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El Sharkawy M, Felix JF, Grote V, Voortman T, Jaddoe VWV, Koletzko B, Küpers LK. Animal and plant protein intake during infancy and childhood DNA methylation: a meta-analysis in the NutriPROGRAM consortium. Epigenetics 2024; 19:2299045. [PMID: 38198623 PMCID: PMC10793674 DOI: 10.1080/15592294.2023.2299045] [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: 03/14/2023] [Accepted: 12/19/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Higher early-life animal protein intake is associated with a higher childhood obesity risk compared to plant protein intake. Differential DNA methylation may represent an underlying mechanism. METHODS We analysed associations of infant animal and plant protein intakes with DNA methylation in early (2-6 years, N = 579) and late (7̄-12 years, N = 604) childhood in two studies. Study-specific robust linear regression models adjusted for relevant confounders were run, and then meta-analysed using a fixed-effects model. We also performed sex-stratified meta-analyses. Follow-up analyses included pathway analysis and eQTM look-up. RESULTS Infant animal protein intake was not associated with DNA methylation in early childhood, but was associated with late-childhood DNA methylation at cg21300373 (P = 4.27 × 10¯8, MARCHF1) and cg10633363 (P = 1.09 × 10¯7, HOXB9) after FDR correction. Infant plant protein intake was associated with early-childhood DNA methylation at cg25973293 (P = 2.26 × 10-7, C1orf159) and cg15407373 (P = 2.13 × 10-7, MBP) after FDR correction. There was no overlap between the findings from the animal and plant protein analyses. We did not find enriched functional pathways at either time point using CpGs associated with animal and plant protein. These CpGs were not previously associated with childhood gene expression. Sex-stratified meta-analyses showed sex-specific DNA methylation associations for both animal and plant protein intake. CONCLUSION Infant animal protein intake was associated with DNA methylation at two CpGs in late childhood. Infant plant protein intake was associated with DNA methylation in early childhood at two CpGs. A potential mediating role of DNA methylation at these CpGs between infant protein intake and health outcomes requires further investigation.
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Affiliation(s)
- Mohammed El Sharkawy
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
- Munich Medical Research School, Faculty of Medicine, LMU - Ludwig-Maximilians Universität Munich, Munich, Germany
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Leanne K. Küpers
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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Tomusiak A, Floro A, Tiwari R, Riley R, Matsui H, Andrews N, Kasler HG, Verdin E. Development of an epigenetic clock resistant to changes in immune cell composition. Commun Biol 2024; 7:934. [PMID: 39095531 PMCID: PMC11297166 DOI: 10.1038/s42003-024-06609-4] [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: 09/22/2023] [Accepted: 07/14/2024] [Indexed: 08/04/2024] Open
Abstract
Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.
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Affiliation(s)
- Alan Tomusiak
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
- Department of Gerontology, University of Southern California, 3715 McClintock Ave, Los Angeles, 90089, CA, USA
| | - Ariel Floro
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
- Department of Gerontology, University of Southern California, 3715 McClintock Ave, Los Angeles, 90089, CA, USA
| | - Ritesh Tiwari
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Rebeccah Riley
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Hiroyuki Matsui
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Nicolas Andrews
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Herbert G Kasler
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA.
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3
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Alsup A, Nissen E, Salas LA, Molinaro AM, Reiner A, Liu S, Madsen TE, Liu L, Auer PL, Christensen BC, Wiencke JK, Kelsey KT, Koestler DC. An assessment of compositional methods for the analysis of DNA methylation-based deconvolution estimates. Epigenomics 2024:1-14. [PMID: 39093129 DOI: 10.1080/17501911.2024.2379242] [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: 05/02/2024] [Accepted: 07/09/2024] [Indexed: 08/04/2024] Open
Abstract
DNA methylation (DNAm)-based deconvolution estimates contain relative data, forming a composition, that standard methods (testing directly on cell proportions) are ill-suited to handle. In this study we examined the performance of an alternative method, analysis of compositions of microbiomes (ANCOM), for the analysis of DNAm-based deconvolution estimates. We performed two different simulation studies comparing ANCOM to a standard approach (two sample t-test performed directly on cell proportions) and analyzed a real-world data from the Women's Health Initiative to evaluate the applicability of ANCOM to DNAm-based deconvolution estimates. Our findings indicate that ANCOM can effectively account for the compositional nature of DNAm-based deconvolution estimates. ANCOM adequately controls the false discovery rate while maintaining statistical power comparable to that of standard methods.
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Affiliation(s)
- Alexander Alsup
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Emily Nissen
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alexander Reiner
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Simin Liu
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Tracy E Madsen
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Longjian Liu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health & Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - John K Wiencke
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Karl T Kelsey
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
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4
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Dye CK, Alschuler DM, Wu H, Duarte C, Monk C, Belsky DW, Lee S, O'Donnell K, Baccarelli AA, Scorza P. Maternal Adverse Childhood Experiences and Biological Aging During Pregnancy and in Newborns. JAMA Netw Open 2024; 7:e2427063. [PMID: 39120899 DOI: 10.1001/jamanetworkopen.2024.27063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/10/2024] Open
Abstract
Importance Adverse childhood experiences (ACEs), potentially traumatic experiences occurring before the age of 18 years, are associated with epigenetic aging later in life and may be transmitted across generations. Objective To test evidence of the transmission of biological embedding of life experience across generations by analyzing maternal ACEs and epigenetic clocks measured in mothers during pregnancy and in their children at birth. Design, Setting, and Participants For this cross-sectional study, data from the Accessible Resource for Integrated Epigenomic Studies (ARIES) substudy of the Avon Longitudinal Study of Parents and Children (ALSPAC) were analyzed. The ALSPAC study recruited 14 541 women who gave birth in the Avon Health District in the UK between April 1, 1991, and December 31, 1992. The ARIES substudy comprised 1018 mother-offspring dyads based on the availability of DNA samples profiled in 2014. Epigenetic age was estimated using DNA methylation-based epigenetic clocks (including Horvath, Hannum, GrimAge, PhenoAge, and DunedinPACE) in mothers during pregnancy and the Knight and Bohlin cord blood epigenetic clocks in newborns. Analyses were performed between October 1, 2022, and November 30, 2023. Exposures A composite measure of maternal ACEs was the primary exposure in both maternal and offspring models; as a secondary analysis, individual ACEs were measured separately. The Edinburgh Postnatal Depression Scale (EPDS) was used to investigate depression during pregnancy as an exposure. Main Outcomes and Measures Changes in epigenetic age acceleration (EAA) were investigated as the primary outcome in maternal models during pregnancy. Changes in epigenetic gestational age acceleration (GAA) were the primary outcome in offspring analyses. Linear regression analyses were used to determine the association between maternal ACEs and both outcomes. Results This study included 883 mother-child dyads. The mean (SD) maternal age at delivery was 29.8 (4.3) years. Pregnant women with higher ACE scores exhibited higher GrimAge EAA (β, 0.22 [95% CI, 0.12 to 0.33] years; P < .001). Maternal ACEs were not associated with GAA in newborns using P < .05 as a cutoff to determine statistical significance. Depression was associated with higher GrimAge EAA (β, 0.06 [95% CI, 0.02 to 0.10] years; P = .01) in mothers during pregnancy, but not in newborns, and did not mediate the association between ACEs and EAA. Conclusions and Relevance The findings of this study suggest that maternal ACEs may be associated with epigenetic aging later in life, including during pregnancy, supporting a role for maternal ACEs in offspring development and health later in life.
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Affiliation(s)
- Christian K Dye
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | | | - Haotian Wu
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Cristiane Duarte
- Division of Behavioral Medicine, New York State Psychiatric Institute, New York
| | - Catherine Monk
- Department of Psychiatry, Columbia University, New York, New York
- Division of Behavioral Medicine, New York State Psychiatric Institute, New York
- Department of Obstetrics and Gynecology, Columbia University, New York, New York
| | - Daniel W Belsky
- Department of Epidemiology, Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, New York
| | - Seonjoo Lee
- Department of Psychiatry, Columbia University, New York, New York
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York
| | - Kieran O'Donnell
- Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Pamela Scorza
- Department of Obstetrics and Gynecology, Columbia University, New York, New York
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5
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Marttila S, Rajić S, Ciantar J, Mak JKL, Junttila IS, Kummola L, Hägg S, Raitoharju E, Kananen L. Biological aging of different blood cell types. GeroScience 2024:10.1007/s11357-024-01287-w. [PMID: 39060678 DOI: 10.1007/s11357-024-01287-w] [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: 05/13/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland.
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ilkka S Junttila
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
- Northern Finland Laboratory Centre (NordLab), Oulu, Finland
- Research Unit of Biomedicine, University of Oulu, Oulu, Finland
| | - Laura Kummola
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Laura Kananen
- Gerontology Research Center, Tampere University, Tampere, Finland.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
- Faculty of Social Sciences (Health Sciences), Tampere University, Tampere, Finland.
- Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Stockholm, Sweden.
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6
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Koncevičius K, Nair A, Šveikauskaitė A, Šeštokaitė A, Kazlauskaitė A, Dulskas A, Petronis A. Epigenetic age oscillates during the day. Aging Cell 2024; 23:e14170. [PMID: 38638005 PMCID: PMC11258449 DOI: 10.1111/acel.14170] [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: 11/30/2023] [Revised: 03/18/2024] [Accepted: 03/20/2024] [Indexed: 04/20/2024] Open
Abstract
Since their introduction, epigenetic clocks have been extensively used in aging, human disease, and rejuvenation studies. In this article, we report an intriguing pattern: epigenetic age predictions display a 24-h periodicity. We tested a circadian blood sample collection using 17 epigenetic clocks addressing different aspects of aging. Thirteen clocks exhibited significant oscillations with the youngest and oldest age estimates around midnight and noon, respectively. In addition, daily oscillations were consistent with the changes of epigenetic age across different times of day observed in an independant populational dataset. While these oscillations can in part be attributed to variations in white blood cell type composition, cell count correction methods might not fully resolve the issue. Furthermore, some epigenetic clocks exhibited 24-h periodicity even in the purified fraction of neutrophils pointing at plausible contributions of intracellular epigenomic oscillations. Evidence for circadian variation in epigenetic clocks emphasizes the importance of the time-of-day for obtaining accurate estimates of epigenetic age.
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Affiliation(s)
- Karolis Koncevičius
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Akhil Nair
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoOntarioCanada
| | - Aušrinė Šveikauskaitė
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Agnė Šeštokaitė
- Laboratory for Genetic DiagnosticsNational Cancer InstituteVilniusLithuania
| | - Auksė Kazlauskaitė
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
| | - Audrius Dulskas
- Department of Abdominal and General Surgery and OncologyNational Cancer InstituteVilniusLithuania
- Faculty of MedicineVilnius UniversityVilniusLithuania
| | - Artūras Petronis
- Institute of Biotechnology, Life Sciences Center, Vilnius UniversityVilniusLithuania
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoOntarioCanada
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7
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Maunakea AK, Phankitnirundorn K, Peres R, Dye C, Juarez R, Walsh C, Slavens C, Park SL, Wilkens LR, Le Marchand L. Socioeconomic Status, Lifestyle, and DNA Methylation Age Among Racially and Ethnically Diverse Adults: NIMHD Social Epigenomics Program. JAMA Netw Open 2024; 7:e2421889. [PMID: 39073814 PMCID: PMC11287425 DOI: 10.1001/jamanetworkopen.2024.21889] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/09/2024] [Indexed: 07/30/2024] Open
Abstract
Importance Variation in DNA methylation at specific loci estimates biological age, which is associated with morbidity, mortality, and social experiences. Aging estimates known as epigenetic clocks, including the Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), were trained on data predominately from individuals of European ancestry; however, limited research has explored DunedinPACE in underrepresented populations experiencing health disparities. Objective To investigate associations of neighborhood and individual sociobehavioral factors with biological aging in a racially and ethnically diverse population. Design, Setting, and Participants This cohort study, part of the Multiethnic Cohort study conducted from May 1993 to September 1996 to examine racial and ethnic disparities in chronic diseases, integrated biospecimen and self-reported data collected between April 2004 and November 2005 from healthy Hawaii residents aged 45 to 76 years. These participants self-identified as of Japanese American, Native Hawaiian, or White racial and ethnic background. Data were analyzed from January 2022 to May 2024. Main Outcomes and Measures DNA methylation data were generated from monocytes enriched from cryopreserved lymphocytes and used to derive DunedinPACE scores from November 2017 to June 2021. Neighborhood social economic status (NSES) was estimated from 1990 US Census Bureau data to include factors such as educational level, occupation, and income. Individual-level factors analyzed included educational level, body mass index (BMI), physical activity (PA), and diet quality measured by the Healthy Eating Index (HEI). Linear regression analysis of DunedinPACE scores was used to examine their associations with NSES and sociobehavioral variables. Results A total of 376 participants were included (113 [30.1%] Japanese American, 144 [38.3%] Native Hawaiian, and 119 [31.6%] White; 189 [50.3%] were female). Mean (SE) age was 57.81 (0.38) years. Overall, mean (SE) DunedinPACE scores were significantly higher among females than among males (1.28 [0.01] vs 1.25 [0.01]; P = .005); correlated negatively with NSES (R = -0.09; P = .08), HEI (R = -0.11; P = .03), and educational attainment (R = -0.15; P = .003) and positively with BMI (R = 0.31; P < .001); and varied by race and ethnicity. Native Hawaiian participants exhibited a higher mean (SE) DunedinPACE score (1.31 [0.01]) compared with Japanese American (1.25 [0.01]; P < .001) or White (1.22 [0.01]; P < .001) participants. Controlling for age, sex, HEI, BMI, and NSES, linear regression analyses revealed a negative association between educational level and DunedinPACE score among Japanese American (β, -0.005 [95% CI, -0.013 to 0.002]; P = .03) and Native Hawaiian (β, -0.003 [95% CI, -0.011 to 0.005]; P = .08) participants, yet this association was positive among White participants (β, 0.007; 95% CI, -0.001 to 0.015; P = .09). Moderate to vigorous PA was associated with lower DunedinPACE scores only among Native Hawaiian participants (β, -0.006; 95% CI, -0.011 to -0.001; P = .005), independent of NSES. Conclusions and Relevance In this study of a racially and ethnically diverse sample of 376 adults, low NSES was associated with a higher rate of biological aging measured by DunedinPACE score, yet individual-level factors such as educational level and physical activity affected this association, which varied by race and ethnicity. These findings support sociobehavioral interventions in addressing health inequities.
