Epigenetic clock

The strong effects of age on DNA methylation levels have been known since the late 1960s. A vast literature describes sets of CpGs whose DNA methylation levels correlate with age. The first robust demonstration that DNA methylation levels in saliva could generate age predictors with an average accuracy of 5.2 years was published by a UCLA team including Sven Bocklandt, Steve Horvath, and Eric Vilain in 2011 (Bocklandt et al. 2011). The laboratories of Trey Ideker and Kang Zhang at the University of California, San Diego published the Hannum epigenetic clock (Hannum 2013), which consisted of 71 markers that accurately estimate age based on blood methylation levels. The first multi-tissue epigenetic clock, Horvath's epigenetic clock, was developed by Steve Horvath, a professor of human genetics and biostatistics at UCLA (Horvath 2013). Horvath spent over 4 years collecting publicly available Illumina DNA methylation data and identifying suitable statistical methods.

The personal story behind the discovery was featured in Nature. The age estimator was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. The major innovation of Horvath's epigenetic clock lies in its wide applicability: the same set of 353 CpGs and the same prediction algorithm is used irrespective of the DNA source within the organism, i.e. it does not require any adjustments or offsets. This property allows one to compare the ages of different areas of the human body using the same aging clock. Shortly afterwards, a derivation of Horvath's clock, the IEAA (Intrinsic Epigenetic Age Acceleration), an estimator based on the cellular composition of the blood, was developed.

A second generation of epigenetic clocks emerged a few years later and improved on the first in age estimation. This was thanks to the incorporation not only of epigenetic variants such as DNA methylation but also environmental variants such as smoking or chronological age. Among these clocks, the PhenoAge and GrimAge clocks stand out. PhenoAge is an epigenetic clock that takes chronological age into account, and GrimAge uses the mortality risks of age together with the smoking variant among others as a risk factor. Taking into account environmental variants allows GrimAge to outperform any other epigenetic clock in "predicting death".

Third-generation epigenetic clocks are designed to be applicable across multiple species simultaneously. Specifically, pan-mammalian epigenetic clocks determine the age of tissues from all mammalian species by analyzing cytosine methylation in DNA regions that are highly conserved.{{cite journal | vauthors = Lu AT, Fei Z, Haghani A, et al. | title = Universal DNA methylation age across mammalian tissues [published correction appears in Nat Aging. 2023 Sep 6;] | journal = Nat Aging | volume = 3 | issue = 9 | pages = 1144–1166 | year = 2023 | doi = 10.1038/s43587-023-00462-6 | doi-access = free | pmid = 37563227 | pmc = 10501909 | hdl = 10023/28280 | hdl-access = free }}

More recently in 2025, age-related changes in histone marks have been leveraged to build a new class of epigenetic clocks that do not rely on DNA methylation.{{cite journal | vauthors = de Lima Camillo LP, Asif MH, Horvath S, Larschan E, Singh R | title = Histone mark age of human tissues and cell types | journal = Science Advances | volume = 11 | issue = 1 | pages = eadk9373 | year = 2025 | doi = 10.1126/sciadv.adk9373 | doi-access = free| pmid = 39742485 | pmc = 11691649 | bibcode = 2025SciA...11K9373D }} These new predictors show promise as an alternative to clocks that use cytosine methylation.

New age estimation tools have been developed continuously, which also facilitate the prognosis of certain diseases.

