Cargando…
Reconstructing the blood metabolome and genotype using long-range chromatin interactions
BACKGROUND: —Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-as...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7424797/ https://www.ncbi.nlm.nih.gov/pubmed/32812909 http://dx.doi.org/10.1016/j.metop.2020.100035 |
_version_ | 1783570396849635328 |
---|---|
author | Fadason, Tayaza Schierding, William Kolbenev, Nikolai Liu, Jiamou Ingram, John R. O’Sullivan, Justin M. |
author_facet | Fadason, Tayaza Schierding, William Kolbenev, Nikolai Liu, Jiamou Ingram, John R. O’Sullivan, Justin M. |
author_sort | Fadason, Tayaza |
collection | PubMed |
description | BACKGROUND: —Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome. OBJECTIVE: —We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs. METHOD: —We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs. FINDINGS: —We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites. CONCLUSIONS: —The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels. |
format | Online Article Text |
id | pubmed-7424797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-74247972020-08-17 Reconstructing the blood metabolome and genotype using long-range chromatin interactions Fadason, Tayaza Schierding, William Kolbenev, Nikolai Liu, Jiamou Ingram, John R. O’Sullivan, Justin M. Metabol Open Original Research Paper BACKGROUND: —Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome. OBJECTIVE: —We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs. METHOD: —We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs. FINDINGS: —We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites. CONCLUSIONS: —The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels. Elsevier 2020-03-19 /pmc/articles/PMC7424797/ /pubmed/32812909 http://dx.doi.org/10.1016/j.metop.2020.100035 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Paper Fadason, Tayaza Schierding, William Kolbenev, Nikolai Liu, Jiamou Ingram, John R. O’Sullivan, Justin M. Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title | Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title_full | Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title_fullStr | Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title_full_unstemmed | Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title_short | Reconstructing the blood metabolome and genotype using long-range chromatin interactions |
title_sort | reconstructing the blood metabolome and genotype using long-range chromatin interactions |
topic | Original Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7424797/ https://www.ncbi.nlm.nih.gov/pubmed/32812909 http://dx.doi.org/10.1016/j.metop.2020.100035 |
work_keys_str_mv | AT fadasontayaza reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions AT schierdingwilliam reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions AT kolbenevnikolai reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions AT liujiamou reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions AT ingramjohnr reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions AT osullivanjustinm reconstructingthebloodmetabolomeandgenotypeusinglongrangechromatininteractions |