Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Dissociable effects of APOE ε4 and β-amyloid pathology on visual working memory

Nature Aging volume 1, pages 1002–1009 (2021)Cite this article

Subjects

Abstract

Although APOE ε4 carriers are at substantially higher risk of developing Alzheimer’s disease than noncarriers1, controversial evidence suggests that APOE ε4 might confer some advantages, explaining the survival of this gene (antagonistic pleiotropy)2,3. In a population-based cohort born in one week in 1946 (assessed aged 69–71 years), we assessed differential effects of APOE ε4 and β-amyloid pathology (quantified using 18F-Florbetapir-PET) on visual working memory (object–location binding). In 398 cognitively normal participants, APOE ε4 and β-amyloid had opposing effects on object identification, predicting better and poorer recall, respectively. ε4 carriers also recalled locations more precisely, with a greater advantage at higher β-amyloid burden. These results provide evidence of superior visual working memory in ε4 carriers, showing that some benefits of this genotype are demonstrable in older age, even in the preclinical stages of Alzheimer’s disease.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Study design.
Fig. 2: Performance on the ‘What was where?’ task in cognitively normal participants (n = 398).
Fig. 3: Association between β-amyloid burden (quantified using SUVR) and localization error on the ‘What was where?’ task for APOE ε4 carriers (n = 120) and noncarriers (n = 278).

Similar content being viewed by others

Data availability

All data from NSHD are curated and stored by the Lifelong Health and Aging Unit at UCL. Anonymized data will be shared by request from qualified investigators (https://skylark.ucl.ac.uk/NSHD/doku.php).

Code availability

Code for the 2D-mixture model (MATLAB) is freely available at https://doi.org/10.5281/zenodo.3752705. Code for statistical analyses conducted in Stata is provided in Supplementary Information.

References

  1. Liu, C.-C., Kanekiyo, T., Xu, H. & Bu, G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat. Rev. Neurol. 9, 106–118 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Smith, C. J., Ashford, J. W. & Perfetti, T. A. Putative survival advantages in young apolipoprotein ɛ4 carriers are associated with increased neural stress. J. Alzheimers Dis. 68, 885–923 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Tuminello, E. R. & Duke Han, S. The apolipoprotein E antagonistic pleiotropy hypothesis: review and recommendations. Int. J. Alzheimers Dis. 2011, 726197 (2011).

    PubMed  PubMed Central  Google Scholar 

  4. Safieh, M., Korczyn, A. D. & Michaelson, D. M. ApoE4: an emerging therapeutic target for Alzheimer’s disease. BMC Med. 17, 64 (2019).

  5. Jack, C. R. et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 12, 207–216 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Villemagne, V. L. et al. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. Lancet Neurol. 12, 357–367 (2013).

    Article  CAS  PubMed  Google Scholar 

  7. Baker, J. E. et al. Cognitive impairment and decline in cognitively normal older adults with high amyloid-β: a meta-analysis. Alzheimers Dement. 6, 108–121 (2017).

    Google Scholar 

  8. Brookmeyer, R. & Abdalla, N. Estimation of lifetime risks of Alzheimer’s disease dementia using biomarkers for preclinical disease. Alzheimers Dement. 14, 981–988 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Byars, S. G. & Voskarides, K. Antagonistic pleiotropy in human disease. J. Mol. Evol. 88, 12–25 (2020).

    Article  CAS  PubMed  Google Scholar 

  10. Jasienska, G. et al. Apolipoprotein E (ApoE) polymorphism is related to differences in potential fertility in women: a case of antagonistic pleiotropy? Proc. R. Soc. B Biol. Sci. 282, 20142395 (2015).

    Article  Google Scholar 

  11. Duke Han, S. & Bondi, M. W. Revision of the apolipoprotein E compensatory mechanism recruitment hypothesis. Alzheimers Dement. 4, 251–254 (2008).

    Article  PubMed  Google Scholar 

  12. Rusted, J. M. et al. APOE e4 polymorphism in young adults is associated with improved attention and indexed by distinct neural signatures. Neuroimage 65, 364–373 (2013).

    Article  CAS  PubMed  Google Scholar 

  13. O’Donoghue, M. C., Murphy, S. E., Zamboni, G., Nobre, A. C. & Mackay, C. E. APOE genotype and cognition in healthy individuals at risk of Alzheimer’s disease: a review. Cortex 104, 103–123 (2018).

