Normative Cognitive Aging

  • Wendy JohnsonEmail author
  • Matt McGue
  • Ian J. Deary
Part of the Advances in Behavior Genetics book series (AIBG, volume 1)


In general, average cognitive function declines across much of the adult life span. This decline has come to be understood as normative, though the rates of decline and the ages at which they commence vary across different aspects of function. Decline takes place in the context of much larger variation among individuals of any given age, and the rates of decline show individual differences as well. Although characterization of these normative patterns is now quite good, understanding of what drives the changes is much more limited. In this chapter, we review studies that have used a variety of different behavior genetic analytical approaches to investigate some of the thorniest questions facing cognitive aging, but we also highlight areas ripe for future behavior genetic approaches. We review quantitative genetic studies that have taken both cross-sectional and longitudinal approaches, as well as studies that have examined the extent to which different aspects of cognitive function and variables with which it is associated show common genetic influences. We then turn to behavior genetic contributions to special topics in cognitive aging including intra-individual variability and terminal decline, the problems of sample selectivity, and gene-environment correlation. Following these topics involving aggregate genetic contributions to individual differences, we consider molecular genetic approaches to identifying individual genes involved in cognitive aging.


Telomere Length Genetic Influence Cognitive Aging General Cognitive Ability Shared Environmental Influence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Autry, A. E., & Monteggia, L. M. (2012). Brain-derived neurotrophic factor and neuropsychiatric disorders. Pharmacoloogical Reviews, 64, 238–258.CrossRefGoogle Scholar
  2. Barnett, J. H., Scoriels, L., & Munafo, M. R. (2008). Meta-analysis of the cognitive effects of the catechol-O-methyltransferase gene Val158/108Met polymorphism. Biological Psychiatry, 64, 137–144.PubMedCrossRefGoogle Scholar
  3. Batterham, P. J., Mackinnon, A. J., & Christensen, H. (2011). The effect of education on the onset and rate of terminal decline. Psychology and Aging, 26, 339–350.PubMedCrossRefGoogle Scholar
  4. Bergen, S. E., Gardner, C. O., & Kendler, K. S. (2007). Age-related changes in heritability of behavioral phenotypes over adolescence and young adulthood: A meta-analysis. Twin Research and Human Genetics, 10(3), 423–433.PubMedCrossRefGoogle Scholar
  5. Bielak, A. A., Hultsch, D. F., Strauss, E., MacDonald, S. W., & Hunter, M. A. (2010). Intraindividual variability in reaction time predicts cognitive outcomes 5 years later. Neuropsychology, 24, 731–741.PubMedCrossRefGoogle Scholar
  6. Blennow, K., de Leon, M. J., & Zetterberg, H. (2006). Alzheimer’s disease. Lancet, 368, 387–403.PubMedCrossRefGoogle Scholar
  7. Bosworth, H. B., & Schaie, K. W. (1999). Survival effects in cognitive function, cognitive style, and sociodemographic variables in the Seattle Longitudinal Study. Experimental Aging Research, 25(2), 121–139.PubMedCrossRefGoogle Scholar
  8. Bryk, A. S., & Raudenbush, S. W. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks: Sage.Google Scholar
  9. Calvin, C. M., Deary, I. J., Fenton, C., Roberts, B. A., Der, G., Leckenby, N., & Batty, G. D. (2011). Intelligence in youth and all-case mortality: Systematic review with meta-analysis. International Journal of Epidemiology, 40, 626–644.PubMedCrossRefGoogle Scholar
  10. Carmelli, D., DeCarli, C., Swan, G. E., Jack, L. M., Reed, T., Wolf, P. A., & Miller, B. L. (1998). Evidence for genetic variance in white matter hypersensitivity volume in normal elderly male twins. Stroke, 29(6), 1177–1181.PubMedCrossRefGoogle Scholar
