6794856 DOI: 10.1186/s12931-019-1167-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 08/15/2019] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Plasma metabolomics profile (PMP) in COPD has been associated with clinical characteristics, but PMP's relationship to survival has not been reported. We determined PMP differences between patients with COPD who died an average of 2 years after enrollment (Non-survivors, NS) compared to those who survived (S) and also with age matched controls (C). METHODS We studied prospectively 90 patients with severe COPD and 30 controls. NS were divided in discovery and validation cohorts (30 patients each) and the results compared to the PMP of 30 S and C. All participants completed lung function tests, dyspnea scores, quality of life, exercise capacity, BODE index, and plasma metabolomics by liquid and gas chromatography / mass spectometry (LC/MS, LC/MS2, GC/MS). Statistically, we used Random Forest Analysis (RFA) and Support Vector Machine (SVM) to determine metabolites that differentiated the 3 groups and compared the ability of metabolites vs. clinical characteristics to classify patients into survivors and non-survivors. RESULTS There were 79 metabolites statistically different between S and NS [p < 0.05 and false discovery rate (q value) < 0.1]. RFA and SVM classification of COPD survivors and non-survivors had a predicted accuracy of 74 and 85% respectively. Elevation of tricyclic acid cycle intermediates branched amino acids depletion and increase in lactate, fructose and xylonate showed the most relevant differences between S vs. NS suggesting alteration in mitochondrial oxidative energy generation. PMP had similar predictive power for risk of death as information provided by clinical characteristics. CONCLUSIONS A plasma metabolomic profile characterized by an oxidative energy production difference between survivors and non-survivors was observed in COPD patients 2 years before death.
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Affiliation(s)
- Victor Pinto-Plata
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
- Pulmonary-Critical Care Medicine Division, Baystate Medical Center, University of Massachusetts-Baystate, 759 Chestnut St, Springfield, MA 01199 USA
| | - Ciro Casanova
- Servicio de Neumologia, Hospital Universitario Nuestra Señora de la Candelaria, Tenerife, Spain
| | - Miguel Divo
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | | | - Vince Calhoun
- The Mind Research Network, Lovelace Respiratory Research Institute, Albuquerque, USA
| | - Jing Sui
- The Mind Research Network, Lovelace Respiratory Research Institute, Albuquerque, USA
| | - Francesca Polverino
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | - Carmen Priolo
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | - Hans Petersen
- Servicio de Neumologia, Hospital Universitario Nuestra Señora de la Candelaria, Tenerife, Spain
| | | | - Jose Maria Marin
- Servicio de Neumologia, Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Caroline A. Owen
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
| | - Rebeca Baz
- Servicio de Neumologia, Hospital Universitario Nuestra Señora de la Candelaria, Tenerife, Spain
| | - Elizabeth Cordova
- Servicio de Neumologia, Hospital Universitario Nuestra Señora de la Candelaria, Tenerife, Spain
| | - Bartolome Celli
- Pulmonary-Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
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Frasca M, Bianchi NC. Multitask Protein Function Prediction through Task Dissimilarity. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:1550-1560. [PMID: 28328509 DOI: 10.1109/tcbb.2017.2684127] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Automated protein function prediction is a challenging problem with distinctive features, such as the hierarchical organization of protein functions and the scarcity of annotated proteins for most biological functions. We propose a multitask learning algorithm addressing both issues. Unlike standard multitask algorithms, which use task (protein functions) similarity information as a bias to speed up learning, we show that dissimilarity information enforces separation of rare class labels from frequent class labels, and for this reason is better suited for solving unbalanced protein function prediction problems. We support our claim by showing that a multitask extension of the label propagation algorithm empirically works best when the task relatedness information is represented using a dissimilarity matrix as opposed to a similarity matrix. Moreover, the experimental comparison carried out on three model organism shows that our method has a more stable performance in both "protein-centric" and "function-centric" evaluation settings.
