Genetic resilience to amyloid related cognitive decline
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Preclinical Alzheimer’s disease (AD) is characterized by amyloid deposition in the absence of overt clinical impairment. There is substantial heterogeneity in the long-term clinical outcomes among amyloid positive individuals, yet limited work has focused on identifying molecular factors driving resilience from amyloid-related cognitive impairment. We apply a recently developed predicted gene expression analysis (PrediXcan) to identify genes that modify the association between baseline amyloid deposition and longitudinal cognitive changes. Participants free of clinical AD (n = 631) were selected from the AD Neuroimaging Initiative (ADNI) who had a baseline positron emission tomography measure of amyloid deposition (quantified as a standard uptake value ratio), longitudinal neuropsychological data, and genetic data. PrediXcan was used to impute gene expression levels across 15 heart and brain tissues. Mixed effect regression models assessed the interaction between predicted gene expression levels and amyloid deposition on longitudinal cognitive outcomes. The predicted gene expression levels for two genes in the coronary artery (CNTLN, PROK1) and two genes in the atrial appendage (PRSS50, PROK1) interacted with amyloid deposition on episodic memory performance. The predicted gene expression levels for two additional genes (TMC4 in the basal ganglia and HMBS in the aorta) interacted with amyloid deposition on executive function performance. Post-hoc analyses provide additional validation of the HMBS and PROK1 effects across two independent subsets of ADNI using two additional metrics of amyloid deposition. These results highlight a subset of unique candidate genes of resilience and provide evidence that cell-cycle regulation, angiogenesis, and heme biosynthesis likely play a role in AD progression.
KeywordsAmyloid Resilience Genetics PrediXcan Cognition PET
Compliance with ethical standards
This research was supported in part by the Building Interdisciplinary Research Careers in Women’s Health program (K12-HD043483, TJH), K01-AG049164 (TJH), R01-HL111516 (ALJ), R01-AG034962 (ALJ), K24-AG046373 (ALJ), and the Vanderbilt Memory & Alzheimer’s Center.
Conflict of interest
The authors report no conflicts of interest.
Informed consent was obtained from all participants included in the study.
- Dwyer, B. E., Smith, M. A., Richardson, S. L., Perry, G., & Zhu, X. (2009). Down-regulation of aminolevulinate synthase, the rate-limiting enzyme for heme biosynthesis in Alzheimer’s disease. Neuroscience Letters, 460(2), 180–184. doi: 10.1016/j.neulet.2009.05.058.CrossRefPubMedPubMedCentralGoogle Scholar
- Gibbons, L. E., Carle, A. C., Mackin, R. S., Harvey, D., Mukherjee, S., Insel, P., et al. (2012). A composite score for executive functioning, validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging and Behavior, 6(4), 517–527.CrossRefPubMedPubMedCentralGoogle Scholar
- Guo, L. H., Alexopoulos, P., & Perneczky, R. (2013). Heart-type fatty acid binding protein and vascular endothelial growth factor: cerebrospinal fluid biomarker candidates for Alzheimer’s disease. European Archives of Psychiatry and Clinical Neuroscience, 263(7), 553–560.CrossRefPubMedGoogle Scholar
- Jack Jr., C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., et al. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. The Lancet Neurology, 9(1), 119–128.Google Scholar
- Jack Jr., C. R., Knopman, D. S., Jagust, W. J., Petersen, R. C., Weiner, M. W., Aisen, P. S., et al. (2013). Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. The Lancet Neurology, 12(2), 207–216.CrossRefPubMedPubMedCentralGoogle Scholar
- Jefferson, A. L., Himali, J. J., Beiser, A. S., Au, R., Massaro, J. M., Seshadri, S., et al. (2010). Cardiac index is associated with brain aging the framingham heart study. Circulation, 122(7), 690–697.Google Scholar
- Jefferson, A. L., Beiser, A. S., Himali, J. J., Seshadri, S., O’Donnell, C. J., Manning, W. J., et al. (2015a). Low cardiac index is associated with incident dementia and Alzheimer Disease: the Framingham Heart Study. Circulation, 131(15), 1333–1339.Google Scholar
- Koran, M. I., Wagener, M. A., & Hohman, T. J. (2016). Sex differences in the association between AD biomarkers and cognitive decline. Brain Imaging and Behavior. doi: 10.1007/s11682-016-9523-8.
- LeCouter, J., Lin, R., & Ferrara, N. (2002). Endocrine gland-derived VEGF and the emerging hypothesis of organ-specific regulation of angiogenesis. Nature Medicine, 8(9), 913–917. doi: 10.1038/nm0902-913.
- Mormino, E. C., Betensky, R. A., Hedden, T., Schultz, A. P., Amariglio, R. E., Rentz, D. M., et al. (2014a). Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals. JAMA Neurology, 71(11), 1379–1385.Google Scholar
- Mormino, E. C., Betensky, R. A., Hedden, T., Schultz, A. P., Ward, A., Huijbers, W., et al. (2014b). Amyloid and APOE ε4 interact to influence short-term decline in preclinical Alzheimer disease. Neurology, 82(20), 1760–1767.Google Scholar
- Nizzari, M., Venezia, V., Repetto, E., Caorsi, V., Magrassi, R., Gagliani, M. C., et al. (2007). Amyloid precursor protein and Presenilin1 interact with the adaptor GRB2 and modulate ERK 1,2 signaling. The Journal of Biological Chemistry, 282(18), 13833–13844.Google Scholar
- Pikula, A., Beiser, A. S., Chen, T. C., Preis, S. R., Vorgias, D., DeCarli, C., et al. (2013). Serum brain-derived neurotrophic factor and vascular endothelial growth factor levels are associated with risk of stroke and vascular brain injury: Framingham Study. Stroke, 44(10), 2768–2775. doi: 10.1161/strokeaha.113.001447.
- Su, M. T., Lin, S. H., Chen, Y. C., & Kuo, P. L. (2014). Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss. Journal of Assisted Reproduction and Genetics, 31(6), 699–705. doi: 10.1007/s10815-014-0223-2.CrossRefPubMedPubMedCentralGoogle Scholar
- Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O’Keeffe, S., et al. (2014). An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. The Journal of Neuroscience, 34(36), 11929–11947.CrossRefPubMedPubMedCentralGoogle Scholar
- Zhang, J. B., Li, M. F., Zhang, H. X., Li, Z. G., Sun, H. R., Zhang, J. S., et al. (2016). Association of serum vascular endothelial growth factor levels and cerebral microbleeds in patients with Alzheimer’s disease. European Journal of Neurology, 23(8), 1337–1342.Google Scholar