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Eisenberg DTA, Ryan CP, Lee NR, Carba DB, MacIsaac JL, Dever K, Atashzay P, Kobor MS, Kuzawa C. DNA methylation-based estimators of telomere length show low correspondence with paternal age at conception and other measures of external validity of telomere length. GeroScience 2024:10.1007/s11357-024-01114-2. [PMID: 38466455 DOI: 10.1007/s11357-024-01114-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/09/2024] [Indexed: 03/13/2024] Open
Abstract
In humans, DNA methylation (DNAm) based estimators of telomere length (TL) have been shown to better predict TL-associated variables (e.g., age, sex, and mortality) than TL itself. The biological significance of DNAm-based estimators of TL (DNAmTL) is unclear. In vitro DNAmTL shortens with cell replications, even when telomerase is maintaining TL. Telomerase is typically suppressed in humans, except in testes. Accordingly, sperm TL increases with age, and offspring with greater paternal age at conception (PAC) have longer TL. Thus, we expect that PAC associations with DNAmTL can shed light on whether in vivo cell replications in the presence of high telomerase activity (production of sperm) shorten DNAmTL or if PAC-lengthened TL causes lengthened DNAmTL. In a pre-registered analysis, using data from 1733 blood samples from the Philippines, we examined the association between paternal age at conception (PAC) and offspring DNAmTL. We did not find an association between PAC and DNAmTL but found a positive association of paternal grandfather's age at father's conception predicting grandchild's DNAmTL. In post hoc analyses, we examined how DNAmTL versus qPCR-measured TL (qPCR-TL) correlated with measures typically associated with TL. Contrary to previous findings, on almost all measures of external validity (correlations with parental TLs, southern blot TL, and age), qPCR-TL outperformed DNAmTL. The "kilobase" units of DNAm-based estimators of TL showed considerable deviations from southern blot-derived kilobase measures. Our findings suggest that DNAmTL is not a reliable index of inherited aspects of TL and underscores uncertainty about the biological meaning of DNAmTL.
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Affiliation(s)
- Dan T A Eisenberg
- Department of Anthropology, University of Washington, Seattle, WA, USA.
- Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA.
| | - Calen P Ryan
- Columbia Aging Center GeroScience Computational Core, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Delia B Carba
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Julie L MacIsaac
- Edwin S.H. Leong Healthy Aging Program, Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Kristy Dever
- Edwin S.H. Leong Healthy Aging Program, Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Parmida Atashzay
- Edwin S.H. Leong Healthy Aging Program, Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Michael S Kobor
- Edwin S.H. Leong Healthy Aging Program, Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Christopher Kuzawa
- Department of Anthropology, Northwestern University; Institute for Policy Research, Northwestern University, Evanston, IL, USA
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Zillich L, Cetin M, Hummel EM, Poisel E, Fries GR, Frank J, Streit F, Foo JC, Sirignano L, Friske MM, Lenz B, Hoffmann S, Adorjan K, Kiefer F, Bakalkin G, Hansson AC, Lohoff FW, Kärkkäinen O, Kok E, Karhunen PJ, Sutherland GT, Walss-Bass C, Spanagel R, Rietschel M, Moser DA, Witt SH. Biological aging markers in blood and brain tissue indicate age acceleration in alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:250-259. [PMID: 38276909 PMCID: PMC10922212 DOI: 10.1111/acer.15241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 01/27/2024]
Abstract
BACKGROUND Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation-related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken. METHODS As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63-94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates. RESULTS The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain. CONCLUSIONS The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain.
