Genome-wide metabolite quantitative trait loci analysis (mQTL) in red blood cells from volunteer blood donors.
J Biol Chem
; 298(12): 102706, 2022 12.
Article
em En
| MEDLINE
| ID: mdl-36395887
ABSTRACT
The red blood cell (RBC)-Omics study, part of the larger NHLBI-funded Recipient Epidemiology and Donor Evaluation Study (REDS-III), aims to understand the genetic contribution to blood donor RBC characteristics. Previous work identified donor demographic, behavioral, genetic, and metabolic underpinnings to blood donation, storage, and (to a lesser extent) transfusion outcomes, but none have yet linked the genetic and metabolic bodies of work. We performed a genome-wide association (GWA) analysis using RBC-Omics study participants with generated untargeted metabolomics data to identify metabolite quantitative trait loci in RBCs. We performed GWA analyses of 382 metabolites in 243 individuals imputed using the 1000 Genomes Project phase 3 all-ancestry reference panel. Analyses were conducted using ProbABEL and adjusted for sex, age, donation center, number of whole blood donations in the past 2 years, and first 10 principal components of ancestry. Our results identified 423 independent genetic loci associated with 132 metabolites (p < 5×10-8). Potentially novel locus-metabolite associations were identified for the region encoding heme transporter FLVCR1 and choline and for lysophosphatidylcholine acetyltransferase LPCAT3 and lysophosphatidylserine 16.0, 18.0, 18.1, and 18.2; these associations are supported by published rare disease and mouse studies. We also confirmed previous metabolite GWA results for associations, including N(6)-methyl-L-lysine and protein PYROXD2 and various carnitines and transporter SLC22A16. Association between pyruvate levels and G6PD polymorphisms was validated in an independent cohort and novel murine models of G6PD deficiency (African and Mediterranean variants). We demonstrate that it is possible to perform metabolomics-scale GWA analyses with a modest, trans-ancestry sample size.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Locos de Características Quantitativas
/
Estudo de Associação Genômica Ampla
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
J Biol Chem
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos