Evidence map›Paper›PMID 39305183›Full record

ArticleAnnals of clinical and translational neurology2024

Association of multiple trace metals in scalp hair with glioma risk: the mediating role of inflammation.

Lingjun Yan, Honghai You, Huiying Wang, Chenyu Ding, Baochang He, Jing Wang, Wenhua Fang, Yuanxiang Lin, Dezhi Kang, Fa Chen

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

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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

1 citing paper in PubMed.

  1. An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026
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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.

Lingjun YanDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Honghai YouDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Huiying WangDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
Chenyu DingDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Baochang HeDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
Jing WangLaboratory Center, The Major Subject of Environment and Health of Fujian Key Universities, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
Wenhua FangDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Yuanxiang LinDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Dezhi KangDepartment of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, 350005, China.
Fa ChenDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.ORCID 0000-0002-5792-9211

Funding

Fujian Natural Science Foundation Program 2022J01232Joint Funds for the Innovation of Science and Technology of Fujian Province 2023Y9091Technology Platform Construction Project of Fujian Province 2021Y2001
6 · The paper itself

Abstract

objectiveTo explore the relationship between 35 trace metals in scalp hair and the glioma risk as well as the potential mediating roles of 27 plasma inflammatory cytokines.

methodsA case-control study involving 228 participants was performed in southeastern China. Trace metals in scalp hair were analyzed using inductively coupled plasma mass spectrometry, and multiplex cytokines were detected based on Luminex® technology. The least absolute shrinkage and selection operator (LASSO) regression in combination with four machine learning methods were used to select trace metals associated with gliomas. The joint exposure effect of trace metals was estimated using the generalized weighted quantile sum (gWQS) regression and quantile-based g-computation (qgcomp) algorithms.

resultsBoth LASSO regression and random forest algorithms identified five trace metals (gadolinium [Gd], lithium [Li], thulium [Tm], thorium [Th], and molybdenum [Mo]) associated with gliomas. After adjustments for potential confounders, Gd (odds ratio [OR] = 2.84, 95% confidence interval [CI]: 1.89-4.43) and Li (OR = 1.77, 95% CI: 1.04-3.02) concentrations were positively associated with glioma risk, while Tm (OR = 0.36, 95% CI: 0.17-0.73) and Th (OR = 0.45, 95% CI: 0.28-0.71) exhibited inverse associations. Both gWQS and qgcomp algorithms showed Gd contributed most to the mixture effect. Moreover, there was a significant interaction between Gd and Tm or Th on glioma risk (p < 0.05). Notably, granulocyte-macrophage colony-stimulating factor (GM-CSF) mediated the association between Gd exposure and glioma risk by 25.75%.

interpretationThese findings suggest potential associations of certain trace metals, especially for Gd, with glioma risk, and may provide new insights into the mechanisms underlying from an inflammatory response perspective.

Indexed as

Brain NeoplasmsGliomaHairScalpTrace ElementsAdultCase-Control StudiesChinaCytokinesFemaleHumansInflammationMaleMiddle AgedCytokinesTrace Elements

Identifiers

PMID39305183
PMCPMC11572748

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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.