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Nascimento M, Huot-Marchand S, Fanny M, Straube M, Le Bert M, Savigny F, Apetoh L, Van Snick J, Trovero F, Chamaillard M, Quesniaux VFJ, Ryffel B, Gosset P, Gombault A, Riteau N, Sokol H, Couillin I. NLRP6 controls pulmonary inflammation from cigarette smoke in a gut microbiota-dependent manner. Front Immunol 2023; 14:1224383. [PMID: 38146368 PMCID: PMC10749332 DOI: 10.3389/fimmu.2023.1224383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/20/2023] [Indexed: 12/27/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a major health issue primarily caused by cigarette smoke (CS) and characterized by breathlessness and repeated airway inflammation. NLRP6 is a cytosolic innate receptor controlling intestinal inflammation and orchestrating the colonic host-microbial interface. However, its roles in the lungs remain largely unexplored. Using CS exposure models, our data show that airway inflammation is strongly impaired in Nlrp6-deficient mice with drastically fewer recruited neutrophils, a key cell subset in inflammation and COPD. We found that NLRP6 expression in lung epithelial cells is important to control airway and lung tissue inflammation in an inflammasome-dependent manner. Since gut-derived metabolites regulate NLRP6 inflammasome activation in intestinal epithelial cells, we investigated the link between NLRP6, CS-driven lung inflammation, and gut microbiota composition. We report that acute CS exposure alters gut microbiota in both wild-type (WT) and Nlrp6-deficient mice and that antibiotic treatment decreases CS-induced lung inflammation. In addition, gut microbiota transfer from dysbiotic Nlrp6-deficient mice to WT mice decreased airway lung inflammation in WT mice, highlighting an NLRP6-dependent gut-to-lung axis controlling pulmonary inflammation.
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Affiliation(s)
- Mégane Nascimento
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Sarah Huot-Marchand
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Manoussa Fanny
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Marjolène Straube
- Sorbonne Université, Institut National de la Recherche Médicale (INSERM), Centre de Recherche Saint-Antoine (CRSA), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Saint Antoine, Service de Gastroenterologie, Paris, France
| | - Marc Le Bert
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Florence Savigny
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | | | | | | | - Mathias Chamaillard
- Univ. Lille, Institut National de la Recherche Médicale (INSERM), U1003 - Laboratoire de physiologie cellulaire (PHYCEL) - Physiologie Cellulaire, Lille, France
| | - Valérie F. J. Quesniaux
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Bernhard Ryffel
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Philippe Gosset
- Institut PASTEUR INSERM U1019, Centre National de Recherche (CNRS) Unité Mixte de Recherche (UMR) 8204, Lille, France
| | - Aurélie Gombault
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Nicolas Riteau
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
| | - Harry Sokol
- Sorbonne Université, Institut National de la Recherche Médicale (INSERM), Centre de Recherche Saint-Antoine (CRSA), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Saint Antoine, Service de Gastroenterologie, Paris, France
- Institut national de la recherche agronomique (INRA), UMR1319 Micalis, AgroParisTech, Jouy-en-Josas, France
- Paris Centre for Microbiome Medicine (PaCeMM) FHU, Paris, France
| | - Isabelle Couillin
- University of Orleans and Centre National de Recherche scientifique (CNRS), Experimental and Molecular Immunology and Neurogenetics (INEM)-UMR7355, Orleans, France
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Balnis J, Lauria EJM, Yucel R, Singer HA, Alisch RS, Jaitovich A. Peripheral Blood Omics and Other Multiplex-based Systems in Pulmonary and Critical Care Medicine. Am J Respir Cell Mol Biol 2023; 69:383-390. [PMID: 37379507 PMCID: PMC10557924 DOI: 10.1165/rcmb.2023-0153ps] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 06/28/2023] [Indexed: 06/30/2023] Open
Abstract
Over the last years, the use of peripheral blood-derived big datasets in combination with machine learning technology has accelerated the understanding, prediction, and management of pulmonary and critical care conditions. The goal of this article is to provide readers with an introduction to the methods and applications of blood omics and other multiplex-based technologies in the pulmonary and critical care medicine setting to better appreciate the current literature in the field. To accomplish that, we provide essential concepts needed to rationalize this approach and introduce readers to the types of molecules that can be obtained from the circulating blood to generate big datasets; elaborate on the differences between bulk, sorted, and single-cell approaches; and the basic analytical pipelines required for clinical interpretation. Examples of peripheral blood-derived big datasets used in recent literature are presented, and limitations of that technology are highlighted to qualify both the current and future value of these methodologies.
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Affiliation(s)
- Joseph Balnis
- Division of Pulmonary and Critical Care Medicine and
- Department of Molecular and Cellular Physiology, Albany Medical College, Albany, New York
| | - Eitel J. M. Lauria
- School of Computer Science and Mathematics, Marist College, Poughkeepsie, New York
| | - Recai Yucel
- Department of Epidemiology and Biostatistics, Temple University, Philadelphia, Pennsylvania; and
| | - Harold A. Singer
- Department of Molecular and Cellular Physiology, Albany Medical College, Albany, New York
| | - Reid S. Alisch
- Department of Neurological Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Ariel Jaitovich
- Division of Pulmonary and Critical Care Medicine and
- Department of Molecular and Cellular Physiology, Albany Medical College, Albany, New York
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3
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Zhu Z, Li Y, Freishtat RJ, Celedón JC, Espinola JA, Harmon B, Hahn A, Camargo CA, Liang L, Hasegawa K. Epigenome-wide association analysis of infant bronchiolitis severity: a multicenter prospective cohort study. Nat Commun 2023; 14:5495. [PMID: 37679381 PMCID: PMC10485022 DOI: 10.1038/s41467-023-41300-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
Abstract
Bronchiolitis is the most common lower respiratory infection in infants, yet its pathobiology remains unclear. Here we present blood DNA methylation data from 625 infants hospitalized with bronchiolitis in a 17-center prospective study, and associate them with disease severity. We investigate differentially methylated CpGs (DMCs) for disease severity. We characterize the DMCs based on their association with cell and tissues types, biological pathways, and gene expression. Lastly, we also examine the relationships of severity-related DMCs with respiratory and immune traits in independent cohorts. We identify 33 DMCs associated with severity. These DMCs are differentially methylated in blood immune cells. These DMCs are also significantly enriched in multiple tissues (e.g., lung) and cells (e.g., small airway epithelial cells), and biological pathways (e.g., interleukin-1-mediated signaling). Additionally, these DMCs are associated with respiratory and immune traits (e.g., asthma, lung function, IgE levels). Our study suggests the role of DNA methylation in bronchiolitis severity.
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Affiliation(s)
- Zhaozhong Zhu
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Yijun Li
- Department of Epidemiology, Harvard T.H.Chan School of Public Health, Boston, MA, USA
| | - Robert J Freishtat
- Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, USA
- Division of Emergency Medicine, Children's National Hospital, Washington, DC, USA
- Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Juan C Celedón
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Janice A Espinola
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Brennan Harmon
- Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, USA
| | - Andrea Hahn
- Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, USA
- Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
- Division of Infectious Diseases, Children's National Hospital, Washington, DC, USA
| | - Carlos A Camargo
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H.Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H.Chan School of Public Health, Boston, MA, USA
| | - Kohei Hasegawa
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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4
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Dugué PA, Yu C, Hodge AM, Wong EM, Joo JE, Jung CH, Schmidt D, Makalic E, Buchanan DD, Severi G, English DR, Hopper JL, Milne RL, Giles GG, Southey MC. Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer. Int J Cancer 2023; 153:489-498. [PMID: 36919377 DOI: 10.1002/ijc.34513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 03/16/2021] [Accepted: 03/22/2021] [Indexed: 03/16/2023]
Abstract
Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.