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43
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Rosado M, Silva R, G Bexiga M, G Jones J, Manadas B, Anjo SI. Advances in biomarker detection: Alternative approaches for blood-based biomarker detection. Adv Clin Chem 2019; 92:141-199. [PMID: 31472753 DOI: 10.1016/bs.acc.2019.04.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
In the clinical setting, a blood sample is typically the starting point for biomarker search and discovery. Mass spectrometry (MS) is a highly sensitive and informative method for characterizing a very wide range of metabolites and proteins and is therefore a potentially powerful tool for biomarker discovery. However, the physicochemical characteristics of blood coupled with very large ranges of protein and metabolite concentrations present a significant technical obstacle for resolving and quantifying putative biomarkers by MS. Blood fractionation procedures are being developed to reduce the proteome/metabolome complexity and concentration ranges, allowing a greater diversity of analytes, including those at very low concentrations, to be quantified. In this chapter, several strategies for enriching and/or isolating specific blood components are summarized, including methods for the analysis of low and high molecular weight compounds, usually neglected in this type of assays, extracellular vesicles, and peripheral blood mononuclear cells (PBMCs). For each method, relevant practical information is presented for effective implementation.
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Affiliation(s)
- Miguel Rosado
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
| | - Rafael Silva
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Mariana G Bexiga
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal; INEB-Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
| | - John G Jones
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Bruno Manadas
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Sandra I Anjo
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.
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Martin F, Talikka M, Ivanov NV, Haziza C, Hoeng J, Peitsch MC. A Meta-Analysis of the Performance of a Blood-Based Exposure Response Gene Signature Across Clinical Studies on the Tobacco Heating System 2.2 (THS 2.2). Front Pharmacol 2019; 10:198. [PMID: 30971916 PMCID: PMC6444181 DOI: 10.3389/fphar.2019.00198] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 02/18/2019] [Indexed: 11/28/2022] Open
Abstract
As part of emerging tobacco harm reduction strategies, modified risk tobacco products (MRTP) are being developed to offer alternatives that have the potential to reduce the individual risk and population harm compared with smoking cigarettes for adult smokers who want to continue using tobacco and nicotine products. MRTPs are defined as any tobacco products that are distributed for use to reduce harm or the risk of tobacco-related disease associated with commercially marketed tobacco products. One such candidate MRTP is the Tobacco Heating System (THS) 2.2, which does not burn tobacco but instead heats it, thus producing significantly reduced levels of harmful and potentially harmful constituents compared with cigarettes. The clinical assessment of candidate MRTPs requires the development of exposure-response markers to distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Toward this end, a whole blood-derived gene signature was previously developed and reported. Four randomized, controlled, open-label, three-arm parallel group reduced exposure clinical studies have been conducted with subjects randomized to three arms: switching from cigarettes to THS 2.2, continuous use of cigarettes, or smoking abstinence. These clinical studies had an investigational period of 5 days in confinement, which was followed by an 85-day ambulatory period in two studies. Here we tested the previously developed blood-derived signature on the samples derived from those clinical studies. We showed that in all four studies, the signature scores were reduced consistently in subjects who either stopped smoking or switched to THS 2.2 compared with subjects who continued smoking cigarettes.
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Affiliation(s)
- Florian Martin
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Marja Talikka
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Nikolai V Ivanov
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Christelle Haziza
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Julia Hoeng
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
| | - Manuel C Peitsch
- Philip Morris International Research and Development, Philip Morris Products S.A., Neuchâtel, Switzerland
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Morrow JD, Chase RP, Parker MM, Glass K, Seo M, Divo M, Owen CA, Castaldi P, DeMeo DL, Silverman EK, Hersh CP. RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD. Respir Res 2019; 20:65. [PMID: 30940135 PMCID: PMC6446359 DOI: 10.1186/s12931-019-1032-z] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Accepted: 03/25/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Multiple gene expression studies have been performed separately in peripheral blood, lung, and airway tissues to study COPD. We performed RNA-sequencing gene expression profiling of large-airway epithelium, alveolar macrophage and peripheral blood samples from the same subset of COPD cases and controls from the COPDGene study who underwent bronchoscopy at a single center. Using statistical and gene set enrichment approaches, we sought to improve the understanding of COPD by studying gene sets and pathways across these tissues, beyond the individual genomic determinants. METHODS We performed differential expression analysis using RNA-seq data obtained from 63 samples from 21 COPD cases and controls (includes four non-smokers) via the R package DESeq2. We tested associations between gene expression and variables related to lung function, smoking history, and CT scan measures of emphysema and airway disease. We examined the correlation of differential gene expression across the tissues and phenotypes, hypothesizing that this would reveal preserved and private gene expression signatures. We performed gene set enrichment analyses using curated databases and findings from prior COPD studies to provide biological and disease relevance. RESULTS The known smoking-related genes CYP1B1 and AHRR were among the top differential expression results for smoking status in the large-airway epithelium data. We observed a significant overlap of genes primarily across large-airway and macrophage results for smoking and airway disease phenotypes. We did not observe specific genes differentially expressed in all three tissues for any of the phenotypes. However, we did observe hemostasis and immune signaling pathways in the overlaps across all three tissues for emphysema, and amyloid and telomere-related pathways for smoking. In peripheral blood, the emphysema results were enriched for B cell related genes previously identified in lung tissue studies. CONCLUSIONS Our integrative analyses across COPD-relevant tissues and prior studies revealed shared and tissue-specific disease biology. These replicated and novel findings in the airway and peripheral blood have highlighted candidate genes and pathways for COPD pathogenesis.
