Integration of Metabolomics and Machine Learning Algorithm
Description
This study performed non-targeted metabolomics and lipidomics analyses using ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) on plasma samples from two independent cohorts to identify diagnostic biomarkers for osteoporosis (OP).
Files
Steps to reproduce
This dataset contains non-targeted UHPLC-MS-based metabolomic profiling of human plasma samples. Sample preparation was performed by protein precipitation with methanol, followed by nitrogen drying and reconstitution. Chromatographic separation was carried out on an HSS T3 column using a water-acetonitrile gradient with 0.1% formic acid. Mass spectrometry data were acquired on an Orbitrap Exploris 120 system in both positive and negative ion modes using a full MS/dd-MS2 strategy. Raw data were processed using Compound Discoverer 3.3 for peak detection, alignment, normalization, and metabolite annotation against HMDB and an in-house library. Multivariate statistical analyses (PCA, OPLS-DA) and differential metabolite screening were performed using SIMCA 14.1 and KEGG pathway analysis.
Institutions
- Tianjin University of Traditional Chinese MedicineTianjin, Tianjin