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References
50
[1]
Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2163–2196. 10.1016/s0140-6736(12)61729-2
[2]
Bocklandt S, Lin W, Sehl ME, Sánchez FJ, Sinsheimer JS, Horvath S et al. Epigenetic predictor of age. PLoS ONE 2011; 6: e14821. 10.1371/journal.pone.0014821
[3]
Horvath S . DNA methylation age of human tissues and cell types. Genome Biol 2013; 14: R115. 10.1186/gb-2013-14-10-r115
[4]
Kruk PA, Rampino NJ, Bohr VA . DNA damage and repair in telomeres: relation to aging. Proc Natl Acad Sci USA 1995; 92: 258–262. 10.1073/pnas.92.1.258
[5]
Vanhooren V, Dewaele S, Libert C, Engelborghs S, De Deyn PP, Toussaint O et al. Serum N-glycan profile shift during human ageing. Exp Gerontol 2010; 45: 738–743. 10.1016/j.exger.2010.08.009
[6]
Krishnamurthy J, Torrice C, Ramsey MR, Kovalev GI, Al-Regaiey K, Su L et al. Ink4a/Arf expression is a biomarker of aging. J Clin Invest 2004; 114: 1299–1307. 10.1172/jci22475
[7]
Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G . The hallmarks of aging. Cell 2013; 153: 1194–1217. 10.1016/j.cell.2013.05.039
[8]
Tucker-Drob EM . Neurocognitive functions and everyday functions change together in old age. Neuropsychology 2011; 25: 368–377. 10.1037/a0022348
[9]
Raz N, Rodrigue KM . Differential aging of the brain: patterns, cognitive correlates and modifiers. Neurosci Biobehav Rev 2006; 30: 730–748. 10.1016/j.neubiorev.2006.07.001
[10]
Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, Toga AW . Mapping cortical change across the human life span. Nat Neurosci 2003; 6: 309–315. 10.1038/nn1008
[11]
Fjell AM, Westlye LT, Grydeland H, Amlien I, Espeseth T, Reinvang I et al. Critical ages in the life course of the adult brain: nonlinear subcortical aging. Neurobiol Aging 2013; 34: 2239–2247. 10.1016/j.neurobiolaging.2013.04.006
[12]
Ritchie SJ, Dickie DA, Cox SR, Valdes Hernandez MDC, Corley J, Royle NA et al. Brain volumetric changes and cognitive ageing during the eighth decade of life. Hum Brain Mapp 2015; 36: 4910–4925. 10.1002/hbm.22959
[13]
Royle NA, Booth T, Valdés Hernández MC, Penke L, Murray C, Gow AJ et al. Estimated maximal and current brain volume predict cognitive ability in old age. Neurobiol Aging 2013; 34: 2726–2733. 10.1016/j.neurobiolaging.2013.05.015
[14]
Deary IJ, Bastin ME, Pattie A, Clayden JD, Whalley LJ, Starr JM et al. White matter integrity and cognition in childhood and old age. Neurology 2006; 66: 505–512. 10.1212/01.wnl.0000199954.81900.e2
[15]
Shenkin SD, Bastin ME, MacGillivray TJ, Deary IJ, Starr JM, Rivers CS et al. Cognitive correlates of cerebral white matter lesions and water diffusion tensor parameters in community-dwelling older people. Cerebrovasc Dis 2005; 20: 310–318. 10.1159/000087930
[16]
Franke K, Ziegler G, Klöppel S, Gaser C . Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: exploring the influence of various parameters. Neuroimage 2010; 50: 883–892. 10.1016/j.neuroimage.2010.01.005
[17]
Franke K, Gaser C . Longitudinal changes in individual BrainAGE in healthy aging, mild cognitive impairment, and Alzheimer's Disease. GeroPsych 2012; 25: 235–245. 10.1024/1662-9647/a000074
[18]
Gaser C, Franke K, Klöppel S, Koutsouleris N, Sauer H . BrainAGE in mild cognitive impaired patients: predicting the conversion to Alzheimer's Disease. PLoS ONE 2013; 8: e67346. 10.1371/journal.pone.0067346
[19]
