Application of Proteomics and Metabolomics in Identifying Candidate Biomarkers for Alzheimer's Disease: A Multi-Omics Bioinformatics Study Using Public Datasets

This Zenodo record contains supplementary files accompanying the project titled “Application of Proteomics and Metabolomics in Identifying Candidate Biomarkers for Alzheimer’s Disease: A Multi-Omics Bioinformatics Study Using Public Datasets.” The project integrated publicly available plasma metabolomics, cerebrospinal fluid metabolomics, and cerebrospinal fluid proteomics datasets to identify candidate Alzheimer’s disease-associated biomarkers and convergent biological pathways. The supplementary package includes processed data summaries, differential biomarker analysis outputs, pathway enrichment tables, machine-learning classification results, Cytoscape-ready node and edge tables, GraphML network files, figure source files, and documentation. Plasma and CSF metabolomics datasets were analysed separately using C18 and HILIC liquid chromatography–mass spectrometry platforms, while CSF proteomics data were incorporated to provide complementary protein-level evidence. The analysis identified metabolomic perturbations involving lipid metabolism, amino acid metabolism, purine/pyrimidine turnover, oxidative stress, pantothenate/CoA biosynthesis, and mitochondrial energy metabolism. CSF proteomics highlighted immune activation, complement dysregulation, amyloid-associated processes, synaptic dysfunction, oxidative stress, and neuronal injury. Machine-learning outputs and Cytoscape-ready network files are provided to support reproducibility and future validation. This repository contains secondary processed outputs and documentation derived from publicly available datasets. Original raw datasets remain available from their source repositories and publications and should be cited accordingly.