Epigenetic age acceleration has been studied as a promising biomarker of age-related conditions, including cognitive aging. This pilot study aims to explore potential cognitive aging-related biomarkers by investigating the relationship of epigenetic age acceleration and cognitive function and by examining the epigenetic age acceleration differences between successful cognitive aging (SCA) and normal cognitive aging (NCA) among Korean community-dwelling older adults (CDOAs).
Methods:
We used data and blood samples of Korean CDOAs from the Korean Frailty and Aging Cohort Study. The participants were classified into two groups, SCA (above the 50th percentile in all domains of cognitive function) and NCA. The genome-wide DNA methylation profiling array using Illumina Infinium MethylationEPIC BeadChip was used to calculate the following: the DNA methylation age, universal epigenetic age acceleration, intrinsic epigenetic age acceleration (IEAA), and extrinsic epigenetic age acceleration (EEAA). We also used Pearson correlation analysis and independent t-tests to analyze the data.
Results:
Universal age acceleration correlated with the Frontal Assessment Battery test results (r = −0.42, p = 0.025); the EEAA correlated with the Word List Recognition test results (r = −0.41, p = 0.027). There was a significant difference between SCA and NCA groups in IEAA (p = 0.041, Cohen’s d = 0.82) and EEAA (p = 0.042, Cohen’s d = 0.78).
Conclusions:
Epigenetic age acceleration can be used as a biomarker for early detection of cognitive decline in Korean community-dwelling older adults. Large longitudinal studies are warranted.
BaumgartM.SnyderH. M.CarrilloM. C.FazioS.KimH.JohnsH. (2015). Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective. Alzheimer’s & Dementia, 11(6), 718–726. https://doi.org/10.1016/j.jalz.2015.05.016
3.
BeydounM. A.ShakedD.TajuddinS. M.WeissJ.EvansM. K.ZondermanA. B. (2020). Accelerated epigenetic age and cognitive decline among urban-dwelling adults. Neurology, 94(6), e613–e625. https://doi.org/10.1212/wnl.0000000000008756
4.
CarrollJ. E.IrwinM. R.LevineM.SeemanT. E.AbsherD.AssimesT.HorvathS. (2017). Epigenetic aging and immune senescence in women with insomnia symptoms: Findings from the women’s health initiative study. Biological Psychiatry, 81(2), 136–144. https://doi.org/10.1016/j.biopsych.2016.07.008
5.
ChenB. H.MarioniR. E.ColicinoE.PetersM. J.Ward-CavinessC. K.TsaiP. C.RoetkerN. S.JustA. C.DemerathE. W.GuanW.BresslerJ.FornageM.StudenskiS.VandiverA. R.MooreA. Z.TanakaT.KielD. P.LiangL.VokonasP.…HorvathS. (2016). DNA methylation-based measures of biological age: Meta-analysis predicting time to death. Aging, 8(9), 1844–1865. https://doi.org/10.18632/aging.101020
6.
ChoiH. J.LeeD. Y.SeoE. H.JoM. K.SohnB. K.ChoeY. M.ByunM. S.KimJ. W.KimS. G.YoonJ. C.JhooJ. H.KimK. W.WooJ. I. (2014). A normative study of the digit span in an educationally diverse elderly population. Psychiatry Investigation, 11(1), 39–43. https://doi.org/10.4306/pi.2014.11.1.39
7.
DegermanS.JosefssonM.AdolfssonA. N.WennstedtS.LandforsM.HaiderZ.PudasS.HultdinM.NybergL.AdolfssonR. (2017). Maintained memory in aging is associated with young epigenetic age. Neurobiology of Aging, 55, 167–171. https://doi.org/10.1016/j.neurobiolaging.2017.02.009
8.
DhingraR.KweeL. C.Diaz-SanchezD.DevlinR. B.CascioW.HauserE. R.GregoryS.ShahS.KrausW. E.OldenK.OldenK. (2019). Evaluating DNA methylation age on the Illumina methylationepic bead chip. PLoS One, 14(4), e0207834. https://doi.org/10.1371/journal.pone.0207834
9.
DuguéP.BassettJ. K.JooJ. E.JungC.Ming WongE.Moreno-BetancurM.SchmidtD.MakalicE.LiS.SeveriG.HodgeA. M.BuchananD. D.EnglishD. R.HopperJ. L.SoutheyM. C.GilesG. G.SeveriG. (2018). DNA methylation-based biological aging and cancer risk and survival: Pooled analysis of seven prospective studies. International Journal of Cancer, 142(8), 1611–1619. https://doi.org/10.1002/ijc.31189
HertzogM. A. (2008). Considerations in determining sample size for pilot studies. Research in Nursing & Health, 31(2), 180–191. https://doi.org/10.1002/nur.20247
HorvathS.RajK. (2018). DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nature Reviews Genetics, 19(6), 371. https://doi.org/10.1038/s41576-018-0004-3
14.
IqbalK.LiuF.GongC. (2014). Alzheimer disease therapeutics: Focus on the disease and not just plaques and tangles. Biochemical Pharmacology, 88(4), 631–639. https://doi.org/10.1016/j.bcp.2014.01.002
15.
KimK. W.GwakK. P.KimB. J.KimS. Y.KimS. K.KimJ. L.KimT. H.MoonS. W.ParkJ. H.BaeJ. N. (2012). 2012 National study on the prevalence of dementia in Korean elders. Seoul National University Bundang Hospital.
16.
