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Bhatt IS, Garay JAR, Torkamani A, Dias R. DNA Methylation Patterns Associated with Tinnitus in Young Adults-A Pilot Study. J Assoc Res Otolaryngol 2024:10.1007/s10162-024-00961-2. [PMID: 39147981 DOI: 10.1007/s10162-024-00961-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 07/31/2024] [Indexed: 08/17/2024] Open
Abstract
PURPOSE Tinnitus, the perception of sound without any external sound source, is a prevalent hearing health concern. Mounting evidence suggests that a confluence of genetic, environmental, and lifestyle factors can influence the pathogenesis of tinnitus. We hypothesized that alteration in DNA methylation, an epigenetic modification that occurs at cytosines of cytosine-phosphate-guanine (CpG) dinucleotide sites, where a methyl group from S-adenyl methionine gets transferred to the fifth carbon of the cytosine, could contribute to tinnitus. DNA methylation patterns are tissue-specific, but the tissues involved in tinnitus are not easily accessible in humans. This pilot study used saliva as a surrogate tissue to identify differentially methylated CpG regions (DMRs) associated with tinnitus. The study was conducted on healthy young adults reporting bilateral continuous chronic tinnitus to limit the influence of age-related confounding factors and health-related comorbidities. METHODS The present study evaluated the genome-wide methylation levels from saliva-derived DNA samples from 24 healthy young adults with bilateral continuous chronic tinnitus (> 1 year) and 24 age, sex, and ethnicity-matched controls with no tinnitus. Genome-wide DNA methylation was evaluated for > 850,000 CpG sites using the Infinium Human Methylation EPIC BeadChip. The association analysis used the Bumphunter algorithm on 23 cases and 20 controls meeting the quality control standards. The methylation level was expressed as the area under the curve of CpG sites within DMRs.The FDR-adjusted p-value threshold of 0.05 was used to identify statistically significant DMRs associated with tinnitus. RESULTS We obtained 25 differentially methylated regions (DMRs) associated with tinnitus. Genes within or in the proximity of the hypermethylated DMRs related to tinnitus included LCLAT1, RUNX1, RUFY1, NUDT12, TTC23, SLC43A2, C4orf27 (STPG2), and EFCAB4B. Genes within or in the proximity of hypomethylated DMRs associated with tinnitus included HLA-DPB2, PM20D1, TMEM18, SNTG2, MUC4, MIR886, MIR596, TXNRD1, EID3, SDHAP3, HLA-DPB2, LASS3 (CERS3), C10orf11 (LRMDA), HLA-DQB1, NADK, SZRD1, MFAP2, NUP210L, TPM3, INTS9, and SLC2A14. The burden of genetic variation could explain the differences in the methylation levels for DMRs involving HLA-DPB2, HLA-DQB1, and MUC4, indicating the need for replication in large independent cohorts. CONCLUSION Consistent with the literature on comorbidities associated with tinnitus, we identified genes within or close to DMRs involved in auditory functions, chemical dependency, cardiovascular diseases, psychiatric conditions, immune disorders, and metabolic syndromes. These results indicate that epigenetic mechanisms could influence tinnitus, and saliva can be a good surrogate for identifying the epigenetic underpinnings of tinnitus in humans. Further research with a larger sample size is needed to identify epigenetic biomarkers and investigate their influence on the phenotypic expression of tinnitus.
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Affiliation(s)
- Ishan Sunilkumar Bhatt
- Department of Communication Sciences & Disorders, University of Iowa, Iowa City, IA, 52242, USA.
| | - Juan Antonio Raygoza Garay
- Department of Communication Sciences & Disorders, University of Iowa, Iowa City, IA, 52242, USA
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, 52242, USA
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Science Institute, La Jolla, CA, 92037, USA
| | - Raquel Dias
- Department of Microbiology and Cell Science, University of Florida, Gainesville, FL, 32608, USA
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Deng WQ, Cawte N, Campbell N, Azab SM, de Souza RJ, Lamri A, Morrison KM, Atkinson SA, Subbarao P, Turvey SE, Moraes TJ, Teo KK, Mandhane PJ, Azad MB, Simons E, Paré G, Anand SS. Maternal smoking DNA methylation risk score associated with health outcomes in offspring of European and South Asian ancestry. eLife 2024; 13:RP93260. [PMID: 39141540 PMCID: PMC11324234 DOI: 10.7554/elife.93260] [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: 08/16/2024] Open
Abstract
Background Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations. Methods We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504). Results Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (-0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (-0.043±0.013 kg, p=0.0011) in the combined cohorts. Conclusions This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers. Funding This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.
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Affiliation(s)
- Wei Q Deng
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Peter Boris Centre for Addictions Research, St. Joseph’s Healthcare HamiltonHamiltonCanada
- Department of Psychiatry and Behavioural Neurosciences, McMaster UniversityHamiltonCanada
| | - Nathan Cawte
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
| | - Natalie Campbell
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
| | - Sandi M Azab
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Department of Health Research Methods, Evidence, and Impact, McMaster UniversityHamiltonCanada
| | - Russell J de Souza
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Department of Health Research Methods, Evidence, and Impact, McMaster UniversityHamiltonCanada
| | - Amel Lamri
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
| | | | | | | | - Stuart E Turvey
- Department of Pediatrics, BC Children’s Hospital, The University of British ColumbiaVancouverCanada
| | - Theo J Moraes
- Department of Pediatrics, University of TorontoTorontoCanada
- Program in Translational Medicine, SickKids Research InstituteTorontoCanada
| | - Koon K Teo
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
- Department of Health Research Methods, Evidence, and Impact, McMaster UniversityHamiltonCanada
| | | | - Meghan B Azad
- Children’s Hospital Research Institute of Manitoba, Department of Pediatrics and Child Health, University of ManitobaWinnipegCanada
| | - Elinor Simons
- Section of Allergy and Immunology, Department of Pediatrics and Child Health, University of ManitobaManitobaCanada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
- Department of Health Research Methods, Evidence, and Impact, McMaster UniversityHamiltonCanada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of MedicineHamiltonCanada
| | - Sonia S Anand
- Department of Medicine, Faculty of Health Sciences, McMaster UniversityHamiltonCanada
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research InstituteHamiltonCanada
- Department of Health Research Methods, Evidence, and Impact, McMaster UniversityHamiltonCanada
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Argentieri MA, Xiao S, Bennett D, Winchester L, Nevado-Holgado AJ, Ghose U, Albukhari A, Yao P, Mazidi M, Lv J, Millwood I, Fry H, Rodosthenous RS, Partanen J, Zheng Z, Kurki M, Daly MJ, Palotie A, Adams CJ, Li L, Clarke R, Amin N, Chen Z, van Duijn CM. Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations. Nat Med 2024:10.1038/s41591-024-03164-7. [PMID: 39117878 DOI: 10.1038/s41591-024-03164-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 06/27/2024] [Indexed: 08/10/2024]
Abstract
Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity and mortality. Here we developed a proteomic age clock in the UK Biobank (n = 45,441) using a proteomic platform comprising 2,897 plasma proteins and explored its utility to predict major disease morbidity and mortality in diverse populations. We identified 204 proteins that accurately predict chronological age (Pearson r = 0.94) and found that proteomic aging was associated with the incidence of 18 major chronic diseases (including diseases of the heart, liver, kidney and lung, diabetes, neurodegeneration and cancer), as well as with multimorbidity and all-cause mortality risk. Proteomic aging was also associated with age-related measures of biological, physical and cognitive function, including telomere length, frailty index and reaction time. Proteins contributing most substantially to the proteomic age clock are involved in numerous biological functions, including extracellular matrix interactions, immune response and inflammation, hormone regulation and reproduction, neuronal structure and function and development and differentiation. In a validation study involving biobanks in China (n = 3,977) and Finland (n = 1,990), the proteomic age clock showed similar age prediction accuracy (Pearson r = 0.92 and r = 0.94, respectively) compared to its performance in the UK Biobank. Our results demonstrate that proteomic aging involves proteins spanning multiple functional categories and can be used to predict age-related functional status, multimorbidity and mortality risk across geographically and genetically diverse populations.
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Affiliation(s)
- M Austin Argentieri
- Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, USA.
| | - Sihao Xiao
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
| | - Derrick Bennett
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Laura Winchester
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Alejo J Nevado-Holgado
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Upamanyu Ghose
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ashwag Albukhari
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
- Biochemistry Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Pang Yao
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mohsen Mazidi
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Iona Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hannah Fry
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Jukka Partanen
- Research and Development, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Zhili Zheng
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Mitja Kurki
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Cassandra J Adams
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia
- Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Robert Clarke
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Najaf Amin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- King Abdulaziz University and the University of Oxford Centre for Artificial Intelligence in Precision Medicine (KO-CAIPM), Jeddah, Saudi Arabia.
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Zellers S, van Dongen J, Maes HHM, Ollikainen M, Fang F, Vrieze S, Kaprio J, Boomsma DI. A Bivariate Twin Study of Lifetime cannabis Initiation and Lifetime Regular Tobacco Smoking Across Three Different Countries. Behav Genet 2024:10.1007/s10519-024-10190-1. [PMID: 39078541 DOI: 10.1007/s10519-024-10190-1] [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: 05/14/2024] [Accepted: 07/23/2024] [Indexed: 07/31/2024]
Abstract
Regular cigarette smoking and cannabis consumption are strongly positively related to each other, yet few studies explore their underlying variation and covariation. We evaluated the genetic and environmental decomposition of variance and covariance of these two traits in twin data from three countries with different social norms and legislation. Data from the Netherlands Twin Register, FinnTwin12/16, and the Minnesota Center for Twin Family Research (total N = 21,617) were analyzed in bivariate threshold models of lifetime regular smoking initiation (RSI) and lifetime cannabis initiation (CI). We ran unstratified models and models stratified by sex and country. Prevalence of RSI was lowest in the Netherlands and prevalence of CI was highest in Minnesota. In the unstratified model, genetic (A) and common environmental factors (C) contributed substantially to the liabilities of RSI (A = 0.47, C = 0.34) and CI (A = 0.28, C = 0.51). The two liabilities were significantly phenotypically (rP = 0.56), genetically (rA = 0.74), and environmentally correlated in the unstratified model (rC = 0.47and rE = 0.48, representing correlations between common and unique environmental factors). The magnitude of phenotypic correlation between liabilities varied by country but not sex (Minnesota rP ~ 0.70, Netherlands rP ~ 0.59, Finland rP ~ 0.45). Comparisons of decomposed correlations could not be reliably tested in the stratified models. The prevalence and association of RSI and CI vary by sex and country. These two behaviors are correlated because there is genetic and environmental overlap between their underlying latent liabilities. There is heterogeneity in the genetic architecture of these traits across country.
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Affiliation(s)
- Stephanie Zellers
- Institute for Molecular Medicine Finland, University of Helsinki, P.O. Box 20, Helsinki, 00014, Finland.
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Hermine H M Maes
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Human and Molecular Genetics, Psychiatry and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, University of Helsinki, P.O. Box 20, Helsinki, 00014, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Fang Fang
- GenOmics and Translational Research Center, Research Triangle Institute International, Research Triangle Park, NC, USA
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, P.O. Box 20, Helsinki, 00014, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
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Machado AS, Bragança M, Vieira-Coelho M. Epigenetic effects of cannabis: A systematic scoping review of behavioral and emotional symptoms associated with cannabis use and exocannabinoid exposure. Drug Alcohol Depend 2024; 263:111401. [PMID: 39137613 DOI: 10.1016/j.drugalcdep.2024.111401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 06/22/2024] [Accepted: 07/11/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND Recent research suggests that epigenetic modifications may mediate the behavioral effects of cannabis, influencing exocannabinnoids' long term effects in cognitive function and its role in the emergence of psychotic symptoms. BASIC PROCEDURES In this systematic scoping review, we assessed the current evidence of epigenetic effects associated with the use of cannabis or exocannabinoid administration and their relationship with behavioral and emotional symptoms. We searched PubMed, Cochrane CENTRAL, and Web of Science, up to January 2022, using the terms "cannabis" and "epigenetics." The search yielded 178 articles, of which 43 underwent full article revision; 37 articles were included in the review. MAIN FINDINGS The gathered evidence included observational cross-sectional studies conducted on human subjects and experimental designs using animal models that conveyed disparity in administration dosage, methods of cannabis use assessment and targeted epigenetic mechanisms. Nine studies performed epigenome-wide analysis with identification of differentially methylated sites; most of these studies found a global hypomethylation, and enrichment in genes related to cellular survival and neurodevelopment. Other studies assessed methylation at specific genes and found that cannabis exposure was associated with reduced methylation at Cg05575921, DNMT1, DRD2, COMT, DLGAP2, Arg1, STAT3, MGMT, and PENK, while hypermethylation was found at DNMT3a/b, NCAM1, and AKT1. CONCLUSIONS The review found evidence of an exocannabinoid-induced epigenetic changes that modulate depressive-anxious, psychotic, and addictive behavioural phenotypes. Further studies will require dosage exposure/administration uniformization and a customized pool of genes to assess their suitability as biomarkers for psychiatric diseases.
