Urinary metabolic phenotype of blood pressure
File(s) ESH-ISH 2020_abstract_BPmetabolites_PosmaJM_pe.pdf (180.69 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Objective:
Metabolic phenotyping (metabolomics) captures systems-level information on metabolic processes by simultaneously measuring hundreds of metabolites using spectroscopic techniques. Concentrations of these metabolites are affected by genetic (host, microbiome), environmental and dietary factors and may provide insights into biochemical pathways underlying raised blood pressure (BP) in populations.
Design and method:
Two separate, timed 24hr urine specimens were obtained from 2,031 women and men, aged 40–59, from 8 USA population samples in the INTERMAP Study. Proton Nuclear Magnetic Resonance (1H NMR) was used to characterize a urinary metabolic signature; this was unaffected by diurnal variability and sampling time as it captures end-products of metabolism over a 24hr period. Demographic, population, medical, lifestyle and anthropometric factors were accounted for in regression models to define a urinary metabolic phenotype associated with BP.
Results:
29 structurally identified urinary metabolites covaried with systolic BP (SBP), after adjustment for demographic variables, and 18 metabolites with diastolic BP (DBP), with 16 metabolites overlapping between SBP and DBP. These included metabolites related to energy metabolism, renal function, diet and gut microbiota. After adjustment for medical and lifestyle covariates, 22/14 metabolites remained associated with SBP/DBP. Joint covariate-metabolite penalized regression models identified Body Mass Index, age and family history as most important contributors, with 14 metabolites, including gut microbial co-metabolites, also included in the model. Metabolites were mapped in a symbiotic metabolic reaction network, that includes reactions mediated by 3,344 commensal gut microbial species, to highlight affected pathways (Figure). Significant single nucleotide polymorphisms (SNPs) from genome-wide association studies on cardiometabolic risk factors were mapped to genes in this network. This revealed multiple subnetworks of gene-metabolite pairs related to BP and related cardiometabolic factors and includes 54 SNPs directly related to reactions in the network. These 54 SNPs were then used as instrumental variables to test for possible causative metabolite-BP associations in an external cohort (Airwave Study).
Metabolic phenotyping (metabolomics) captures systems-level information on metabolic processes by simultaneously measuring hundreds of metabolites using spectroscopic techniques. Concentrations of these metabolites are affected by genetic (host, microbiome), environmental and dietary factors and may provide insights into biochemical pathways underlying raised blood pressure (BP) in populations.
Design and method:
Two separate, timed 24hr urine specimens were obtained from 2,031 women and men, aged 40–59, from 8 USA population samples in the INTERMAP Study. Proton Nuclear Magnetic Resonance (1H NMR) was used to characterize a urinary metabolic signature; this was unaffected by diurnal variability and sampling time as it captures end-products of metabolism over a 24hr period. Demographic, population, medical, lifestyle and anthropometric factors were accounted for in regression models to define a urinary metabolic phenotype associated with BP.
Results:
29 structurally identified urinary metabolites covaried with systolic BP (SBP), after adjustment for demographic variables, and 18 metabolites with diastolic BP (DBP), with 16 metabolites overlapping between SBP and DBP. These included metabolites related to energy metabolism, renal function, diet and gut microbiota. After adjustment for medical and lifestyle covariates, 22/14 metabolites remained associated with SBP/DBP. Joint covariate-metabolite penalized regression models identified Body Mass Index, age and family history as most important contributors, with 14 metabolites, including gut microbial co-metabolites, also included in the model. Metabolites were mapped in a symbiotic metabolic reaction network, that includes reactions mediated by 3,344 commensal gut microbial species, to highlight affected pathways (Figure). Significant single nucleotide polymorphisms (SNPs) from genome-wide association studies on cardiometabolic risk factors were mapped to genes in this network. This revealed multiple subnetworks of gene-metabolite pairs related to BP and related cardiometabolic factors and includes 54 SNPs directly related to reactions in the network. These 54 SNPs were then used as instrumental variables to test for possible causative metabolite-BP associations in an external cohort (Airwave Study).
Date Issued
2021-04-01
Date Acceptance
2021-04-01
Citation
Journal of Hypertension, 2021, 39, pp.E70-E70
ISSN
0263-6352
Publisher
Lippincott, Williams & Wilkins
Start Page
E70
End Page
E70
Journal / Book Title
Journal of Hypertension
Volume
39
Copyright Statement
© 2021 Wolters Kluwer Health, Inc. All rights reserved.
Sponsor
National Institutes of Health
National Institutes of Health
National Institutes of Health
National Institute for Health Research
Medical Research Council (MRC)
Medical Research Council
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000672599900184&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
0600 370 D330 1362
60024563 ICL
60045948 ICSTM
3R01HL135486-02S1
MR/S004033/1
MR/S004033/1
Source
19TH INTERNATIONAL SHR SYMPOSIUM SHR
Subjects
Science & Technology
Life Sciences & Biomedicine
Peripheral Vascular Disease
Cardiovascular System & Cardiology
Publication Status
Published
Start Date
2021-04-11
Finish Date
2021-04-14
Coverage Spatial
Online event
Date Publish Online
2021-04