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Affiliation(s)
- Alika K. Maunakea
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Krit Phankitnirundorn
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Rafael Peres
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - Christian Dye
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Ruben Juarez
- Department of Economics, University of Hawaii at Manoa, Honolulu
| | - Catherine Walsh
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Connor Slavens
- Department of Anatomy, Biochemistry, and Physiology, University of Hawaii at Manoa, John A. Burns School of Medicine, Honolulu
| | - S. Lani Park
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Lynne R. Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
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8
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Großbach A, Suderman MJ, Hüls A, Lussier AA, Smith AD, Walton E, Dunn EC, Simpkin AJ. Maximizing Insights from Longitudinal Epigenetic Age Data: Simulations, Applications, and Practical Guidance. RESEARCH SQUARE 2024:rs.3.rs-4482915. [PMID: 38947070 PMCID: PMC11213208 DOI: 10.21203/rs.3.rs-4482915/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: 07/02/2024]
Abstract
Background Epigenetic Age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional - using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (i) their choice of model; (ii) the primary outcome (EA vs. EAA); and (iii) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA. Results Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered an accelerated EA rate in males and an advanced EA that decelerates over time in children with higher birthweight. Conclusion Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.
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Affiliation(s)
- Anna Großbach
- School of Mathematical and Statistical Sciences, University of Galway, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Ireland
| | - Matthew J. Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Alexandre A. Lussier
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Andrew D.A.C. Smith
- Mathematics and Statistics Research Group, University of the West of England, Bristol, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Erin C. Dunn
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Andrew J. Simpkin
- School of Mathematical and Statistical Sciences, University of Galway, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Ireland
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9
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Yasumizu Y, Hagiwara M, Umezu Y, Fuji H, Iwaisako K, Asagiri M, Uemoto S, Nakamura Y, Thul S, Ueyama A, Yokoi K, Tanemura A, Nose Y, Saito T, Wada H, Kakuda M, Kohara M, Nojima S, Morii E, Doki Y, Sakaguchi S, Ohkura N. Neural-net-based cell deconvolution from DNA methylation reveals tumor microenvironment associated with cancer prognosis. NAR Cancer 2024; 6:zcae022. [PMID: 38751935 PMCID: PMC11094754 DOI: 10.1093/narcan/zcae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/18/2024] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
DNA methylation is a pivotal epigenetic modification that defines cellular identity. While cell deconvolution utilizing this information is considered useful for clinical practice, current methods for deconvolution are limited in their accuracy and resolution. In this study, we collected DNA methylation data from 945 human samples derived from various tissues and tumor-infiltrating immune cells and trained a neural network model with them. The model, termed MEnet, predicted abundance of cell population together with the detailed immune cell status from bulk DNA methylation data, and showed consistency to those of flow cytometry and histochemistry. MEnet was superior to the existing methods in the accuracy, speed, and detectable cell diversity, and could be applicable for peripheral blood, tumors, cell-free DNA, and formalin-fixed paraffin-embedded sections. Furthermore, by applying MEnet to 72 intrahepatic cholangiocarcinoma samples, we identified immune cell profiles associated with cancer prognosis. We believe that cell deconvolution by MEnet has the potential for use in clinical settings.
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Affiliation(s)
- Yoshiaki Yasumizu
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, Osaka, Japan
| | - Masaki Hagiwara
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
- Department of Basic Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
- Pharmaceutical Research Division, Shionogi & Co., Ltd., Toyonaka, Osaka, Japan
| | - Yuto Umezu
- Faculty of Medicine, Osaka University, Suita, Osaka, Japan
| | - Hiroaki Fuji
- Department of Hepato-Biliary-Pancreatic Surgery, Hyogo Medical University, Nishinomiya, Hyogo, Japan
- Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
| | - Keiko Iwaisako
- Division of Hepato-Biliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Kyoto, Japan
- Faculty of Life and Medical Sciences, Doshisha University, Kyotanabe, Kyoto, Japan
| | - Masataka Asagiri
- Department of Pharmacology, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi, Japan
| | - Shinji Uemoto
- Shiga University Medical Science, Otsu, Shiga, Japan
| | - Yamami Nakamura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
| | - Sophia Thul
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
| | - Azumi Ueyama
- Pharmaceutical Research Division, Shionogi & Co., Ltd., Toyonaka, Osaka, Japan
- Department of Clinical Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Kazunori Yokoi
- Department of Dermatology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Atsushi Tanemura
- Department of Dermatology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Yohei Nose
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Takuro Saito
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Hisashi Wada
- Department of Clinical Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Mamoru Kakuda
- Department of Obstetrics and Gynecology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Masaharu Kohara
- Department of Pathology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Satoshi Nojima
- Department of Pathology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Eiichi Morii
- Department of Pathology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Yuichiro Doki
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Shimon Sakaguchi
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
- Department of Experimental Immunology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Kyoto, Japan
| | - Naganari Ohkura
- Department of Experimental Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan
- Department of Basic Research in Tumor Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
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10
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Mak JKL, Skovgaard AC, Nygaard M, Kananen L, Reynolds CA, Wang Y, Kuja‐Halkola R, Karlsson IK, Pedersen NL, Hägg S, Soerensen M, Jylhävä J. Epigenome-wide analysis of frailty: Results from two European twin cohorts. Aging Cell 2024; 23:e14135. [PMID: 38414347 PMCID: PMC11166364 DOI: 10.1111/acel.14135] [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: 10/13/2023] [Revised: 02/11/2024] [Accepted: 02/17/2024] [Indexed: 02/29/2024] Open
Abstract
Epigenetics plays an important role in the aging process, but it is unclear whether epigenetic factors also influence frailty, an age-related state of physiological decline. In this study, we performed a meta-analysis of epigenome-wide association studies in four samples drawn from the Swedish Adoption/Twin Study of Aging (SATSA) and the Longitudinal Study of Aging Danish Twins (LSADT) to explore the association between DNA methylation and frailty. Frailty was defined using the frailty index (FI), and DNA methylation levels were measured in whole blood using Illumina's Infinium HumanMethylation450K and MethylationEPIC arrays. In the meta-analysis consisting of a total of 829 participants, we identified 589 CpG sites that were statistically significantly associated with either the continuous or categorical FI (false discovery rate <0.05). Many of these CpGs have previously been associated with age and age-related diseases. The identified sites were also largely directionally consistent in a longitudinal analysis using mixed-effects models in SATSA, where the participants were followed up to a maximum of 20 years. Moreover, we identified three differentially methylated regions within the MGRN1, MIR596, and TAPBP genes that have been linked to neuronal aging, tumor growth, and immune functions. Furthermore, our meta-analysis results replicated 34 of the 77 previously reported frailty-associated CpGs at p < 0.05. In conclusion, our findings demonstrate robust associations between frailty and DNA methylation levels in 589 novel CpGs, previously unidentified for frailty, and strengthen the role of neuronal/brain pathways in frailty.
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Affiliation(s)
- Jonathan K. L. Mak
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of MedicineThe University of Hong KongHong KongChina
| | - Asmus Cosmos Skovgaard
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public HealthUniversity of Southern DenmarkOdense MDenmark
| | - Marianne Nygaard
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public HealthUniversity of Southern DenmarkOdense MDenmark
| | - Laura Kananen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
| | - Chandra A. Reynolds
- Institute for Behavioral Genetics, University of ColoradoBoulderColoradoUSA
- Department of PsychologyUniversity of CaliforniaRiversideCaliforniaUSA
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of Clinical Sciences, Danderyd HospitalKarolinska InstitutetStockholmSweden
| | - Ralf Kuja‐Halkola
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Ida K. Karlsson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Mette Soerensen
- The Danish Twin Registry and Epidemiology, Biostatistics and Biodemography, Department of Public HealthUniversity of Southern DenmarkOdense MDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC)University of TampereTampereFinland
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11
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Sasaki A, Takeshima H, Yamashita S, Ichita C, Kawachi J, Naito W, Ohashi Y, Takeuchi C, Fukuda M, Furuichi Y, Yamamichi N, Ando T, Kobara H, Kotera T, Itoi T, Sumida C, Hamada A, Koizumi K, Ushijima T. Severe induction of aberrant DNA methylation by nodular gastritis in adults. J Gastroenterol 2024; 59:442-456. [PMID: 38499886 DOI: 10.1007/s00535-024-02094-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/29/2024] [Indexed: 03/20/2024]
Abstract
BACKGROUND Nodular gastritis (NG) is characterized by marked antral lymphoid follicle formation, and is a strong risk factor for diffuse-type gastric cancer in adults. However, it is unknown whether aberrant DNA methylation, which is induced by atrophic gastritis (AG) and is a risk for gastric cancer, is induced by NG. Here, we analyzed methylation induction by NG. METHODS Gastric mucosal samples were obtained from non-cancerous antral tissues of 16 NG and 20 AG patients with gastric cancer and 5 NG and 6 AG patients without, all age- and gender-matched. Genome-wide methylation analysis and expression analysis were conducted by a BeadChip array and RNA-sequencing, respectively. RESULTS Clustering analysis of non-cancerous antral tissues of NG and AG patients with gastric cancer was conducted using methylation levels of 585 promoter CpG islands (CGIs) of methylation-resistant genes, and a large fraction of NG samples formed a cluster with strong methylation induction. Promoter CGIs of CDH1 and DAPK1 tumor-suppressor genes were more methylated in NG than in AG. Notably, methylation levels of these genes were also higher in the antrum of NG patients without cancer. Genes related to lymphoid follicle formation, such as CXCL13/CXCR5 and CXCL12/CXCR4, had higher expression in NG, and genes involved in DNA demethylation TET2 and IDH1, had only half the expression in NG. CONCLUSIONS Severe aberrant methylation, involving multiple tumor-suppressor genes, was induced in the gastric antrum and body of patients with NG, in accordance with their high gastric cancer risk.
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Affiliation(s)
- Akiko Sasaki
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Gastroenterology Medicine Center, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Hideyuki Takeshima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Satoshi Yamashita
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Chikamasa Ichita
- Gastroenterology Medicine Center, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Jun Kawachi
- Department of General Surgery, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Wataru Naito
- Department of Diagnostic Pathology, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Yui Ohashi
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Chihiro Takeuchi
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Masahide Fukuda
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Gastroenterology, Faculty of Medicine, Oita University, Oita, Japan
| | - Yumi Furuichi
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
- Department of Gastroenterological Surgery, Faculty of Medicine, Kagawa University, Kagawa, Japan
| | - Nobutake Yamamichi
- Center for Epidemiology and Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takayuki Ando
- Third Department of Internal Medicine, University of Toyama, Toyama, Japan
| | - Hideki Kobara
- Department of Gastroenterology and Neurology, Kagawa University, Kagawa, Japan
| | - Tohru Kotera
- Department of Medical Examination, Uji-Tokushukai Medical Center, Kyoto, Japan
| | - Takao Itoi
- Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan
| | - Chihiro Sumida
- Gastroenterology Medicine Center, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Akinobu Hamada
- Division of Molecular Pharmacology, National Cancer Center Research Institute, Tokyo, Japan
| | - Kazuya Koizumi
- Gastroenterology Medicine Center, Shonan Kamakura General Hospital, Kanagawa, Japan
| | - Toshikazu Ushijima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan.
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan.
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12
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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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13
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Yap CX, Vo DD, Heffel MG, Bhattacharya A, Wen C, Yang Y, Kemper KE, Zeng J, Zheng Z, Zhu Z, Hannon E, Vellame DS, Franklin A, Caggiano C, Wamsley B, Geschwind DH, Zaitlen N, Gusev A, Pasaniuc B, Mill J, Luo C, Gandal MJ. Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics. SCIENCE ADVANCES 2024; 10:eadn7655. [PMID: 38781333 PMCID: PMC11114225 DOI: 10.1126/sciadv.adn7655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 03/14/2024] [Indexed: 05/25/2024]
Abstract
Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.
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Affiliation(s)
- Chloe X. Yap
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel D. Vo
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew G. Heffel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Institute for Data Science in Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cindy Wen
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yuanhao Yang
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Kathryn E. Kemper
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- The National Centre for Register-based Research, Aarhus University, Denmark
| | - Eilis Hannon
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Dorothea Seiler Vellame
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Alice Franklin
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Christa Caggiano
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Brie Wamsley
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H. Geschwind
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham & Women’s Hospital, Boston, MA, USA
- Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jonathan Mill
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Chongyuan Luo
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Michael J. Gandal
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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14
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Rendek T, Pos O, Duranova T, Saade R, Budis J, Repiska V, Szemes T. Current Challenges of Methylation-Based Liquid Biopsies in Cancer Diagnostics. Cancers (Basel) 2024; 16:2001. [PMID: 38893121 PMCID: PMC11171112 DOI: 10.3390/cancers16112001] [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: 04/23/2024] [Revised: 05/13/2024] [Accepted: 05/16/2024] [Indexed: 06/21/2024] Open
Abstract
In current clinical practice, effective cancer testing and screening paradigms are limited to specific types of cancer, exhibiting varying efficiency, acceptance, and adherence. Cell-free DNA (cfDNA) methylation profiling holds promise in providing information about the presence of malignity regardless of its type and location while leveraging blood-based liquid biopsies as a method to obtain analytical samples. However, technical difficulties, costs and challenges resulting from biological variations, tumor heterogeneity, and exogenous factors persist. This method exploits the mechanisms behind cfDNA release but faces issues like fragmentation, low concentrations, and high background noise. This review explores cfDNA methylation's origins, means of detection, and profiling for cancer diagnostics. The critical evaluation of currently available multi-cancer early detection methods (MCEDs) as well as tests targeting single genes, emphasizing their potential and limits to refine strategies for early cancer detection, are explained. The current methodology limitations, workflows, comparisons of clinically approved liquid biopsy-based methylation tests for cancer, their utilization in companion diagnostics as well as the biological limitations of the epigenetics approach are discussed, aiming to help healthcare providers as well as researchers to orient themselves in this increasingly complex and evolving field of diagnostics.
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Affiliation(s)
- Tomas Rendek
- Institute of Medical Biology, Genetics and Clinical Genetics, Faculty of Medicine, Comenius University, 811 08 Bratislava, Slovakia;
| | - Ondrej Pos
- Geneton Ltd., 841 04 Bratislava, Slovakia; (O.P.); (J.B.); (T.S.)
- Comenius University Science Park, 841 04 Bratislava, Slovakia;
| | | | - Rami Saade
- 2nd Department of Gynaecology and Obstetrics, Faculty of Medicine, Comenius University, 811 08 Bratislava, Slovakia;
| | - Jaroslav Budis
- Geneton Ltd., 841 04 Bratislava, Slovakia; (O.P.); (J.B.); (T.S.)
- Comenius University Science Park, 841 04 Bratislava, Slovakia;
| | - Vanda Repiska
- Institute of Medical Biology, Genetics and Clinical Genetics, Faculty of Medicine, Comenius University, 811 08 Bratislava, Slovakia;
| | - Tomas Szemes
- Geneton Ltd., 841 04 Bratislava, Slovakia; (O.P.); (J.B.); (T.S.)
- Comenius University Science Park, 841 04 Bratislava, Slovakia;
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15
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Biskup E, Lopacinska-Jørgensen J, Vestergaard LK, Høgdall E. Validating reference-based algorithms to determine cell-type heterogeneity in ovarian cancer DNA methylation studies. Sci Rep 2024; 14:11048. [PMID: 38745057 PMCID: PMC11094148 DOI: 10.1038/s41598-024-61857-y] [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: 02/16/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024] Open
Abstract
Information about cell composition in tissue samples is crucial for biomarker discovery and prognosis. Specifically, cancer tissue samples present challenges in deconvolution studies due to mutations and genetic rearrangements. Here, we optimized a robust, DNA methylation-based protocol, to be used for deconvolution of ovarian cancer samples. We compared several state-of-the-art methods (HEpiDISH, MethylCIBERSORT and ARIC) and validated the proposed protocol in an in-silico mixture and in an external dataset containing samples from ovarian cancer patients and controls. The deconvolution protocol we eventually implemented is based on MethylCIBERSORT. Comparing deconvolution methods, we paid close attention to the role of a reference panel. We postulate that a possibly high number of samples (in our case: 247) should be used when building a reference panel to ensure robustness and to compensate for biological and technical variation between samples. Subsequently, we tested the performance of the validated protocol in our own study cohort, consisting of 72 patients with malignant and benign ovarian disease as well as in five external cohorts. In conclusion, we refined and validated a reference-based algorithm to determine cell type composition of ovarian cancer tissue samples to be used in cancer biology studies in larger cohorts.
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Affiliation(s)
- Edyta Biskup
- Department of Pathology, Copenhagen University Hospital, Herlev, Denmark.
| | | | | | - Estrid Høgdall
- Department of Pathology, Copenhagen University Hospital, Herlev, Denmark
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16
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Semancik CS, Zhao N, Koestler DC, Boerwinkle E, Bressler J, Buchsbaum RJ, Kelsey KT, Platz EA, Michaud DS. DNA Methylation-Derived Immune Cell Proportions and Cancer Risk, Including Lung Cancer, in Black Participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.09.24307118. [PMID: 38766207 PMCID: PMC11100922 DOI: 10.1101/2024.05.09.24307118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Prior cohort studies assessing cancer risk based on immune cell subtype profiles have predominantly focused on White populations. This limitation obscures vital insights into how cancer risk varies across race. Immune cell subtype proportions were estimated using deconvolution based on leukocyte DNA methylation markers from blood samples collected at baseline on participants without cancer in the Atherosclerosis Risk in Communities (ARIC) Study. Over a mean of 17.5 years of follow-up, 668 incident cancers were diagnosed in 2,467 Black participants. Cox proportional hazards regression was used to examine immune cell subtype proportions and overall cancer incidence and site-specific incidence (lung, breast, and prostate cancers). Higher T regulatory cell proportions were associated with statistically significantly higher lung cancer risk (hazard ratio = 1.22, 95% confidence interval = 1.06-1.41 per percent increase). Increased memory B cell proportions were associated with significantly higher risk of prostate cancer (1.17, 1.04-1.33) and all cancers (1.13, 1.05-1.22). Increased CD8+ naïve cell proportions were associated with significantly lower risk of all cancers in participants ≥55 years (0.91, 0.83-0.98). Other immune cell subtypes did not display statistically significant associations with cancer risk. These results in Black participants align closely with prior findings in largely White populations. Findings from this study could help identify those at high cancer risk and outline risk stratifying to target patients for cancer screening, prevention, and other interventions. Further studies should assess these relationships in other cancer types, better elucidate the interplay of B cells in cancer risk, and identify biomarkers for personalized risk stratification.
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Affiliation(s)
- Christopher S. Semancik
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C. Koestler
- The University of Kansas Cancer Center, Kansas City, KS, USA
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Karl T. Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Dominique S. Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
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17
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Lee MK, Azizgolshani N, Zhang Z, Perreard L, Kolling FW, Nguyen LN, Zanazzi GJ, Salas LA, Christensen BC. Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors. Nat Commun 2024; 15:3635. [PMID: 38688903 PMCID: PMC11061294 DOI: 10.1038/s41467-024-47943-9] [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] [Received: 02/18/2023] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.
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Affiliation(s)
- Min Kyung Lee
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Nasim Azizgolshani
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Surgery, Columbia University Medical Center, New York, NY, USA
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Laurent Perreard
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Fred W Kolling
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lananh N Nguyen
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - George J Zanazzi
- Dartmouth Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Pathology and Laboratory Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
- Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
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18
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Aguilar-Lacasaña S, Fontes Marques I, de Castro M, Dadvand P, Escribà X, Fossati S, González JR, Nieuwenhuijsen M, Alfano R, Annesi-Maesano I, Brescianini S, Burrows K, Calas L, Elhakeem A, Heude B, Hough A, Isaevska E, W V Jaddoe V, Lawlor DA, Monaghan G, Nawrot T, Plusquin M, Richiardi L, Watmuff A, Yang TC, Vrijheid M, F Felix J, Bustamante M. Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study. ENVIRONMENT INTERNATIONAL 2024; 188:108684. [PMID: 38776651 DOI: 10.1016/j.envint.2024.108684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/21/2024] [Accepted: 04/21/2024] [Indexed: 05/25/2024]
Abstract
Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.
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Affiliation(s)
- Sofia Aguilar-Lacasaña
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain; Universitat de Barcelona, Barcelona, Spain.
| | - Irene Fontes Marques
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Montserrat de Castro
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Payam Dadvand
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Xavier Escribà
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Serena Fossati
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Juan R González
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Rossella Alfano
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Isabella Annesi-Maesano
- Desbrest Institute of Epidemiology and Public Health (IDESP), Montpellier University and Inserm, Montpellier, Service des Maladies Allergiques et Respiratoires, CHU, Montpellier, France
| | - Sonia Brescianini
- Centre for Behavioural Science and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Kimberley Burrows
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lucinda Calas
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France
| | - Ahmed Elhakeem
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Barbara Heude
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France
| | - Amy Hough
- Born in Bradford, Wolfson Centre for Applied Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Elena Isaevska
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Sciences, University of Turin, CPO-Piemonte, Turin, Italy
| | - Vincent W V Jaddoe
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Genevieve Monaghan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tim Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium; Department of Public Health, Leuven University (KU Leuven), Leuven, Belgium
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin, CPO-Piemonte, Turin, Italy
| | - Aidan Watmuff
- Born in Bradford, Wolfson Centre for Applied Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Tiffany C Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, UK
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
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19
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Webster AP, Ecker S, Moghul I, Liu X, Dhami P, Marzi S, Paul DS, Kuxhausen M, Lee SJ, Spellman SR, Wang T, Feber A, Rakyan V, Peggs KS, Beck S. Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation. Front Genet 2024; 15:1242636. [PMID: 38633407 PMCID: PMC11021570 DOI: 10.3389/fgene.2024.1242636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 03/04/2024] [Indexed: 04/19/2024] Open
Abstract
Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.
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Affiliation(s)
- Amy P. Webster
- UCL Cancer Institute, University College London, London, United Kindom
- The University of Exeter Medical School, University of Exeter, Exeter, United Kindom
| | - Simone Ecker
- UCL Cancer Institute, University College London, London, United Kindom
| | - Ismail Moghul
- UCL Cancer Institute, University College London, London, United Kindom
| | - Xiaohong Liu
- UCL Cancer Institute, University College London, London, United Kindom
| | - Pawan Dhami
- UCL Cancer Institute, University College London, London, United Kindom
- NIHR Biomedical Research Centre, Guy’s Hospital London, London, United Kindom
| | - Sarah Marzi
- Blizard Institute, Barts and the London School of Medicine and Dentistry, London, United Kindom
| | - Dirk S. Paul
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kindom
| | - Michelle Kuxhausen
- Center for International Blood and Marrow Transplant Research, NMDP, Minneapolis, United Kindom
| | - Stephanie J. Lee
- Center for International Blood and Marrow Transplant Research, Medical College of Wisconsin, Milwaukee, United Kindom
- Fred Hutchinson Cancer Research Center, University of Washington, Seattle, United Kindom
| | - Stephen R. Spellman
- Center for International Blood and Marrow Transplant Research, NMDP, Minneapolis, United Kindom
| | - Tao Wang
- Center for International Blood and Marrow Transplant Research, Medical College of Wisconsin, Milwaukee, United Kindom
- Division of Biostatistics, Medical College of Wisconsin, Milwaukee, United Kindom
| | - Andrew Feber
- UCL Cancer Institute, University College London, London, United Kindom
- The Institute of Cancer Research, London, United Kindom
| | - Vardhman Rakyan
- Blizard Institute, Barts and the London School of Medicine and Dentistry, London, United Kindom
| | - Karl S. Peggs
- UCL Cancer Institute, University College London, London, United Kindom
- Department of Haematology, University College London, London, United Kindom
| | - Stephan Beck
- UCL Cancer Institute, University College London, London, United Kindom
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20
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Yurkovich JT, Evans SJ, Rappaport N, Boore JL, Lovejoy JC, Price ND, Hood LE. The transition from genomics to phenomics in personalized population health. Nat Rev Genet 2024; 25:286-302. [PMID: 38093095 DOI: 10.1038/s41576-023-00674-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 03/21/2024]
Abstract
Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.
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Affiliation(s)
- James T Yurkovich
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
| | - Simon J Evans
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Noa Rappaport
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Jeffrey L Boore
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Jennifer C Lovejoy
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Nathan D Price
- Institute for Systems Biology, Seattle, WA, USA
- Thorne HealthTech, New York, NY, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Leroy E Hood
- Phenome Health, Seattle, WA, USA.
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA.
- Institute for Systems Biology, Seattle, WA, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA.
- Department of Immunology, University of Washington, Seattle, WA, USA.
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21
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Ferro dos Santos MR, Giuili E, De Koker A, Everaert C, De Preter K. Computational deconvolution of DNA methylation data from mixed DNA samples. Brief Bioinform 2024; 25:bbae234. [PMID: 38762790 PMCID: PMC11102637 DOI: 10.1093/bib/bbae234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/30/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024] Open
Abstract
In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.
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Affiliation(s)
- Maísa R Ferro dos Santos
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Edoardo Giuili
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Andries De Koker
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Celine Everaert
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Katleen De Preter
- VIB-UGent Center for Medical Biotechnology (CMB), Technologiepark-Zwijnaarde 75, 9052 Zwijnaarde, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
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22
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Luo C, Pi X, Zhang Q, Hu N, Xiao Y, Sweeney JA, Bishop JR, Gong Q, Xie D, Lui S. A subtype of schizophrenia patients with altered methylation level of genes related to immune cell activity. Psychol Med 2024:1-9. [PMID: 38505948 DOI: 10.1017/s0033291724000667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
BACKGROUND Epigenetic changes are plausible molecular sources of clinical heterogeneity in schizophrenia. A subgroup of schizophrenia patients with elevated inflammatory or immune-dysregulation has been reported by previous studies. However, little is known about epigenetic changes in genes related to immune activation in never-treated first-episode patients with schizophrenia (FES) and its consistency with that in treated long-term ill (LTS) patients. METHODS In this study, epigenome-wide profiling with a DNA methylation array was applied using blood samples of both FES and LTS patients, as well as their corresponding healthy controls. Non-negative matrix factorization (NMF) and k -means clustering were performed to parse heterogeneity of schizophrenia, and the consistency of subtyping results from two cohorts. was tested. RESULTS This study identified a subtype of patients in FES participants (47.5%) that exhibited widespread methylation level alterations of genes enriched in immune cell activity and a significantly higher proportion of neutrophils. This clustering of FES patients was validated in LTS patients, with high correspondence in epigenetic and clinical features across two cohorts. CONCLUSIONS In summary, this study demonstrated a subtype of schizophrenia patients across both FES and LTS cohorts, defined by widespread alterations in methylation profile of genes related to immune function and distinguishing clinical features. This finding illustrates the promise of novel treatment strategies targeting immune dysregulation for a subpopulation of schizophrenia patients.
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Affiliation(s)
- Chunyan Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
| | - Xuenan Pi
- Laboratory of Omics Technology and Bioinformatics, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Qi Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
| | - Na Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati OH 45219, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
| | - Dan Xie
- Laboratory of Omics Technology and Bioinformatics, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China
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23
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Malta TM, Sabedot TS, Morosini NS, Datta I, Garofano L, Vallentgoed W, Varn FS, Aldape K, D'Angelo F, Bakas S, Barnholtz-Sloan JS, Gan HK, Hasanain M, Hau AC, Johnson KC, Cazacu S, deCarvalho AC, Khasraw M, Kocakavuk E, Kouwenhoven MC, Migliozzi S, Niclou SP, Niers JM, Ormond DR, Paek SH, Reifenberger G, Sillevis Smitt PA, Smits M, Stead LF, van den Bent MJ, Van Meir EG, Walenkamp A, Weiss T, Weller M, Westerman BA, Ylstra B, Wesseling P, Lasorella A, French PJ, Poisson LM, Verhaak RG, Iavarone A, Noushmehr H. The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen. Cancer Res 2024; 84:741-756. [PMID: 38117484 PMCID: PMC10911804 DOI: 10.1158/0008-5472.can-23-2093] [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: 07/14/2023] [Revised: 09/15/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023]
Abstract
Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype. SIGNIFICANCE Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.
