Impaired glymphatic function contributes to high-frequency attacks in patients with episodic migraine
Abstract
BACKGROUND AND OBJECTIVE: Previous studies have reported inconsistent results regarding glymphatic function in migraine patients. This study aimed to investigate glymphatic function in patients with episodic migraine (EM), focusing on varying attack frequencies, and to explore its potential pathophysiologic role in migraine.
METHODS: In this cross-sectional study, migraine clinical parameters and psychiatric comorbidities, including depression, anxiety, and sleep disorders, were collected. Three MRI measures were quantified, i.e., the diffusion tensor imaging (DTI) along the perivascular space (DTI-ALPS) index, perivascular space (PVS) volume in the basal ganglia (BG) and white matter (WM), and white matter hyperintensity (WMH) volume in the periventricular WM and deep WM. Patients with 4 or more monthly migraine days (MMDs) were categorized into the high-frequency episodic migraine (HFEM) group, whereas patients with fewer than 4 MMDs were placed in the low-frequency episodic migraine (LFEM) group. The differences in the DTI-ALPS index, PVS volume, and WMH volume were compared between the controls and patients with EM, as well as among the EM subgroups. Correlations between the DTI-ALPS index and migraine clinical parameters, WMH, and PVS were determined.
RESULTS: A total of 74 patients with EM without cardiovascular risk factors and 42 age- and sex-matched controls were enrolled. The HFEM group (1.37 ± 0.12) exhibited a significantly lower DTI-ALPS index compared to…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 74 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.