KimM. D.HongS. C.LeeC. I.KimS. Y.KangI. O.LeeS. Y. (2009). Caregiver burden among caregivers of Koreans with dementia. Gerontology, 55(1), 106–113. https://doi.org/10.1159/000176300
17.
KimT. H.HuhY.ChoeJ. Y.JeongJ. W.ParkJ. H.LeeS. BLeeJ. J.JhooJ. H.LeeD. Y.WooJ. I.KimK. W. (2010). Korean version of frontal assessment battery: Psychometric properties and normative data. Dementia and Geriatric Cognitive Disorders, 29(4), 363–370. https://doi.org/10.1159/000297523
18.
LeeD. Y.LeeK. U.LeeJ. H.KimK. W.JhooJ. H.KimS. Y.YoonJ. C.WooS. I.HaJ.WooJ. I. (2004). A normative study of the CERAD neuropsychological assessment battery in the Korean elderly. Journal of the International Neuropsychological Society, 10(1), 72–81. https://doi.org/10.1017/s1355617704101094
19.
LeeJ. H.LeeK. U.LeeD. Y.KimK. W.JhooJ. H.KimJ. H.LeeK. H.KimS. Y.HanS. H.WooJ. I. (2002). Development of the Korean version of the consortium to establish a registry for Alzheimer’s disease assessment packet (CERAD-K) clinical and neuropsychological assessment batteries. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 57(1), P47–P53. https://doi.org/10.1093/geronb/57.1.p47
20.
LeeK.CheongH.OhB.HongC. (2009). Comparison of the validity of screening tests for dementia and mild cognitive impairment of the elderly in a community: K-MMSE, MMSE-K, MMSE-KC, and K-HDS. Journal of Korean Neuropsychiatric Association, 48(2), 61–69.
21.
LegdeurN.HeymansM.ComijsH.HuismanM.MaierA.VisserP. (2018). Age dependency of risk factors for cognitive decline. BMC Geriatrics, 18(1), 187. https://doi.org/10.1186/s12877-018-0876-2
22.
LevineM. E.LuA. T.BennettD. A.HorvathS. (2015). Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning. Aging, 7(12), 1198–1211. https://doi.org/10.18632/aging.100864
23.
LevineM. E.LuA. T.QuachA.ChenB. H.AssimesT. L.BandinelliS.HouL.BaccarelliA. A.StewartJ. D.LiY.WhitselE. A.WilsonJ. G.ReinerA. P.AvivA.LohmanK.LiuY.FerrucciL.HorvathS. (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging, 10(4), 573–591. https://doi:10.18632/aging.101414
24.
LipnickiD. M.SachdevP. S.CrawfordJ.ReppermundS.KochanN. A.TrollorJ. N.DraperB.SlavinM. J.KangK.MatherK. A.LuxO.LuxO. (2013). Risk factors for late-life cognitive decline and variation with age and sex in the Sydney memory and ageing study. PLoS One, 8(6), e65841. https://doi.org/10.1371/journal.pone.0065841
25.
LuA. T.HannonE.LevineM. E.CrimminsE. M.LunnonK.MillJ.GeschwindD. H.HorvathS. (2017). Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nature Communications, 8, 15353. https://doi.org/10.1038/ncomms15353
26.
MarioniR. E.ShahS.McRaeA. F.RitchieS. J.Muniz-TerreraG.HarrisS. E.GibsonJ.RedmondP.CoxS. R.PattieA.CorleyJ.TaylorA.MurphyL.StarrJ. M.HorvathS.VisscherP. M.WrayN. R.PattieA. (2015). The epigenetic clock is correlated with physical and cognitive fitness in the Lothian birth cohort 1936. International Journal of Epidemiology, 44(4), 1388–1396. https://doi.org/10.1093/ije/dyu277
27.
MartinE. M.FryR. C. (2018). Environmental influences on the epigenome: Exposure-associated DNA methylation in human populations. Annual Review of Public Health, 39, 309–333. https://doi.org/10.1146/annurev-publhealth-040617-014629
28.
NegashS.SmithG. E.PankratzS.AakreJ.GedaY. E.RobertsR. O.KnopmanD. S.BoeveB. F.IvnikR. J.PetersenR. C. (2011). Successful aging: Definitions and prediction of longevity and conversion to mild cognitive impairment. The American Journal of Geriatric Psychiatry, 19(6), 581–588. https://doi.org/10.1097/JGP.0b013e3181f17ec9
29.
PetersenR. C.RobertsR. O.KnopmanD. S.GedaY. E.ChaR. H.PankratzV. S.BoeveB. F.TangalosE. G.IvnikR. J.RoccaW. A. (2010). Prevalence of mild cognitive impairment is higher in men: The Mayo Clinic Study of Aging. Neurology, 75(10), 889–897. https://doi.org/10.1212/WNL.0b013e3181f11d85
SmithG. E. (2016). Healthy cognitive aging and dementia prevention. American Psychologist, 71(4), 268. https://doi.org/10.1037/a0040250
33.
WonC. W.LeeS.KimJ.ChonD.KimS.KimC.KimM. K.ChoB.ChoiK. M.RohE.JangH. C.SonS. J.LeeJ. H.ParkY. S.LeeS. G.KimB. J.KimB. J.KimH. J.ChoiJ.GaH.LeeK. J.LeeY.RohE. (2020). Korean frailty and aging cohort study (KFACS): Cohort profile. BMJ Open, 10(4), e035573. https://doi.org/10.1136/bmjopen-2019-035573
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
