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Identification of predictive biomarkers for the progression from episodic migraine to chronic migraine

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NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/7941095
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This database includes the raw data linked with the RF project, “ Identification of predictive biomarkers for the progression from episodic migraine to chronic migraine”. In this study, we reported results of the identification of biomarkers of progression of Episodic Migraine (EM) into Chronic Migraine with medication overuse (CM-MO). In order to achieve this objective, we investigated the possible factors associated to a risk of CM by comparing differences in genetic, clinical, psychological, serological and neurophysiological variables between EM and CM sufferers. Methods. We compared in a paired case-control study 200 EM and 200 CM-MO patients with respect to clinical, psychological, biochemical and neurophysiological variables. Clinical variables were collected by headache neurologists and included: migraine history (i.e. EM/CM onset) and its characteristics, family history, present/previous use of medications/other substances, medical history, lifestyle habits. A psychopathological assessment has been performed by a trained psychologist and included also a series of questionnaires for assessing traumatic experiences, stressful life-events, anxiety and depression, Alexithymia, level of dependence. According to the project, we also conducted a case-control candidate gene association study aimed to evaluate the role of candidate single nucleotide polymorphisms (SNPs) as genetic predictors of migraine chronification. We selected SNPs in genes that are relevant for migraine pathophysiology, gene polymorphisms that have reached genome wide significance for migraine susceptibility, as well as SNPs in genes involved in risk for addiction and/or drug-seeking behavior. We firstly tested the potential correlations between SNPs and migraine chronification in an exploratory set of CM patients (cases) and EM patients (controls), enrolled for previously conducted research projects. Then, SNPs that emerged as nominally significant in the exploratory dataset (P<0.05) have been selected for validation in an independent confirmatory population generated by the recruitment of 200 EM and 200 with CM-MO patients enrolled in this study. Finally, a subset of 20 EM, 20 CM-MO patients and 20 Healthy Controls underwent the parallel evaluation of neurophysiological parameters and serological markers. Results (in brief). Here we report data from study involving 200 episodic migraine patients with a long history of migraine and 200 chronic migraine with medication overuse patients. We considered several aspects that may be involved in the development of chronic migraine. First, after a multivariate analysis we identified clinical factors associated to CM-MO, some of them expected, such as alcohol daily use, snoring, use of hypnotic and antidepressant drugs, hypertension, and the others unexpected, such as astenia as accompanying headache symptom and dysmenorrhea. In our study, CM-MO results characterized by a more complex psychopathological profile that affects different dimensions (more presence of anxiety and depressive symptoms, dependence level, early traumatic experiences). Plasma levels of calcitonin gene-related peptide (CGRP) and the expression of miR-34a-5p and miR-382-5p in peripheral blood mononuclear cells, were significantly higher in migraine subjects when compared to healthy volunteers. In the CM-MO group, detoxification significantly decreased CGRP levels and miRNAs expression. Plasma levels of Kynurenic Acyd were lower in all migraine patients when compared to controls, while levels of Kynolonic Acyd were similar in all groups. As neurophysiological correlate, we found no significant differences between migraine patients and HV for NWR threshold, single stimulus threshold, latency and area under the curve. Temporal summation threshold showed a higher trend in migraine patients when compared to control group, but this data has not been confirmed in the post-hoc analysis. Finally, genetic data showed that LRP1 rs11172113 single nucleotide polymorphism is associated with CM, while other SNPs investigated do not reach the significance.
创建时间:
2023-05-23
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