Integrating Divergence-Based Proteomic Analysis and Directed Network Diffusion to Characterize Diagnosis-Anchored Molecular Variability at the Metabolic Syndrome–Migraine Interface
International Journal of Molecular Sciences, 2026
Wang B., Li Y., Liu Y., Han D.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Metabolic Diseases Neurology | Patient Stratification | Plasma | Olink Explore 3072/384 |
Abstract
Metabolic syndrome (MetS) has been associated with migraine, but the prediagnostic phase and the molecular features preceding migraine onset remain unclear. We aimed to identify a diagnosis-anchored proteomic variability window and to characterize pathways, candidate bridge proteins, and druggable targets within a direction-consistent MetS-to-migraine molecular framework. We first assessed the association between baseline MetS and incident migraine in 452,471 UK Biobank participants using Cox models. We then conducted a nested proteomics case–control analysis stratified by MetS status and applied single-sample Jensen–Shannon divergence (sJSD), network proximity, directed diffusion, and drug–target proximity analyses. Baseline MetS was associated with a higher risk of incident migraine (hazard ratio 1.09, 95% confidence interval (CI) 1.01–1.18; p = 0.022). A diagnosis-anchored proteomic divergence pattern peaked 4.71–6.76 years before migraine diagnosis in the MetS stratum. The parallel within-stratum analysis in the NoMetS stratum showed no T2-centered peak. We identified 11 direction-consistent novel pathways, seven candidate bridge proteins spanning metabolic, endothelial, and brain tissues, and three candidate drugs. These findings support a diagnosis-stratified framework for studying MetS-related migraine and provide testable hypotheses for future mechanistic and pharmacological evaluation.