1
|
Eckhardt CM, Balte P, Morris JE, Bhatt SP, Couper D, Fetterman J, Freedman N, Jacobs DR, Hou L, Kalhan R, Liu Y, Loehr L, Lutsey PL, Schwartz JE, White W, Yende S, London SJ, Sanchez TR, Oelsner EC. Non-cigarette tobacco products, aryl-hydrocarbon receptor repressor gene methylation and smoking-related health outcomes. Thorax 2024:thorax-2023-220731. [PMID: 39033027 DOI: 10.1136/thorax-2023-220731] [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: 07/18/2023] [Accepted: 07/01/2024] [Indexed: 07/23/2024]
Abstract
INTRODUCTION Cigarette smoking leads to altered DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) gene. However, it remains unknown whether pipe or cigar smoking is associated with AHRR methylation. We evaluated associations of non-cigarette tobacco use with AHRR methylation and determined if AHRR methylation was associated with smoking-related health outcomes. METHODS Data were pooled across four population-based cohorts that enrolled participants from 1985 to 2002. Tobacco exposures were evaluated using smoking questionnaires. AHRR cg05575921 methylation was measured in peripheral blood leucocyte DNA. Spirometry and respiratory symptoms were evaluated at the time of methylation measurements and in subsequent visits. Vital status was monitored using the National Death Index. RESULTS Among 8252 adults (mean age 56.7±10.3 years, 58.1% women, 40.6% black), 4857 (58.9%) participants used cigarettes and 634 (7.7%) used non-cigarette tobacco products. Exclusive use of non-cigarette tobacco products was independently associated with lower AHRR methylation (-2.44 units, 95% CI -4.42 to -0.45), though to a lesser extent than exclusive use of cigarettes (-6.01 units, 95% CI -6.01 to -4.10). Among participants who exclusively used non-cigarette tobacco products, reduced AHRR methylation was associated with increased respiratory symptom burden (OR 1.60, 95% CI 1.03 to 2.68) and higher all-cause mortality (log-rank p=0.02). CONCLUSION Pipe and cigar smoking were independently associated with lower AHRR methylation in a multiethnic cohort of US adults. Among users of non-cigarette tobacco products, lower AHRR methylation was associated with poor respiratory health outcomes and increased mortality. AHRR methylation may identify non-cigarette tobacco users with an increased risk of adverse smoking-related health outcomes.
Collapse
Affiliation(s)
- Christina M Eckhardt
- Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
- Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Pallavi Balte
- Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Jack E Morris
- Columbia University Mailman School of Public Health, New York, New York, USA
| | - Surya P Bhatt
- Pulmonary, Allergy and Critical Care Medicine, University of Alabama School of Natural Sciences and Mathematics, Birmingham, Alabama, USA
| | - David Couper
- Biostatistics, The University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Neal Freedman
- Nutritional Epidemiology, National Institutes of Health, Bethesda, Maryland, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Lifang Hou
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Ravi Kalhan
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Yongmei Liu
- Duke University, Durham, North Carolina, USA
| | - Laura Loehr
- The University of North Carolina, Chapel Hill, North Carolina, USA
| | - Pamela L Lutsey
- University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Joseph E Schwartz
- Center for Behavioral Cardiovascular Health, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Wendy White
- Tougaloo College, Tougaloo, Mississippi, USA
| | - Sachin Yende
- University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Tiffany R Sanchez
- Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Elizabeth C Oelsner
- Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| |
Collapse
|
2
|
Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [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: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
Collapse
Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
| |
Collapse
|
3
|
Zhang T, Sang J, Hoang PH, Zhao W, Rosenbaum J, Johnson KE, Klimczak LJ, McElderry J, Klein A, Wirth C, Bergstrom EN, Díaz-Gay M, Vangara R, Colon-Matos F, Hutchinson A, Lawrence SM, Cole N, Zhu B, Przytycka TM, Shi J, Caporaso NE, Homer R, Pesatori AC, Consonni D, Imielinski M, Chanock SJ, Wedge DC, Gordenin DA, Alexandrov LB, Harris RS, Landi MT. APOBEC shapes tumor evolution and age at onset of lung cancer in smokers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587805. [PMID: 38617360 PMCID: PMC11014539 DOI: 10.1101/2024.04.02.587805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.
Collapse
Affiliation(s)
- Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jian Sang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Phuc H. Hoang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | | | | | - Leszek J. Klimczak
- Integrative Bioinformatics Support Group, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - John McElderry
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Alyssa Klein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Christopher Wirth
- Manchester Cancer Research Centre, The University of Manchester, Manchester, UK
| | - Erik N. Bergstrom
- Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Marcos Díaz-Gay
- Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Raviteja Vangara
- Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Frank Colon-Matos
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Amy Hutchinson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Scott M. Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Nathan Cole
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Bin Zhu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Teresa M. Przytycka
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Neil E. Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Robert Homer
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Angela C. Pesatori
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Dario Consonni
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - David C. Wedge
- Manchester Cancer Research Centre, The University of Manchester, Manchester, UK
| | - Dmitry A. Gordenin
- Genome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Ludmil B. Alexandrov
- Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Reuben S. Harris
- Department of Biochemistry and Structural Biology, University of Texas Health San Antonio, San Antonio, TX, USA
- Howard Hughes Medical Institute, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| |
Collapse
|
4
|
Tomkiewicz C, Coumoul X, Nioche P, Barouki R, Blanc EB. Costs of molecular adaptation to the chemical exposome: a focus on xenobiotic metabolism pathways. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220510. [PMID: 38310928 PMCID: PMC10838638 DOI: 10.1098/rstb.2022.0510] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 12/04/2023] [Indexed: 02/06/2024] Open
Abstract
Organisms adapt to their environment through different pathways. In vertebrates, xenobiotics are detected, metabolized and eliminated through the inducible xenobiotic-metabolizing pathways (XMP) which can also generate reactive toxic intermediates. In this review, we will discuss the impacts of the chemical exposome complexity on the balance between detoxication and side effects. There is a large discrepancy between the limited number of proteins involved in these pathways (few dozens) and the diversity and complexity of the chemical exposome (tens of thousands of chemicals). Several XMP proteins have a low specificity which allows them to bind and/or metabolize a large number of chemicals. This leads to undesired consequences, such as cross-inhibition, inefficient metabolism, release of toxic intermediates, etc. Furthermore, several XMP proteins have endogenous functions that may be disrupted upon exposure to exogenous chemicals. The gut microbiome produces a very large number of metabolites that enter the body and are part of the chemical exposome. It can metabolize xenobiotics and either eliminate them or lead to toxic derivatives. The complex interactions between chemicals of different origins will be illustrated by the diverse roles of the aryl hydrocarbon receptor which binds and transduces the signals of a large number of xenobiotics, microbiome metabolites, dietary chemicals and endogenous compounds. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.
Collapse
Affiliation(s)
| | - Xavier Coumoul
- Université Paris Cité, Inserm unit UMRS 1124, 75006 Paris, France
| | - Pierre Nioche
- Université Paris Cité, Inserm unit UMRS 1124, 75006 Paris, France
| | - Robert Barouki
- Université Paris Cité, Inserm unit UMRS 1124, 75006 Paris, France
- Hôpital Necker Enfants malades, AP-HP, 75006 Paris, France
| | - Etienne B. Blanc
- Université Paris Cité, Inserm unit UMRS 1124, 75006 Paris, France
| |
Collapse
|
5
|
Fitzgerald S, Bhat B, Print C, Jones GT. A validated restriction enzyme ddPCR cg05575921 (AHRR) assay to accurately assess smoking exposure. Clin Epigenetics 2024; 16:45. [PMID: 38528596 PMCID: PMC10962207 DOI: 10.1186/s13148-024-01659-1] [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: 01/16/2024] [Accepted: 03/15/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND & METHODS In this study, a novel restriction enzyme (RE) digestion-based droplet digital polymerase chain reaction (ddPCR) assay was designed for cg005575921 within the AHRR gene body and compared with matching results obtained by bisulfite conversion (BIS) ddPCR and Illumina DNA methylation array. RESULTS The RE ddPCR cg05575921 assay appeared concordant with BIS ddPCR (r2 = 0.94, P < 0.0001) and, when compared with the Illumina array, had significantly better smoking status classification performance for current versus never smoked (AUC 0.96 versus 0.93, P < 0.04) and current versus ex-smoker (AUC 0.88 versus 0.83, P < 0.04) comparisons. CONCLUSIONS The RE ddPCR cg05575921 assay accurately predicts smoking status and could be a useful component of 'precision-medicine' chronic disease risk screening tools.
Collapse
Affiliation(s)
- Sandra Fitzgerald
- Department of Molecular Medicine & Pathology, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre of Research Excellence, Auckland, New Zealand
| | - Basharat Bhat
- Vascular Research Group, Department of Surgical Sciences, Dunedin Medical School, University of Otago, PO Box 56, Dunedin, 9054, New Zealand
| | - Cristin Print
- Department of Molecular Medicine & Pathology, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre of Research Excellence, Auckland, New Zealand
| | - Gregory T Jones
- Vascular Research Group, Department of Surgical Sciences, Dunedin Medical School, University of Otago, PO Box 56, Dunedin, 9054, New Zealand.
| |
Collapse
|
6
|
Mulder RH, Neumann A, Felix JF, Suderman M, Cecil CAM. What makes clocks tick? Characterizing developmental dynamics of adult epigenetic clock sites. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.584597. [PMID: 38559237 PMCID: PMC10979995 DOI: 10.1101/2024.03.12.584597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
DNA methylation (DNAm) at specific sites can be used to calculate 'epigenetic clocks', which in adulthood are used as indicators of age(ing). However, little is known about how these clock sites 'behave' during development and what factors influence their variability in early life. This knowledge could be used to optimize healthy aging well before the onset of age-related conditions. Here, we leveraged results from two longitudinal population-based cohorts (N=5,019 samples from 2,348 individuals) to characterize trajectories of adult clock sites from birth to early adulthood. We find that clock sites (i) diverge widely in their developmental trajectories, often showing non-linear change over time; (ii) are substantially more likely than non-clock sites to vary between individuals already from birth, differences that are predictive of DNAm variation at later ages; and (iii) show enrichment for genetic and prenatal environmental exposures, supporting an early-origins perspective to epigenetic aging.
Collapse
Affiliation(s)
- Rosa H. Mulder
- Department of Child and Adolescent Psychiatry / Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alexander Neumann
- Department of Child and Adolescent Psychiatry / Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Charlotte A. M. Cecil
- Department of Child and Adolescent Psychiatry / Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| |
Collapse
|
7
|
Saint-André V, Charbit B, Biton A, Rouilly V, Possémé C, Bertrand A, Rotival M, Bergstedt J, Patin E, Albert ML, Quintana-Murci L, Duffy D. Smoking changes adaptive immunity with persistent effects. Nature 2024; 626:827-835. [PMID: 38355791 PMCID: PMC10881394 DOI: 10.1038/s41586-023-06968-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/13/2023] [Indexed: 02/16/2024]
Abstract
Individuals differ widely in their immune responses, with age, sex and genetic factors having major roles in this inherent variability1-6. However, the variables that drive such differences in cytokine secretion-a crucial component of the host response to immune challenges-remain poorly defined. Here we investigated 136 variables and identified smoking, cytomegalovirus latent infection and body mass index as major contributors to variability in cytokine response, with effects of comparable magnitudes with age, sex and genetics. We find that smoking influences both innate and adaptive immune responses. Notably, its effect on innate responses is quickly lost after smoking cessation and is specifically associated with plasma levels of CEACAM6, whereas its effect on adaptive responses persists long after individuals quit smoking and is associated with epigenetic memory. This is supported by the association of the past smoking effect on cytokine responses with DNA methylation at specific signal trans-activators and regulators of metabolism. Our findings identify three novel variables associated with cytokine secretion variability and reveal roles for smoking in the short- and long-term regulation of immune responses. These results have potential clinical implications for the risk of developing infections, cancers or autoimmune diseases.
Collapse
Affiliation(s)
- Violaine Saint-André
- Translational Immunology Unit, Department of Immunology, Institut Pasteur, Université Paris Cité, Paris, France.
