Skip to main content

Advertisement

SpringerLink
Log in

A methodological approach to studying resilience mechanisms: demonstration of utility in age and Alzheimer’s disease-related brain pathology

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

The present work aims at providing a methodological approach for the investigation of resilience factors and mechanisms in normal aging, Alzheimer’s disease (AD) and other neurodegenerative disorders. By expanding and re-conceptualizing traditional regression approaches, we propose an approach that not only aims at identifying potential resilience factors but also allows for a differentiation between general and dynamic resilience factors in terms of their association with pathology. Dynamic resilience factors are characterized by an increasing relevance with increasing levels of pathology, while the relevance of general resilience factors is independent of the amount of pathology. Utility of the approach is demonstrated in age and AD-related brain pathology by investigating widely accepted resilience factors, including education and brain volume. Moreover, the approach is used to test hippocampal volume as potential resilience factor. Education and brain volume could be identified as general resilience factors against age and AD-related pathology. Beyond that, analyses highlighted that hippocampal volume may not only be disease target but also serve as a potential resilience factor in age and AD-related pathology, particularly at higher levels of tau-pathology (i.e. dynamic resilience factor). Given its unspecific and superordinate nature the approach is suitable for the investigation of a wide range of potential resilience factors in normal aging, AD and other neurodegenerative disorders. Consequently, it may find a wide application and thereby promote the comparability between studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. NeuroImage, 38(1), 95–113.

    Article  Google Scholar 

  • Braak, H., & Braak, E. (1995). Staging of Alzheimer's disease-related neurofibrillary changes. Neurobiology of Aging, 16(3), 271–278.

    Article  CAS  Google Scholar 

  • Cannon, W. B. (1932). The wisdom of the body. New York: W.W. Norton and Co..

    Book  Google Scholar 

  • Chételat, G., Villemagne, V. L., Pike, K. E., Baron, J.-C., Bourgeat, P., Jones, G.,. .. Szoeke, C. (2010). Larger temporal volume in elderly with high versus low beta-amyloid deposition. Brain, awq 187.

  • Christensen, H., Anstey, K. J., Leach, L. S., & Mackinnon, A. J. (2008). Intelligence, education, and the brain reserve hypothesis. The Handbook of Aging and Cognition, 3.

  • Cohen, J. (1983). The cost of dichotomization. Applied Psychological Measurement, 7(3), 249–253.

    Article  Google Scholar 

  • Crane, P. K., Carle, A., Gibbons, L. E., Insel, P., Mackin, R. S., Gross, A., et al. (2012). Development and assessment of a composite score for memory in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Brain Imaging and Behavior, 6(4), 502–516.

    Article  Google Scholar 

  • Davis, D., Schmitt, F., Wekstein, D., & Markesbery, W. (1999). Alzheimer neuropathologic alterations in aged cognitively normal subjects. Journal of Neuropathology & Experimental Neurology, 58(4), 376–388.

    Article  CAS  Google Scholar 

  • de Calignon, A., Polydoro, M., Suárez-Calvet, M., William, C., Adamowicz, D. H., Kopeikina, K. J., et al. (2012). Propagation of tau pathology in a model of early Alzheimer's disease. Neuron, 73(4), 685–697.

    Article  Google Scholar 

  • DeCarli, C., Fletcher, E., Ramey, V., Harvey, D., & Jagust, W. J. (2005). Anatomical mapping of white matter hyperintensities (WMH). Stroke, 36(1), 50–55.

    Article  Google Scholar 

  • Erten-Lyons, D., Woltjer, R., Dodge, H., Nixon, R., Vorobik, R., Calvert, J., et al. (2009). Factors associated with resistance to dementia despite high Alzheimer disease pathology. Neurology, 72(4), 354–360.

    Article  CAS  Google Scholar 

  • Ewers, M., Insel, P. S., Stern, Y., Weiner, M. W., & Initiative, A. s. D. N. (2013). Cognitive reserve associated with FDG-PET in preclinical Alzheimer disease. Neurology, 80(13), 1194–1201.

    Article  CAS  Google Scholar 

  • Fletcher, E., Singh, B., Harvey, D., Carmichael, O., & DeCarli, C. (2012). Adaptive image segmentation for robust measurement of longitudinal brain tissue change. Paper presented at the Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE.

  • Frisoni, G. B., Jack, C. R., Bocchetta, M., Bauer, C., Frederiksen, K. S., Liu, Y., et al. (2015). The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity. Alzheimer's & Dementia, 11(2), 111–125.

    Article  Google Scholar 

  • Hohman, T. J., McLaren, D. G., Mormino, E. C., Gifford, K. A., Libon, D. J., Jefferson, A. L., et al. (2016). Asymptomatic Alzheimer disease Defining resilience. Neurology, 87(23), 2443–2450.