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Affiliation(s)
- Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Kimberly Glass
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Minseok Seo
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Miguel Divo
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Caroline A Owen
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Peter Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
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46
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Wang L, Cheng H, Wang D, Zhao B, Zhang J, Cheng L, Yao P, Di Narzo A, Shen Y, Yu J, Li Y, Xu S, Chen J, Fan L, Lu J, Jiang J, Zhou Y, Wang C, Zhang Z, Hao K. Airway microbiome is associated with respiratory functions and responses to ambient particulate matter exposure. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2019; 167:269-277. [PMID: 30342360 PMCID: PMC6257984 DOI: 10.1016/j.ecoenv.2018.09.079] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2018] [Revised: 09/16/2018] [Accepted: 09/18/2018] [Indexed: 07/21/2023]
Abstract
BACKGROUND Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure. METHODS During October 2016-October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data: (1) respiratory functions, (2) airway microbiome from sputum, and (3) PM2.5 (PM of ≤ 2.5 µm in diameter) level in ambient air. We investigated the impact of PM2.5 on airway microbiome as well as the link between airway microbiome and respiratory functions using linear mixed regression models. RESULTS The respiratory function of our primary interest includes forced vital capacity (FVC) and forced expiratory volume in 1st second (FEV1). FEV1/FVC, an important respiratory function trait and key diagnosis criterion of COPD, was significantly associated with airway bacteria load (p = 0.0038); and FEV1 was associated with airway microbiome profile (p = 0.013). Further, airway microbiome was significantly influenced by PM2.5 exposure (p = 4.48E-11). CONCLUSIONS To our knowledge, for the first time, we demonstrated the impact of PM2.5 on airway microbiome, and reported the link between airway microbiome and respiratory functions. The results expand our understanding on the scope of PM2.5 exposure's influence on human respiratory system, and point to novel etiological mechanism of PM2.5 exposure induced diseases.
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Affiliation(s)
- Liping Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dongbin Wang
- School of Environment, Tsinghua University, Beijing, China
| | - Bo Zhao
- School of Life Sciences, Tongji University, Shanghai, China
| | - Jushan Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Long Cheng
- School of Software Engineering, Tongji University, Shanghai, China
| | - Pengfei Yao
- School of Software Engineering, Tongji University, Shanghai, China
| | - Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yuan Shen
- Department of Psychiatry, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jing Yu
- Department of Ophthalmology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Yuanyuan Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shunqing Xu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lihong Fan
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jianwei Lu
- School of Software Engineering, Tongji University, Shanghai, China
| | - Jingkun Jiang
- School of Environment, Tsinghua University, Beijing, China
| | - Yang Zhou
- School of Life Sciences, Tongji University, Shanghai, China
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Ke Hao
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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47
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Reinhold D, Pielke-Lombardo H, Jacobson S, Ghosh D, Kechris K. Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data. Methods Mol Biol 2019; 1978:323-340. [PMID: 31119672 PMCID: PMC7346099 DOI: 10.1007/978-1-4939-9236-2_20] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Metabolomics is the science of characterizing and quantifying small molecule metabolites in biological systems. These metabolites give organisms their biochemical characteristics, providing a link between genotype, environment, and phenotype. With these opportunities also come data challenges, such as compound annotation, missing values, and batch effects. We present the steps of a general pipeline to process untargeted mass spectrometry data to alleviate the latter two challenges. We assume to have a matrix with metabolite abundances, with metabolites in rows and samples in columns. The steps in the pipeline include summarizing technical replicates (if available), filtering, imputing, transforming, and normalizing the data. In each of these steps, a method and parameters should be chosen based on assumptions one is willing to make, the question of interest, and diagnostic tools. Besides giving a general pipeline that can be adapted by the reader, our goal is to review diagnostic tools and criteria that are helpful when making decisions in each step of the pipeline and assessing the effectiveness of normalization and batch correction. We conclude by giving a list of useful packages and discuss some alternative approaches that might be more appropriate for the reader's data.