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France.
| | - Bruno Charbit
- Cytometry and Biomarkers UTechS, Center for Translational Research, Institut Pasteur, Université Paris Cité, Paris, France
| | - Anne Biton
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France
| | | | - Céline Possémé
- Translational Immunology Unit, Department of Immunology, Institut Pasteur, Université Paris Cité, Paris, France
| | - Anthony Bertrand
- Translational Immunology Unit, Department of Immunology, Institut Pasteur, Université Paris Cité, Paris, France
- Frontiers of Innovation in Research and Education PhD Program, LPI Doctoral School, Université Paris Cité, Paris, France
| | - Maxime Rotival
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris, France
| | - Jacob Bergstedt
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris, France
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Etienne Patin
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris, France
| | | | - Lluis Quintana-Murci
- Institut Pasteur, Université Paris Cité, CNRS UMR2000, Human Evolutionary Genetics Unit, Paris, France
- Chair Human Genomics and Evolution, Collège de France, Paris, France
| | - Darragh Duffy
- Translational Immunology Unit, Department of Immunology, Institut Pasteur, Université Paris Cité, Paris, France.
- Cytometry and Biomarkers UTechS, Center for Translational Research, Institut Pasteur, Université Paris Cité, Paris, France.
| |
Collapse
|
8
|
Zhang H, Kalla R, Chen J, Zhao J, Zhou X, Adams A, Noble A, Ventham NT, Wellens J, Ho GT, Dunlop MG, Nowak JK, Ding Y, Liu Z, Satsangi J, Theodoratou E, Li X. Altered DNA methylation within DNMT3A, AHRR, LTA/TNF loci mediates the effect of smoking on inflammatory bowel disease. Nat Commun 2024; 15:595. [PMID: 38238335 PMCID: PMC10796384 DOI: 10.1038/s41467-024-44841-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/04/2024] [Indexed: 01/22/2024] Open
Abstract
This work aims to investigate how smoking exerts effect on the development of inflammatory bowel disease (IBD). A prospective cohort study and a Mendelian randomization study are first conducted to evaluate the association between smoking behaviors, smoking-related DNA methylation and the risks of Crohn's disease (CD) and ulcerative colitis (UC). We then perform both genome-wide methylation analysis and co-localization analysis to validate the observed associations. Compared to never smoking, current and previous smoking habits are associated with increased CD (P = 7.09 × 10-10) and UC (P < 2 × 10-16) risk, respectively. DNA methylation alteration at cg17742416 [DNMT3A] is linked to both CD (P = 7.30 × 10-8) and UC (P = 1.04 × 10-4) risk, while cg03599224 [LTA/TNF] is associated with CD risk (P = 1.91 × 10-6), and cg14647125 [AHRR] and cg23916896 [AHRR] are linked to UC risk (P = 0.001 and 0.002, respectively). Our study identifies biological mechanisms and pathways involved in the effects of smoking on the pathogenesis of IBD.
Collapse
Affiliation(s)
- Han Zhang
- Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Rahul Kalla
- Edinburgh IBD Science Unit, Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK
| | - Jie Chen
- Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jianhui Zhao
- Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xuan Zhou
- Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Alex Adams
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Alexandra Noble
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Nicholas T Ventham
- Academic Coloproctology, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Judith Wellens
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
- Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders (TARGID), KU Leuven, Leuven, Belgium
| | - Gwo-Tzer Ho
- Edinburgh IBD Science Unit, Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK
| | - Malcolm G Dunlop
- Cancer Research UK Scotland Centre and Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, UK
| | - Jan Krzysztof Nowak
- Department of Paediatric Gastroenterology and Metabolic Diseases, Poznan University of Medical Sciences, Poznan, Poland
| | - Yuan Ding
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhanju Liu
- Center for IBD Research, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Jack Satsangi
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK.
| | - Evropi Theodoratou
- Cancer Research UK Scotland Centre and Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, UK.
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
| | - Xue Li
- Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
9
|
Kasela S, Aguet F, Kim-Hellmuth S, Brown BC, Nachun DC, Tracy RP, Durda P, Liu Y, Taylor KD, Johnson WC, Van Den Berg D, Gabriel S, Gupta N, Smith JD, Blackwell TW, Rotter JI, Ardlie KG, Manichaikul A, Rich SS, Barr RG, Lappalainen T. Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects. Am J Hum Genet 2024; 111:133-149. [PMID: 38181730 PMCID: PMC10806864 DOI: 10.1016/j.ajhg.2023.11.013] [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: 06/22/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
Collapse
Affiliation(s)
- Silva Kasela
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA.
| | | | - Sarah Kim-Hellmuth
- New York Genome Center, New York, NY, USA; Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital LMU Munich, Munich, Germany; Computational Health Center, Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Brielin C Brown
- New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA
| | - Daniel C Nachun
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Russell P Tracy
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Peter Durda
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joshua D Smith
- Northwest Genomics Center, University of Washington, Seattle, WA, USA
| | - Thomas W Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA; Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
| |
Collapse
|
10
|
Liu Y, Lu L, Yang H, Wu X, Luo X, Shen J, Xiao Z, Zhao Y, Du F, Chen Y, Deng S, Cho CH, Li Q, Li X, Li W, Wang F, Sun Y, Gu L, Chen M, Li M. Dysregulation of immunity by cigarette smoking promotes inflammation and cancer: A review. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 339:122730. [PMID: 37838314 DOI: 10.1016/j.envpol.2023.122730] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/26/2023] [Accepted: 10/11/2023] [Indexed: 10/16/2023]
Abstract
Smoking is a serious global health issue. Cigarette smoking contains over 7000 different chemicals. The main harmful components include nicotine, acrolein, aromatic hydrocarbons and heavy metals, which play the key role for cigarette-induced inflammation and carcinogenesis. Growing evidences show that cigarette smoking and its components exert a remarkable impact on regulation of immunity and dysregulated immunity promotes inflammation and cancer. Therefore, this comprehensive and up-to-date review covers four interrelated topics, including cigarette smoking, inflammation, cancer and immune system. The known harmful chemicals from cigarette smoking were summarized. Importantly, we discussed in depth the impact of cigarette smoking on the formation of inflammatory or tumor microenvironment, primarily by affecting immune effector cells, such as macrophages, neutrophils, and T lymphocytes. Furthermore, the main molecular mechanisms by which cigarette smoking induces inflammation and cancer, including changes in epigenetics, DNA damage and others were further summarized. This article will contribute to a better understanding of the impact of cigarette smoking on inducing inflammation and cancer.
Collapse
Affiliation(s)
- Yubin Liu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China
| | - Lan Lu
- Antibiotics Research and Re-evaluation Key Laboratory of Sichuan Province, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, Sichuan, China
| | - Huan Yang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China
| | - Xu Wu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Xinyue Luo
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Jing Shen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Zhangang Xiao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Yueshui Zhao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Fukuan Du
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Yu Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Shuai Deng
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China
| | - Chi Hin Cho
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China
| | - Qianxiu Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China
| | - Xiaobing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Wanping Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Fang Wang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Yuhong Sun
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Li Gu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Meijuan Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Mingxing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China; Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou, Sichuan, China; South Sichuan Institute of Translational Medicine, Luzhou, Sichuan, China.
| |
Collapse
|
11
|
Domingo-Relloso A, Joehanes R, Rodriguez-Hernandez Z, Lahousse L, Haack K, Fallin MD, Herreros-Martinez M, Umans JG, Best LG, Huan T, Liu C, Ma J, Yao C, Jerolon A, Bermudez JD, Cole SA, Rhoades DA, Levy D, Navas-Acien A, Tellez-Plaza M. Smoking, blood DNA methylation sites and lung cancer risk. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 334:122153. [PMID: 37442331 PMCID: PMC10528956 DOI: 10.1016/j.envpol.2023.122153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/07/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023]
Abstract
Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.
Collapse
Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain; Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Statistics and Operations Research, University of Valencia, Spain.
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Zulema Rodriguez-Hernandez
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Lies Lahousse
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, USA; Department of Epidemiology, Johns Hopkins University, Baltimore, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Washington DC, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Lyle G Best
- Missouri Breaks Industries and Research Inc., Eagle Butte, SD, USA
| | - Tianxiao Huan
- Framingham Heart Study, Framingham, MA, USA; University of Massachusetts Medical School, Worcester, MA, USA
| | - Chunyu Liu
- Framingham Heart Study, Framingham, MA, USA; Boston University School of Public Health, Boston, MA, USA
| | - Jiantao Ma
- Framingham Heart Study, Framingham, MA, USA; Tufts University Friedman School of Nutrition Science and Policy, Boston, MA, USA
| | - Chen Yao
- Framingham Heart Study, Framingham, MA, USA; Bristol Myers Squibb, Cambridge, MA, USA
| | - Allan Jerolon
- Université Paris Cité, CNRS, MAP5, F-75006, Paris, France
| | - Jose D Bermudez
- Department of Statistics and Operations Research, University of Valencia, Spain
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dorothy A Rhoades
- Stephenson Cancer Center, University of Oklahoma Health Sciences Department of Medicine, Oklahoma City, OK, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| |
Collapse
|
12
|
Opitz CA, Holfelder P, Prentzell MT, Trump S. The complex biology of aryl hydrocarbon receptor activation in cancer and beyond. Biochem Pharmacol 2023; 216:115798. [PMID: 37696456 PMCID: PMC10570930 DOI: 10.1016/j.bcp.2023.115798] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/08/2023] [Accepted: 09/08/2023] [Indexed: 09/13/2023]
Abstract
The aryl hydrocarbon receptor (AHR) signaling pathway is a complex regulatory network that plays a critical role in various biological processes, including cellular metabolism, development, and immune responses. The complexity of AHR signaling arises from multiple factors, including the diverse ligands that activate the receptor, the expression level of AHR itself, and its interaction with the AHR nuclear translocator (ARNT). Additionally, the AHR crosstalks with the AHR repressor (AHRR) or other transcription factors and signaling pathways and it can also mediate non-genomic effects. Finally, posttranslational modifications of the AHR and its interaction partners, epigenetic regulation of AHR and its target genes, as well as AHR-mediated induction of enzymes that degrade AHR-activating ligands may contribute to the context-specificity of AHR activation. Understanding the complexity of AHR signaling is crucial for deciphering its physiological and pathological roles and developing therapeutic strategies targeting this pathway. Ongoing research continues to unravel the intricacies of AHR signaling, shedding light on the regulatory mechanisms controlling its diverse functions.
Collapse
Affiliation(s)
- Christiane A Opitz
- German Cancer Research Center (DKFZ), Heidelberg, Division of Metabolic Crosstalk in Cancer and the German Cancer Consortium (DKTK), DKFZ Core Center Heidelberg, 69120 Heidelberg, Germany; Neurology Clinic and National Center for Tumor Diseases, 69120 Heidelberg, Germany.
| | - Pauline Holfelder
- German Cancer Research Center (DKFZ), Heidelberg, Division of Metabolic Crosstalk in Cancer and the German Cancer Consortium (DKTK), DKFZ Core Center Heidelberg, 69120 Heidelberg, Germany; Faculty of Bioscience, Heidelberg University, 69120 Heidelberg, Germany
| | - Mirja Tamara Prentzell
- German Cancer Research Center (DKFZ), Heidelberg, Division of Metabolic Crosstalk in Cancer and the German Cancer Consortium (DKTK), DKFZ Core Center Heidelberg, 69120 Heidelberg, Germany; Faculty of Bioscience, Heidelberg University, 69120 Heidelberg, Germany
| | - Saskia Trump
- Molecular Epidemiology Unit, Berlin Institute of Health at Charité and the German Cancer Consortium (DKTK), Partner Site Berlin, a partnership between DKFZ and Charité -Universitätsmedizin Berlin, 10117 Berlin, Germany
| |
Collapse
|
13
|
Zhou X, Xiao Q, Jiang F, Sun J, Wang L, Yu L, Zhou Y, Zhao J, Zhang H, Yuan S, Timofeeva M, Spiliopoulou A, Mesa-Eguiagaray I, Farrington SM, Law PJ, Houlston RS, Ding K, Dunlop MG, Theodoratou E, Li X. Dissecting the pathogenic effects of smoking and its hallmarks in blood DNA methylation on colorectal cancer risk. Br J Cancer 2023; 129:1306-1313. [PMID: 37608097 PMCID: PMC10576058 DOI: 10.1038/s41416-023-02397-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 07/30/2023] [Accepted: 08/07/2023] [Indexed: 08/24/2023] Open
Abstract
BACKGROUND Tobacco smoking is suggested as a risk factor for colorectal cancer (CRC), but the complex relationship and the potential pathway are not fully understood. METHODS We performed two-sample Mendelian randomisation (MR) analyses with genetic instruments for smoking behaviours and related DNA methylation in blood and summary-level GWAS data of colorectal cancer to disentangle the relationship. Colocalization analyses and prospective gene-environment interaction analyses were also conducted as replication. RESULTS Convincing evidence was identified for the pathogenic effect of smoking initiation on CRC risk and suggestive evidence was observed for the protective effect of smoking cessation in the univariable MR analyses. Multivariable MR analysis revealed that these associations were independent of other smoking phenotypes and alcohol drinking. Genetically predicted methylation at CpG site cg17823346 [ZMIZ1] were identified to decrease CRC risk; while genetically predicted methylation at cg02149899 would increase CRC risk. Colocalization and gene-environment interaction analyses added further evidence to the relationship between epigenetic modification at cg17823346 [ZMIZ1] as well as cg02149899 and CRC risk. DISCUSSION Our study confirms the significant association between tobacco smoking, DNA methylation and CRC risk and yields a novel insight into the pathogenic effect of tobacco smoking on CRC risk.
