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Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform

Physiological status and pathological changes in an individual can be captured by metabolic state that reflects the influence of both genetic variants and environmental factors such as diet, lifestyle and gut microbiome. The totality of environmental exposure throughout lifetime – i.e., exposome – i...

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Autores principales: Kong, Sek Won, Hernandez-Ferrer, Carles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6910716/
https://www.ncbi.nlm.nih.gov/pubmed/31797630
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author Kong, Sek Won
Hernandez-Ferrer, Carles
author_facet Kong, Sek Won
Hernandez-Ferrer, Carles
author_sort Kong, Sek Won
collection PubMed
description Physiological status and pathological changes in an individual can be captured by metabolic state that reflects the influence of both genetic variants and environmental factors such as diet, lifestyle and gut microbiome. The totality of environmental exposure throughout lifetime – i.e., exposome – is difficult to measure with current technologies. However, targeted measurement of exogenous chemicals and untargeted profiling of endogenous metabolites have been widely used to discover biomarkers of pathophysiologic changes and to understand functional impacts of genetic variants. To investigate the coverage of chemical space and interindividual variation related to demographic and pathological conditions, we profiled 169 plasma samples using an untargeted metabolomics platform. On average, 1,009 metabolites were quantified in each individual (range 906 – 1,038) out of 1,244 total chemical compounds detected in our cohort. Of note, age was positively correlated with the total number of detected metabolites in both males and females. Using the robust Q(n) estimator, we found metabolite outliers in each sample (mean 22, range from 7 to 86). A total of 50 metabolites were outliers in a patient with phenylketonuria including the ones known for phenylalanine pathway suggesting multiple metabolic pathways perturbed in this patient. The largest number of outliers (N=86) was found in a 5-year-old boy with alpha-1-antitrypsin deficiency who were waiting for liver transplantation due to cirrhosis. Xenobiotics including drugs, diets and environmental chemicals were significantly correlated with diverse endogenous metabolites and the use of antibiotics significantly changed gut microbial products detected in host circulation. Several challenges such as annotation of features, reference range and variance for each feature per age group and gender, and population scale reference datasets need to be addressed; however, untargeted metabolomics could be immediately deployed as a biomarker discovery platform and to evaluate the impact of genomic variants and exposures on metabolic pathways for some diseases.
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spelling pubmed-69107162020-01-01 Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform Kong, Sek Won Hernandez-Ferrer, Carles Pac Symp Biocomput Article Physiological status and pathological changes in an individual can be captured by metabolic state that reflects the influence of both genetic variants and environmental factors such as diet, lifestyle and gut microbiome. The totality of environmental exposure throughout lifetime – i.e., exposome – is difficult to measure with current technologies. However, targeted measurement of exogenous chemicals and untargeted profiling of endogenous metabolites have been widely used to discover biomarkers of pathophysiologic changes and to understand functional impacts of genetic variants. To investigate the coverage of chemical space and interindividual variation related to demographic and pathological conditions, we profiled 169 plasma samples using an untargeted metabolomics platform. On average, 1,009 metabolites were quantified in each individual (range 906 – 1,038) out of 1,244 total chemical compounds detected in our cohort. Of note, age was positively correlated with the total number of detected metabolites in both males and females. Using the robust Q(n) estimator, we found metabolite outliers in each sample (mean 22, range from 7 to 86). A total of 50 metabolites were outliers in a patient with phenylketonuria including the ones known for phenylalanine pathway suggesting multiple metabolic pathways perturbed in this patient. The largest number of outliers (N=86) was found in a 5-year-old boy with alpha-1-antitrypsin deficiency who were waiting for liver transplantation due to cirrhosis. Xenobiotics including drugs, diets and environmental chemicals were significantly correlated with diverse endogenous metabolites and the use of antibiotics significantly changed gut microbial products detected in host circulation. Several challenges such as annotation of features, reference range and variance for each feature per age group and gender, and population scale reference datasets need to be addressed; however, untargeted metabolomics could be immediately deployed as a biomarker discovery platform and to evaluate the impact of genomic variants and exposures on metabolic pathways for some diseases. 2020 /pmc/articles/PMC6910716/ /pubmed/31797630 Text en http://creativecommons.org/licenses/by-nc/4.0/ Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License.
spellingShingle Article
Kong, Sek Won
Hernandez-Ferrer, Carles
Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title_full Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title_fullStr Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title_full_unstemmed Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title_short Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
title_sort assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6910716/
https://www.ncbi.nlm.nih.gov/pubmed/31797630
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