AHS 2023 | Deep and unbiased proteomics for the identification of candidate biomarker signatures in migraine

The diagnosis of migraine relies on self-reported symptoms, which can often lead to misdiagnosis and mistreatment. Yohannes Woldeamanuel, MD, Stanford University, Stanford, CA, discusses a study that performed a complete proteome profile to identify candidate biomarker signatures in migraine patients to improve diagnosis, migraine subclassification, and prediction of treatment response. The study included episodic and chronic migraine patients as well as healthy controls. Untargeted proteome profiling was carried out in serum and cerebrospinal fluid samples, and machine learning was employed to construct classification models to distinguish migraine patients from healthy controls and subcategorize migraine patients. Through the utilization of high-throughput proteomics and data-driven methodologies, the study identified potential biomarkers that may serve for the diagnosis and prediction of treatment response in people with migraine. Further longitudinal studies with bigger sample sizes are needed to substantiate these promising but preliminary results. This interview took place at the American Headache Society 2023 meeting in Austin, TX.

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