Elongation Of Very Long Chain Fatty Acids-Like 2 is a gene that codes for a transmembrane protein that plays a role in the synthesis of VLCFAs.{{Cite journal |last1=Leonard |first1=Amanda E. |last2=Kelder |first2=Bruce |last3=Bobik |first3=Emil G. |last4=Chuang |first4=Lu-Te |last5=Lewis |first5=Christopher J. |last6=Kopchick |first6=John J. |last7=Mukerji |first7=Pradip |last8=Huang |first8=Yung-Sheng |date=August 2002 |title=Identification and expression of mammalian long-chain PUFA elongation enzymes |url=https://aocs.onlinelibrary.wiley.com/doi/10.1007/s11745-002-0955-6 |journal=Lipids |language=en |volume=37 |issue=8 |pages=733–740 |doi=10.1007/s11745-002-0955-6 |pmid=12371743 |issn=0024-4201}} The inhibition of its expression has been associated with increased aging of the retina in mice while its upregulation resulted in a slower aging of the retina.{{Cite journal |last1=Chao |first1=Daniel L. |last2=Skowronska-Krawczyk |first2=Dorota |date=2020-01-01 |title=ELOVL2: Not just a biomarker of aging |journal=Translational Medicine of Aging |volume=4 |pages=78–80 |doi=10.1016/j.tma.2020.06.004 |issn=2468-5011 |pmc=7544151 |pmid=33043173}} Methylation sites in the promoter region of this gene have consistently been part of the top most age correlated in different studies.{{Cite journal |last1=Bacalini |first1=Maria Giulia |last2=Deelen |first2=Joris |last3=Pirazzini |first3=Chiara |last4=De Cecco |first4=Marco |last5=Giuliani |first5=Cristina |last6=Lanzarini |first6=Catia |last7=Ravaioli |first7=Francesco |last8=Marasco |first8=Elena |last9=van Heemst |first9=Diana |last10=Suchiman |first10=H. Eka D. |last11=Slieker |first11=Roderick |last12=Giampieri |first12=Enrico |last13=Recchioni |first13=Rina |last14=Mercheselli |first14=Fiorella |last15=Salvioli |first15=Stefano |date=2016-09-26 |title=Systemic Age-Associated DNA Hypermethylation of ELOVL2 Gene: In Vivo and In Vitro Evidences of a Cell Replication Process |url=https://academic.oup.com/biomedgerontology/article/72/8/1015/2630029 |journal=The Journals of Gerontology: Series A |volume=72 |issue=8 |pages=1015–1023 |doi=10.1093/gerona/glw185 |issn=1079-5006 |pmc=5861890 |pmid=27672102}}{{Cite journal |last1=Paparazzo |first1=Ersilia |last2=Lagani |first2=Vincenzo |last3=Geracitano |first3=Silvana |last4=Citrigno |first4=Luigi |last5=Aceto |first5=Mirella Aurora |last6=Malvaso |first6=Antonio |last7=Bruno |first7=Francesco |last8=Passarino |first8=Giuseppe |last9=Montesanto |first9=Alberto |date=January 2023 |title=An ELOVL2-Based Epigenetic Clock for Forensic Age Prediction: A Systematic Review |journal=International Journal of Molecular Sciences |language=en |volume=24 |issue=3 |pages=2254 |doi=10.3390/ijms24032254 |doi-access=free |issn=1422-0067 |pmc=9916975 |pmid=36768576}}{{Cite journal |last1=Johnson |first1=Adiv A. |last2=Torosin |first2=Nicole S. |last3=Shokhirev |first3=Maxim N. |last4=Cuellar |first4=Trinna L. |date=November 2022 |title=A set of common buccal CpGs that predict epigenetic age and associate with lifespan-regulating genes |journal=iScience |volume=25 |issue=11 |pages=105304 |doi=10.1016/j.isci.2022.105304 |issn=2589-0042 |pmc=9593711 |pmid=36304118|bibcode=2022iSci...25j5304J }} The methylation in those sites increases with age which reduce its expression.{{Cite journal |last1=Chen |first1=Daniel |last2=Chao |first2=Daniel L. |last3=Rocha |first3=Lorena |last4=Kolar |first4=Matthew |last5=Nguyen Huu |first5=Viet Anh |last6=Krawczyk |first6=Michal |last7=Dasyani |first7=Manish |last8=Wang |first8=Tina |last9=Jafari |first9=Maryam |last10=Jabari |first10=Mary |last11=Ross |first11=Kevin D. |last12=Saghatelian |first12=Alan |last13=Hamilton |first13=Bruce A. |last14=Zhang |first14=Kang |last15=Skowronska-Krawczyk |first15=Dorota |date=February 2020 |title=The lipid elongation enzyme ELOVL2 is a molecular regulator of aging in the retina |journal=Aging Cell |language=en |volume=19 |issue=2 |pages=e13100 |doi=10.1111/acel.13100 |issn=1474-9718 |pmc=6996962 |pmid=31943697}}

Four-and-a-Half LIM domain protein 2 is a gene implicated in signal transduction. Increase in its expression has been associated with obesity.{{Cite journal |last1=Clemente-Olivo |first1=Maria P. |last2=Habibe |first2=Jayron J. |last3=Vos |first3=Mariska |last4=Ottenhoff |first4=Roelof |last5=Jongejan |first5=Aldo |last6=Herrema |first6=Hilde |last7=Zelcer |first7=Noam |last8=Kooijman |first8=Sander |last9=Rensen |first9=Patrick C.N. |last10=van Raalte |first10=Daniël H. |last11=Nieuwdorp |first11=Max |last12=Eringa |first12=Etto C. |last13=de Vries |first13=Carlie J. |date=August 2021 |title=Four-and-a-half LIM domain protein 2 (FHL2) deficiency protects mice from diet-induced obesity and high FHL2 expression marks human obesity |url=https://linkinghub.elsevier.com/retrieve/pii/S0026049521001153 |journal=Metabolism |volume=121 |pages=154815 |doi=10.1016/j.metabol.2021.154815 |pmid=34119536 |issn=0026-0495|hdl=1887/3237837 |hdl-access=free }} The methylation in its promoter is also strongly correlated with age in numerous studies.{{Cite journal |last1=Fulea |first1=R.C. |last2=Reynard |first2=L. |last3=Young |first3=D. |last4=Bou-Gharios |first4=G. |date=April 2021 |title=FHL2 promoter DNA methylation increases with chronological age in joint tissues and impacts target gene expression |url=https://linkinghub.elsevier.com/retrieve/pii/S1063458421004647 |journal=Osteoarthritis and Cartilage |volume=29 |pages=S310 |doi=10.1016/j.joca.2021.02.409 |issn=1063-4584}}{{Cite journal |last1=Habibe |first1=Jayron J. |last2=Clemente-Olivo |first2=Maria P. |last3=de Vries |first3=Carlie J. |date=October 2021 |title=How (Epi)Genetic Regulation of the LIM-Domain Protein FHL2 Impacts Multifactorial Disease |journal=Cells |language=en |volume=10 |issue=10 |pages=2611 |doi=10.3390/cells10102611 |doi-access=free |issn=2073-4409 |pmc=8534169 |pmid=34685595}} In this case the methylation, which increases with age,{{Cite journal |last1=Ronn |first1=T. |last2=Volkov |first2=P. |last3=Gillberg |first3=L. |last4=Kokosar |first4=M. |last5=Perfilyev |first5=A. |last6=Jacobsen |first6=A. L. |last7=Jorgensen |first7=S. W. |last8=Brons |first8=C. |last9=Jansson |first9=P.-A. |last10=Eriksson |first10=K.-F. |last11=Pedersen |first11=O. |last12=Hansen |first12=T. |last13=Groop |first13=L. |last14=Stener-Victorin |first14=E. |last15=Vaag |first15=A. |date=2015-04-10 |title=Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood |url=https://academic.oup.com/hmg/article-lookup/doi/10.1093/hmg/ddv124 |journal=Human Molecular Genetics |volume=24 |issue=13 |pages=3792–4513 |doi=10.1093/hmg/ddv124 |pmid=25861810 |issn=0964-6906}} is associated with an increase in FHL2 expression{{Cite journal |last1=Bacos |first1=Karl |last2=Gillberg |first2=Linn |last3=Volkov |first3=Petr |last4=Olsson |first4=Anders H. |last5=Hansen |first5=Torben |last6=Pedersen |first6=Oluf |last7=Gjesing |first7=Anette Prior |last8=Eiberg |first8=Hans |last9=Tuomi |first9=Tiinamaija |last10=Almgren |first10=Peter |last11=Groop |first11=Leif |last12=Eliasson |first12=Lena |last13=Vaag |first13=Allan |last14=Dayeh |first14=Tasnim |last15=Ling |first15=Charlotte |date=2016-03-31 |title=Blood-based biomarkers of age-associated epigenetic changes in human islets associate with insulin secretion and diabetes |journal=Nature Communications |language=en |volume=7 |issue=1 |pages=11089 |doi=10.1038/ncomms11089 |issn=2041-1723 |pmc=4821875 |pmid=27029739|bibcode=2016NatCo...711089B }} but surprisingly also with a decreased expression in some tissues.

It is not yet known what exactly is measured by DNA methylation age. Horvath hypothesized that DNA methylation age measures the cumulative effect of an epigenetic maintenance system but details are unknown. The fact that DNA methylation age of blood predicts all-cause mortality in later life has been used to argue that it relates to a process that causes aging. However, if a particular CpG played a direct causal role in the aging process, the mortality it created would make it less likely to be observed in older individuals, making the site less likely to have been chosen as a predictor; the 353 clock CpGs, therefore, likely have no causal effect.{{cite journal | vauthors = Nelson PG, Promislow DE, Masel J | title = Biomarkers for Aging Identified in Cross-sectional Studies Tend to Be Non-causative | journal = The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences | volume = 75 | issue = 3 | pages = 466–472 | date = February 2020 | pmid = 31353411 | pmc = 7457180 | doi = 10.1093/gerona/glz174 }} Rather, the epigenetic clock captures an emergent property of the epigenome.

In 2010, Axel Schumacher proposed a new unifying model of aging and the development of complex diseases, incorporating classical aging theories and epigenetics. Steve Horvath and Kenneth Raj{{cite journal |vauthors=Horvath S, Raj K |date=June 2018 |title=DNA methylation-based biomarkers and the epigenetic clock theory of ageing |journal=Nature Reviews. Genetics |volume=19 |issue=6 |pages=371–384 |doi=10.1038/s41576-018-0004-3 |pmid=29643443 |s2cid=4709691}} extended this theory, proposing an epigenetic clock theory of aging with the following tenets:

• Biological aging results as an unintended consequence of both developmental programs and maintenance program, the molecular footprints of which give rise to DNA methylation age estimators.
• The precise mechanisms linking the innate molecular processes (underlying DNAm age) to the decline in tissue function probably relate to both intracellular changes (leading to a loss of cellular identity) and subtle changes in cell composition, for example, fully functioning somatic stem cells.
• At the molecular level, DNAm age is a proximal readout of a collection of innate aging processes that conspire with other, independent root causes of aging to the detriment of tissue function.

In general, biological aging clocks and biomarkers of aging are expected to find many uses in biological research since age is a fundamental characteristic of most organisms. Accurate measures of biological age (biological aging clocks) could be useful for

• testing the validity of various theories of biological aging,
• diagnosing various age related diseases and for defining cancer subtypes,
• predicting/prognosticating the onset of various diseases,
• serving as surrogate markers for evaluating therapeutic interventions including rejuvenation approaches,
• studying developmental biology and cell differentiation,
• forensic applications, for example to estimate the age of a suspect based on blood left on a crime scene.

Overall, biological clocks are expected to be useful for studying what causes aging and what can be done against it. However, they can only capture the effects of interventions that affect the rate of future aging, i.e. the slope of the Gompertz curve by which mortality increases with age, and not that of interventions that act at one moment in time, e.g. to lower mortality across all ages, i.e. the intercept of the Gompertz curve.

The clock is defined as an age estimation method based on 353 epigenetic markers on the DNA. The 353 markers measure DNA methylation of CpG dinucleotides. Estimated age ("predicted age" in mathematical usage), also referred to as DNA methylation age, has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues (which are used as human analogs for biological testing purposes). Organismal growth (and concomitant cell division) leads to a high ticking rate of the epigenetic clock that slows down to a constant ticking rate (linear dependence) after adulthood (age 20). The fact that DNA methylation age of blood predicts all-cause mortality in later life even after adjusting for known risk factors is compatible with a variety of causal relationships, e.g. a common cause for both. Similarly, markers of physical and mental fitness are associated with the epigenetic clock (lower abilities associated with age acceleration). It systematically underestimates age from older individuals.{{cite journal | vauthors = El Khoury LY, Gorrie-Stone T, Smart M, Hughes A, Bao Y, Andrayas A, Burrage J, Hannon E, Kumari M, Mill J, Schalkwyk LC | display-authors = 6 | title = Systematic underestimation of the epigenetic clock and age acceleration in older subjects | journal = Genome Biology | volume = 20 | issue = 1 | pages = 283 | date = December 2019 | pmid = 31847916 | pmc = 6915902 | doi = 10.1186/s13059-019-1810-4 | doi-access = free }}

Salient features of Horvath's epigenetic clock include its applicability to a broad spectrum of tissues and cell types. Since it allows one to contrast the ages of different tissues from the same subject, it can be used to identify tissues that show evidence of accelerated age due to disease.