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Affiliation(s)
- Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Allison M Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - JiHoon E Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Chol-Hee Jung
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
| | - Daniel Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Department of Data Science and AI, Faculty of IT, Monash University, Clayton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
- Melbourne Bioinformatics, University of Melbourne, Parkville, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Gianluca Severi
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Médecine Universités Paris-Saclay, UVSQ, Gustave Roussy, Villejuif, France
| | - Dallas R English
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Roger L Milne
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Graham G Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
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McCrory C, Fiorito G, O'Halloran AM, Polidoro S, Vineis P, Kenny RA. Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks. Psychoneuroendocrinology 2022; 137:105643. [PMID: 34999481 DOI: 10.1016/j.psyneuen.2021.105643] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 10/29/2021] [Accepted: 12/21/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE This retrospective cross-sectional study was designed to explore whether the experience of childhood adversity was associated with epigenetic age acceleration in mid-life and older ages using the next generation GrimAge and Pace of Aging DNA methylation clocks. METHOD The study involved a sub-sample of 490 individuals aged 50-87 years of age participating in the Irish Longitudinal Study on Aging (TILDA); a large nationally representative prospective cohort study of aging in Ireland. Childhood adversity was ascertained via self-report using 5-items that were deemed to indicate potentially nefarious childhood exposures, including growing up poor, death of a parent, parental substance abuse in the family, childhood physical abuse, and childhood sexual abuse. RESULTS Only childhood poverty was associated with significant epigenetic age acceleration according to the GrimAge and Pace of Aging clocks, hastening biological aging by 2.04 years [CI= 1.07, 3.00; p < 0.001] and 1.16 years [CI= 0.11, 2.21; p = 0.030] respectively. Analysis of the dose-response pattern revealed each additional adversity was associated with 0.69 years of age acceleration [CI= 0.23, 1.15; p = 0.004] according to the GrimAge clock. Mediation analysis suggested that lifetime smoking explains a substantial portion (>50%) of the excess risk of age acceleration amongst those who experienced childhood poverty. CONCLUSIONS This study adds to the growing body of evidence which implicates early life adversity, particularly deprivation as a potential precipitant of earlier biological aging, and implicates smoking-related changes to DNA methylation processes as a candidate pathway and mechanism through which the social environment gets transduced at a biological level to hasten the aging process.
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Fan H, Xie Q, Zhang Z, Wang J, Chen X, Qiu P. Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models. Front Bioeng Biotechnol 2022; 9:819991. [PMID: 35141217 PMCID: PMC8819006 DOI: 10.3389/fbioe.2021.819991] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 12/21/2021] [Indexed: 11/13/2022] Open
Abstract
Epigenetic clock, a highly accurate age estimator based on DNA methylation (DNAm) level, is the basis for predicting mortality/morbidity and elucidating the molecular mechanism of aging, which is of great significance in forensics, justice, and social life. Herein, we integrated machine learning (ML) algorithms to construct blood epigenetic clock in Southern Han Chinese (CHS) for chronological age prediction. The correlation coefficient (r) meta-analyses of 7,084 individuals were firstly implemented to select five genes (ELOVL2, C1orf132, TRIM59, FHL2, and KLF14) from a candidate set of nine age-associated DNAm biomarkers. The DNAm-based profiles of the CHS cohort (240 blood samples differing in age from 1 to 81 years) were generated by the bisulfite targeted amplicon pyrosequencing (BTA-pseq) from 34 cytosine-phosphate-guanine sites (CpGs) of five selected genes, revealing that the methylation levels at different CpGs exhibit population specificity. Furthermore, we established and evaluated four chronological age prediction models using distinct ML algorithms: stepwise regression (SR), support vector regression (SVR-eps and SVR-nu), and random forest regression (RFR). The median absolute deviation (MAD) values increased with chronological age, especially in the 61–81 age category. No apparent gender effect was found in different ML models of the CHS cohort (all p > 0.05). The MAD values were 2.97, 2.22, 2.19, and 1.29 years for SR, SVR-eps, SVR-nu, and RFR in the CHS cohort, respectively. Eventually, compared to the MAD range of the meta cohort (2.53–5.07 years), a promising RFR model (ntree = 500 and mtry = 8) was optimized with an MAD of 1.15 years in the 1–60 age categories of the CHS cohort, which could be regarded as a robust epigenetic clock in blood for age-related issues.
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Affiliation(s)
- Haoliang Fan
- *Correspondence: Haoliang Fan, ; Xuncai Chen, ; Pingming Qiu,
| | | | | | | | - Xuncai Chen
- *Correspondence: Haoliang Fan, ; Xuncai Chen, ; Pingming Qiu,
| | - Pingming Qiu
- *Correspondence: Haoliang Fan, ; Xuncai Chen, ; Pingming Qiu,
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Bravo-Gutiérrez OA, Falfán-Valencia R, Ramírez-Venegas A, Sansores RH, Hernández-Zenteno RJ, Hernández-Pérez A, García-Gómez L, Osio-Echánove J, Abarca-Rojano E, Pérez-Rubio G. Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population. Genes (Basel) 2021; 12:1276. [PMID: 34440450 DOI: 10.3390/genes12081276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/16/2021] [Accepted: 08/19/2021] [Indexed: 11/17/2022] Open
Abstract
Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).