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Affiliation(s)
- Tathiane M. Malta
- School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Thais S. Sabedot
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | | | - Indrani Datta
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Luciano Garofano
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Wies Vallentgoed
- Neurology Department, The Brain Tumour Center, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Frederick S. Varn
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | | | - Fulvio D'Angelo
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Hui K. Gan
- Olivia Newton-John Cancer Research Institute, Austin Health, Heidelberg, Melbourne, Australia
| | - Mohammad Hasanain
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | | | - Kevin C. Johnson
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
| | - Simona Cazacu
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Ana C. deCarvalho
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | | | - Emre Kocakavuk
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
- Department of Hematology and Stem Cell Transplantation, West German Cancer Center (WTZ), National Center for Tumor Diseases (NCT) West, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Mathilde C.M. Kouwenhoven
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Simona Migliozzi
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | | | - Johanna M. Niers
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - D. Ryan Ormond
- University of Colorado School of Medicine, Department of Neurosurgery, Aurora, Colorado
| | - Sun Ha Paek
- Department of Neurosurgery, Cancer Research Institute, Hypoxia Ischemia Disease Institute, Seoul National University, Seoul, Republic of Korea (South)
| | - Guido Reifenberger
- Institute of Neuropathology, Heinrich Heine University, Dusseldorf, Germany
| | - Peter A. Sillevis Smitt
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- The Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Lucy F. Stead
- Leeds Institute of Medical Research, University of Leeds, Leeds, United Kingdom
| | - Martin J. van den Bent
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- The Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Erwin G. Van Meir
- Department of Neurosurgery and O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama
| | | | - Tobias Weiss
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Bart A. Westerman
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Bauke Ylstra
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Pieter Wesseling
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, Amsterdam, the Netherlands
- Laboratory for Childhood Cancer Pathology, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Anna Lasorella
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, Miami, Florida
| | - Pim J. French
- Neurology Department, The Brain Tumour Center, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Laila M. Poisson
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Roel G.W. Verhaak
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
- Department of Neurosurgery, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Antonio Iavarone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida
| | - Houtan Noushmehr
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
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24
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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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25
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Bozack AK, Rifas-Shiman SL, Baccarelli AA, Wright RO, Gold DR, Oken E, Hivert MF, Cardenas A. Associations of prenatal one-carbon metabolism nutrients and metals with epigenetic aging biomarkers at birth and in childhood in a US cohort. Aging (Albany NY) 2024; 16:3107-3136. [PMID: 38412256 PMCID: PMC10929819 DOI: 10.18632/aging.205602] [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: 10/31/2023] [Accepted: 01/29/2024] [Indexed: 02/29/2024]
Abstract
Epigenetic gestational age acceleration (EGAA) at birth and epigenetic age acceleration (EAA) in childhood may be biomarkers of the intrauterine environment. We investigated the extent to which first-trimester folate, B12, 5 essential, and 7 non-essential metals in maternal circulation are associated with EGAA and EAA in early life. Bohlin EGAA and Horvath pan-tissue and skin and blood EAA were calculated using DNA methylation measured in cord blood (N=351) and mid-childhood blood (N=326; median age = 7.7 years) in the Project Viva pre-birth cohort. A one standard deviation increase in individual essential metals (copper, manganese, and zinc) was associated with 0.94-1.2 weeks lower Horvath EAA at birth, and patterns of exposures identified by exploratory factor analysis suggested that a common source of essential metals was associated with Horvath EAA. We also observed evidence nonlinear associations of zinc with Bohlin EGAA, magnesium and lead with Horvath EAA, and cesium with skin and blood EAA at birth. Overall, associations at birth did not persist in mid-childhood; however, arsenic was associated with greater EAA at birth and in childhood. Prenatal metals, including essential metals and arsenic, are associated with epigenetic aging in early life, which might be associated with future health.
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Affiliation(s)
- Anne K. Bozack
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sheryl L. Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, NY 10032, USA
| | - Robert O. Wright
- Department of Environmental Medicine and Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
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26
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Wani A, Katrinli S, Zhao X, Daskalakis N, Zannas A, Aiello A, Baker D, Boks M, Brick L, Chen CY, Dalvie S, Fortier C, Geuze E, Hayes J, Kessler R, King A, Koen N, Liberzon I, Lori A, Luykx J, Maihofer A, Milberg W, Miller M, Mufford M, Nugent N, Rauch S, Ressler K, Risbrough V, Rutten B, Stein D, Stein M, Ursano R, Verfaellie M, Ware E, Wildman D, Wolf E, Nievergelt C, Logue M, Smith A, Uddin M, Vermetten E, Vinkers C. Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts. RESEARCH SQUARE 2024:rs.3.rs-3952163. [PMID: 38410438 PMCID: PMC10896387 DOI: 10.21203/rs.3.rs-3952163/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: 02/28/2024]
Abstract
Background Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.
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Affiliation(s)
- Agaz Wani
- University of South Florida College of Public Health, Genomics Program
| | - Seyma Katrinli
- Emory University Department of Gynecology and Obstetrics
| | - Xiang Zhao
- Boston University School of Public Health
| | | | - Anthony Zannas
- University of North Carolina at Chapel Hill, Carolina Stress Initiative
| | - Allison Aiello
- Robert N Butler Columbia Aging Center, Columbia University
| | - Dewleen Baker
- University of California San Diego, Department of Psychiatry
| | - Marco Boks
- Brain Center University Medical Center Utrecht, Department of Psychiatry
| | | | | | | | | | - Elbert Geuze
- Netherlands Ministry of Defence, Brain Research and Innovation Centre
| | | | - Ronald Kessler
- Harvard Medical School, Department of Health Care Policy
| | - Anthony King
- The Ohio State University, College of Medicine, Institute for Behavioral Medicine Research
| | - Nastassja Koen
- University of Cape Town, Department of Psychiatry & Mental Health
| | - Israel Liberzon
- Texas A&M University College of Medicine, Department of Psychiatry and Behavioral Sciences
| | - Adriana Lori
- Emory University, Department of Psychiatry and Behavioral Sciences
| | - Jurjen Luykx
- UMC Utrecht Brain Center Rudolf Magnus, Department of Psychiatry
| | | | | | - Mark Miller
- Boston University School of Medicine, Psychiatry
| | | | - Nicole Nugent
- Alpert Brown Medical School, Department of Emergency Medicine
| | - Sheila Rauch
- Emory University, Department of Psychiatry & Behavioral Sciences
| | | | | | - Bart Rutten
- Maastricht Universitair Medisch Centrum, School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology
| | - Dan Stein
- University of Cape Town, Department of Psychiatry & Mental Health
| | - Murrary Stein
- University of California San Diego, Department of Psychiatry
| | - Robert Ursano
- Uniformed Services University, Department of Psychiatry
| | | | - Erin Ware
- University of Michigan, Population Studies Center
| | - Derek Wildman
- University of South Florida College of Public Health, Genomics Program
| | - Erika Wolf
- VA Boston Healthcare System, National Center for PTSD
| | | | - Mark Logue
- Boston University School of Public Health
| | - Alicia Smith
- Emory University Department of Gynecology and Obstetrics
| | - Monica Uddin
- University of South Florida College of Public Health, Genomics Program
| | - Eric Vermetten
- Leiden University Medical Center, Department of Psychiatry
| | - Christiaan Vinkers
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program
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27
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Choudhary P, Monasso GS, Karhunen V, Ronkainen J, Mancano G, Howe CG, Niu Z, Zeng X, Guan W, Dou J, Feinberg JI, Mordaunt C, Pesce G, Baïz N, Alfano R, Martens DS, Wang C, Isaevska E, Keikkala E, Mustaniemi S, Thio CHL, Fraszczyk E, Tobi EW, Starling AP, Cosin-Tomas M, Urquiza J, Röder S, Hoang TT, Page C, Jima DD, House JS, Maguire RL, Ott R, Pawlow X, Sirignano L, Zillich L, Malmberg A, Rauschert S, Melton P, Gong T, Karlsson R, Fore R, Perng W, Laubach ZM, Czamara D, Sharp G, Breton CV, Schisterman E, Yeung E, Mumford SL, Fallin MD, LaSalle JM, Schmidt RJ, Bakulski KM, Annesi-Maesano I, Heude B, Nawrot TS, Plusquin M, Ghantous A, Herceg Z, Nisticò L, Vafeiadi M, Kogevinas M, Vääräsmäki M, Kajantie E, Snieder H, Corpeleijn E, Steegers-Theunissen RPM, Yang IV, Dabelea D, Fossati S, Zenclussen AC, Herberth G, Magnus M, Håberg SE, London SJ, Munthe-Kaas MC, Murphy SK, Hoyo C, Ziegler AG, Hummel S, Witt SH, Streit F, Frank J, Räikkönen K, Lahti J, Huang RC, Almqvist C, Hivert MF, Jaddoe VWV, Järvelin MR, Kantomaa M, Felix JF, Sebert S. Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence. Mol Psychiatry 2024; 29:348-358. [PMID: 38052982 PMCID: PMC11116099 DOI: 10.1038/s41380-023-02331-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 11/07/2023] [Accepted: 11/15/2023] [Indexed: 12/07/2023]
Abstract
Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.
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Affiliation(s)
- Priyanka Choudhary
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland.
| | - Giulietta S Monasso
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Ville Karhunen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
- Research Unit of Mathematical Sciences, Faculty of Science, University of Oulu, Oulu, Finland
| | - Justiina Ronkainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
| | - Giulia Mancano
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Medical School Population Health Sciences, University of Bristol, Bristol, UK
| | - Caitlin G Howe
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Zhongzheng Niu
- Department of Population and Public Health Sciences, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA
| | - John Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jason I Feinberg
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MA, USA
| | - Charles Mordaunt
- Department of Medical Micriobiology and Immunology, University of California Davis, Davis, CA, USA
| | - Giancarlo Pesce
- Epidemiology of Allergic and Respiratory Diseases (EPAR) team, Faculté de Médecine Saint-Antoine, Institute Pierre Louis d'Epidemiologie et Sante Publique (IPLESP), Sorbonne Université and INSERM, Paris, France
- Paris-Saclay University, Paris-South University, UVSQ, Center for Research in Epidemiology and Population Health (CESP), INSERM, Villejuif, France
| | - Nour Baïz
- Institute Desbrest of Epidemiology and Public Health, University of Montpellier and INSERM, Montpellier, France
| | - Rossella Alfano
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Dries S Martens
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Elena Isaevska
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO-Piemonte, Torino, Italy
| | - Elina Keikkala
- Department of Obstetrics and Gynaecology, Research Unit of Clinical Medicine, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
- Finnish Institute for Health and Welfare, Population Health Unit, Public Health and Welfare, Helsinki and Oulu, Finland
| | - Sanna Mustaniemi
- Department of Obstetrics and Gynaecology, Research Unit of Clinical Medicine, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
- Finnish Institute for Health and Welfare, Population Health Unit, Public Health and Welfare, Helsinki and Oulu, Finland
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Eliza Fraszczyk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Elmar W Tobi
- Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Erasmus MC, University Medical Center, 3000 CA, Rotterdam, the Netherlands
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marta Cosin-Tomas
- ISGlobal (Barcelona Institute for Global Health), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Jose Urquiza
- ISGlobal (Barcelona Institute for Global Health), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Stefan Röder
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany
| | - Thanh T Hoang
- Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Christian Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Oslo Centre for Biostatistics and Epidemiology, Section for Research Support, Oslo University Hospital, Oslo, Norway
| | - Dereje D Jima
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27606, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, 27606, USA
| | - John S House
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27606, USA
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, Durham, NC, 27709, USA
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Raffael Ott
- Institute of Diabetes Research, Helmholtz Munich, German Research Center for Environmental Health, Munich, Germany
- Forschergruppe Diabetes eV, Neuherberg, Germany
| | - Xenia Pawlow
- Institute of Diabetes Research, Helmholtz Munich, German Research Center for Environmental Health, Munich, Germany
- Forschergruppe Diabetes eV, Neuherberg, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anni Malmberg
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Phillip Melton
- Menzies Institute of Medical Research, University of Tasmania, Hobart, TAS, Australia
- University of Western Australia, School of Population and Global Health, Perth, WA, Australia
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ruby Fore
- Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Wei Perng
- Department of Epidemiology and the Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Zachary M Laubach
- Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA
| | - Darina Czamara
- Department Genes and Environment, Max Planck Institute for Psychiatry, Kraepelinstrasse 2+10, 80804, Munich, Germany
| | - Gemma Sharp
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Medical School Population Health Sciences, University of Bristol, Bristol, UK
- School of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Carrie V Breton
- Department of Population and Public Health Sciences, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Enrique Schisterman
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edwina Yeung
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, 20817, USA
| | - Sunni L Mumford
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, 20817, USA
| | - M Daniele Fallin
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MA, USA
| | - Janine M LaSalle
- Department of Medical Micriobiology and Immunology, University of California Davis, Davis, CA, USA
| | - Rebecca J Schmidt
- Department of Public Health Sciences, School of Medicine, University of California Davis (UC Davis), Davis, CA, USA
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Isabella Annesi-Maesano
- Institute Desbrest of Epidemiology and Public Health, University of Montpellier and INSERM, Montpellier, France
| | - Barbara Heude
- Université de Paris Cité, Inserm, INRAE, Centre of Research in Epidemiology and StatisticS (CRESS), F-75004, Paris, France
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Lorenza Nisticò
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Viale Regina Elena, Rome, Italy
| | - Marina Vafeiadi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - Manolis Kogevinas
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Centro de Investigación Biomédicaen Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Marja Vääräsmäki
- Department of Obstetrics and Gynaecology, Research Unit of Clinical Medicine, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
- Finnish Institute for Health and Welfare, Population Health Unit, Public Health and Welfare, Helsinki and Oulu, Finland
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Population Health Unit, Public Health and Welfare, Helsinki and Oulu, Finland
- Clinical Medicine Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
- Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Eva Corpeleijn
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Regine P M Steegers-Theunissen
- Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Erasmus MC, University Medical Center, 3000 CA, Rotterdam, the Netherlands
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Serena Fossati
- ISGlobal (Barcelona Institute for Global Health), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Ana C Zenclussen
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany
| | - Gunda Herberth
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany
| | - Maria Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Monica Cheng Munthe-Kaas
- Department of Pediatrics, Oncology and Hematology, Oslo University Hospital, Oslo, Norway
- Norwegian Institute of Public Health, Oslo, Norway
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27606, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Anette-G Ziegler
- Institute of Diabetes Research, Helmholtz Munich, German Research Center for Environmental Health, Munich, Germany
- Forschergruppe Diabetes eV, Neuherberg, Germany
- Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany
| | - Sandra Hummel
- Institute of Diabetes Research, Helmholtz Munich, German Research Center for Environmental Health, Munich, Germany
- Forschergruppe Diabetes eV, Neuherberg, Germany
- Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Center for Innovative Psychiatric and Psychotherapeutic Research, Biobank, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Rae-Chi Huang
- Telethon Kids Institute, Perth, WA, Australia
- Edith Cowan University, School of Medicine and Health Sciences, Joondalup, WA, Australia
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Marko Kantomaa
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
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Yoshioka S, Arakawa Y, Hasegawa M, Kato S, Hashimoto H, Mori S, Ueda H, Watanabe M. Twin study: genotype-dependent epigenetic factors affecting free thyroxine levels in the normal range. Epigenomics 2024; 16:147-158. [PMID: 38264851 DOI: 10.2217/epi-2023-0372] [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: 01/25/2024] Open
Abstract
Aim: To explore the clinical application of DNA methylation affecting thyroid function, we evaluated the association of DNA methylation with free thyroxine (FT4) and TSH measurements in monozygotic twins. Materials & methods: Discordant pairs for FT4 or TSH levels were examined for the relationship between the within-pair difference of each measurement and the DNA methylation levels using epigenome-wide association studies. The contribution of polymorphisms to the methylation sensitivity was also examined. Results: We found two CpG sites significantly associated with FT4 levels, and also some CpG sites showing significant differences in their methylation levels within FT4-discordant pairs depending on the polymorphism in EPHB2. Conclusion: The FT4 level may be associated with a combination of methylation and polymorphisms in the EPHB2 gene.
