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Novel Time-dependent Multi-omics Integration in Sepsis-associated Liver Dysfunction
The recently developed technologies that allow the analysis of each single omics have provided an unbiased insight into ongoing disease processes. However, it remains challenging to specify the study design for the subsequent integration strategies that can associate sepsis pathophysiology and clini...
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Published in: | Genomics, proteomics & bioinformatics proteomics & bioinformatics, 2023-12, Vol.21 (6), p.1101-1116 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The recently developed technologies that allow the analysis of each single omics have provided an unbiased insight into ongoing disease processes. However, it remains challenging to specify the study design for the subsequent integration strategies that can associate sepsis pathophysiology and clinical outcomes. Here, we conducted a time-dependent multi-omics integration (TDMI) in a sepsis-associated liver dysfunction (SALD) model. We successfully deduced the relation of the Toll-like receptor 4 (TLR4) pathway with SALD. Although TLR4 is a critical factor in sepsis progression, it is not specified in single-omics analyses but only in the TDMI analysis. This finding indicates that the TDMI-based approach is more advantageous than single-omics analyses in terms of exploring the underlying pathophysiological mechanism of SALD. Furthermore, TDMI-based approach can be an ideal paradigm for insightful biological interpretations of multi-omics datasets that will potentially reveal novel insights into basic biology, health, and diseases, thus allowing the identification of promising candidates for therapeutic strategies. |
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ISSN: | 1672-0229 2210-3244 |
DOI: | 10.1016/j.gpb.2023.04.002 |