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Integrative Pathway Analysis of SNP and Metabolite Data Using a Hierarchical Structural Component Model
- Title
- Integrative Pathway Analysis of SNP and Metabolite Data Using a Hierarchical Structural Component Model
- Authors
- Jung, Taeyeong; Jung, Youngae; Moon, Min Kyong; Kwon, Oran; Hwang, Geum-Sook; Park, Taesung
- Ewha Authors
- 권오란; 황금숙
- SCOPUS Author ID
- 권오란; 황금숙
- Issue Date
- 2022
- Journal Title
- FRONTIERS IN GENETICS
- ISSN
- 1664-8021
- Citation
- FRONTIERS IN GENETICS vol. 13
- Keywords
- pathway analysis; multi-omics integration; mGWAS; metabolite; SNP
- Publisher
- FRONTIERS MEDIA SA
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- Integrative multi-omics analysis has become a useful tool to understand molecular mechanisms and drug discovery for treatment. Especially, the couplings of genetics to metabolomics have been performed to identify the associations between SNP and metabolite. However, while the importance of integrative pathway analysis is increasing, there are few approaches to utilize pathway information to analyze phenotypes using SNP and metabolite. We propose an integrative pathway analysis of SNP and metabolite data using a hierarchical structural component model considering the structural relationships of SNPs, metabolites, pathways, and phenotypes. The proposed method utilizes genome-wide association studies on metabolites and constructs the genetic risk scores for metabolites referred to as genetic metabolomic scores. It is based on the hierarchical model using the genetic metabolomic scores and pathways. Furthermore, this method adopts a ridge penalty to consider the correlations between genetic metabolomic scores and between pathways. We apply our method to the SNP and metabolite data from the Korean population to identify pathways associated with type 2 diabetes (T2D). Through this application, we identified well-known pathways associated with T2D, demonstrating that this method adds biological insights into disease-related pathways using genetic predispositions of metabolites.
- DOI
- 10.3389/fgene.2022.814412
- Appears in Collections:
- 신산업융합대학 > 식품영양학과 > Journal papers
- Files in This Item:
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