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We determined the potential biomarkers of refractory gout and attempted to explore the relation between potential biomarkers and diet structures and exercise patterns.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      The study employed a questionnaire survey to analyze diet structures and exercise patterns from 100 patients of refractory gout and 79 healthy volunteers. At the same time, using\n                      <jats:sup>1<\/jats:sup>\n                      H-NMR metabolic technology to analyze the metabolites present in the serum samples obtained from 39 patients of refractory gout (group B) and 20 healthy subjects (group A). Employing MestReNova (Version 8.0.1) to analyze the metabolites\u00a0maps, collecting the NMR results, further importing into SIMCA-P+\u200914.0 software (Umetrics, Sweden) for principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) statistical analysis. Combining patterns recognition and multivariate statistics, potential biomarkers were searched. Other experimental data, including creatinine and adiponectin, were counted by the SPSS21.0. The measurement data were expressed by X\u2009\u00b1\u2009S and\n                      <jats:italic>t<\/jats:italic>\n                      test. The counting data were expressed in percent and performed by\n                      <jats:italic>X<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      test.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Our results revealed that patients with gout tended to be obese, and there were differences in their lifestyle with exercise, sleep, and smoking, as well as in their preference for fructose drinks, alcohol, and total and structural distribution of meat, milk, eggs, and so on when compared with the healthy volunteers. Importantly, we found the adiponectin in the gout group was lower as compared to the healthy group. Further, metabolomics in combination with KEGG analysis revealed that the biosynthesis of aminoacyl tRNA, biosynthesis of valine, leucine, and isoleucine, metabolism of alanine, aspartic, and glutamate, metabolism of glycine, serine, and threonine, phenylalanine, glycolysis\/gluconeogenesis, ketone body synthesis and degradation, metabolism of\n                      <jats:sc>d<\/jats:sc>\n                      \u2010glutamine, citric acid cycle (TCA cycle), triglyceride metabolism, and others could be used as specific biomarkers of this disease.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Recurrent refractory gout and formation of tophus may be related to the diet structures and lifestyles between the patients and the healthy people, and their abnormal metabolic network may be related to the disorder of mitochondrial energy metabolism, which further results in abnormal metabolism of glucose, lipids, amino acids, and deposition of uric acid in joints, peripheral connective tissue, and kidney, inducing an inflammatory response.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13018-024-04540-2","type":"journal-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T07:02:42Z","timestamp":1705647762000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Analysis of the relationship of refractory gout between potential biomarkers and diet structure and lifestyle based on 1H-NMR"],"prefix":"10.1186","volume":"19","author":[{"given":"Liang","family":"Weidong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Liuting","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Xiangcong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Jianhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Xueying","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,19]]},"reference":[{"issue":"1","key":"4540_CR1","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1186\/s12891-019-2519-y","volume":"20","author":"P Towiwat","year":"2019","unstructured":"Towiwat P, Chhana A, Dalbeth N. 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