The Horvath clock, specifically the IEAA variant, is associated with several ageing-related genes:14

• TRIM59: of the tripartite motif family, strongly associated with chronological age and whose expression has been observed in multiple cancers
• SMC4: inhibits cellular senescence, an established hallmark of ageing
• KPNA4: member of the importin family, nuclear transport receptors. Dysfunction of nuclear transport has been proposed as a marker of ageing
• CD46: encodes a regulator of T-cell function and the complement system, a key component of the innate immune system where it promotes inflammation
• ATP8B4: encodes for a lipid transporter protein and contains variants that have been reported in association with Alzheimer's disease
• CXXC4: encodes Idax, an inhibitor of Wnt signalling{{cite journal | vauthors = McCartney DL, Min JL, Richmond RC, Lu AT, Sobczyk MK, Davies G, Broer L, Guo X, Jeong A, Jung J, Kasela S, Katrinli S, Kuo PL, Matias-Garcia PR, Mishra PP, Nygaard M, Palviainen T, Patki A, Raffield LM, Ratliff SM, Richardson TG, Robinson O, Soerensen M, Sun D, Tsai PC, van der Zee MD, Walker RM, Wang X, Wang Y, Xia R, Xu Z, Yao J, Zhao W, Correa A, Boerwinkle E, Dugué PA, Durda P, Elliott HR, Gieger C, de Geus EJ, Harris SE, Hemani G, Imboden M, Kähönen M, Kardia SL, Kresovich JK, Li S, Lunetta KL, Mangino M, Mason D, McIntosh AM, Mengel-From J, Moore AZ, Murabito JM, Ollikainen M, Pankow JS, Pedersen NL, Peters A, Polidoro S, Porteous DJ, Raitakari O, Rich SS, Sandler DP, Sillanpää E, Smith AK, Southey MC, Strauch K, Tiwari H, Tanaka T, Tillin T, Uitterlinden AG, Van Den Berg DJ, van Dongen J, Wilson JG, Wright J, Yet I, Arnett D, Bandinelli S, Bell JT, Binder AM, Boomsma DI, Chen W, Christensen K, Conneely KN, Elliott P, Ferrucci L, Fornage M, Hägg S, Hayward C, Irvin M, Kaprio J, Lawlor DA, Lehtimäki T, Lohoff FW, Milani L, Milne RL, Probst-Hensch N, Reiner AP, Ritz B, Rotter JI, Smith JA, Taylor JA, van Meurs JB, Vineis P, Waldenberger M, Deary IJ, Relton CL, Horvath S, Marioni RE | display-authors = 6 | title = Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging | journal = Genome Biology | volume = 22 | issue = 1 | pages = 194 | date = June 2021 | pmid = 34187551 | pmc = 8243879 | doi = 10.1186/s13059-021-02398-9 | doi-access = free }} 50px Text was copied from this source, which is available under a [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License].

The basic approach is to form a weighted average of the 353 clock CpGs, which is then transformed to DNAm age using a calibration function. The calibration function reveals that the epigenetic clock has a high ticking rate until adulthood, after which it slows to a constant ticking rate. Using the training data sets, Horvath used a penalized regression model (Elastic net regularization) to regress a calibrated version of chronological age on 21,369 CpG probes that were present both on the Illumina 450K and 27K platform and had fewer than 10 missing values. DNAm age is defined as estimated ("predicted") age. The elastic net predictor automatically selected 353 CpGs. 193 of the 353 CpGs correlate positively with age while the remaining 160 CpGs correlate negatively with age. R software and a freely available web-based tool can be found at the following webpage.

The median error of estimated age is 3.6 years across a wide spectrum of tissues and cell types, although this increases for older individuals The epigenetic clock performs well in heterogeneous tissues (for example, whole blood, peripheral blood mononuclear cells, cerebellar samples, occipital cortex, buccal epithelium, colon, adipose, kidney, liver, lung, saliva, uterine cervix, epidermis, muscle) as well as in individual cell types such as CD4 T cells, CD14 monocytes, glial cells, neurons, immortalized B cells, mesenchymal stromal cells. However, accuracy depends to some extent on the source of the DNA.

The epigenetic clock leads to a chronological age prediction that has a Pearson correlation coefficient of r = 0.96 with chronological age (Figure 2 in). Thus the age correlation is close to its maximum possible correlation value of 1. Other biological clocks are based on a) telomere length, b) p16INK4a expression levels (also known as INK4a/ARF locus), and c) microsatellite mutations.{{cite journal | vauthors = Forster P, Hohoff C, Dunkelmann B, Schürenkamp M, Pfeiffer H, Neuhuber F, Brinkmann B | title = Elevated germline mutation rate in teenage fathers | journal = Proceedings. Biological Sciences | volume = 282 | issue = 1803 | pages = 20142898 | date = March 2015 | pmid = 25694621 | pmc = 4345458 | doi = 10.1098/rspb.2014.2898 }} The correlation between chronological age and telomere length is r = −0.51 in women and r = −0.55 in men. The correlation between chronological age and expression levels of p16INK4a in T cells is r = 0.56.

By contrasting DNA methylation age (estimated age) with chronological age, one can define measures of age acceleration. Age acceleration can be defined as the difference between DNA methylation age and chronological age. Alternatively, it can be defined as the residual that results from regressing DNAm age on chronological age. The latter measure is attractive because it does not correlate with chronological age.

A positive/negative value of epigenetic age acceleration suggests that the underlying tissue ages faster/slower than expected.

The broad sense heritability (defined via Falconer's formula) of age acceleration of blood from older subjects is around 40% but it appears to be much higher in newborns. Similarly, the age acceleration of brain tissue (prefrontal cortex) was found to be 41% in older subjects. Genome-wide association studies (GWAS) of epigenetic age acceleration in postmortem brain samples have identified several SNPs at a genomewide significance level. GWAS of age acceleration in blood have identified several genome-wide significant genetic loci including the telomerase reverse transcriptase gene (TERT) locus.{{cite journal | vauthors = Lu AT, Xue L, Salfati EL, Chen BH, Ferrucci L, Levy D, Joehanes R, Murabito JM, Kiel DP, Tsai PC, Yet I, Bell JT, Mangino M, Tanaka T, McRae AF, Marioni RE, Visscher PM, Wray NR, Deary IJ, Levine ME, Quach A, Assimes T, Tsao PS, Absher D, Stewart JD, Li Y, Reiner AP, Hou L, Baccarelli AA, Whitsel EA, Aviv A, Cardona A, Day FR, Wareham NJ, Perry JR, Ong KK, Raj K, Lunetta KL, Horvath S | display-authors = 6 | title = GWAS of epigenetic aging rates in blood reveals a critical role for TERT | journal = Nature Communications | volume = 9 | issue = 1 | pages = 387 | date = January 2018 | pmid = 29374233 | pmc = 5786029 | doi = 10.1038/s41467-017-02697-5 | bibcode = 2018NatCo...9..387L }} Genetic variants associated with longer leukocyte telomere length in TERT gene paradoxically confer higher epigenetic age acceleration in blood.

In general, lifestyle factors have only weak associations with epigenetic age acceleration in blood.{{cite journal | vauthors = Quach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, Ritz B, Bandinelli S, Neuhouser ML, Beasley JM, Snetselaar L, Wallace RB, Tsao PS, Absher D, Assimes TL, Stewart JD, Li Y, Hou L, Baccarelli AA, Whitsel EA, Horvath S | display-authors = 6 | title = Epigenetic clock analysis of diet, exercise, education, and lifestyle factors | journal = Aging | volume = 9 | issue = 2 | pages = 419–446 | date = February 2017 | pmid = 28198702 | pmc = 5361673 | doi = 10.18632/aging.101168 }}{{cite journal | vauthors = Kresovich JK, Garval EL, Martinez Lopez AM, Xu Z, Niehoff NM, White AJ, Sandler DP, Taylor JA | display-authors = 6 | title = Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration | journal = American Journal of Epidemiology | volume = 190 | issue = 6 | pages = 984–993 | date = June 2021 | pmid = 33693587 | pmc = 8168202 | doi = 10.1093/aje/kwaa251 }}{{cite journal | vauthors = Kresovich JK, Martinez Lopez AM, Garval EL, Xu Z, White AJ, Sandler DP, Taylor JA | title = Alcohol Consumption and Methylation-Based Measures of Biological Age | journal = The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences | volume = 76 | issue = 12 | pages = 2107–2111 | date = November 2021 | pmid = 34038541 | pmc = 8599006 | doi = 10.1093/gerona/glab149 | doi-access = free }} Cross sectional studies of extrinsic epigenetic aging rates in blood show reduced epigenetic aging correlates with higher education, eating a high plant diet with lean meats, moderate alcohol consumption, and physical activity and the risks associated with metabolic syndrome. However, studies suggest that high levels of alcohol consumption are associated with accelerated aging of certain epigenetic clocks.

The epigenetic clock was used to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle and adipose tissue. A significant correlation (r = 0.42) between BMI and epigenetic age acceleration could be observed for the liver. A much larger sample size (n = 4200 blood samples) revealed a weak but statistically significant correlation (r = 0.09) between BMI and intrinsic age acceleration of blood. The same large study found that various biomarkers of metabolic syndrome (glucose-, insulin-, triglyceride levels, C-reactive protein, waist-to-hip ratio) were associated with epigenetic age acceleration in blood. Conversely, high levels of HDL cholesterol were associated with a lower epigenetic aging rate of blood. Other research suggests very strong associations between higher body mass index, waist-to-hip ratio, and waist circumference and accelerated epigenetic clocks, with evidence that physical activity may lessen these effects.

DNAm age is higher than chronological age in female breast tissue that is adjacent to breast cancer tissue. Since normal tissue which is adjacent to other cancer types does not exhibit a similar age acceleration effect, this finding suggests that normal female breast tissue ages faster than other parts of the body. Similarly, normal breast tissue samples from women without cancer have been found to be substantially older than blood samples collected from the same women at the same time.{{cite journal | vauthors = Sehl ME, Henry JE, Storniolo AM, Ganz PA, Horvath S | title = DNA methylation age is elevated in breast tissue of healthy women | journal = Breast Cancer Research and Treatment | volume = 164 | issue = 1 | pages = 209–219 | date = July 2017 | pmid = 28364215 | pmc = 5487725 | doi = 10.1007/s10549-017-4218-4 }}

In a study of three epigenetic clocks and breast cancer risk, DNAm age was found to be accelerated in blood samples of cancer-free women, years before diagnosis.{{cite journal | vauthors = Kresovich JK, Xu Z, O'Brien KM, Weinberg CR, Sandler DP, Taylor JA | title = Methylation-Based Biological Age and Breast Cancer Risk | journal = Journal of the National Cancer Institute | volume = 111 | issue = 10 | pages = 1051–1058 | date = October 2019 | pmid = 30794318 | pmc = 6792078 | doi = 10.1093/jnci/djz020 | author4-link = Clarice Weinberg }}