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Affiliation(s)
- Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Metin Cetin
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Elisabeth M. Hummel
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, Germany
| | - Eric Poisel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gabriel R. Fries
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, 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
| | - Jerome C. Foo
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marion M. Friske
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Bernd Lenz
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabine Hoffmann
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Georgy Bakalkin
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Anita C. Hansson
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Falk W. Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Olli Kärkkäinen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Eloise Kok
- Department of Pathology, University of Helsinki, Helsinki, Finland and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pekka J. Karhunen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories Ltd., Pirkanmaa Hospital District, and Finnish Cardiovascular Research Centre Tampere, Tampere, Finland
| | - Greg T Sutherland
- Charles Perkins Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Consuelo Walss-Bass
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Rainer Spanagel
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dirk A. Moser
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, 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
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Ferrer A, Stephens ZD, Kocher JPA. Experimental and Computational Approaches to Measure Telomere Length: Recent Advances and Future Directions. Curr Hematol Malig Rep 2023; 18:284-291. [PMID: 37947937 PMCID: PMC10709248 DOI: 10.1007/s11899-023-00717-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/30/2023] [Indexed: 11/12/2023]
Abstract
PURPOSE OF REVIEW The length of telomeres, protective structures at the chromosome ends, is a well-established biomarker for pathological conditions including multisystemic syndromes called telomere biology disorders. Approaches to measure telomere length (TL) differ on whether they estimate average, distribution, or chromosome-specific TL, and each presents their own advantages and limitations. RECENT FINDINGS The development of long-read sequencing and publication of the telomere-to-telomere human genome reference has allowed for scalable and high-resolution TL estimation in pre-existing sequencing datasets but is still impractical as a dedicated TL test. As sequencing costs continue to fall and strategies for selectively enriching telomere regions prior to sequencing improve, these approaches may become a promising alternative to classic methods. Measurement methods rely on probe hybridization, qPCR or more recently, computational methods using sequencing data. Refinements of existing techniques and new approaches have been recently developed but a test that is accurate, simple, and scalable is still lacking.
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Affiliation(s)
- Alejandro Ferrer
- Division of Hematology, Mayo Clinic, Rochester, 200 First Street SW, Rochester, MN, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
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Coltell O, Asensio EM, Sorlí JV, Ortega-Azorín C, Fernández-Carrión R, Pascual EC, Barragán R, González JI, Estruch R, Alzate JF, Pérez-Fidalgo A, Portolés O, Ordovas JM, Corella D. Associations between the New DNA-Methylation-Based Telomere Length Estimator, the Mediterranean Diet and Genetics in a Spanish Population at High Cardiovascular Risk. Antioxidants (Basel) 2023; 12:2004. [PMID: 38001857 PMCID: PMC10669035 DOI: 10.3390/antiox12112004] [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: 10/26/2023] [Revised: 11/10/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Biological aging is a relevant risk factor for chronic diseases, and several indicators for measuring this factor have been proposed, with telomere length (TL) among the most studied. Oxidative stress may regulate telomere shortening, which is implicated in the increased risk. Using a novel estimator for TL, we examined whether adherence to the Mediterranean diet (MedDiet), a highly antioxidant-rich dietary pattern, is associated with longer TL. We determined TL using DNA methylation algorithms (DNAmTL) in 414 subjects at high cardiovascular risk from Spain. Adherence to the MedDiet was assessed by a validated score, and genetic variants in candidate genes and at the genome-wide level were analyzed. We observed several significant associations (p < 0.05) between DNAmTL and candidate genes (TERT, TERF2, RTEL1, and DCAF4), contributing to the validity of DNAmTL as a biomarker in this population. Higher adherence to the MedDiet was associated with lower odds of having a shorter TL in the whole sample (OR = 0.93; 95% CI: 0.85-0.99; p = 0.049 after fully multivariate adjustment). Nevertheless, this association was stronger in women than in men. Likewise, in women, we observed a direct association between adherence to the MedDiet score and DNAmTL as a continuous variable (beta = 0.015; SE: 0.005; p = 0.003), indicating that a one-point increase in adherence was related to an average increase of 0.015 ± 0.005 kb in TL. Upon examination of specific dietary items within the global score, we found that fruits, fish, "sofrito", and whole grains exhibited the strongest associations in women. The novel score combining these items was significantly associated in the whole population. In the genome-wide association study (GWAS), we identified ten polymorphisms at the suggestive level of significance (p < 1 × 10-5) for DNAmTL (intergenics, in the IQSEC1, NCAPG2, and ABI3BP genes) and detected some gene-MedDiet modulations on DNAmTL. As this is the first study analyzing the DNAmTL estimator, genetics, and modulation by the MedDiet, more studies are needed to confirm these findings.
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Affiliation(s)
- Oscar Coltell
- Department of Computer Languages and Systems, Universitat Jaume I, 12071 Castellón, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
| | - Eva M. Asensio
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - José V. Sorlí
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Carolina Ortega-Azorín
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Rebeca Fernández-Carrión
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Eva C. Pascual
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Rocío Barragán
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - José I. González
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Ramon Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain
| | - Juan F. Alzate
- Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad de Antioquia, Medellín 050010, Colombia
- Facultad de Medicina, Centro Nacional de Secuenciación Genómica—CNSG, Sede de Investigación Universitaria—SIU, Universidad de Antioquia, Medellín 050010, Colombia
| | - Alejandro Pérez-Fidalgo
- Department of Medical Oncology, University Clinic Hospital of Valencia, 46010 Valencia, Spain; (A.P.-F.)
