Evidence map›Paper›PMID 38276312›Full record

ArticleMetabolites2024

Reliability of Time-Series Plasma Metabolome Data over 6 Years in a Large-Scale Cohort Study.

Atsuko Miyake, Sei Harada, Daisuke Sugiyama, Minako Matsumoto, Aya Hirata, Naoko Miyagawa, Ryota Toki, Shun Edagawa, Kazuyo Kuwabara, Tomonori Okamura and 9 more

Abstract read
In one paragraph

Article in Metabolites, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

19 authors.

Atsuko MiyakeDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.ORCID 0000-0003-1391-4576
Sei HaradaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Daisuke SugiyamaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Minako MatsumotoDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Aya HirataDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Naoko MiyagawaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.ORCID 0000-0002-9148-1078
Ryota TokiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Shun EdagawaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Kazuyo KuwabaraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Tomonori OkamuraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.ORCID 0000-0003-0488-0351
Asako SatoInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.
Kaori AmanoInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.
Akiyoshi HirayamaInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.ORCID 0000-0002-0440-6820
Masahiro SugimotoInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.ORCID 0000-0003-3316-2543
Tomoyoshi SogaInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.ORCID 0000-0001-9502-2509
Masaru TomitaInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.
Kazuharu ArakawaInstitute for Advanced Biosciences, Keio University, Yamagata, Tsuruoka 997-0052, Japan.ORCID 0000-0002-2893-4919
Toru TakebayashiDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.
Miho IidaDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku, Tokyo 160-8582, Japan.

Funding

City of Tsuruoka NAJapan Agency for Medical Research and Development JP18059131Japan Society for the Promotion of Science 15H04778Japan Society for the Promotion of Science 15K19231Japan Society for the Promotion of Science 16H05249Japan Society for the Promotion of Science 16H06277Japan Society for the Promotion of Science 16K19259Japan Society for the Promotion of Science 17K09150Japan Society for the Promotion of Science 17K19838Japan Society for the Promotion of Science 18H04079Japan Society for the Promotion of Science 18K17394Japan Society for the Promotion of Science 18KT0074Japan Society for the Promotion of Science 19K10652Japan Society for the Promotion of Science 19K10669Japan Society for the Promotion of Science 19K19416Japan Society for the Promotion of Science 19K19441Japan Society for the Promotion of Science 19K21458Japan Society for the Promotion of Science 21H04854Japan Society for the Promotion of Science 21K17275Japan Society for the Promotion of Science 22H03351Japan Society for the Promotion of Science 22H03353Japan Society for the Promotion of Science 22H03356Japan Society for the Promotion of Science 22K10592Japan Society for the Promotion of Science JP24390168Japan Society for the Promotion of Science JP25670303Japan Society for the Promotion of Science JP26670319Japan Society for the Promotion of Science JP26670340Japan Society for the Promotion of Science JP26860421Japan Society for the Promotion of Science JP26893258Ministry of Health, Labor and Welfare, Health and Labor Sciences research grants H23-Junkankitou [Seishuu]-Ippan-005; H26-Junkankitou [Seisaku]-Ippan-001; H29-Junkankitou-Ippan-003, 20FA1002 and 23FA1006Yamagata Prefectural Government NA
6 · The paper itself

Abstract

Studies examining long-term longitudinal metabolomic data and their reliability in large-scale populations are limited. Therefore, we aimed to evaluate the reliability of repeated measurements of plasma metabolites in a prospective cohort setting and to explore intra-individual concentration changes at three time points over a 6-year period. The study participants included 2999 individuals (1317 men and 1682 women) from the Tsuruoka Metabolomics Cohort Study, who participated in all three surveys-at baseline, 3 years, and 6 years. In each survey, 94 plasma metabolites were quantified for each individual and quality control (QC) sample. The coefficients of variation of QC, intraclass correlation coefficients, and change rates of QC were calculated for each metabolite, and their reliability was classified into three categories: excellent, fair to good, and poor. Seventy-six percent (71/94) of metabolites were classified as fair to good or better. Of the 39 metabolites grouped as excellent, 29 (74%) in men and 26 (67%) in women showed significant intra-individual changes over 6 years. Overall, our study demonstrated a high degree of reliability for repeated metabolome measurements. Many highly reliable metabolites showed significant changes over the 6-year period, suggesting that repeated longitudinal metabolome measurements are useful for epidemiological studies.

Indexed as

capillary electrophoresis–mass spectrometrycohort studieslongitudinal datametabolomicsreliabilityrepeated measurementstime-series data

Identifiers

PMID38276312
PMCPMC10819202

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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.