Summary of Study ST002949

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001834. The data can be accessed directly via it's Project DOI: 10.21228/M8NH80 This work is supported by NIH grant, U2C- DK119886.

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This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002949
Study TitleSerum metabolomics reveals metabolic profile and potential biomarkers of ankylosing spondylitis
Study SummaryAnkylosing spondylitis (AS) is a chronic systemic inflammatory disease that significantly impairs physical function, quality of life, and work ability in young individuals. Nonetheless, the identification of early radiographic changes in AS is frequently delayed, and the diagnostic efficacy of biomarkers remains moderately effective, with unsatisfactory sensitivity and specificity. Hence, it is imperative to identify biomarkers that can facilitate early diagnosis, prognosis, and monitoring of AS. A total of 67 AS patients and 67 healthy controls were recruited to procure plasma samples for the purpose of screening potential biomarkers of AS via untargeted combined with targeted metabolomics approach utlizing UHPLC-QTOF-MS/MS and UHPLC-QQQ-MS/MS. Multivariate pattern recognition and univariate statistical analysis were employed to compare and elucidate the differential metabolites. The results indicated a notable divergence between the two groups, and a total of 170 different metabolites associated with the primary 6 metabolic pathways exhibiting a correlation with AS. Among those, 26 metabolites exhibited high sensitivity and specificity with area under curve (AUC) value were greater than 0.8. Subsequent targeted quantitative analysis discovered 3 metabolites, namely 3-amino-2-piperidone, hypoxanthine and octadecylamine, exhibiting excellent distinguishing ability based on the results of ROC curve and Random Forest model, thus qualifying as potential biomarkers for AS. Summarily, our non-targeted and targeted metabolomics investigations provide new insights into the metabolic profile and potential biomarker candidates of AS. These findings may provide additional diagnostic options for AS and enhance the understanding of the underlying pathophysiology of the condition.
Institute
Ningxia Medical University
Last NameMa
First NameXueqin
Address1160 Shenli Street, Yinchuan, Ningxia, 750004, China
Emailmaxueqin217@126.com
Phone+86 0951688069
Submit Date2023-09-15
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2023-11-15
Release Version1
Xueqin Ma Xueqin Ma
https://dx.doi.org/10.21228/M8NH80
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Combined analysis:

Analysis ID AN004836 AN004837
Analysis type MS MS
Chromatography type Reversed phase Reversed phase
Chromatography system Agilent 1290 Infinity II Agilent 1290 Infinity II
Column Waters XBridge BEH C18 (100 x 2.1mm,3.5um) Waters XBridge BEH C18 (100 x 2.1mm,3.5um)
MS Type ESI ESI
MS instrument type QTOF QTOF
MS instrument name Agilent 6545 QTOF Agilent 6545 QTOF
Ion Mode POSITIVE NEGATIVE
Units ppm ppm

Chromatography:

Chromatography ID:CH003655
Instrument Name:Agilent 1290 Infinity II
Column Name:Waters XBridge BEH C18 (100 x 2.1mm,3.5um)
Column Temperature:30℃
Flow Gradient:The gradient elution set as follows: 90-50% A from 0 to 1 min, 50-20% A from 1 to 2 min,20-2% A from 2 to 7 min, 2% A from 7 to 9 min, 2-20% A from 9 to 11 min, 20-50% A from 11 to 12 min, and 50-90% A from 12 to 13 min.
Flow Rate:0.2 ml/min
Solvent A:0.1% formic acid
Solvent B:acetonitrile
Chromatography Type:Reversed phase
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