Cancer tissues show both positive and negative age acceleration effects. For most tumor types, no significant relationship can be observed between age acceleration and tumor morphology (grade/stage). On average, cancer tissues with mutated TP53 have a lower age acceleration than those without it. Further, cancer tissues with high age acceleration tend to have fewer somatic mutations than those with low age acceleration. Age acceleration is highly related to various genomic aberrations in cancer tissues. Somatic mutations in estrogen receptors or progesterone receptors are associated with accelerated DNAm age in breast cancer. Colorectal cancer samples with a BRAF (V600E) mutation or promoter hypermethylation of the mismatch repair gene MLH1 are associated with an increased age acceleration. Age acceleration in glioblastoma multiforme samples is highly significantly associated with certain mutations in H3F3A. One study suggests that the epigenetic age of blood tissue may be prognostic of lung cancer incidence.{{cite journal | vauthors = Levine ME, Hosgood HD, Chen B, Absher D, Assimes T, Horvath S | title = DNA methylation age of blood predicts future onset of lung cancer in the women's health initiative | journal = Aging | volume = 7 | issue = 9 | pages = 690–700 | date = September 2015 | pmid = 26411804 | pmc = 4600626 | doi = 10.18632/aging.100809 }}

Down syndrome entails an increased risk of many chronic diseases that are typically associated with older age. The clinical manifestations of accelerated aging suggest that trisomy 21 increases the biological age of tissues, but molecular evidence for this hypothesis has been sparse. According to the epigenetic clock, trisomy 21 significantly increases the age of blood and brain tissue (on average by 6.6 years).

Epigenetic age acceleration of the human prefrontal cortex was found to be correlated with several neuropathological measurements that play a role in Alzheimer's disease Further, it was found to be associated with a decline in global cognitive functioning, and memory functioning among individuals with Alzheimer's disease. The epigenetic age of blood relates to cognitive functioning in the elderly. Overall, these results strongly suggest that the epigenetic clock lends itself for measuring the biological age of the brain.

It has been difficult to identify tissues that seem to evade aging due to the lack of biomarkers of tissue age that allow one to contrast compare the ages of different tissues. An application of epigenetic clock to 30 anatomic sites from six centenarians and younger subjects revealed that the cerebellum ages slowly: it is about 15 years younger than expected in a centenarian. This finding might explain why the cerebellum exhibits fewer neuropathological hallmarks of age related dementias compared to other brain regions. In younger subjects (e.g. younger than 70), brain regions and brain cells appear to have roughly the same age. Several SNPs and genes have been identified that relate to the epigenetic age of the cerebellum.

Huntington's disease has been found to increase the epigenetic aging rates of several human brain regions.{{cite journal | vauthors = Horvath S, Langfelder P, Kwak S, Aaronson J, Rosinski J, Vogt TF, Eszes M, Faull RL, Curtis MA, Waldvogel HJ, Choi OW, Tung S, Vinters HV, Coppola G, Yang XW | display-authors = 6 | title = Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels | journal = Aging | volume = 8 | issue = 7 | pages = 1485–1512 | date = July 2016 | pmid = 27479945 | pmc = 4993344 | doi = 10.18632/aging.101005 }}

The offspring of semi-supercentenarians (subjects who reached an age of 105–109 years) have a lower epigenetic age than age-matched controls (age difference = 5.1 years in blood) and centenarians are younger (8.6 years) than expected based on their chronological age.

Infection with the Human Immunodeficiency Virus-1 (HIV) is associated with clinical symptoms of accelerated aging, as evidenced by increased incidence and diversity of age-related illnesses at relatively young ages. But it has been difficult to detect an accelerated aging effect on a molecular level. An epigenetic clock analysis of human DNA from HIV+ subjects and controls detected a significant age acceleration effect in brain (7.4 years) and blood (5.2 years) tissue due to HIV-1 infection. These results are consistent with an independent study that also found an age advancement of 5 years in blood of HIV patients and a strong effect of the HLA locus.{{cite journal | vauthors = Gross AM, Jaeger PA, Kreisberg JF, Licon K, Jepsen KL, Khosroheidari M, Morsey BM, Swindells S, Shen H, Ng CT, Flagg K, Chen D, Zhang K, Fox HS, Ideker T | display-authors = 6 | title = Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA | journal = Molecular Cell | volume = 62 | issue = 2 | pages = 157–168 | date = April 2016 | pmid = 27105112 | pmc = 4995115 | doi = 10.1016/j.molcel.2016.03.019 }}

A large-scale study suggests that the blood of Parkinson's disease subjects, in particular, their granulocyte ratio, exhibits (relatively weak) accelerated aging effects.{{cite journal | vauthors = Horvath S, Ritz BR | title = Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients | journal = Aging | volume = 7 | issue = 12 | pages = 1130–1142 | date = December 2015 | pmid = 26655927 | pmc = 4712337 | doi = 10.18632/aging.100859 }}

Children with a very rare disorder known as syndrome X maintain the façade of persistent toddler-like features while aging from birth to adulthood. Since the physical development of these children is dramatically delayed, these children appear to be a toddler or at best a preschooler. According to an epigenetic clock analysis, blood tissue from syndrome X cases is not younger than expected.

