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Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine

[Image: see text] Gene products can affect the concentrations of small molecules (aka “metabolites”), and conversely, some metabolites can modulate the concentrations of gene transcripts. While many specific instances of this interplay have been revealed, a global approach to systematically uncover...

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Autores principales: Sönmez Flitman, Reyhan, Khalili, Bita, Kutalik, Zoltan, Rueedi, Rico, Brümmer, Anneke, Bergmann, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286311/
https://www.ncbi.nlm.nih.gov/pubmed/34699229
http://dx.doi.org/10.1021/acs.jproteome.1c00585
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author Sönmez Flitman, Reyhan
Khalili, Bita
Kutalik, Zoltan
Rueedi, Rico
Brümmer, Anneke
Bergmann, Sven
author_facet Sönmez Flitman, Reyhan
Khalili, Bita
Kutalik, Zoltan
Rueedi, Rico
Brümmer, Anneke
Bergmann, Sven
author_sort Sönmez Flitman, Reyhan
collection PubMed
description [Image: see text] Gene products can affect the concentrations of small molecules (aka “metabolites”), and conversely, some metabolites can modulate the concentrations of gene transcripts. While many specific instances of this interplay have been revealed, a global approach to systematically uncover human gene-metabolite interactions is still lacking. We performed a metabolome- and transcriptome-wide association study to identify genes influencing the human metabolome using untargeted metabolome features, extracted from (1)H nuclear magnetic resonance spectroscopy (NMR) of urine samples, and gene expression levels, quantified from RNA-Seq of lymphoblastoid cell lines (LCL) from 555 healthy individuals. We identified 20 study-wide significant associations corresponding to 15 genes, of which 5 associations (with 2 genes) were confirmed with follow-up NMR data. Using metabomatching, we identified the metabolites corresponding to metabolome features associated with the genes, namely, N-acetylated compounds with ALMS1 and trimethylamine (TMA) with HPS1. Finally, Mendelian randomization analysis supported a potential causal link between the expression of genes in both the ALMS1- and HPS1-loci and their associated metabolite concentrations. In the case of HPS1, we additionally observed that TMA concentration likely exhibits a reverse causal effect on HPS1 expression levels, indicating a negative feedback loop. Our study highlights how the integration of metabolomics, gene expression, and genetic data can pinpoint causal genes modulating metabolite concentrations.
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spelling pubmed-92863112022-07-16 Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine Sönmez Flitman, Reyhan Khalili, Bita Kutalik, Zoltan Rueedi, Rico Brümmer, Anneke Bergmann, Sven J Proteome Res [Image: see text] Gene products can affect the concentrations of small molecules (aka “metabolites”), and conversely, some metabolites can modulate the concentrations of gene transcripts. While many specific instances of this interplay have been revealed, a global approach to systematically uncover human gene-metabolite interactions is still lacking. We performed a metabolome- and transcriptome-wide association study to identify genes influencing the human metabolome using untargeted metabolome features, extracted from (1)H nuclear magnetic resonance spectroscopy (NMR) of urine samples, and gene expression levels, quantified from RNA-Seq of lymphoblastoid cell lines (LCL) from 555 healthy individuals. We identified 20 study-wide significant associations corresponding to 15 genes, of which 5 associations (with 2 genes) were confirmed with follow-up NMR data. Using metabomatching, we identified the metabolites corresponding to metabolome features associated with the genes, namely, N-acetylated compounds with ALMS1 and trimethylamine (TMA) with HPS1. Finally, Mendelian randomization analysis supported a potential causal link between the expression of genes in both the ALMS1- and HPS1-loci and their associated metabolite concentrations. In the case of HPS1, we additionally observed that TMA concentration likely exhibits a reverse causal effect on HPS1 expression levels, indicating a negative feedback loop. Our study highlights how the integration of metabolomics, gene expression, and genetic data can pinpoint causal genes modulating metabolite concentrations. American Chemical Society 2021-10-26 2021-11-05 /pmc/articles/PMC9286311/ /pubmed/34699229 http://dx.doi.org/10.1021/acs.jproteome.1c00585 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Sönmez Flitman, Reyhan
Khalili, Bita
Kutalik, Zoltan
Rueedi, Rico
Brümmer, Anneke
Bergmann, Sven
Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title_full Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title_fullStr Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title_full_unstemmed Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title_short Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine
title_sort untargeted metabolome- and transcriptome-wide association study suggests causal genes modulating metabolite concentrations in urine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286311/
https://www.ncbi.nlm.nih.gov/pubmed/34699229
http://dx.doi.org/10.1021/acs.jproteome.1c00585
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