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Ohlei O, Sommerer Y, Dobricic V, Homann J, Deecke L, Schilling M, Bartrés-Faz D, Cattaneo G, Düzel S, Fjell AM, Lindenberger U, Pascual-Leone Á, Sedghpour Sabet S, Solé-Padullés C, Tormos JM, Vetter VM, Walhovd KB, Wesse T, Wittig M, Franke A, Demuth I, Lill CM, Bertram L. Genome-wide QTL mapping across three tissues highlights several Alzheimer's and Parkinson's disease loci potentially acting via DNA methylation. medRxiv 2023:2023.12.22.23300365. [PMID: 38196633 PMCID: PMC10775408 DOI: 10.1101/2023.12.22.23300365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
DNA methylation (DNAm) is an epigenetic mark with essential roles in disease development and predisposition. Here, we created genome-wide maps of methylation quantitative trait loci (meQTL) in three peripheral tissues and used Mendelian randomization (MR) analyses to assess the potential causal relationships between DNAm and risk for two common neurodegenerative disorders, i.e. Alzheimer's disease (AD) and Parkinson's disease (PD). Genome-wide single nucleotide polymorphism (SNP; ~5.5M sites) and DNAm (~850K CpG sites) data were generated from whole blood (n=1,058), buccal (n=1,527) and saliva (n=837) specimens. We identified between 11 and 15 million genome-wide significant (p<10-14) SNP-CpG associations in each tissue. Combining these meQTL GWAS results with recent AD/PD GWAS summary statistics by MR strongly suggests that the previously described associations between PSMC3, PICALM, and TSPAN14 and AD may be founded on differential DNAm in or near these genes. In addition, there is strong, albeit less unequivocal, support for causal links between DNAm at PRDM7 in AD as well as at KANSL1/MAPT in AD and PD. Our study adds valuable insights on AD/PD pathogenesis by combining two high-resolution "omics" domains, and the meQTL data shared along with this publication will allow like-minded analyses in other diseases.
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Affiliation(s)
- Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Jan Homann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Laura Deecke
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Marcel Schilling
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, Barcelona, Spain
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Gabriele Cattaneo
- Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Camí de les Escoles, Badalona, Barcelona, Spain
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Álvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Josep M Tormos
- Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Camí de les Escoles, Badalona, Barcelona, Spain
| | - Valentin M Vetter
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases, Division of Lipid Metabolism, Charité-Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Ilja Demuth
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases, Division of Lipid Metabolism, Charité-Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christina M Lill
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
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2
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Sommerer Y, Dobricic V, Schilling M, Ohlei O, Sabet SS, Wesse T, Fuß J, Franzenburg S, Franke A, Parkkinen L, Lill CM, Bertram L. Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease. Alzheimers Res Ther 2023; 15:92. [PMID: 37149695 PMCID: PMC10163801 DOI: 10.1186/s13195-023-01232-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 04/15/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Studies on DNA methylation (DNAm) in Alzheimer's disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression. METHODS Here, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n = 337). RESULTS We identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braak's tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in the brains of AD patients vs. controls. CONCLUSION In summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression.
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Affiliation(s)
- Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Marcel Schilling
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Janina Fuß
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Sören Franzenburg
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Laura Parkkinen
- Nuffield Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
- Ageing Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany.
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway.
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Nyberg L, Andersson M, Lundquist A, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demnitz N, Drevon CA, Duezel S, Ebmeier KP, Ghisletta P, Henson R, Jensen DEA, Kievit RA, Knights E, Kühn S, Lindenberger U, Plachti A, Pudas S, Roe JM, Madsen KS, Solé-Padullés C, Sommerer Y, Suri S, Zsoldos E, Fjell AM, Walhovd KB. Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates. Cereb Cortex 2023; 33:5075-5081. [PMID: 36197324 PMCID: PMC10151879 DOI: 10.1093/cercor/bhac400] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 11/13/2022] Open
Abstract
It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.
