Evidence map›Paper›PMID 37468430›Full record

ReviewTrends in endocrinology and metabolism: TEM2023

An epidemiological introduction to human metabolomic investigations.

Amit D Joshi, Ali Rahnavard, Priyadarshini Kachroo, Kevin M Mendez, Wayne Lawrence, Sachelly Julián-Serrano, Xinwei Hua, Harriett Fuller, Nasa Sinnott-Armstrong, Fred K Tabung and 4 more

Abstract readReview
In one paragraph

Review in Trends in endocrinology and metabolism: TEM, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 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.

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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Uncovering the sex steroid hormone secrets in alcohol.Alcohol, clinical & experimental research · 2025
    Article
  12. Review
  13. Article
  14. Article
  15. Article
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

14 authors.

Amit D JoshiClinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
Ali RahnavardComputational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
Priyadarshini KachrooChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Kevin M MendezChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Wayne LawrenceDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Sachelly Julián-SerranoDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Public Health, University of Massachusetts Lowell, Lowell, MA, USA.
Xinwei HuaClinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA; Department of Cardiology, Peking University Third Hospital, Beijing, China.
Harriett FullerPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Nasa Sinnott-ArmstrongPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Fred K TabungThe Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, OH, USA.
Katherine H ShuttaChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Laura M RaffieldDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Burcu F DarstPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. Electronic address: bdarst@fredhutch.org.
COMETS Early Career Scientist Working Group

Funding

Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
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
Systems Biology of Airway DiseaseP01HL132825 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI DEMEO, DAWN L · 2016 to 2020
$12.6M
North Carolina Translational and Clinical Science Institute (NC TraCS) KL2KL2TR002490 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WEINBERGER, MORRIS · 2018 to 2022
$11.0M
Network Models for MetabolomicsR01LM013444 · NLM · UNIVERSITY OF MASSACHUSETTS AMHERST · PI BALASUBRAMANIAN, RAJI, SCHOLTENS, DENISE M · 2020 to 2023
$1.4M
Risk Prediction of Symptomatic Gallbladder DiseaseK01DK110267 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI JOSHI, AMIT DOLAR · 2016 to 2021
$876k
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
Methylomic and metabolomic determinants of Lung Function in AsthmaticsK99HL159234 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI KACHROO, PRIYADARSHINI · 2022 to 2023
$346k
Metabolomics of symptomatic gallstone disease in COMETSR03DK127148 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI JOSHI, AMIT DOLAR · 2021 to 2022
$252k
Intramural NIH HHS Z99 CA999999NCATS NIH HHS KL2 TR002490NCI NIH HHS R00 CA246063NHLBI NIH HHS K99 HL159234NHLBI NIH HHS P01 HL132825NHLBI NIH HHS T32 HL007427NHLBI NIH HHS U01 HL089856NIDDK NIH HHS K01 DK110267NIDDK NIH HHS R03 DK127148NLM NIH HHS R01 LM013444
6 · The paper itself

Abstract

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Indexed as

MetabolomicsHumansPhenotypeepidemiologyhigh-dimensional statistical methodsintegrative omicsmetabolitesmetabolomic epidemiologyquality control

Identifiers

PMID37468430
PMCPMC10527234

What OpenQuestion 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 OpenQuestion graph.