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当代阿耳茨海默病研究

Editor-in-Chief

ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

Research Article

外周血表观遗传加速老化并不能预测痴呆风险

卷 18, 期 5, 2021

发表于: 23 August, 2021

页: [443 - 451] 页: 9

弟呕挨: 10.2174/1567205018666210823100721

价格: $65

Open Access Journals Promotions 2
摘要

背景:有强有力的证据表明,表观遗传年龄加速与晚年疾病和全因死亡率的风险增加有关。然而,目前有限的证据表明表观遗传年龄的增加与痴呆风险有关。 目的:本研究旨在阐明加速衰老的表观遗传生物标志物是否可以预测痴呆风险,这是一个重要的考虑因素,因为衰老是该疾病的最大风险因素。 方法:从 ASPirin in Reducing Events in the Elderly 研究的 160 名参与者提供的外周血样本中测量 DNA 甲基化,包括 73 名症状前痴呆病例和 87 名年龄、性别、吸烟和教育状况匹配的对照。使用 Horvath、Hannum、GrimAge 和 PhenoAge DNA 甲基化时钟计算表观遗传年龄,并确定年龄加速(实足年龄和表观遗传年龄之间的差异)。 结果:痴呆病例和对照组之间的年龄加速没有差异。在男性中,与对照相比,在症状前痴呆病例中,只有 Hannum 的内在表观遗传年龄加速增加(Δ +1.8 岁,p = 0.03)。 结论:这些发现没有提供强有力的证据表明外周血中测量的表观遗传老化可以预测痴呆风险。

