Network approaches for omics studies of neurodegenerative diseases

Abstract

The recent methodological advances in multi-omics approaches, including genomic, transcriptomic, metabolomic, lipidomic, and proteomic, have revolutionized the research field by generating “big data” which greatly enhanced our understanding of the molecular complexity of the brain and disease states. Network approaches have been routinely applied to single-omics data to provide critical insight into disease biology. Furthermore, multi-omics integration has emerged as both a vital need and a new direction to connect the different layers of information underlying disease mechanisms. In this review article, we summarize popular network analytic approaches for single-omics data and multi-omics integration and discuss how these approaches have been utilized in studying neurodegenerative diseases.

Omics and Network-based Approaches in Understanding HD Pathogenesis

“…Other network and bioinformatics-based approaches conducted in HD include Sneha et al [132], Pirhaji et al [133], Pradhan et al [134], Xiang et al [135], Zaho et al [136], Fu et al [137], Shirasaki et al [138], Christodoulou [139][140][141], and Onisiforou [142].…”

Multiomics Evaluation of Human iPSCs and iPSC-Derived Neurons

“…10−13 Network-based multiomics integration perceives biological systems as interconnected units, where each omics layer contributes to uncovering the authentic connections within the networks. 14 Enabled by these bioinformatics tools, integrating proteomics, lipidomics, and metabolomics analyses of iPSCs and neurons can provide us a holistic view of the neuron differentiation process and allow us to understand the alteration of molecular profiles under both healthy and disease states.…”

“…Multiomics analysis has been used to unravel the complex biological processes underlying neurodegenerative diseases. ,, Multiomics experiments must be paired with sophisticated bioinformatic tools to decipher the large-scale multidimensional data sets and integrate different omics data sets into the same biological processes, where genes control protein expression and proteins serve as enzymes for lipid and metabolic pathways. − Network-based multiomics integration perceives biological systems as interconnected units, where each omics layer contributes to uncovering the authentic connections within the networks . Enabled by these bioinformatics tools, integrating proteomics, lipidomics, and metabolomics analyses of iPSCs and neurons can provide us a holistic view of the neuron differentiation process and allow us to understand the alteration of molecular profiles under both healthy and disease states.…”