    Article  PubMed  Google Scholar 

  14. Iacono, D. & Feltis, G. C. Impact of apolipoprotein E gene polymorphism during normal and pathological conditions of the brain across the lifespan. Aging 11, 787–816 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zink, N., Bensmann, W., Arning, L., Beste, C. & Stock, A. K. Apolipoprotein ε4 is associated with better cognitive control allocation in healthy young adults. Neuroimage 185, 274–285 (2019).

    Article  CAS  PubMed  Google Scholar 

  16. Marchant, N. L., King, S. L., Tabet, N. & Rusted, J. M. Positive effects of cholinergic stimulation favor young APOE e4 carriers. Neuropsychopharmacology 35, 1090–1096 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. D’Souza, H. et al. Differential associations of apolipoprotein E ε4 genotype with attentional abilities across the life span of individuals with Down syndrome. JAMA Netw. Open 3, e2018221 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Austad, S. N. & Hoffman, J. M. Is antagonistic pleiotropy ubiquitous in aging biology? Evol. Med. Public Health 2018, 287–294 (2018).

  19. Abondio, P. et al. The genetic variability of APOE in different human populations and its implications for longevity. Genes (Basel) 10, 222 (2019).

  20. Raichlen, D. A. & Alexander, G. E. Exercise, APOE genotype, and the evolution of the human lifespan. Trends Neurosci. 37, 247–255 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Weissberger, G. H., Nation, D. A., Nguyen, C. P., Bondi, M. W. & Han, S. D. Meta-analysis of cognitive ability differences by apolipoprotein e genotype in young humans. Neurosci. Biobehav. Rev. 94, 49–58 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pertzov, Y., Dong, M. Y., Peich, M.-C. & Husain, M. Forgetting what was where: the fragility of object-location binding. PLoS ONE 7, e48214 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zokaei, N. et al. Sex and APOE: a memory advantage in male APOE ε4 carriers in midlife. Cortex 88, 98–105 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Zokaei, N. et al. Dissociable effects of the apolipoprotein-E (APOE) gene on short- and long-term memories. Neurobiol. Aging 73, 115–122 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zokaei, N. et al. Short-term memory advantage for brief durations in human APOE ε4 carriers. Sci. Rep. 10, 9503 (2020).

  26. Ma, W. J., Husain, M. & Bays, P. M. Changing concepts of working memory. Nat. Neurosci. 17, 347–356 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Zokaei, N., Burnett Heyes, S., Gorgoraptis, N., Budhdeo, S. & Husain, M. Working memory recall precision is a more sensitive index than span. J. Neuropsychol. 9, 319–329 (2015).

    Article  PubMed  Google Scholar 

  28. Lane, C. A. et al. Study protocol: Insight 46 – a neuroscience sub-study of the MRC National Survey of Health and Development. BMC Neurol. 17, dec2017 (2017).

    Article  Google Scholar 

  29. Kuh, D. et al. The MRC National Survey of Health and Development reaches age 70: maintaining participation at older ages in a birth cohort study. Eur. J. Epidemiol. 31, 1135–1147 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Roberts, R. O. et al. Prevalence and outcomes of amyloid positivity among persons without dementia in a longitudinal, population-based setting. JAMA Neurol. 75, 970–979 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Kern, S. et al. Prevalence of preclinical Alzheimer disease: comparison of current classification systems. Neurology 90, e1682–e1691 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Prins, N. D. & Scheltens, P. White matter hyperintensities, cognitive impairment and dementia: an update. Nat. Rev. Neurol. 11, 157–165 (2015).

    Article  PubMed  Google Scholar 

  33. Pertzov, Y., Heider, M., Liang, Y. & Husain, M. Effects of healthy ageing on precision and binding of object location in visual short term memory. Psychol. Aging 30, 26–35 (2015).

    Article  PubMed  Google Scholar 

  34. Grogan, J. P. et al. A new toolbox to distinguish the sources of spatial memory error. J. Vis. 20, 6 (2020).

  35. Di Battista, A. M., Heinsinger, N. M. & Rebeck, G. W. Alzheimer’s disease genetic risk factor APOE-ε4 also affects normal brain function. Curr. Alzheimer Res. 13, 1200–1207 (2016).

    Article  PubMed  Google Scholar 

  36. Scheller, E. et al. APOE moderates compensatory recruitment of neuronal resources during working memory processing in healthy older adults. Neurobiol. Aging 56, 127–137 (2017).

    Article  CAS  PubMed  Google Scholar 

  37. Rawle, M. J. et al. Apolipoprotein-E (Apoe) ε4 and cognitive decline over the adult life course. Transl. Psychiatry 8, 18 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Salvato, G. Does apolipoprotein e genotype influence cognition in middle-aged individuals? Curr. Opin. Neurol. 28, 612–617 (2015).