关键词: 加速衰老、痴呆、DNA 甲基化、表观遗传时钟、grimage、hannum、horvath、phenoAge。

« Previous
[1]
Hickman RA, Faustin A, Wisniewski T. Alzheimer disease and its growing epidemic: Risk factors, biomarkers, and the urgent need for therapeutics. Neurol Clin 2016; 34(4): 941-53.[http://dx.doi.org/10.1016/j.ncl.2016.06.009] [PMID: 27720002]
[2]
Booth LN, Brunet A. The aging epigenome. Mol Cell 2016; 62(5): 728-44.[http://dx.doi.org/10.1016/j.molcel.2016.05.013] [PMID: 27259204]
[3]
Zhang W, Qu J, Liu G-H, Belmonte JCI. The ageing epigenome and its rejuvenation. Nat Rev Mol Cell Biol 2020; 21(3): 137-50.[http://dx.doi.org/10.1038/s41580-019-0204-5] [PMID: 32020082]
[4]
Campbell RR, Wood MA. How the epigenome integrates information and reshapes the synapse. Nat Rev Neurosci 2019; 20(3): 133-47.[http://dx.doi.org/10.1038/s41583-019-0121-9] [PMID: 30696992]
[5]
Lyko F. The DNA methyltransferase family: A versatile toolkit for epigenetic regulation. Nat Rev Genet 2018; 19(2): 81-92.[http://dx.doi.org/10.1038/nrg.2017.80] [PMID: 29033456]
[6]
Moore LD, Le T, Fan G. DNA methylation and its basic function. Neuropsychopharmacol 2013; 38(1): 23-38.[http://dx.doi.org/10.1038/npp.2012.112]
[7]
Jin Z, Liu Y. DNA methylation in human diseases. Genes Dis 2018; 5(1): 1-8.[http://dx.doi.org/10.1016/j.gendis.2018.01.002] [PMID: 30258928]
[8]
Nebbioso A, Tambaro FP, Dell’Aversana C, Altucci L. Cancer epigenetics: Moving forward. PLoS Genet 2018; 14(6): e1007362.[http://dx.doi.org/10.1371/journal.pgen.1007362] [PMID: 29879107]
[9]
Soler-Botija C, Gálvez-Montón C, Bayés-Genís A. Epigenetic biomarkers in cardiovascular diseases. Front Genet 2019; 10(950): 950.[http://dx.doi.org/10.3389/fgene.2019.00950] [PMID: 31649728]
[10]
Fransquet PD, Ryan J. The current status of blood epigenetic biomarkers for dementia. Crit Rev Clin Lab Sci 2019; 56(7): 435-57.[http://dx.doi.org/10.1080/10408363.2019.1639129] [PMID: 31328605]
[11]
Horvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet 2018; 19(6): 371-84.[http://dx.doi.org/10.1038/s41576-018-0004-3] [PMID: 29643443]
[12]
Horvath S. DNA methylation age of human tissues and cell types. Genome Biol 2013; 14(10): R115.[http://dx.doi.org/10.1186/gb-2013-14-10-r115] [PMID: 24138928]
[13]
Hannum G, Guinney J, Zhao L, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell 2013; 49(2): 359-67.[http://dx.doi.org/10.1016/j.molcel.2012.10.016] [PMID: 23177740]
[14]
Fransquet PD, Wrigglesworth J, Woods RL, Ernst ME, Ryan J. The epigenetic clock as a predictor of disease and mortality risk: A systematic review and meta-analysis. Clin Epigenetics 2019; 11(1): 62.[http://dx.doi.org/10.1186/s13148-019-0656-7] [PMID: 30975202]
[15]
Ryan J, Wrigglesworth J, Loong J, Fransquet PD, Woods RL. A systematic review and meta-analysis of environmental, lifestyle, and health factors associated with DNA methylation age. J Gerontol A Biol Sci Med Sci 2020; 75(3): 481-94.[http://dx.doi.org/10.1093/gerona/glz099] [PMID: 31001624]
[16]
Levine ME. Modeling the rate of senescence: Can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci 2013; 68(6): 667-74.[http://dx.doi.org/10.1093/gerona/gls233] [PMID: 23213031]
[17]
Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY) 2018; 10(4): 573-91.[http://dx.doi.org/10.18632/aging.101414] [PMID: 29676998]
[18]
Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY) 2019; 11(2): 303-27.[http://dx.doi.org/10.18632/aging.101684] [PMID: 30669119]
[19]
Degerman S, Josefsson M, Nordin Adolfsson A, et al. Maintained memory in aging is associated with young epigenetic age. Neurobiol Aging 2017; 55: 167-71.[http://dx.doi.org/10.1016/j.neurobiolaging.2017.02.009] [PMID: 28292535]
[20]
Horvath S, Ritz BR. Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients. Aging (Albany NY) 2015; 7(12): 1130-42.[http://dx.doi.org/10.18632/aging.100859] [PMID: 26655927]
[21]
Beam CR, Kaneshiro C, Jang JY, Reynolds CA, Pedersen NL, Gatz M. Differences between women and men in incidence rates of dementia and Alzheimer’s disease. J Alzheimers Dis 2018; 64(4): 1077-83.[http://dx.doi.org/10.3233/JAD-180141] [PMID: 30010124]
[22]
Miller IN, Cronin-Golomb A. Gender differences in Parkinson’s disease: Clinical characteristics and cognition. Mov Disord 2010; 25(16): 2695-703.[http://dx.doi.org/10.1002/mds.23388] [PMID: 20925068]
[23]
Horvath S, Gurven M, Levine ME, et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol 2016; 17(1): 171-93.[http://dx.doi.org/10.1186/s13059-016-1030-0] [PMID: 27511193]
[24]
Hillary RF, Stevenson AJ, Cox SR, et al. An epigenetic predictor of death captures multi-modal measures of brain health. Mol Psychiatry 2019.[http://dx.doi.org/10.1038/s41380-019-0616-9] [PMID: 31796892]
[25]
McNeil JJ, Woods RL, Nelson MR, et al. Baseline characteristics of participants in the ASPREE (ASPirin in Reducing Events in the Elderly) study. J Gerontol A Biol Sci Med Sci 2017; 72(11): 1586-93.[http://dx.doi.org/10.1093/gerona/glw342] [PMID: 28329340]
