Pharmacogenomic study-A pilot study of the effect of pharmacogenomic phenotypes on the adequate dosing of verapamil for migraine prevention.

OBJECTIVE: To investigate factors affecting the efficacy and tolerability of verapamil for migraine prevention using individual pharmacogenomic phenotypes. BACKGROUND: Verapamil has a wide range of dosing in headache disorders without reliable tools to predict the optimal doses for an individual. METHODS: This is a retrospective chart review examining adults with existing pharmacogenomic reports at Mayo Clinic who had used verapamil for migraine. Effects of six cytochrome P450 phenotypes on the doses of verapamil for migraine prevention were assessed. RESULTS: Our final analysis included 33 migraine patients (82% with aura). The mean minimum effective and maximum tolerable doses of verapamil were 178.2(20-320) mg and 227.9(20-480) mg. A variety of CYP2C9, CYP2D6, and CYP3A5 phenotypes were found, without significant association with the verapamil doses after adjusting for age, sex, body mass index, and smoking status. CONCLUSIONS: We demonstrated a wide range of effective and tolerable verapamil doses used for migraine in a cohort with various pharmacogenomic phenotypes.

Advancing toward precision migraine treatment: Predicting responses to preventive medications with machine learning models based on patient and migraine features.

OBJECTIVE: To develop machine learning models using patient and migraine features that can predict treatment responses to commonly used migraine preventive medications. BACKGROUND: Currently, there is no accurate way to predict response to migraine preventive medications, and the standard trial-and-error approach is inefficient. METHODS: In this cohort study, we analyzed data from the Mayo Clinic Headache database prospectively collected from 2001 to December 2023. Adult patients with migraine completed questionnaires during their initial headache consultation to record detailed clinical features and then at each follow-up to track preventive medication changes and monthly headache days. We included patients treated with at least one of the following migraine preventive medications: topiramate, beta-blockers (propranolol, metoprolol, atenolol, nadolol, timolol), tricyclic antidepressants (amitriptyline, nortriptyline), verapamil, gabapentin, onabotulinumtoxinA, and calcitonin gene-related peptide (CGRP) monoclonal antibodies (mAbs) (erenumab, fremanezumab, galcanezumab, eptinezumab). We pre-trained a deep neural network, "TabNet," using 145 variables, then employed TabNet-embedded data to construct prediction models for each medication to predict binary outcomes (responder vs. non-responder). A treatment responder was defined as having at least a 30% reduction in monthly headache days from baseline. All model performances were evaluated, and metrics were reported in the held-out test set (train 85%, test 15%). SHapley Additive exPlanations (SHAP) were conducted to determine variable importance. RESULTS: Our final analysis included 4260 patients. The responder rate for each medication ranged from 28.7% to 34.9%, and the mean time to treatment outcome for each medication ranged from 151.3 to 209.5 days. The CGRP mAb prediction model achieved a high area under the receiver operating characteristics curve (AUC) of 0.825 (95% confidence interval [CI] 0.726, 0.920) and an accuracy of 0.80 (95% CI 0.70, 0.88). The AUCs of prediction models for beta-blockers, tricyclic antidepressants, topiramate, verapamil, gabapentin, and onabotulinumtoxinA were: 0.664 (95% CI 0.579, 0.745), 0.611 (95% CI 0.562, 0.682), 0.605 (95% CI 0.520, 0.688), 0.673 (95% CI 0.569, 0.724), 0.628 (0.533, 0.661), and 0.581 (95% CI 0.550, 0.632), respectively. Baseline monthly headache days, age, body mass index (BMI), duration of migraine attacks, responses to previous medication trials, cranial autonomic symptoms, family history of headache, and migraine attack triggers were among the most important variables across all models. A variable could have different contributions; for example, lower BMI predicts responsiveness to CGRP mAbs and beta-blockers, while higher BMI predicts responsiveness to onabotulinumtoxinA, topiramate, and gabapentin. CONCLUSION: We developed an accurate prediction model for CGRP mAbs treatment response, leveraging detailed migraine features gathered from a headache questionnaire before starting treatment. Employing the same methods, the model performances for other medications were less impressive, though similar to the machine learning models reported in the literature for other diseases. This may be due to CGRP mAbs being migraine-specific. Incorporating medical comorbidities, genomic, and imaging factors might enhance the model performance. We demonstrated that migraine characteristics are important in predicting treatment responses and identified the most crucial predictors for each of the seven types of preventive medications. Our results suggest that precision migraine treatment is feasible.

Migraine with aura associates with a higher artificial intelligence: ECG atrial fibrillation prediction model output compared to migraine without aura in both women and men.

