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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
MICRORNA-AUGMENTED PATHWAYS (mirAP) AND THEIR APPLICATIONS TO PATHWAY ANALYSIS AND DISEASE SUBTYPING
Diana Diaz1, Michele Donato, Tin Nguyen
1Department of Computer Science, Wayne State University, Detroit, MI 48202, U.S.A.
Abstract:
MicroRNAs play important roles in the development of many complex diseases. Because of their importance, the analysis of signaling pathways including miRNA interactions holds the potential for unveiling the mechanisms underlying such diseases. However, current signaling pathway databases are limited to interactions between genes and ignore miRNAs. Here, we use the information on miRNA targets to build a database of miRNA-augmented pathways (mirAP), and we show its application in the contexts of integrative pathway analysis and disease subtyping. Our miRNA-mRNA integrative pathway analysis pipeline incorporates a topology-aware approach that we previously implemented. Our integrative disease subtyping pipeline takes into account survival data, gene and miRNA expression, and knowledge of the interactions among genes. We demonstrate the advantages of our approach by analyzing nine sample-matched datasets that provide both miRNA and mRNA expression. We show that integrating miRNAs into pathway analysis results in greater statistical power, and provides a more comprehensive view of the underlying phenomena. We also compare our disease subtyping method with the state-of-the-art integrative analysis by analyzing a colorectal cancer database from TCGA. The colorectal cancer subtypes identified by our approach are significantly different in terms of their survival expectation. These miRNA-augmented pathways offer a more comprehensive view and a deeper understanding of biological pathways. A better understanding of the molecular processes associated with patients' survival can help to a better prognosis and an appropriate treatment for each subtype.
Insights
We developed miRNA-augmented pathways (mirAP) to integrate microRNA (miRNA) and gene interactions for disease analysis. This approach enhances pathway analysis power and improves disease subtyping for better patient prognosis.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- MicroRNAs (miRNAs) are crucial in complex disease development.
- Current pathway databases lack miRNA interactions, limiting disease mechanism insights.
- Integrating miRNA targets into pathway analysis is essential for comprehensive understanding.
Purpose of the Study:
- To develop a database of miRNA-augmented pathways (mirAP).
- To apply mirAP for integrative pathway analysis and disease subtyping.
- To improve understanding of molecular mechanisms underlying complex diseases and patient survival.
Main Methods:
- Constructed mirAP using miRNA target information.
- Developed a miRNA-mRNA integrative pathway analysis pipeline with a topology-aware approach.
- Created an integrative disease subtyping pipeline incorporating survival data, gene, and miRNA expression.
Main Results:
- Analyzed nine sample-matched miRNA and mRNA expression datasets.
- Demonstrated increased statistical power and a more comprehensive view by integrating miRNAs into pathway analysis.
- Identified colorectal cancer subtypes with significantly different survival expectations using TCGA data.
Conclusions:
- miRNA-augmented pathways provide a deeper understanding of biological processes.
- The developed approach enhances disease subtyping accuracy and prognostic capabilities.
- Improved understanding of molecular mechanisms can lead to better patient prognosis and tailored treatments.
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