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

Atsuko MiyakeSei HaradaDaisuke SugiyamaMinako MatsumotoAya HirataNaoko MiyagawaRyota TokiShun EdagawaKazuyo KuwabaraTomonori OkamuraAsako SatoKaori AmanoAkiyoshi HirayamaMasahiro SugimotoTomoyoshi SogaMasaru TomitaKazuharu ArakawaToru TakebayashiMiho Iida
Published in: Metabolites (2024)
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.
Keyphrases
  • ms ms
  • quality control
  • cross sectional
  • electronic health record
  • big data
  • type diabetes
  • metabolic syndrome
  • skeletal muscle
  • pregnant women
  • middle aged
  • data analysis