  11. Carroll, J. B. (1993). Human cognitive abilities: A survey of factor analytic studies. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  12. Caspi, A., Williams, B., Kim-Cohen, J., Craig, I. W., Milne, B. J., Poulton, R., et al. (2007). Moderation of breastfeeding effects on the IQ by genetic variation in fatty acid metabolism. Proceedings of the National Academy of Sciences of the United States of America, 104, 18860–18865.PubMedCrossRefGoogle Scholar
  13. Christensen, K., Holm, N. V., McGue, M., Corder, L., & Vaupel, J. W. (1999). A Danish population-based twin study on general health in the elderly. Journal of Aging and Health, 11, 49–64.PubMedCrossRefGoogle Scholar
  14. Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., et al. (2003). Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset. Science, 261, 921–923.CrossRefGoogle Scholar
  15. Craik, F. I. M., & McDowd, J. M. (1987).Age differences in recall and recognition. Journal of Experimental Psychology-Learning Memory and Cognition, 13(3), 474–479. doi:10.1037//0278-7393.13.3.474.Google Scholar
  16. Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., et al. (2011). Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry, 16, 996–1005.PubMedCrossRefGoogle Scholar
  17. De Jager, P. L., Shulman, J. M., Chibnik, L. B., Keenan, B. T., Raj, T., Wilson, R. S., et al. (2012). A genome-wide scan for common variants affecting the rate of age-related cognitive decline. Neurobiology of Aging. doi:10.1016/j.neurobiolaging.2011.09.033.Google Scholar
  18. Deary, I. J. (2000). Looking down on human intelligence. Oxford: Oxford University Press.CrossRefGoogle Scholar
  19. Deary, I. J., & Der, G. (2005). Reaction time, age, and cognitive ability: Longitudinal findings from age 16 to 63 years in representative population samples. Aging, Neuropsychology, and Cognition, 12, 187–215.CrossRefGoogle Scholar
  20. Deary, I. J., Whiteman, M. C., Pattie, A., Starr, J. M., Hayward, C., Wright, A. F., Carothers, A., & Whalley, L. J. (2002). Cognitive change and the APOE e4 allele. Nature, 418, 932.PubMedCrossRefGoogle Scholar
  21. Deary, I. J., Yang, J., Davies, G., Harries, S. E., Tenesa, A., et al. (2012). Genetic contributions to stability and change in intelligence from childhood to old age. Nature, 482, 212–215.PubMedGoogle Scholar
  22. Deary, I. J., Johnson, W., & Houlihan, L. (2009). Genetic foundations of human intelligence. Human Genetics, 126, 613–624.Google Scholar
  23. Dickinson, D., & Elevag, B. (2009). Genes, cognition and brain through a COMT lens. Neuroscience, 164, 72–87.PubMedCrossRefGoogle Scholar
  24. Dincheva, I., Glatt, C. E., & Lee, F. S. (2012). Impact of the BDNF Val66Met polymorphism on cognition: implications for behavioral genetics. The Neuroscientist. doi:10.1177/1073858411431646.Google Scholar
  25. Feil, R., & Fraga, M. F. (2012). Epigenetics and the environment: emerging patterns and implications. Nature Reviews Genetics, 13, 97–109.PubMedGoogle Scholar
  26. Finkel, D., & McGue, M. (1993). The origins of individual differences in memory among the elderly: A behavior genetic. Psychology and Aging, 8, 527–537.PubMedCrossRefGoogle Scholar
  27. Finkel, D., & McGue, M. (2007). Genetic and environmental influences on intraindividual variability in reaction time. Experimental Aging Research, 33(1), 13–35.PubMedCrossRefGoogle Scholar
  28. Finkel, D., & Pedersen, N. (2004). Processing speed and longitudinal trajectories of change for cognitive abilities: the Swedish Adoption/Twin Study of Aging. Aging Neuropsychology and Cognition, 11, 325–345.CrossRefGoogle Scholar
