Identification of Gene Signatures and Molecular Mechanisms Underlying the Comorbidity of Alzheimer's Disease and Crohn's Disease Using Machine Learning.

Objective

Alzheimer's disease (AD) and Crohn's disease (CD) both involve inflammation and immune dysregulation, yet the potential molecular mechanisms underlying their comorbidity remain unclear.

Methods

We integrated transcriptomic data from AD and CD patients and applied differential expression analysis, weighted gene coexpression network analysis, protein-protein interaction networks, and multiple machine learning approaches to identify key comorbidity genes. Functional enrichment, single-cell sequencing validation, and virtual knockout analyses were used to explore their biological roles. Molecular docking was performed to evaluate the binding affinity of candidate small-molecule drugs to the identified core genes.

Results

CXCL1 and IGFBP5 were identified as core comorbidity genes. CXCL1 was associated with inflammatory signaling, including cytokine receptor binding, neutrophil migration, and NOD-like receptor signaling. IGFBP5 was linked to growth factor binding, smooth muscle cell proliferation, and extracellular matrix-receptor interactions. Single-cell and virtual knockout analyses indicated that these genes play pivotal roles in inflammation, immune regulation, cell migration, and tissue remodeling, potentially bridging central and peripheral inflammation via the gut-brain axis and IgSF CAM signaling. Candidate drug prediction and molecular docking suggested that small molecules such as Dasatinib, Mifepristone, and Retinoic acid may modulate these pathways.

Conclusion

This study reveals the critical roles of CXCL1 and IGFBP5 in AD-CD comorbidity, providing a theoretical basis for exploring gut-brain axis mechanisms and potential targeted interventions.