Collapse
Affiliation(s)
- Xuan Zhou
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Qian Xiao
- Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fangyuan Jiang
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Sun
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lijuan Wang
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Lili Yu
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yajing Zhou
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianhui Zhao
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Han Zhang
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria Timofeeva
- Danish Institute for Advanced Study (DIAS), Epidemiology, Biostatistics and Biodemography Research Unit, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Athina Spiliopoulou
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Ines Mesa-Eguiagaray
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Cancer Research UK Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Susan M Farrington
- Cancer Research UK Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Philip J Law
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Kefeng Ding
- Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Malcolm G Dunlop
- Cancer Research UK Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Colon Cancer Genetics Group, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Cancer Research UK Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, and Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
14
|
Dahl C, Hvidtfeldt UA, Tjønneland A, Guldberg P, Raaschou-Nielsen O. Blood Leukocyte AHRR Methylation and Risk of Non-smoking-associated Cancer: A Case-cohort Study of Non-Hodgkin Lymphoma. CANCER RESEARCH COMMUNICATIONS 2023; 3:1781-1787. [PMID: 37691855 PMCID: PMC10484117 DOI: 10.1158/2767-9764.crc-23-0151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/07/2023] [Accepted: 08/11/2023] [Indexed: 09/12/2023]
Abstract
Aryl-hydrocarbon receptor repressor (AHRR) hypomethylation in peripheral blood is tightly linked with tobacco smoking and lung cancer. Here, we investigated AHRR methylation in non-Hodgkin lymphoma (NHL), a non-smoking-associated cancer. In a case-cohort study within the population-based Danish Diet, Cancer and Health cohort, we measured AHRR (cg23576855) methylation in prediagnostic blood from 161 participants who developed NHL within 13.4 years of follow-up (median: 8.5 years), with a comparison group of 164 randomly chosen participants. We measured DNA-methylation levels using bisulfite pyrosequencing and estimated incidence rate ratios (IRR) using Cox proportional hazards models with adjustment for baseline age, sex, educational level, smoking status, body mass index, alcohol intake, physical activity, and diet score. Global DNA-methylation levels were assessed by long interspersed nucleotide element 1 (LINE-1) analysis. Overall, the IRR for AHRR hypomethylation (lowest vs. other quartiles) was 2.52 [95% confidence interval (CI), 1.24-5.15]. When stratified according to time between blood draw and diagnosis, low AHRR methylation levels were associated with a future diagnosis of NHL [IRR: 4.50 (95% CI, 1.62-12.50) at 0-<5 years, 7.04 (95% CI, 2.36-21.02) at 5-<10 years, and 0.56 (95% CI, 0.21-1.45) at ≥10 years]. There was no association between global DNA-methylation levels and risk of NHL. Our results show that AHRR hypomethylation in blood leukocytes is associated with a higher risk of NHL in a time-dependent manner, suggesting that it occurs as a response to tumor development. Significance Our population-based study demonstrated that lower AHRR methylation levels in peripheral blood leukocytes were associated with an increased risk of NHL. This association was independent of tobacco smoking, sex, and lifestyle characteristics, but was highly dependent on time to diagnosis. These findings highlight the potential of AHRR methylation as a biomarker for NHL risk, effective up to 10 years after blood draw.
Collapse
Affiliation(s)
- Christina Dahl
- Molecular Diagnostics, Danish Cancer Institute, Copenhagen, Denmark
| | - Ulla A. Hvidtfeldt
- Work, Environment and Cancer, Danish Cancer Institute, Copenhagen, Denmark
| | - Anne Tjønneland
- Diet, Cancer and Health, Danish Cancer Institute, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Per Guldberg
- Molecular Diagnostics, Danish Cancer Institute, Copenhagen, Denmark
- Department of Cancer and Inflammation Research, Institute for Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | - Ole Raaschou-Nielsen
- Work, Environment and Cancer, Danish Cancer Institute, Copenhagen, Denmark
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| |
Collapse
|
15
|
Kheirkhah Rahimabad P, Jones AD, Zhang H, Chen S, Jiang Y, Ewart S, Holloway JW, Arshad H, Eslamimehr S, Bruce R, Karmaus W. Polymorphisms in Glutathione S-Transferase ( GST) Genes Modify the Effect of Exposure to Maternal Smoking Metabolites in Pregnancy and Offspring DNA Methylation. Genes (Basel) 2023; 14:1644. [PMID: 37628696 PMCID: PMC10454475 DOI: 10.3390/genes14081644] [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: 07/20/2023] [Revised: 08/09/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
Maternal smoking in pregnancy (MSP) affects the offspring's DNA methylation (DNAm). There is a lack of knowledge regarding individual differences in susceptibility to exposure to MSP. Glutathione S-transferase (GST) genes are involved in protection against harmful oxidants such as those found in cigarette smoke. This study aimed to test whether polymorphisms in GST genes influence the effect of MSP on offspring DNAm. Using data from the Isle of Wight birth cohort, we assessed the association of MSP and offspring DNAm in 493 mother-child dyads (251 male, 242 female) with the effect-modifying role of GST gene polymorphism (at rs506008, rs574344, rs12736389, rs3768490, rs1537234, and rs1695). MSP was assessed by levels of nicotine and its downstream metabolites (cotinine, norcotinine, and hydroxycotinine) in maternal sera. In males, associations of hydroxycotinine with DNAm at cg18473733, cg25949550, cg11647108, and cg01952185 and norcotinine with DNAm at cg09935388 were modified by GST gene polymorphisms (p-values < 0.05). In females, associations of hydroxycotinine with DNAm at cg12160087 and norcotinine with DNAm at cg18473733 were modified by GST gene polymorphisms (p-values < 0.05). Our study emphasizes the role of genetic polymorphism in GST genes in DNAm's susceptibility to MSP.
Collapse
Affiliation(s)
- Parnian Kheirkhah Rahimabad
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN 38111, USA; (P.K.R.); (H.Z.); (Y.J.); (S.E.)
| | - A. Daniel Jones
- Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI 48824, USA;
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN 38111, USA; (P.K.R.); (H.Z.); (Y.J.); (S.E.)
| | - Su Chen
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA;
| | - Yu Jiang
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN 38111, USA; (P.K.R.); (H.Z.); (Y.J.); (S.E.)
| | - Susan Ewart
- Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - John W. Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK;
| | - Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK;
- The David Hide Asthma and Allergy Research Centre, Isle of Wight, Newport PO30 5TG, UK
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Hampshire, Southampton SO16 6YD, UK
| | - Shakiba Eslamimehr
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN 38111, USA; (P.K.R.); (H.Z.); (Y.J.); (S.E.)
| | - Robert Bruce
- Department of Anesthesiology, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA;
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health Sciences, School of Public Health, University of Memphis, Memphis, TN 38111, USA; (P.K.R.); (H.Z.); (Y.J.); (S.E.)
| |
Collapse
|
16
|
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] [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.
Collapse
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
| |
Collapse
|
17
|
Kasela S, Aguet F, Kim-Hellmuth S, Brown BC, Nachun DC, Tracy RP, Durda P, Liu Y, Taylor KD, Craig Johnson W, Berg DVD, Gabriel S, Gupta N, Smith JD, Blackwell TW, Rotter JI, Ardlie KG, Manichaikul A, Rich SS, Graham Barr R, Lappalainen T. Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.26.546528. [PMID: 37425716 PMCID: PMC10326995 DOI: 10.1101/2023.06.26.546528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Bulk tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, while context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell type proportions, we demonstrate that cell type iQTLs could be considered as proxies for cell type-specific QTL effects. The interpretation of age iQTLs, however, warrants caution as the moderation effect of age on the genotype and molecular phenotype association may be mediated by changes in cell type composition. Finally, we show that cell type iQTLs contribute to cell type-specific enrichment of diseases that, in combination with additional functional data, may guide future functional studies. Overall, this study highlights iQTLs to gain insights into the context-specificity of regulatory effects.
Collapse
Affiliation(s)
- Silva Kasela
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | | | - Sarah Kim-Hellmuth
- New York Genome Center, New York, NY, USA
- Department of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital LMU Munich, Munich, Germany
- Computational Health Center, Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Brielin C. Brown
- New York Genome Center, New York, NY, USA
- Data Science Institute, Columbia University, New York, NY, USA
| | | | - Russell P. Tracy
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Peter Durda
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joshua D. Smith
- Northwest Genomic Center, University of Washington, Seattle, WA, USA
| | - Thomas W. Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Ani Manichaikul
- Center for Public health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S. Rich
- Center for Public health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R. Graham Barr
- Epidemiology and Medicine, Columbia University Medical Center, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| |
Collapse
|
18
|
Skov-Jeppesen SM, Kobylecki CJ, Jacobsen KK, Bojesen SE. Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population. Chest 2023; 163:1565-1575. [PMID: 36621758 PMCID: PMC10258440 DOI: 10.1016/j.chest.2022.12.036] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/07/2022] [Accepted: 12/19/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Hypomethylation of the aryl hydrocarbon receptor repressor (AHRR) gene indicates long-term smoking exposure and might therefore be a monitor for smoking-induced disease risk. However, studies of individual longitudinal changes in AHRR methylation are sparse. RESEARCH QUESTION How does the recovery of AHRR methylation depend on change in smoking behaviors and demographic variables? STUDY DESIGN AND METHODS This study included 4,432 individuals from the Copenhagen City Heart Study, with baseline and follow-up blood samples and smoking information collected approximately 10 years apart. AHRR methylation at the cg05575921 site was measured in bisulfite-treated leukocyte DNA. Four smoking groups were defined: participants who never smoked (Never-Never), participants who formerly smoked (Former-Former), participants who quit during the study period (Current-Former), and individuals who smoked at both baseline and follow-up (Current-Current). Methylation recovery was defined as the increase in AHRR methylation between baseline and follow-up examination. RESULTS Methylation recovery was highest among participants who quit, with a median methylation recovery of 5.58% (interquartile range, 1.79; 9.15) vs 1.64% (interquartile range, -1.88; 4.96) in the Current-Current group (P < .0001). In individuals who quit smoking, older age was associated with lower methylation recovery (P < .0001). In participants who quit aged > 65 years, methylation recovery was 5.9% at 5.6 years after quitting; methylation recovery was 8.5% after 2.8 years for participants who quit aged < 55 years. INTERPRETATION AHRR methylation recovered after individuals quit smoking, and recovery was more pronounced and occurred faster in younger compared with older interim quitters.
