Is the Alzheimer’s disease cortical thickness signature a biological marker for memory?
Recent work suggests that analysis of the cortical thickness in key brain regions can be used to identify individuals at greatest risk for development of Alzheimer’s disease (AD). It is unclear to what extent this “signature” is a biological marker of normal memory function – the primary cognitive domain affected by AD. We examined the relationship between the AD signature biomarker and memory functioning in a group of neurologically healthy young and older adults. Cortical thickness measurements and neuropsychological evaluations were obtained in 110 adults (age range 21–78, mean = 46) drawn from the Brain Resource International Database. The cohort was divided into young adult (n = 64, age 21–50) and older adult (n = 46, age 51–78) groups. Cortical thickness analysis was performed with FreeSurfer, and the average cortical thickness extracted from the eight regions that comprise the AD signature. Mean AD-signature cortical thickness was positively associated with performance on the delayed free recall trial of a list learning task and this relationship did not differ between younger and older adults. Mean AD-signature cortical thickness was not associated with performance on a test of psychomotor speed, as a control task, in either group. The results suggest that the AD signature cortical thickness is a marker for memory functioning across the adult lifespan.
KeywordsAlzheimer’s Disease Cortical thickness Structural MRI Neuropsychology Memory
We acknowledge the data and support provided by BRAINnet; www.BRAINnet.net, under the governance of the BRAINnet Foundation. BRAINnet is the scientific network that coordinates access to the Brain Resource International Database for independent scientific purposes. We also thank the individuals who gave their time to participate in the database. This research was approved by local ethics committees. SMG acknowledges the Sydney Medical School Foundation for support.
Dr. Grieve previously received consulting fees from Brain Resource Ltd.
Dr. Williams previously received consulting fees and stock options from Brain Resource Ltd.
Mr. Busovaca, Dr. Zimmerman, Ms. Meier, Ms. Griffith, and Dr. Korgaonkar declare that they do not have financial and personal relationships that might bias this work.
All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.
- Bakkour, A., Morris, J. C., Wolk, D. A., & Dickerson, B. C. (2013). The effects of aging and Alzheimer’s disease on cerebral cortical anatomy: specificity and differential relationships with cognition. NeuroImage, 76, 332–344. doi: 10.1016/j.neuroimage.2013.02.059.CrossRefPubMedPubMedCentralGoogle Scholar
- Brickman, A. M., Meier, I. B., Korgaonkar, M. S., Provenzano, F. A., Grieve, S. M., Siedlecki, K. L., & Zimmerman, M. E. (2012). Testing the white matter retrogenesis hypothesis of cognitive aging. Neurobiology of Aging, 33(8), 1699–1715. doi: 10.1016/j.neurobiolaging.2011.06.001.CrossRefPubMedGoogle Scholar
- Clark, C. R., Paul, R. H., Williams, L. M., Arns, M., Fallahpour, K., Handmer, C., & Gordon, E. (2006). Standardized assessment of cognitive functioning during development and aging using an automated touchscreen battery. Archives of Clinical Neuropsychology, 21(5), 449–467.CrossRefPubMedGoogle Scholar
- Desikan, R. S., Segonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980. doi: 10.1016/j.neuroimage.2006.01.021.CrossRefPubMedGoogle Scholar
- Dickerson, B. C., Bakkour, A., Salat, D. H., Feczko, E., Pacheco, J., Greve, D. N., & Buckner, R. L. (2009). The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals. Cerebral Cortex, 19(3), 497–510. doi: 10.1093/cercor/bhn113.CrossRefPubMedGoogle Scholar
- Dickerson, B. C., Stoub, T. R., Shah, R. C., Sperling, R. A., Killiany, R. J., Albert, M. S., & Detoledo-Morrell, L. (2011). Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults. Neurology, 76(16), 1395–1402. doi: 10.1212/WNL.0b013e3182166e96.CrossRefPubMedPubMedCentralGoogle Scholar
- Grieve, S. M., Korgaonkar, M. S., Clark, C. R., & Williams, L. M. (2011). Regional heterogeneity in limbic maturational changes: evidence from integrating cortical thickness, volumetric and diffusion tensor imaging measures. NeuroImage, 55(3), 868–879. doi: 10.1016/j.neuroimage.2010.12.087.CrossRefPubMedGoogle Scholar
- Paul, R. H., Lawrence, J., Williams, L. M., Richard, C. C., Cooper, N., & Gordon, E. (2005). Preliminary validity of “integneuro”: a new computerized battery of neurocognitive tests. The International Journal of Neuroscience, 115(11), 1549–1567. doi: 10.1080/00207450590957890.CrossRefPubMedGoogle Scholar
- Silverstein, S. M., Jaeger, J., Donovan-Lepore, A. M., Wilkniss, S. M., Savitz, A., Malinovsky, I., & Dent, G. (2010). A comparative study of the MATRICS and IntegNeuro cognitive assessment batteries. Journal of Clinical and Experimental Neuropsychology, 32(9), 937–952. doi: 10.1080/13803391003596496.CrossRefPubMedGoogle Scholar
- Squire, L. R., & Kowlton, B. J. (1999). The medial temporal lobe, the hippcomapus, and the memory systems of the brain. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences. Cambridge: The MIT Press.Google Scholar
- Troster, A. I., Butters, N., Salmon, D. P., Cullum, C. M., Jacobs, D., Brandt, J., & White, R. F. (1993). The diagnostic utility of savings scores: differentiating Alzheimer’s and huntington’s diseases with the logical memory and visual reproduction tests. Journal of Clinical and Experimental Neuropsychology, 15(5), 773–788. doi: 10.1080/01688639308402595.CrossRefPubMedGoogle Scholar
- Williams, L. M., Simms, E., Clark, C. R., Paul, R. H., Rowe, D., & Gordon, E. (2005). The test-retest reliability of a standardized neurocognitive and neurophysiological test battery: “neuromarker”. The International Journal of Neuroscience, 115(12), 1605–1630. doi: 10.1080/00207450590958475.CrossRefPubMedGoogle Scholar