  29. Finkel, D., & Reynolds, C. A. (2010). Behavioral Genetic Investigations of Cognitive Aging. In Y. K. Kim (Ed.), Handbook of Behavior Genetics (pp. 101–112). New York: Springer.Google Scholar
  30. Finkel, D., Pedersen, N. L., McGue, M., & McClearn, G. E. (1995). Heritability of cognitive abilities in adult twins: Comparison of Minnesota and Swedish data. Behavior Genetics, 25, 421–431.PubMedCrossRefGoogle Scholar
  31. Finkel, D., Reynolds, C. A., McArdle, J. J., & Pedersen, N. (2005). The longitudinal relationship between processing speed and cognitive ability: Genetic and environmental influences. Behavior Genetics, 35, 535–549.PubMedCrossRefGoogle Scholar
  32. Finkel, D., McArdle, J. J., Reynolds, C. A., & Pedersen, N. L. (2007). Age changes in processing speed as a leading indicator of cognitive aging. Psychology and Aging, 22(3), 558–568.PubMedCrossRefGoogle Scholar
  33. Finkel, D., Andel, R., Gatz, M., & Pedersen, N. L. (2009). The role of occupational complexity in trajectories of cognitive aging before and after retirement. Psychology and Aging, 24, 563–573.PubMedCrossRefGoogle Scholar
  34. Finkel, D., Reynolds, C. A., McArdle, J. J., Hamagami, F., & Pedersen, N. L. (2009). Genetic variance in processing speed drives variation in aging of spatial and memory abilities. Developmental Psychology, 45, 820–834.PubMedCrossRefGoogle Scholar
  35. Fjell, A. M., & Walhovd, K. B. (2010). Structural brain changes in aging: Courses, causes and cognitive consequences. Reviews in the Neurosciences, 21(3), 187–221.PubMedCrossRefGoogle Scholar
  36. Fuentes, K., Hunter, M. A., Strauss, E., & Hultsch, D. F. (2001). Intraindividual variability in cognitive performance in persons with chronic fatigue syndrome. Clinical Neuropsychologist, 15, 210–227.PubMedCrossRefGoogle Scholar
  37. Gatz, M., Fratiglioni, L., Johansson, B., Berg, S., Mortimer, J. A., Reynolds, C. A., Fiske, A., Pedersen, N. L. (2005). Complete ascertainment of dementia in the Swedish Twin Registry: The HARMONY study. Neurobiology of Aging, 26, 439–447.PubMedCrossRefGoogle Scholar
  38. Gerstorf, D., Ram, N., Hoppmann, C., Willis, S. L., & Schaie, K. W. (2011). Cohort differences in cognitive aging and terminal decline in the Seattle Longitudinal Study. Developmental Psychology, 47, 1026–1041.PubMedCrossRefGoogle Scholar
  39. Geschwind, D. H., & Konopka, G. (2009). Neuroscience in the era of functional genomics and systems biology. Nature, 461, 908–915.PubMedCrossRefGoogle Scholar
  40. Giubilei, F., Medda, E., Fagnani, C., Bianchi, V., De Carolis, A., Salvetti, M., Stazi, M. A. (2008).Heritability of neurocognitive functioning in the elderly: Evidence from an Italian twin study. Age and Aging, 37(6), 640–646. doi:10.1093/aging/afn132.Google Scholar
  41. Hamilton, G., Harris, S. E., Davies, G., Liewald, D. C., Tenesa, A., Starr, J. M., Porteous, D., & Deary, I. J. (2011). Alzheimer’s disease genes are associated with measures of cognitive aging in the Lothian Birth Cohorts of 1921 and 1936. International Journal of Alzheimer’s Disease, 2011, 505984.PubMedGoogle Scholar
  42. Harris, S. E., & Deary, I. J. (2011). The genetics of cognitive ability and cognitive aging in healthy older people. Trends in Cognitive Sciences, 15, 388–394.PubMedGoogle Scholar
  43. Harris, S. E., Fox, H., Wright, A. F., Hayward, C., Starr, J. M., Whalley, L. J., & Deary, I. J. (2007). A genetic association analysis of cognitive ability and cognitive aging using 325 markers for 109 genes associated with oxidative stress or cognition. BMC Genetics, 8, 43.PubMedCrossRefGoogle Scholar
  44. Harris, S. E., Martin-Ruiz, C., von Zglinicki, T., Starr, J. M., & Deary, I. J. (2010). Telomere length and aging biomarkers in 70 year-olds: The Lothian Birth Cohort 1936. Neurobiology of Aging. doi:10.1016/j.neurobiolaging.2010.11.013.Google Scholar
