Abstract
The dysregulation of lipid metabolism has been strongly associated with Alzheimer's Disease (AD); however, the biomedical implications and clinical relevance of these findings have not been systematically examined. Here, we conducted a comprehensive bioinformatic evaluation of AD-derived transcriptome datasets from postnatal brains and peripheral blood. We utilized differential gene expression and hierarchical clustering to identify co-expressed modules of lipid metabolism genes in patients based on their molecular functions in biological enrichment and molecular pathway analysis, association with pathological phenotypes, and molecular network correlation. Additionally, we analyzed the expression patterns of these genes in immune and nonimmune cells as well as cell type enrichments in both brain tissue and peripheral blood. By categorizing patients into distinct transcriptional clusters and stratified groups, we found enrichment in biological pathways for neurodegenerative diseases, oxidative phosphorylation, synaptic transmission, unexpected infections, and molecular functions for cellular translation and energy production in the stratified clusters and groups. Biological network analysis indicates striking differences between lipid-metabolism differential expression genes (DEGs) in the periphery and CNS, with restricted processes being enriched. Notably, neurons, glial cells involved in neuroinflammation, and peripheral blood immune cell infiltration revealed a marked disparity in the clustering subgroups in patients’ hippocampi and peripheral regions. Differentially expressed genes such as PLD3, NDUFAB1, OXCT1, PI4KA, and AACS in the brain and DBI, MBOAT7, and RXRA in the periphery correlate well with disease pathologies and immune cell preferences. These results suggest that lipid metabolism is critical for disease progression and immune cell activation, thus providing an innovative approach to diagnosing and treating AD.