Alzheimer's disease (AD) is the most common cause of dementia characterized by brain accumulation of senile plaques and neurofibrillary tangles. AD risk is likely influenced by a multitude of genetic and environmental risk factors and their complex interplay, which subsequently lead to cascades of downstream pathophysiologic events that include but are not limited to aberrant proteostasis and lipid metabolism, as well as inflammatory, vascular, and oxidative mechanisms. The array of risk factors that lead to AD and their downstream influences are likely to be heterogeneous amongst AD patients, which complicates the search for drug targets, biomarkers and their potential downstream beneficial use in any given AD patient. For this reason, drug target and biomarker discovery efforts in AD have to focus on identification of both molecular mechanisms that are commonly perturbed in AD patients, as well as those mechanisms that may underlie heterogeneity in AD. To overcome this massive challenge, team-science efforts, including the NIH initiatives, Accelerating Medicines Partnership-AD (AMP-AD) and Molecular Mechanisms of the Vascular Etiology of AD (M2OVE-AD) Consortia, have launched large-scale generation and analyses of multi-omics data from well- phenotyped human cohorts and model systems. These consortia aim to integrate multi-omics and clinical endophenotype data to build a model(s) of AD that captures these common and heterogeneous pathomechanisms. Our teams are leading participants of both AMP-AD and M2OVE-AD. The initial findings from these consortia reveal concerted changes in networks of expressed genes and proteins in AD subjects and model systems, with biological significance. Despite this progress and wide and immediate sharing of the data generated by these programs, significant gaps remain in the available ?omics data, and the ability to integrate, harmonize and annotate these datasets. Our proposal is in response to the RFA-AG-17-054, which aims to close these gaps. In this proposal, we maintain the overall objective of our parent funded M2OVE-AD project (RF1 AG51504), which is to determine APOE- and sex-dependent effects, and uncover novel genes and pathways that influence vascular risk in aging, AD and other dementias.
Our specific aims are: 1. Integrative functional genomic analysis of human brains to discover novel pathways in AD. 2. Integrative functional genomic analysis in a prospective cohort to validate and discover AD pathways. 3. Investigate the impact of APOE genotype and sex on transcriptional networks and the metabolome in model systems. 4. Perform single-cell profiling to annotate the transcriptome data from AMP-AD and M2OVE-AD. These studies will add key epigenetic data (H3K9Ac and RRBS methylome) to the human and transcriptome and metabolomics data to the mouse cohorts, generate human and mouse single cell transcriptome data, and perform integrative network analyses. We expect this proposal to fill key gaps in knowledge and further enhance the AMP-AD and M2OVE-AD initiatives in their drug and biomarker discovery goals.

Public Health Relevance

Alzheimer's disease (AD) is a heterogeneous disease influenced by genetic and environmental risk factors that subsequently lead to cascades of downstream pathophysiologic events including aberrant proteostasis and lipid metabolism, as well as inflammatory, vascular, and oxidative mechanisms. The goal of our proposed project is to identify the key genetic events and their associated biological consequences in AD, by leveraging and enhancing the data we and others generate as part of the AMP-AD and M2OVE-AD consortia. With a focus especially on vascular mechanisms and identification on novel perturbed networks of genes and metabolites, we will also explore sex and APOE-effects with the ultimate goal of discovering novel drug targets and biomarkers in AD.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
3RF1AG051504-01S2
Application #
9421402
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Petanceska, Suzana
Project Start
2017-09-15
Project End
2020-08-31
Budget Start
2017-09-15
Budget End
2020-08-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Mayo Clinic Jacksonville
Department
Type
DUNS #
153223151
City
Jacksonville
State
FL
Country
United States
Zip Code
32224
Dickson, Dennis W; Heckman, Michael G; Murray, Melissa E et al. (2018) APOE ?4 is associated with severity of Lewy body pathology independent of Alzheimer pathology. Neurology 91:e1182-e1195
Chakrabarty, Paramita; Li, Andrew; Ladd, Thomas B et al. (2018) TLR5 decoy receptor as a novel anti-amyloid therapeutic for Alzheimer's disease. J Exp Med 215:2247-2264
Whitwell, Jennifer L; Graff-Radford, Jonathan; Tosakulwong, Nirubol et al. (2018) [18 F]AV-1451 clustering of entorhinal and cortical uptake in Alzheimer's disease. Ann Neurol 83:248-257
Zhao, Na; Liu, Chia-Chen; Qiao, Wenhui et al. (2018) Apolipoprotein E, Receptors, and Modulation of Alzheimer's Disease. Biol Psychiatry 83:347-357
Chung, Jaeyoon; Zhang, Xiaoling; Allen, Mariet et al. (2018) Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer's disease. Alzheimers Res Ther 10:22
Whitwell, Jennifer L; Graff-Radford, Jonathan; Tosakulwong, Nirubol et al. (2018) Imaging correlations of tau, amyloid, metabolism, and atrophy in typical and atypical Alzheimer's disease. Alzheimers Dement 14:1005-1014
Allen, Mariet; Wang, Xue; Burgess, Jeremy D et al. (2018) Conserved brain myelination networks are altered in Alzheimer's and other neurodegenerative diseases. Alzheimers Dement 14:352-366
Ogaki, Kotaro; Martens, Yuka A; Heckman, Michael G et al. (2018) Multiple system atrophy and apolipoprotein E. Mov Disord 33:647-650
Conway, Olivia J; Carrasquillo, Minerva M; Wang, Xue et al. (2018) ABI3 and PLCG2 missense variants as risk factors for neurodegenerative diseases in Caucasians and African Americans. Mol Neurodegener 13:53
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872

Showing the most recent 10 out of 55 publications