    Article  Google Scholar 

  • Iacono, D., Markesbery, W., Gross, M., Pletnikova, O., Rudow, G., Zandi, P., & Troncoso, J. (2009). The Nun Study Clinically silent AD, neuronal hypertrophy, and linguistic skills in early life. Neurology, 73(9), 665–673.

    Article  CAS  Google Scholar 

  • Jack, C., Petersen, R. C., Xu, Y., O’brien, P., Smith, G. E., Ivnik, R. J., et al. (2000). Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology, 55(4), 484–490.

    Article  Google Scholar 

  • Johnson, K. A., Schultz, A., Betensky, R. A., Becker, J. A., Sepulcre, J., Rentz, D., et al. (2016). Tau positron emission tomographic imaging in aging and early Alzheimer disease. Annals of Neurology, 79(1), 110–119.

    Article  Google Scholar 

  • Katzman, R., Terry, R., DeTeresa, R., Brown, T., Davies, P., Fuld, P., et al. (1988). Clinical, pathological, and neurochemical changes in dementia: a subgroup with preserved mental status and numerous neocortical plaques. Annals of Neurology, 23(2), 138–144.

    Article  CAS  Google Scholar 

  • Lloyd, D., Aon, M. A., & Cortassa, S. (2001). Why homeodynamics, not homeostasis? The Scientific World Journal, 1, 133–145.

    Article  CAS  Google Scholar 

  • Mufson, E. J., Mahady, L., Waters, D., Counts, S. E., Perez, S. E., DeKosky, S. T., et al. (2015). Hippocampal plasticity during the progression of Alzheimer's disease. NeuroScience, 309, 51–67.

    Article  CAS  Google Scholar 

  • Riley, K. P., Snowdon, D. A., & Markesbery, W. R. (2002). Alzheimer's neurofibrillary pathology and the spectrum of cognitive function: findings from the Nun Study. Annals of Neurology, 51(5), 567–577.

    Article  Google Scholar 

  • Riudavets, M. A., Iacono, D., Resnick, S. M., O’Brien, R., Zonderman, A. B., Martin, L. J., et al. (2007). Resistance to Alzheimer's pathology is associated with nuclear hypertrophy in neurons. Neurobiology of Aging, 28(10), 1484–1492.

    Article  CAS  Google Scholar 

  • Rosen, W. G., Mohs, R. C., & Davis, K. L. (1984). A new rating scale for Alzheimer's disease. The American journal of psychiatry.

  • Shaw, L. M., Vanderstichele, H., Knapik-Czajka, M., Clark, C. M., Aisen, P. S., Petersen, R. C., et al. (2009). Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects. Annals of Neurology, 65(4), 403–413.

    Article  CAS  Google Scholar 

  • Shi, F., Liu, B., Zhou, Y., Yu, C., & Jiang, T. (2009). Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: Meta-analyses of MRI studies. Hippocampus, 19(11), 1055–1064.

    Article  Google Scholar 

  • Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8(03), 448–460.

    Article  Google Scholar 

  • Stern, Y. (2006). Cognitive reserve and Alzheimer disease. Alzheimer Disease & Associated Disorders, 20(2), 112–117.

    Article  Google Scholar 

  • Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47(10), 2015–2028.

    Article  Google Scholar 

  • Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer's disease. The Lancet Neurology, 11(11), 1006–1012.

    Article  Google Scholar 

  • Wolf, D., Bocchetta, M., Preboske, G. M., Boccardi, M., Grothe, M. J., & Initiative, A. s. D. N. (2017). Reference standard space hippocampus labels according to the EADC-ADNI harmonized protocol: Utility in automated volumetry. In Alzheimer's & Dementia.

    Google Scholar 

  • Yates, F. E. (1994). Order and complexity in dynamical systems: homeodynamics as a generalized mechanics for biology. Mathematical and Computer Modelling, 19(6), 49–74.

    Article  Google Scholar 

Download references

Acknowledgements

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/about/governance/principal-investigators/

Author information

Authors and Affiliations

  1. Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Untere Zahlbacher Str. 8, 55131, Mainz, Germany

    Dominik Wolf, Florian Udo Fischer & Andreas Fellgiebel

Authors
  1. Dominik Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florian Udo Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andreas Fellgiebel
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

for the Alzheimer’s Disease Neuroimaging Initiative

Corresponding author

Correspondence to Dominik Wolf.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Statement on the welfare of animals

This article does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wolf, D., Fischer, F.U., Fellgiebel, A. et al. A methodological approach to studying resilience mechanisms: demonstration of utility in age and Alzheimer’s disease-related brain pathology. Brain Imaging and Behavior 13, 162–171 (2019). https://doi.org/10.1007/s11682-018-9870-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-018-9870-8

Keywords

Search

Navigation