    Article  CAS  PubMed  Google Scholar 

  39. Small, B. J., Rosnick, C. B., Fratiglioni, L. & Bäckman, L. Apolipoprotein E and cognitive performance: a meta-analysis. Psychol. Aging 19, 592–600 (2004).

    Article  PubMed  Google Scholar 

  40. Vermunt, L. et al. Duration of preclinical, prodromal, and dementia stages of Alzheimer’s disease in relation to age, sex, and APOE genotype. Alzheimers Dement. 15, 888–898 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Lim, Y. Y. et al. Aβ-related memory decline in APOE ε4 noncarriers: implications for Alzheimer disease. Neurology 86, 1635–1642 (2016).

    Article  CAS  PubMed  Google Scholar 

  42. Liang, Y. et al. Visual short-term memory binding deficit in familial Alzheimer’s disease. Cortex 78, 150–164 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Lu, K. et al. Cognition at age 70: life course predictors and associations with brain pathologies. Neurology 93, e2144–e2156 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Lu, K. et al. Increased variability in reaction time is associated with amyloid beta pathology at age 70. Alzheimers Dement. (Amst.) 12, e12076 (2020).

    Google Scholar 

  45. James, S.-N. et al. Using a birth cohort to study brain health and preclinical dementia: recruitment and participation rates in Insight 46. BMC Res. Notes 11, 885 (2018).

  46. Livingston, G. et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 396, 413–446 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Lane, C. A. et al. Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): an epidemiological study. Lancet Neurol. 18, 942–952 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lu, K. et al. Visuomotor integration deficits are common to both familial and sporadic preclinical Alzheimer’s disease. Brain Commun. 3, fcab003 (2021).

  49. Pertzov, Y. et al. Binding deficits in memory following medial temporal lobe damage in patients with voltage-gated potassium channel complex antibody-associated limbic encephalitis. Brain 136, 2474–2485 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Grogan, J. P. johnPGrogan/MemToolbox2D: updated release. Zenodo https://zenodo.org/record/3752705/export/hx#.YSi5UPlKjIU (2020).

  51. Parker, T. D. et al. Hippocampal subfield volumes and pre-clinical Alzheimer’s disease in 408 cognitively normal adults born in 1946. PLoS ONE 14, e0224030 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Sudre, C. H. et al. Bayesian model selection for pathological neuroimaging data applied to white matter lesion segmentation. IEEE Trans. Med. Imaging 34, 2079–2102 (2015).

    Article  PubMed  Google Scholar 

  53. Cardoso, J. et al. STEPS: similarity and truth estimation for propagated segmentations and its application to hippocampal segmentation and brain parcelation. Med. Image Anal. 17, 671–684 (2013).

    Article  Google Scholar 

  54. Malone, I. B. et al. Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance. Neuroimage 104, 366–372 (2015).

    Article  PubMed  Google Scholar 

  55. Richards, M. & Sacker, A. Lifetime antecedents of cognitive reserve. J. Clin. Exp. Neuropsychol. 25, 614–624 (2003).

    Article  PubMed  Google Scholar 

  56. Richards, M. et al. Identifying the lifetime cognitive and socioeconomic antecedents of cognitive state: seven decades of follow-up in a British birth cohort study. BMJ Open 9, e024404 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Armstrong, R. A. When to use the Bonferroni correction. Ophthalmic Physiol. Opt. 34, 502–508 (2014).