Collapse
Affiliation(s)
- Sune Moeller Skov-Jeppesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Camilla Jannie Kobylecki
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Katja Kemp Jacobsen
- Department of Technology, Faculty of Health and Technology, University College Copenhagen, Copenhagen, Denmark
| | - Stig Egil Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark; The Copenhagen City Heart Study, Copenhagen University Hospital, Frederiksberg and Bispebjerg Hospital, Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
19
|
Jacobsen KK, Kobylecki CJ, Skov-Jeppesen SM, Bojesen SE. Development and validation of a simple general population lung cancer risk model including AHRR-methylation. Lung Cancer 2023; 181:107229. [PMID: 37150141 DOI: 10.1016/j.lungcan.2023.107229] [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: 03/07/2023] [Revised: 04/27/2023] [Accepted: 04/29/2023] [Indexed: 05/09/2023]
Abstract
INTRODUCTION Screening reduces lung cancer mortality of high-risk populations. Currently proposed screening eligibility criteria only identify half of those individuals, who later develop lung cancer. This study aimed to develop and validate a sensitive and simple model for predicting 10-year lung cancer risk. METHODS Using the 1991-94 examination of The Copenhagen City Heart Study in Denmark, 6,820 former or current smokers from the general population were followed for lung cancer within 10 years after examination. Logistic regression of baseline variables (age, sex, education, chronic obstructive pulmonary disease, family history of lung cancer, smoking status and cumulative smoking, secondhand smoking, occupational exposures to dust and fume, body mass index, lung function, plasma C-reactive protein, and AHRR(cg05575921) methylation) identified the best predictive model. The model was validated among 3,740 former or current smokers from the 2001-03 examination, also followed for 10 years. A simple risk chart was developed with Poisson regression. RESULTS Age, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation identified 65 of 88 individuals who developed lung cancer in the validation cohort. The highest risk group, consisting of less educated men aged >65 with current smoking status and cumulative smoking >20 pack-years, had absolute 10-year risks varying from 4% to 16% by AHRR(cg05575921) methylation. CONCLUSION A simple risk chart including age, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation, identifies individuals with 10-year lung cancer risk from below 1% to 16%. Including AHRR(cg05575921) methylation in the eligibility criteria for screening identifies smokers who would benefit the most from screening.
Collapse
Affiliation(s)
- Katja Kemp Jacobsen
- Department of Technology, Faculty of Health and Technology, University College Copenhagen, Copenhagen, Denmark
| | - Camilla Jannie Kobylecki
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Sune Moeller Skov-Jeppesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Stig Egil Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark; The Copenhagen City Heart Study, Copenhagen University Hospital, Frederiksberg and Bispebjerg Hospital, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
20
|
Hejazi NS, Boileau P, van der Laan MJ, Hubbard AE. A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology. Stat Methods Med Res 2023; 32:539-554. [PMID: 36573044 PMCID: PMC11078029 DOI: 10.1177/09622802221146313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational and high-dimensional biology. As the dimensionality of datasets continues to grow, so too does the complexity of identifying biomarkers linked to exposure patterns. The statistical analysis of such data often relies upon parametric modeling assumptions motivated by convenience, inviting opportunities for model misspecification. While estimation frameworks incorporating flexible, data adaptive regression strategies can mitigate this, their standard variance estimators are often unstable in high-dimensional settings, resulting in inflated Type-I error even after standard multiple testing corrections. We adapt a shrinkage approach compatible with parametric modeling strategies to semiparametric variance estimators of a family of efficient, asymptotically linear estimators of causal effects, defined by counterfactual exposure contrasts. Augmenting the inferential stability of these estimators in high-dimensional settings yields a data adaptive approach for robustly uncovering stable causal associations, even when sample sizes are limited. Our generalized variance estimator is evaluated against appropriate alternatives in numerical experiments, and an open source R/Bioconductor package, biotmle, is introduced. The proposal is demonstrated in an analysis of high-dimensional DNA methylation data from an observational study on the epigenetic effects of tobacco smoking.
Collapse
Affiliation(s)
- Nima S Hejazi
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Philippe Boileau
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Mark J van der Laan
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
- Department of Statistics, University of California, Berkeley, CA, USA
| | - Alan E Hubbard
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| |
Collapse
|
21
|
Bernabeu E, McCartney DL, Gadd DA, Hillary RF, Lu AT, Murphy L, Wrobel N, Campbell A, Harris SE, Liewald D, Hayward C, Sudlow C, Cox SR, Evans KL, Horvath S, McIntosh AM, Robinson MR, Vallejos CA, Marioni RE. Refining epigenetic prediction of chronological and biological age. Genome Med 2023; 15:12. [PMID: 36855161 PMCID: PMC9976489 DOI: 10.1186/s13073-023-01161-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 02/06/2023] [Indexed: 03/02/2023] Open
Abstract
BACKGROUND Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. METHODS First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study). RESULTS Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. CONCLUSIONS The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.
Collapse
Affiliation(s)
- Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - David Liewald
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Cathie Sudlow
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- BHF Data Science Centre, Health Data Research UK, London, UK
- Edinburgh Medical School, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | | | - Catalina A Vallejos
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- The Alan Turing Institute, London, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
22
|
Lu AT, Binder AM, Zhang J, Yan Q, Reiner AP, Cox SR, Corley J, Harris SE, Kuo PL, Moore AZ, Bandinelli S, Stewart JD, Wang C, Hamlat EJ, Epel ES, Schwartz JD, Whitsel EA, Correa A, Ferrucci L, Marioni RE, Horvath S. DNA methylation GrimAge version 2. Aging (Albany NY) 2022; 14:9484-9549. [PMID: 36516495 PMCID: PMC9792204 DOI: 10.18632/aging.204434] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/21/2022] [Indexed: 12/15/2022]
Abstract
We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10-167 versus P=2.6x10-144) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10-136), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10-54). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10-155). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10-267) and visceral fat (cor=0.41, P=4.7x10-41). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk.
Collapse
Affiliation(s)
- Ake T. Lu
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
| | - Alexandra M. Binder
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI 96813, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA 90095, USA
| | - Joshua Zhang
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Qi Yan
- San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
| | - Alex P. Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
| | - Pei-Lun Kuo
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Ann Z. Moore
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Stefania Bandinelli
- Geriatric Unit, Local Health Unit Tuscany Centre, Firenze, Tuscany 40125, Italy
| | - James D. Stewart
- Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516-8050, USA
| | - Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Elissa J. Hamlat
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143-0848, USA
| | - Elissa S. Epel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143-0848, USA
| | - Joel D. Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Eric A. Whitsel
- Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516-8050, USA
- Dept. of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Adolfo Correa
- Departments of Medicine and Population Health Science, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Steve Horvath
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
- Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
| |
Collapse
|
23
|
Maki KA, Ganesan SM, Meeks B, Farmer N, Kazmi N, Barb JJ, Joseph PV, Wallen GR. The role of the oral microbiome in smoking-related cardiovascular risk: a review of the literature exploring mechanisms and pathways. J Transl Med 2022; 20:584. [PMID: 36503487 PMCID: PMC9743777 DOI: 10.1186/s12967-022-03785-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Abstract
Cardiovascular disease is a leading cause of morbidity and mortality. Oral health is associated with smoking and cardiovascular outcomes, but there are gaps in knowledge of many mechanisms connecting smoking to cardiovascular risk. Therefore, the aim of this review is to synthesize literature on smoking and the oral microbiome, and smoking and cardiovascular risk/disease, respectively. A secondary aim is to identify common associations between the oral microbiome and cardiovascular risk/disease to smoking, respectively, to identify potential shared oral microbiome-associated mechanisms. We identified several oral bacteria across varying studies that were associated with smoking. Atopobium, Gemella, Megasphaera, Mycoplasma, Porphyromonas, Prevotella, Rothia, Treponema, and Veillonella were increased, while Bergeyella, Haemophilus, Lautropia, and Neisseria were decreased in the oral microbiome of smokers versus non-smokers. Several bacteria that were increased in the oral microbiome of smokers were also positively associated with cardiovascular outcomes including Porphyromonas, Prevotella, Treponema, and Veillonella. We review possible mechanisms that may link the oral microbiome to smoking and cardiovascular risk including inflammation, modulation of amino acids and lipids, and nitric oxide modulation. Our hope is this review will inform future research targeting the microbiome and smoking-related cardiovascular disease so possible microbial targets for cardiovascular risk reduction can be identified.
Collapse
Affiliation(s)
- Katherine A. Maki
- grid.410305.30000 0001 2194 5650Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, 10 Center Drive, Building 10, Bethesda, MD 20814 USA
| | - Sukirth M. Ganesan
- grid.214572.70000 0004 1936 8294Department of Periodontics, The University of Iowa College of Dentistry and Dental Clinics, 801 Newton Rd., Iowa City, IA 52242 USA
| | - Brianna Meeks
- grid.411024.20000 0001 2175 4264University of Maryland, School of Social Work, Baltimore, MD USA
| | - Nicole Farmer
- grid.410305.30000 0001 2194 5650Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, 10 Center Drive, Building 10, Bethesda, MD 20814 USA
| | - Narjis Kazmi
- grid.410305.30000 0001 2194 5650Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, 10 Center Drive, Building 10, Bethesda, MD 20814 USA
| | - Jennifer J. Barb
- grid.410305.30000 0001 2194 5650Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, 10 Center Drive, Building 10, Bethesda, MD 20814 USA
| | - Paule V. Joseph
- grid.420085.b0000 0004 0481 4802National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD USA ,grid.280738.60000 0001 0035 9863National Institute of Nursing Research, National Institutes of Health, Bethesda, MD USA
| | - Gwenyth R. Wallen
- grid.410305.30000 0001 2194 5650Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, 10 Center Drive, Building 10, Bethesda, MD 20814 USA
| |
Collapse
|
24
|
Philibert R, Dawes K, Moody J, Hoffman R, Sieren J, Long J. Using Cg05575921 methylation to predict lung cancer risk: a potentially bias-free precision epigenetics approach. Epigenetics 2022; 17:2096-2108. [PMID: 35920547 PMCID: PMC9665144 DOI: 10.1080/15592294.2022.2108082] [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: 06/04/2022] [Accepted: 07/25/2022] [Indexed: 01/25/2023] Open
Abstract
The decision to engage in lung cancer screening (LCS) necessitates weighing benefits versus harms. Previously, clinicians in the United States have used the PLCOM2012 algorithm to guide LCS decision-making. However, that formula contains race and gender-based variables. Previously, using data from a European study, Bojesen and colleagues have suggested that cg05575921 methylation could guide decision-making. To test this hypothesis in a more diverse American population, we examined DNA and clinical data from 3081 subjects from the National Lung Screening Trial (NLST) study. Using survival analysis, we found a simple linear predictor consisting of age, pack-year consumption and cg05575921, to have the best predictive power among several alternatives (AUC = 0.66). Results showed that the highest quartile of risk was more than 2-fold more likely to develop lung cancer than those in the lowest quartile. Race, ethnicity, and gender had no effect on prediction with both cg05575921 and pack years contributing equally (both p < 0.003) to risk prediction. Current smokers had considerably lower methylation than former smokers (46% vs 67%; p < 0.001) with the average methylation of those who quit approaching 80% after 25 years of cessation. Finally, current male smokers had lower mean cg05575921 percentage than female smokers (46% vs 49%; p < 0.001). We conclude that cg05575921 (along with age and pack years) can be used to guide LCS decision-making, and additional studies might focus on how best to use methylation to inform decision-making.
