Dissecting genetic regulation of metabolic coordination

Understanding genetic regulation of metabolism is critical for gaining insights into the causes of metabolic diseases. Traditional metabolome-based genome-wide association studies (mGWAS) focus on static associations between single nucleotide polymorphisms (SNPs) and metabolite levels, overlooking the changing relationships caused by genotypes within the metabolic network. Notably, some metabolites exhibit changes in correlation patterns with other metabolites under certain physiological conditions while maintaining their overall abundance level. In this manuscript, we develop Metabolic Differential-coordination GWAS (mdGWAS), an innovative framework that detects SNPs associated with the changing correlation patterns between metabolites and metabolic pathways. This approach transcends and complements conventional mean-based analyses by identifying latent regulatory factors that govern the system-level metabolic coordination. Through comprehensive simulation studies, mdGWAS demonstrated robust performance in detecting SNP-metabolite-metabolite associations. Applying mdGWAS to genotyping and mass spectrometry (MS)-based metabolomics data of the METabolic Syndrome In Men (METSIM) Study revealed novel SNPs and genes potentially involved in the regulation of the coordination between metabolic pathways.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2025-03-01
DOI
https://doi.org/10.1093/bib/bbaf095
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Dissecting genetic regulation of metabolic coordination

Tianwei Yu, Jian Kang, Emily C. Hector, Daiwei Zhang et al.
Briefings in Bioinformatics
Metabolomics and Mass Spectrometry Studies
article

Dissecting genetic regulation of metabolic coordination

Tianwei Yu, Jian Kang, Emily C. Hector, Daiwei Zhang, Jiashun Xiao, Tianyi Xu, Leqi Tian, Xianyong Yin, Yun Bai, Junning Feng, Markku Laakso
article en

Abstract

Understanding genetic regulation of metabolism is critical for gaining insights into the causes of metabolic diseases. Traditional metabolome-based genome-wide association studies (mGWAS) focus on static associations between single nucleotide polymorphisms (SNPs) and metabolite levels, overlooking the changing relationships caused by genotypes within the metabolic network. Notably, some metabolites exhibit changes in correlation patterns with other metabolites under certain physiological conditions while maintaining their overall abundance level. In this manuscript, we develop Metabolic Differential-coordination GWAS (mdGWAS), an innovative framework that detects SNPs associated with the changing correlation patterns between metabolites and metabolic pathways. This approach transcends and complements conventional mean-based analyses by identifying latent regulatory factors that govern the system-level metabolic coordination. Through comprehensive simulation studies, mdGWAS demonstrated robust performance in detecting SNP-metabolite-metabolite associations. Applying mdGWAS to genotyping and mass spectrometry (MS)-based metabolomics data of the METabolic Syndrome In Men (METSIM) Study revealed novel SNPs and genes potentially involved in the regulation of the coordination between metabolic pathways.

Briefings in BioinformaticsVol. 26(2)
University of North Carolina at Chapel Hill (US), North Carolina State University (US), University of Eastern Finland (FI), University of Michigan (US), Shenzhen Research Institute of Big Data (CN), Chinese University of Hong Kong, Shenzhen (CN)
National Science Foundation, National Institutes of Health
Openalex Percentile: Top 96%
Metabolomics and Mass Spectrometry Studies
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