  45. Haworth, C. M. A., Wright, M. J., Luciano, M., Martin, N. G., de Geus, E. J. C., van Beijsterveldt, C. E. M., Plomin, R. (2010).The heritability of general cognitive ability increases linearly from childhood to young adulthood. Molecular Psychiatry, 15(11), 1112–1120. doi: 10.1038/mp.2009.55.Google Scholar
  46. Hernandez, D. G., Nalls, M. A., Gibbs, J. R., Arepalli, S., van der Brug, M., Chong, S., et al. (2011). Distinct DNA methylation changes highly correlated with chronological age in the human brain. Human Molecular Genetics, 20, 1164–1172.PubMedCrossRefGoogle Scholar
  47. Hoffman, L., Hofer, S. H., & Sliwinski, M. J. (2011). On the confounds among retest gains and age-cohort differences in the estimation of within-person change in longitudinal studies: A simulation study. Psychology and Aging, 26, 778–791.PubMedCrossRefGoogle Scholar
  48. Hultsch, D. F., MacDonald, S. W., Hunter, M. A., Levy-Benchton, J., & Strauss, E. (2000). Intraindividual variability in cognitive performance in older adults: Comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology, 14, 588–598.PubMedCrossRefGoogle Scholar
  49. Ihle, A., Bunce, D., & Kliegel, M. (2012). APOE e4 and cognitive function in early life: a meta-analysis. Neuropsychology. doi:10.1037/a0026769.Google Scholar
  50. Jarvik, L. F., & Falek, A. (1963). Intellectual stability and survival in the aged. Journal of Gerontology, 18, 173–176.PubMedCrossRefGoogle Scholar
  51. Johansson, B., Hofer, S. M., Allaire, J. C., Maldonado-Molina, M. M., Piccinin, A. M., Berg, S., et al. (2004). Change in cognitive capabilities in the oldest old: The effects of proximity to death in genetically related individuals over a 6-year period. Psychology and Aging, 19, 145–156.PubMedCrossRefGoogle Scholar
  52. Johnson, W. (2007). Genetic and environmental influences on behavior: Capturing all the interplay. Psychological Review, 114, 423–440.PubMedCrossRefGoogle Scholar
  53. Johnson, W. (2011). What do genes have to do with cognition? In S. Kreitler (Ed.), Cognition and motivation. New York: Cambridge University Press.Google Scholar
  54. Johnson, W., Bouchard, T. J., Krueger, R. F., McGue, M., & Gottesman, I. I. (2004). Just one g: Consistent results from three test batteries. Intelligence, 32, 95–107.CrossRefGoogle Scholar
  55. Johnson, W., te Nijenhuis, J., & Bouchard, T. J. (2008). Still just one g: Consistent results from five test batteries. Intelligence, 36, 81–95.CrossRefGoogle Scholar
  56. Johnson, W., Deary, I. J., McGue, M., & Christensen, K. (2009). Genetic and environmental transactions linking cognitive ability, physical fitness, and education in late life. Psychology and Aging, 24, 48–62.PubMedCrossRefGoogle Scholar
  57. Kennedy, K. M., & Raz, N. (2009). Aging white matter and cognition: Differential effects of regional variations in diffusion properties on memory, executive functions, and speed. Neuropsychologia, 47(3), 916–927.PubMedCrossRefGoogle Scholar
  58. Kleemeier, R. W. (1962). Intellectual changes in the senium. Proceedings of the American Statistical Association, 1, 290–295.Google Scholar
  59. Lachman, R., Lachman, J. L., & Taylor, D. W. (1982). Reallocation of mental resources over the productive life-span: Assumptions and task analyses. In F. I. Craik, & S. Trehub (Eds.), Aging and cognitive process (pp. 304–350). New York: Plenum Press.Google Scholar
  60. Lee, T., Henry, J. D., Trollor, J. N., & Sachdev, P. S. (2010). Genetic influences on cognitive functions in the elderly: A selective review of twin studies. Brain Research Reviews, 64, 1–13.PubMedCrossRefGoogle Scholar
  61. Lee, T., Mosing, M. A., Henry, J. D., Trollor, J. N., Lammel, A., Ames, D., Sachdev, P. S. (2012).Genetic influences on five measures of processing speed and their covariation with general cognitive ability in the elderly: The Older Australian Twins Study. Behavior Genetics, 42(1), 96–106. doi:10.1007/s10519-011-9474-1.Google Scholar