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Affiliation(s)
- Ana Sofia Machado
- Psychiatry Service of São João Local Health Unit, Porto, Portugal; Clinical Neurosciences and Mental Health Department, Medicine Faculty of Porto University (FMUP), Porto, Portugal.
| | - Miguel Bragança
- Psychiatry Service of São João Local Health Unit, Porto, Portugal; Clinical Neurosciences and Mental Health Department, Medicine Faculty of Porto University (FMUP), Porto, Portugal
| | - Maria Vieira-Coelho
- Psychiatry Service of São João Local Health Unit, Porto, Portugal; Biomedicine Department, Medicine Faculty of Porto University (FMUP), Porto, Portugal
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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.
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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
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7
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Martin FZ, Easey KE, Howe LD, Fraser A, Lawlor DA, Relton CL, Sharp GC. A novel hypothesis-generating approach for detecting phenotypic associations using epigenetic data. Epigenomics 2024:1-14. [PMID: 39016098 DOI: 10.1080/17501911.2024.2366157] [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: 01/15/2024] [Accepted: 06/06/2024] [Indexed: 07/18/2024] Open
Abstract
Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example. Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC. Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase. Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.
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Affiliation(s)
- Florence Z Martin
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Kayleigh E Easey
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, London, UK
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- School of Psychology, University of Exeter, Exeter, UK
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Levy D, Kirmani S, Huan T, Van Amburg J, Joehanes R, Uddin MM, Nguyen NQ, Yu B, Brody J, Fornage M, Bressler J, Sotoodehnia N, Ong D, Puddu F, Floyd J, Ballantyne C, Psaty B, Raffield L, Natarajan P, Conneely K, Carson A, Lange L, Ferrier K, Heard-Costa N, Murabito J, Bick A. Epigenome-wide DNA Methylation Association Study of CHIP Provides Insight into Perturbed Gene Regulation. RESEARCH SQUARE 2024:rs.3.rs-4656898. [PMID: 39070619 PMCID: PMC11276001 DOI: 10.21203/rs.3.rs-4656898/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed "clonal hematopoiesis of indeterminate potential" (CHIP). How these mutations confer a proliferative advantage and result in increased risk for numerous age-related diseases remains poorly understood. We conducted a multiracial meta-analysis of epigenome-wide association studies (EWAS) of CHIP and its subtypes in four cohorts (N=8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. The EWAS findings were functionally validated using human hematopoietic stem cell (HSC) models of CHIP. A total of 9615 CpGs were associated with any CHIP, 5990 with DNMT3A CHIP, 5633 with TET2 CHIP, and 6078 with ASXL1 CHIP (P <1×10-7). CpGs associated with CHIP subtypes overlapped moderately, and the genome-wide DNA methylation directions of effect were opposite for TET2 and DNMT3A CHIP, consistent with their opposing effects on global DNA methylation. There was high directional concordance between the CpGs shared from the meta-EWAS and human edited CHIP HSCs. Expression quantitative trait methylation analysis further identified transcriptomic changes associated with CHIP-associated CpGs. Causal inference analyses revealed 261 CHIP-associated CpGs associated with cardiovascular traits and all-cause mortality (FDR adjusted p-value <0.05). Taken together, our study sheds light on the epigenetic changes impacted by CHIP and their associations with age-related disease outcomes. The novel genes and pathways linked to the epigenetic features of CHIP may serve as therapeutic targets for preventing or treating CHIP-mediated diseases.
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Affiliation(s)
- Daniel Levy
- Framingham Heart Study, Framingham, MA, 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health
| | - Sara Kirmani
- Framingham Heart Study, Framingham, MA, 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda
| | | | - Joseph Van Amburg
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
| | | | | | | | - Bing Yu
- University of Texas Health Science Center at Houston
| | | | - Myriam Fornage
- 1. Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center 2. Human Genetics Center, Department of Epidemiology, School of Public Health
| | - Jan Bressler
- School of Public Health, University of Texas Health Science Center at Houston
| | | | - David Ong
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | | | | | | | | | | | - Pradeep Natarajan
- Broad Institute of Harvard and Massachusetts Institute of Technology
| | | | | | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine
| | | | | | - Joanne Murabito
- Section of General Internal Medicine, Boston University Chobanian & Avedisian School of Medicine
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9
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Yusipov I, Kalyakulina A, Trukhanov A, Franceschi C, Ivanchenko M. Map of epigenetic age acceleration: A worldwide analysis. Ageing Res Rev 2024; 100:102418. [PMID: 39002646 DOI: 10.1016/j.arr.2024.102418] [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: 04/17/2024] [Revised: 07/03/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.
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Affiliation(s)
- Igor Yusipov
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Alena Kalyakulina
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Arseniy Trukhanov
- Mriya Life Institute, National Academy of Active Longevity, Moscow 124489, Russia.
| | - Claudio Franceschi
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Mikhail Ivanchenko
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
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10
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Jiang H, Huang C, Shi Y, Wang CH, Chen SY, Li J, Wang Q, Li MT, Tian XP, Zeng XF, Zhao Y, Zhao JL. Effect of smoking on thrombotic antiphospholipid syndrome: a 10-year prospective cohort study. Rheumatology (Oxford) 2024; 63:1917-1922. [PMID: 37738261 DOI: 10.1093/rheumatology/kead498] [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: 04/15/2023] [Revised: 08/16/2023] [Accepted: 08/21/2023] [Indexed: 09/24/2023] Open
Abstract
OBJECTIVES Cigarette smoking is an established risk factor for autoimmune diseases. However, whether smoking plays a clear role in thrombotic APS (TAPS) has not been determined. We aimed to investigate the effects of smoking on the clinical characteristics and prognosis of TAPS. METHODS This was a prospective cohort study from 2013 to 2022. During the study period, 297 patients were diagnosed with TAPS, including 82 smokers and 215 non-smokers. After propensity score matching, 57 smokers and 57 non-smokers matched by age and sex were analysed. RESULTS Overall, smokers with TAPS had more cardiovascular risk factors than non-smokers, including hypertension (36.59% vs 14.42%, P < 0.001), obesity (15.85% vs 7.44%, P = 0.029), dyslipidaemia (64.63% vs 48.37%, P = 0.012) and hyperhomocysteinaemia (62.20% vs 36.28%, P < 0.001). Arterial thrombotic events were more common in smokers at diagnosis (62.20% vs 46.05%, P = 0.013), especially myocardial infarction, visceral thrombosis and peripheral vascular thrombosis. After matching, smokers showed balanced cardiovascular risk factors with non-smokers at baseline, but retained a higher prevalence of arterial thrombosis (59.65% vs 33.33%, P = 0.005), mainly distributed in cerebral vascular, cardiovascula and retinal vascular territories. During follow-up, smokers presented a tendency for more recurrent arterial thrombosis and less recurrent venous thrombosis. Smokers had significantly poorer outcomes for organ damage with higher Damage Index for APS score (median 2.00 vs 1.00, P = 0.008), especially in the cardiovascular (26.32% vs 3.51%, P = 0.001), gastrointestinal (15.79% vs 1.75%, P = 0.016) and ophthalmologic (10.53% vs 00.00%, P = 0.027) systems. CONCLUSION Smoking is related to increased arterial events and poor prognosis in TAPS patients. Patients with TAPS should be fully encouraged to avoid smoking.
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Affiliation(s)
- Hui Jiang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Can Huang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
| | - Yu Shi
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chu-Han Wang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Si-Yun Chen
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jun Li
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qian Wang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Meng-Tao Li
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Xin-Ping Tian
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Xiao-Feng Zeng
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Yan Zhao
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Jiu-Liang Zhao
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Dermatologic and Immunologic Diseases, Ministry of Science & Technology, Beijing, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing, China
- Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
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11
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Djordjilović V, Ponzi E, Nøst TH, Thoresen M. penalizedclr: an R package for penalized conditional logistic regression for integration of multiple omics layers. BMC Bioinformatics 2024; 25:226. [PMID: 38937668 PMCID: PMC11212437 DOI: 10.1186/s12859-024-05850-2] [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: 01/08/2024] [Accepted: 06/20/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND The matched case-control design, up until recently mostly pertinent to epidemiological studies, is becoming customary in biomedical applications as well. For instance, in omics studies, it is quite common to compare cancer and healthy tissue from the same patient. Furthermore, researchers today routinely collect data from various and variable sources that they wish to relate to the case-control status. This highlights the need to develop and implement statistical methods that can take these tendencies into account. RESULTS We present an R package penalizedclr, that provides an implementation of the penalized conditional logistic regression model for analyzing matched case-control studies. It allows for different penalties for different blocks of covariates, and it is therefore particularly useful in the presence of multi-source omics data. Both L1 and L2 penalties are implemented. Additionally, the package implements stability selection for variable selection in the considered regression model. CONCLUSIONS The proposed method fills a gap in the available software for fitting high-dimensional conditional logistic regression models accounting for the matched design and block structure of predictors/features. The output consists of a set of selected variables that are significantly associated with case-control status. These variables can then be investigated in terms of functional interpretation or validation in further, more targeted studies.
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Affiliation(s)
- Vera Djordjilović
- Department of Economics, Ca' Foscari University of Venice, Venice, Italy.
- Department of Biostatistics, University of Oslo, Oslo, Norway.
| | - Erica Ponzi
- Department of Biostatistics, University of Oslo, Oslo, Norway
| | - Therese Haugdahl Nøst
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Community Medicine, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
| | - Magne Thoresen
- Department of Biostatistics, University of Oslo, Oslo, Norway
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12
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Singh M, Dolan CV, Lapato DM, Hottenga JJ, Pool R, Verhulst B, Boomsma DI, Breeze CE, de Geus EJC, Hemani G, Min JL, Peterson RE, Maes HHM, van Dongen J, Neale MC. Twin-based Mendelian Randomization Analyses Highlight Smoking's Effects on Blood DNA Methylation, with Putative Reverse Causation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.19.24309184. [PMID: 38946972 PMCID: PMC11213072 DOI: 10.1101/2024.06.19.24309184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Epigenome-wide association studies (EWAS) aim to identify differentially methylated loci associated with complex traits and disorders. EWAS of cigarette smoking shows some of the most widespread DNA methylation (DNAm) associations in blood. However, traditional EWAS cannot differentiate between causation and confounding, leading to ambiguity in etiological interpretations. Here, we apply an integrated approach combining Mendelian Randomization and twin-based Direction-of-Causation analyses (MR-DoC) to examine causality underlying smoking-associated blood DNAm changes in the Netherlands Twin Register (N=2577). Evidence across models suggests that current smoking's causal effects on DNAm likely drive many of the previous EWAS findings, implicating functional pathways relevant to several adverse health outcomes of smoking, including hemopoiesis, cell- and neuro-development, and immune regulation. Additionally, we find evidence of potential reverse causal influences at some DNAm sites, with 17 of these sites enriched for gene regulatory functional elements in the brain. The top three sites with evidence of DNAm's effects on smoking annotate to genes involved in G protein-coupled receptor signaling (GNG7, RGS3) and innate immune response (SLC15A4), elucidating potential biological risk factors for smoking. This study highlights the utility of integrating genotypic and DNAm measures in twin cohorts to clarify the causal relationships between health behaviors and blood DNAm.
