Details

Autor(en) / Beteiligte

• Wang, Minghui
• Li, Aiqun
• Sekiya, Michiko
• Beckmann, Noam D.
• Quan, Xiuming
• Schrode, Nadine
• Fernando, Michael B.
• Yu, Alex
• Zhu, Li
• Cao, Jiqing
• Lyu, Liwei
• Horgusluoglu, Emrin
• Wang, Qian
• Guo, Lei
• Wang, Yuan-shuo
• Neff, Ryan
• Song, Won-min
• Wang, Erming
• Shen, Qi
• Zhou, Xianxiao
• Ming, Chen
• Ho, Seok-Man
• Vatansever, Sezen
• Kaniskan, H. Ümit
• Jin, Jian
• Zhou, Ming-Ming
• Ando, Kanae
• Ho, Lap
• Slesinger, Paul A.
• Yue, Zhenyu
• Zhu, Jun
• Katsel, Pavel
• Gandy, Sam
• Ehrlich, Michelle E.
• Fossati, Valentina
• Noggle, Scott
• Cai, Dongming
• Haroutunian, Vahram
• Iijima, Koichi M.
• Schadt, Eric
• Brennand, Kristen J.
• Zhang, Bin

Titel

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

Ist Teil von

• Neuron (Cambridge, Mass.), 2021-01, Vol.109 (2), p.257-272.e14

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2021

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. [Display omitted] •Development of gene network models of four cortical areas affected by LOAD•Identification of region-specific molecular changes and gene subnetworks in LOAD•ATP6V1A is a top key regulator of a neuronal subnetwork most disrupted in LOAD•NCH-51 normalizes neuronal impairment and neurodegeneration caused by ATP6V1A deficit Employing an integrative network biology approach, Wang et al. identify critical gene subnetworks associated with late-onset Alzheimer’s disease (LOAD) and predict ATP6V1A as a key regulator of a neuron-specific subnetwork most affected by LOAD. ATP6V1A deficit causes neuronal impairment and neurodegeneration, which are normalized by a predicted compound, NCH-51.