  62. Li, S.-C., Aggen, S. H., Nesselroade, J. R., & Baltes, P. B. (2001). Short-term fluctuations in elderly people’s sensorimotor functioning predict text and spatial memory performance: the Macarthur successful aging studies. Gerontology, 47, 100–116.PubMedCrossRefGoogle Scholar
  63. Li, S.-C., Lindenberger, U., & Sikstrom, S. (2001). Aging cognition: From neuromodulation to representation. Trends in Cognitive Sciences, 5, 479–486.PubMedCrossRefGoogle Scholar
  64. Li, S.-C., Lindenberger, U., Hommel, B., Aschersleben, G., Prinz, W., & Baltes, P. B. (2004). Transformations in the couplings among intellectual abilities and constituent cognitive processes across the life span. Psychological Science, 15, 155–163.PubMedCrossRefGoogle Scholar
  65. Lieberman, M. A. (1966). Observations on death and dying. Journal of Gerontology, 6, 70–72.CrossRefGoogle Scholar
  66. Lopez, L. M., Harris, S. E., Luciano, L., Liewald, D., Davies, G., Gow, A. J., et al. (2011). Evolutionary conserved longevity genes and human cognitive abilities in elderly cohorts. European Journal of Human Genetics. doi:10.1038/ejhg.2011.201.Google Scholar
  67. Lopez, L. M., Mullen, W., Zurbig, P., Harris, S. E., Gow, A. J., Starr, J. M., et al. (2011). A pilot study of urinary peptides as biomarkers for intelligence in old age. Intelligence, 39, 46–53.CrossRefGoogle Scholar
  68. Lopez, L. M., Bastin, M. E., Munoz Maniega, S., Penke, L., Davies, G., Christoforou, A., et al. (2012). A genome-wide search for genetic influences and biological pathways related to the brain’s white matter integrity. Neurobiology of Aging, 33(8), 1847.PubMedCrossRefGoogle Scholar
  69. Lovden, M., Li, S.-C., Shing, Y. L., & Lindenberger, U. (2007). Within-person trial-to-trial variability precedes and predicts cognitive decline in old and very old age: Longitudinal data from the Berlin Aging Study. Neuropsychologia, 45, 2827–2838.PubMedCrossRefGoogle Scholar
  70. Luciano, M., Hansell, N., Lahti, J., Davies, G., Medland, S. E., Raikkonen, K., et al. (2011). Whole genome association scan for genetic polymorphisms influencing information processing speed. Biological Psychology, 86, 193–202.PubMedCrossRefGoogle Scholar
  71. Luciano, M., Posthuma, D., Wright, M. J., de Geus, E. J., Smith, G. A., Geffen, G. M., et al. (2005). Perceptual speed does not cause intelligence, and intelligence does not cause perceptual speed. Biological Psychology, 70, 1–8.PubMedCrossRefGoogle Scholar
  72. MacDonald, S. W., Hultsch, D. F., & Dixon, R. A. (2003). Performance variability is related to change in cognition: Evidence from the Victoria Longitudinal Study. Psychology and Aging, 18, 510–523.PubMedCrossRefGoogle Scholar
  73. MacDonald, S. W., Hultsch, D. F., & Dixon, R. A. (2011). Aging and the shape of cognitive change before death: Terminal decline or terminal drop? Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 66, 292–301.CrossRefGoogle Scholar
  74. McArdle, J. J., & Plassman, B. J. (2009). A biometric latent curve analysis of memory decline in older men of the NAS-NRC Twin Registry. Behavior Genetics, 39, 472–495Google Scholar
  75. McClearn, G. E., Johansson, B., Berg, S., Pedersen, N. L., Ahern, F., Petrill, S. A., & Plomin, R. (1997). Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science, 276, 1560–1563.PubMedCrossRefGoogle Scholar
  76. McGue, M., & Christensen, K. (2001). The heritability of cognitive functioning in very old adults: Evidence from Danish twins aged 75 years and older. Psychology and Aging, 16, 272–280.PubMedCrossRefGoogle Scholar
  77. McGue, M., & Christensen, K. (2007). Social activity and healthy aging: A study of aging Danish twins. Twin Research and Human Genetics, 10(2), 255–265.PubMedCrossRefGoogle Scholar
