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Updated: Nov 28, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
Published on: December 15, 2023
Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential
Minghui Wang1, Aiqun Li2, Michiko Sekiya3
1Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA.
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.
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