Collapse
Affiliation(s)
- Rob Philibert
- Behavioural Diagnostics LLC, Coralville, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Kelsey Dawes
- Behavioural Diagnostics LLC, Coralville, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Joanna Moody
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Richard Hoffman
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Jessica Sieren
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
- Department of Radiology, University of Iowa, Iowa City, IA, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| | - Jeffrey Long
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| |
Collapse
|
25
|
Childhood Trauma and Epigenetics: State of the Science and Future. Curr Environ Health Rep 2022; 9:661-672. [PMID: 36242743 DOI: 10.1007/s40572-022-00381-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/22/2022] [Indexed: 01/31/2023]
Abstract
PURPOSE OF REVIEW There is a great deal of interest regarding the biological embedding of childhood trauma and social exposures through epigenetic mechanisms, including DNA methylation (DNAm), but a comprehensive understanding has been hindered by issues of limited reproducibility between studies. This review presents a summary of the literature on childhood trauma and DNAm, highlights issues in the field, and proposes some potential solutions. RECENT FINDINGS Investigations of the associations between DNAm and childhood trauma are commonly performed using candidate gene approaches, specifically involving genes related to neurological and stress pathways. Childhood trauma is defined in a wide range of ways in several societal contexts. However, although variations in DNAm are frequently found in stress-related genes, unsupervised epigenome-wide association studies (EWAS) have shown limited reproducibility both between studies and in relating these changes to exposures. The reproducibility of childhood trauma DNAm studies, and the field of social epigenetics in general, may be improved by increasing sample sizes, standardizing variables, making use of effect size thresholds, collecting longitudinal and intervention samples, appropriately accounting for known confounding factors, and applying causal analysis wherever possible, such as "two-step epigenetic Mendelian randomization."
Collapse
|
26
|
Tsuboi Y, Yamada H, Munetsuna E, Fujii R, Yamazaki M, Ando Y, Mizuno G, Hattori Y, Ishikawa H, Ohashi K, Hashimoto S, Hamajima N, Suzuki K. Intake of vegetables and fruits rich in provitamin A is positively associated with aryl hydrocarbon receptor repressor DNA methylation in a Japanese population. Nutr Res 2022; 107:206-217. [PMID: 36334347 DOI: 10.1016/j.nutres.2022.10.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/06/2022]
Abstract
DNA methylation can be affected by numerous lifestyle factors, including diet. Tobacco smoking induces aryl hydrocarbon receptor repressor (AHRR) DNA hypomethylation, which increases the risk of lung and other cancers. However, no lifestyle habits that might increase or restore percentage of AHRR DNA methylation have been identified. We hypothesized that dietary intakes of vegetables/fruits and serum carotenoid concentrations are related to AHRR DNA methylation. A total of 813 individuals participated in this cross-sectional study. A food frequency questionnaire was used to assess dietary intake of vegetables and fruits. AHRR DNA methylation in peripheral blood mononuclear cells were measured using pyrosequencing method. In men, dietary fruit intake was significantly and positively associated with AHRR DNA methylation among current smokers (P for trend = .034). A significant positive association of serum provitamin A with AHRR DNA methylation was observed among current smokers (men: standardized β = 0.141 [0.045 to 0.237], women: standardized β = 0.570 [0.153 to 0.990]). However, compared with never smokers with low provitamin A concentrations, percentages of AHRR DNA methylation were much lower among current smokers, even those with high provitamin A concentrations (men: β = -19.1% [-33.8 to -19.8], women: β = -6.0% [-10.2 to -1.7]). Dietary intake of vegetables and fruits rich in provitamin A may increase percentage of AHRR DNA methylation in current smokers. However, although we found a beneficial effect of provitamin A on AHRR DNA methylation, this beneficial effect could not completely remove the effect of smoking on AHRR DNA demethylation.
Collapse
Affiliation(s)
- Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Hiroya Yamada
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Aichi, Japan, 470-1192.
| | - Eiji Munetsuna
- Department of Biochemistry, Fujita Health University School of Medicine, Toyoake, Aichi, Japan, 470-1192.
| | - Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Mirai Yamazaki
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Kagawa, Japan, 761-0123.
| | - Yoshitaka Ando
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Genki Mizuno
- Department of Medical Technology, Tokyo University of Technology School of Health Sciences, Ota, Tokyo, Japan, 144-8535.
| | - Yuji Hattori
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Hiroaki Ishikawa
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Koji Ohashi
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Aichi, Japan, 470-1192.
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan, 466-8550.
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi, Japan, 470-1192.
| |
Collapse
|
27
|
Chen Q, Nwozor KO, van den Berge M, Slebos DJ, Faiz A, Jonker MR, Boezen HM, Heijink IH, de Vries M. From Differential DNA Methylation in COPD to Mitochondria: Regulation of AHRR Expression Affects Airway Epithelial Response to Cigarette Smoke. Cells 2022; 11:3423. [PMID: 36359818 PMCID: PMC9656229 DOI: 10.3390/cells11213423] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/20/2022] [Accepted: 10/27/2022] [Indexed: 08/01/2023] Open
Abstract
Cigarette smoking causes hypomethylation of the gene Aryl Hydrocarbon Receptor Repressor (AHRR), which regulates detoxification and oxidative stress-responses. We investigated whether AHRR DNA methylation is related to chronic obstructive pulmonary disease (COPD) and studied its function in airway epithelial cells (AECs). The association with COPD was assessed in blood from never and current smokers with/without COPD, and in AECs from ex-smoking non-COPD controls and GOLD stage II-IV COPD patients cultured with/without cigarette smoke extract (CSE). The effect of CRISPR/Cas9-induced AHRR knockout on proliferation, CSE-induced mitochondrial membrane potential and apoptosis/necrosis in human bronchial epithelial 16HBE cells was studied. In blood, DNA methylation of AHRR at cg05575921 and cg21161138 was lower in smoking COPD subjects than smoking controls. In vitro, AHRR DNA methylation at these CpG-sites was lower in COPD-derived than control-derived AECs only upon CSE exposure. Upon AHRR knockout, we found a lower proliferation rate at baseline, stronger CSE-induced decrease in mitochondrial membrane potential, and higher CSE-induced late apoptosis/necroptosis. Together, our results show lower DNA methylation of AHRR upon smoking in COPD patients compared to non-COPD controls. Our data suggest that higher airway epithelial AHRR expression may lead to impaired cigarette smoke-induced mitochondrial dysfunction and apoptosis/necroptosis, potentially promoting unprogrammed/immunogenic cell death.
Collapse
Affiliation(s)
- Qing Chen
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
| | - Kingsley Okechukwu Nwozor
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- Centre for Heart Lung Innovation, Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, BC V6Z 1Y6, Canada
| | - Maarten van den Berge
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Pulmonology Disease, 9713 GZ Groningen, The Netherlands
| | - Dirk-Jan Slebos
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Pulmonology Disease, 9713 GZ Groningen, The Netherlands
| | - Alen Faiz
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Pulmonology Disease, 9713 GZ Groningen, The Netherlands
- Respiratory Bioinformatics and Molecular Biology (RBMB), School of Life Sciences, University of Technology Sydney, Sydney, NSW 2007, Australia
| | - Marnix R. Jonker
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
| | - H. Marike Boezen
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, 9713 GZ Groningen, The Netherlands
| | - Irene H. Heijink
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Pulmonology Disease, 9713 GZ Groningen, The Netherlands
| | - Maaike de Vries
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), 9713 GZ Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, 9713 GZ Groningen, The Netherlands
| |
Collapse
|
28
|
Keshawarz A, Joehanes R, Guan W, Huan T, DeMeo DL, Grove ML, Fornage M, Levy D, O’Connor G. Longitudinal change in blood DNA epigenetic signature after smoking cessation. Epigenetics 2022; 17:1098-1109. [PMID: 34570667 PMCID: PMC9542417 DOI: 10.1080/15592294.2021.1985301] [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: 06/07/2021] [Revised: 08/20/2021] [Accepted: 09/21/2021] [Indexed: 12/14/2022] Open
Abstract
Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta β values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.
Collapse
Affiliation(s)
- Amena Keshawarz
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Tianxiao Huan
- Framingham Heart Study, Framingham, MA, USA
- Department of Ophthalmology and Visual Sciences, University of Massachusetts Medical School, Worcester, 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
| | - Megan L. Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Myriam Fornage
- McGovern Medical School and Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Brown Foundation Institute of Molecular Medicine, Houston, TX, USA
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - George O’Connor
- Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
| |
Collapse
|
29
|
Gene Expression Trajectories from Normal Nonsmokers to COPD Smokers and Disease Progression Discriminant Modeling in Response to Cigarette Smoking. DISEASE MARKERS 2022; 2022:9354286. [PMID: 36157207 PMCID: PMC9493146 DOI: 10.1155/2022/9354286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/22/2022] [Indexed: 11/25/2022]
Abstract
Background Cigarette smoking (CS) is considered to the predominant risk factor contributing to the etiopathogenesis of chronic obstructive pulmonary disease (COPD); meanwhile, genetic predisposition likely plays a role in determining disease susceptibility. Objectives We aimed to investigate gene expression trajectories from normal nonsmokers to COPD smokers and disease progression discriminant modeling in response to cigarette smoking. Methods Small airway epithelial samples of human with different smoking status using fiberoptic bronchoscopy and corresponding rat lung tissues following 0, 3, and 6 months of CS exposure were obtained. The expression of the significant overlapping genes between human and rats was confirmed in 16HBE cells, rat lung tissues, and human peripheral PBMC using qRT-PCR. Binary logistic regression analysis was carried out to establish discrimination models. Results The integrated bioinformatic analysis of 8 human GEO datasets (293 individuals) and 9 rat transcriptome databases revealed 13 overlapping genes between humans and rats in response to smoking exposure during COPD progression. Of these, 5 genes (AKR1C3/Akr1c3, ERP27/Erp27, AHRR/Ahrr, KCNMB2/Kcnmb2, and MRC1/Mrc1) were consistently identified in both the human and rat and validated by qRT-PCR. Among them, ERP27/Erp27, KCNMB2/Kcnmb2, and MRC1/Mrc1 were newly identified. On the basis of the overlapping gene panel, discriminant models were established with the receiver operating characteristic curve (AUC) of 0.98 (AKR1C3/Akr1c3 + ERP27/Erp27) and 0.99 (AHRR/Ahrr + KCNMB2/Kcnmb2) in differentiating progressive COPD from normal nonsmokers. In addition, we also found that DEG obtained from each expression profile dataset was better than combined analysis as more genes could be identified. Conclusion This study identified 5 DEG candidates of COPD progression in response to smoking and developed effective and convenient discriminant models that can accurately predict the disease progression.
Collapse
|
30
|
El-Haddad NW, El Kawak M, El Asmar K, Jabbour ME, Moussa MA, Habib RR, Dhaini HR. AhRR methylation contributes to disease progression in urothelial bladder cancer. Cancer Biomark 2022; 35:167-177. [PMID: 36093686 DOI: 10.3233/cbm-220002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Bladder Cancer (BCa) is the tenth most incidental malignancy worldwide. BCa is mostly attributed to environmental exposure and lifestyle, particularly tobacco smoking. The Aryl Hydrocarbon Receptor Repressor (AhRR) participates in the induction of many enzymes involved in metabolizing carcinogens, including tobacco smoke components. Additionally, studies have shown that smoking demethylates the (AhRR) gene in blood, suggesting AhRR demethylation as a specific serum smoking biomarker. OBJECTIVE This study aimed to validate AhRR demethylation as a smoking biomarker in the target tissue and investigate its contribution to bladder carcinogenesis. METHODS AhRR percent methylation was tested for its association with patient smoking status and oncogenic outcome indicators, particularly p53, RB1, and FGFR3 activating mutations, muscle-invasiveness, and tumor grade, in 180 BCa tissue-based DNA. RESULTS Results showed significantly higher AhRR percent methylation in muscle-invasive compared to non-muscle invasive tumors (42.86% vs. 33.98%; p= 0.011), while lower AhRR methylation was significantly associated with FGFR3 Codon 248 mutant genotype compared to wild-type (28.11% ± 9.44 vs. 37.87% ± 22.53; p= 0.036). All other tested associations were non-statistically significant. CONCLUSIONS Although AhRR methylation did not predict smoking status in BCa tumors, it seems to play a role in carcinogenesis and disease progression. Our findings make a basis for further research.
