Deep trans‐omic network fusion for altered functional interactions underlying Alzheimer’s Disease
Year: 2023
Type: article
Abstract: Background Multi‐omic data like genotype, gene expression and protein expression have been increasingly explored in post‐GWAS era to interpret GWAS findings and to gain more insight of the Alzheimer’s disease (AD) mechanism. However, each ‐omics data type is usually examined individually and identified genetic variations, genes and proteins are not necessarily functionally related. Method We used GWAS genotype, RNA‐Seq gene expression, and protein expression data from 133 subjects of ROS/MAP Project for original study and 121 subjects of Mount Sinai Brain Bank (MSBB) for replication (Fig. 1a). The multi‐omic data pre‐processing steps were shown in Fig. 1b. We proposed a new interpretable deep neural network MoFNet, extended from Varmole [1], to jointly model the prior knowledge of functional interactions using ROS/MAP cohort (Fig. 1c). It aimed to identify a subnetwork of functional interactions from prior knowledge that are both predictive of AD and evidenced by multi‐omic data. Particularly, prior functional interaction network was embedded into the architecture of MoFNet in a way that it resembles the information flow from DNA to gene and protein. Result The proposed model MoFNet significantly outperformed all other state‐of‐art classifiers when evaluated using multi‐omic data from ROS/MAP cohort (Table 1). It yielded three major multi‐omic sub‐networks related to innate immune system, clearance of mis‐folded proteins, and neurotransmitter release respectively (Fig. 2a). One subnetwork includes all the major members of the SNARE complex, an essential mediator of synaptic vesicle fusion. Majority of our identified genes/proteins are related to synaptic activities in neuronal, astrocyte and microglial cells. Differential expression analysis show MoFNet returned more genes and proteins due to functional connections (Fig. 2b). Around 50% of these findings were replicated in another independent cohort (MSBB). Conclusion Our identified gene/proteins are highly related to synaptic vesicle function. Altered regulation or expression of these genes/proteins could cause disruption in neuron‐neuron or neuron‐glia cross talk and further lead to neuronal and synapse loss in AD. Further investigation of these identified genes/proteins could possibly help decipher the mechanisms underlying synaptic dysfunction in AD, and ultimately inform therapeutic strategies to modify AD progression in the early stage. [1] Nguyen et al., Bioinformatics, 2021.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.077343
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4390199375