{"title":"Plasma metabolomics dataset of race-walking athletes illuminating systemic metabolic reaction of exercise.","authors":"Yeheng He, Yunshu Zhang, Jinwen Lai, Shurong Ma, Peiyuan Yin, Zeming Wu, Jian Zhou","doi":"10.1038/s41597-025-04751-0","DOIUrl":null,"url":null,"abstract":"<p><p>This study investigates the metabolic changes induced by endurance exercise, specifically race walking, in a cohort of 19 athletes. Blood samples were collected at four time points: pre-exercise (REST), immediately post-exercise (STAT), 3 hours into recovery (REC3), and 22 hours post-exercise (REC22). A total of 859 metabolites were identified through the untargeted method, and 465 metabolites and 411 lipids were identified through the targeted methods. Rigorous quality control measures were implemented throughout the study to ensure data reliability. The comprehensive dataset, which is publicly available on the Metabolomics Workbench website, offers valuable insights into the systemic metabolic shifts triggered by endurance exercise. This resource may prove instrumental in uncovering biomarkers associated with athletic performance, providing a foundation for future research in exercise physiology and metabolic health.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"448"},"PeriodicalIF":5.8000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920029/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-04751-0","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
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Abstract
This study investigates the metabolic changes induced by endurance exercise, specifically race walking, in a cohort of 19 athletes. Blood samples were collected at four time points: pre-exercise (REST), immediately post-exercise (STAT), 3 hours into recovery (REC3), and 22 hours post-exercise (REC22). A total of 859 metabolites were identified through the untargeted method, and 465 metabolites and 411 lipids were identified through the targeted methods. Rigorous quality control measures were implemented throughout the study to ensure data reliability. The comprehensive dataset, which is publicly available on the Metabolomics Workbench website, offers valuable insights into the systemic metabolic shifts triggered by endurance exercise. This resource may prove instrumental in uncovering biomarkers associated with athletic performance, providing a foundation for future research in exercise physiology and metabolic health.
期刊介绍：
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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