    Article  PubMed  Google Scholar 

  58. Althouse, A. D. Adjust for multiple comparisons? It’s not that simple. Ann. Thorac. Surg. 101, 1644–1645 (2016).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was principally funded by grants from Alzheimer’s Research UK (nos. ARUK-PG2014-1946 and ARUK-PG2017-1946), the Medical Research Council Dementias Platform UK (no. CSUB19166) and the Selfridges Group Foundation (no. PR/ylr/18575). Genetic analyses were funded by the Brain Research Trust (no. UCC14191). The Florbetapir amyloid tracer was kindly provided by AVID Radiopharmaceuticals (a wholly owned subsidiary of Eli Lilly), who had no part in the design of the study. NSHD is funded by the Medical Research Council (nos. MC_UU_12019/06 and MC_UU_12019/08). The funders of the study had no role in study design, data collection, analysis, interpretation, report writing or the decision to submit the article for publication. T.D.P. was supported by a Wellcome Trust Clinical Research Fellowship (no. 200109/Z/15/Z). A.K. was supported by a Wolfson Clinical Research Fellowship. C.H.S. is supported by an Alzheimer’s Society Junior Fellowship (no. AS-JF-17-011). N.C.F. acknowledges support from the UK Dementia Research Institute at University College London, the National Institute for Health Research (Senior Investigator award) and University College London Hospitals Biomedical Research Centre. J.M.S. is supported by University College London Hospitals Biomedical Research Centre, Engineering and Physical Sciences Research Council (no. EP/J020990/1), British Heart Foundation (no. PG/17/90/33415) and EU’s Horizon 2020 research and innovation program (no. 666992). We thank participants both for their contributions to Insight 46 and for their commitments to research over the past seven decades. We are grateful to the radiographers and nuclear medicine physicians (A. Groves, J. Bomanji and I. Kayani) at the UCL Institute of Nuclear Medicine, and to the staff at the Leonard Wolfson Experimental Neurology Centre at UCL. We thank D. Marcus and R. Herrick for assistance with XNAT, P. Curran for assistance with data sharing with the MRC Unit for Lifelong Health and Ageing, the DRC trials team for assistance with imaging quality control, M. White for his work on data connectivity and J. Dickson, A. Barnes and D. Thomas for help with imaging.

Author information

Author notes

  1. These authors jointly supervised this work: Jonathan M. Schott, Sebastian J. Crutch.

Authors and Affiliations

  1. Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK

    Kirsty Lu, Ivanna M. Pavisic, Thomas D. Parker, Christopher A. Lane, Ashvini Keshavan, Sarah E. Keuss, Sarah M. Buchanan, Heidi Murray-Smith, David M. Cash, Ian B. Malone, Carole H. Sudre, William Coath, Susie M. D. Henley, Nick C. Fox, Jonathan M. Schott & Sebastian J. Crutch

  2. Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK

    Jennifer M. Nicholas

  3. Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, Israel

    Yoni Pertzov

  4. Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

    John Grogan & Masud Husain

  5. Department of Experimental Psychology, University of Oxford, Oxford, UK

    Masud Husain

  6. UK Dementia Research Institute at UCL, University College London, London, UK

    Ivanna M. Pavisic, David M. Cash & Nick C. Fox

  7. MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK

    Sarah-Naomi James, Carole H. Sudre, Andrew Wong & Marcus Richards

  8. Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK

    Carole H. Sudre

  9. School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK

    Carole H. Sudre

Authors
  1. Kirsty Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jennifer M. Nicholas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yoni Pertzov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. John Grogan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Masud Husain
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ivanna M. Pavisic
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sarah-Naomi James
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Thomas D. Parker
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Christopher A. Lane
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ashvini Keshavan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Sarah E. Keuss
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Sarah M. Buchanan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Heidi Murray-Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. David M. Cash
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Ian B. Malone
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Carole H. Sudre
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. William Coath
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Andrew Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Susie M. D. Henley
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Nick C. Fox
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Marcus Richards
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Jonathan M. Schott
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Sebastian J. Crutch
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.M.S., S.J.C., M.R. and N.C.F. conceptualized and led the Insight 46 study. Y.P. and M.H. designed the visual working memory experiment. K.L., I.M.P. and S.-N.J. collected data for the visual working memory test. T.D.P., C.A.L., A.K., S.E.K. and S.M.B. collected clinical and neuroimaging data. H.M.-S. and A.W. were responsible for study coordination and data management. K.L., S.M.D.H., J.M.S. and S.J.C. conceived the manuscript. J.G. and M.H. developed the 2D-mixture model. K.L. analyzed data and drafted the initial manuscript. J.M.N. provided statistical support. D.M.C., I.B.M., C.H.S. and W.C. generated neuroimaging outcomes. K.L., S.M.D.H., J.G., M.H., J.M.S. and S.J.C. aided in manuscript preparation and interpretation. All authors revised and approved the manuscript.

Corresponding author

Correspondence to Kirsty Lu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Aging thanks Duke Han, Miranka Wirth and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

43587_2021_117_MOESM1_ESM.pdf

Supplementary analyses and discussion in nine subsections, incorporating Tables 1–5 and Figs. 1–6; code for statistical analyses reported in the main manuscript and supplementary analyses; and visual representation of the raw response locations for each trial.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, K., Nicholas, J.M., Pertzov, Y. et al. Dissociable effects of APOE ε4 and β-amyloid pathology on visual working memory. Nat Aging 1, 1002–1009 (2021). https://doi.org/10.1038/s43587-021-00117-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43587-021-00117-4

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing