Evidence map›Paper›PMID 27642271›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society

Metabolomics enables precision medicine: "A White Paper, Community Perspective".

Richard D Beger, Warwick Dunn, Michael A Schmidt, Steven S Gross, Jennifer A Kirwan, Marta Cascante, Lorraine Brennan, David S Wishart, Matej Oresic, Thomas Hankemeier and 9 more

Registry-linked trialAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03736993 (Towards Better Therapy for Resectable Lung Cancer), which is not on this map. Cited by 300 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
300citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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.

NCT03736993 nacompletednot on this map

Towards Better Therapy for Resectable Lung Cancer: Metabolomics Predict Therapy Response

TypeinterventionalSponsorHasselt UniversityRan2018 to 2022Enrolled160ConditionsNSCLC, Stage IIIAArmsAdditional blood sampling
3 · Its place in the literature

Who cites it

300 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Periodontal disease metabolomics signatures from different biofluids: a systematic review.Metabolomics : Official journal of the Metabolomic Society · 2022
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240 more citing papers are in PubMed but not listed here.

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

19 authors.

Richard D BegerDivision of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079 USA.
Warwick DunnSchool of Biosciences, Phenome Centre Birmingham and Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Edgbaston, Birmingham, B15 2TT UK.
Michael A SchmidtAdvanced Pattern Analysis and Countermeasures Group, Research Innovation Center, Colorado State University, Fort Collins, CO 80521 USA.
Steven S GrossDepartment of Pharmacology, Weill Cornell Medical College, New York, NY 10021 USA.
Jennifer A KirwanSchool of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK.
Marta CascanteDepartment of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Av Diagonal 643, 08028 Barcelona, Spain ; Institute of Biomedicine of Universitat de Barcelona (IBUB) and CSIC-Associated Unit, Barcelona, Spain.
Lorraine BrennanUCD Institute of Food and Health, UCD, Belfield, Dublin Ireland.
David S WishartDepartments of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB Canada.
Matej OresicTurku Centre for Biotechnology, University of Turku, Turku, Finland.
Thomas HankemeierDivision of Analytical Biosciences and Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University & Netherlands Metabolomics Centre, Leiden, The Netherlands.
David I BroadhurstSchool of Science, Edith Cowan University, Perth, Australia.
Andrew N LaneCenter for Environmental Systems Biochemistry, Department Toxicology and Cancer Biology, Markey Cancer Center, Lexington, KY USA.
Karsten SuhreDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Doha, Qatar.
Gabi KastenmüllerInstitute of Bioinformatics and Systems Biology, Helmholtz Center Munich, Oberschleißheim, Germany.
Susan J SumnerDiscovery Sciences, RTI International, Research Triangle Park, Durham, NC USA.
Ines ThieleUniversity of Luxembourg, Luxembourg Centre for Systems Biomedicine, Campus Belval, Esch-Sur-Alzette, Luxembourg.
Oliver FiehnWest Coast Metabolomics Center, UC Davis, Davis, CA USA ; Biochemistry Department, King Abdulaziz University, Jeddah, Saudi Arabia.
Rima Kaddurah-DaoukPsychiatry and Behavioral Sciences, Duke Internal Medicine and Duke Institute for Brain Sciences and Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Box 3903, Durham, NC 27710 USA.
for “Precision Medicine and Pharmacometabolomics Task Group”-Metabolomics Society Initiative

Funding

SAMPLE COREU24DK097215 · NIDDK · UNIVERSITY OF KENTUCKY · PI FAN, TERESA WHEI-MEI, HIGASHI, RICHARD M · 2013 to 2017
$8.7M
Metabolic Signatures Underlying Vascular Risk Factors for Alzheimer-type DementiasRF1AG051550 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KLING, MITCHEL ALLAN · 2015 to 2016
$6.3M
Metabolomics Network for Drug Response PhenotypeRC2GM092729 · NIGMS · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F · 2009 to 2010
$4.5M
Metabolic Networks and Pathways in Alzheimer's DiseaseR01AG046171 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F · 2014 to 2017
$4.4M
Diabetic Vasculopathy and Mitochondrial eNOSR37HL087062 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GROSS, STEVEN S · 2007 to 2016
$4.2M
Metabolomics Network for Drug Response PhenotypeR24GM078233 · NIGMS · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F · 2007 to 2010
$2.1M
Medical Research Council MR/M009157/1NHLBI NIH HHS R37 HL087062NIA NIH HHS R01 AG046171NIA NIH HHS RF1 AG051550NIDDK NIH HHS U24 DK097215NIGMS NIH HHS R24 GM078233NIGMS NIH HHS RC2 GM092729
6 · The paper itself

Abstract

introduction background to metabolomicsMetabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. OBJECTIVES OF WHITE PAPER—EXPECTED TREATMENT OUTCOMES AND METABOLOMICS ENABLING TOOL FOR PRECISION MEDICINE: We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. CONCLUSIONS KEY SCIENTIFIC CONCEPTS AND RECOMMENDATIONS FOR PRECISION MEDICINE: Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.

Indexed as

MetabolomicsMetabonomicsPersonalized medicinePharmacometabolomicsPharmacometabonomicsPrecision medicine

Identifiers

PMID27642271
PMCPMC5009152

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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 OpenQuestion graph.