Analyses of high-throughput human data, including gene expression profiles of human brains, constitute a powerful strategy for nominating biological networks associated with Alzheimer?s disease (AD) pathophysiology as potential therapeutic targets. The Accelerating Medicines Partnership-Alzheimer?s Disease (AMP-AD) Target Discovery Project has defined consensus, AD-associated molecular networks based on joint analyses of transcriptomic profiles in ~2,000 human brain autopsy samples. The critical next step is to rigorously test computational predictions in experimental animal models to (i) unambiguously link promising networks to specific AD triggers (i.e. Amyloid-, Tau, and/or aging), (ii) confirm the network architecture, (iii) validate implicated molecular pathways in the nervous system context, and (iv) discover which molecular changes are truly causal, including distinguishing between amplifiers of pathogenesis versus protective, compensatory responses. We have developed a cross-species strategy for functional dissection of emerging AD molecular networks using high-throughput assays in the nervous system of transgenic Drosophila expressing human wild-type human Tau or the Amyloid- peptide. When applied to candidates from AD-associated networks, these rapid and complementary in vivo assays enable identification of those genes and pathways that are likely causal modifiers of Tau- and/or A-induced neuronal dysfunction, including both drivers of pathogenesis and compensatory responses. The overall goal of this proposal is to deploy our cross-species strategy to accelerate the discovery, refinement, and functional dissection of AD molecular networks derived from human brain transcriptomes and proteomes.
First (AIM 1), transcriptomic and proteomic profiling in Drosophila AD models will be coupled with comprehensive screening of conserved network candidates in order to identify those genes causally linked to neurodegeneration and differentiate in vivo interactions with Tau-, A-, or other age-dependent mechanisms. The proposed screen will deploy robotic instrumentation for high-throughput, quantitative analyses of Drosophila motor impairment due to neuronal dysfunction.
Second (AIM 2), using systems biology approaches, gene expression and functional data from Drosophila will be integrated with the human AD networks. The resulting multi-scale atlas of AD molecular systems will pinpoint causal networks and key gene/protein drivers with the greatest potential to alter neurodegeneration upon perturbation.
Next (AIM 3), we will experimentally confirm the network architecture for the most promising modules highlighting key drivers with roles as AD amplifying/protective factors. Lastly (AIM 4), all project results will be made publicly available via the AMP-AD Knowledge Portal. IMPACT: Our integrative, cross-species discovery strategy will comprehensively probe AD molecular networks with powerful, in vivo functional assays to reveal age- dependent drivers, including amplifiers and protectors, for Tau- and A-induced neurotoxicity, and elucidate the complex network architecture underlying AD pathogenesis.

Public Health Relevance

Alzheimer?s disease is a devastating and incurable neurodegenerative disorder projected to affect 13 million individuals in the US by 2050. Integrating recent advances from studies of large human brain autopsy collections with innovative model organism investigations, we will discover the gene and protein networks responsible for Alzheimer?s disease. An improved functional understanding of Alzheimer?s disease gene regulatory networks, including disease amplifying and protective factors, holds enormous potential for therapeutic breakthroughs.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG057339-02
Application #
9564813
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Kohanski, Ronald A
Project Start
2017-09-15
Project End
2022-05-31
Budget Start
2018-06-01
Budget End
2019-05-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
Guo, Caiwei; Jeong, Hyun-Hwan; Hsieh, Yi-Chen et al. (2018) Tau Activates Transposable Elements in Alzheimer's Disease. Cell Rep 23:2874-2880
Raman, Ayush T; Pohodich, Amy E; Wan, Ying-Wooi et al. (2018) Apparent bias toward long gene misregulation in MeCP2 syndromes disappears after controlling for baseline variations. Nat Commun 9:3225