[26]
Ryan J, Woods RL, Britt C, et al. Normative performance of healthy older individuals on the Modified Mini-Mental State (3MS) examination according to ethno-racial group, gender, age, and education level. Clin Neuropsychol 2019; 33(4): 779-97.[http://dx.doi.org/10.1080/13854046.2018.1488996] [PMID: 29976121]
[27]
Jones TG, Schinka JA, Vanderploeg RD, Small BJ, Graves AB, Mortimer JA. 3MS normative data for the elderly. Arch Clin Neuropsychol 2002; 17(2): 171-7.[http://dx.doi.org/10.1093/arclin/17.2.171] [PMID: 14589746]
[28]
Smith A. Symbol digit modalities test : Manual Los Angeles Western Psychological Services 1982.
[29]
Ruff RM, Light RH, Parker SB, Levin HS. Benton controlled oral word association test: Reliability and updated norms. Arch Clin Neuropsychol 1996; 11(4): 329-38.[http://dx.doi.org/10.1093/arclin/11.4.329] [PMID: 14588937]
[30]
Ryan J, Woods RL, Murray AM, et al. Normative performance of older individuals on the Hopkins Verbal Learning Test-Revised (HVLT-R) according to ethno-racial group, gender, age and education level. Clin Neuropsychol 2020; 1-17.[http://dx.doi.org/10.1080/13854046.2020.1730444] [PMID: 32100619]
[31]
Benedict RHB, Schretlen D, Groninger L, Brandt J. Hopkins Verbal Learning Test – Revised: Normative data and analysis of inter- form and test-retest reliability. Clin Neuropsychol 1998; 12(1): 43-55.[http://dx.doi.org/10.1076/clin.12.1.43.1726]
[32]
First MB, Frances A, Pincus HA. DSM-IV-TR handbook of differential diagnosis. Arlington, VA, US American Psychiatric Publishing, Inc 2002.[http://dx.doi.org/10.1176/appi.books.9781585622658]
[33]
Triche TJ Jr, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-level processing of Illumina Infinium DNA Methylation BeadArrays. Nucleic Acids Res 2013; 41(7): e90-0.[http://dx.doi.org/10.1093/nar/gkt090] [PMID: 23476028]
[34]
Ryan J, Storey E, Murray AM, et al. Randomized placebo-controlled trial of the effects of aspirin on dementia and cognitive decline. Neurology 2020; 95(3): e320-31.[http://dx.doi.org/10.1212/WNL.0000000000009277] [PMID: 32213642]
[35]
Sibbett RA, Altschul DM, Marioni RE, Deary IJ, Starr JM, Russ TC. DNA methylation-based measures of accelerated biological ageing and the risk of dementia in the oldest-old: A study of the Lothian Birth Cohort 1921. BMC Psychiatry 2020; 20(1): 91.[http://dx.doi.org/10.1186/s12888-020-2469-9] [PMID: 32111184]
[36]
El Khoury LY, Gorrie-Stone T, Smart M, et al. Systematic underestimation of the epigenetic clock and age acceleration in older subjects. Genome Biol 2019; 20(1): 283.[http://dx.doi.org/10.1186/s13059-019-1810-4] [PMID: 31847916]
[37]
Bell CG, Lowe R, Adams PD, et al. DNA methylation aging clocks: Challenges and recommendations. Genome Biol 2019; 20(1): 249.[http://dx.doi.org/10.1186/s13059-019-1824-y] [PMID: 31767039]
[38]
Palma-Gudiel H, Eixarch E, Crispi F, Morán S, Zannas AS, Fañanás L. Prenatal adverse environment is associated with epigenetic age deceleration at birth and hypomethylation at the hypoxia-responsive EP300 gene. Clin Epigenetics 2019; 11(1): 73.[http://dx.doi.org/10.1186/s13148-019-0674-5] [PMID: 31072398]
[39]
Salas LA, Koestler DC, Butler RA, et al. An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome Biol 2018; 19(1): 64.[http://dx.doi.org/10.1186/s13059-018-1448-7] [PMID: 29843789]
[40]
Illumina Inc. Illumina Infinium MethylationEPIC Array Illumina Inc 2020.
[41]
Pidsley R, Zotenko E, Peters TJ, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol 2016; 17(1): 208-08.[http://dx.doi.org/10.1186/s13059-016-1066-1] [PMID: 27717381]
[42]
McEwen LM, Jones MJ, Lin DTS, et al. Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array. Clin Epigenetics 2018; 10(1): 123.[http://dx.doi.org/10.1186/s13148-018-0556-2] [PMID: 30326963]
[43]
Zhang Q, Vallerga CL, Walker RM, et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Med 2019; 11(1): 54.[http://dx.doi.org/10.1186/s13073-019-0667-1] [PMID: 31443728]
[44]
Braun PR, Han S, Hing B, et al. Genome-wide DNA methylation comparison between live human brain and peripheral tissues within individuals. Transl Psychiatry 2019; 9(1): 47.[http://dx.doi.org/10.1038/s41398-019-0376-y] [PMID: 30705257]
[45]
Shireby GL, Davies JP, Francis PT, et al. Recalibrating the epigenetic clock: Implications for assessing biological age in the human cortex. Brain 2020; 143(12): 3763-75.[http://dx.doi.org/10.1093/brain/awaa334] [PMID: 33300551]
[46]
Grodstein F, Lemos B, Yu L, Iatrou A, De Jager PL, Bennett DA. Characteristics of epigenetic clocks across blood and brain tissue in older women and men. Front Neurosci 2021; 14: 555307-07.[http://dx.doi.org/10.3389/fnins.2020.555307] [PMID: 33488342]

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