Wang, M., Li, A., Sekiya, M., Beckmann, N.D., Quan, X., Schrode, N., Fernando, M.B., 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., Kaniskan, H.Ü., Jin, J., Zhou, M.M., Ando, K., Ho, L., Slesinger, P.A., Yue, Z., Zhu, J., Katsel, P., Gandy, S., Ehrlich, M.E., Fossati, V., Noggle, S., Cai, D., Haroutunian, V., Iijima, K.M., Schadt, E., Brennand, K.J., Zhang, B. (2021). Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer's Disease.  Neuron 109(2): 257--272.e14.

FBrf0247836

Research paper

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.

PMC7855384 (PMC) (EuropePMC)