Koutsouleris N, Davatzikos C, Borgwardt S, Gaser C, Bottlender R, Frodl T et al. Accelerated brain aging in schizophrenia and beyond: a neuroanatomical marker of psychiatric disorders. Schizophr Bull 2013; 40: 1140–1153. 10.1093/schbul/sbt142
[20]
Cole JH, Leech R, Sharp DJ, for the Alzheimer's Disease Neuroimaging I. Prediction of brain age suggests accelerated atrophy after traumatic brain injury. Ann Neurol 2015; 77: 571–581. 10.1002/ana.24367
[21]
Steffener J, Habeck C, O'Shea D, Razlighi Q, Bherer L, Stern Y . Differences between chronological and brain age are related to education and self-reported physical activity. Neurobiol Aging 2016; 40: 138–144. 10.1016/j.neurobiolaging.2016.01.014
[22]
Luders E, Cherbuin N, Gaser C . Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners. Neuroimage 2016; 134: 508–513. 10.1016/j.neuroimage.2016.04.007
[23]
Sprott RL . Biomarkers of aging and disease: introduction and definitions. Exp Gerontol 2010; 45: 2–4. 10.1016/j.exger.2009.07.008
[24]
Cevenini E, Invidia L, Lescai F, Salvioli S, Tieri P, Castellani G et al. Human models of aging and longevity. Expert Opin Biol Ther 2008; 8: 1393–1405. 10.1517/14712598.8.9.1393
[25]
Cawthon RM, Smith KR, O'Brien E, Sivatchenko A, Kerber RA . Association between telomere length in blood and mortality in people aged 60 years or older. Lancet 2003; 361: 393–395. 10.1016/s0140-6736(03)12384-7
[26]
Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol 2015; 16: 25. 10.1186/s13059-015-0584-6
[27]
Deary IJ, Gow AJ, Pattie A, Starr JM . Cohort profile: the Lothian Birth Cohorts of 1921 and 1936. Int J Epidemiol 2012; 41: 1576–1584. 10.1093/ije/dyr197
[28]
Deary IJ, Gow AJ, Taylor MD, Corley J, Brett C, Wilson V et al. The Lothian Birth Cohort 1936: A study to examine influences on cognitive ageing from age 11 to age 70 and beyond. BMC Geriatr 2007; 7: 28. 10.1186/1471-2318-7-28
[29]
Scottish Council for Research in Education The Trend of Scottish intelligence: A Comparison of the 1947 and 1932 Surveys of the Intelligence of eleven-year-old Pupils. University of London Press: London, 1949.
[30]
Lara J, Godfrey A, Evans E, Heaven B, Brown LJE, Barron E et al. Towards measurement of the Healthy Ageing Phenotype in lifestyle-based intervention studies. Maturitas 2013; 76: 189–199. 10.1016/j.maturitas.2013.07.007
[31]
Booth T, Starr JM, Deary I . Modeling multisystem biological risk in later life: allostatic load in the lothian birth cohort study 1936. Am J Hum Biol 2013; 25: 538–543. 10.1002/ajhb.22406
[32]
Marioni RE, Shah S, McRae AF, Ritchie SJ, Muniz-Terrera G, Harris SE et al. The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936. Int J Epidemiol 2015; 44: 1388–1396. 10.1093/ije/dyu277
[33]
Harris SE, Martin-Ruiz C, von Zglinicki T, Starr JM, Deary IJ . Telomere length and aging biomarkers in 70-year-olds: the Lothian Birth Cohort 1936. Neurobiol Aging 2012; 33: 1486.e1483–1488. 10.1016/j.neurobiolaging.2010.11.013
[34]
Miller KL, Alfaro-Almagro F, Bangerter NK, Thomas DL, Yacoub E, Xu J et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci 2016; 19: 1523–1536. 10.1038/nn.4393
[35]
Horvath S, Levine AJ . HIV-1 infection accelerates age according to the epigenetic clock. J Infect Dis 2015; 212: 1563–1573. 10.1093/infdis/jiv277
[36]
Horvath S, Garagnani P, Bacalini MG, Pirazzini C, Salvioli S, Gentilini D et al. Accelerated epigenetic aging in Down syndrome. Aging Cell 2015; 14: 491–495. 10.1111/acel.12325
[37]