- Biomedical Research Networking Centre on Cancer (CIBERONC), Health Institute Carlos III, 28029 Madrid, Spain
- INCLIVA Biomedical Research Institute, 46010 Valencia, Spain
| | - Olga Portolés
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
| | - Jose M. Ordovas
- Department of Medical Oncology, University Clinic Hospital of Valencia, 46010 Valencia, Spain; (A.P.-F.)
- Nutrition and Genomics, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, UAM + CSIC, 28049 Madrid, Spain
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain; (E.M.A.); (C.O.-A.); (J.I.G.); (R.E.)
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain
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Waziry R, Gu Y, Williams O, Hägg S. Connections between cross-tissue and intra-tissue biomarkers of aging biology in older adults. EPIGENETICS COMMUNICATIONS 2023; 3:7. [PMID: 38037563 PMCID: PMC10688599 DOI: 10.1186/s43682-023-00022-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 09/28/2023] [Indexed: 12/02/2023]
Abstract
Background Saliva measures are generally more accessible than blood, especially in vulnerable populations. However, connections between aging biology biomarkers in different body tissues remain unknown. Methods The present study included individuals (N = 2406) who consented for saliva and blood draw in the Health and Retirement Telomere length study in 2008 and the Venous blood study in 2016 who had complete data for both tissues. We assessed biological aging based on telomere length in saliva and DNA methylation and physiology measures in blood. DNA methylation clocks combine information from CpGs to produce the aging measures representative of epigenetic aging in humans. We analyzed DNA methylation clocks proposed by Horvath (353 CpG sites), Hannum (71 CpG sites), Levine or PhenoAge, (513 CpG sites), GrimAge, (epigenetic surrogate markers for select plasma proteins), Horvath skin and blood (391 CpG sites), Lin (99 CpG sites), Weidner (3 CpG sites), and VidalBralo (8 CpG sites). Physiology measures (referred to as phenotypic age) included albumin, creatinine, glucose, [log] C-reactive protein, lymphocyte percent, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count. The phenotypic age algorithm is based on parametrization of Gompertz proportional hazard models. Average telomere length was assayed using quantitative PCR (qPCR) by comparing the telomere sequence copy number in each patient's sample (T) to a single-copy gene copy number (S). The resulting T/S ratio was proportional to telomere length, mean. Within individual, relationships between aging biology measures in blood and saliva and variations according to sex were assessed. Results Saliva-based telomere length showed inverse associations with both physiology-based and DNA methylation-based aging biology biomarkers in blood. Longer saliva-based telomere length was associated with 1 to 4 years slower biological aging based on blood-based biomarkers with the highest magnitude being Weidner (β = - 3.97, P = 0.005), GrimAge (β = - 3.33, P < 0.001), and Lin (β = - 3.45, P = 0.008) biomarkers of DNA methylation. Conclusions There are strong connections between aging biology biomarkers in saliva and blood in older adults. Changes in telomere length vary with changes in DNA methylation and physiology biomarkers of aging biology. We observed variations in the relationship between each body system represented by physiology biomarkers and biological aging, particularly at the DNA methylation level. These observations provide novel opportunities for integration of both blood-based and saliva-based biomarkers in clinical care of vulnerable and clinically difficult to reach populations where either or both tissues would be accessible for clinical monitoring purposes.
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Affiliation(s)
- R. Waziry
- Department of Neurology, Columbia University Irving Medical Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Y. Gu
- Department of Neurology, Columbia University Irving Medical Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- The Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- The Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - O. Williams
- Department of Neurology, Columbia University Irving Medical Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - S. Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
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Carlund O, Norberg A, Osterman P, Landfors M, Degerman S, Hultdin M. DNA methylation variations and epigenetic aging in telomere biology disorders. Sci Rep 2023; 13:7955. [PMID: 37193737 DOI: 10.1038/s41598-023-34922-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/10/2023] [Indexed: 05/18/2023] Open
Abstract
Telomere Biology Disorders (TBDs) are characterized by mutations in telomere-related genes leading to short telomeres and premature aging but with no strict correlation between telomere length and disease severity. Epigenetic alterations are also markers of aging and we aimed to evaluate whether DNA methylation (DNAm) could be part of the pathogenesis of TBDs. In blood from 35 TBD cases, genome-wide DNAm were analyzed and the cases were grouped based on relative telomere length (RTL): short (S), with RTL close to normal controls, and extremely short (ES). TBD cases had increased epigenetic age and DNAm alterations were most prominent in the ES-RTL group. Thus, the differentially methylated (DM) CpG sites could be markers of short telomeres but could also be one of the mechanisms contributing to disease phenotype since DNAm alterations were observed in symptomatic, but not asymptomatic, cases with S-RTL. Furthermore, two or more DM-CpGs were identified in four genes previously linked to TBD or telomere length (PRDM8, SMC4, VARS, and WNT6) and in three genes that were novel in telomere biology (MAS1L, NAV2, and TM4FS1). The DM-CpGs in these genes could be markers of aging in hematological cells, but they could also be of relevance for the progression of TBD.
