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Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer's Disease.

TitleTransformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer's Disease.
Publication TypeJournal Article
Year of Publication2021
AuthorsWang M, Li A, Sekiya M, Beckmann ND, Quan X, Schrode N, Fernando MB, Yu A, Zhu L, Cao J, Lyu L, Horgusluoglu E, Wang Q, Guo L, Wang Y-S, Neff R, Song W-M, Wang E, Shen Q, Zhou X, Ming C, Ho S-M, Vatansever S, H Kaniskan Ü, Jin J, Zhou M-M, Ando K, Ho L, Slesinger PA, Yue Z, Zhu J, Katsel P, Gandy S, Ehrlich ME, Fossati V, Noggle S, Cai D, Haroutunian V, Iijima KM, Schadt E, Brennand KJ, Zhang B
JournalNeuron
Volume109
Issue2
Pagination257-272.e14
Date Published2021 01 20
ISSN1097-4199
KeywordsAlzheimer Disease, Animals, Animals, Genetically Modified, Brain, Databases, Genetic, Drosophila melanogaster, Female, Gene Regulatory Networks, Humans, Induced Pluripotent Stem Cells, Male, Sequence Analysis, RNA, Signal Transduction
Abstract

To identify the molecular mechanisms and novel therapeutic targets of late-onset Alzheimer's Disease (LOAD), we performed an integrative network analysis of multi-omics profiling of four cortical areas across 364 donors with varying cognitive and neuropathological phenotypes. Our analyses revealed thousands of molecular changes and uncovered neuronal gene subnetworks as the most dysregulated in LOAD. ATP6V1A was identified as a key regulator of a top-ranked neuronal subnetwork, and its role in disease-related processes was evaluated through CRISPR-based manipulation in human induced pluripotent stem cell-derived neurons and RNAi-based knockdown in Drosophila models. Neuronal impairment and neurodegeneration caused by ATP6V1A deficit were improved by a repositioned compound, NCH-51. This study provides not only a global landscape but also detailed signaling circuits of complex molecular interactions in key brain regions affected by LOAD, and the resulting network models will serve as a blueprint for developing next-generation therapeutic agents against LOAD.

DOI10.1016/j.neuron.2020.11.002
Pubmed Linkhttps://www.ncbi.nlm.nih.gov/pubmed/33238137?dopt=Abstract
page_expoInternal
Alternate JournalNeuron
PubMed ID33238137
PubMed Central IDPMC7855384
Grant ListRF1 AG057440 / AG / NIA NIH HHS / United States
RF1 AG054014 / AG / NIA NIH HHS / United States
U01 AG052411 / AG / NIA NIH HHS / United States
R01 AG068030 / AG / NIA NIH HHS / United States
R56 AG058655 / AG / NIA NIH HHS / United States
U01 AI111598 / AI / NIAID NIH HHS / United States
RF1 AG057443 / AG / NIA NIH HHS / United States
P30 AG066514 / AG / NIA NIH HHS / United States
R01 AG062355 / AG / NIA NIH HHS / United States
R56 MH101454 / MH / NIMH NIH HHS / United States
U01 AG046170 / AG / NIA NIH HHS / United States
R01 AG057907 / AG / NIA NIH HHS / United States
R01 DA043247 / DA / NIDA NIH HHS / United States
RF1 AG059319 / AG / NIA NIH HHS / United States
U01 AG058635 / AG / NIA NIH HHS / United States
R01 DK118243 / DK / NIDDK NIH HHS / United States
R03 DE026814 / DE / NIDCR NIH HHS / United States
R01 MH121074 / MH / NIMH NIH HHS / United States

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