  78. McGue, M., Osler, M., & Christensen, K. (2010). Causal inference and observational research: The utility of twins. Perspectives on Psychological Science, 5(5), 546–556.PubMedCrossRefGoogle Scholar
  79. McNamee, R. (2003). Confounding and confounders. Occupational and Environmental Medicine, 60, 227–234.PubMedCrossRefGoogle Scholar
  80. Miyajima, F., Quinn, J. P., Horan, M., Pickles, A., Ollier, W. E., Pendleton, N., et al. (2008). Additive effect of BDNF and REST polymorphisms is associated with improved general cognitive ability. Genes, Brain and Behavior, 7, 714–719.CrossRefGoogle Scholar
  81. Neale, M. C., & McArdle, J. J. (2000). Structured latent growth curves for twin data. Twin Research, 3, 165–177.PubMedGoogle Scholar
  82. Need, A., Attix, D. K., McElvoy, J. M., Cirulli, E. T., Linney, K. L., Hunt, P., et al. (2009). A genome-wide study of common SNPs and CNVs in cognitive performance in the CANTAB. Human Molecular Genetics, 18, 4650–4661.PubMedCrossRefGoogle Scholar
  83. Nishiwaki, Y., Clark, H., Morton, S. M., & Leon, D. A. (2005). Early life factors, childhood cognition and postal questionnaire response rate in middle age: The Aberdeen Children of the 1950s study. BMC Medical Research Methodology, 5, 16.PubMedCrossRefGoogle Scholar
  84. Payton, A. (2009). The impact of genetic research on our understanding of normal cognitive aging: 1995 to 2009. Neuropsychological Review, 19, 451–477.CrossRefGoogle Scholar
  85. Pedersen, N. L., Plomin, R., Nesselroade, J. R., & McClearn, G. E. (1992). A quantitative genetic analysis of cognitive abilities during the second half of the life span. Psychological Science, 3(6), 346–353.CrossRefGoogle Scholar
  86. Pedersen, N. L., Ripatti, S., Berg, S., Reynolds, C., Hofer, S. M., Finkel, D., Gatz, M., & Palmgren, J. (2003). The influence of mortality on twin models of change: Addressing missingness through multiple imputation. Behavior Genetics, 33, 161–169.PubMedCrossRefGoogle Scholar
  87. Penke, L., Munoz Maniega, S., Murray, C., Gow, A. J., Valdes Hernandez, M. C., Clayden, J. D., et al. (2010). A general factor of brain white matter integrity predicts information processing speed in healthy older people. Journal of Neuroscience, 30, 7559, 7674.Google Scholar
  88. Piccinin, A. M., Muniz, G., Matthews, F. E., & Johansson, B. (2011). Terminal Decline from within- and between-person perspectives, accounting for incident dementia. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 66, 391–401.CrossRefGoogle Scholar
  89. Platt, J. R. (1964). Strong inference: Certain systematic methods of scientific thinking may produce much more rapid progress that others. Science, 146, 347–353.PubMedCrossRefGoogle Scholar
  90. Plomin, R., Pedersen, N., Lichtenstein, P., & McClearn, G. E. (1994). Variability and stability in cognitive abilities are largely genetic later in life. Behavior Genetics, 24, 207–215.PubMedCrossRefGoogle Scholar
  91. Potter, G. G., Plassman, B. L., Helms, M. J., Foster, S. M., & Edwards, N. W. (2006). Occupational characteristics and cognitive performance among elderly male twins. Neurology, 67(8), 1377–1382.PubMedCrossRefGoogle Scholar
  92. Purcell, S. (2002). Variance component models for gene-environment interaction in twin analysis. Twin Research, 5, 554–571.PubMedGoogle Scholar
  93. Qureshi, I. A., & Mehler, M. F. (2011). Non-coding RNA networks underlying cognitive disorders across the life-span. Trends in Molecular Medicine, 17, 337–346.PubMedCrossRefGoogle Scholar
  94. Rabbitt, P. M., Osman, P., Moore, B., & Stollery, B. (2001). There are stable individual differences in performance variability, both from moment to moment and from day to day. The Quarterly Journal of Experimental Psychology A, Human Experimental Psychology, 4, 981–1003.Google Scholar