Collapse
Affiliation(s)
- Nataly W El-Haddad
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Michelle El Kawak
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Khalil El Asmar
- Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon
| | - Michel E Jabbour
- Department of Urology, St George Hospital University Medical Center, Beirut, Lebanon.,Faculty of Medicine, University of Balamand, Beirut, Lebanon
| | - Mohamad A Moussa
- Department of Urology, Lebanese University, Beirut, Lebanon.,Department of Surgery, Division of Urology, Al-Zahraa University Hospital, Beirut, Lebanon
| | - Rima R Habib
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| | - Hassan R Dhaini
- Department of Environmental Health, American University of Beirut, Beirut, Lebanon
| |
Collapse
|
31
|
Salminen A. Aryl hydrocarbon receptor (AhR) reveals evidence of antagonistic pleiotropy in the regulation of the aging process. Cell Mol Life Sci 2022; 79:489. [PMID: 35987825 PMCID: PMC9392714 DOI: 10.1007/s00018-022-04520-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 07/14/2022] [Accepted: 08/08/2022] [Indexed: 11/24/2022]
Abstract
The antagonistic pleiotropy hypothesis is a well-known evolutionary theory to explain the aging process. It proposes that while a particular gene may possess beneficial effects during development, it can exert deleterious properties in the aging process. The aryl hydrocarbon receptor (AhR) has a significant role during embryogenesis, but later in life, it promotes several age-related degenerative processes. For instance, AhR factor (i) controls the pluripotency of stem cells and the stemness of cancer stem cells, (ii) it enhances the differentiation of embryonal stem cells, especially AhR signaling modulates the differentiation of hematopoietic stem cells and progenitor cells, (iii) it also stimulates the differentiation of immunosuppressive Tregs, Bregs, and M2 macrophages, and finally, (iv) AhR signaling participates in the differentiation of many peripheral tissues. On the other hand, AhR signaling is involved in many processes promoting cellular senescence and pathological processes, e.g., osteoporosis, vascular dysfunction, and the age-related remodeling of the immune system. Moreover, it inhibits autophagy and aggravates extracellular matrix degeneration. AhR signaling also stimulates oxidative stress, promotes excessive sphingolipid synthesis, and disturbs energy metabolism by catabolizing NAD+ degradation. The antagonistic pleiotropy of AhR signaling is based on the complex and diverse connections with major signaling pathways in a context-dependent manner. The major regulatory steps include, (i) a specific ligand-dependent activation, (ii) modulation of both genetic and non-genetic responses, (iii) a competition and crosstalk with several transcription factors, such as ARNT, HIF-1α, E2F1, and NF-κB, and (iv) the epigenetic regulation of target genes with binding partners. Thus, not only mTOR signaling but also the AhR factor demonstrates antagonistic pleiotropy in the regulation of the aging process.
Collapse
Affiliation(s)
- Antero Salminen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland.
| |
Collapse
|
32
|
Eckhardt CM, Wu H, Prada D, Vokonas PS, Sparrow D, Hou L, Schwartz J, Baccarelli AA. Predicting risk of lung function impairment and all-cause mortality using a DNA methylation-based classifier of tobacco smoke exposure. Respir Med 2022; 200:106896. [PMID: 35716602 PMCID: PMC10560590 DOI: 10.1016/j.rmed.2022.106896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 05/09/2022] [Accepted: 05/30/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND The Epigenetic Smoking Status Estimator (EpiSmokEr) predicts smoking phenotypes based on DNA methylation at 121 CpG sites. OBJECTIVE Evaluate associations of EpiSmokEr-predicted versus self-reported smoking phenotypes with lung function and all-cause mortality in a cohort of older adults. METHODS The prospective Normative Aging Study collected DNA methylation measurements from 1999 to 2012 with follow-up through 2016. The R package EpiSmokEr derived predicted smoking phenotypes based on DNA methylation levels assayed by the Illumina HumanMethylation450 Beadchip. Spirometry was collected every 3-5 years. Airflow limitation was defined as forced expiratory volume in 1 s/forced vital capacity <0.7. Vital status was monitored through periodic mailings. RESULTS Among 784 participants contributing 5414 person-years of follow-up, the EpiSmokEr-predicted smoking phenotypes matched the self-reported phenotypes for 228 (97%) never smokers and 22 (71%) current smokers. In contrast, EpiSmokEr classified 407 (79%) self-reported former smokers as never smokers. Nonetheless, the EpiSmokEr-predicted former smoking phenotype was more strongly associated with incident airflow limitation (hazard ratio [HR] = 3.15, 95% confidence interval [CI] = 1.50-6.59) and mortality (HR = 2.11, 95% CI = 1.56-2.85) compared to the self-reported former smoking phenotype (airflow limitation: HR = 2.21, 95% CI = 1.13-4.33; mortality: HR = 1.08, 95% CI = 0.86-1.36). Risk of airflow limitation and death did not differ among self-reported never smokers and former smokers who were classified as never smokers. The discriminative accuracy of EpiSmokEr-predicted phenotypes for incident airflow limitation and mortality was improved compared to self-reported phenotypes. CONCLUSIONS The DNA methylation-based EpiSmokEr classifier may be a useful surrogate of smoking-induced lung damage and may identify former smokers most at risk of adverse smoking-related health effects.
Collapse
Affiliation(s)
- Christina M Eckhardt
- Columbia University Irving Medical Center, Division of Pulmonary, Allergy and Critical, Care Medicine, Department of Medicine, New York, NY, USA.
| | - Haotian Wu
- Columbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA
| | - Diddier Prada
- Columbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA; Instituto Nacional de Cancerología, México City, Mexico
| | - Pantel S Vokonas
- Boston University School of Medicine, VA Normative Aging Study, VA, Boston, USA; Healthcare System and Department of Medicine, Boston, MA, USA
| | - David Sparrow
- Boston University School of Medicine, VA Normative Aging Study, VA, Boston, USA; Healthcare System and Department of Medicine, Boston, MA, USA
| | - Lifang Hou
- Northwestern Feinberg School of Medicine, Department of Preventive Medicine, Chicago, IL, USA
| | - Joel Schwartz
- Harvard T.H. Chan School of Public Health, Department of Epidemiology, Cambridge, MA, USA
| | - Andrea A Baccarelli
- Columbia University Mailman School of Public Health, Environmental Health Sciences, Department, New York, NY, USA
| |
Collapse
|
33
|
Hung RJ, Khodayari Moez E, Kim SJ, Budhathoki S, Brooks JD. Considerations of Biomarker Application for Cancer Continuum in the Era of Precision Medicine. CURR EPIDEMIOL REP 2022; 9:200-211. [DOI: 10.1007/s40471-022-00295-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
34
|
Domingo-Relloso A, Riffo-Campos AL, Powers M, Tellez-Plaza M, Haack K, Brown RH, Umans JG, Fallin MD, Cole SA, Navas-Acien A, Sanchez TR. An epigenome-wide study of DNA methylation profiles and lung function among American Indians in the Strong Heart Study. Clin Epigenetics 2022; 14:75. [PMID: 35681244 PMCID: PMC9185990 DOI: 10.1186/s13148-022-01294-8] [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: 01/07/2022] [Accepted: 05/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epigenetic modifications, including DNA methylation (DNAm), are often related to environmental exposures, and are increasingly recognized as key processes in the pathogenesis of chronic lung disease. American Indian communities have a high burden of lung disease compared to the national average. The objective of this study was to investigate the association of DNAm and lung function in the Strong Heart Study (SHS). We conducted a cross-sectional study of American Indian adults, 45-74 years of age who participated in the SHS. DNAm was measured using the Illumina Infinium Human MethylationEPIC platform at baseline (1989-1991). Lung function was measured via spirometry, including forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), at visit 2 (1993-1995). Airflow limitation was defined as FEV1 < 70% predicted and FEV1/FVC < 0.7, restriction was defined as FEV1/FVC > 0.7 and FVC < 80% predicted, and normal spirometry was defined as FEV1/FVC > 0.7, FEV1 > 70% predicted, FVC > 80% predicted. We used elastic-net models to select relevant CpGs for lung function and spirometry-defined lung disease. We also conducted bioinformatic analyses to evaluate the biological plausibility of the findings. RESULTS Among 1677 participants, 21.2% had spirometry-defined airflow limitation and 13.6% had spirometry-defined restrictive pattern lung function. Elastic-net models selected 1118 Differentially Methylated Positions (DMPs) as predictors of airflow limitation and 1385 for restrictive pattern lung function. A total of 12 DMPs overlapped between airflow limitation and restrictive pattern. EGFR, MAPK1 and PRPF8 genes were the most connected nodes in the protein-protein interaction network. Many of the DMPs targeted genes with biological roles related to lung function such as protein kinases. CONCLUSION We found multiple differentially methylated CpG sites associated with chronic lung disease. These signals could contribute to better understand molecular mechanisms involved in lung disease, as assessed systemically, as well as to identify patterns that could be useful for diagnostic purposes. Further experimental and longitudinal studies are needed to assess whether DNA methylation has a causal role in lung disease.
Collapse
Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain. .,Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA. .,Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
| | - Angela L Riffo-Campos
- Millennium Nucleus on Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile.,Department of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Martha Powers
- United States Environmental Protection Agency, Washington, DC, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, 28029, Madrid, Spain
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Robert H Brown
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - M Daniele Fallin
- Departments of Mental Health and Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| | - Tiffany R Sanchez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| |
Collapse
|
35
|
Yousefi PD, Suderman M, Langdon R, Whitehurst O, Davey Smith G, Relton CL. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet 2022; 23:369-383. [PMID: 35304597 DOI: 10.1038/s41576-022-00465-w] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 12/12/2022]
Abstract
DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
Collapse
Affiliation(s)
- Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Oliver Whitehurst
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.
| |
Collapse
|
36
|
Tsuboi Y, Yamada H, Munetsuna E, Fujii R, Yamazaki M, Ando Y, Mizuno G, Hattori Y, Ishikawa H, Ohashi K, Hashimoto S, Hamajima N, Suzuki K. Increased risk of cancer mortality by smoking-induced aryl hydrocarbon receptor repressor DNA hypomethylation in Japanese population: A long-term cohort study. Cancer Epidemiol 2022; 78:102162. [PMID: 35461154 DOI: 10.1016/j.canep.2022.102162] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 04/07/2022] [Accepted: 04/12/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Smoking is well known to be a major risk factor for cancer, and to decrease the levels of aryl hydrocarbon receptor repressor (AHRR) DNA methylation. AHRR is a key regulator for AHR signaling, which is involved in chemical metabolism and cancer development. Therefore, smoking-induced AHRR DNA hypomethylation may be associated with cancer development. However, it has not been reported that association between AHHR DNA methylation and cancer mortality in Asian population. Hence, we examined whether AHRR DNA methylation levels were associated with cancer mortality in a Japanese population. METHODS This study was conducted with 812 participants (aged 38-80 years) who received a health check-up in 1990, and did not have a clinical histories. We followed up the participants until the end of 2019 (median: 27.8 years), and 100 participants died from cancer. The AHRR DNA methylation levels in peripheral blood mononuclear cells (PBMCs) were measured by the pyrosequencing method. We calculated the hazard ratio (HR) and 95% confidence interval (CI) for cancer mortality according to the baseline levels of AHRR DNA methylation. RESULTS We found that AHRR DNA hypomethylation was associated with a higher risk of all cancer mortality, especially smoking related cancers and lung cancer. (all cancer: HR, 1.28, 95% CI, 1.09-1.51; smoking-related cancers: HR, 1.35, 95% CI, 1.12-1.62; lung cancer: HR, 1.68, 95% CI, 1.24-2.26). CONCLUSIONS Smoking-induced AHRR DNA hypomethylation in PBMCs was associated with the risk of cancer mortality in Japanese population; therefore, hypomethylation of AHRR may be a useful biomarker of cancer mortality risk.
Collapse
Affiliation(s)
- Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Hiroya Yamada
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Aichi 470-1192, Japan.
| | - Eiji Munetsuna
- Department of Biochemistry, Fujita Health University School of Medicine, Toyoake, Aichi 470-1192, Japan.
| | - Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Mirai Yamazaki
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Kagawa 761-0123, Japan.
| | - Yoshitaka Ando
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Genki Mizuno
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Yuji Hattori
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Hiroaki Ishikawa
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Koji Ohashi
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Aichi 470-1192, Japan.
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Aichi 466-8550, Japan.
