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Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer’s disease

Merchant, Julie P., Zhu, Kuixi, Henrion, Marc, Zaidi, Syed S. A., Lau, Branden, Moein, Sara, Alamprese, Melissa L., Pearse, Richard V., Bennett, David A., Ertekin-Taner, Nilüfer, Young-Pearse, Tracy L. and Chang, Rui (2023) 'Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer’s disease'. Communications Biology, Vol 6, Issue 1, e503.

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Despite decades of genetic studies on late-onset Alzheimer’s disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer’s pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer’s-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer’s disease.

Item Type: Article
Subjects: WL Nervous System > WL 140 Nervous system diseases (General)
WL Nervous System > WL 20 Research (General)
WL Nervous System > WL 300 General works (Include works on brain alone)
Faculty: Department: Clinical Sciences & International Health > Malawi-Liverpool-Wellcome Programme (MLW)
Digital Object Identifer (DOI):
SWORD Depositor: JISC Pubrouter
Depositing User: JISC Pubrouter
Date Deposited: 16 May 2023 07:39
Last Modified: 09 Jun 2023 10:51


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