Imperial College London
Alternate

DrIsabelGarcia Perez

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Senior Lecturer in Precision and Systems Medicine
 
 
 
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Contact

 

i.garcia-perez

 
 
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Location

 

101Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Posma:2021:10.1097/01.hjh.0000745100.86512.60,
author = {Posma, JM and Stamler, J and Garcia-Perez, I and Chan, Q and Wijeyesekera, A and Daviglus, M and Van, Horn L and Holmes, E and Nicholson, J and Elliott, P},
doi = {10.1097/01.hjh.0000745100.86512.60},
pages = {E70--E70},
publisher = {Lippincott, Williams & Wilkins},
title = {Urinary metabolic phenotype of blood pressure},
url = {http://dx.doi.org/10.1097/01.hjh.0000745100.86512.60},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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 sub
AU  - Posma,JM
AU  - Stamler,J
AU  - Garcia-Perez,I
AU  - Chan,Q
AU  - Wijeyesekera,A
AU  - Daviglus,M
AU  - Van,Horn L
AU  - Holmes,E
AU  - Nicholson,J
AU  - Elliott,P
DO  - 10.1097/01.hjh.0000745100.86512.60
EP  - 70
PB  - Lippincott, Williams & Wilkins
PY  - 2021///
SN  - 0263-6352
SP  - 70
TI  - Urinary metabolic phenotype of blood pressure
UR  - http://dx.doi.org/10.1097/01.hjh.0000745100.86512.60
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000672599900184&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://journals.lww.com/jhypertension/Abstract/2021/04001/URINARY_METABOLIC_PHENOTYPE_OF_BLOOD_PRESSURE.186.aspx
UR  - http://hdl.handle.net/10044/1/90713
ER  -
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