Evidence map›Paper›PMID 29346414›Full record

ArticlePloS one2018

Reliability of plasma polar metabolite concentrations in a large-scale cohort study using capillary electrophoresis-mass spectrometry.

Sei Harada, Akiyoshi Hirayama, Queenie Chan, Ayako Kurihara, Kota Fukai, Miho Iida, Suzuka Kato, Daisuke Sugiyama, Kazuyo Kuwabara, Ayano Takeuchi and 10 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

38 citing papers in PubMed, 72 citations in OpenAlex.

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  18. Chemotherapy-Induced Peripheral Neuropathy.Handbook of experimental pharmacology · 2023
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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 2 institutions in 2 countries.

Sei HaradaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.ORCID 0000-0003-2666-4932
Akiyoshi HirayamaInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Queenie ChanDepartment of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom.
Ayako KuriharaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Kota FukaiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Miho IidaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Suzuka KatoDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Daisuke SugiyamaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Kazuyo KuwabaraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Ayano TakeuchiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Miki AkiyamaInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Tomonori OkamuraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Timothy M D EbbelsMRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom.
Paul ElliottDepartment of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom.
Masaru TomitaInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Asako SatoInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Chizuru SuzukiInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Masahiro SugimotoInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Tomoyoshi SogaInstitute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.
Toru TakebayashiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Keio University · JPImperial College London · GB

Funding

Medical Research Council MR/L01341X/1
6 · The paper itself

Abstract

backgroundCohort studies with metabolomics data are becoming more widespread, however, large-scale studies involving 10,000s of participants are still limited, especially in Asian populations. Therefore, we started the Tsuruoka Metabolomics Cohort Study enrolling 11,002 community-dwelling adults in Japan, and using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry. The CE-MS method is highly amenable to absolute quantification of polar metabolites, however, its reliability for large-scale measurement is unclear. The aim of this study is to examine reproducibility and validity of large-scale CE-MS measurements. In addition, the study presents absolute concentrations of polar metabolites in human plasma, which can be used in future as reference ranges in a Japanese population.

methodsMetabolomic profiling of 8,413 fasting plasma samples were completed using CE-MS, and 94 polar metabolites were structurally identified and quantified. Quality control (QC) samples were injected every ten samples and assessed throughout the analysis. Inter- and intra-batch coefficients of variation of QC and participant samples, and technical intraclass correlation coefficients were estimated. Passing-Bablok regression of plasma concentrations by CE-MS on serum concentrations by standard clinical chemistry assays was conducted for creatinine and uric acid. RESULTS AND

conclusionsIn QC samples, coefficient of variation was less than 20% for 64 metabolites, and less than 30% for 80 metabolites out of the 94 metabolites. Inter-batch coefficient of variation was less than 20% for 81 metabolites. Estimated technical intraclass correlation coefficient was above 0.75 for 67 metabolites. The slope of Passing-Bablok regression was estimated as 0.97 (95% confidence interval: 0.95, 0.98) for creatinine and 0.95 (0.92, 0.96) for uric acid. Compared to published data from other large cohort measurement platforms, reproducibility of metabolites common to the platforms was similar to or better than in the other studies. These results show that our CE-MS platform is suitable for conducting large-scale epidemiological studies.

Indexed as

AdultAgedAnalysis of VarianceAsian PeopleBiomarkersCohort StudiesElectrophoresis, CapillaryFemaleHumansJapanMaleMass SpectrometryMetabolomeMetabolomicsMiddle AgedPlasmaBiomarkers

Identifiers

PMID29346414
PMCPMC5773198
OpenAlexW2786378174

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.