Elevated CGRP levels in chronic migraine: investigating the risk of developing major depressive disorder. A prospective observational cohort study

Gehrig Sansalvadó, Hanna
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BACKGROUND: Chronic migraine (CM) is a common and disabling neurologic condition that affects all areas of the patient's life. Major depressive disorder (MDD) is one of the most frequent psychiatric disorders and is recognized to be the second most disabling condi:on worldwide. Recent studies have shown a bidirec:onal relationship between CM and MDD, where patients with CM are at higher risk of developing MDD, and vice versa, leading to increased disability and reduced quality of life. It has been suggested that both conditions may share different aspects in terms of genetics, pathophysiological mechanisms, clinical features and treatment. Among common pathways, evidence indicates that CGRP, a neuropeptide well known for its role in migraine pathophysiology, has also emerged as a possible mediator of mood regulation. This suggests that CGRP could explain the high comorbidity of migraine and depression, however, further research is needed to fully comprehend its dual role. OBJECTIVES: The aim of this study is to explore the relationship between CM and MDD by evaluating the role of CGRP in identifying individuals at heightened risk of comorbidity. Secondary objectives include assessing the likelihood of MDD relapse, the severity of depressive symptoms and the impact on quality of life. DESIGN: The study is designed as a prospective, observational, cohort study that will be carried out in the Xarxa de Salut Mental i Addiccions (XSMiA) of the Girona province. The follow-up period will be 2 years. PARTICIPANTS AND METHODS: A total of 528 patients diagnosed with CM will we recruited using a non-probabilistic convenience method, and those who fulfil the criteria and sign the informed consent will be included. Data collection will include blood samples to determine CGRP levels using the ELISA assay, alongside psychological assessments using validated scales. The results will be analyzed through a descriptive, bivariate and multivariate analysis by a professional statistician ​
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