OC-12 | The potential role of sleep quality in the relationship between glymphatic function and migraine frequency: insights from a cross-sectional study
Abstract
Background: Migraine has a complex pathophysiology involving genetic predispositions, comorbidities, and psychosocial factors. Emerging evidence highlights the glymphatic system – responsible for brain waste clearance – as a potential contributor to migraine pathogenesis. As poor sleep quality exacerbates glymphatic dysfunction, it might have an impact on migraine chronification.
Methods: This cross-sectional study included 106 individuals with migraine (80.2% female; median age: 45.0 years, IQR = 37.0–52.0) between June 2018 and February 2020. Glymphatic function was assessed using the DTI-ALPS index derived from brain magnetic resonance imaging, while sleep quality was evaluated with the Pittsburgh Sleep Quality Index. First, we evaluated the association between DTI-ALPS index and monthly headache days. A second model included the dichotomized Pittsburgh Sleep Quality Index score (“poor” vs. “good” sleepers) and its interaction with the DTI-ALPS index to examine the moderating role of sleep quality in the relationship between glymphatic function and monthly headache days.
Results: Higher DTI-ALPS index values were associated with fewer monthly headache days in the overall sample while controlling for age and sex [adjusted IRR = 0.37, 95% CI = 0.16 – 0.86, p = 0.020]. Additionally, there was a significant interaction between DTI-ALPS index and sleep quality [adjusted IRR = 0.13, 95% CI = 0.02 – 0.76, p = 0.024] in predicting monthly headache days. We found an association…
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: 106 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.