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Affiliation(s)
- Lars Nyberg
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Micael Andersson
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Department of Statistics, USBE, Umeå University, Umeå S-90187, Sweden
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Faculty of Medical and Health Sciences, Institute for Clinical Medicine, University of Copenhagen, 2400 Copenhagen, Denmark
- Department of Neurology, Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital - Bispebjerg and Frederiksberg, 2400 Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- MSB Medical School Berlin, 14197 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Christian A Drevon
- Vitas AS, Science Park, 0349 Oslo, Norway
- Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo Norway
| | - Sandra Duezel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, 1204 Geneva, Switzerland
- UniDistance Suisse, 3900 Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, 1204 Geneva, Switzerland
| | - Richard Henson
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Daria E A Jensen
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, OX3 9DU Oxford, UK
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Ethan Knights
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Simone Kühn
- Lise Meitner Group for Environmental Neuroscience, Max Planck Institute for Human Development & Clinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - James M Roe
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, 2200 Copenhagen N, Denmark
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Sana Suri
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
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Demuth I, Düzel S, Vetter V, Drewelies J, Sommerer Y, Steinhagen-Thiessen E, Gerstorf D, Bertram L. RELATIONSHIP BETWEEN METABOLIC HEALTH AND 5 EPIGENETIC CLOCKS IN THE BERLIN AGING STUDY II (BASE-II). Innov Aging 2022. [PMCID: PMC9765848 DOI: 10.1093/geroni/igac059.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The diagnosis of metabolic syndrome (MetS) relies on cut-off values for five cardiovascular risk factors, three of which must be met to make the diagnosis. While this approach has certain advantages in the clinical setting, it only allows a binary classification relying on cut-off values. Thus, individuals receiving the same MetS diagnosis may differ in terms of disease severity. We have recently developed a continuous measure of the metabolic load (MetL) that was calculated as a latent factor from indicators that are used to diagnose the MetS enabling a more differentiated assessment. DNA methylation age acceleration (DNAmAA) is a widely accepted biomarker of aging which can be derived from a variety of epigenetic clocks. However, it is still unclear which aspects of aging these biomarkers represent best. Aim of the current study was to evaluate whether and how the MetS and MetL relate to DNAmAA derived from five epigenetic clocks (7-CpG clock, Horvath’s clock, Hannum’s clock, PhenoAge, and GrimAge). MetS was diagnosed according to the AHA/IDF/NHLBI criteria (2009) and the latent MetL factor was extracted from a confirmatory factor analysis considering the same diagnostic parameters. DNAmAA estimated from PhenoAge and GrimAge were significantly associated with MetS (beta=0.036 and beta=0.063, both p<0.05) and MetL (both beta=0.009 and p<0.05) in regression analyses adjusted for age and gender including 1,100 participants from the follow-up assessments of the Berlin Aging Study II (BASE-II, mean age 75.6 ±3.8 years). The results will be discussed with respect to clinical relevance in the context of current literature.