  95. Rabbitt, P., Diggle, P., Holland, F., & McInnes, L. (2004). Practice and drop-out effects during a 17-year longitudinal study of cognitive aging. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 59(2), 84–97.CrossRefGoogle Scholar
  96. Rabbitt, P., Lunn, M., & Wong, D. (2008). Death, dropout, and longitudinal measurements of cognitive change in old age. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 63, 271–278.CrossRefGoogle Scholar
  97. Rabbitt, P., Lunn, M., Pendleton, N., & Yardafagar, G. (2011). Terminal pathologies affect rates of decline to different extents and age accelerates the effects of terminal pathology on cognitive decline. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 66, 325–334.CrossRefGoogle Scholar
  98. Ram, N., Rabbitt, P., Stollery, B., & Nesselroade, J. R. (2005). Cognitive performance inconsistency: Intraindividual change and variability. Psychology and Aging, 20, 981–1003.CrossRefGoogle Scholar
  99. Rathouz, P. J., Van Hulle, C. A., Rodgers, J. L., Waldman, I. D., & Lahey, B. B. (2008). Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation. Behavior Genetics, 38, 301–315.PubMedCrossRefGoogle Scholar
  100. Reinvang, I., Deary, I. J., Fjell, A. M., Steen, V. M., Espeseth, T., & Parasuraman, R. (2010). Neurogenetic effects on cognition in aging brains: a window of opportunity for intervention? Frontiers in Aging Neuroscience, 2, 143.PubMedCrossRefGoogle Scholar
  101. Reynolds, C. A., Finkel, D., McArdle, J. J., Gatz, M., Berg, S., & Pedersen, N. L. (2005). Quantitative genetic analysis of latent growth curve models of cognitive abilities in adulthood. Developmental Psychology, 41(1), 3–16.PubMedCrossRefGoogle Scholar
  102. Riegel, K. F., & Riegel, R. M. (1972). Development, drop, and death. Developmental Psychology, 6, 306–319.CrossRefGoogle Scholar
  103. Roses, A. D. (2010). An inherited variable poly-T repeat genotype in TOMM40 in Alzheimer disease. Archives of Neurology, 67, 536–541.PubMedCrossRefGoogle Scholar
  104. Salthouse, T. A. (1996). The processing speed theory of adult age differences in cognition. Psychological Review, 103, 403–428.PubMedCrossRefGoogle Scholar
  105. Salthouse, T. A. (2004). Localizing age-related individual differences in a hierarchical structure. Intelligence, 32, 541–561.CrossRefGoogle Scholar
  106. Salthouse, T. A. (2006). Mental exercise and mental aging evaluating the validity of the “use it or lose it” hypothesis. Perspectives on Psychological Science, 1(1), 68–87.CrossRefGoogle Scholar
  107. Schiepers, O. J. G., Harris, S. E., Gow, A. J., Pattie, A., Brett, C. E., Starr, J. M., & Deary, I. J. (2012). APOE E4 status predicts age-related cognitive decline in the ninth decade: longitudinal follow-up of the Lothian Birth Cohort 1921. Molecular Psychiatry, 17, 315–324.PubMedCrossRefGoogle Scholar
  108. Schooler, C., & Mulatu, M. S. (2001). The reciprocal effects of leisure time activities and intellectual functioning in older people: A longitudinal analysis. Psychology and Aging, 16(3), 466–482.PubMedCrossRefGoogle Scholar
  109. Seshadri, S., Fitzpatrick, A. L., Ikram, A., DeStephano, A. L., Gudnason, V., Boada, M., et al. (2010). Genome-wide analysis of genetic loci associated with Alzheimer disease. Journal of the American Medical Association, 303, 1832–1840.PubMedCrossRefGoogle Scholar
  110. Singer, T., Lindenberger, U., & Baltes, P. B. (2003). Plasticity of memory for new learning in very old age: A story of major loss? Psychology and Aging, 18(2), 306–317.PubMedCrossRefGoogle Scholar
  111. Sliwinski, M. J., Stawski, R. S., Hall, C. B., Katz, M., Verghese, J., & Lipton, R. (2006). Distinguishing preterminal and terminal cognitive decline. European Psychologist, 11, 172–181.CrossRefGoogle Scholar