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Affiliation(s)
- Olivia Carlund
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Anna Norberg
- Department of Medical Biosciences, Medical and Clinical Genetics, Umeå University, Umeå, Sweden
| | - Pia Osterman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Mattias Landfors
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Sofie Degerman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Magnus Hultdin
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.
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Doherty T, Dempster E, Hannon E, Mill J, Poulton R, Corcoran D, Sugden K, Williams B, Caspi A, Moffitt TE, Delany SJ, Murphy TM. A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator. BMC Bioinformatics 2023; 24:178. [PMID: 37127563 PMCID: PMC10152624 DOI: 10.1186/s12859-023-05282-4] [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: 03/29/2022] [Accepted: 04/11/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine-guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We utilised both nested cross-validation and two independent test sets for the comparisons. RESULTS We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. This approach achieved a correlation between estimated and actual TL of 0.295 (83.4% CI [0.201, 0.384]) on the EXTEND test data set. Contrastingly, the baseline model of elastic net regression with no prior feature reduction stage performed less well in general-suggesting a prior feature-selection stage may have important utility. A previously developed TL estimator, DNAmTL, achieved a correlation of 0.216 (83.4% CI [0.118, 0.310]) on the EXTEND data. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. CONCLUSIONS The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.
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Affiliation(s)
- Trevor Doherty
- School of Biological, Health and Sports Sciences, Technological University Dublin, Dublin, Ireland.
- SFI Centre for Research Training in Machine Learning, Technological University Dublin, Dublin, Ireland.
| | - Emma Dempster
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Richie Poulton
- Department of Psychology, University of Otago, Dunedin, 9016, New Zealand
| | - David Corcoran
- Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Ben Williams
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Avshalom Caspi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Terrie E Moffitt
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Sarah Jane Delany
- School of Computer Science, Technological University Dublin, Dublin, Ireland
| | - Therese M Murphy
- School of Biological, Health and Sports Sciences, Technological University Dublin, Dublin, Ireland
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Pearce EE, Alsaggaf R, Katta S, Dagnall C, Aubert G, Hicks BD, Spellman SR, Savage SA, Horvath S, Gadalla SM. Telomere length and epigenetic clocks as markers of cellular aging: a comparative study. GeroScience 2022; 44:1861-1869. [PMID: 35585300 DOI: 10.1007/s11357-022-00586-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 05/06/2022] [Indexed: 12/11/2022] Open
Abstract
Telomere length (TL) and DNA methylation-based epigenetic clocks are markers of biological age, but the relationship between the two is not fully understood. Here, we used multivariable regression models to evaluate the relationships between leukocyte TL (LTL; measured by qPCR [n = 635] or flow FISH [n = 144]) and five epigenetic clocks (Hannum, DNAmAge pan-tissue, PhenoAge, SkinBlood, or GrimAge clocks), or their epigenetic age acceleration measures in healthy adults (age 19-61 years). LTL showed statistically significant negative correlations with all clocks (qPCR: r = - 0.26 to - 0.32; flow FISH: r = - 0.34 to - 0.49; p < 0.001 for all). Yet, models adjusted for age, sex, and race revealed significant associations between three of five clocks (PhenoAge, GrimAge, and Hannum clocks) and LTL by flow FISH (p < 0.01 for all) or qPCR (p < 0.001 for all). Significant associations between age acceleration measures for the same three clocks and qPCR or flow FISH TL were also found (p < 0.01 for all). Additionally, LTL (by qPCR or flow FISH) showed significant associations with extrinsic epigenetic age acceleration (EEAA: p < 0.0001 for both), but not intrinsic epigenetic age acceleration (IEAA; p > 0.05 for both). In conclusion, the relationships between LTL and epigenetic clocks were limited to clocks reflecting phenotypic age. The observed association between LTL and EEAA reflects the ability of both measures to detect immunosenescence. The observed modest correlations between LTL and epigenetic clocks highlight a possible benefit from incorporating both measures in understanding disease etiology and prognosis.
