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Cluster Analysis Revealed Two Hidden Phenotypes of Cluster Headache.
Pinar Yalinay Dikmen1, Cagla Ari2, Erdi Sahin3
1Department of Neurology, Acibadem University School of Medicine, Istanbul, Turkey.
Frontiers in Neurology
|June 7, 2022
Summary
Cluster analysis identified two distinct patient subgroups for Cluster Headache (CH). One group showed better triptan response, while the other had higher smoking rates and longer attacks, suggesting different underlying mechanisms.
Area of Science:
- Neurology
- Genetics
- Epidemiology
Background:
- Cluster Headache (CH) is a debilitating neurological disorder.
- Understanding patient heterogeneity is crucial for targeted treatment strategies.
Purpose of the Study:
- To identify distinct patient subgroups within Cluster Headache using K-means cluster analysis.
- To investigate potential differences in clinical features and treatment responses between these subgroups.
Main Methods:
- A cross-sectional, multi-center study involving 209 patients diagnosed with Cluster Headache.
- Data collection included sociodemographic characteristics, clinical features, and treatment experiences via semi-structured surveys.
- K-means cluster analysis was employed to identify patient subgroups.
Main Results:
- Two distinct subgroups emerged: Cluster 1 (n=81) and Cluster 2 (n=122).
- Cluster 1 patients were younger at diagnosis, experienced more autonomic symptoms, and had better triptan response.
- Cluster 2 patients exhibited higher rates of current and past smoking, childhood tobacco exposure, longer attack durations, and more emergency department visits.
Conclusions:
- The identified subgroups possess different phenotypic features, suggesting potentially distinct underlying genetic or epigenetic mechanisms.
- Cigarette smoking appears to be a significant factor in Cluster 2, potentially contributing to drug resistance and prolonged attacks.
- Further research is needed to elucidate the neurobiological pathways linking smoking to these distinct CH phenotypes.