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Abstract
The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.
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Affiliation(s)
- Xiaojing Chu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Bowen Zhang
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Valerie A. C. M. Koeken
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
| | - Manoj Kumar Gupta
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
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9
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Koo HK, Morrow J, Kachroo P, Tantisira K, Weiss ST, Hersh CP, Silverman EK, DeMeo DL. Sex-specific associations with DNA methylation in lung tissue demonstrate smoking interactions. Epigenetics 2021; 16:692-703. [PMID: 32962511 PMCID: PMC8143227 DOI: 10.1080/15592294.2020.1819662] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 08/08/2020] [Accepted: 08/18/2020] [Indexed: 01/01/2023] Open
Abstract
Cigarette smoking impacts DNA methylation, but the investigation of sex-specific features of lung tissue DNA methylation in smokers has been limited. Women appear more susceptible to cigarette smoke, and often develop more severe lung disease at an earlier age with less smoke exposure. We aimed to analyse whether there are sex differences in DNA methylation in lung tissue and whether these DNA methylation marks interact with smoking. We collected lung tissue samples from former smokers who underwent lung tissue resection. One hundred thirty samples from white subjects were included for this analysis. Regression models for sex as a predictor of methylation were adjusted for age, presence of COPD, smoking variables and technical batch variables revealed 710 associated sites. 294 sites demonstrated robust sex-specific methylation associations in foetal lung tissue. Pathway analysis identified 6 nominally significant pathways including the mitophagy pathway. Three CpG sites demonstrated a suggested interaction between sex and pack-years of smoking: GPR132, ANKRD44 and C19orf60. All of them were nominally significant in both male- and female-specific models, and the effect estimates were in opposite directions for male and female; GPR132 demonstrated significant association between DNA methylation and gene expression in lung tissue (P < 0.05). Sex-specific associations with DNA methylation in lung tissue are wide-spread and may reveal genes and pathways relevant to sex differences for lung damaging effects of cigarette smoking.
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Affiliation(s)
- Hyeon-Kyoung Koo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Ilsan, Republic of Korea
| | - Jarrett Morrow
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Kelan Tantisira
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
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Terzikhan N, Xu H, Edris A, Bracke KR, Verhamme FM, Stricker BH, Dupuis J, Lahousse L, O'Connor GT, Brusselle GG. Epigenome-wide association study on diffusing capacity of the lung. ERJ Open Res 2021; 7:00567-2020. [PMID: 33748261 PMCID: PMC7957297 DOI: 10.1183/23120541.00567-2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 09/21/2020] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Epigenetics may play an important role in the pathogenesis of lung diseases. However, little is known about the epigenetic factors that influence impaired gas exchange at the lung. AIM To identify the epigenetic signatures of the diffusing capacity of the lung measured by carbon monoxide uptake (the diffusing capacity of the lung for carbon monoxide (D LCO)). METHODS An epigenome-wide association study (EWAS) was performed on diffusing capacity, measured by carbon monoxide uptake (D LCO) and per alveolar volume (V A) (as D LCO/V A), using the single-breath technique in 2674 individuals from two population-based cohort studies. These were the Rotterdam Study (RS, the "discovery panel") and the Framingham Heart Study (FHS, the "replication panel"). We assessed the clinical relevance of our findings by investigating the identified sites in whole blood and by lung tissue specific gene expression. RESULTS We identified and replicated two CpG sites (cg05575921 and cg05951221) that were significantly associated with D LCO/V A and one (cg05575921) suggestively associated with D LCO. Furthermore, we found a positive association between aryl hydrocarbon receptor repressor (AHRR) gene (cg05575921) hypomethylation and gene expression of exocyst complex component 3 (EXOC3) in whole blood. We confirmed that the expression of EXOC3 in lung tissue is positively associated with D LCO/V A and D LCO. CONCLUSIONS We report on epigenome-wide associations with diffusing capacity in the general population. Our results suggest EXOC3 to be an excellent candidate, through which smoking-induced hypomethylation of AHRR might affect pulmonary gas exchange.