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Affiliation(s)
- Saki Yoshioka
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Yuya Arakawa
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
- Center for Twin Research, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Mika Hasegawa
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Shiho Kato
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Hinako Hashimoto
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Saho Mori
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Hiromichi Ueda
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
| | - Mikio Watanabe
- Department of Clinical Laboratory & Biomedical Sciences, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
- Center for Twin Research, Osaka University Graduate School of Medicine, Yamadaoka 1-7, Suita, Osaka, 565-0871, Japan
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29
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Laubach ZM, Bozack A, Aris IM, Slopen N, Tiemeier H, Hivert MF, Cardenas A, Perng W. Maternal prenatal social experiences and offspring epigenetic age acceleration from birth to mid-childhood. Ann Epidemiol 2024; 90:28-34. [PMID: 37839726 PMCID: PMC10842218 DOI: 10.1016/j.annepidem.2023.10.003] [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: 07/12/2023] [Revised: 09/27/2023] [Accepted: 10/10/2023] [Indexed: 10/17/2023]
Abstract
PURPOSE Investigate associations of maternal social experiences with offspring epigenetic age acceleration (EAA) from birth through mid-childhood among 205 mother-offspring dyads of minoritized racial and ethnic groups. METHODS We used linear regression to examine associations of maternal experiences of racial bias or discrimination (0 = none, 1-2 = intermediate, or 3+ = high), social support (tertile 1 = low, 2 = intermediate, 3 = high), and socioeconomic status index (tertile 1 = low, 2 = intermediate, 3 = high) during the prenatal period with offspring EAA according to Horvath's Pan-Tissue, Horvath's Skin and Blood, and Intrinsic EAA clocks at birth, 3 years, and 7 years. RESULTS In comparison to children of women who did not experience any racial bias or discrimination, those whose mothers reported highest levels of racial bias or discrimination had lower Pan-Tissue clock EAA in early (-0.50 years; 90% CI: -0.91, -0.09) and mid-childhood (-0.75 years; -1.41, -0.08). We observed similar associations for the Skin and Blood clock and Intrinsic EAA. Maternal experiences of discrimination were not associated with Pan-Tissue EAA at birth. Neither maternal social support nor socioeconomic status predicted offspring EAA. CONCLUSIONS Children whose mothers experienced higher racial bias or discrimination exhibited slower EAA. Future studies are warranted to confirm these findings and establish associations of early-life EAA with long-term health outcomes.
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Affiliation(s)
- Zachary M Laubach
- Department of Ecology and Evolutionary Biology (EBIO), University of Colorado Boulder
| | - Anne Bozack
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA
| | - Natalie Slopen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Henning Tiemeier
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse (CORAL), Department of Population Medicine, Harvard Medical School, Boston, MA; Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA
| | - Wei Perng
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD Center), Department of Epidemiology, Colorado School of Public Health, Aurora, CO.
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30
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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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31
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Kasela S, Aguet F, Kim-Hellmuth S, Brown BC, Nachun DC, Tracy RP, Durda P, Liu Y, Taylor KD, Johnson WC, Van Den Berg D, Gabriel S, Gupta N, Smith JD, Blackwell TW, Rotter JI, Ardlie KG, Manichaikul A, Rich SS, Barr RG, Lappalainen T. Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects. Am J Hum Genet 2024; 111:133-149. [PMID: 38181730 PMCID: PMC10806864 DOI: 10.1016/j.ajhg.2023.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024] Open
Abstract
Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
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Affiliation(s)
- Silva Kasela
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA.
| | | | - Sarah Kim-Hellmuth
- New York Genome Center, New York, NY, USA; Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital LMU Munich, Munich, Germany; Computational Health Center, Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Brielin C Brown
- New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA
| | - Daniel C Nachun
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Russell P Tracy
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Peter Durda
- Pathology and Laboratory Medicine, The University of Vermont, Larner College of Medicine, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | | | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joshua D Smith
- Northwest Genomics Center, University of Washington, Seattle, WA, USA
| | - Thomas W Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA; Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
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32
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Chen JQ, Salas LA, Wiencke JK, Koestler DC, Molinaro AM, Andrew AS, Seigne JD, Karagas MR, Kelsey KT, Christensen BC. Matched analysis of detailed peripheral blood and tumor immune microenvironment profiles in bladder cancer. Epigenomics 2024; 16:41-56. [PMID: 38221889 PMCID: PMC10804212 DOI: 10.2217/epi-2023-0358] [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: 10/13/2023] [Accepted: 12/11/2023] [Indexed: 01/16/2024] Open
Abstract
Background: Bladder cancer and therapy responses hinge on immune profiles in the tumor microenvironment (TME) and blood, yet studies linking tumor-infiltrating immune cells to peripheral immune profiles are limited. Methods: DNA methylation cytometry quantified TME and matched peripheral blood immune cell proportions. With tumor immune profile data as the input, subjects were grouped by immune infiltration status and consensus clustering. Results: Immune hot and cold groups had different immune compositions in the TME but not in circulating blood. Two clusters of patients identified with consensus clustering had different immune compositions not only in the TME but also in blood. Conclusion: Detailed immune profiling via methylation cytometry reveals the significance of understanding tumor and systemic immune relationships in cancer patients.
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Affiliation(s)
- Ji-Qing Chen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Angeline S Andrew
- Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - John D Seigne
- Department of Surgery, Section of Urology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
| | - Karl T Kelsey
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
- Departments of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03766, USA
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Luo M, Walton E, Neumann A, Thio CHL, Felix JF, van IJzendoorn MH, Pappa I, Cecil CAM. DNA methylation at birth and lateral ventricular volume in childhood: a neuroimaging epigenetics study. J Child Psychol Psychiatry 2024; 65:77-90. [PMID: 37469193 PMCID: PMC10953396 DOI: 10.1111/jcpp.13866] [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] [Accepted: 06/05/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Lateral ventricular volume (LVV) enlargement has been repeatedly linked to schizophrenia; yet, what biological factors shape LVV during early development remain unclear. DNA methylation (DNAm), an essential process for neurodevelopment that is altered in schizophrenia, is a key molecular system of interest. METHODS In this study, we conducted the first epigenome-wide association study of neonatal DNAm in cord blood with LVV in childhood (measured using T1-weighted brain scans at 10 years), based on data from a large population-based birth cohort, the Generation R Study (N = 840). Employing both probe-level and methylation profile score (MPS) approaches, we further examined whether epigenetic modifications identified at birth in cord blood are: (a) also observed cross-sectionally in childhood using peripheral blood DNAm at age of 10 years (Generation R, N = 370) and (b) prospectively associated with LVV measured in young adulthood in an all-male sample from the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 114). RESULTS At birth, DNAm levels at four CpGs (annotated to potassium channel tetramerization domain containing 3, KCTD3; SHH signaling and ciliogenesis regulator, SDCCAG8; glutaredoxin, GLRX) prospectively associated with childhood LVV after genome-wide correction; these genes have been implicated in brain development and psychiatric traits including schizophrenia. An MPS capturing a broader epigenetic profile of LVV - but not individual top hits - showed significant cross-sectional associations with LVV in childhood in Generation R and prospectively associated with LVV in early adulthood within ALSPAC. CONCLUSIONS This study finds suggestive evidence that DNAm at birth prospectively associates with LVV at different life stages, albeit with small effect sizes. The prediction of MPS on LVV in a childhood sample and an independent male adult sample further underscores the stability and reproducibility of DNAm as a potential marker for LVV. Future studies with larger samples and comparable time points across development are needed to further elucidate how DNAm associates with this clinically relevant brain structure and risk for neuropsychiatric disorders, and what factors explain the identified DNAm profile of LVV at birth.
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Affiliation(s)
- Mannan Luo
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamThe Netherlands
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | | | - Alexander Neumann
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Chris H. L. Thio
- Department of EpidemiologyUniversity Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Janine F. Felix
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Marinus H. van IJzendoorn
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamThe Netherlands
- Research Department of Clinical, Educational and Health Psychology, Faculty of Brain Sciences, UCLUniversity of LondonLondonUK
| | - Irene Pappa
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Clinical Child and Family StudiesVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Charlotte A. M. Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Epidemiology, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Molecular Epidemiology, Department of Biomedical Data SciencesLeiden University Medical CenterLeidenThe Netherlands
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Nikolaienko O, Eikesdal HP, Ognedal E, Gilje B, Lundgren S, Blix ES, Espelid H, Geisler J, Geisler S, Janssen EAM, Yndestad S, Minsaas L, Leirvaag B, Lillestøl R, Knappskog S, Lønning PE. Prenatal BRCA1 epimutations contribute significantly to triple-negative breast cancer development. Genome Med 2023; 15:104. [PMID: 38053165 PMCID: PMC10698991 DOI: 10.1186/s13073-023-01262-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 11/16/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Normal cell BRCA1 epimutations have been associated with increased risk of triple-negative breast cancer (TNBC). However, the fraction of TNBCs that may have BRCA1 epimutations as their underlying cause is unknown. Neither are the time of occurrence and the potential inheritance patterns of BRCA1 epimutations established. METHODS To address these questions, we analyzed BRCA1 methylation status in breast cancer tissue and matched white blood cells (WBC) from 408 patients with 411 primary breast cancers, including 66 TNBCs, applying a highly sensitive sequencing assay, allowing allele-resolved methylation assessment. Furthermore, to assess the time of origin and the characteristics of normal cell BRCA1 methylation, we analyzed umbilical cord blood of 1260 newborn girls and 200 newborn boys. Finally, we assessed BRCA1 methylation status among 575 mothers and 531 fathers of girls with (n = 102) and without (n = 473) BRCA1 methylation. RESULTS We found concordant tumor and mosaic WBC BRCA1 epimutations in 10 out of 66 patients with TNBC and in four out of six patients with estrogen receptor (ER)-low expression (< 10%) tumors (combined: 14 out of 72; 19.4%; 95% CI 11.1-30.5). In contrast, we found concordant WBC and tumor methylation in only three out of 220 patients with 221 ER ≥ 10% tumors and zero out of 114 patients with 116 HER2-positive tumors. Intraindividually, BRCA1 epimutations affected the same allele in normal and tumor cells. Assessing BRCA1 methylation in umbilical WBCs from girls, we found mosaic, predominantly monoallelic BRCA1 epimutations, with qualitative features similar to those in adults, in 113/1260 (9.0%) of individuals, but no correlation to BRCA1 methylation status either in mothers or fathers. A significantly lower fraction of newborn boys carried BRCA1 methylation (9/200; 4.5%) as compared to girls (p = 0.038). Similarly, WBC BRCA1 methylation was found less common among fathers (16/531; 3.0%), as compared to mothers (46/575; 8.0%; p = 0.0003). CONCLUSIONS Our findings suggest prenatal BRCA1 epimutations might be the underlying cause of around 20% of TNBC and low-ER expression breast cancers. Such constitutional mosaic BRCA1 methylation likely arise through gender-related mechanisms in utero, independent of Mendelian inheritance.
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Affiliation(s)
- Oleksii Nikolaienko
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Hans P Eikesdal
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Elisabet Ognedal
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Bjørnar Gilje
- Department of Hematology and Oncology, Stavanger University Hospital, Stavanger, Norway
| | - Steinar Lundgren
- Cancer Clinic, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Egil S Blix
- Department of Oncology, University Hospital of North Norway, Tromsø, Norway
| | - Helge Espelid
- Department of Surgery, Haugesund Hospital, Haugesund, Norway
| | - Jürgen Geisler
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Stephanie Geisler
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway
| | - Emiel A M Janssen
- Department of Pathology, Stavanger University Hospital, Stavanger, Norway
- Department of Chemistry, Bioscience and Environmental Engineering, Stavanger University, Stavanger, Norway
| | - Synnøve Yndestad
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Laura Minsaas
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Beryl Leirvaag
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Reidun Lillestøl
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Stian Knappskog
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway
| | - Per E Lønning
- K.G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Department of Oncology, Haukeland University Hospital, Jonas Lies Vei 65, N5021, Bergen, Norway.
