Evidence map›Paper›PMID 38651675›Full record

ArticleInternational journal of cancer2024

A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study.

Mohammad L Rahman, Xiao-Ou Shu, Dean P Jones, Wei Hu, Bu-Tian Ji, Batel Blechter, Jason Y Y Wong, Qiuyin Cai, Gong Yang, Yu-Tang Gao and 4 more

Open access · greenAbstract read
In one paragraph

Article in International journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. A seven-year longitudinal study of the Alzheimer's disease blood metabolome.medRxiv : the preprint server for health sciences · 2025
    Article
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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

14 authors at 4 institutions in 2 countries.

Mohammad L RahmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0001-8322-0495
Xiao-Ou ShuDivision of Epidemiology, Vanderbilt University, Nashville, Tennessee, USA.
Dean P JonesClinical Biomarkers Laboratory, Department of Medicine, Emory University, Atlanta, Georgia, USA.
Wei HuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Bu-Tian JiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Batel BlechterDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0001-7610-2554
Jason Y Y WongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0003-2820-2133
Qiuyin CaiDivision of Epidemiology, Vanderbilt University, Nashville, Tennessee, USA.
Gong YangDivision of Epidemiology, Vanderbilt University, Nashville, Tennessee, USA.
Yu-Tang GaoDepartment of Epidemiology, Shanghai Cancer Institute, Shanghai, China.
Wei ZhengDivision of Epidemiology, Vanderbilt University, Nashville, Tennessee, USA.
Nathaniel RothmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0002-0866-9943
Douglas WalkerDivision of Environmental Health, School of Public Health, Emory University, Atlanta, Georgia, USA.
Qing LanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
National Cancer Institute · USVanderbilt University · USEmory University · USShanghai Cancer Institute · CN

Funding

National Metabolomics Data Repository - nextgen Metabolomics WorkbenchU2CDK119886 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2018 to 2021
$12.7M
Southern Environmental Health StudyUH3CA265846 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Martha J. Shrubsole, Wei Zheng · 2023 to 2026
$9.8M
Occupational and Environmental Determinants of Cancer among Women and MinoritiesZIACP010123 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI HOFMANN, JONATHAN · 2009 to 2025
$8.3M
Shanghai Womens Health StudyUM1CA182910 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2014 to 2018
$5.9M
Biological mechanisms underlying the relationships between environmental exposures and risk of respiratory and cardiovascular diseasesZIAHL006285 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI WONG, JASON · 2023 to 2025
$3.8M
Biomedical Data Commons Workbench (BDCW)OT2OD030544 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2020 to 2024
$3.2M
Southern Environmental Health StudyUG3CA265846 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHRUBSOLE, MARTHA J., ZHENG, WEI · 2021 to 2022
$2.3M
NCI NIH HHS UG3 CA265846NCI NIH HHS UH3 CA265846NCI NIH HHS UM1 CA182910NIDDK NIH HHS U2C DK119886NIH HHS OT2 OD030544NIH HHS OT2-OD030544NIH HHS U2C-DK119886NIH HHS UG3 CA265846NIH HHS UM1 CA182910
6 · The paper itself

Abstract

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.

Indexed as

Lung NeoplasmsMetabolomicsAgedBiomarkers, TumorCase-Control StudiesChinaFemaleHumansMetabolic Networks and PathwaysMiddle AgedNon-SmokersProspective StudiesRisk FactorsSmokingWomen's HealthBiomarkers, Tumorlung cancermetabolomicsnetwork analysisnever‐smokersoxidative stress

Identifiers

PMID38651675
PMCPMC11284831
OpenAlexW4395039333

What OpenQuestion holds

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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.