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Affiliation(s)
- Madhurbain Singh
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
| | - Conor V. Dolan
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Dana M. Lapato
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University, College Station, TX, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Current address: Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
| | - Charles E. Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, MD, USA
- UCL Cancer Institute, University College London, London, UK
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Josine L. Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Roseann E. Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Hermine H. M. Maes
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- These authors jointly supervised this work
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- These authors jointly supervised this work
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13
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Macias-Gómez A, Jiménez-Balado J, Fernández-Pérez I, Suárez-Pérez A, Vallverdú-Prats M, Guimaraens L, Vivas E, Saldaña J, Giralt-Steinhauer E, Guisado-Alonso D, Villalba G, Gracia MP, Esteller M, Rodriguez-Campello A, Jiménez-Conde J, Ois A, Cuadrado-Godia E. The influence of epigenetic biological age on key complications and outcomes in aneurysmal subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry 2024; 95:675-681. [PMID: 38302433 DOI: 10.1136/jnnp-2023-332889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/16/2024] [Indexed: 02/03/2024]
Abstract
BACKGROUND We aimed to investigate the association between DNA-methylation biological age (B-age) calculated as age acceleration (ageAcc) and key aneurysmal subarachnoid haemorrhage (aSAH) complications such as vasospasm, delayed cerebral ischaemia (DCI), poor outcome, and mortality. METHODS We conducted a prospective study involving 277 patients with aSAH. B-age was determined in whole blood samples using five epigenetic clocks: Hannum's, Horvath's, Levine's and both versions of Zhang's clocks. Age acceleration was calculated as the residual obtained from regressing out the effect of C-age on the mismatch between C-age and B-age. We then tested the association between ageAcc and vasospasm, DCI and 12-month poor outcome (mRS 3-5) and mortality using linear regression models adjusted for confounders. RESULTS Average C-age was 55.0 years, with 66.8% being female. Vasospasm occurred in 143 cases (51.6%), DCI in 70 (25.3%) and poor outcomes in 99 (35.7%), with a mortality rate of 20.6%. Lower ageAcc was linked to vasospasm in Horvath's and Levine's clocks, whereas increased ageAcc was associated with 12-month mortality in Hannum's clock. No significant differences in ageAcc were found for DCI or poor outcome at 12 months with other clocks. CONCLUSIONS Our study indicates that B-age is independently associated with vasospasm and 12-month mortality in patients with aSAH. These findings underscore the potential role of epigenetics in understanding the pathophysiology of aSAH-related complications and outcomes.
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Affiliation(s)
- Adrià Macias-Gómez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Joan Jiménez-Balado
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Isabel Fernández-Pérez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Antoni Suárez-Pérez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Marta Vallverdú-Prats
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Leopoldo Guimaraens
- J.J. Merland of Therapeutic Neuroangiography, Hospital del Mar, Barcelona, Catalunya, Spain
| | - Elio Vivas
- J.J. Merland of Therapeutic Neuroangiography, Hospital del Mar, Barcelona, Catalunya, Spain
| | - Jesus Saldaña
- J.J. Merland of Therapeutic Neuroangiography, Hospital del Mar, Barcelona, Catalunya, Spain
| | - Eva Giralt-Steinhauer
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Daniel Guisado-Alonso
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
| | - Gloria Villalba
- Neurosurgery Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Maria-Pilar Gracia
- Pompeu Fabra University, Barcelona, Catalunya, Spain
- Intensive Care Department, Hospital del Mar, Barcelona, Catalunya, Spain
| | - Manel Esteller
- Cancer Epigenetics Group, Research Institute Against Leukemia Josep Carreras, Badalona, Catalunya, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Catalunya, Spain
| | - Ana Rodriguez-Campello
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Jordi Jiménez-Conde
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Angel Ois
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Elisa Cuadrado-Godia
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
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14
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Polli A, Nijs J. Exploring biological mechanisms of lifestyle and environmental factors in humans: Current challenges and future directions. Invited comment on: "Environmental factors and their impact on chronic pain development and maintenance", by Sant'Anna et al. Phys Life Rev 2024; 50:43-45. [PMID: 38905875 DOI: 10.1016/j.plrev.2024.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 06/23/2024]
Affiliation(s)
- Andrea Polli
- Pain in Motion (PAIN) research group, Department of Physiotherapy, Human Physiology, and Anatomy, Vrije Universiteit Brussel, Brussels, Belgium; Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium; Research Foundation, Flanders (FWO), Belgium.
| | - Jo Nijs
- Pain in Motion (PAIN) research group, Department of Physiotherapy, Human Physiology, and Anatomy, Vrije Universiteit Brussel, Brussels, Belgium; Institute of Neuroscience and Physiology, Department of Health and Rehabilitation, University of Gothenburg, Gothenburg, Sweden
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15
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Lai L, Matías-García PR, Kretschmer A, Gieger C, Wilson R, Linseisen J, Peters A, Waldenberger M. Smoking-Induced DNA Hydroxymethylation Signature Is Less Pronounced than True DNA Methylation: The Population-Based KORA Fit Cohort. Biomolecules 2024; 14:662. [PMID: 38927065 PMCID: PMC11201877 DOI: 10.3390/biom14060662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 05/31/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
Despite extensive research on 5-methylcytosine (5mC) in relation to smoking, there has been limited exploration into the interaction between smoking and 5-hydroxymethylcytosine (5hmC). In this study, total DNA methylation (5mC+5hmC), true DNA methylation (5mC) and hydroxymethylation (5hmC) levels were profiled utilizing conventional bisulphite (BS) and oxidative bisulphite (oxBS) treatment, measured with the Illumina Infinium Methylation EPIC BeadChip. An epigenome-wide association study (EWAS) of 5mC+5hmC methylation revealed a total of 38,575 differentially methylated positions (DMPs) and 2023 differentially methylated regions (DMRs) associated with current smoking, along with 82 DMPs and 76 DMRs associated with former smoking (FDR-adjusted p < 0.05). Additionally, a focused examination of 5mC identified 33 DMPs linked to current smoking and 1 DMP associated with former smoking (FDR-adjusted p < 0.05). In the 5hmC category, eight DMPs related to current smoking and two DMPs tied to former smoking were identified, each meeting a suggestive threshold (p < 1 × 10-5). The substantial number of recognized DMPs, including 5mC+5hmC (7069/38,575, 2/82), 5mC (0/33, 1/1), and 5hmC (2/8, 0/2), have not been previously reported. Our findings corroborated previously established methylation positions and revealed novel candidates linked to tobacco smoking. Moreover, the identification of hydroxymethylated CpG sites with suggestive links provides avenues for future research.
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Affiliation(s)
- Liye Lai
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Pettenkofer School of Public Health, Faculty of Medicine, Ludwig Maximilians University, 81377 Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
| | - Pamela R. Matías-García
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
| | - Anja Kretschmer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
| | - Jakob Linseisen
- Epidemiology, Faculty of Medicine, University Hospital of Augsburg, University of Augsburg, 86156 Augsburg, Germany;
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Pettenkofer School of Public Health, Faculty of Medicine, Ludwig Maximilians University, 81377 Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, 81377 Munich, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (P.R.M.-G.); (C.G.); (R.W.); (A.P.)
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany;
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, 81377 Munich, Germany
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16
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Carbonneau M, Li Y, Prescott B, Liu C, Huan T, Joehanes R, Murabito JM, Heard‐Costa NL, Xanthakis V, Levy D, Ma J. Epigenetic Age Mediates the Association of Life's Essential 8 With Cardiovascular Disease and Mortality. J Am Heart Assoc 2024; 13:e032743. [PMID: 38808571 PMCID: PMC11255626 DOI: 10.1161/jaha.123.032743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 03/25/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Life's Essential 8 (LE8) is an enhanced metric for cardiovascular health. The interrelations among LE8, biomarkers of aging, and disease risks are unclear. METHODS AND RESULTS LE8 score was calculated for 5682 Framingham Heart Study participants. We implemented 4 DNA methylation-based epigenetic age biomarkers, with older epigenetic age hypothesized to represent faster biological aging, and examined whether these biomarkers mediated the associations between the LE8 score and cardiovascular disease (CVD), CVD-specific mortality, and all-cause mortality. We found that a 1 SD increase in the LE8 score was associated with a 35% (95% CI, 27-41; P=1.8E-15) lower risk of incident CVD, a 36% (95% CI, 24-47; P=7E-7) lower risk of CVD-specific mortality, and a 29% (95% CI, 22-35; P=7E-15) lower risk of all-cause mortality. These associations were partly mediated by epigenetic age biomarkers, particularly the GrimAge and the DunedinPACE scores. The potential mediation effects by epigenetic age biomarkers tended to be more profound in participants with higher genetic risk for older epigenetic age, compared with those with lower genetic risk. For example, in participants with higher GrimAge polygenic scores (greater than median), the mean proportion of mediation was 39%, 39%, and 78% for the association of the LE8 score with incident CVD, CVD-specific mortality, and all-cause mortality, respectively. No significant mediation was observed in participants with lower GrimAge polygenic score. CONCLUSIONS DNA methylation-based epigenetic age scores mediate the associations between the LE8 score and incident CVD, CVD-specific mortality, and all-cause mortality, particularly in individuals with higher genetic predisposition for older epigenetic age.
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Affiliation(s)
- Madeleine Carbonneau
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Framingham Heart StudyFraminghamMA
| | - Yi Li
- Department of BiostatisticsBoston University School of Public HealthBostonMA
| | - Brenton Prescott
- Section of Preventive Medicine and EpidemiologyBoston University School of MedicineBostonMA
| | - Chunyu Liu
- Department of BiostatisticsBoston University School of Public HealthBostonMA
| | - Tianxiao Huan
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Framingham Heart StudyFraminghamMA
| | - Roby Joehanes
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Framingham Heart StudyFraminghamMA
| | - Joanne M. Murabito
- Framingham Heart StudyFraminghamMA
- Department of MedicineSection of General Internal Medicine Boston University Chobanian & Avedisian School of Medicine, Boston, MA and Boston Medical CenterBostonMA
| | - Nancy L. Heard‐Costa
- Department of MedicineSection of General Internal Medicine Boston University Chobanian & Avedisian School of Medicine, Boston, MA and Boston Medical CenterBostonMA
| | - Vanessa Xanthakis
- Framingham Heart StudyFraminghamMA
- Department of BiostatisticsBoston University School of Public HealthBostonMA
- Section of Preventive Medicine and EpidemiologyBoston University School of MedicineBostonMA
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Framingham Heart StudyFraminghamMA
| | - Jiantao Ma
- Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and PolicyTufts UniversityBostonMA
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17
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Carnes MU, Quach BC, Zhou L, Han S, Tao R, Mandal M, Deep-Soboslay A, Marks JA, Page GP, Maher BS, Jaffe AE, Won H, Bierut LJ, Hyde TM, Kleinman JE, Johnson EO, Hancock DB. Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci. Neuropsychopharmacology 2024:10.1038/s41386-024-01885-4. [PMID: 38830989 DOI: 10.1038/s41386-024-01885-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 04/19/2024] [Accepted: 05/06/2024] [Indexed: 06/05/2024]
Abstract
Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.
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Affiliation(s)
- Megan Ulmer Carnes
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Bryan C Quach
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Linran Zhou
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Shizhong Han
- Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA
| | - Ran Tao
- Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA
| | - Meisha Mandal
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | | | - Jesse A Marks
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Grier P Page
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
| | - Brion S Maher
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Andrew E Jaffe
- Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development (LIBD), Baltimore, MD, USA
| | - Eric O Johnson
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
| | - Dana B Hancock
- Genomics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.
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18
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Herzog C, Jones A, Evans I, Raut JR, Zikan M, Cibula D, Wong A, Brenner H, Richmond RC, Widschwendter M. Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis. Cancer Res 2024; 84:1898-1914. [PMID: 38503267 PMCID: PMC11148547 DOI: 10.1158/0008-5472.can-23-2957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/30/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024]
Abstract
Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer, and elicits profound epigenetic changes thought to be associated with long-term cancer risk. While electronic cigarettes (e-cigarettes) have been advocated as harm reduction alternatives to tobacco products, recent studies have revealed potential detrimental effects, highlighting the urgent need for further research into the molecular and health impacts of e-cigarettes. Here, we applied computational deconvolution methods to dissect the cell- and tissue-specific epigenetic effects of tobacco or e-cigarette use on DNA methylation (DNAme) in over 3,500 buccal/saliva, cervical, or blood samples, spanning epithelial and immune cells at directly and indirectly exposed sites. The 535 identified smoking-related DNAme loci [cytosine-phosphate-guanine sites (CpG)] clustered into four functional groups, including detoxification or growth signaling, based on cell type and anatomic site. Loci hypermethylated in buccal epithelial cells of smokers associated with NOTCH1/RUNX3/growth factor receptor signaling also exhibited elevated methylation in cancer tissue and progressing lung carcinoma in situ lesions, and hypermethylation of these sites predicted lung cancer development in buccal samples collected from smokers up to 22 years prior to diagnosis, suggesting a potential role in driving carcinogenesis. Alarmingly, these CpGs were also hypermethylated in e-cigarette users with a limited smoking history. This study sheds light on the cell type-specific changes to the epigenetic landscape induced by smoking-related products. SIGNIFICANCE The use of both cigarettes and e-cigarettes elicits cell- and exposure-specific epigenetic effects that are predictive of carcinogenesis, suggesting caution when broadly recommending e-cigarettes as aids for smoking cessation.