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Díez-Villanueva A, Martín B, Moratalla-Navarro F, Morón-Duran FD, Galván-Femenía I, Obón-Santacana M, Carreras A, de Cid R, Peinado MA, Moreno V. Identification of intergenerational epigenetic inheritance by whole genome DNA methylation analysis in trios. Sci Rep 2023; 13:21266. [PMID: 38042866 PMCID: PMC10693549 DOI: 10.1038/s41598-023-48517-3] [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: 08/01/2023] [Accepted: 11/27/2023] [Indexed: 12/04/2023] Open
Abstract
Genome-wide association studies have identified thousands of loci associated with common diseases and traits. However, a large fraction of heritability remains unexplained. Epigenetic modifications, such as the observed in DNA methylation have been proposed as a mechanism of intergenerational inheritance. To investigate the potential contribution of DNA methylation to the missing heritability, we analysed the methylomes of four healthy trios (two parents and one offspring) using whole genome bisulphite sequencing. Of the 1.5 million CpGs (19%) with over 20% variability between parents in at least one family and compatible with a Mendelian inheritance pattern, only 3488 CpGs (0.2%) lacked correlation with any SNP in the genome, marking them as potential sites for intergenerational epigenetic inheritance. These markers were distributed genome-wide, with some preference to be located in promoters. They displayed a bimodal distribution, being either fully methylated or unmethylated, and were often found at the boundaries of genomic regions with high/low GC content. This analysis provides a starting point for future investigations into the missing heritability of simple and complex traits.
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Affiliation(s)
- Anna Díez-Villanueva
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
| | - Berta Martín
- Germans Trias i Pujol Institute (IGTP), Translational Program in Cancer Research (CARE), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Ferran Moratalla-Navarro
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain
| | - Francisco D Morón-Duran
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain
| | - Iván Galván-Femenía
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
| | - Anna Carreras
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Rafael de Cid
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Miguel A Peinado
- Germans Trias i Pujol Institute (IGTP), Translational Program in Cancer Research (CARE), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Victor Moreno
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain.
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain.
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain.
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain.
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Vellame DS, Shireby G, MacCalman A, Dempster EL, Burrage J, Gorrie-Stone T, Schalkwyk LS, Mill J, Hannon E. Uncertainty quantification of reference-based cellular deconvolution algorithms. Epigenetics 2023; 18:2137659. [PMID: 36539387 PMCID: PMC9980651 DOI: 10.1080/15592294.2022.2137659] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 10/12/2022] [Indexed: 12/24/2022] Open
Abstract
The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).
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Affiliation(s)
| | - Gemma Shireby
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Ailsa MacCalman
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Emma L Dempster
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Joe Burrage
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Tyler Gorrie-Stone
- School of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK
| | | | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
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Pahkuri S, Ekman I, Vandamme C, Näntö-Salonen K, Toppari J, Veijola R, Knip M, Kinnunen T, Ilonen J, Lempainen J. DNA methylation differences within INS, PTPN22 and IL2RA promoters in lymphocyte subsets in children with type 1 diabetes and controls. Autoimmunity 2023; 56:2259118. [PMID: 37724526 DOI: 10.1080/08916934.2023.2259118] [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: 03/28/2023] [Accepted: 09/10/2023] [Indexed: 09/21/2023]
Abstract
We elucidated the effect of four known T1D-susceptibility associated single nucleotide polymorphism (SNP) markers in three genes (rs12722495 and rs2104286 in IL2RA, rs689 in INS and rs2476601 in PTPN22) on CpG site methylation of their proximal promoters in different lymphocyte subsets using pyrosequencing. The study cohort comprised 25 children with newly diagnosed T1D and 25 matched healthy controls. The rs689 SNP was associated with methylation at four CpG sites in INS promoter: -234, -206, -102 and -69. At all four CpG sites, the susceptibility genotype AA was associated with a higher methylation level compared to the other genotypes. We also found an association between rs12722495 and methylation at CpG sites -373 and -356 in IL2RA promoter in B cells, where the risk genotype AA was associated with lower methylation level compared to the AG genotype. The other SNPs analyzed did not demonstrate significant associations with CpG site methylation in the examined genes. Additionally, we compared the methylation between children with T1D and controls, and found statistically significant methylation differences at CpG -135 in INS in CD8+ T cells (p = 0.034), where T1D patients had a slightly higher methylation compared to controls (87.3 ± 7.2 vs. 78.8 ± 8.9). At the other CpG sites analyzed, the methylation was similar. Our results not only confirm the association between INS methylation and rs689 discovered in earlier studies but also report this association in sorted immune cells. We also report an association between rs12722495 and IL2RA promoter methylation in B cells. These results suggest that at least part of the genetic effect of rs689 and rs12722495 on T1D pathogenesis may be conveyed by DNA methylation.
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Affiliation(s)
- Sirpa Pahkuri
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Ilse Ekman
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Céline Vandamme
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Kirsti Näntö-Salonen
- Department of Pediatrics, University of Turku and Turku University Hospital, Turku, Finland
| | - Jorma Toppari
- Department of Pediatrics, University of Turku and Turku University Hospital, Turku, Finland
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, and Centre for Population Health Research, University of Turku, Turku, Finland
| | - Riitta Veijola
- Department of Pediatrics, PEDEGO Research Unit, Medical Research Center, University of Oulu, Oulu, Finland
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Mikael Knip
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
| | - Tuure Kinnunen
- Department of Clinical Microbiology, Institute of Clinical Medicine, University of Eastern Finland, Eastern Finland Laboratory Centre (ISLAB), Kuopio, Finland
| | - Jorma Ilonen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
| | - Johanna Lempainen
- Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
- Department of Pediatrics, University of Turku and Turku University Hospital, Turku, Finland
- Clinical Microbiology, Turku University Hospital, Turku, Finland
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Sumida K, Mozhui K, Liang X, Mallisetty Y, Han Z, Kovesdy CP. Association of DNA methylation signatures with premature ageing and cardiovascular death in patients with end-stage kidney disease: a pilot epigenome-wide association study. Epigenetics 2023; 18:2214394. [PMID: 37207321 PMCID: PMC10202091 DOI: 10.1080/15592294.2023.2214394] [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: 12/29/2022] [Revised: 04/25/2023] [Accepted: 05/09/2023] [Indexed: 05/21/2023] Open
Abstract
Patients with end-stage kidney disease (ESKD) display features of premature aging. There is strong evidence that changes in DNA methylation (DNAm) contribute to age-related pathologies; however, little is known about their association with premature aging and cardiovascular mortality in patients with ESKD. We assayed genome-wide DNAm in a pilot case-control study of 60 hemodialysis patients with (n=30, cases) and without (n=30, controls) a fatal cardiovascular event. DNAm was profiled on the Illumina EPIC BeadChip. Four established DNAm clocks (i.e., Horvath-, Hannum-, Pheno-, and GrimAge) were used to estimate epigenetic age (DNAmAge). Epigenetic age acceleration (EAA) was derived as the residuals of regressing DNAmAge on chronological age (chroAge), and its association with cardiovascular death was examined using multivariable conditional logistic regression. An epigenome-wide association study (EWAS) was performed to identify differentially methylated CpGs associated with cardiovascular death. All clocks performed well at predicting chroAge (correlation between DNAmAges and chroAge of r=0.76-0.89), with GrimAge showing the largest deviation from chroAge (a mean of +21.3 years). There was no significant association of EAAs with cardiovascular death. In the EWAS, a CpG (cg22305782) in the FBXL19 gene had the strongest association with cardiovascular death with significantly lower DNAm in cases vs. controls (PFDR=2.0x10-6). FBXL19 is involved in cell apoptosis, inflammation, and adipogenesis. Overall, we observed more accelerated aging in patients with ESKD, although there was no significant association of EAAs with cardiovascular death. EWAS suggests a potential novel DNAm biomarker for premature cardiovascular mortality in ESKD.
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Affiliation(s)
- Keiichi Sumida
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Xiaoyu Liang
- Department of Epidemiology and Biostatistics, Michigan State University College of Human Medicine, East Lansing, MI, USA
| | - Yamini Mallisetty
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Zhongji Han
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Csaba P Kovesdy
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
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39
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Ng JWY, Felix JF, Olson DM. A novel approach to risk exposure and epigenetics-the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health. BMC Med 2023; 21:466. [PMID: 38012757 PMCID: PMC10683259 DOI: 10.1186/s12916-023-03168-z] [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: 02/02/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Each mother-child dyad represents a unique combination of genetic and environmental factors. This constellation of variables impacts the expression of countless genes. Numerous studies have uncovered changes in DNA methylation (DNAm), a form of epigenetic regulation, in offspring related to maternal risk factors. How these changes work together to link maternal-child risks to childhood cardiometabolic and neurocognitive traits remains unknown. This question is a key research priority as such traits predispose to future non-communicable diseases (NCDs). We propose viewing risk and the genome through a multidimensional lens to identify common DNAm patterns shared among diverse risk profiles. METHODS We identified multifactorial Maternal Risk Profiles (MRPs) generated from population-based data (n = 15,454, Avon Longitudinal Study of Parents and Children (ALSPAC)). Using cord blood HumanMethylation450 BeadChip data, we identified genome-wide patterns of DNAm that co-vary with these MRPs. We tested the prospective relation of these DNAm patterns (n = 914) to future outcomes using decision tree analysis. We then tested the reproducibility of these patterns in (1) DNAm data at age 7 and 17 years within the same cohort (n = 973 and 974, respectively) and (2) cord DNAm in an independent cohort, the Generation R Study (n = 686). RESULTS We identified twenty MRP-related DNAm patterns at birth in ALSPAC. Four were prospectively related to cardiometabolic and/or neurocognitive childhood outcomes. These patterns were replicated in DNAm data from blood collected at later ages. Three of these patterns were externally validated in cord DNAm data in Generation R. Compared to previous literature, DNAm patterns exhibited novel spatial distribution across the genome that intersects with chromatin functional and tissue-specific signatures. CONCLUSIONS To our knowledge, we are the first to leverage multifactorial population-wide data to detect patterns of variability in DNAm. This context-based approach decreases biases stemming from overreliance on specific samples or variables. We discovered molecular patterns demonstrating prospective and replicable relations to complex traits. Moreover, results suggest that patterns harbour a genome-wide organisation specific to chromatin regulation and target tissues. These preliminary findings warrant further investigation to better reflect the reality of human context in molecular studies of NCDs.
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Affiliation(s)
- Jane W Y Ng
- Department of Pediatrics, Cummings School of Medicine, University of Calgary, 28 Oki Drive NW, Calgary, AB, T3B 6A8, Canada
| | - Janine F Felix
- The Generation F Study Group, Erasmus MC University Medical Center Rotterdam, Postbus, 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - David M Olson
- Departments of Obstetrics and Gynecology, Physiology, and Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, 220 HMRC, Edmonton, AB, T6G2S2, Canada.
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Urbarova I, Skogholt AH, Sun YQ, Mai XM, Grønberg BH, Sandanger TM, Sætrom P, Nøst TH. Increased expression of individual genes in whole blood is associated with late-stage lung cancer at and close to diagnosis. Sci Rep 2023; 13:20760. [PMID: 38007577 PMCID: PMC10676373 DOI: 10.1038/s41598-023-48216-z] [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: 08/31/2023] [Accepted: 11/23/2023] [Indexed: 11/27/2023] Open
Abstract
Lung cancer (LC) mortality rates are still increasing globally. As survival is linked to stage, there is a need to identify markers for earlier LC diagnosis and individualized treatment. The whole blood transcriptome of LC patients represents a source of potential LC biomarkers. We compared expression of > 60,000 genes in whole blood specimens taken from LC cases at diagnosis (n = 128) and controls (n = 62) using genome-wide RNA sequencing, and identified 14 candidate genes associated with LC. High expression of ANXA3, ARG1 and HP was strongly associated with lower survival in late-stage LC cases (hazard ratios (HRs) = 2.81, 2.16 and 2.54, respectively). We validated these markers in two independent population-based studies with pre-diagnostic whole blood specimens taken up to eight years prior to LC diagnosis (n = 163 cases, 184 matched controls). ANXA3 and ARG1 expression was strongly associated with LC in these specimens, especially with late-stage LC within two years of diagnosis (odds ratios (ORs) = 3.47 and 5.00, respectively). Additionally, blood CD4 T cells, NK cells and neutrophils were associated with LC at diagnosis and improved LC discriminative ability beyond candidate genes. Our results indicate that in whole blood, increased expression levels of ANXA3, ARG1 and HP are diagnostic and prognostic markers of late-stage LC.
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Affiliation(s)
- Ilona Urbarova
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.
| | - Anne Heidi Skogholt
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Yi-Qian Sun
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Pathology, Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Center for Oral Health Services and Research Mid-Norway (TkMidt), Trondheim, Norway
| | - Xiao-Mei Mai
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bjørn Henning Grønberg
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Oncology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Torkjel Manning Sandanger
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Pål Sætrom
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Oncology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
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Ho PJ, Khng AJ, Tan BKT, Lim GH, Tan SM, Tan VKM, Tan RSYC, Lim EH, Iau PTC, Chew YJ, Lim YY, Hartman M, Tan EY, Li J. Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway. Breast Cancer Res 2023; 25:136. [PMID: 37932858 PMCID: PMC10626732 DOI: 10.1186/s13058-023-01730-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/15/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Exposure to cytotoxic chemotherapy treatment may alter DNA methylation (DNAm) in breast cancer patients. METHODS We performed DNAm analysis in 125 breast cancer patients with blood drawn before and after chemotherapy, using the Illumina MethylationEPIC array. DNAm changes of 588,798 individual CpGs (including 41,207 promoter regions) were evaluated using linear regression models adjusted for monocyte proportion. Gene set enrichment analyses (GSEA) were conducted to identify key Gene Ontology (GO) biological processes or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with chemotherapy. Results were validated in a separate cohort of breast cancer patients who were treated (n = 1273) and not treated (n = 872) by chemotherapy (1808 blood, 337 saliva). RESULTS A total of 141 differentially methylated CpGs and 11 promoters were significantly associated with chemotherapy after multiple testing corrections in both the paired sample and single time point analyses. GSEA of promoter regions (pre-ranked by test statistics) identified six suppressed biological processes (p < 4.67e-8) related to sensory perception and detection of chemical stimuli, including smell perception (GO:0007606, GO:0007608, GO:0009593, GO:0050906, GO:0050907, and GO:0050911). The same six biological processes were significantly suppressed in the validation dataset (p < 9.02e-14). The KEGG pathway olfactory transduction (hsa04740) was also found to be significantly suppressed (ppaired-samples = 1.72e-9, psingle-timepoint-blood = 2.03e-15 and psingle-timepoint-saliva = 7.52e-56). CONCLUSION The enrichment of imprinted genes within biological processes and pathways suggests a biological mechanism by which chemotherapy could affect the perception of smell.