  112. Stuss, D. T., Pogue, J., Buckle, L., & Bondar, J. (1994). Characterization of stability of performance in patients with traumatic brain injury: Variability and consistency on reaction time tests. Neuropsychology, 8, 316–324.CrossRefGoogle Scholar
  113. Swan, G. E., & Carmelli, D. (2002). Evidence for genetic mediation of executive control: A study of aging male twins. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 57(2), 133–143.CrossRefGoogle Scholar
  114. Swan, G. E., Reed, T., Jack, L. M., Miller, B. L., Markee, T., Wolf, P. A., & DeCarli, C. (1999). Differential genetic influence for components of memory in aging adult twins. Archives of Neurology, 56, 1127–1132.PubMedCrossRefGoogle Scholar
  115. Tuminello, E. R., & Han, S. D. (2011). The apolipoprotein e antagonistic pleiotropy hypothesis: review and recommendations. International Journal of Alzheimer’s Disease, 2011, 72616.Google Scholar
  116. Turkheimer, E. (2000).Three laws of behavior genetics and what they mean. Current Directions in Psychological Science, 9(5), 160–164. doi:10.1111/1467-8721.00084.Google Scholar
  117. Valdes, A. M., Deary, I. J., Aviv, A., Gardner, J., Kimura, M., Lu, X., Spector, T. D., & Cherkas, L. F. (2010). Leukocyte telomere length is associated with cognitive performance in healthy women. Neurobiology of Aging, 31, 986–992.PubMedCrossRefGoogle Scholar
  118. Verhaeghen, P., & Salthouse, T. A. (1997). Meta-analyses of age-cognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin, 122(3), 231–249.PubMedCrossRefGoogle Scholar
  119. Vernon, P. A. (1989). The heritability of measures of speed of information processing. Personality and Individual Differences, 10, 573–576.CrossRefGoogle Scholar
  120. Visscher, P. M., Yang, J., & Goddard, M. E. (2010). A commentary on ‘‘Common SNPs explain a large proportion of the heritability for human height’’ by Yang et al. Twin Research and Human Genetics, 13, 517–524.PubMedCrossRefGoogle Scholar
  121. West, R., Murphy, K. J., Armilio, M. L., Craik, F. I., & Stuss, D. T. (2002). Lapses of intention and performance variability reveal age-related increases in fluctuations of executive control. Brain and Cognition, 49, 402–419.PubMedCrossRefGoogle Scholar
  122. Williams, G. C. (1957). Pleiotropy, natural selection, and the evolution of senescence. Evolution, 11, 398–411.CrossRefGoogle Scholar
  123. Wilson, R. S., Beckett, L. A., Bienias, J. L., Evans, D. A., & Bennett, D. A. (2003). Terminal decline in cognitive function. Neurology, 60, 1782–1787.PubMedCrossRefGoogle Scholar
  124. Winterer, G., & Weinberger, D. R. (2004). Genes, dopamine, and cortical signal-to-noise ratio in schizophrenia. Trends in Neuroscience, 27, 683–690.CrossRefGoogle Scholar
  125. Wisdom, N. M., Callahan, J. L., & Hawkins, K. A. (2011). The effects of apolipoprotein E on non-impaired cognitive functioning: a meta-analysis. Neurobiology of Aging, 32, 63–74.PubMedCrossRefGoogle Scholar
  126. Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., et al. (2010). Common SNPs explain a large proportion of the heritability for human height. Nature Genetics, 42, 565–569.PubMedCrossRefGoogle Scholar
  127. Yeo, R. A., Gangestad, S. W., Liu, J. Y., Calhoun, V. D., & Hutchison, K. E. (2011). Rare copynumber deletions predict individual variation in intelligence. PLoS One, 6, e16339. doi:10.137/jounal.pone.0016339Google Scholar
  128. Zhang, J.-P., Burdick, K. E., Lencz, T., & Malhotra, A. K. (2010). Meta-analysis of genetic variation in DTNBP1 and general cognitive ability. Biological Psychiatry, 68, 1126–1133.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2014

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of EdinburghEdinburghUK
  2. 2.Department of PsychologyUniversity of MinnesotaMinneapolisUSA

Personalised recommendations