Previously unrecognized high-dimensional structure was revealed within the phenotypic landscape of cluster headache, enabling the prediction of treatment response to verapamil with modest fidelity.
Why this matters
Cluster headache has no clear molecular target in the causal pathway and the precise mechanism of causation is unknown, thus hindering the development of treatments for this trigeminal autonomic cephalalgia. Moreover, treatment selection remains investigative, as no treatment response has ever been robustly linked to any clinical or physiological parameters.
Verapamil is the first-line therapy for cluster headache, but often patients only receive the dose required to determine whether it is effective after incremental dose escalations lasting weeks or even months. Therefore, a system for distinguishing patients who are likely to respond to first-line verapamil, versus those who are not, is urgently needed.
To resolve this unmet need, the authors applied high-dimensional machine phenotyping to a sequential, unselected cohort of MRI patients with cluster headache.