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Affiliation(s)
- Peh Joo Ho
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Alexis Jiaying Khng
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore
| | - Benita Kiat-Tee Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Republic of Singapore
- Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
- Department of General Surgery, Sengkang General Hospital, Singapore, Republic of Singapore
| | - Geok Hoon Lim
- KK Breast Department, KK Women's and Children's Hospital, Singapore, 229899, Republic of Singapore
| | - Su-Ming Tan
- Division of Breast Surgery, Changi General Hospital, Singapore, Republic of Singapore
| | - Veronique Kiak Mien Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Republic of Singapore
- Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
| | - Ryan Shea Ying Cong Tan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
- Oncology Academic Programme, Duke-NUS Medical School, Singapore, Republic of Singapore
| | - Elaine Hsuen Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
| | - Philip Tsau-Choong Iau
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
- Department of General Surgery, Ng Teng Fong General Hospital, 1 Jurong East St 21, Singapore, 609606, Republic of Singapore
| | - Ying Jia Chew
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
- Department of General Surgery, Ng Teng Fong General Hospital, 1 Jurong East St 21, Singapore, 609606, Republic of Singapore
| | - Yi Ying Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
| | - Ern Yu Tan
- Department of General Surgery, Tan Tock Seng Hospital, Singapore, 308433, Republic of Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore
| | - Jingmei Li
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore.
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore.
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Hubens WHG, Maié T, Schnitker M, Bocova L, Puri D, Wessiepe M, Kramer J, Rink L, Koschmieder S, Costa IG, Wagner W. Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples. Clin Chem 2023; 69:1283-1294. [PMID: 37708296 DOI: 10.1093/clinchem/hvad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 08/10/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND Cell-type specific DNA methylation (DNAm) can be employed to determine the numbers of leukocyte subsets in blood. In contrast to conventional methods for leukocyte counts, which are based on cellular morphology or surface marker protein expression, the cellular deconvolution based on DNAm levels is applicable for frozen or dried blood. Here, we further enhanced targeted DNAm assays for leukocyte counts in clinical application. METHODS DNAm profiles of 40 different studies were compiled to identify CG dinucleotides (CpGs) with cell-type specific DNAm using a computational framework, CimpleG. DNAm levels at these CpGs were then measured with digital droplet PCR in venous blood from 160 healthy donors and 150 patients with various hematological disorders. Deconvolution was further validated with venous blood (n = 75) and capillary blood (n = 31) that was dried on Whatman paper or on Mitra microsampling devices. RESULTS In venous blood, automated cell counting or flow cytometry correlated well with epigenetic estimates of relative leukocyte counts for granulocytes (r = 0.95), lymphocytes (r = 0.97), monocytes (r = 0.82), CD4 T cells (r = 0.84), CD8 T cells (r = 0.94), B cells (r = 0.96), and NK cells (r = 0.72). Similar correlations and precisions were achieved for dried blood samples. Spike-in with a reference plasmid enabled accurate epigenetic estimation of absolute leukocyte counts from dried blood samples, correlating with conventional venous (r = 0.86) and capillary (r = 0.80) blood measurements. CONCLUSIONS The advanced selection of cell-type specific CpGs and utilization of digital droplet PCR analysis provided accurate epigenetic blood counts. Analysis of dried blood facilitates self-sampling with a finger prick, thereby enabling easier accessibility to testing.
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Affiliation(s)
- Wouter H G Hubens
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Tiago Maié
- Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Matthis Schnitker
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Ledio Bocova
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Deepika Puri
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Martina Wessiepe
- Institute for Transfusion Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Jan Kramer
- Division of Nephrology and Transplantation Unit, Department of Internal Medicine I, University of Lübeck, Lübeck, Germany
- LADR Laboratory Group Dr. Kramer & Colleagues, Geesthacht, Germany
| | - Lothar Rink
- Institute of Immunology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Steffen Koschmieder
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany
| | - Ivan G Costa
- Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
| | - Wolfgang Wagner
- Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany
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Cuomo M, Coretti L, Costabile D, Della Monica R, De Riso G, Buonaiuto M, Trio F, Bravaccio C, Visconti R, Berni Canani R, Chiariotti L, Lembo F. Host fecal DNA specific methylation signatures mark gut dysbiosis and inflammation in children affected by autism spectrum disorder. Sci Rep 2023; 13:18197. [PMID: 37875530 PMCID: PMC10598023 DOI: 10.1038/s41598-023-45132-0] [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: 08/03/2023] [Accepted: 10/16/2023] [Indexed: 10/26/2023] Open
Abstract
The gut-brain axis involves several bidirectional pathway communications including microbiome, bacterial metabolites, neurotransmitters as well as immune system and is perturbed both in brain and in gastrointestinal disorders. Consistently, microbiota-gut-brain axis has been found altered in autism spectrum disorder (ASD). We reasoned that such alterations occurring in ASD may impact both on methylation signatures of human host fecal DNA (HFD) and possibly on the types of human cells shed in the stools from intestinal tract giving origin to HFD. To test this hypothesis, we have performed whole genome methylation analysis of HFD from an age-restricted cohort of young children with ASD (N = 8) and healthy controls (N = 7). In the same cohort we have previously investigated the fecal microbiota composition and here we refined such analysis and searched for eventual associations with data derived from HFD methylome analysis. Our results showed that specific epigenetic signatures in human fecal DNA, especially at genes related to inflammation, associated with the disease. By applying methylation-based deconvolution algorithm, we found that the HFD derived mainly from immune cells and the relative abundance of those differed between patients and controls. Consistently, most of differentially methylated regions fitted with genes involved in inflammatory response. Interestingly, using Horvath epigenetic clock, we found that ASD affected children showed both epigenetic and microbiota age accelerated. We believe that the present unprecedented approach may be useful for the identification of the ASD associated HFD epigenetic signatures and may be potentially extended to other brain disorders and intestinal inflammatory diseases.
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Affiliation(s)
- Mariella Cuomo
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy
| | - Lorena Coretti
- Department of Pharmacy, University of Naples "Federico II", Via Domenico Montesano 49, 80131, Naples, Italy
| | - Davide Costabile
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy
- SEMM-European School of Molecular Medicine, University of Naples "Federico II", Naples, Italy
| | - Rosa Della Monica
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy
| | - Giulia De Riso
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy
| | - Michela Buonaiuto
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy
| | - Federica Trio
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy
| | - Carmela Bravaccio
- Department of Translational Medical Science - Pediatric Section, University of Naples Federico II, Naples, Italy
| | - Roberta Visconti
- Institute for the Experimental Endocrinology and Oncology "G. Salvatore", Italian National Council of Research, Via S. Pansini 5, 80131, Naples, Italy
| | - Roberto Berni Canani
- Department of Translational Medical Science - Pediatric Section, University of Naples Federico II, Naples, Italy
| | - Lorenzo Chiariotti
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy.
- CEINGE Advanced Biotechnologies "Franco Salvatore", Via G. Salvatore 482, 80145, Naples, Italy.
- SEMM-European School of Molecular Medicine, University of Naples "Federico II", Naples, Italy.
| | - Francesca Lembo
- Department of Pharmacy, University of Naples "Federico II", Via Domenico Montesano 49, 80131, Naples, Italy.
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Mattox AK, Douville C, Wang Y, Popoli M, Ptak J, Silliman N, Dobbyn L, Schaefer J, Lu S, Pearlman AH, Cohen JD, Tie J, Gibbs P, Lahouel K, Bettegowda C, Hruban RH, Tomasetti C, Jiang P, Chan KA, Lo YMD, Papadopoulos N, Kinzler KW, Vogelstein B. The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer. Cancer Discov 2023; 13:2166-2179. [PMID: 37565753 PMCID: PMC10592331 DOI: 10.1158/2159-8290.cd-21-1252] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 12/16/2022] [Accepted: 08/09/2023] [Indexed: 08/12/2023]
Abstract
Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared with those of healthy controls, but the sources of this extra cfDNA have never been determined. To address this issue, we assessed cfDNA methylation patterns in 178 patients with cancers of the colon, pancreas, lung, or ovary and 64 patients without cancer. Eighty-three of these individuals had cfDNA concentrations much greater than those generally observed in healthy subjects. The major contributor of cfDNA in all samples was leukocytes, accounting for ∼76% of cfDNA, with neutrophils predominating. This was true regardless of whether the samples were derived from patients with cancer or the total plasma cfDNA concentration. High levels of cfDNA observed in patients with cancer did not come from either neoplastic cells or surrounding normal epithelial cells from the tumor's tissue of origin. These data suggest that cancers may have a systemic effect on cell turnover or DNA clearance. SIGNIFICANCE The origin of excess cfDNA in patients with cancer is unknown. Using cfDNA methylation patterns, we determined that neither the tumor nor the surrounding normal tissue contributes this excess cfDNA-rather it comes from leukocytes. This finding suggests that cancers have a systemic impact on cell turnover or DNA clearance. See related commentary by Thierry and Pisareva, p. 2122. This article is featured in Selected Articles from This Issue, p. 2109.
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Affiliation(s)
- Austin K. Mattox
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Christopher Douville
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Yuxuan Wang
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Maria Popoli
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Janine Ptak
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Natalie Silliman
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Lisa Dobbyn
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Joy Schaefer
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Steve Lu
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Alexander H. Pearlman
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Joshua D. Cohen
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Jeanne Tie
- Division of Systems Biology and Personalized Medicine, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Oncology, Western Health, St Albans, Victoria 3021, Australia
- Department of Medical Oncology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Peter Gibbs
- Division of Systems Biology and Personalized Medicine, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Oncology, Western Health, St Albans, Victoria 3021, Australia
- Department of Medical Oncology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Kamel Lahouel
- Division of Mathematics for Cancer Evolution and Early Detection, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010
| | - Chetan Bettegowda
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21287
| | - Ralph H. Hruban
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Cristian Tomasetti
- Division of Mathematics for Cancer Evolution and Early Detection, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010
| | - Peiyong Jiang
- State Key Laboratory of Translational Oncology and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
- Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - K.C. Allen Chan
- State Key Laboratory of Translational Oncology and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
- Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - Yuk Ming Dennis Lo
- State Key Laboratory of Translational Oncology and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
- Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - Nickolas Papadopoulos
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Kenneth W. Kinzler
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - Bert Vogelstein
- Ludwig Center for Cancer Genetics and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287
- Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287
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Nishiyama K, Nishinakamura H, Takeshima H, Yuyu L, Takeuchi C, Hattori N, Takeda H, Yamashita S, Wakabayashi M, Sato K, Obama K, Ushijima T. Mouse methylation profiles for leukocyte cell types, and estimation of leukocyte fractions in inflamed gastrointestinal DNA samples. PLoS One 2023; 18:e0290034. [PMID: 37797047 PMCID: PMC10553802 DOI: 10.1371/journal.pone.0290034] [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: 04/17/2023] [Accepted: 07/31/2023] [Indexed: 10/07/2023] Open
Abstract
Precise analysis of tissue DNA and RNA samples is often hampered by contaminating non-target cells whose amounts are highly variable. DNA methylation profiles are specific to cell types, and can be utilized for assessment of the fraction of such contaminating non-target cells. Here, we aimed 1) to identify methylation profiles specific to multiple types of mouse leukocytes, and 2) to estimate the fraction of leukocytes infiltrating inflamed tissues using DNA samples. First, genome-wide DNA methylation analysis was conducted for three myeloid-lineage cells and four lymphoid-lineage cells isolated by fluorescence-activated cell sorting after magnetic-activated cell sorting from leukocytes in the spleen. Clustering analysis using CpG sites within enhancers separated the three myeloid-lineage cells and four lymphoid-lineage cells while that using promoter CpG islands (TSS200CGIs) did not. Among the 266,108 CpG sites analyzed, one CpG site was specifically hypermethylated (β value ≥ 0.7) in B cells, and four, seven, 183, and 34 CpG sites were specifically hypomethylated (β value < 0.2) in CD4+ T cells, CD8+ T cells, B cells, and NK cells, respectively. Importantly, cell type-specific hypomethylated CpG sites were located at genes involved in cell type-specific biological functions. Then, marker CpG sites to estimate the leukocyte fraction in a tissue with leukocyte infiltration were selected, and an estimation algorithm was established. The fractions of infiltrating leukocytes were estimated to be 1.6-12.4% in the stomach (n = 10) with Helicobacter pylori-induced inflammation and 1.5-4.3% in the colon with dextran sulfate sodium-induced colitis (n = 4), and the fractions were highly correlated with those estimated histologically using Cd45-stained tissue sections [R = 0.811 (p = 0.004)]. These results showed that mouse methylation profiles at CpG sites within enhancers reflected leukocyte cell lineages, and the use of marker CpG sites successfully estimated the leukocyte fraction in inflamed gastric and colon tissues.