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Affiliation(s)
- Chiara Herzog
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Universität Innsbruck, Innsbruck, Austria
- Research Institute for Biomedical Aging, Universität Innsbruck, Innsbruck, Austria
| | - Allison Jones
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, London, United Kingdom
| | - Iona Evans
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, London, United Kingdom
| | - Janhavi R Raut
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michal Zikan
- Department of Gynecology and Obstetrics, First Faculty of Medicine and Hospital Na Bulovce, Charles University in Prague, Prague, Czech Republic
| | - David Cibula
- Gynecologic Oncology Center, Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University in Prague, General University Hospital in Prague, Prague, Czech Republic
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Universität Innsbruck, Innsbruck, Austria
- Research Institute for Biomedical Aging, Universität Innsbruck, Innsbruck, Austria
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, London, United Kingdom
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
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19
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Hu W, Chen S, Cai J, Yang Y, Yan H, Chen F. High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study. BMC Med Res Methodol 2024; 24:125. [PMID: 38831262 PMCID: PMC11145821 DOI: 10.1186/s12874-024-02254-x] [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: 03/15/2024] [Accepted: 05/22/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it's an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation. METHODS In this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing. RESULTS Simulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene. CONCLUSIONS The proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies.
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Affiliation(s)
- Weiwei Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Shiyu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Jiaxin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Yuhui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Hong Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Fangyao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
- Department of Radiology, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
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20
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Yan Ang Q, Plichta D, Kim S, Hyun-A Kim I, Gregory S, Xia Y, Lau H, Xavier R, Ananthakrishnan AN. Differential Impact of Smoking on Methylome and Transcriptome in Crohn's Disease and Ulcerative Colitis. Inflamm Bowel Dis 2024; 30:981-991. [PMID: 38001042 PMCID: PMC11145016 DOI: 10.1093/ibd/izad268] [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: 09/25/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND Smoking is an environmental factor that differentially impacts Crohn's disease (CD) and ulcerative colitis (UC). The mechanism of impact of smoking on disease risk and clinical outcomes remains to be established. METHODS This study used a prospective cohort of patients with CD or UC. Self-reported smoking status was validated using serum cotinine measurement. We profiled methylation changes in peripheral blood using the Illumina Methylation BeadChip. Transcriptomic profiling was performed on ileal and colonic tissue using an Illumina TruSeq platform. We compared the methylation and transcriptional changes in current, former, and never smokers stratified by disease type. RESULTS Our cohort included 200 patients with CD or UC with methylation profiles and 160 with transcriptomic data. The mean serum cotinine level was higher in current compared with former or never smokers. Epigenetic changes common to both CD and UC included hypomethylation at AHRR. Smoking-associated MGAT3 hypomethylation was associated with severe disease course only in UC, while IER3 hypomethylation was associated with worse course only in CD. Smoking downregulated several inflammatory pathways in UC. Current smoking in CD but not in UC was associated with upregulation of several genes mediating Paneth cell function. Genes with opposite direction of effects in CD and UC include HSD3B2 and GSTA1. CONCLUSIONS Our findings suggest both common and differential effects of cigarette smoking on CD and UC. Paneth cell dysfunction may mediate adverse impact of smoking on CD. Bile acid and oxidative stress pathways may be relevant for the differential effect of smoking on CD and UC.
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Affiliation(s)
| | | | - Sean Kim
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
| | - Iris Hyun-A Kim
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
| | - Sadie Gregory
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
| | - Yan Xia
- Broad Institute, Cambridge, MA, USA
| | - Helena Lau
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
| | - Ramnik Xavier
- Broad Institute, Cambridge, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Ashwin N Ananthakrishnan
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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21
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Domingo-Relloso A, Tellez-Plaza M, Valeri L. Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology. Curr Environ Health Rep 2024; 11:109-117. [PMID: 38386268 DOI: 10.1007/s40572-024-00436-9] [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] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE OF REVIEW Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data. RECENT FINDINGS The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Biostatistics, Columbia University Mailman School of Public Health, 722 West 168Th Street, New York, NY, 10032, USA.
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Linda Valeri
- Department of Biostatistics, Columbia University Mailman School of Public Health, 722 West 168Th Street, New York, NY, 10032, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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22
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Tong H, Dwaraka VB, Chen Q, Luo Q, Lasky-Su JA, Smith R, Teschendorff AE. Quantifying the stochastic component of epigenetic aging. NATURE AGING 2024; 4:886-901. [PMID: 38724732 PMCID: PMC11186785 DOI: 10.1038/s43587-024-00600-8] [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: 09/22/2023] [Accepted: 02/21/2024] [Indexed: 05/15/2024]
Abstract
DNA methylation clocks can accurately estimate chronological age and, to some extent, also biological age, yet the process by which age-associated DNA methylation (DNAm) changes are acquired appears to be quasi-stochastic, raising a fundamental question: how much of an epigenetic clock's predictive accuracy could be explained by a stochastic process of DNAm change? Here, using DNAm data from sorted immune cells, we build realistic simulation models, subsequently demonstrating in over 22,770 sorted and whole-blood samples from 25 independent cohorts that approximately 66-75% of the accuracy underpinning Horvath's clock could be driven by a stochastic process. This fraction increases to 90% for the more accurate Zhang's clock, but is lower (63%) for the PhenoAge clock, suggesting that biological aging is reflected by nonstochastic processes. Confirming this, we demonstrate that Horvath's age acceleration in males and PhenoAge's age acceleration in severe coronavirus disease 2019 cases and smokers are not driven by an increased rate of stochastic change but by nonstochastic processes. These results significantly deepen our understanding and interpretation of epigenetic clocks.
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Affiliation(s)
- Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | | | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
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23
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Bourassa KJ, Halverson TF, Garrett ME, Hair L, Dennis M, Ashley-Koch AE, Beckham JC, Kimbrel NA. Demographic characteristics and epigenetic biological aging among post-9/11 veterans: Associations of DunedinPACE with sex, race, and age. Psychiatry Res 2024; 336:115908. [PMID: 38626626 PMCID: PMC11070289 DOI: 10.1016/j.psychres.2024.115908] [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: 02/05/2024] [Revised: 04/01/2024] [Accepted: 04/06/2024] [Indexed: 04/18/2024]
Abstract
Measures of epigenetic aging derived from DNA methylation (DNAm) have enabled the assessment of biological aging in new populations and cohorts. In the present study, we used an epigenetic measure of aging, DunedinPACE, to examine rates of aging across demographic groups in a sample of 2,309 United States military veterans from the VISN 6 MIRECC's Post-Deployment Mental Health Study. As assessed by DunedinPACE, female veterans were aging faster than male veterans (β = 0.39, 95 % CI [0.29, 0.48], p < .001), non-Hispanic Black veterans were aging faster than non-Hispanic White veterans (β = 0.58, 95 % CI [0.50, 0.66], p < .001), and older veterans were biologically aging faster than younger veterans (β = 0.21, 95 % CI [0.18, 0.25], p < .001). In secondary analyses, these differences in rates of aging were not explained by a variety of biopsychosocial covariates. In addition, the percentage of European genetic admixture in non-Hispanic Black veterans was not associated with DunedinPACE. Our findings suggest that female and non-Hispanic Black veterans are at greater risk of accelerated aging among post-9/11 veterans. Interventions that slow aging might provide relatively greater benefit among veterans comprising these at-risk groups.
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Affiliation(s)
- Kyle J Bourassa
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System; Geriatric Research, Education, and Clinical Center, Durham VA Health Care System; Center for the Study of Aging and Human Development, Duke University Medical Center.
| | - Tate F Halverson
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System
| | | | - Lauren Hair
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine
| | - Michelle Dennis
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine
| | | | - Jean C Beckham
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine
| | - Nathan A Kimbrel
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Health Care System; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine; VA Health Services Research and Development Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System
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Vahidi S, Agah S, Mirzajani E, Asghari Gharakhyli E, Norollahi SE, Rahbar Taramsari M, Babaei K, Samadani AA. microRNAs, oxidative stress, and genotoxicity as the main inducers in the pathobiology of cancer development. Horm Mol Biol Clin Investig 2024; 45:55-73. [PMID: 38507551 DOI: 10.1515/hmbci-2023-0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 03/06/2024] [Indexed: 03/22/2024]
Abstract
Cancer is one of the most serious leading causes of death in the world. Many eclectic factors are involved in cancer progression including genetic and epigenetic alongside environmental ones. In this account, the performance and fluctuations of microRNAs are significant in cancer diagnosis and treatment, particularly as diagnostic biomarkers in oncology. So, microRNAs manage and control the gene expression after transcription by mRNA degradation, or also they can inhibit their translation. Conspicuously, these molecular structures take part in controlling the cellular, physiological and pathological functions, which many of them can accomplish as tumor inhibitors or oncogenes. Relatively, Oxidative stress is defined as the inequality between the creation of reactive oxygen species (ROS) and the body's ability to detoxify the reactive mediators or repair the resulting injury. ROS and microRNAs have been recognized as main cancer promoters and possible treatment targets. Importantly, genotoxicity has been established as the primary reason for many diseases as well as several malignancies. The procedures have no obvious link with mutagenicity and influence the organization, accuracy of the information, or fragmentation of DNA. Conclusively, mutations in these patterns can lead to carcinogenesis. In this review article, we report the impressive and practical roles of microRNAs, oxidative stress, and genotoxicity in the pathobiology of cancer development in conjunction with their importance as reliable cancer biomarkers and their association with circulating miRNA, exosomes and exosomal miRNAs, RNA remodeling, DNA methylation, and other molecular elements in oncology.
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Affiliation(s)
- Sogand Vahidi
- Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Shahram Agah
- Colorectal Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Ebrahim Mirzajani
- Department of Biochemistry and Biophysics, School of Medicine, 37554 Guilan University of Medical Sciences , Rasht, Iran
| | | | - Seyedeh Elham Norollahi
- Cancer Research Center and Department of Immunology, Semnan University of Medical Sciences, Semnan, Iran
| | - Morteza Rahbar Taramsari
- Department of Forensic Medicine, School of Medicine, 37554 Guilan University of Medical Sciences , Rasht, Iran
| | - Kosar Babaei
- Noncommunicable Diseases Research Center, Neyshabur University of Medical Sciences, Neyshabur, Iran
| | - Ali Akbar Samadani
- Guilan Road Trauma Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran
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Shorey-Kendrick LE, Davis B, Gao L, Park B, Vu A, Morris CD, Breton CV, Fry R, Garcia E, Schmidt RJ, O’Shea TM, Tepper RS, McEvoy CT, Spindel ER. Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67005. [PMID: 38885141 PMCID: PMC11218700 DOI: 10.1289/ehp13838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/27/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established. OBJECTIVE Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost. METHODS We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 . RESULTS Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ). DISCUSSION To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.
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Affiliation(s)
- Lyndsey E. Shorey-Kendrick
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
| | - Brett Davis
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Lina Gao
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Byung Park
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Health & Science University–Portland State University School of Public Health, Portland, Oregon, USA
| | - Annette Vu
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cynthia D. Morris
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Carrie V. Breton
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca Fry
- Department of Environmental Sciences and Engineering, UNC Gillings School of Public Health, Chapel Hill, North Carolina, USA
| | - Erika Garcia
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California, USA
- MIND Institute, School of Medicine, University of California Davis, Davis, California, USA
| | - T. Michael O’Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Robert S. Tepper
- Department of Pediatrics, Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Cindy T. McEvoy
- Department of Pediatrics, Oregon Health & Science University, Portland, Oregon, USA
| | - Eliot R. Spindel
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
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26
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Li MD, Liu Q, Shi X, Wang Y, Zhu Z, Guan Y, He J, Han H, Mao Y, Ma Y, Yuan W, Yao J, Yang Z. Integrative analysis of genetics, epigenetics and RNA expression data reveal three susceptibility loci for smoking behavior in Chinese Han population. Mol Psychiatry 2024:10.1038/s41380-024-02599-1. [PMID: 38789676 DOI: 10.1038/s41380-024-02599-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 04/18/2024] [Accepted: 05/03/2024] [Indexed: 05/26/2024]
Abstract
Despite numerous studies demonstrate that genetics and epigenetics factors play important roles on smoking behavior, our understanding of their functional relevance and coordinated regulation remains largely unknown. Here we present a multiomics study on smoking behavior for Chinese smoker population with the goal of not only identifying smoking-associated functional variants but also deciphering the pathogenesis and mechanism underlying smoking behavior in this under-studied ethnic population. After whole-genome sequencing analysis of 1329 Chinese Han male samples in discovery phase and OpenArray analysis of 3744 samples in replication phase, we discovered that three novel variants located near FOXP1 (rs7635815), and between DGCR6 and PRODH (rs796774020), and in ARVCF (rs148582811) were significantly associated with smoking behavior. Subsequently cis-mQTL and cis-eQTL analysis indicated that these variants correlated significantly with the differential methylation regions (DMRs) or differential expressed genes (DEGs) located in the regions where these variants present. Finally, our in silico multiomics analysis revealed several hub genes, like DRD2, PTPRD, FOXP1, COMT, CTNNAP2, to be synergistic regulated each other in the etiology of smoking.
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Affiliation(s)
- Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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.
| | - Qiang Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
| | - Xiaoqiang Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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, National Medical 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
| | - Zhouhai Zhu
- Joint Institute of Tobacco and Health, Kunming, Yunnan, China
| | - Ying Guan
- Joint Institute of Tobacco and Health, Kunming, Yunnan, China
| | - Jingmin He
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
- College of Biological Sciences, Shanxi Agricultural University, Taigu, Shanxi, China
| | - Haijun Han
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
| | - Ying Mao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
| | - Yunlong Ma
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
| | - Wenji Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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
| | - Jianhua Yao
- Joint Institute of Tobacco and Health, Kunming, Yunnan, China
| | - Zhongli Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical 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.
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27
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Chen B, Zeng G, Sun L, Jiang C. When smoke meets gut: deciphering the interactions between tobacco smoking and gut microbiota in disease development. SCIENCE CHINA. LIFE SCIENCES 2024; 67:854-864. [PMID: 38265598 DOI: 10.1007/s11427-023-2446-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/09/2023] [Indexed: 01/25/2024]
Abstract
Tobacco smoking is a prevalent and detrimental habit practiced worldwide, increasing the risk of various diseases, including chronic obstructive pulmonary disease (COPD), cardiovascular disease, liver disease, and cancer. Although previous research has explored the detrimental health effects of tobacco smoking, recent studies suggest that gut microbiota dysbiosis may play a critical role in these outcomes. Numerous tobacco smoke components, such as nicotine, are found in the gastrointestinal tract and interact with gut microbiota, leading to lasting impacts on host health and diseases. This review delves into the ways tobacco smoking and its various constituents influence gut microbiota composition and functionality. We also summarize recent advancements in understanding how tobacco smoking-induced gut microbiota dysbiosis affects host health. Furthermore, this review introduces a novel perspective on how changes in gut microbiota following smoking cessation may contribute to withdrawal syndrome and the degree of health improvements in smokers.
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Affiliation(s)
- Bo Chen
- Center of Basic Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, 100191, China
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, 100191, China
- Center for Obesity and Metabolic Disease Research, School of Basic Medical Sciences, Peking University, Beijing, 100191, China
| | - Guangyi Zeng
- Center of Basic Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, 100191, China
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, 100191, China
- Center for Obesity and Metabolic Disease Research, School of Basic Medical Sciences, Peking University, Beijing, 100191, China
| | - Lulu Sun
- State Key Laboratory of Women's Reproductive Health and Fertility Promotion, Peking University, Beijing, 100191, China.
- Department of Endocrinology and Metabolism, Peking University Third Hospital, Beijing, 100191, China.
| | - Changtao Jiang
- Center of Basic Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, 100191, China.
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, 100191, China.
- Center for Obesity and Metabolic Disease Research, School of Basic Medical Sciences, Peking University, Beijing, 100191, China.
- State Key Laboratory of Women's Reproductive Health and Fertility Promotion, Peking University, Beijing, 100191, China.
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Sun X, Chen W, Razavi AC, Shi M, Pan Y, Li C, Argos M, Layden BT, Daviglus ML, He J, Carmichael OT, Bazzano LA, Kelly TN. Associations of Epigenetic Age Acceleration With CVD Risks Across the Lifespan: The Bogalusa Heart Study. JACC Basic Transl Sci 2024; 9:577-590. [PMID: 38984046 PMCID: PMC11228118 DOI: 10.1016/j.jacbts.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/09/2024] [Accepted: 01/09/2024] [Indexed: 07/11/2024]
Abstract
Although epigenetic age acceleration (EAA) might serve as a molecular signature of childhood cardiovascular disease (CVD) risk factors and further promote midlife subclinical CVD, few studies have comprehensively examined these life course associations. This study sought to test whether childhood CVD risk factors predict EAA in adulthood and whether EAA mediates the association between childhood CVD risks and midlife subclinical disease. Among 1,580 Bogalusa Heart Study participants, we estimated extrinsic EAA, intrinsic EAA, PhenoAge acceleration (PhenoAgeAccel), and GrimAge acceleration (GrimAgeAccel) during adulthood. We tested prospective associations of longitudinal childhood body mass index (BMI), blood pressure, lipids, and glucose with EAAs using linear mixed effects models. After confirming EAAs with midlife carotid intima-media thickness and carotid plaque, structural equation models examined mediating effects of EAAs on associations of childhood CVD risk factors with subclinical CVD measures. After stringent multiple testing corrections, each SD increase in childhood BMI was significantly associated with 0.6-, 0.9-, and 0.5-year increases in extrinsic EAA, PhenoAgeAccel, and GrimAgeAccel, respectively (P < 0.001 for all 3 associations). Likewise, each SD increase in childhood log-triglycerides was associated with 0.5- and 0.4-year increases in PhenoAgeAccel and GrimAgeAccel (P < 0.001 for both), respectively, whereas each SD increase in childhood high-density lipoprotein cholesterol was associated with a 0.3-year decrease in GrimAgeAccel (P = 0.002). Our findings indicate that PhenoAgeAccel mediates an estimated 27.4% of the association between childhood log-triglycerides and midlife carotid intima-media thickness (P = 0.022). Our data demonstrate that early life CVD risk factors may accelerate biological aging and promote subclinical atherosclerosis.
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Affiliation(s)
- Xiao Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Alexander C Razavi
- Emory Clinical Cardiovascular Research Institute, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Mengyao Shi
- Department of Epidemiology, School of Public Health, and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases Medical College of Soochow University, Jiangsu, China
| | - Yang Pan
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Maria Argos
- Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, Illinois, USA
| | - Brian T Layden
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | | | - Lydia A Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
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29
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Fernández-Pérez I, Jiménez-Balado J, Macias-Gómez A, Suárez-Pérez A, Vallverdú-Prats M, Pérez-Giraldo A, Viles-García M, Peris-Subiza J, Vidal-Notari S, Giralt-Steinhauer E, Guisado-Alonso D, Esteller M, Rodriguez-Campello A, Jiménez-Conde J, Ois A, Cuadrado-Godia E. Blood DNA Methylation Analysis Reveals a Distinctive Epigenetic Signature of Vasospasm in Aneurysmal Subarachnoid Hemorrhage. Transl Stroke Res 2024:10.1007/s12975-024-01252-x. [PMID: 38649590 DOI: 10.1007/s12975-024-01252-x] [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: 02/27/2024] [Revised: 03/28/2024] [Accepted: 04/06/2024] [Indexed: 04/25/2024]
Abstract
Vasospasm is a potentially preventable cause of poor prognosis in patients with aneurysmal subarachnoid hemorrhage (aSAH). Epigenetics might provide insight on its molecular mechanisms. We aimed to analyze the association between differential DNA methylation (DNAm) and development of vasospasm. We conducted an epigenome-wide association study in 282 patients with aSAH admitted to our hospital. DNAm was assessed with the EPIC Illumina chip (> 850 K CpG sites) in whole-blood samples collected at hospital admission. We identified differentially methylated positions (DMPs) at the CpG level using Cox regression models adjusted for potential confounders, and then we used the DMP results to find differentially methylated regions (DMRs) and enriched biological pathways. A total of 145 patients (51%) experienced vasospasm. In the DMP analysis, we identified 31 CpGs associated with vasospasm at p-value < 10-5. One of them (cg26189827) was significant at the genome-wide level (p-value < 10-8), being hypermethylated in patients with vasospasm and annotated to SUGCT gene, mainly expressed in arteries. Region analysis revealed 13 DMRs, some of them annotated to interesting genes such as POU5F1, HLA-DPA1, RUFY1, and CYP1A1. Functional enrichment analysis showed the involvement of biological processes related to immunity, inflammatory response, oxidative stress, endothelial nitric oxide, and apoptosis. Our findings show, for the first time, a distinctive epigenetic signature of vasospasm in aSAH, establishing novel links with essential biological pathways, including inflammation, immune responses, and oxidative stress. Although further validation is required, our results provide a foundation for future research into the complex pathophysiology of vasospasm.
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Affiliation(s)
- Isabel Fernández-Pérez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
| | - Joan Jiménez-Balado
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain.
| | - Adrià Macias-Gómez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
| | - Antoni Suárez-Pérez
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
| | - Marta Vallverdú-Prats
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
| | | | - Marc Viles-García
- Neuroradiology Department, Hospital del Mar, Barcelona, Catalunya, Spain
| | | | | | - Eva Giralt-Steinhauer
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Daniel Guisado-Alonso
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
| | - Manel Esteller
- Cancer Epigenetics Group, Research Institute Against Leukemia Josep Carreras, Badalona, Catalunya, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Catalunya, Spain
| | - Ana Rodriguez-Campello
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Jordi Jiménez-Conde
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Angel Ois
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
| | - Elisa Cuadrado-Godia
- Neurology Department, Hospital del Mar, Barcelona, Catalunya, Spain
- Neurovascular Research Group, Hospital del Mar Medical Research Institute, C/Dr. Aiguader, 88, 08003, Barcelona, Catalunya, Spain
- Pompeu Fabra University, Barcelona, Catalunya, Spain
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30
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Teschendorff AE. On epigenetic stochasticity, entropy and cancer risk. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230054. [PMID: 38432318 PMCID: PMC10909509 DOI: 10.1098/rstb.2023.0054] [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: 04/01/2023] [Accepted: 09/26/2023] [Indexed: 03/05/2024] Open
Abstract
Epigenetic changes are known to accrue in normal cells as a result of ageing and cumulative exposure to cancer risk factors. Increasing evidence points towards age-related epigenetic changes being acquired in a quasi-stochastic manner, and that they may play a causal role in cancer development. Here, I describe the quasi-stochastic nature of DNA methylation (DNAm) changes in ageing cells as well as in normal cells at risk of neoplastic transformation, discussing the implications of this stochasticity for developing cancer risk prediction strategies, and in particular, how it may require a conceptual paradigm shift in how we select cancer risk markers. I also describe the mounting evidence that a significant proportion of DNAm changes in ageing and cancer development are related to cell proliferation, reflecting tissue-turnover and the opportunity this offers for predicting cancer risk via the development of epigenetic mitotic-like clocks. Finally, I describe how age-associated DNAm changes may be causally implicated in cancer development via an irreversible suppression of tissue-specific transcription factors that increases epigenetic and transcriptomic entropy, promoting a more plastic yet aberrant cancer stem-cell state. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Andrew E. Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, People's Republic of China
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Bui H, Keshawarz A, Wang M, Lee M, Ratliff SM, Lin L, Birditt KS, Faul JD, Peters A, Gieger C, Delerue T, Kardia SLR, Zhao W, Guo X, Yao J, Rotter JI, Li Y, Liu X, Liu D, Tavares JF, Pehlivan G, Breteler MMB, Karabegovic I, Ochoa-Rosales C, Voortman T, Ghanbari M, van Meurs JBJ, Nasr MK, Dörr M, Grabe HJ, London SJ, Teumer A, Waldenberger M, Weir DR, Smith JA, Levy D, Ma J, Liu C. Association analysis between an epigenetic risk score and blood pressure. RESEARCH SQUARE 2024:rs.3.rs-4243866. [PMID: 38699335 PMCID: PMC11065078 DOI: 10.21203/rs.3.rs-4243866/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
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Affiliation(s)
| | | | | | - Mikyeong Lee
- National Institute of Environmental Health Sciences
| | | | | | | | | | - Annette Peters
- Helmholtz Munich, German Research Center for Environmental Health
| | - Christian Gieger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance
| | - Thomas Delerue
- Helmholtz Munich, German Research Center for Environmental Health
| | | | | | - Xiuqing Guo
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Jie Yao
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Jerome I Rotter
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Yi Li
- Boston University School of Public Health
| | - Xue Liu
- Boston University School of Public Health
| | - Dan Liu
- German Center for Neurodegenerative Diseases
| | | | | | | | | | | | | | | | | | | | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald
| | | | | | | | - Melanie Waldenberger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance
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Bui H, Keshawarz A, Wang M, Lee M, Ratliff SM, Lin L, Birditt KS, Faul JD, Peters A, Gieger C, Delerue T, Kardia SLR, Zhao W, Guo X, Yao J, Rotter JI, Li Y, Liu X, Liu D, Tavares JF, Pehlivan G, Breteler MM, Karabegovic I, Ochoa-Rosales C, Voortman T, Ghanbari M, van Meurs JB, Nasr MK, Dörr M, Grabe HJ, London SJ, Teumer A, Waldenberger M, Weir DR, Smith JA, Levy D, Ma J, Liu C. Association analysis between an epigenetic alcohol risk score and blood pressure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.29.24303545. [PMID: 38464320 PMCID: PMC10925472 DOI: 10.1101/2024.02.29.24303545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
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Affiliation(s)
- Helena Bui
- 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
| | - 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
| | - Mengyao Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Kira S. Birditt
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, German
- Institute for Medical Informatics, Biometrics and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Christian Gieger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Xiuqing Guo
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jie Yao
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Yi Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Xue Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Dan Liu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Juliana F. Tavares
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Gökhan Pehlivan
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Monique M.B. Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Irma Karabegovic
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Centro de Vida Saludable de la Universidad de Concepción, Concepción, Chile
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Joyce B.J. van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohamed Kamal Nasr
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine, Greifswald, Germany
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, site Greifswald, Germany
| | - Stephanie J. London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Melanie Waldenberger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Daniel Levy
- 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
| | - Jiantao Ma
- Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Chunyu Liu
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
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33
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Li JL, Jain N, Tamayo LI, Tong L, Jasmine F, Kibriya MG, Demanelis K, Oliva M, Chen LS, Pierce BL. The association of cigarette smoking with DNA methylation and gene expression in human tissue samples. Am J Hum Genet 2024; 111:636-653. [PMID: 38490207 PMCID: PMC11023923 DOI: 10.1016/j.ajhg.2024.02.012] [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: 08/14/2023] [Revised: 02/17/2024] [Accepted: 02/21/2024] [Indexed: 03/17/2024] Open
Abstract
Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.
