{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:59:43Z","timestamp":1790830783407,"version":"4.1.0"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Physiol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Chronic exposure to cold environments may impose distinct metabolic demands that are relevant to physical performance; however, the metabolic characteristics associated with physical performance in individuals living in cold environments remain incompletely understood. We aimed to characterize serum metabolomic profiles associated with differences in physical performance among healthy adults residing in a cold region.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Among 178 healthy males residing in a cold-region environment, 141 participants with available serum metabolomics data were included and stratified according to 3,000-meter running performance into Good (\u226414 minutes 13 seconds, n = 76) and Poor (&amp;gt;14 minutes 13 seconds, n = 65) groups. Fasting serum samples underwent untargeted ultra-performance liquid chromatography\u2013tandem mass spectrometry profiling. Differentially abundant metabolites were identified using covariate-adjusted linear models implemented in the limma framework, with appendicular skeletal muscle mass index included as a continuous covariate. Differentially abundant metabolites were defined using a Benjamini\u2013Hochberg FDR-adjusted\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.05 and |log\n                      <jats:sub>2<\/jats:sub>\n                      FC| &amp;gt; 0.25. Global metabolic profiles were explored using PCA and PLS-DA, followed by KEGG pathway enrichment analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 141 males aged 28\u201340 years were included. After adjustment for ASMI, 10 differentially abundant metabolites were identified between the Good and Poor groups. Six metabolites showed higher adjusted abundances in the Good group, including cortisol (FDR\u00a0=\u00a00.031, log\n                      <jats:sub>2<\/jats:sub>\n                      FC = 0.321, 95% CI: 0.155 to 0.488), whereas four metabolites showed higher adjusted abundances in the Poor group, including glutamic acid (FDR\u00a0=\u00a00.013, log\n                      <jats:sub>2<\/jats:sub>\n                      FC = \u22120.262, 95% CI: \u22120.380 to \u22120.145). Nominally significant enrichment was observed for nitrogen metabolism (\n                      <jats:italic>P<\/jats:italic>\n                      value = 0.011), arginine biosynthesis (\n                      <jats:italic>P<\/jats:italic>\n                      value = 0.026), butanoate metabolism (\n                      <jats:italic>P<\/jats:italic>\n                      value = 0.028), and histidine metabolism (\n                      <jats:italic>P<\/jats:italic>\n                      value = 0.030); however, no pathway remained significant after FDR correction.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Differences in running performance were associated with distinct serum metabolic patterns involving amino-acid and nitrogen metabolism, phospholipid metabolism, and stress- and redox-associated metabolic processes. These findings may provide metabolic hypotheses on inter-individual differences in running performance and identify candidate metabolic pathways for further investigation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphys.2026.1920016","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:40:32Z","timestamp":1790829632000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Serum metabolic signatures associated with running performance in healthy men living in a cold environment: insights into amino acid and energy metabolism"],"prefix":"10.3389","volume":"17","author":[{"given":"Kexin","family":"Fang","sequence":"first","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixia","family":"Yu","sequence":"additional","affiliation":[{"name":"Military Medical Sciences Academy, Academy of Military Sciences","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruixin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjing","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiran","family":"Zheng","sequence":"additional","affiliation":[{"name":"Peking University Third Hospital","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tieqiang","family":"Sun","sequence":"additional","affiliation":[{"name":"Military Medical Sciences Academy, Academy of Military Sciences","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanxin","family":"Yao","sequence":"additional","affiliation":[{"name":"Military Medical Sciences Academy, Academy of Military Sciences","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Guo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University","place":["Beijing, China"]},{"name":"Department of Clinical Neuroscience, Karolinska Institutet","place":["Stockholm, Sweden"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1038\/s41586-020-2896-2","article-title":"A reference map of potential determinants for the human serum metabolome","volume":"588","author":"Bar","year":"2020","journal-title":"Nature"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2021.756618","article-title":"Association between changes in serum and skeletal muscle metabolomics profile with maximum power output gains in response to different aerobic training programs: The Times Study","volume":"12","author":"Castro","year":"2021","journal-title":"Front. 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