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Aichi 470-1192, Japan.
| |
Collapse
|
37
|
Corbin LJ, White SJ, Taylor AE, Williams CM, Taylor K, van den Bosch MT, Teasdale JE, Jones M, Bond M, Harper MT, Falk L, Groom A, Hazell GG, Paternoster L, Munafò MR, Nordestgaard BG, Tybjærg-Hansen A, Bojesen SE, Relton C, Min JL, Davey Smith G, Mumford AD, Poole AW, Timpson NJ. Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function. Circ Res 2022; 130:384-400. [PMID: 35012325 PMCID: PMC8812435 DOI: 10.1161/circresaha.121.318836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 12/30/2021] [Accepted: 01/04/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease. METHODS We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression. RESULTS Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression. CONCLUSIONS Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.
Collapse
Affiliation(s)
- Laura J. Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Stephen J. White
- Department of Life Sciences, Manchester Metropolitan University, United Kingdom (S.J.W.)
| | - Amy E. Taylor
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom (A.E.T.)
| | - Christopher M. Williams
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Kurt Taylor
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
- UK Centre for Tobacco and Alcohol Studies and School of Experimental Psychology (M.R.M.), University of Bristol, United Kingdom
- School of Cellular and Molecular Medicine (A.D.M.), University of Bristol, United Kingdom
- Department of Life Sciences, Manchester Metropolitan University, United Kingdom (S.J.W.)
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom (A.E.T.)
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Department of Clinical Biochemistry, Rigshospitalet (A.T.-H.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Marion T. van den Bosch
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Jack E. Teasdale
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Matthew Jones
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Mark Bond
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Matthew T. Harper
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
| | - Louise Falk
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Alix Groom
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Georgina G.J. Hazell
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Marcus R. Munafò
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- UK Centre for Tobacco and Alcohol Studies and School of Experimental Psychology (M.R.M.), University of Bristol, United Kingdom
| | - Børge G. Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Anne Tybjærg-Hansen
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Department of Clinical Biochemistry, Rigshospitalet (A.T.-H.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Stig E. Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Josine L. Min
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Andrew D. Mumford
- School of Cellular and Molecular Medicine (A.D.M.), University of Bristol, United Kingdom
| | - Alastair W. Poole
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| |
Collapse
|
38
|
Takeuchi F, Takano K, Yamamoto M, Isono M, Miyake W, Mori K, Hara H, Hiroi Y, Kato N. Clinical Implication of Smoking-Related Aryl-Hydrocarbon Receptor Repressor (AHRR) Hypomethylation in Japanese Adults. Circ J 2022; 86:986-992. [PMID: 35110429 DOI: 10.1253/circj.cj-21-0958] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND Tobacco smoking is a leading preventable cause of morbidity and mortality worldwide; still, the success rate of smoking cessation is low in general. From the viewpoint of public health and clinical care, an objective biomarker of long-term smoking behavior is sought.Methods and Results:This study assessed DNA methylation as a biomarker of smoking in a hospital setting through a combination of molecular approaches including genetic, DNA methylation and mRNA expression analyses. First, in an epigenome-wide association study involving Japanese individuals with chronic cardiovascular disease (n=94), genome-wide significant smoking association was identified at 2 CpG sites on chromosome 5, with the strongest signal at cg05575921 located in intron 3 of the aryl-hydrocarbon receptor repressor (AHRR) gene. Highly significant (P<1×10-27) smoking-cg05575921 association was validated in 2 additional panels (n=339 and n=300). For the relationship of cg05575921 methylation extent with time after smoking cessation and cumulative cigarette consumption among former smokers, smoking-related hypomethylation was found to remain for ≥20 years after smoking cessation and to be affected by multiple factors, such ascis-interaction of genetic variation. There was a significant inverse correlation (P=0.0005) between cg05575921 methylation extent andAHRRmRNA expression. CONCLUSIONS The present study results support that reversion of AHRR hypomethylation can be a quantifiable biomarker for progress in and observance of smoking cessation, although some methodological points need to be considered.
Collapse
Affiliation(s)
- Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine.,Medical Genomics Center, Research Institute, National Center for Global Health and Medicine
| | - Kozue Takano
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine.,Department of Genomic Medicine, Center Hospital, National Center for Global Health and Medicine
| | - Masaya Yamamoto
- Department of Cardiology, Center Hospital, National Center for Global Health and Medicine
| | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine
| | - Wataru Miyake
- Department of Cardiology, Center Hospital, National Center for Global Health and Medicine
| | - Kotaro Mori
- Medical Genomics Center, Research Institute, National Center for Global Health and Medicine
| | - Hisao Hara
- Department of Cardiology, Center Hospital, National Center for Global Health and Medicine
| | - Yukio Hiroi
- Department of Cardiology, Center Hospital, National Center for Global Health and Medicine
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine.,Medical Genomics Center, Research Institute, National Center for Global Health and Medicine.,Department of Genomic Medicine, Center Hospital, National Center for Global Health and Medicine
| |
Collapse
|
39
|
Jacobsen KK, Schnohr P, Jensen GB, Bojesen SE. AHRR (cg5575921) methylation safely improves specificity of lung cancer screening eligibility criteria: A cohort study. Cancer Epidemiol Biomarkers Prev 2022; 31:758-765. [DOI: 10.1158/1055-9965.epi-21-1059] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 11/19/2021] [Accepted: 01/04/2022] [Indexed: 11/16/2022] Open
|
40
|
Avci E, Sarvari P, Savai R, Seeger W, Pullamsetti SS. Epigenetic Mechanisms in Parenchymal Lung Diseases: Bystanders or Therapeutic Targets? Int J Mol Sci 2022; 23:ijms23010546. [PMID: 35008971 PMCID: PMC8745712 DOI: 10.3390/ijms23010546] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 12/28/2021] [Accepted: 12/30/2021] [Indexed: 12/17/2022] Open
Abstract
Epigenetic responses due to environmental changes alter chromatin structure, which in turn modifies the phenotype, gene expression profile, and activity of each cell type that has a role in the pathophysiology of a disease. Pulmonary diseases are one of the major causes of death in the world, including lung cancer, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), pulmonary hypertension (PH), lung tuberculosis, pulmonary embolism, and asthma. Several lines of evidence indicate that epigenetic modifications may be one of the main factors to explain the increasing incidence and prevalence of lung diseases including IPF and COPD. Interestingly, isolated fibroblasts and smooth muscle cells from patients with pulmonary diseases such as IPF and PH that were cultured ex vivo maintained the disease phenotype. The cells often show a hyper-proliferative, apoptosis-resistant phenotype with increased expression of extracellular matrix (ECM) and activated focal adhesions suggesting the presence of an epigenetically imprinted phenotype. Moreover, many abnormalities observed in molecular processes in IPF patients are shown to be epigenetically regulated, such as innate immunity, cellular senescence, and apoptotic cell death. DNA methylation, histone modification, and microRNA regulation constitute the most common epigenetic modification mechanisms.
Collapse
MESH Headings
- Animals
- Biomarkers
- Combined Modality Therapy
- DNA Methylation
- Diagnosis, Differential
- Disease Management
- Disease Susceptibility
- Epigenesis, Genetic
- Gene Expression Regulation
- Histones/metabolism
- Humans
- Idiopathic Pulmonary Fibrosis/diagnosis
- Idiopathic Pulmonary Fibrosis/etiology
- Idiopathic Pulmonary Fibrosis/metabolism
- Idiopathic Pulmonary Fibrosis/therapy
- Lung Diseases, Interstitial/diagnosis
- Lung Diseases, Interstitial/etiology
- Lung Diseases, Interstitial/metabolism
- Lung Diseases, Interstitial/therapy
- Pulmonary Disease, Chronic Obstructive/diagnosis
- Pulmonary Disease, Chronic Obstructive/etiology
- Pulmonary Disease, Chronic Obstructive/metabolism
- Pulmonary Disease, Chronic Obstructive/therapy
- Treatment Outcome
Collapse
Affiliation(s)
- Edibe Avci
- Department of Lung Development and Remodeling, Max-Planck Institute for Heart and Lung Research, Parkstrasse 1, 61231 Bad Nauheim, Germany; (E.A.); (P.S.); (R.S.); (W.S.)
| | - Pouya Sarvari
- Department of Lung Development and Remodeling, Max-Planck Institute for Heart and Lung Research, Parkstrasse 1, 61231 Bad Nauheim, Germany; (E.A.); (P.S.); (R.S.); (W.S.)
| | - Rajkumar Savai
- Department of Lung Development and Remodeling, Max-Planck Institute for Heart and Lung Research, Parkstrasse 1, 61231 Bad Nauheim, Germany; (E.A.); (P.S.); (R.S.); (W.S.)
- Department of Internal Medicine, Justus Liebig University, 35392 Giessen, Germany
- Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
| | - Werner Seeger
- Department of Lung Development and Remodeling, Max-Planck Institute for Heart and Lung Research, Parkstrasse 1, 61231 Bad Nauheim, Germany; (E.A.); (P.S.); (R.S.); (W.S.)
- Department of Internal Medicine, Justus Liebig University, 35392 Giessen, Germany
- Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
| | - Soni S. Pullamsetti
- Department of Lung Development and Remodeling, Max-Planck Institute for Heart and Lung Research, Parkstrasse 1, 61231 Bad Nauheim, Germany; (E.A.); (P.S.); (R.S.); (W.S.)
- Department of Internal Medicine, Justus Liebig University, 35392 Giessen, Germany
- Correspondence: ; Tel.: +49-603-270-5380; Fax: +49-603-270-5385
| |
Collapse
|
41
|
Ohmomo H, Harada S, Komaki S, Ono K, Sutoh Y, Otomo R, Umekage S, Hachiya T, Katanoda K, Takebayashi T, Shimizu A. DNA Methylation Abnormalities and Altered Whole Transcriptome Profiles after Switching from Combustible Tobacco Smoking to Heated Tobacco Products. Cancer Epidemiol Biomarkers Prev 2022; 31:269-279. [PMID: 34728466 PMCID: PMC9398167 DOI: 10.1158/1055-9965.epi-21-0444] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/29/2021] [Accepted: 10/18/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The use of heated tobacco products (HTP) has increased exponentially in Japan since 2016; however, their effects on health remain a major concern. METHODS Tsuruoka Metabolome Cohort Study participants (n = 11,002) were grouped on the basis of their smoking habits as never smokers (NS), past smokers (PS), combustible tobacco smokers (CS), and HTP users for <2 years. Peripheral blood mononuclear cells were collected from 52 participants per group matched to HTP users using propensity scores, and DNA and RNA were purified from the samples. DNA methylation (DNAm) analysis of the 17 smoking-associated DNAm biomarker genes (such as AHRR, F2RL3, LRRN3, and GPR15), as well as whole transcriptome analysis, was performed. RESULTS Ten of the 17 genes were significantly hypomethylated in CS and HTP users compared with NS, among which AHRR, F2RL3, and RARA showed intermediate characteristics between CS and NS; nonetheless, AHRR expression was significantly higher in CS than in the other three groups. Conversely, LRRN3 and GPR15 were more hypomethylated in HTP users than in NS, and GPR15 expression was markedly upregulated in all the groups when compared with that in NS. CONCLUSIONS HTP users (switched from CS <2 years) display abnormal DNAm and transcriptome profiles, albeit to a lesser extent than the CS. However, because the molecular genetic effects of long-term HTP use are still unknown, long-term molecular epidemiologic studies are needed. IMPACT This study provides new insights into the molecular genetic effects on DNAm and transcriptome profiles in HTP users who switched from CS.