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Affiliation(s)
- Ilja Demuth
- Charité Universitätsmedizin Berlin, Berlin, Berlin, Germany
| | - Sandra Düzel
- Max Planck Institute for Human Development, Berlin, Berlin, Germany
| | - Valentin Vetter
- Charité - Universitätsmedizin Berlin, Berlin, Berlin, Germany
| | | | | | | | | | - Lars Bertram
- University of Lübeck, Lübeck, Schleswig-Holstein, Germany
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Vetter V, Sommerer Y, Kalies C, Spira D, Bertram L, Demuth I. VITAMIN D DEFICIENCY AND FASTER EPIGENETIC AGING: RESULTS FROM THE BERLIN AGING STUDY II (BASE-II). Innov Aging 2022. [PMCID: PMC9766449 DOI: 10.1093/geroni/igac059.1738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Particularly older people are at risk for deficient vitamin D levels, as their capability for cutaneous synthetization is lower and they are often less exposed to sunlight. However, the resulting impact on one individual’s health is not fully understood. To examine potential consequences of low vitamin D levels for health of older people, we examined its relationship with a DNA related biomarker of aging, DNA methylation age acceleration (DNAmAA). Several epigenetic clocks, that are used to estimate this parameter from methylation fractions of specific cytosine-phosphate-guanine sites, are available and differ in aspects of aging they represent best. Five clocks, 7-CpG clock, Horvath’s clock, Hannum’s clock, PhenoAge, and GrimAge, were available in the longitudinal BASE-II cohort (n=1,100) at follow-up examination. DNAmAA estimated from 7-CpG clock and GrimAge was associated with vitamin D levels in covariate adjusted regression analysis. Additionally, a quasi-interventional study design was employed and showed 2.6 year lower 7-CpG DNAmAA (p=0.011) and 1.3-year lower Horvath DNAmAA (p=0.042) in vitamin D deficient participants that chose to start vitamin D supplementation during the follow-up period of 7.4 ± 1.5 years compared to a matched control-group of participants with untreated vitamin D deficiency. No statistically significant difference was found between sufficiently treated participants with vitamin D deficiency and a matched group of participants that reached sufficient vitamin D level without supplementation. Although validation of our results in a randomized controlled trial is needed, our findings suggest, that vitamin D deficiency associated higher rates of epigenetic aging can potentially be reversed through supplementation.
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Affiliation(s)
- Valentin Vetter
- Charité - Universitätsmedizin Berlin, Berlin, Berlin, Germany
| | | | | | - Dominik Spira
- Charité - Universitätsmedizin Berlin, Berlin, Berlin, Germany
| | - Lars Bertram
- University of Lübeck, Lübeck, Schleswig-Holstein, Germany
| | - Ilja Demuth
- Charité Universitätsmedizin Berlin, Berlin, Berlin, Germany
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6
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Sommerer Y, Ohlei O, Dobricic V, Oakley DH, Wesse T, Sedghpour Sabet S, Demuth I, Franke A, Hyman BT, Lill CM, Bertram L. A correlation map of genome-wide DNA methylation patterns between paired human brain and buccal samples. Clin Epigenetics 2022; 14:139. [PMID: 36320053 PMCID: PMC9628033 DOI: 10.1186/s13148-022-01357-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Epigenome-wide association studies (EWAS) assessing the link between DNA methylation (DNAm) and phenotypes related to structural brain measures, cognitive function, and neurodegenerative diseases are becoming increasingly more popular. Due to the inaccessibility of brain tissue in humans, several studies use peripheral tissues such as blood, buccal swabs, and saliva as surrogates. To aid the functional interpretation of EWAS findings in such settings, there is a need to assess the correlation of DNAm variability across tissues in the same individuals. In this study, we performed a correlation analysis between DNAm data of a total of n = 120 matched post-mortem buccal and prefrontal cortex samples. We identified nearly 25,000 (3% of approximately 730,000) cytosine-phosphate-guanine (CpG) sites showing significant (false discovery rate q < 0.05) correlations between buccal and PFC samples. Correlated CpG sites showed a preponderance to being located in promoter regions and showed a significant enrichment of being determined by genetic factors, i.e. methylation quantitative trait loci (mQTL), based on buccal and dorsolateral prefrontal cortex mQTL databases. Our novel buccal–brain DNAm correlation map will provide a valuable resource for future EWAS using buccal samples for studying DNAm effects on phenotypes relating to the brain. All correlation results are made freely available to the public online.
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Affiliation(s)
- Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Derek H Oakley
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Division of Lipid Metabolism, Department of Endocrinology and Metabolic Diseases, Berlin Institute of Health, Berlin, Germany.,BCRT - Berlin Institute of Health Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany.,Ageing Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.,Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany. .,Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Oslo, Norway.
