MultiNEP: a multi-omics network enhancement framework for prioritizing disease genes and metabolites simultaneously.

TitleMultiNEP: a multi-omics network enhancement framework for prioritizing disease genes and metabolites simultaneously.
Publication TypeJournal Article
Year of Publication2023
AuthorsXu Z, Marchionni L, Wang S
Date Published2023 Jun 01
KeywordsComputer Simulation, Gene Regulatory Networks, Humans, Metabolome, Multiomics, Neoplasms

MOTIVATION: Many studies have successfully used network information to prioritize candidate omics profiles associated with diseases. The metabolome, as the link between genotypes and phenotypes, has accumulated growing attention. Using a "multi-omics" network constructed with a gene-gene network, a metabolite-metabolite network, and a gene-metabolite network to simultaneously prioritize candidate disease-associated metabolites and gene expressions could further utilize gene-metabolite interactions that are not used when prioritizing them separately. However, the number of metabolites is usually 100 times fewer than that of genes. Without accounting for this imbalance issue, we cannot effectively use gene-metabolite interactions when simultaneously prioritizing disease-associated metabolites and genes.

RESULTS: Here, we developed a Multi-omics Network Enhancement Prioritization (MultiNEP) framework with a weighting scheme to reweight contributions of different sub-networks in a multi-omics network to effectively prioritize candidate disease-associated metabolites and genes simultaneously. In simulation studies, MultiNEP outperforms competing methods that do not address network imbalances and identifies more true signal genes and metabolites simultaneously when we down-weight relative contributions of the gene-gene network and up-weight that of the metabolite-metabolite network to the gene-metabolite network. Applications to two human cancer cohorts show that MultiNEP prioritizes more cancer-related genes by effectively using both within- and between-omics interactions after handling network imbalance.

AVAILABILITY AND IMPLEMENTATION: The developed MultiNEP framework is implemented in an R package and available at:

Alternate JournalBioinformatics
PubMed ID37216914
PubMed Central IDPMC10250081
Grant ListR01 CA200859 / CA / NCI NIH HHS / United States
Related Faculty: 
Luigi Marchionni, M.D., Ph.D.

Pathology & Laboratory Medicine 1300 York Avenue New York, NY 10065 Phone: (212) 746-6464
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