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Affiliation(s)
- James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Interdisciplinary Scientist Training Program, University of Chicago, Chicago, IL 60637, USA
| | - Niyati Jain
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Committee on Genetics, Genomics, Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Lizeth I Tamayo
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Farzana Jasmine
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL 60637, USA
| | - Muhammad G Kibriya
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA; UPMC Hillman Cancer Center, Pittsburgh, PA 15232, USA
| | - Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Genomics Research Center, AbbVie, North Chicago, IL 60064, USA
| | - Lin S Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Comprehensive Cancer Center, University of Chicago, Chicago, IL 60637, USA.
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34
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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.
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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
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35
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Vermeulen R, Bodinier B, Dagnino S, Wada R, Wang X, Silverman D, Albanes D, Freedman N, Rahman M, Bell D, Chadeau-Hyam M, Rothman N. A prospective study of smoking-related white blood cell DNA methylation markers and risk of bladder cancer. Eur J Epidemiol 2024; 39:393-407. [PMID: 38554236 PMCID: PMC11101379 DOI: 10.1007/s10654-024-01110-y] [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: 07/27/2023] [Accepted: 02/20/2024] [Indexed: 04/01/2024]
Abstract
Bladder cancer, a common neoplasm, is primarily caused by tobacco smoking. Epigenetic alterations including DNA methylation have the potential to be used as prospective markers of increased risk, particularly in at-risk populations such as smokers. We aimed to investigate the potential of smoking-related white blood cell (WBC) methylation markers to contribute to an increase in bladder cancer risk prediction over classical questionnaire-based smoking metrics (i.e., duration, intensity, packyears) in a nested case-control study within the prospective prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial and the alpha-tocopherol, beta-carotene cancer (ATBC) Prevention Study (789 cases; 849 controls). We identified 200 differentially methylated sites associated with smoking status and 28 significantly associated (after correction for multiple testing) with bladder cancer risk among 2670 previously reported smoking-related cytosine-phosphate-guanines sites (CpGs). Similar patterns were observed across cohorts. Receiver operating characteristic (ROC) analyses indicated that cg05575921 (AHHR), the strongest smoking-related association we identified for bladder cancer risk, alone yielded similar predictive performance (AUC: 0.60) than classical smoking metrics (AUC: 0.59-0.62). Best prediction was achieved by including the first principal component (PC1) from the 200 smoking-related CpGs alongside smoking metrics (AUC: 0.63-0.65). Further, PC1 remained significantly associated with elevated bladder cancer risk after adjusting for smoking metrics. These findings suggest DNA methylation profiles reflect aspects of tobacco smoke exposure in addition to those captured by smoking duration, intensity and packyears, and/or individual susceptibility relevant to bladder cancer etiology, warranting further investigation.
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Affiliation(s)
- Roel Vermeulen
- Institute for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, PO Box 80178, 3508 TD, Utrecht, The Netherlands.
| | - Barbara Bodinier
- Faculty of Medicine, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Sonia Dagnino
- Faculty of Medicine, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC Centre for Environment and Health, Imperial College London, London, UK
- Commissariat À L'Energie Atomique Et Aux Énergies Alternatives (CEA), Institut Des Sciences du Vivant Fréderic Joliot, Université Côte d'Azur, Nice, France
| | - Rin Wada
- Faculty of Medicine, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Xuting Wang
- Immunity Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, RTP, Durham, NC, USA
| | - Debra Silverman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Neal Freedman
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Mohammad Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Douglas Bell
- Immunity Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, RTP, Durham, NC, USA
| | - Marc Chadeau-Hyam
- Faculty of Medicine, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Commissariat À L'Energie Atomique Et Aux Énergies Alternatives (CEA), Institut Des Sciences du Vivant Fréderic Joliot, Université Côte d'Azur, Nice, France
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
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36
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Fotopoulos NH, Chaumette B, Devenyi GA, Karama S, Chakravarty M, Labbe A, Grizenko N, Schmitz N, Fageera W, Joober R. Maternal smoking during pregnancy and cortical structure in children with attention-deficit/hyperactivity disorder. Psychiatry Res 2024; 334:115791. [PMID: 38367455 DOI: 10.1016/j.psychres.2024.115791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 01/28/2024] [Accepted: 02/11/2024] [Indexed: 02/19/2024]
Abstract
Maternal smoking during pregnancy (MSDP) is considered a risk factor for ADHD. While the mechanisms underlying this association are not well understood, MSDP may impact the developing brain in ways that lead to ADHD. Here, we investigated the effect of prenatal smoking exposure on cortical brain structures in children with ADHD using two methods of assessing prenatal exposure: maternal recall and epigenetic typing. Exposure groups were defined according to: (1) maternal recall (+MSDP: n = 24; -MSDP: n = 85) and (2) epigenetic markers (EM) (+EM: n = 14 -EM: n = 21). CIVET-1.1.12 and RMINC were used to acquire cortical brain measurements and perform statistical analyses, respectively. The vertex with highest significance was tested for association with Continuous Performance Test (CPT) dimensions. While no differences of brain structures were identified between +MSDP and -MSDP, +EM children (n = 10) had significantly smaller surface area in the right orbitofrontal cortex (ROFc), middle temporal cortex (RTc) and parahippocampal gyrus (RPHg) (15% FDR) compared to -EM children (n = 20). Cortical surface area in the RPHg significantly correlated with CPT commission errors T-scores. This study suggests that molecular markers may better define exposure to environmental risks, as compared to human recall.
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Affiliation(s)
- Nellie H Fotopoulos
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Boris Chaumette
- Department of Psychiatry, McGill University, Montréal, Québec, Canada; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GHU-Paris Psychiatrie et Neurosciences, Paris, France
| | - Gabriel A Devenyi
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Sherif Karama
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada; Montréal Neurological Institute, Montréal, Québec, Canada
| | - Mallar Chakravarty
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, Canada
| | - Aurelie Labbe
- Department of Decision Sciences, HEC Montreal, Montréal, Québec, Canada
| | - Natalie Grizenko
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Norbert Schmitz
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada
| | - Weam Fageera
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Ridha Joober
- Douglas Mental Health University Institute, Montréal, Québec, Canada; Department of Human Genetics, McGill University, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada.
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37
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Huang BZ, Binder AM, Quon B, Patel YM, Lum-Jones A, Tiirikainen M, Murphy SE, Loo L, Maunakea AK, Haiman CA, Wilkens LR, Koh WP, Cai Q, Aldrich MC, Siegmund KD, Hecht SS, Yuan JM, Blot WJ, Stram DO, Le Marchand L, Park SL. Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts. Am J Hum Genet 2024; 111:456-472. [PMID: 38367619 PMCID: PMC10940014 DOI: 10.1016/j.ajhg.2024.01.012] [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: 07/13/2023] [Revised: 01/22/2024] [Accepted: 01/25/2024] [Indexed: 02/19/2024] Open
Abstract
The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.
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Affiliation(s)
- Brian Z Huang
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA.
| | - Alexandra M Binder
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Brandon Quon
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Yesha M Patel
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Annette Lum-Jones
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Maarit Tiirikainen
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Sharon E Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Lenora Loo
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Alika K Maunakea
- Department of Anatomy, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Christopher A Haiman
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Lynne R Wilkens
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melinda C Aldrich
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kimberly D Siegmund
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stephen S Hecht
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel O Stram
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Sungshim L Park
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA.
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Yeung-Luk BH, Wally A, Swaby C, Jauregui S, Lee E, Zhang R, Chen D, Luk SH, Upadya N, Tieng E, Wilmsen K, Sherman E, Sudhakar D, Luk M, Shrivastav AK, Cao S, Ghosh B, Christenson SA, Huang YJ, Ortega VE, Biswal S, Tang WY, Sidhaye VK. Epigenetic Reprogramming Drives Epithelial Disruption in Chronic Obstructive Pulmonary Disease. Am J Respir Cell Mol Biol 2024; 70:165-177. [PMID: 37976469 PMCID: PMC10914773 DOI: 10.1165/rcmb.2023-0147oc] [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: 04/25/2023] [Accepted: 11/17/2023] [Indexed: 11/19/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) remains a major public health challenge that contributes greatly to mortality and morbidity worldwide. Although it has long been recognized that the epithelium is altered in COPD, there has been little focus on targeting it to modify the disease course. Therefore, mechanisms that disrupt epithelial cell function in patients with COPD are poorly understood. In this study, we sought to determine whether epigenetic reprogramming of the cell-cell adhesion molecule E-cadherin, encoded by the CDH1 gene, disrupts epithelial integrity. By reducing these epigenetic marks, we can restore epithelial integrity and rescue alveolar airspace destruction. We used differentiated normal and COPD-derived primary human airway epithelial cells, genetically manipulated mouse tracheal epithelial cells, and mouse and human precision-cut lung slices to assess the effects of epigenetic reprogramming. We show that the loss of CDH1 in COPD is due to increased DNA methylation site at the CDH1 enhancer D through the downregulation of the ten-eleven translocase methylcytosine dioxygenase (TET) enzyme TET1. Increased DNA methylation at the enhancer D region decreases the enrichment of RNA polymerase II binding. Remarkably, treatment of human precision-cut slices derived from patients with COPD with the DNA demethylation agent 5-aza-2'-deoxycytidine decreased cell damage and reduced air space enlargement in the diseased tissue. Here, we present a novel mechanism that targets epigenetic modifications to reverse the tissue remodeling in human COPD lungs and serves as a proof of concept for developing a disease-modifying target.