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7
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Vetter VM, Sommerer Y, Kalies CH, Spira D, Bertram L, Demuth I. Vitamin D supplementation is associated with slower epigenetic aging. GeroScience 2022; 44:1847-1859. [PMID: 35562603 PMCID: PMC9213628 DOI: 10.1007/s11357-022-00581-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/26/2022] [Indexed: 11/21/2022] Open
Abstract
Adverse effects of low vitamin D level on mortality and morbidity are controversially discussed. Especially older people are at risk for vitamin D deficiency and therefore exposed to its potentially harmful consequences. A way of measuring differences in the biological age is through DNA methylation age (DNAm age) and its deviation from chronological age, DNAm age acceleration (DNAmAA). We previously reported on an association between vitamin D deficiency and higher 7-CpG DNAmAA in participants of the Berlin Aging Study II (BASE-II). In this study, we employ a quasi-interventional study design to assess the relationship between DNAmAA of five epigenetic clocks and vitamin D supplementation. Longitudinal data were available for 1,036 participants of BASE-II that were reexamined on average 7.4 years later in the GendAge study (mean age at follow-up: 75.6 years, SD = 3.8 years, age range: 64.9–94.1 years, 51.9% female). DNAmAA was estimated with the 7-CpG clock, Horvath’s clock, Hannum’s clock, PhenoAge, and GrimAge. Methylation data were obtained through methylation-sensitive single nucleotide primer extension (MS-SNuPE) or Illumina’s Infinium “MethylationEPIC” array. Vitamin D–deficient participants who chose to start vitamin D supplementation after baseline examination showed a 2.6-year lower 7-CpG DNAmAA (p = 0.011) and 1.3-year lower Horvath DNAmAA (p = 0.042) compared to untreated and vitamin D–deficient participants. DNAmAA did not statistically differ between participants with successfully treated vitamin D deficiency and healthy controls (p > 0.16). Therefore, we conclude that intake of vitamin D supplement is associated with lower DNAmAA in participants with vitamin D deficiency.
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Affiliation(s)
- Valentin Max Vetter
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Department of Psychology, Humboldt University Berlin, Berlin, Germany
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Christian Humberto Kalies
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Dominik Spira
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Ilja Demuth
- Biology of Aging Working Group, Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
- BCRT - Berlin Institute of Health Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Biology of Aging Group, Lipid Clinic at the Interdisciplinary Metabolism Center, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
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Vetter VM, Kalies CH, Sommerer Y, Bertram L, Demuth I. Seven-CpG DNA Methylation Age Determined by Single Nucleotide Primer Extension and Illumina's Infinium MethylationEPIC Array Provide Highly Comparable Results. Front Genet 2022; 12:759357. [PMID: 35111197 PMCID: PMC8802213 DOI: 10.3389/fgene.2021.759357] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/14/2021] [Indexed: 11/24/2022] Open
Abstract
DNA methylation age (DNAm age, epigenetic clock) is a novel and promising biomarker of aging. It is calculated from the methylation fraction of specific cytosine phosphate guanine sites (CpG sites) of genomic DNA. Several groups have proposed epigenetic clock algorithms and these differ mostly regarding the number and location of the CpG sites considered and the method used to assess the methylation status. Most epigenetic clocks are based on a large number of CpGs, e.g. as measured by DNAm microarrays. We have recently evaluated an epigenetic clock based on the methylation fraction of seven CpGs that were determined by methylation-sensitive single nucleotide primer extension (MS-SNuPE). This method is more cost-effective when compared to array-based technologies as only a few CpGs need to be examined. However, there is only little data on the correspondence in epigenetic age estimation using the 7-CpG clock and other algorithms. To bridge this gap, in this study we measured the 7-CpG DNAm age using two methods, via MS-SNuPE and via the MethylationEPIC array, in a sample of 1,058 participants of the Berlin Aging Study II (BASE-II), assessed as part of the GendAge study. On average, participants were 75.6 years old (SD: 3.7, age range: 64.9-90.0, 52.6% female). Agreement between methods was assessed by Bland-Altman plots. DNAm age was highly correlated between methods (Pearson's r = 0.9) and Bland-Altman plots showed a difference of 3.1 years. DNAm age by the 7-CpG formula was 71.2 years (SD: 6.9 years, SNuPE) and 68.1 years (SD: 6.4 years, EPIC array). The mean of difference in methylation fraction between methods for the seven individual CpG sites was between 0.7 and 13 percent. To allow direct conversion of DNAm age obtained from both methods we developed an adjustment formula with a randomly selected training set of 529 participants using linear regression. After conversion of the Illumina data in a second and independent validation set, the adjusted DNAm age was 71.44 years (SD: 6.1 years, n = 529). In summary, we found the results of DNAm clocks to be highly comparable. Furthermore, we developed an adjustment formula that allows for direct conversion of DNAm age estimates between methods and enables one singular clock to be used in studies that employ either the Illumina or the SNuPE method.
