Evidence map›Paper›PMID 32160915›Full record

ArticleHuman genomics2020

Metabolomic profiling of metoprolol hypertension treatment reveals altered gut microbiota-derived urinary metabolites.

Chad N Brocker, Thomas Velenosi, Hania K Flaten, Glenn McWilliams, Kyle McDaniel, Shelby K Shelton, Jessica Saben, Kristopher W Krausz, Frank J Gonzalez, Andrew A Monte

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Human genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02293096 (Pharmacogenetic Prediction of Metoprolol Effectiveness), which is not on this map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02293096 naterminatednot on this map

Pharmacogenetic Prediction of Metoprolol Effectiveness

TypeinterventionalSponsorUniversity of Colorado, DenverRan2014 to 2017Enrolled462ConditionsHypertensionArmsmetoprolol succinate, Genotyping, CYP2D6 Phenotyping
3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 33 citations in OpenAlex.

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  13. The gut microbiome and hypertension.Nature reviews. Nephrology · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Chad N BrockerLaboratory of Metabolism, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Thomas VelenosiLaboratory of Metabolism, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Hania K FlatenDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Glenn McWilliamsDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Kyle McDanielDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Shelby K SheltonDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Jessica SabenDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Kristopher W KrauszLaboratory of Metabolism, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Frank J GonzalezLaboratory of Metabolism, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Andrew A MonteDepartment of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA. Andrew.Monte@ucdenver.edu.
University of Colorado Denver · USNational Institutes of Health · USNational Cancer Institute · US

Funding

Colorado Clinical and Translational Sciences InstituteUL1TR001082 · NCATS · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2013 to 2017
$48.0M
Xenobiotic ReceptorsZIABC005708 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GONZALEZ, FRANK J · 2009 to 2025
$16.4M
PERSONALIZING EMERGENCY/ACUTE THERAPEUTICS UTILIZING SYSTEMS BIOLOGY (PEGASUS)R35GM124939 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI MONTE, ANDREW ALBERT · 2017 to 2021
$2.1M
An Integrated Approach to Personalized MedicineK23GM110516 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI MONTE, ANDREW ALBERT · 2014 to 2016
$588k
NCATS NIH HHS NIH CTSI UL1 TR001082NCATS NIH HHS UL1 TR001082NIGMS NIH HHS K23 GM110516NIGMS NIH HHS R35 GM124939
6 · The paper itself

Abstract

introductionMetoprolol succinate is a long-acting beta-blocker prescribed for the management of hypertension (HTN) and other cardiovascular diseases. Metabolomics, the study of end-stage metabolites of upstream biologic processes, yield insight into mechanisms of drug effectiveness and safety. Our aim was to determine metabolomic profiles associated with metoprolol effectiveness for the treatment of hypertension.

methodsWe performed a prospective pragmatic trial (NCT02293096) that enrolled patients between 30 and 80 years with uncontrolled HTN. Patients were started on metoprolol succinate at a dose based upon systolic blood pressure (SBP). Urine and blood pressure measurements were collected weekly. Individuals with a 10% decline in SBP or heart rate (HR) were considered responsive. Genotype for the CYP2D6 enzyme, the primary metabolic pathway for metoprolol, was evaluated for each subject. Unbiased metabolomic analyses were performed on urine samples using UPLC-QTOF mass spectrometry.

resultsUrinary metoprolol metabolite ratios are indicative of patient CYP2D6 genotypes. Patients taking metoprolol had significantly higher urinary levels of many gut microbiota-dependent metabolites including hydroxyhippuric acid, hippuric acid, and methyluric acid. Urinary metoprolol metabolite profiles of normal metabolizer (NM) patients more closely correlate to ultra-rapid metabolizer (UM) patients than NM patients. Metabolites did not predict either 10% SBP or HR decline.

conclusionIn summary, urinary metabolites predict CYP2D6 genotype in hypertensive patients taking metoprolol. Metoprolol succinate therapy affects the microbiome-derived metabolites.

Indexed as

Gastrointestinal MicrobiomeAdultAgedAged, 80 and overAntihypertensive AgentsBacteriaBlood PressureFemaleHumansHypertensionMaleMetabolomeMetoprololMiddle AgedProspective StudiesUrinalysisAntihypertensive AgentsMetoprololCYP2D6HypertensionLisinoprilMetabolomicsMetoprolol

Identifiers

PMID32160915
PMCPMC7066769
OpenAlexW3011492247

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.