A Novel Palmitoylation-Related Molecular Signature for Predicting and Therapeutically Targeting Alzheimer's Disease.
Miao. Xiuling X; Luo. Kaiyu K; Li. Yinglei Y; Zhou. Yang Y; Wei. Meng M; Zhang. Ting T; Hu. Yazhuo Y; Wang. Heran H; Jia. Jianjun J
Key Findings
- 65 palmitoylation‑related genes were linked to Alzheimer’s disease
- Seven key genes (CALM1, VAMP2, SYT1, MET, BAG3, TJP1, NOTCH1) form a strong diagnostic model (AUC up to 0.91)
- Potential drug targets and regulatory molecules were identified, but none involve the peptide directly
Practical Outcomes
- At this stage the study is purely molecular and doesn’t give any actionable supplement or dosing guidance for palmitoyl‑dipeptide‑6. It simply highlights that palmitoylation pathways are important in Alzheimer’s, suggesting future research might eventually lead to interventions, but nothing you can apply right now.
Summary
Scientists looked at gene activity related to a chemical process called palmitoylation and found a set of genes that can help predict Alzheimer's disease, but they didn’t test the peptide palmitoyl‑dipeptide‑6 itself, so there’s no direct advice for using it.
Abstract
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by amyloid-beta (Aβ) plaques and hyperphosphorylated tau pathology. Although palmitoylation has been implicated in AD, its specific mechanisms remain poorly defined. To investigate this, seven transcriptomic datasets were obtained from the GEO database. Differential expression and Gene Set Enrichment Analysis (GSEA) were performed across five training sets (GSE5281, GSE29378, GSE36980, GSE122063, and GSE132903). By intersecting differentially expressed genes (DEGs) with palmitoylation-related genes from GeneCards, 65 AD-associated palmitoylation-related genes (AD-PRGs) were identified. Functional enrichment analyses (KEGG and GO) were performed on these genes. Furthermore, seven key AD-PRGs (CALM1, VAMP2, SYT1, MET, BAG3, TJP1, NOTCH1) were prioritized using protein-protein interaction (PPI) networks and three machine learning algorithms (LASSO, SVM-RFE, and Random Forest). A diagnostic model constructed from these seven genes exhibited strong predictive performance, with AUC values of 0.834 in the training set and 0.907/0.865 in two external validation sets (GSE33000, GSE44770). Single-gene GSEA indicated associations with synaptic function and oxidative phosphorylation pathways. Protein docking analyses using GRAMM (Global RAnge Molecular Matching) and PISA (Proteins, Interfaces, Surfaces, and Assemblies) further suggested interactions between these key genes and Aβ/tau, supporting their involvement in AD pathogenesis. Additionally, regulatory network analysis identified 23 miRNAs, 33 transcription factors, and 14 potential therapeutic agents targeting these key genes. Our findings underscore the importance of palmitoylation in synaptic dysfunction-notably VAMP2 and SYT1 roles in vesicle recycling and neurotransmitter release-and offer promising targets for novel therapeutic strategies in AD.
Study Information
pubmed
2025
2025-12-09T00:00:00.000Z
10.1007/s12035-025-05574-1
88