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Affiliation(s)
| | - Ara Wally
- Department of Environmental Health and Engineering and
- Department of Biochemistry and Molecular Biology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Carter Swaby
- Department of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Sofia Jauregui
- Department of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Esther Lee
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Rachel Zhang
- Department of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Daniel Chen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Sean H. Luk
- Department of Environmental Health and Engineering and
| | - Nisha Upadya
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Ethan Tieng
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Kai Wilmsen
- Department of Environmental Health and Engineering and
| | - Ethan Sherman
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Dheeksha Sudhakar
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Matthew Luk
- Department of Environmental Health and Engineering and
| | - Abhishek Kumar Shrivastav
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | - Shuo Cao
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | | | - Stephanie A. Christenson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | - Yvonne J. Huang
- Department of Medicine, University of Michigan, Ann Arbor, Michigan; and
| | | | - Shyam Biswal
- Department of Environmental Health and Engineering and
| | - Wan-yee Tang
- Department of Environmental Health and Engineering and
- Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Venkataramana K. Sidhaye
- Department of Environmental Health and Engineering and
- Department of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
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39
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Huo W, Hu H, Li T, Yuan L, Zhang J, Feng Y, Wu Y, Fu X, Ke Y, Wang M, Zhang W, Wang L, Chen Y, Gao Y, Li X, Liu J, Huang Z, Hu F, Zhang M, Sun L, Hu D, Zhao Y. Association of methylation risk score with incident type 2 diabetes mellitus: A nested case-control study. J Diabetes 2024; 16:e13512. [PMID: 38062913 PMCID: PMC10940902 DOI: 10.1111/1753-0407.13512] [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: 09/11/2023] [Revised: 11/13/2023] [Accepted: 11/14/2023] [Indexed: 03/16/2024] Open
Abstract
AIMS To investigate the association of methylation risk score (MRS) and its interactions with environmental factors with type 2 diabetes mellitus (T2DM) risk. METHODS We conducted a nested case-control study with 241 onset cases and 241 matched controls. Conditional logistic regression models were employed to identify risk CpG sites. Simple and weighted MRSs were constructed based on the methylation levels of ATP-binding cassette G1 gene, fat mass and obesity associated gene, potassium voltage-gated channel member 1 gene, and thioredoxin-interacting protein gene previously associated with T2DM to estimate the association of MRS with T2DM risk. Stratified analyses were used to investigate interactions between MRS and environmental factors. RESULTS A total of 10 CpG loci were identified from the aforementioned genes to calculate MRS. After controlling for potential confounding factors, taking tertile 1 as reference, the odds ratios (ORs) and 95% confidence intervals (CIs) for T2DM of tertile 3 was 2.39 (1.36-4.20) for simple MRS and 2.59 (1.45-4.63) for weighted MRS. With per SD score increment in MRS, the OR (95% CI) was 1.66 (1.29-2.14) and 1.60 (1.24-2.08) for simple and weighted MRSs, respectively. J-curved associations were observed between both simple and weighted MRSs and T2DM risks. Additionally, multiplication interactions for smoking and hypertension with simple MRS on the risk of T2DM were found, similarly for smoking and obesity with weighted MRS on the risk of T2DM (all Pinteraction < .05). CONCLUSION Elevated simple and weighted MRSs were associated with increased risk of T2DM. Environmental risk factors may influence the association between MRS and T2DM.
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Affiliation(s)
- Weifeng Huo
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Huifang Hu
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Tianze Li
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Lijun Yuan
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Jinli Zhang
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yifei Feng
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yuying Wu
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Xueru Fu
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yamin Ke
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Mengmeng Wang
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Wenkai Zhang
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Longkang Wang
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yaobing Chen
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yajuan Gao
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Xi Li
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Jiong Liu
- Department of Preventive MedicineSchool of Public Health, Shenzhen University Medical SchoolShenzhenChina
| | - Zelin Huang
- Department of Preventive MedicineSchool of Public Health, Shenzhen University Medical SchoolShenzhenChina
| | - Fulan Hu
- Department of Biostatistics and EpidemiologySchool of Public Health, Shenzhen University Medical SchoolShenzhenChina
| | - Ming Zhang
- Department of Biostatistics and EpidemiologySchool of Public Health, Shenzhen University Medical SchoolShenzhenChina
| | - Liang Sun
- Department of Social Medicine and Health Service ManagementCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Dongsheng Hu
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
| | - Yang Zhao
- Department of Epidemiology and BiostatisticsCollege of Public Health, Zhengzhou UniversityZhengzhouChina
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40
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Garrett ME, Dennis MF, Bourassa KJ, Hauser MA, Kimbrel NA, Beckham JC, Ashley-Koch AE. Genome-wide DNA methylation analysis of cannabis use disorder in a veteran cohort enriched for posttraumatic stress disorder. Psychiatry Res 2024; 333:115757. [PMID: 38309009 PMCID: PMC10922626 DOI: 10.1016/j.psychres.2024.115757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 02/05/2024]
Abstract
Cannabis use has been increasing over the past decade, not only in the general US population, but particularly among military veterans. With this rise in use has come a concomitant increase in cannabis use disorder (CUD) among veterans. Here, we performed an epigenome-wide association study for lifetime CUD in an Iraq/Afghanistan era veteran cohort enriched for posttraumatic stress disorder (PTSD) comprising 2,310 total subjects (1,109 non-Hispanic black and 1,201 non-Hispanic white). We also investigated CUD interactions with current PTSD status and examined potential indirect effects of DNA methylation (DNAm) on the relationship between CUD and psychiatric diagnoses. Four CpGs were associated with lifetime CUD, even after controlling for the effects of current smoking (AHRR cg05575921, LINC00299 cg23079012, VWA7 cg22112841, and FAM70A cg08760398). Importantly, cg05575921, a CpG strongly linked to smoking, remained associated with lifetime CUD even when restricting the analysis to veterans who reported never smoking cigarettes. Moreover, CUD interacted with current PTSD to affect cg05575921 and cg23079012 such that those with both CUD and PTSD displayed significantly lower DNAm compared to the other groups. Finally, we provide preliminary evidence that AHRR cg05575921 helps explain the association between CUD and any psychiatric diagnoses, specifically mood disorders.
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Affiliation(s)
- Melanie E Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, 300N Duke St, Durham, NC 27701, USA
| | - Michelle F Dennis
- Durham Veterans Affairs (VA) Health Care System, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Kyle J Bourassa
- Durham Veterans Affairs (VA) Health Care System, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center, Durham, NC, USA; Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA
| | - Michael A Hauser
- Duke Molecular Physiology Institute, Duke University Medical Center, 300N Duke St, Durham, NC 27701, USA
| | - Nathan A Kimbrel
- Durham Veterans Affairs (VA) Health Care System, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Jean C Beckham
- Durham Veterans Affairs (VA) Health Care System, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research, Education, and Clinical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Allison E Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, 300N Duke St, Durham, NC 27701, USA.
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41
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Istvan P, Birkeland E, Avershina E, Kværner AS, Bemanian V, Pardini B, Tarallo S, de Vos WM, Rognes T, Berstad P, Rounge TB. Exploring the gut DNA virome in fecal immunochemical test stool samples reveals associations with lifestyle in a large population-based study. Nat Commun 2024; 15:1791. [PMID: 38424056 PMCID: PMC10904388 DOI: 10.1038/s41467-024-46033-0] [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: 08/25/2023] [Accepted: 02/08/2024] [Indexed: 03/02/2024] Open
Abstract
Stool samples for fecal immunochemical tests (FIT) are collected in large numbers worldwide as part of colorectal cancer screening programs. Employing FIT samples from 1034 CRCbiome participants, recruited from a Norwegian colorectal cancer screening study, we identify, annotate and characterize more than 18000 DNA viruses, using shotgun metagenome sequencing. Only six percent of them are assigned to a known taxonomic family, with Microviridae being the most prevalent viral family. Linking individual profiles to comprehensive lifestyle and demographic data shows 17/25 of the variables to be associated with the gut virome. Physical activity, smoking, and dietary fiber consumption exhibit strong and consistent associations with both diversity and relative abundance of individual viruses, as well as with enrichment for auxiliary metabolic genes. We demonstrate the suitability of FIT samples for virome analysis, opening an opportunity for large-scale studies of this enigmatic part of the gut microbiome. The diverse viral populations and their connections to the individual lifestyle uncovered herein paves the way for further exploration of the role of the gut virome in health and disease.
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Affiliation(s)
- Paula Istvan
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Einar Birkeland
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ekaterina Avershina
- Department of Tumor Biology, Institute of Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Bioinformatics, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Ane S Kværner
- Section for Colorectal Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway
| | - Vahid Bemanian
- Pathology Department, Akershus University Hospital, Lørenskog, Norway
| | - Barbara Pardini
- Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
- Italian Institute for Genomic Medicine (IIGM), c/o IRCCS Candiolo, Turin, Italy
| | - Sonia Tarallo
- Candiolo Cancer Institute, FPO-IRCCS, Turin, Italy
- Italian Institute for Genomic Medicine (IIGM), c/o IRCCS Candiolo, Turin, Italy
| | - Willem M de Vos
- Human Microbiome Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands
| | - Torbjørn Rognes
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Paula Berstad
- Section for Colorectal Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway
| | - Trine B Rounge
- Department of Tumor Biology, Institute of Cancer Research, Oslo University Hospital, Oslo, Norway.
- Centre for Bioinformatics, Department of Pharmacy, University of Oslo, Oslo, Norway.
- Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.
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42
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Petralia F, Ma W, Yaron TM, Caruso FP, Tignor N, Wang JM, Charytonowicz D, Johnson JL, Huntsman EM, Marino GB, Calinawan A, Evangelista JE, Selvan ME, Chowdhury S, Rykunov D, Krek A, Song X, Turhan B, Christianson KE, Lewis DA, Deng EZ, Clarke DJB, Whiteaker JR, Kennedy JJ, Zhao L, Segura RL, Batra H, Raso MG, Parra ER, Soundararajan R, Tang X, Li Y, Yi X, Satpathy S, Wang Y, Wiznerowicz M, González-Robles TJ, Iavarone A, Gosline SJC, Reva B, Robles AI, Nesvizhskii AI, Mani DR, Gillette MA, Klein RJ, Cieslik M, Zhang B, Paulovich AG, Sebra R, Gümüş ZH, Hostetter G, Fenyö D, Omenn GS, Cantley LC, Ma'ayan A, Lazar AJ, Ceccarelli M, Wang P. Pan-cancer proteogenomics characterization of tumor immunity. Cell 2024; 187:1255-1277.e27. [PMID: 38359819 PMCID: PMC10988632 DOI: 10.1016/j.cell.2024.01.027] [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: 04/26/2023] [Revised: 09/29/2023] [Accepted: 01/16/2024] [Indexed: 02/17/2024]
Abstract
Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.
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Affiliation(s)
- Francesca Petralia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Weiping Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tomer M Yaron
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA
| | - Francesca Pia Caruso
- BIOGEM Institute of Molecular Biology and Genetics, 83031 Ariano Irpino, Italy; Department of Electrical Engineering and Information Technologies, University of Naples "Federico II", Naples, Italy
| | - Nicole Tignor
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joshua M Wang
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Daniel Charytonowicz
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jared L Johnson
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Emily M Huntsman
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Giacomo B Marino
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anna Calinawan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John Erol Evangelista
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Myvizhi Esai Selvan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Dmitry Rykunov
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Azra Krek
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xiaoyu Song
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Berk Turhan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Karen E Christianson
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - David A Lewis
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Eden Z Deng
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Daniel J B Clarke
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jeffrey R Whiteaker
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Jacob J Kennedy
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Lei Zhao
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Rossana Lazcano Segura
- Departments of Pathology & Genomic Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Harsh Batra
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Maria Gabriela Raso
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Edwin Roger Parra
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rama Soundararajan
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ximing Tang
- Department of Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yize Li
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Xinpei Yi
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shankha Satpathy
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Ying Wang
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Maciej Wiznerowicz
- Department of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznań, Poland; International Institute for Molecular Oncology, 60-203 Poznań, Poland; Department of Oncology, Heliodor Swiecicki Clinical Hospital, 60-203 Poznań, Poland
| | - Tania J González-Robles
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Antonio Iavarone
- Department of Neurological Surgery, Department of Biochemistry, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sara J C Gosline
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Boris Reva
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Alexey I Nesvizhskii
- Departments of Pathology and Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - D R Mani
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Michael A Gillette
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Marcin Cieslik
- Departments of Pathology and Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Amanda G Paulovich
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zeynep H Gümüş
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Lipschultz Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Galen Hostetter
- Pathology and Biorepository Core, Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - David Fenyö
- Institute for Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Gilbert S Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, & Environmental Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lewis C Cantley
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alexander J Lazar
- Departments of Pathology & Genomic Medicine, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Michele Ceccarelli
- Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA; Department of Public Health Sciences, University of Miami, Miami, FL, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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Tang Z, Gaskins AJ, Hood RB, Ford JB, Hauser R, Smith AK, Everson TM. Former smoking associated with epigenetic modifications in human granulosa cells among women undergoing assisted reproduction. Sci Rep 2024; 14:5009. [PMID: 38424222 PMCID: PMC10904848 DOI: 10.1038/s41598-024-54957-2] [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: 11/14/2023] [Accepted: 02/19/2024] [Indexed: 03/02/2024] Open
Abstract
Smoking exposure during adulthood can disrupt oocyte development in women, contributing to infertility and possibly adverse birth outcomes. Some of these effects may be reflected in epigenome profiles in granulosa cells (GCs) in human follicular fluid. We compared the epigenetic modifications throughout the genome in GCs from women who were former (N = 15) versus never smokers (N = 44) undergoing assisted reproductive technologies (ART). This study included 59 women undergoing ART. Smoking history including time since quitting was determined by questionnaire. GCs were collected during oocyte retrieval and DNA methylation (DNAm) levels were profiled using the Infinium MethylationEPIC BeadChip. We performed an epigenome-wide association study with robust linear models, regressing DNAm level at individual loci on smoking status, adjusting for age, ovarian stimulation protocol, and three surrogate variables. We performed differentially methylated regions (DMRs) analysis and over-representation analysis of the identified CpGs and corresponding gene set. 81 CpGs were differentially methylated among former smokers compared to never smokers (FDR < 0.05). We identified 2 significant DMRs (KCNQ1 and RHBDD2). The former smoking-associated genes were enriched in oxytocin signaling, adrenergic signaling in cardiomyocytes, platelet activation, axon guidance, and chemokine signaling pathway. These epigenetic variations have been associated with inflammatory responses, reproductive outcomes, cancer development, neurodevelopmental disorder, and cardiometabolic health. Secondarily, we examined the relationships between time since quitting and DNAm at significant CpGs. We observed three CpGs in negative associations with the length of quitting smoking (p < 0.05), which were cg04254052 (KCNIP1), cg22875371 (OGDHL), and cg27289628 (LOC148145), while one in positive association, which was cg13487862 (PLXNB1). As a pilot study, we demonstrated epigenetic modifications associated with former smoking in GCs. The study is informative to potential biological pathways underlying the documented association between smoking and female infertility and biomarker discovery for smoking-associated reproductive outcomes.
