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Genetic Drivers of Resilience to Alzheimer's Disease

PI
Hohman, Timothy
DAR ID
10121
Initial Approval Date
November 8, 2019
Current DAR Status
Active
PI Institution
Vanderbilt University Medical Center
PI Institution Country
United States
PI Institution Type
Non-Profit
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“Asymptomatic” Alzheimer’s disease (AD) is a phenomenon in which 30% of individuals over age 65 meet criteria for autopsy-confirmed pathological AD (beta-amyloid plaques and tau aggregation) but do not clinically manifest cognitive impairment.1-3 The resilience that underlies asymptomatic AD is marked by both protection from neurodegeneration (brain resilience)4 and preserved cognition (cognitive resilience).

Our central hypothesis is that
genetic effects allow a subset of individuals to endure extensive AD neuropathology without marked brain atrophy or cognitive impairment. We are uniquely positioned to identify resilience genes by leveraging the Resilience from Alzheimer’s Disease (RAD) database, a local resource in which we
have harmonized a validated quantitative phenotype of resilience across 8 large AD cohort studies.

Our strong interdisciplinary team represents international leaders in genetics, neuroscience, neuropsychology, neuropathology, and psychometrics who will leverage the infrastructure and rich resources of the AD Genetics Consortium, IGAP, ADSP, and our recently established and harmonzed continuous metric of resilience to fulfill the following aims:

Aim 1. Identify and replicate common genetic variants that predict cognitive resilience (preserved cognition) and brain resilience (protection from brain
atrophy) in the presence of AD pathology. We hypothesize that common genetic variation will explain variance in resilience above and beyond known
predictors like education. Replication analyses will leverage age of onset data from IGAP to demonstrate that resilience loci predict a later age of AD onset.

Aim 2. Identify and replicate rare and low-frequency genetic variants that predict cognitive and brain resilience. Rare and low-frequency variants with large effects have been identified in AD case/control studies, providing new insight into the genetic architecture of AD.

Aim 3: Identify sex-specific genetic drivers of cognitive and brain resilience to AD pathology. Our preliminary results highlight sex differences in the downstream consequences of AD neuropathology, including sex-specific genetic markers of resilience.
As the population ages, late-onset Alzheimer’s disease (AD) is becoming an increasingly important public health issue. Clinical trials targeted a reducing AD progression have demonstrated that patients continue to decline despite therapeutic intervention. Thus, there is a pressing need for new treatments aimed at novel therapeutic targets. A shift in focus from risk to resilience has tremendous potential to have a major public health impact by highlighting mechanisms that naturally counteract the damaging effects of AD neuropathology. The goal of the present project is to characterize genetic factors that protect the brain from the downstream consequences of AD neuropathology. We will identify both rare and common genetic
variants using a robust metric of resilience developed and validated by our research team. The identification of such genetic effects will provide novel targets for therapeutic intervention in AD.

Reported Publications (14)

Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.

  1. Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease. Archer DB, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 37985223
  2. Sex and gender differences in cognitive resilience to aging and Alzheimer's disease. Arenaza-Urquijo EM, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 38967222
  3. Sex-specific genetic architecture of late-life memory performance. Eissman JM, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2024. PMID: 37984853
  4. Variants in the MS4A cluster interact with soluble TREM2 expression on biomarkers of neuropathology. Winfree RL, et al. Molecular neurodegeneration. 2024. PMID: 38760857
  5. ZCCHC17 modulates neuronal RNA splicing and supports cognitive resilience in Alzheimer's disease. Bartosch AMW, et al. bioRxiv : the preprint server for biology. 2023. PMID: 36993746
  6. Association between WWOX/MAF variants and dementia-related neuropathologic endophenotypes. Dugan AJ, et al. Neurobiology of aging. 2022. PMID: 34852950
  7. Evaluation of Sex-Aware PrediXcan Models for Predicting Gene Expression. Mahoney E, et al. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2022. PMID: 34890163
  8. Amyloid PET Imaging in Self-Identified Non-Hispanic Black Participants of the Anti-Amyloid in Asymptomatic Alzheimer's Disease (A4) Study. Deters KD, et al. Neurology. 2021. PMID: 33568538
  9. Brain expression of the vascular endothelial growth factor gene family in cognitive aging and alzheimer's disease. Mahoney ER, et al. Molecular psychiatry. 2021. PMID: 31332262
  10. Comparison of Education and Episodic Memory as Modifiers of Brain Atrophy Effects on Cognitive Decline: Implications for Measuring Cognitive Reserve. Mungas D, et al. Journal of the International Neuropsychological Society : JINS. 2021. PMID: 33455611
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  1. Evaluation of Selective Survival and Sex/Gender Differences in Dementia Incidence Using a Simulation Model. Shaw C, et al. JAMA network open. 2021. PMID: 33687445
  2. PLD3 is a neuronal lysosomal phospholipase D associated with β-amyloid plaques and cognitive function in Alzheimer's disease. Nackenoff AG, et al. PLoS genetics. 2021. PMID: 33830999
  3. Protective genes and pathways in Alzheimer's disease: moving towards precision interventions. Seto M, et al. Molecular neurodegeneration. 2021. PMID: 33926499
  4. The relationship between white matter microstructure and self-perceived cognitive decline. Archer DB, et al. NeuroImage. Clinical. 2021. PMID: 34479171