Evidence map›Paper›PMID 38556356›Full record

ArticleEnvironmental health and preventive medicine2024

A population-based urinary and plasma metabolomics study of environmental exposure to cadmium.

Yoshiki Ishibashi, Sei Harada, Yoko Eitaki, Ayako Kurihara, Suzuka Kato, Kazuyo Kuwabara, Miho Iida, Aya Hirata, Mizuki Sata, Minako Matsumoto and 10 more

Open access · goldAbstract read
In one paragraph

Article in Environmental health and preventive medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

20 authors at 1 institution in 1 country.

Yoshiki IshibashiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.ORCID http://orcid.org/0000-0003-4440-9169
Sei HaradaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Yoko EitakiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Ayako KuriharaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Suzuka KatoDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Kazuyo KuwabaraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Miho IidaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Aya HirataDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Mizuki SataDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Minako MatsumotoDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Takuma ShibukiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Tomonori OkamuraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Daisuke SugiyamaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Asako SatoInstitute for Advanced Biosciences, Keio University.
Kaori AmanoInstitute for Advanced Biosciences, Keio University.
Akiyoshi HirayamaInstitute for Advanced Biosciences, Keio University.
Masahiro SugimotoInstitute for Advanced Biosciences, Keio University.
Tomoyoshi SogaInstitute for Advanced Biosciences, Keio University.
Masaru TomitaInstitute for Advanced Biosciences, Keio University.
Toru TakebayashiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Keio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies.

methodWe analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure.

resultUrinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle).

conclusionThese results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Indexed as

CadmiumEnvironmental ExposureBiomarkersCohort StudiesFemaleHumansKidneyMaleRegression AnalysisBiomarkersCadmiumCadmiumMetabolomicsMultivariable regression modelPlasmaUrine

Identifiers

PMID38556356
PMCPMC10992994
OpenAlexW4393302534

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.