Evidence map›Paper›PMID 37872285›Full record

ReviewNature metabolism2023

Metabolomic epidemiology offers insights into disease aetiology.

Harriett Fuller, Yiwen Zhu, Jayna Nicholas, Haley A Chatelaine, Emily M Drzymalla, Afrand K Sarvestani, Sachelly Julián-Serrano, Usman A Tahir, Nasa Sinnott-Armstrong, Laura M Raffield and 4 more

Erratum issuedOpen access · greenAbstract readReview
In one paragraph

Review in Nature metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
7.5field-weighted citation impact, top 2% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 47 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 9 institutions in 2 countries.

Harriett FullerPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0001-8381-519X
Yiwen ZhuDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Jayna NicholasDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Haley A ChatelaineNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7086-4918
Emily M DrzymallaDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Afrand K SarvestaniComputational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
Sachelly Julián-SerranoDepartment of Public Health, University of Massachusetts Lowell, Lowell, MA, USA.
Usman A TahirDepartment of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA.ORCID 0000-0002-3657-6082
Nasa Sinnott-ArmstrongPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Laura M RaffieldDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Ali RahnavardComputational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.ORCID 0000-0002-9710-0248
Xinwei HuaDepartment of Cardiology, Peking University Third Hospital, Beijing, China.ORCID 0000-0003-2114-2975
Katherine H ShuttaChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-0402-3771
Burcu F DarstPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA. bdarst@fredhutch.org.ORCID 0000-0002-6205-4632
Fred Hutch Cancer Center · USUniversity of North Carolina at Chapel Hill · USMilken Institute · USBeth Israel Deaconess Medical Center · USBrigham and Women's Hospital · USHarvard University · USNational Institutes of Health · USPeking University · CNUniversity of Massachusetts Lowell · US

Funding

SYSTEMS APPROACHES TO THE EPIDEMIOLOGY, GENETICS AND GENOMICS OF LUNG DISEASEST32HL007427 · NHLBI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI DAWN L DEMEO, Edwin K Silverman · 1985 to 2026
$13.6M
Informatics Research CoreZICTR000410 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI MATHÉ, EWY · 2021 to 2025
$11.7M
Integrating Genomics and Metabolomics to Develop Predictive Models of Prostate Cancer in Multiethnic MenR00CA246063 · NCI · FRED HUTCHINSON CANCER CENTER · PI DARST, BURCU FRANCES · 2022 to 2024
$830k
The Role of SECTM1 in Monocyte Biology and AtherosclerosisK08HL161445 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Usman A. Tahir · 2022 to 2026
$822k
Intramural NIH HHS ZIC TR000410NCI NIH HHS R00 CA246063NHLBI NIH HHS K08 HL161445NHLBI NIH HHS T32 HL007427
6 · The paper itself

Abstract

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

Indexed as

MetabolomicsPrecision MedicineDisease ProgressionHumansPhenotypePrognosis

Identifiers

PMID37872285
PMCPMC11164316
OpenAlexW4387873878

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.