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Untargeted metabolomics analysis of the urinary metabolic signature of acute and chronic gout.
Jia, Qiangqiang; Dong, Qiuxia; Zhang, Jie; Zhao, Qing; Li, Yanhong; Chao, Zhu; Liu, Ju.
Affiliation
  • Jia Q; State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China.
  • Dong Q; Qinghai Red Cross Hospital, The Second Ward of Oncology, Xining, People's Republic of China, Xining 810001, China.
  • Zhang J; Qinghai Red Cross Hospital, The Second Ward of Oncology, Xining, People's Republic of China, Xining 810001, China.
  • Zhao Q; State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China.
  • Li Y; State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China.
  • Chao Z; Shandong Engineering Research Center of Novel Pharmaceutical Excipients, Sustained and Controlled Released Preparations, School of Pharmacy, Dezhou University, Dezhou, Shandong 253023, China. Electronic address: zhuchao830111@163.com.
  • Liu J; Department of Rheumatology, Jiujiang City Key Laboratory of Cell Therapy, Jiujiang First People's Hospital, Jiujiang 332000, China. Electronic address: jjliuju@163.com.
Clin Chim Acta ; : 119968, 2024 Sep 12.
Article in En | MEDLINE | ID: mdl-39276825
ABSTRACT

BACKGROUND:

Gout is a common kind of inflammatory arthritis with metabolic disorders. However, the detailed pathogenesis of gout is complex and not fully clear. We investigated the urine metabolic profiling of gout patients by ultra-performance liquid chromatograph quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS).

METHOD:

Urine metabolites were extracted from 26 acute gout patients, 31 chronic gout patients, and 32 healthy controls. Metabolite extracts were analyzed by UPLC-Q-TOF-MS for untargeted metabolomics. The peak area of creatinine was used to correct the content variations of urine samples for the semi-quantitative analysis. The value of variable importance in the projection (VIP) was obtained through the orthogonal partial least squares-discrimination analysis (OPLS-DA), and several differential metabolites were screened out.

RESULTS:

The potential metabolic markers of gout in different stages were found based on the t-test. Finally, 18 different metabolites were identified through Human Metabolome Database (HMDB) and Targeted-MS/MS. The receiver operating characteristic (ROC) curve results revealed that all the screened biomarkers exerted high accuracy and diagnostic value. Pathway analysis indicated that the significantly different metabolites were mainly involved in purine metabolism and amino acid metabolism.

CONCLUSION:

The identified potential biomarkers are mainly involved in purine metabolism and amino acid metabolism, which leads us to further explore the pathogenesis of gout. This will lead us to further explore the pathogenesis of gout and provide the basis and ideas for the prevention and treatment of gout.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Clin Chim Acta Year: 2024 Document type: Article Affiliation country: China Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Clin Chim Acta Year: 2024 Document type: Article Affiliation country: China Country of publication: Netherlands