The following results strongly suggest that the loss of female hormones resulting from menopause accelerates the epigenetic aging rate of blood and possibly that of other tissues. First, early menopause has been found to be associated with an increased epigenetic age acceleration of blood. Second, surgical menopause (due to bilateral oophorectomy) is associated with epigenetic age acceleration in blood and saliva. Third, menopausal hormone therapy, which mitigates hormonal loss, is associated with a negative age acceleration of buccal cells (but not of blood cells). Fourth, genetic markers that are associated with early menopause are also associated with increased epigenetic age acceleration in blood.

A confounding aspect of biological aging is the nature and role of senescent cells. It is unclear whether the three major types of cellular senescence, namely replicative senescence, oncogene-induced senescence and DNA damage-induced senescence are descriptions of the same phenomenon instigated by different sources, or if each of these is distinct, and how they are associated with epigenetic aging.

Induction of replicative senescence (RS) and oncogene-induced senescence (OIS) were found to be accompanied by epigenetic aging of primary cells but senescence induced by DNA damage was not, even though RS and OIS activate the cellular DNA damage response pathway.{{cite journal | vauthors = Lowe D, Horvath S, Raj K | title = Epigenetic clock analyses of cellular senescence and ageing | journal = Oncotarget | volume = 7 | issue = 8 | pages = 8524–8531 | date = February 2016 | pmid = 26885756 | pmc = 4890984 | doi = 10.18632/oncotarget.7383 }} These results highlight the independence of cellular senescence from epigenetic aging. Consistent with this, telomerase-immortalised cells continued to age (according to the epigenetic clock) without having been treated with any senescence inducers or DNA-damaging agents, re-affirming the independence of the process of epigenetic ageing from telomeres, cellular senescence, and the DNA damage response pathway.

Although the uncoupling of senescence from cellular aging appears at first sight to be inconsistent with the fact that senescent cells contribute to the physical manifestation of organism ageing, as demonstrated by Baker et al., where removal of senescent cells slowed down aging.{{cite journal | vauthors = Baker DJ, Wijshake T, Tchkonia T, LeBrasseur NK, Childs BG, van de Sluis B, Kirkland JL, van Deursen JM | display-authors = 6 | title = Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders | journal = Nature | volume = 479 | issue = 7372 | pages = 232–236 | date = November 2011 | pmid = 22048312 | pmc = 3468323 | doi = 10.1038/nature10600 | bibcode = 2011Natur.479..232B }}

The epigenetic clock analysis of senescence, however, suggests that cellular senescence is a state that cells are forced into as a result of external pressures such as DNA damage, ectopic oncogene expression and exhaustive proliferation of cells to replenish those eliminated by external/environmental factors. These senescent cells, in sufficient numbers, will probably cause the deterioration of tissues, which is interpreted as organism ageing. However, at the cellular level, aging, as measured by the epigenetic clock, is distinct from senescence. It is an intrinsic mechanism that exists from the birth of the cell and continues. This implies that if cells are not shunted into senescence by the external pressures described above, they would still continue to age. This is consistent with the fact that mice with naturally long telomeres still age and eventually die even though their telomere lengths are far longer than the critical limit, and they age prematurely when their telomeres are forcibly shortened, due to replicative senescence. Therefore, cellular senescence is a route by which cells exit prematurely from the natural course of cellular aging.

Men age faster than women according to epigenetic age acceleration in blood, brain, saliva, but it depends on the structure being researched and the lifestyle.{{cite journal | vauthors = Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, Ritz BR, Chen B, Lu AT, Rickabaugh TM, Jamieson BD, Sun D, Li S, Chen W, Quintana-Murci L, Fagny M, Kobor MS, Tsao PS, Reiner AP, Edlefsen KL, Absher D, Assimes TL | display-authors = 6 | title = An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease | journal = Genome Biology | volume = 17 | issue = 1 | pages = 171 | date = August 2016 | pmid = 27511193 | pmc = 4980791 | doi = 10.1186/s13059-016-1030-0 | doi-access = free }}

The epigenetic clock method applies to all examined racial/ethnic groups in the sense that DNAm age is highly correlated with chronological age. But ethnicity can be associated with epigenetic age acceleration. For example, the blood of Hispanics and the Tsimané ages more slowly than that of other populations which might explain the Hispanic mortality paradox.

Hematopoietic stem cell transplantation, which transplants these cells from a young donor to an older recipient, rejuvenates the epigenetic age of blood to that of the donor. However, graft-versus-host disease is associated with increased DNA methylation age.{{cite journal | vauthors = Stölzel F, Brosch M, Horvath S, Kramer M, Thiede C, von Bonin M, Ammerpohl O, Middeke M, Schetelig J, Ehninger G, Hampe J, Bornhäuser M | display-authors = 6 | title = Dynamics of epigenetic age following hematopoietic stem cell transplantation | journal = Haematologica | volume = 102 | issue = 8 | pages = e321–e323 | date = August 2017 | pmid = 28550187 | pmc = 5541887 | doi = 10.3324/haematol.2016.160481 }}

Adult progeria also known as Werner syndrome is associated with epigenetic age acceleration in blood.

Fibroblast samples from children with Hutchinson-Gilford Progeria exhibit accelerated epigenetic aging effects according to the "skin & blood" epigenetic clock but not according to the original pan tissue clock from Horvath.{{cite journal | vauthors = Horvath S, Oshima J, Martin GM, Lu AT, Quach A, Cohen H, Felton S, Matsuyama M, Lowe D, Kabacik S, Wilson JG, Reiner AP, Maierhofer A, Flunkert J, Aviv A, Hou L, Baccarelli AA, Li Y, Stewart JD, Whitsel EA, Ferrucci L, Matsuyama S, Raj K | display-authors = 6 | title = Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies | journal = Aging | volume = 10 | issue = 7 | pages = 1758–1775 | date = July 2018 | pmid = 30048243 | pmc = 6075434 | doi = 10.18632/aging.101508 | doi-access = free }}

Horvath hypothesized that his clock arises from a methylation footprint left by an epigenomic maintenance system.