Collapse
Affiliation(s)
- Hideki Ohmomo
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Sei Harada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan
| | - Shohei Komaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Kanako Ono
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Ryo Otomo
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - So Umekage
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Kota Katanoda
- Division of Cancer Statistics Integration, National Cancer Center Research Institute, Chuo, Tokyo, Japan
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan.,Corresponding Author: Atsushi Shimizu, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate 028-3694, Japan. Phone: 81-19-651-5110, ext. 5473; E-mail:
| |
Collapse
|
42
|
Andersen A, Reimer R, Dawes K, Becker A, Hutchens N, Miller S, Dogan M, Hundley B, A Mills J, D Long J, Philibert R. DNA methylation differentiates smoking from vaping and non-combustible tobacco use. Epigenetics 2022; 17:178-190. [PMID: 33588690 PMCID: PMC8865289 DOI: 10.1080/15592294.2021.1890875] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 01/08/2021] [Accepted: 02/10/2021] [Indexed: 02/06/2023] Open
Abstract
Increasing use of non-combusted forms of nicotine such as e-cigarettes poses important public health questions regarding their specific risks relative to combusted tobacco products such as cigarettes. To fully delineate these risks, improved biomarkers that can distinguish between these forms of nicotine use are needed. Prior work has suggested that methylation status at cg05575921 may serve as a specific biomarker of combusted tobacco smoke exposure. We hypothesized combining this epigenetic biomarker with conventional metabolite assays could classify the type of nicotine product consumption. Therefore, we determined DNA methylation and serum cotinine values in samples from 112 smokers, 35 e-cigarette users, 19 smokeless tobacco users, and 269 controls, and performed mass spectroscopy analyses of urine samples from all nicotine users and 22 verified controls to determine urinary levels of putatively nicotine product-specific substances; propylene glycol, 2-cyanoethylmercapturic acid (CEMA), and anabasine. 1) Cigarette smoking was associated with a dose dependent demethylation of cg05575921 and increased urinary CEMA and anabasine levels, 2) e-cigarette use did not demethylate cg05575921, 3) smokeless tobacco use also did not demethylate cg05575921 but was positively associated with anabasine levels 4) CEMA and cg05575921 levels were highly correlated and 5) propylene glycol levels did not reliably distinguish use groups. Cg05575921 assessments distinguish exposure to tobacco smoke from smokeless sources of nicotine including e-cigarettes and smokeless tobacco, neither of which are associated with cg05575921 demethylation. A combination of methylomic and metabolite profiling may allow for accurate classification use status of a variety of nicotine containing products.
Collapse
Affiliation(s)
- Allan Andersen
- Department of Psychiatry, University of Iowa, Iowa City, USA
| | - Rachel Reimer
- College of Public Health, Des Moines University, Des Moines, USA
| | - Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, USA
| | - Ashley Becker
- Department of Psychiatry, University of Iowa, Iowa City, USA
| | | | | | - Meesha Dogan
- Department of Psychiatry, University of Iowa, Iowa City, USA
- Behavioral Diagnostics LLC, Coralville, USA
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, United States
| | - Brandon Hundley
- Department of Psychiatry, University of Iowa, Iowa City, USA
| | - James A Mills
- Department of Psychiatry, University of Iowa, Iowa City, USA
| | - Jeffrey D Long
- Department of Psychiatry, University of Iowa, Iowa City, USA
- Department of Biostatistics, University of Iowa, Iowa City, USA
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, USA
- Behavioral Diagnostics LLC, Coralville, USA
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, United States
| |
Collapse
|
43
|
Mao Y, Huang P, Wang Y, Wang M, Li MD, Yang Z. Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking. Clin Epigenetics 2021; 13:215. [PMID: 34886889 PMCID: PMC8662854 DOI: 10.1186/s13148-021-01208-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 12/01/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). RESULTS We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the "immunosuppression" pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. CONCLUSIONS In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.
Collapse
Affiliation(s)
- Ying Mao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Peng Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Maiqiu Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China.
| | - Zhongli Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| |
Collapse
|
44
|
Dawes K, Andersen A, Reimer R, Mills JA, Hoffman E, Long JD, Miller S, Philibert R. The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies. Sci Rep 2021; 11:21627. [PMID: 34732805 PMCID: PMC8566492 DOI: 10.1038/s41598-021-01088-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/18/2021] [Indexed: 11/23/2022] Open
Abstract
Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.
Collapse
Affiliation(s)
- Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
- Molecular Medicine Program, University of Iowa, Iowa City, IA, 52242, USA
| | - Allan Andersen
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
| | - Rachel Reimer
- Department of Public Health, Des Moines University, Des Moines, IA, 50312, USA
| | - James A Mills
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
| | - Eric Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, 52242, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, 52242, USA
| | - Jeffrey D Long
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA
- Department of Biostatistics, University of Iowa, Iowa City, IA, 52242, USA
| | - Shelly Miller
- Behavioral Diagnostics LLC, Coralville, IA, 52241, USA
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA, 52242, USA.
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, 52242, USA.
- Behavioral Diagnostics LLC, Coralville, IA, 52241, USA.
| |
Collapse
|
45
|
Abstract
Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.
Collapse
|
46
|
Richmond RC, Sillero-Rejon C, Khouja JN, Prince C, Board A, Sharp G, Suderman M, Relton CL, Munafò M, Gage SH. Investigating the DNA methylation profile of e-cigarette use. Clin Epigenetics 2021; 13:183. [PMID: 34583751 PMCID: PMC8479883 DOI: 10.1186/s13148-021-01174-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 09/18/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Little evidence exists on the health effects of e-cigarette use. DNA methylation may serve as a biomarker for exposure and could be predictive of future health risk. We aimed to investigate the DNA methylation profile of e-cigarette use. RESULTS Among 117 smokers, 117 non-smokers and 116 non-smoking vapers, we evaluated associations between e-cigarette use and epigenome-wide methylation from saliva. DNA methylation at 7 cytosine-phosphate-guanine sites (CpGs) was associated with e-cigarette use at p < 1 × 10-5 and none at p < 5.91 × 10-8. 13 CpGs were associated with smoking at p < 1 × 10-5 and one at p < 5.91 × 10-8. CpGs associated with e-cigarette use were largely distinct from those associated with smoking. There was strong enrichment of known smoking-related CpGs in the smokers but not the vapers. We also tested associations between e-cigarette use and methylation scores known to predict smoking and biological ageing. Methylation scores for smoking and biological ageing were similar between vapers and non-smokers. Higher levels of all smoking scores and a biological ageing score (GrimAge) were observed in smokers. A methylation score for e-cigarette use showed poor prediction internally (AUC 0.55, 0.41-0.69) and externally (AUC 0.57, 0.36-0.74) compared with a smoking score (AUCs 0.80) and was less able to discriminate lung squamous cell carcinoma from adjacent normal tissue (AUC 0.64, 0.52-0.76 versus AUC 0.73, 0.61-0.85). CONCLUSIONS The DNA methylation profile for e-cigarette use is largely distinct from that of cigarette smoking, did not replicate in independent samples, and was unable to discriminate lung cancer from normal tissue. The extent to which methylation related to long-term e-cigarette use translates into chronic effects requires further investigation.
Collapse
Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Carlos Sillero-Rejon
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- National Institute for Health Research Applied Research Collaboration West (NIHR ARC West), University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Jasmine N Khouja
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Claire Prince
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Alexander Board
- Department of Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Gemma Sharp
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Marcus Munafò
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Suzanne H Gage
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Psychological Sciences, University of Liverpool, Liverpool, UK
| |
Collapse
|
47
|
Yu C, Jordahl KM, Bassett JK, Joo JE, Wong EM, Brinkman MT, Schmidt DF, Bolton DM, Makalic E, Brasky TM, Shadyab AH, Tinker LF, Longano A, Hopper JL, English DR, Milne RL, Bhatti P, Southey MC, Giles GG, Dugué PA. Smoking Methylation Marks for Prediction of Urothelial Cancer Risk. Cancer Epidemiol Biomarkers Prev 2021; 30:2197-2206. [PMID: 34526299 DOI: 10.1158/1055-9965.epi-21-0313] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/22/2021] [Accepted: 09/10/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. METHODS Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). RESULTS The meta-analysis identified associations (P < 4.7 × 10-5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00-1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91-1.30). CONCLUSIONS Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. IMPACT DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.
Collapse
Affiliation(s)
- Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Kristina M Jordahl
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.,Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
| | - Julie K Bassett
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Jihoon Eric Joo
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Maree T Brinkman
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Daniel F Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.,Department of Data Science & AI, Faculty of IT, Monash University, Clayton, Victoria, Australia
| | - Damien M Bolton
- Department of Surgery, University of Melbourne and Olivia Newton-John Cancer Centre, Austin Hospital, Melbourne, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Theodore M Brasky
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, California
| | - Lesley F Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Anthony Longano
- Department of Anatomical Pathology, Eastern Health, Box Hill Hospital, Box Hill, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - 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
| | - 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
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer Research Centre, Vancouver, British Columbia, Canada
| | - 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
| | - 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
| | - 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
| |
Collapse
|
48
|
Abstract
ABSTRACT Recent research efforts have provided compelling evidence of genome-wide DNA methylation alterations in pediatrics. It is currently well established that epigenetic clocks, composed of DNA methylation sites, can estimate the gestational and chronological age of cells and tissues from different ages. Also, extensive research is aimed at their correlation with early life exposure and pediatric diseases. This review aimed to systematically summarize the epigenetic clocks in the pediatric population. Publications were collected from PubMed and Web of Science databases up to Apr 2021. Epigenetic clocks, DNA methylation clocks, epigenetic age acceleration or deceleration, pediatric and the pediatric population were used as search criteria. Here, we first review the currently applicative pediatric epigenetic clocks. We then highlight the interpretation for epigenetic age deviations in the pediatric population and their association with external factors, developmental trajectories, and pediatric diseases. Considering the remaining unknown of pediatric clocks, research strategies into them are also discussed. In all, pediatric epigenetic clocks may act as potent tools to understand development, growth and diseases in early life.
Collapse
|
49
|
Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population. Genes (Basel) 2021; 12:genes12081276. [PMID: 34440450 PMCID: PMC8391630 DOI: 10.3390/genes12081276] [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: 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).
Collapse
|
50
|
Raffington L, Belsky DW, Kothari M, Malanchini M, Tucker-Drob EM, Harden KP. Socioeconomic Disadvantage and the Pace of Biological Aging in Children. Pediatrics 2021; 147:e2020024406. [PMID: 34001641 PMCID: PMC8785753 DOI: 10.1542/peds.2020-024406] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/27/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Children who grow up in socioeconomic disadvantage face increased burden of disease and disability throughout their lives. One hypothesized mechanism for this increased burden is that early-life disadvantage accelerates biological processes of aging, increasing vulnerability to subsequent disease. To evaluate this hypothesis and the potential impact of preventive interventions, measures are needed that can quantify early acceleration of biological aging in childhood. METHODS Saliva DNA methylation and socioeconomic circumstances were measured in N = 600 children and adolescents aged 8 to 18 years (48% female) participating in the Texas Twin Project. We measured pace of biological aging using the DunedinPoAm DNA methylation algorithm, developed to quantify the pace-of-aging-related decline in system integrity. We tested if children in more disadvantaged families and neighborhoods exhibited a faster pace of aging as compared with children in more affluent contexts. RESULTS Children living in more disadvantaged families and neighborhoods exhibited a faster DunedinPoAm-measured pace of aging (r = 0.18; P = .001 for both). Latinx-identifying children exhibited a faster DunedinPoAm-measured pace of aging compared with both White- and Latinx White-identifying children, consistent with higher levels of disadvantage in this group. Children with more advanced pubertal development, higher BMI, and more tobacco exposure exhibited faster a faster DunedinPoAm-measured pace of aging. However, DunedinPoAm-measured pace of aging associations with socioeconomic disadvantage were robust to control for these factors. CONCLUSIONS Children growing up under conditions of socioeconomic disadvantage exhibit a faster pace of biological aging. DNA methylation pace of aging might be useful as a surrogate end point in evaluation of programs and policies to address the childhood social determinants of lifelong health disparities.
Collapse
Affiliation(s)
- Laurel Raffington
- Department of Psychology and
- Population Research Center, The University of Texas at Austin, Austin, Texas
| | - Daniel W Belsky
- Department of Epidemiology and
- The Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York; and
| | - Meeraj Kothari
- The Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York; and
| | - Margherita Malanchini
- Department of Psychology and
- Population Research Center, The University of Texas at Austin, Austin, Texas
- Department of Biological and Experimental Psychology, Queen Mary University of London, London, United Kingdom
| | - Elliot M Tucker-Drob
- Department of Psychology and
- Population Research Center, The University of Texas at Austin, Austin, Texas
- Contributed equally as co-lead authors
| | - K Paige Harden
- Department of Psychology and
- Population Research Center, The University of Texas at Austin, Austin, Texas
- Contributed equally as co-lead authors
| |
Collapse
|