ArticlePloS one2015
Multi-Organ Contribution to the Metabolic Plasma Profile Using Hierarchical Modelling.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 23 citations in OpenAlex.
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- Simulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies.Scientific reports · 2025Article
- Impact of the delay in cryopreservation timing during biobanking procedures on human liver tissue metabolomics.PloS one · 2024Article
- Guanidine acetic acid supplementation altered plasma and tissue free amino acid profiles in finishing pigs.Porcine health management · 2022Article
- Increased plasma disequilibrium between pro- and anti-oxidants during the early phase resuscitation after cardiac arrest is associated with increased levels of oxidative stress end-products.Molecular medicine (Cambridge, Mass.) · 2021Article
- Angiotensin AT2 Receptor is Anti-inflammatory and Reno-Protective in Lipopolysaccharide Mice Model: Role of IL-10.Frontiers in pharmacology · 2021Article
- Article
- Reconstructing the blood metabolome and genotype using long-range chromatin interactions.Metabolism open · 2020Article
- Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome.Journal of inherited metabolic disease · 2018Review
- Dietary Probiotic Effect ofFrontiers in microbiology · 2018Article
- Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.International journal of molecular sciences · 2016Review
- Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era.International journal of molecular sciences · 2016Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hierarchical modelling was applied in order to identify the organs that contribute to the levels of metabolites in plasma. Plasma and organ samples from gut, kidney, liver, muscle and pancreas were obtained from mice. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC TOF-MS) at the Swedish Metabolomics centre, Umeå University, Sweden. The multivariate analysis was performed by means of principal component analysis (PCA) and orthogonal projections to latent structures (OPLS). The main goal of this study was to investigate how each organ contributes to the metabolic plasma profile. This was performed using hierarchical modelling. Each organ was found to have a unique metabolic profile. The hierarchical modelling showed that the gut, kidney and liver demonstrated the greatest contribution to the metabolic pattern of plasma. For example, we found that metabolites were absorbed in the gut and transported to the plasma. The kidneys excrete branched chain amino acids (BCAAs) and fatty acids are transported in the plasma to the muscles and liver. Lactic acid was also found to be transported from the pancreas to plasma. The results indicated that hierarchical modelling can be utilized to identify the organ contribution of unknown metabolites to the metabolic profile of plasma.
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