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Affiliation(s)
- Emily E Pearce
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Rotana Alsaggaf
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Shilpa Katta
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.,Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Casey Dagnall
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.,Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Geraldine Aubert
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, V5Z 1L3, Canada
| | - Belynda D Hicks
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.,Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Stephen R Spellman
- Center for International Blood and Marrow Transplant Research, Minneapolis, MN, 55401, USA
| | - Sharon A Savage
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
| | - Shahinaz M Gadalla
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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9
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Pantziarka P, Blagden S. Inhibiting the Priming for Cancer in Li-Fraumeni Syndrome. Cancers (Basel) 2022; 14:cancers14071621. [PMID: 35406393 PMCID: PMC8997074 DOI: 10.3390/cancers14071621] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/08/2022] [Accepted: 03/20/2022] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Li-Fraumeni Syndrome (LFS) is a rare cancer pre-disposition syndrome associated with a germline mutation in the TP53 tumour suppressor gene. People with LFS have a 90% chance of suffering one or more cancers in their lifetime. No treatments exist to reduce this cancer risk. This paper reviews the evidence for how cancers start in people with LFS and proposes that a series of commonly used non-cancer drugs, including metformin and aspirin, can help reduce that lifetime risk of cancer. Abstract The concept of the pre-cancerous niche applies the ‘seed and soil’ theory of metastasis to the initial process of carcinogenesis. TP53 is at the nexus of this process and, in the context of Li-Fraumeni Syndrome (LFS), is a key determinant of the conditions in which cancers are formed and progress. Important factors in the creation of the pre-cancerous niche include disrupted tissue homeostasis, cellular metabolism and chronic inflammation. While druggability of TP53 remains a challenge, there is evidence that drug re-purposing may be able to address aspects of pre-cancerous niche formation and thereby reduce the risk of cancer in individuals with LFS.
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Affiliation(s)
- Pan Pantziarka
- The George Pantziarka TP53 Trust, London KT1 2JP, UK
- The Anti-Cancer Fund, Brusselsesteenweg 11, 1860 Meise, Belgium
- Correspondence:
| | - Sarah Blagden
- Department of Oncology, University of Oxford, Oxford OX3 7DQ, UK;
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10
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Hastings WJ, Etzel L, Heim CM, Noll JG, Rose EJ, Schreier HMC, Shenk CE, Tang X, Shalev I. Comparing qPCR and DNA methylation-based measurements of telomere length in a high-risk pediatric cohort. Aging (Albany NY) 2022; 14:660-677. [PMID: 35077392 PMCID: PMC8833135 DOI: 10.18632/aging.203849] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 01/17/2022] [Indexed: 11/25/2022]
Abstract
Various approaches exist to assess population differences in biological aging. Telomere length (TL) is one such measure, and is associated with disease, disability and early mortality. Yet, issues surrounding precision and reproducibility are a concern for TL measurement. An alternative method to estimate TL using DNA methylation (DNAmTL) was recently developed. Although DNAmTL has been characterized in adult and elderly cohorts, its utility in pediatric populations remains unknown. We examined the comparability of leukocyte TL measurements generated using qPCR (absolute TL; aTL) to those estimated using DNAmTL in a high-risk pediatric cohort (N = 269; age: 8–13 years, 83% investigated for maltreatment). aTL and DNAmTL measurements were correlated with one another (r = 0.20, p = 0.001), but exhibited poor measurement agreement and were significantly different in paired-sample t-tests (Cohen’s d = 0.77, p < 0.001). Shorter DNAmTL was associated with older age (r = −0.25, p < 0.001), male sex (β = −0.27, p = 0.029), and White race (β = −0.74, p = 0.008). By contrast, aTL was less strongly associated with age (r = −0.13, p = 0.040), was longer in males (β = 0.31, p = 0.012), and was not associated with race (p = 0.820). These findings highlight strengths and limitations of high-throughput measures of TL; although DNAmTL replicated hypothesized associations, aTL measurements were positively skewed and did not replicate associations with external validity measures. These results also extend previous research in adults and suggest that DNAmTL is a sensitive TL measure for use in pediatric populations.
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Affiliation(s)
- Waylon J Hastings
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | - Laura Etzel
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | - Christine M Heim
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Medical Psychology, Berlin, Germany
| | - Jennie G Noll
- Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA
| | - Emma J Rose
- Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA.,The Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA 16802, USA
| | - Hannah M C Schreier
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | - Chad E Shenk
- Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA.,Department of Pediatrics, The Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Xin Tang
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | - Idan Shalev
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
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