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Affiliation(s)
| | - Harrison Pielke-Lombardo
- Computational Bioscience Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sean Jacobson
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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48
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Zhang C, Ramsey C, Berical A, Yu L, Leng L, McGinnis KA, Song Y, Michael H, McCormack MC, Allore H, Morris A, Crothers K, Bucala R, Lee PJ, Sauler M. A functional macrophage migration inhibitory factor promoter polymorphism is associated with reduced diffusing capacity. Am J Physiol Lung Cell Mol Physiol 2018; 316:L400-L405. [PMID: 30520689 DOI: 10.1152/ajplung.00439.2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Cigarette smoke exposure is the leading modifiable risk factor for chronic obstructive pulmonary disease (COPD); however, the clinical and pathologic consequences of chronic cigarette smoke exposure are variable among smokers. Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine implicated in the pathogenesis of COPD. Within the promoter of the MIF gene is a functional polymorphism that regulates MIF expression (-794 CATT5-8 microsatellite repeat) ( rs5844572 ). The role of this polymorphim in mediating disease susceptibility to COPD-related traits remains unknown. We performed a cross-sectional analysis of DNA samples from 641 subjects to analyze MIF-794 CATT5-8 ( rs5844572 ) polymorphism by standard methods. We generated multivariable logistic regression models to determine the risk of low expressing MIF alleles for airflow obstruction [defined by forced expiratory volume in 1 s (FEV1)/forced vital capacity ratio <0.70] and an abnormal diffusion capacity [defined by a diffusion capacity for carbon monoxide (DLCO) percent predicted <80%]. We then used generalized linear models to determine the association of MIF genotypes with FEV1 percent predicted and DLCO percent predicted. The MIF-794 CATT5 allele was associated with an abnormal diffusion capacity in two cohorts [odds ratio (OR): 9.31, 95% confidence interval (CI): 1.97-4.06; and OR: 2.21, 95% CI: 1.03-4.75]. Similarly, the MIF-794 CATT5 allele was associated with a reduced DLCO percentage predicted in these two cohorts: 63.5 vs. 70.0 ( P = 0.0023) and 60.1 vs. 65.4 ( P = 0.059). This study suggests an association between a common genetic polymorphism of an endogenous innate immune gene, MIF, with reduced DLCO, an important measurement of COPD severity.