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Affiliation(s)
- Natalie Terzikhan
- Dept of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Dept of Epidemiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
- These authors contributed equally
| | - Hanfei Xu
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- These authors contributed equally
| | - Ahmed Edris
- Dept of Epidemiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
- Dept of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Ken R. Bracke
- Dept of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Fien M. Verhamme
- Dept of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Bruno H.C. Stricker
- Dept of Epidemiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Josée Dupuis
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- These authors contributed equally
| | - Lies Lahousse
- Dept of Epidemiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
- Dept of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
- These authors contributed equally
| | - George T. O'Connor
- Pulmonary Center, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- These authors contributed equally
| | - Guy G. Brusselle
- Dept of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Dept of Epidemiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
- Dept of Respiratory Medicine, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
- These authors contributed equally
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Swarr D, Putcha N, Zacharias W. "PIK"ing Out New Epigenetic Markers in Lung Disease. Am J Respir Crit Care Med 2020; 201:1029-1030. [PMID: 32109362 PMCID: PMC7193860 DOI: 10.1164/rccm.202002-0295ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Daniel Swarr
- Cincinnati Children's HospitalUniversity of Cincinnati School of MedicineCincinnati, Ohioand
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care MedicineJohns Hopkins University School of MedicineBaltimore, Maryland
| | - William Zacharias
- Cincinnati Children's HospitalUniversity of Cincinnati School of MedicineCincinnati, Ohioand
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Arslan AA, Tuminello S, Yang L, Zhang Y, Durmus N, Snuderl M, Heguy A, Zeleniuch-Jacquotte A, Shao Y, Reibman J. Genome-Wide DNA Methylation Profiles in Community Members Exposed to the World Trade Center Disaster. Int J Environ Res Public Health 2020; 17:ijerph17155493. [PMID: 32751422 PMCID: PMC7432006 DOI: 10.3390/ijerph17155493] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/22/2020] [Accepted: 07/25/2020] [Indexed: 12/17/2022]
Abstract
The primary goal of this pilot study was to assess feasibility of studies among local community members to address the hypothesis that complex exposures to the World Trade Center (WTC) dust and fumes resulted in long-term epigenetic changes. We enrolled 18 WTC-exposed cancer-free women from the WTC Environmental Health Center (WTC EHC) who agreed to donate blood samples during their standard clinical visits. As a reference WTC unexposed group, we randomly selected 24 age-matched cancer-free women from an existing prospective cohort who donated blood samples before 11 September 2001. The global DNA methylation analyses were performed using Illumina Infinium MethylationEpic arrays. Statistical analyses were performed using R Bioconductor package. Functional genomic analyses were done by mapping the top 5000 differentially expressed CpG sites to the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database. Among cancer-free subjects, we observed substantial methylation differences between WTC-exposed and unexposed women. The top 15 differentially methylated gene probes included BCAS2, OSGIN1, BMI1, EEF1A2, SPTBN5, CHD8, CDCA7L, AIDA, DDN, SNORD45C, ZFAND6, ARHGEF7, UBXN8, USF1, and USP12. Several cancer-related pathways were enriched in the WTC-exposed subjects, including endocytosis, mitogen-activated protein kinase (MAPK), viral carcinogenesis, as well as Ras-associated protein-1 (Rap1) and mammalian target of rapamycin (mTOR) signaling. The study provides preliminary data on substantial differences in DNA methylation between WTC-exposed and unexposed populations that require validation in further studies.
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Affiliation(s)
- Alan A. Arslan
- Department of Obstetrics and Gynecology, New York University Langone Health, New York, NY 10016, USA
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
- NYU Perlmutter Comprehensive Cancer Center, New York, NY 10016, USA
- Correspondence:
| | - Stephanie Tuminello
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
| | - Lei Yang
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
| | - Yian Zhang
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
| | - Nedim Durmus
- Department of Medicine, New York University Langone Health, New York, NY 10016, USA; (N.D.); (J.R.)
| | - Matija Snuderl
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA; (M.S.); (A.H.)
| | - Adriana Heguy
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA; (M.S.); (A.H.)
- NYU Langone’s Genome Technology Center, New York, NY 10016, USA
| | - Anne Zeleniuch-Jacquotte
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
- NYU Perlmutter Comprehensive Cancer Center, New York, NY 10016, USA
| | - Yongzhao Shao
- Department of Population Health, New York University Langone Health, New York, NY 10016, USA; (S.T.); (L.Y.); (Y.Z.); (A.Z.-J.); (Y.S.)
- NYU Perlmutter Comprehensive Cancer Center, New York, NY 10016, USA
| | - Joan Reibman
- Department of Medicine, New York University Langone Health, New York, NY 10016, USA; (N.D.); (J.R.)
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