Deep and unbiased proteomics, pathway enrichment analysis, and protein–protein interaction of biomarker signatures in migraine

Abstract

Background: Currently, there are no biomarkers for migraine. Objectives: We aimed to identify proteomic biomarker signatures for diagnosing, subclassifying, and predicting treatment response in migraine. Design: This is a cross-sectional and longitudinal study of untargeted serum and cerebrospinal fluid (CSF) proteomics in episodic migraine (EM; n = 26), chronic migraine (CM; n = 26), and healthy controls (HC; n = 26). Methods: We developed classification models for biomarker identification and natural clusters through unsupervised classification using agglomerative hierarchical clustering (AHC). Pathway analysis of differentially expressed proteins was performed. Results: Of 405 CSF proteins, the top five proteins that discriminated between migraine patients and HC were angiotensinogen, cell adhesion molecule 3, immunoglobulin heavy variable (IGHV) V-III region JON, insulin-like growth factor binding protein 6 (IGFBP-6), and IGFBP-7. The top-performing classifier demonstrated 100% sensitivity and 75% specificity in differentiating the two groups. Of 229 serum proteins, the top five proteins in classifying patients with migraine were immunoglobulin heavy variable 3-74 (IGHV 3-74), proteoglycan 4, immunoglobulin kappa variable 3D-15, zinc finger protein (ZFP)-814, and mediator of RNA polymerase II transcription subunit 12. The best-performing classifier exhibited 94% sensitivity and 92% specificity. AHC separated EM, CM, and HC into distinct clusters with 90% success. Migraine patients exhibited increased ZFP-814 and calcium voltage-gated channel subunit alpha 1F (CACNA1F) levels, while IGHV 3-74 levels decreased in both cross-sectional and longitudinal serum analyses. ZFP-814 remained upregulated during the CM-to-EM reversion but was suppressed when CM persisted. CACNA1F was pronounced in CM persistence. Pathway analysis revealed immune, coagulation, glucose metabolism, erythrocyte oxygen and carbon dioxide exchange, and insulin-like growth factor regulation pathways. Conclusion: Our data-driven study provides evidence for identifying novel proteomic biomarker signatures to diagnose, subclassify, and predict treatment responses for migraine. The dysregulated biomolecules affect multiple pathways, leading to cortical spreading depression, trigeminal nociceptor sensitization, oxidative stress, blood–brain barrier disruption, immune response, and coagulation cascades. Trial registration: NCT03231241, ClincialTrials.gov.