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Affiliation(s)
- Ziyin Tang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Audrey J Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Robert B Hood
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jennifer B Ford
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Alicia K Smith
- Department of Obstetrics and Gynecology, School of Medicine, Emory University, Atlanta, GA, USA
| | - Todd M Everson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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Choudhary P, Ronkainen J, Carson J, Karhunen V, Lin A, Melton PE, Jarvelin MR, Miettunen J, Huang RC, Sebert S. Developmental origins of psycho-cardiometabolic multimorbidity in adolescence and their underlying pathways through methylation markers: a two-cohort study. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02390-1. [PMID: 38366065 DOI: 10.1007/s00787-024-02390-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/26/2024] [Indexed: 02/18/2024]
Abstract
Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent's psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother-child dyads from pregnancy and adolescents at 16-17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1prenatal-BMI (NFBC1986 = β: 0.27; Raine = β: 0.39) and F2prenatal-SOP (β: -0.11) factors were observed on adolescent psycho-cardiometabolic multimorbidity. We observed an indirect effect of prenatal latent factors through epigenetic markers on a psycho-cardiometabolic multimorbidity factor in Raine study (P < 0.05). The present study exemplifies an evidence-based approach in two different birth cohorts to demonstrate similar composite structure of prenatal exposures and psycho-cardiometabolic traits (despite cultural, social, and genetic differences) and a common plausible pathway between them through underlying epigenetic markers.
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Affiliation(s)
- Priyanka Choudhary
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland.
| | - Justiina Ronkainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Jennie Carson
- Telethon Kids Institute, Perth, Australia
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - Ville Karhunen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Research Unit of Mathematical Sciences, Faculty of Science, University of Oulu, Oulu, Finland
| | - Ashleigh Lin
- Telethon Kids Institute, Perth, Australia
- UWA Centre for Child Health Research, University of Western Australia, Perth, Australia
| | - Phillip E Melton
- School of Population and Global Health, University of Western Australia, Perth, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, Middlesex, UK
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Rae-Chi Huang
- Telethon Kids Institute, Perth, Australia
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
- Nutrition and Health Innovation Research Institute (NHIRI), School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
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Cai X, Li K, Meng X, Song Q, Shi S, Li W, Niu Y, Jin L, Kan H, Wang S. Epigenome-wide association study on short-, intermediate- and long-term ozone exposure in Han Chinese, the NSPT study. JOURNAL OF HAZARDOUS MATERIALS 2024; 463:132780. [PMID: 37898092 DOI: 10.1016/j.jhazmat.2023.132780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/09/2023] [Accepted: 10/12/2023] [Indexed: 10/30/2023]
Abstract
Epidemiological and epigenetic studies have acknowledged ambient ozone exposure associated with inflammatory and cardiovascular disease. However, the molecular mechanisms still remained unclear, and epigenome-wide analysis in cohort were lacking, especially in Chinese. We included blood-derived DNA methylation for 3365 Chinese participants from the NSPT cohort and estimated individual ozone exposure level of short-, intermediate- and long-term, based on a validated prediction model. We performed epigenome-wide association studies which identified 59 CpGs and 30 DMRs at a strict genome-wide significance (P < 5 ×10-8). We also conducted comparison on the DNA methylation alteration corresponding to different time windows, and observed an enhanced differentiated methylation trend for intermediate- and long-term exposure, while the short-term exposure associated methylation changes did not retain. The targeted genes of methylation alteration were involved in mechanism related to aging, inflammation disease, metabolic syndrome, neurodevelopmental disorders, and oncogenesis. Underlying pathways were enriched in biological activities including telomere maintenance process, DNA damage response and megakaryocyte differentiation. In conclusion, our study is the first EWAS on ozone exposure conducted in large-scale Han Chinese cohort and identified associated DNA methylation change on CpGs and regions, as well as related gene functions and pathways.
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Affiliation(s)
- Xiyang Cai
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kaixuan Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xia Meng
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Qinglin Song
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Su Shi
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Wenran Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yue Niu
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China; Taizhou Institute of Health Sciences, Fudan University, Taizhou, Jiangsu, China
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 201102, China.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China; Taizhou Institute of Health Sciences, Fudan University, Taizhou, Jiangsu, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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46
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Satomi K, Ichimura K, Shibahara J. Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis. Pathol Int 2024; 74:51-67. [PMID: 38224248 DOI: 10.1111/pin.13402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/16/2023] [Accepted: 12/18/2023] [Indexed: 01/16/2024]
Abstract
The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.
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Affiliation(s)
- Kaishi Satomi
- Department of Pathology, Kyorin University Faculty of Medicine, Tokyo, Japan
| | - Koichi Ichimura
- Department of Brain Disease Translational Research, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Junji Shibahara
- Department of Pathology, Kyorin University Faculty of Medicine, Tokyo, Japan
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Krutz M, Acharya P, Elliott J, Zhao D, Mhawej R, Queimado L. Tobacco Cessation Following Laryngeal Cancer Diagnosis Predicts Response to Treatment and Laryngectomy-Free Survival. Otolaryngol Head Neck Surg 2024; 170:438-446. [PMID: 37890055 PMCID: PMC10872773 DOI: 10.1002/ohn.567] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/19/2023] [Accepted: 10/04/2023] [Indexed: 10/29/2023]
Abstract
OBJECTIVE To determine the effect of tobacco cessation following laryngeal cancer diagnosis on response to first-line therapy, laryngectomy-free survival, and overall survival in patients who were current smokers at the time of diagnosis. STUDY DESIGN Retrospective, case-control study. SETTING OU Stephenson Cancer Center, National Cancer Institute-Designated Cancer Center. METHODS We included 140 patients diagnosed with laryngeal squamous cell carcinoma, who were current smokers at the time of diagnosis, and were treated with first-line definitive radiation or chemo/radiation with the intent to cure. The association between patient characteristics and treatment response was assessed using the χ2 test and logistic regression analysis. Survival outcomes were analyzed using Kaplan-Meier methods and Cox proportional-hazards models. RESULTS Of the 140 current smokers, 61 patients (45%) quit smoking prior to treatment initiation. In adjusted logistic regression analysis, quitters had 3.7 times higher odds of achieving a complete response to first-line therapy than active smokers (odds ratio: 3.694 [1.575-8.661]; P = .003). In the adjusted Cox proportional-hazards model, quitters were 54% less likely to require salvage laryngectomy within 7 years of diagnosis than active smokers (hazard ratio: 0.456 [0.246-0.848]; P = .013). Quitters had a statistically significant increase in 7-year overall survival compared to active smokers (P = .02). CONCLUSION This is the first study to show that in newly diagnosed laryngeal cancer patients who are current smokers at the time of diagnosis, tobacco cessation significantly increases therapy response, laryngectomy-free survival, and overall survival. These data stress the importance of systematically incorporating tobacco cessation programs into laryngeal cancer treatment plans.
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Affiliation(s)
- Matthew Krutz
- Department of Otolaryngology Head and Neck Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
| | - Pawan Acharya
- Department of Biostatistics & Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
| | - Jacey Elliott
- Department of Otolaryngology Head and Neck Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
| | - Daniel Zhao
- Department of Biostatistics & Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Rachad Mhawej
- Department of Otolaryngology Head and Neck Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
| | - Lurdes Queimado
- Department of Otolaryngology Head and Neck Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
- Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Cell Biology, The University of Oklahoma Health Sciences Center, Oklahoma City OK, USA
- TSET Health Promotion Research Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
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48
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Hoang TT, Lee Y, McCartney DL, Kersten ETG, Page CM, Hulls PM, Lee M, Walker RM, Breeze CE, Bennett BD, Burkholder AB, Ward J, Brantsæter AL, Caspersen IH, Motsinger-Reif AA, Richards M, White JD, Zhao S, Richmond RC, Magnus MC, Koppelman GH, Evans KL, Marioni RE, Håberg SE, London SJ. Comprehensive evaluation of smoking exposures and their interactions on DNA methylation. EBioMedicine 2024; 100:104956. [PMID: 38199042 PMCID: PMC10825325 DOI: 10.1016/j.ebiom.2023.104956] [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: 07/07/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS). METHODS We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C). FINDINGS Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs. INTERPRETATION Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases. FUNDING Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.
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Affiliation(s)
- Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Department of Pediatrics, Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA; Cancer and Hematology Center, Texas Children's Hospital, Houston, TX, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Elin T G Kersten
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Physical Health and Ageing, Division for Physical and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Paige M Hulls
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Charles E Breeze
- UCL Cancer Institute, University College London, Paul O'Gorman Building, London, UK; Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Brian D Bennett
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Adam B Burkholder
- Department of Health and Human Services, Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - James Ward
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Anne Lise Brantsæter
- Department of Food Safety, Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ida H Caspersen
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Alison A Motsinger-Reif
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | | | - Julie D White
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; GenOmics and Translational Research Center, Analytics Practice Area, RTI International, Research Triangle Park, NC, USA
| | - Shanshan Zhao
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
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Viola TW, Danzer C, Mardini V, Szobot C, Chrusciel JH, Stertz L, Schmitz JM, Walss-Bass C, Fries GR, Grassi-Oliveira R. Prenatal cocaine exposure and its influence on pediatric epigenetic clocks and epigenetic scores in humans. Sci Rep 2024; 14:1946. [PMID: 38253635 PMCID: PMC10803757 DOI: 10.1038/s41598-024-52433-5] [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: 10/09/2023] [Accepted: 01/18/2024] [Indexed: 01/24/2024] Open
Abstract
The investigation of the effects of prenatal cocaine exposure (PCE) on offspring has been inconsistent, with few studies investigating biological outcomes in humans. We profiled genome-wide DNA methylation (DNAm) of umbilical cord blood (UCB) from newborns with (n = 35) and without (n = 47) PCE. We used DNAm data to (1) assess pediatric epigenetic clocks at birth and (2) to estimate epigenetic scores (ES) for lifetime disorders. We generated gestational epigenetic age estimates (DNAmGA) based on Knight and Bohlin epigenetic clocks. We also investigated the association between DNAmGA and UCB serum brain-derived neurotrophic factor (BDNF) levels. Considering the large-scale DNAm data availability and existing evidence regarding PCE as a risk for health problems later in life, we generated ES for tobacco smoking, psychosis, autism, diabetes, and obesity. A gene ontology (GO) analysis on the CpGs included in the ES with group differences was performed. PCE was associated with lower DNAmGA in newborns, and this effect remained significant when controlling for potential confounders, such as blood cell type composition predicted by DNAm and obstetric data. DNAmGA was negatively correlated with BDNF levels in the serum of UCB. Higher tobacco smoking, psychosis, and diabetes ES were found in the PCE group. The GO analysis revealed GABAergic synapses as a potential pathway altered by PCE. Our findings of decelerated DNAmGA and ES for adverse phenotypes associated with PCE, suggest that the effects of gestational cocaine exposure on the epigenetic landscape of human newborns are detectable at birth.
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Affiliation(s)
- Thiago Wendt Viola
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil
| | - Christina Danzer
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, A701-129, 8200, Aarhus, Denmark
| | - Victor Mardini
- Clinical Hospital of Porto Alegre, Porto Alegre, RS, Brazil
| | - Claudia Szobot
- Clinical Hospital of Porto Alegre, Porto Alegre, RS, Brazil
| | - João Henrique Chrusciel
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil
| | - Laura Stertz
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Joy M Schmitz
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Consuelo Walss-Bass
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Gabriel R Fries
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Rodrigo Grassi-Oliveira
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil.
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, A701-129, 8200, Aarhus, Denmark.
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50
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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.
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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.
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