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Affiliation(s)
- C Zhang
- Department of Medicine Saint Louis University Hospital , Saint Louis, Missouri
| | - C Ramsey
- Yale Center for Medical Informatics, Yale School of Medicine , New Haven, Connecticut
| | - A Berical
- Department of Medicine, Boston University School of Medicine , Boston, Massachusetts
| | - L Yu
- Department of Medicine, Massachusetts General Hospital , Boston, Massachusetts
| | - L Leng
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
| | - K A McGinnis
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
| | - Y Song
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
| | - H Michael
- Department of Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - M C McCormack
- Department of Medicine, Johns Hopkins University , Baltimore, Maryland
| | - H Allore
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
| | - A Morris
- Department of Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - K Crothers
- Department of Medicine, University of Washington School of Medicine , Seattle, Washington
| | - R Bucala
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
| | - P J Lee
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
| | - M Sauler
- Department of Medicine, Yale School of Medicine , New Haven, Connecticut
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49
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Metabolomics and transcriptomics pathway approach reveals outcome-specific perturbations in COPD. Sci Rep 2018; 8:17132. [PMID: 30459441 PMCID: PMC6244246 DOI: 10.1038/s41598-018-35372-w] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 10/25/2018] [Indexed: 12/22/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) comprises multiple phenotypes such as airflow obstruction, emphysema, and frequent episodes of acute worsening of respiratory symptoms, known as exacerbations. The goal of this pilot study was to test the usefulness of unbiased metabolomics and transcriptomics approaches to delineate biological pathways associated with COPD phenotypes and outcomes. Blood was collected from 149 current or former smokers with or without COPD and separated into peripheral blood mononuclear cells (PBMC) and plasma. PBMCs and plasma were analyzed using microarray and liquid chromatography mass spectrometry, respectively. Statistically significant transcripts and compounds were mapped to pathways using IMPaLA. Results showed that glycerophospholipid metabolism was associated with worse airflow obstruction and more COPD exacerbations. Sphingolipid metabolism was associated with worse lung function outcomes and exacerbation severity requiring hospitalizations. The strongest associations between a pathway and a certain COPD outcome were: fat digestion and absorption and T cell receptor signaling with lung function outcomes; antigen processing with exacerbation frequency; arginine and proline metabolism with exacerbation severity; and oxidative phosphorylation with emphysema. Overlaying transcriptomic and metabolomics datasets across pathways enabled outcome and phenotypic differences to be determined. Findings are relevant for identifying molecular targets for animal intervention studies and early intervention markers in human cohorts.
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50
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Sharma A, Kitsak M, Cho MH, Ameli A, Zhou X, Jiang Z, Crapo JD, Beaty TH, Menche J, Bakke PS, Santolini M, Silverman EK. Integration of Molecular Interactome and Targeted Interaction Analysis to Identify a COPD Disease Network Module. Sci Rep 2018; 8:14439. [PMID: 30262855 PMCID: PMC6160419 DOI: 10.1038/s41598-018-32173-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 08/20/2018] [Indexed: 12/21/2022] Open
Abstract
The polygenic nature of complex diseases offers potential opportunities to utilize network-based approaches that leverage the comprehensive set of protein-protein interactions (the human interactome) to identify new genes of interest and relevant biological pathways. However, the incompleteness of the current human interactome prevents it from reaching its full potential to extract network-based knowledge from gene discovery efforts, such as genome-wide association studies, for complex diseases like chronic obstructive pulmonary disease (COPD). Here, we provide a framework that integrates the existing human interactome information with experimental protein-protein interaction data for FAM13A, one of the most highly associated genetic loci to COPD, to find a more comprehensive disease network module. We identified an initial disease network neighborhood by applying a random-walk method. Next, we developed a network-based closeness approach (CAB) that revealed 9 out of 96 FAM13A interacting partners identified by affinity purification assays were significantly close to the initial network neighborhood. Moreover, compared to a similar method (local radiality), the CAB approach predicts low-degree genes as potential candidates. The candidates identified by the network-based closeness approach were combined with the initial network neighborhood to build a comprehensive disease network module (163 genes) that was enriched with genes differentially expressed between controls and COPD subjects in alveolar macrophages, lung tissue, sputum, blood, and bronchial brushing datasets. Overall, we demonstrate an approach to find disease-related network components using new laboratory data to overcome incompleteness of the current interactome.
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Affiliation(s)
- Amitabh Sharma
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA. .,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA. .,Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, MA, 02115, USA. .,Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA, 02115, USA.
| | - Maksim Kitsak
- Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, MA, 02115, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA.,Pulmonary and Critical Care Division, Brigham and Women's Hospital and Harvard Medical School, Boston, USA.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Asher Ameli
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA.,Department of Physics, Northeastern University, Boston, MA, 02115, United States
| | - Xiaobo Zhou
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Zhiqiang Jiang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA
| | - James D Crapo
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jörg Menche
- Department of Bioinformatics, CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, A-1090, Vienna, Austria
| | - Per S Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Marc Santolini
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA.,Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, MA, 02115, USA.,Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, USA. .,Pulmonary and Critical Care Division, Brigham and Women's Hospital and Harvard Medical School, Boston, USA. .,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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