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...

Descripción completa

Detalles Bibliográficos
Autores principales: Fadason, Tayaza, Schierding, William, Kolbenev, Nikolai, Liu, Jiamou, Ingram, John R., O’Sullivan, Justin M.
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