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Affiliation(s)
- Valentin Max Vetter
- Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Biology of Aging Working Group, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, Humboldt University Berlin, Berlin, Germany
| | - Christian Humberto Kalies
- Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Biology of Aging Working Group, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
- Center for Lifespan Changes in Brain and Cognition (LCBC), Dept of Psychology, University of Oslo, Oslo, Norway
| | - Ilja Demuth
- Department of Endocrinology and Metabolic Diseases (Including Division of Lipid Metabolism), Biology of Aging Working Group, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, BCRT - Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
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Vetter VM, Kalies CH, Sommerer Y, Spira D, Drewelies J, Regitz-Zagrosek V, Bertram L, Gerstorf D, Demuth I. Relationship between five Epigenetic Clocks, Telomere Length and Functional Capacity assessed in Older Adults: Cross-sectional and Longitudinal Analyses. J Gerontol A Biol Sci Med Sci 2022; 77:1724-1733. [PMID: 35032170 DOI: 10.1093/gerona/glab381] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Indexed: 11/14/2022] Open
Abstract
DNA methylation age acceleration (DNAmAA, derived from an epigenetic clock) and relative leukocyte telomere length (rLTL) are widely accepted biomarkers of aging. Nevertheless, it is still unclear which aspects of aging they represent best. Here we evaluated longitudinal associations between baseline rLTL and DNAmAA (estimated with 7-CpG clock) and functional assessments covering different domains of aging. Additionally, we made use of cross-sectional data on these assessments and examined their association with DNAmAA estimated by five different DNAm age measures. Two-wave longitudinal data was available for 1,083 participants of the Berlin Aging Study II (BASE-II) who were re-examined on average 7.4 years after baseline as part of the GendAge study. Functional outcomes were assessed with Fried's frailty score, Tinetti mobility test, falls in the past 12 months (yes/no), Finger-floor distance, Mini Mental State Examination (MMSE), Center for Epidemiologic Studies Depression Scale (CES-D), Activities of Daily Living (ADL), Instrumented ADL (IADL) and Mini Nutritional Assessment (MNA). Overall, we found no evidence for an association between the molecular biomarkers measured at baseline, rLTL and DNAmAA (7-CpG clock), and functional assessments assessed at follow-up. Similarly, a cross-sectional analyses of follow-up data did also not show evidence for associations of the various DNAmAA measures (7-CpG clock, Horvath's clock, Hannum's clock PhenoAge, and GrimAge) with functional assessments. In conclusion, neither rLTL nor 7-CpG DNAmAA were able to predict impairment in the analyzed assessments over a ~7-year time-course. Similarly, DNAmAA estimated from five epigenetic clocks was not a good cross-sectional marker of health deterioration either.
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Affiliation(s)
- Valentin Max Vetter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Germany.,Department of Psychology, Humboldt University Berlin, Berlin, Germany
| | - Christian Humberto Kalies
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Germany
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Dominik Spira
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Germany
| | - Johanna Drewelies
- Department of Psychology, Humboldt University Berlin, Berlin, Germany
| | - Vera Regitz-Zagrosek
- Institute for Gender in Medicine, Center for Cardiovascular Research, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Cardiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.,Center for Lifespan Changes in Brain and Cognition (LCBC), Dept of Psychology, University of Oslo, Oslo, Norway
| | - Denis Gerstorf
- Department of Psychology, Humboldt University Berlin, Berlin, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Germany.,Charité - Universitätsmedizin Berlin, BCRT - Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
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