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Affiliation(s)
- Kazuhiro Nishiyama
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Division of Surgery, University of Kyoto, Kyoto, Japan
| | - Hitomi Nishinakamura
- Division of Cancer Immunology, Research Institute/Exploratory Oncology Research & Clinical Trial Center (EPOC), National Cancer Center, Tokyo, Chiba, Japan
| | - Hideyuki Takeshima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Liu Yuyu
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Chihiro Takeuchi
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Naoko Hattori
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Haruna Takeda
- Laboratory of Molecular Genetics, National Cancer Center Research Institute, Tokyo, Japan
| | - Satoshi Yamashita
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Life Engineering, Faculty of Engineering, Maebashi Institute of Technology, Maebashi, Japan
| | - Mika Wakabayashi
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
| | - Kotomi Sato
- Laboratory of Molecular Genetics, National Cancer Center Research Institute, Tokyo, Japan
| | | | - Toshikazu Ushijima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo, Japan
- Department of Epigenomics, Institute for Advanced Life Sciences, Hoshi University, Tokyo, Japan
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Chen JQ, Salas LA, Wiencke JK, Koestler DC, Molinaro AM, Andrew AS, Seigne JD, Karagas MR, Kelsey KT, Christensen BC. Genome-Scale Methylation Analysis Identifies Immune Profiles and Age Acceleration Associations with Bladder Cancer Outcomes. Cancer Epidemiol Biomarkers Prev 2023; 32:1328-1337. [PMID: 37527159 PMCID: PMC10543967 DOI: 10.1158/1055-9965.epi-23-0331] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/06/2023] [Accepted: 07/28/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND Immune profiles have been associated with bladder cancer outcomes and may have clinical applications for prognosis. However, associations of detailed immune cell subtypes with patient outcomes remain underexplored and may contribute crucial prognostic information for better managing bladder cancer recurrence and survival. METHODS Bladder cancer case peripheral blood DNA methylation was measured using the Illumina HumanMethylationEPIC array. Extended cell-type deconvolution quantified 12 immune cell-type proportions, including memory, naïve T and B cells, and granulocyte subtypes. DNA methylation clocks determined biological age. Cox proportional hazards models tested associations of immune cell profiles and age acceleration with bladder cancer outcomes. The partDSA algorithm discriminated 10-year overall survival groups from clinical variables and immune cell profiles, and a semi-supervised recursively partitioned mixture model (SS-RPMM) with DNA methylation data was applied to identify a classifier for 10-year overall survival. RESULTS Higher CD8T memory cell proportions were associated with better overall survival [HR = 0.95, 95% confidence interval (CI) = 0.93-0.98], while higher neutrophil-to-lymphocyte ratio (HR = 1.36, 95% CI = 1.23-1.50), CD8T naïve (HR = 1.21, 95% CI = 1.04-1.41), neutrophil (HR = 1.04, 95% CI = 1.03-1.06) proportions, and age acceleration (HR = 1.06, 95% CI = 1.03-1.08) were associated with worse overall survival in patient with bladder cancer. partDSA and SS-RPMM classified five groups of subjects with significant differences in overall survival. CONCLUSIONS We identified associations between immune cell subtypes and age acceleration with bladder cancer outcomes. IMPACT The findings of this study suggest that bladder cancer outcomes are associated with specific methylation-derived immune cell-type proportions and age acceleration, and these factors could be potential prognostic biomarkers.
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Affiliation(s)
- Ji-Qing Chen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - Lucas A. Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - John K. Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Devin C. Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas
| | - Annette M. Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Angeline S. Andrew
- Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - John D. Seigne
- Department of Surgery, Section of Urology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - Margaret R. Karagas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
| | - Karl T. Kelsey
- Departments of Epidemiology and Pathology and Laboratory Medicine, Brown University, Providence, Rhode Island
| | - Brock C. Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
- Departments of Molecular and Systems Biology, and Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire
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47
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Zhu M, An D, Zhang J, Tang X, Wang Y, Zhu D. Genome-wide analysis of DNA methylation and its relationship with serum homocysteine levels in patients with hypertension. J Hypertens 2023; 41:1626-1633. [PMID: 37466420 DOI: 10.1097/hjh.0000000000003515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND Homocysteine (Hcy) is an independent risk factor for cardiovascular diseases, and elevated plasma Hcy levels could aggravate vascular injury in hypertension. Hyperhomocysteinemia can change the methylation status of global DNA and specific genes. In the present study, we aim to examine the comprehensive influence of Hcy levels on DNA methylation status in patients with hypertension. METHODS Epigenome-wide methylation profiles of the peripheral leukocyte DNA of 218 patients with hypertension were analyzed using the Illumina Infinium Methylation EPIC BeadChip. Differentially methylated positions (DMPs) associated with serum Hcy levels were identified by mixed linear regression with the adjustment of potential confounders. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to determine the potential functions of the identified DMPs. The association between the methylation level of DMPs and carotid-femoral pulse wave velocity (Cf-PWV) was also analyzed. RESULTS Five DMPs at cg13169662, cg03179312, cg21976560, cg25262698, and cg09433843 showed significant association with serum Hcy levels (false discovery rate-corrected P < 0.05). An additional six CpG sites met the threshold for suggestive significance ( P < 1 × 10 -6 ), among which three DMPs (cg25781123, cg26463106, and cg06679221) were annotated to THUMPD3 . Furthermore, the methylation levels of cg13169662 and cg25262698 (RPRD1A) were significantly associated with Cf-PWV. CONCLUSION Our results suggest that Hcy could induce DNA methylation alteration in patients with hypertension. Further functional research is warranted to elucidate the concrete role of DMPs in hypertension.
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Affiliation(s)
- Min Zhu
- Department of Cardiovascular Medicine, Research Center for Hypertension Management and Prevention in Community, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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48
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Lin Z, Lu Y, Yu G, Teng H, Wang B, Yang Y, Li Q, Sun Z, Xu S, Wang W, Tian P. Genome-wide DNA methylation landscape of four Chinese populations and epigenetic variation linked to Tibetan high-altitude adaptation. SCIENCE CHINA. LIFE SCIENCES 2023; 66:2354-2369. [PMID: 37115492 DOI: 10.1007/s11427-022-2284-8] [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: 10/28/2022] [Accepted: 01/18/2023] [Indexed: 04/29/2023]
Abstract
DNA methylation (DNAm) is one of the major epigenetic mechanisms in humans and is important in diverse cellular processes. The variation of DNAm in the human population is related to both genetic and environmental factors. However, the DNAm profiles have not been investigated in the Chinese population of diverse ethnicities. Here, we performed double-strand bisulfite sequencing (DSBS) for 32 Chinese individuals representing four major ethnic groups including Han Chinese, Tibetan, Zhuang, and Mongolian. We identified a total of 604,649 SNPs and quantified DNAm at more than 14 million CpGs in the population. We found global DNAm-based epigenetic structure is different from the genetic structure of the population, and ethnic difference only partially explains the variation of DNAm. Surprisingly, non-ethnic-specific DNAm variations showed stronger correlation with the global genetic divergence than these ethnic-specific DNAm. Differentially methylated regions (DMRs) among these ethnic groups were found around genes in diverse biological processes. Especially, these DMR-genes between Tibetan and non-Tibetans were enriched around high-altitude genes including EPAS1 and EGLN1, suggesting DNAm alteration plays an important role in high-altitude adaptation. Our results provide the first batch of epigenetic maps for Chinese populations and the first evidence of the association of epigenetic changes with Tibetans' high-altitude adaptation.
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Affiliation(s)
- Zeshan Lin
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Guoliang Yu
- GrandOmics Biosciences, Beijing, 102200, China
| | - Huajing Teng
- Department of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, China
| | - Bao Wang
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Yajun Yang
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, 201203, China
| | - Qinglan Li
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhongsheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, 201203, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Wen Wang
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710072, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Peng Tian
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, China.
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49
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Kadalayil L, Alam MZ, White CH, Ghantous A, Walton E, Gruzieva O, Merid SK, Kumar A, Roy RP, Solomon O, Huen K, Eskenazi B, Rzehak P, Grote V, Langhendries JP, Verduci E, Ferre N, Gruszfeld D, Gao L, Guan W, Zeng X, Schisterman EF, Dou JF, Bakulski KM, Feinberg JI, Soomro MH, Pesce G, Baiz N, Isaevska E, Plusquin M, Vafeiadi M, Roumeliotaki T, Langie SAS, Standaert A, Allard C, Perron P, Bouchard L, van Meel ER, Felix JF, Jaddoe VWV, Yousefi PD, Ramlau-Hansen CH, Relton CL, Tobi EW, Starling AP, Yang IV, Llambrich M, Santorelli G, Lepeule J, Salas LA, Bustamante M, Ewart SL, Zhang H, Karmaus W, Röder S, Zenclussen AC, Jin J, Nystad W, Page CM, Magnus M, Jima DD, Hoyo C, Maguire RL, Kvist T, Czamara D, Räikkönen K, Gong T, Ullemar V, Rifas-Shiman SL, Oken E, Almqvist C, Karlsson R, Lahti J, Murphy SK, Håberg SE, London S, Herberth G, Arshad H, Sunyer J, Grazuleviciene R, Dabelea D, Steegers-Theunissen RPM, Nohr EA, Sørensen TIA, Duijts L, Hivert MF, Nelen V, Popovic M, Kogevinas M, Nawrot TS, Herceg Z, Annesi-Maesano I, Fallin MD, Yeung E, Breton CV, Koletzko B, Holland N, Wiemels JL, Melén E, Sharp GC, Silver MJ, Rezwan FI, Holloway JW. Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude. Clin Epigenetics 2023; 15:148. [PMID: 37697338 PMCID: PMC10496224 DOI: 10.1186/s13148-023-01542-5] [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: 02/13/2023] [Accepted: 07/27/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.
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Affiliation(s)
- Latha Kadalayil
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Md Zahangir Alam
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Cory Haley White
- Merck Exploratory Science Center in Cambridge MA, Merck Research Laboratories, Cambridge, MA, 02141, USA
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Simon Kebede Merid
- Centre for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Ashish Kumar
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Ritu P Roy
- Helen Diller Family Comprehensive Cancer Center University of California, San Francisco, CA, 94143, USA
- Computational Biology and Informatics Core, University of California, San Francisco, CA, 94143, USA
| | - Olivia Solomon
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Karen Huen
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | | | - Elvira Verduci
- Department of Pediatrics, Vittore Buzzi Children Hospital, University of Milan, Milan, Italy
| | - Natalia Ferre
- Pediatric Nutrition and Human Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Darek Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Lu Gao
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, 420 Delaware St. SE, Minneapolis, MN, 55455, USA
| | | | - Enrique F Schisterman
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Philadelphia, PA, 19104, USA
| | - John F Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - Jason I Feinberg
- Wendy Klag Center for Autism and Developmental Disabilities Johns Hopkins University, Baltimore, MD, USA
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Munawar Hussain Soomro
- Sorbonne Université and INSERM, Epidemiology of Allergic and Respiratory Diseases Department, Pierre Louis Institute of Epidemiology and Public Health (IPLESP UMRS 1136), Saint-Antoine Medical School, Paris Cedex 12, France
- Department of Community Medicine and Public Health, SMBB Medical University, Larkana, Pakistan
| | - Giancarlo Pesce
- Sorbonne Université and INSERM, Epidemiology of Allergic and Respiratory Diseases Department, Pierre Louis Institute of Epidemiology and Public Health (IPLESP UMRS 1136), Saint-Antoine Medical School, Paris Cedex 12, France
| | - Nour Baiz
- Institut Desbrest de Santé Publique (IDESP), INSERM and Montpellier University, Montpellier, France
| | - Elena Isaevska
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, CPO Piemonte, Italy
| | - Michelle Plusquin
- Center for Environmental Sciences, University of Hasselt, 3590, Diepenbeek, Belgium
| | - Marina Vafeiadi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Theano Roumeliotaki
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Sabine A S Langie
- Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium
- Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
- Department of Pharmacology and Toxicology, School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Limburg, The Netherlands
| | - Arnout Standaert
- Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier de l'Universite de Sherbrooke, Sherbrooke, Canada
| | - Patrice Perron
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, Canada
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Universite de Sherbrooke, Sherbrooke, Canada
- Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, Chicoutimi, Canada
| | - Evelien R van Meel
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Respiratory Medicine and Allergology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Elmar W Tobi
- Periconceptional Epidemiology, Department of Obstetrics and Gynecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Anne P Starling
- Life Course Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Maria Llambrich
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | - Johanna Lepeule
- Institute for Advanced Biosciences, University Grenoble-Alpes, INSERM, CNRS, Grenoble, France
| | - Lucas A Salas
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Center for Molecular Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Lebanon, NH, USA
| | - Mariona Bustamante
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Susan L Ewart
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Stefan Röder
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Ana Claudia Zenclussen
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Jianping Jin
- 2530 Meridian Pkwy, Suite 200, Durham, NC 27713, USA
| | - Wenche Nystad
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Section for Statistics and Data Science, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Maria Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Dereje D Jima
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Obstetrics and Gynaecology, Duke University Medical Center, Durham, NC, USA
| | - Tuomas Kvist
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, 80804, Munich, Germany
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Susan K Murphy
- Department of Obstetrics and Gynaecology, Duke University Medical Center, Durham, NC, USA
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie London
- Department of Health and Human Services, National Institute of Environmental Health Sciences, National Institutes of Health, RTP, NC, 27709, USA
| | - Gunda Herberth
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
- NIHR Southampton Biomedical Research Centre, Southampton General Hospital, Southampton, UK
| | - Jordi Sunyer
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Dana Dabelea
- Life Course Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Régine P M Steegers-Theunissen
- Periconceptional Epidemiology, Department of Obstetrics and Gynecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Ellen A Nohr
- Department of Clinical Research, Odense Universitetshospital, Odense, Denmark
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liesbeth Duijts
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Respiratory Medicine and Allergology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Neonatology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Vera Nelen
- Provincial Institute for Hygiene, Antwerp, Belgium
| | - Maja Popovic
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, CPO Piemonte, Italy
| | | | - Tim S Nawrot
- Center for Environmental Sciences, University of Hasselt, 3590, Diepenbeek, Belgium
- Department of Public Health and Primary Care, Leuven University, Louvain, Belgium
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Isabella Annesi-Maesano
- Institut Desbrest de Santé Publique (IDESP), INSERM and Montpellier University, Montpellier, France
| | - M Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities Johns Hopkins University, Baltimore, MD, USA
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Edwina Yeung
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, 6710B Rockledge Dr, MSC 7004, Bethesda, MD, USA
| | - Carrie V Breton
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Nina Holland
- Children's Environmental Health Laboratory, CERCH, Berkeley Public Health, University of California, 2121 Berkeley Way #5216, Berkeley, CA, 94720, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Gemma C Sharp
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychology, University of Exeter, Exeter, UK
| | - Matt J Silver
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, The Gambia
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, London, UK
| | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK.
- NIHR Southampton Biomedical Research Centre, Southampton General Hospital, Southampton, UK.
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50
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Luo Q, Dwaraka VB, Chen Q, Tong H, Zhu T, Seale K, Raffaele JM, Zheng SC, Mendez TL, Chen Y, Carreras N, Begum S, Mendez K, Voisin S, Eynon N, Lasky-Su JA, Smith R, Teschendorff AE. A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes. Genome Med 2023; 15:59. [PMID: 37525279 PMCID: PMC10388560 DOI: 10.1186/s13073-023-01211-5] [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: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.
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Affiliation(s)
- Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Varun B Dwaraka
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Tianyu Zhu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Joseph M Raffaele
- PhysioAge LLC, 30 Central Park South / Suite 8A, New York, NY, 10019, USA
| | - Shijie C Zheng
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Tavis L Mendez
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | | | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Nir Eynon
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
| | - Ryan Smith
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, 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, 320 Yue Yang Road, Shanghai, 200031, China.
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