OBJECTIVE: To compare the artificial intelligence-enabled electrocardiogram (AI-ECG) atrial fibrillation (AF) prediction model output in patients with migraine with aura (MwA) and migraine without aura (MwoA). BACKGROUND: MwA is associated with an approximately twofold risk of ischemic stroke. Longitudinal cohort studies showed that patients with MwA have a higher incidence of developing AF compared to those with MwoA. The Mayo Clinic Cardiology team developed an AI-ECG algorithm that calculates the probability of concurrent paroxysmal or impending AF in ECGs with normal sinus rhythm (NSR). METHODS: Adult patients with an MwA or MwoA diagnosis and at least one NSR ECG within the past 20 years at Mayo Clinic were identified. Patients with an ECG-confirmed diagnosis of AF were excluded. For each patient, the ECG with the highest AF prediction model output was used as the index ECG. Comparisons between MwA and MwoA were conducted in the overall group (including men and women of all ages), women only, and men only in each age range (18 to <35, 35 to <55, 55 to <75, ≥75 years), and adjusted for age, sex, and six common vascular comorbidities that increase risk for AF. RESULTS: The final analysis of our cross-sectional study included 40,002 patients (17,840 with MwA, 22,162 with MwoA). The mean (SD) age at the index ECG was 48.2 (16.0) years for MwA and 45.9 (15.0) years for MwoA (p < 0.001). The AF prediction model output was significantly higher in the MwA group compared to MwoA (mean [SD] 7.3% [15.0%] vs. 5.6% [12.4%], mean difference [95% CI] 1.7% [1.5%, 2.0%], p < 0.001). After adjusting for vascular comorbidities, the difference between MwA and MwoA remained significant in the overall group (least square means of difference [95% CI] 0.7% [0.4%, 0.9%], p < 0.001), 18 to <35 (0.4% [0.1%, 0.7%], p = 0.022), and 35 to <55 (0.5% [0.2%, 0.8%], p < 0.001), women of all ages (0.6% [0.3%, 0.8%], p < 0.001), men of all ages (1.0% [0.4%, 1.6%], p = 0.002), women 35 to <55 (0.6% [0.3%, 0.9%], p < 0.001), and men 18 to <35 (1.2% [0.3%, 2.1%], p = 0.008). CONCLUSIONS: Utilizing a novel AI-ECG algorithm on a large group of patients, we demonstrated that patients with MwA have a significantly higher AF prediction model output, implying a higher probability of concurrent paroxysmal or impending AF, compared to MwoA in both women and men. Our results suggest that MwA is an independent risk factor for AF, especially in patients <55 years old, and that AF-mediated cardioembolism may play a role in the migraine-stroke association for some patients.

Brain Changes in Responders vs. Non-Responders in Chronic Migraine: Markers of Disease Reversal.

The aim of this study was to identify structural and functional brain changes that accompanied the transition from chronic (CM; ≥15 headache days/month) to episodic (EM; <15 headache days/month) migraine following prophylactic treatment with onabotulinumtoxinA (BoNT-A). Specifically, we examined whether CM patients responsive to prophylaxis (responders; n = 11), as evidenced by a reversal in disease status (defined by at least a 50% reduction in migraine frequency and <15 headache days/month), compared to CM patients whose migraine frequency remained unchanged (non-responders; n = 12), showed differences in cortical thickness using surface-based morphometry. We also investigated whether areas showing group differences in cortical thickness displayed altered resting-state functional connectivity (RS-FC) using seed-to-voxel analyses. Migraine characteristics measured across groups included disease duration, pain intensity and headache frequency. Patient reports of headache frequency over the 4 weeks prior to (pre-treatment) and following (post-treatment) prophylaxis were compared (post minus pre) and this measure served as the clinical endpoint that determined group assignment. All patients were scanned within 2 weeks of the post-treatment visit. Results revealed that responders showed significant cortical thickening in the right primary somatosensory cortex (SI) and anterior insula (aINS), and left superior temporal gyrus (STG) and pars opercularis (ParsOp) compared to non-responders. In addition, disease duration was negatively correlated with cortical thickness in fronto-parietal and temporo-occipital regions in responders but not non-responders, with the exception of the primary motor cortex (MI) that showed the opposite pattern; disease duration was positively associated with MI cortical thickness in responders versus non-responders. Our seed-based RS-FC analyses revealed anti-correlations between the SI seed and lateral occipital (LOC) and dorsomedial prefrontal cortices (DMPFC) in responders, whereas non-responders showed increased connectivity between the ParsOp seed and LOC. Overall, our findings revealed distinct morphometric and functional brain changes in CM patients that reverted to EM following prophylactic treatment compared to CM patients that showed no change in disease status. Elucidating the CNS changes involved in disease reversal may be critical to discovering interventions that prevent or slow the progression of CM. Such changes may aid in the evaluation of treatments as well as provide markers for disease "de-chronification".

Superficial siderosis of the central nervous system associated with incomplete dural closure following posterior fossa surgery: report of 3 cases.

This report reviews a series of 3 patients who developed superficial siderosis following posterior fossa operations in which dural closure was incomplete. In all 3 patients, revision surgery and complete duraplasty was performed to halt the progression of superficial siderosis. Following surgery, 2 patients experienced resolution of their CSF xanthochromia while 1 patient had reduced CSF xanthochromia. In this paper the authors also review the etiology, pathophysiology, diagnosis, and treatment of this condition. The authors suggest that posterior fossa dural patency and pseudomeningocele are risk factors for the latent development of superficial siderosis and recommend that revision duraplasty be performed in patients with posterior fossa pseudomeningoceles and superficial siderosis to prevent progression of the disease.