Figure 1. Asymptomatic Alzheimer's disease phenomenon.

Resilience Updated Model Figure1.jpg


Limited empirical attention has focused on elucidating factors underlying “asymptomatic” Alzheimer’s disease (AD), a phenomenon in which individuals present with autopsy-confirmed pathological AD (β-amyloid plaques and aggregation of tau) but without the clinical manifestation of cognitive impairment. Asymptomatic AD is present in approximately 30% of cognitively normal older adults, suggesting that there may be naturally occurring factors that fight against the damaging effects of plaques and tangles (Figure 1).

This research initiative seeks to better understand asymptomatic AD by (1) building better endophenotypes of resilience using advanced biostatistical methods, and (2) leveraging the growing wealth of ‘omic data to identify novel pathways of resilience. We work in active collaboration with the Alzheimer’s Disease Genetics Consortium, while also leveraging data from our local cohort here at Vanderbilt (the Memory and Aging Project) and multiple publicly available multi-center datasets such as the Alzheimer’s Disease Neuroimaging Initiative and the National Alzheimer’s Coordinating Center dataset. We also take a multidisciplinary approach that leverages advanced techniques from the fields of neuroimaging, biomarker detection, genomics, neuropsychology, and neuropathology. Our work has built a robust phenotype of resilience leveraging advanced statistical approaches (Figure 2) resulting in a metric of resilience that is particularly sensitive to detecting preserved cognition in the presence of enhanced biomarkers of AD neuropathology (Figure 3).


Figure 2: Partial least squares path model that leverages residuals relating AD biomarkers to cognitive and neuroimaging outcomes. The model integrates our metrics of resilience within an established framework of cognitive and brain reserve. (Hohman et al., 2016, Neurology)


Figure 3: Higher levels of global resilience are related to slower rates of cognitive decline, particularly among individuals who are positive for biomarkers of AD neuropathology. (Hohman et al., 2016, Neurology)

Additional work in this initiative has evaluated complex genomic (Figure 4) and proteomic (Figure 5) interaction models to identify factors that modulate the association between known AD biomarkers and neurodegenerative disease. These research projects have resulted in the identification of novel genomic and proteomic markers of risk and resilience including the Protection of Telomeres 1 gene, Glycogen Synthase Kinase 3 beta gene, and the Vascular Endothelial Growth Factor protein. As we build out the sophistication of our endophenotype definitions and genomic/proteomic prediction models we are excited by the prospect of identifying markers of resilience that act across the spectrum of neurodegenerative diseases.



Figure 4. POT1 (rs4728029) modifies the relationship between posphorylated tau (PTau) and lateral inferior ventricular volume in ventricle dilation. The y-axis represents annual change in ventricular volume in cubic millimeter. The x-axis represents cerebrospinal fluid (CSF) PTau in pg/mL. Points and lines are color coded by rs4728029 genotype. The R2 linear for A/A carriers is 0.17, for A/G or G/A carriers it is 0.06, and for G/G carrier it is 0.02. ICV, intracranial volume. (Hohman et al., 2014, Alzheimer's & Dementia)


Figure 5: High levels of vascular endothelial growth factor (VEGF) measured in the cererbrospinal fluid are associated with a slower rate of cognitive decline. The beneficial effect of VEGF is particularly strong among individuals who are positive for biomarkers of AD neuropathology. (Hohman et al., 2015, JAMA Neurology)


Relevant Publications




  • Deming Y, Dumitrescu L, Barnes LL, Thambisetty M, Kunkle B, Gifford KA, Bush WS, Chibnik LB, Mukherjee S, De Jager PL, Kukull W, Huentelman M, Crane PK, Resnick SM, Keene CD, Montine TJ, Schellenberg GD, Haines JL, Zetterberg H, Blennow K, Larson EB, Johnson SC, Albert M, Moghekar A, Del Aguila JL, Fernandez MV, Budde J, Hassenstab J, Fagan AM, Riemenschneider M, Petersen RC, Minthon L, Chao MJ, Van Deerlin VM, Lee VM, Shaw LM, Trojanowski JQ, Peskind ER, Li G, Davis LK, Sealock JM, Cox NJ, Goate AM, Bennett DA, Schneider JA, Jefferson AL, Cruchaga C, Hohman TJ. Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta neuropathologica. 2018 Jul 2. PMID: 29967939 [PubMed]