{{Synthesis|section|date=December 2016}}

Endogenous DNA damages occur frequently including about 50 double-strand DNA breaks per cell cycle{{cite journal | vauthors = Vilenchik MM, Knudson AG | title = Endogenous DNA double-strand breaks: production, fidelity of repair, and induction of cancer | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 100 | issue = 22 | pages = 12871–12876 | date = October 2003 | pmid = 14566050 | pmc = 240711 | doi = 10.1073/pnas.2135498100 | doi-access = free | bibcode = 2003PNAS..10012871V }} and about 10,000 oxidative damages per day (see DNA damage (naturally occurring)). During repair of double-strand breaks many epigenetic alterations are introduced, and in a percentage of cases epigenetic alterations remain after repair is completed, including increased methylation of CpG island promoters.{{cite journal | vauthors = Cuozzo C, Porcellini A, Angrisano T, Morano A, Lee B, Di Pardo A, Messina S, Iuliano R, Fusco A, Santillo MR, Muller MT, Chiariotti L, Gottesman ME, Avvedimento EV | display-authors = 6 | title = DNA damage, homology-directed repair, and DNA methylation | journal = PLOS Genetics | volume = 3 | issue = 7 | pages = e110 | date = July 2007 | pmid = 17616978 | pmc = 1913100 | doi = 10.1371/journal.pgen.0030110 | doi-access = free }}{{cite journal | vauthors = O'Hagan HM, Mohammad HP, Baylin SB | title = Double strand breaks can initiate gene silencing and SIRT1-dependent onset of DNA methylation in an exogenous promoter CpG island | journal = PLOS Genetics | volume = 4 | issue = 8 | pages = e1000155 | date = August 2008 | pmid = 18704159 | pmc = 2491723 | doi = 10.1371/journal.pgen.1000155 | doi-access = free }}{{cite journal | vauthors = Morano A, Angrisano T, Russo G, Landi R, Pezone A, Bartollino S, Zuchegna C, Babbio F, Bonapace IM, Allen B, Muller MT, Chiariotti L, Gottesman ME, Porcellini A, Avvedimento EV | display-authors = 6 | title = Targeted DNA methylation by homology-directed repair in mammalian cells. Transcription reshapes methylation on the repaired gene | journal = Nucleic Acids Research | volume = 42 | issue = 2 | pages = 804–821 | date = January 2014 | pmid = 24137009 | pmc = 3902918 | doi = 10.1093/nar/gkt920 }} Similar, but usually transient epigenetic alterations were recently found during repair of oxidative damages caused by H₂O₂, and it was suggested that occasionally these epigenetic alterations may also remain after repair.{{cite journal | vauthors = Ding N, Bonham EM, Hannon BE, Amick TR, Baylin SB, O'Hagan HM | title = Mismatch repair proteins recruit DNA methyltransferase 1 to sites of oxidative DNA damage | journal = Journal of Molecular Cell Biology | volume = 8 | issue = 3 | pages = 244–254 | date = June 2016 | pmid = 26186941 | pmc = 4937888 | doi = 10.1093/jmcb/mjv050 }} These accumulated epigenetic alterations may contribute to the epigenetic clock. Accumulation of epigenetic alterations may parallel the accumulation of un-repaired DNA damages that are proposed to cause aging (see DNA damage theory of aging). In line with stochastic DNA damage accumulation, age-related alterations in DNA methylation have been observed to predominantly undergo stochastic changes as individuals age.{{Cite journal |last1=Tarkhov |first1=Andrei E. |last2=Lindstrom-Vautrin |first2=Thomas |last3=Zhang |first3=Sirui |last4=Ying |first4=Kejun |last5=Moqri |first5=Mahdi |last6=Zhang |first6=Bohan |last7=Tyshkovskiy |first7=Alexander |last8=Levy |first8=Orr |last9=Gladyshev |first9=Vadim N. |date=2024-05-09 |title=Nature of epigenetic aging from a single-cell perspective |url=https://www.nature.com/articles/s43587-024-00616-0 |journal=Nature Aging |volume=4 |issue=6 |language=en |pages=854–870 |doi=10.1038/s43587-024-00616-0 |pmid=38724733 |issn=2662-8465}} This accumulation of stochastic variation has demonstrated sufficient capacity to build aging clocks, further supporting the notion that epigenetic changes may be driven by the gradual accrual of unprogrammed stochastic damage.{{Cite journal |last1=Meyer |first1=David H. |last2=Schumacher |first2=Björn |date=2024-05-09 |title=Aging clocks based on accumulating stochastic variation |journal=Nature Aging |volume=4 |issue=6 |language=en |pages=871–885 |doi=10.1038/s43587-024-00619-x |pmid=38724736 |issn=2662-8465|pmc=11186771 }}

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{{refend}}

• {{Cite web |last=Wickelgren |first=Ingrid |date=2022-08-17 |title=Epigenetic 'Clocks' Predict Animals' True Biological Age |url=https://www.quantamagazine.org/epigenetic-clocks-predict-animals-true-biological-age-20220817/|website=Quanta Magazine |language=en}}

Category:Ageing

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Category:Biogerontology

Category:Epigenetics

Category:Life extension