ArticleOmics : a journal of integrative biology2016
A Causal Network Analysis of the Fatty Acid Metabolome in African-Americans Reveals a Critical Role for Palmitoleate and Margarate.
Article in Omics : a journal of integrative biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
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- Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity.Metabolomics : Official journal of the Metabolomic Society · 2024Article
- Gene signatures derived from transcriptomic-causal networks stratified colorectal cancer patients for effective targeted therapy.Research square · 2023Article
- From classical mendelian randomization to causal networks for systematic integration of multi-omics.Frontiers in genetics · 2022Review
- Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics.BMC genomics · 2019Article
- A Multi-Trait Approach Identified Genetic Variants Including a Rare Mutation in RGS3 with Impact on Abnormalities of Cardiac Structure/Function.Scientific reports · 2019Article
- Arachidonic acid as a target for treating hypertriglyceridemia reproduced by a causal network analysis and an intervention study.Metabolomics : Official journal of the Metabolomic Society · 2018Article
- A comparison of methods for inferring causal relationships between genotype and phenotype using additional biological measurements.Genetic epidemiology · 2017Article
- Article
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
Fatty acids are important sources of energy and possible predictors and etiologic factors in many common complex pathologies such as cardiovascular disease, diabetes, and certain forms of cancers. While fatty acids are thought to covary with each other, their underlying causal networks have not been fully elucidated. This study reports the identification and analysis of a statistical causal network among 15 mostly long-chain fatty acids. In an African-American population sample and using the Genome granularity-Directed Acyclic Graph (GDAG) algorithm, we determined directions or causal relationships in the fatty acid metabolome. A directed causal network was constructed that revealed 29 significant edges among the 15 nodes (p < 0.001). We report that two fatty acid metabolites, palmitoleate and margarate, which originate from dietary intake, together influence every other fatty acid in the network. On the other hand, despite its high connectivity, dihomo-linoleate did not appear to play an important role over the whole fatty acid network. These findings collectively suggest possible strategic entry points for new treatments or preventive modalities against diseases affected by fatty acid metabolites such as cardiovascular disease, diabetes, and obesity. Further studies examining the embedded substructure of the fatty acid metabolite networks in independent population samples would be timely and warranted as we move toward novel postgenomic diagnostics and therapeutics.
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