Horvath S, Erhart W, Brosch M, Ammerpohl O, Von Schönfels W, Ahrens M et al. Obesity accelerates epigenetic aging of human liver. Proc Natl Acad Sci USA 2014; 111: 15538–15543. 10.1073/pnas.1412759111
[38]
Sabayan B, van der Grond J, Westendorp RG, van Buchem MA, de Craen AJ . Accelerated progression of white matter hyperintensities and subsequent risk of mortality: a 12-year follow-up study. Neurobiol Aging 2015; 36: 2130–2135. 10.1016/j.neurobiolaging.2015.03.003
[39]
Olesen PJ, Guo X, Gustafson D, Börjesson-Hanson A, Sacuíu S, Eckerström C et al. A population-based study on the influence of brain atrophy on 20-year survival after age 85. Neurology 2011; 76: 879–886. 10.1212/wnl.0b013e31820f2e26
[40]
Staff RT, Murray AD, Ahearn T, Salarirad S, Mowat D, Starr JM et al. Brain volume and survival from age 78 to 85: The contribution of alzheimer-type magnetic resonance imaging findings. J Am Geriatr Soc 2010; 58: 688–695. 10.1111/j.1532-5415.2010.02765.x
[41]
Van Elderen SS, Zhang Q, Sigurdsson S, Haight TJ, Lopez O, Eiriksdottir G et al. Brain volume as an integrated marker for the risk of death in a community-based sample: age gene/environment susceptibility-reykjavik study. J Gerontol A Biol Sci Med Sci 2016; 71: 131–137. 10.1093/gerona/glu192
[42]
Ikram MA, Vernooij MW, Vrooman HA, Hofman A, Breteler MMB . Brain tissue volumes and small vessel disease in relation to the risk of mortality. Neurobiol Aging 2009; 30: 450–456. 10.1016/j.neurobiolaging.2007.07.009
[43]
The IST-3 collaborative group. Association between brain imaging signs, early and late outcomes, and response to intravenous alteplase after acute ischaemic stroke in the third International Stroke Trial (IST-3): secondary analysis of a randomised controlled trial. Lancet Neurol 2015; 14: 485–496. 10.1016/s1474-4422(15)00012-5
[44]
Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A Jr, Orlandini A et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet 2015; 386: 266–273. 10.1016/s0140-6736(14)62000-6
[45]
Grip Strength Predicts Cause-Specific Mortality in Middle-Aged and Elderly Persons

Hideo Sasaki, Fumiyoshi Kasagi, Michiko Yamada et al.

The American Journal of Medicine 2007 10.1016/j.amjmed.2006.04.018
[46]
Sayer AA, Kirkwood TBL . Grip strength and mortality: a biomarker of ageing? Lancet 2015; 386: 226–227. 10.1016/s0140-6736(14)62349-7
[47]
Schunemann HJ, Dorn J, Grant BJ, Winkelstein W Jr., Trevisan M . Pulmonary function is a long-term predictor of mortality in the general population: 29-year follow-up of the Buffalo Health Study. Chest 2000; 118: 656–664. 10.1378/chest.118.3.656
[48]
Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M et al. Gait speed and survival in older adults. J Am Med Assoc 2011; 305: 50–58. 10.1001/jama.2010.1923
[49]
Swan GE, Carmelli D, Larue A . Performance on the digit symbol substitution test and 5-year mortality in the western collaborative group study. Am J Epidemiol 1995; 141: 32–40. 10.1093/oxfordjournals.aje.a117342
[50]
Seeman TE, McEwen BS, Rowe JW, Singer BH . Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proc Natl Acad Sci USA 2001; 98: 4770–4775. 10.1073/pnas.081072698
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Published
Apr 25, 2017
Vol/Issue
23(5)
Pages
1385-1392
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Cite This Article
J H Cole, S J Ritchie, M E Bastin, et al. (2017). Brain age predicts mortality. Molecular Psychiatry, 23(5), 1385-1392. https://doi.org/10.1038/mp.2017.62