Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine

OBJECTIVES

The objective of this longitudinal study was to determine whether brain iron accumulation, measured using magnetic resonance imaging magnetic transverse relaxation rates (T2*), is associated with response to erenumab for the treatment of migraine.

METHODS

Participants (n = 28) with migraine, diagnosed using international classification of headache disorders 3rd edition criteria, were eligible if they had six to 25 migraine days during a four-week headache diary run-in phase. Participants received two treatments with 140 mg erenumab, one immediately following the pre-treatment run-in phase and a second treatment four weeks later. T2* data were collected immediately following the pre-treatment phase, and at two weeks and eight weeks following the first erenumab treatment. Patients were classified as erenumab responders if their migraine-day frequency at five-to-eight weeks post-initial treatment was reduced by at least 50% compared to the pre-treatment run-in phase. A longitudinal Sandwich estimator approach was used to compare longitudinal group differences (responders vs non-responders) in T2* values, associated with iron accumulation. Group visit effects were calculated with a significance threshold of p = 0.005 and cluster forming threshold of 250 voxels. T2* values of 19 healthy controls were used for a reference. The average of each significant region was compared between groups and visits with Bonferroni corrections for multiple comparisons with significance defined as p < 0.05.

RESULTS

Pre- and post-treatment longitudinal imaging data were available from 28 participants with migraine for a total of 79 quantitative T2* images. Average subject age was 42 ± 13 years (25 female, three male). Of the 28 subjects studied, 53.6% were erenumab responders. Comparing longitudinal T2* between erenumab responders vs non-responders yielded two comparisons which survived the significance threshold of p < 0.05 after correction for multiple comparisons: the difference at eight weeks between the erenumab-responders and non-responders in the periaqueductal gray (mean ± standard error; responders 43 ± 1 ms vs non-responders 32.5 ± 1 ms, p = 0.002) and the anterior cingulate cortex (mean ± standard error; responders 50 ± 1 ms vs non-responders 40 ± 1 ms, p = 0.01).

CONCLUSIONS

Erenumab response is associated with higher T2* in the periaqueductal gray and anterior cingulate cortex, regions that participate in pain processing and modulation. T2* differences between erenumab responders vs non-responders, a measure of brain iron accumulation, are seen at eight weeks post-treatment. Less iron accumulation in the periaqueductal gray and anterior cingulate cortex might play a role in the therapeutic mechanisms of migraine reduction associated with erenumab.

The value of brain MRI functional connectivity data in a machine learning classifier for distinguishing migraine from persistent post-traumatic headache

Background

Post-traumatic headache (PTH) and migraine often have similar phenotypes. The objective of this exploratory study was to develop classification models to differentiate persistent PTH (PPTH) from migraine using clinical data and magnetic resonance imaging (MRI) measures of brain structure and functional connectivity (fc).

Methods

Thirty-four individuals with migraine and 48 individuals with PPTH attributed to mild TBI were included. All individuals completed questionnaires assessing headache characteristics, mood, sensory hypersensitivities, and cognitive function and underwent brain structural and functional imaging during the same study visit. Clinical features, structural and functional resting-state measures were included as potential variables. Classifiers using ridge logistic regression of principal components were fit on the data. Average accuracy was calculated using leave-one-out cross-validation. Models were fit with and without fc data. The importance of specific variables to the classifier were examined.

Results

With internal variable selection and principal components creation the average accuracy was 72% with fc data and 63.4% without fc data. This classifier with fc data identified individuals with PPTH and individuals with migraine with equal accuracy.

Conclusion

Multivariate models based on clinical characteristics, fc, and brain structural data accurately classify and differentiate PPTH vs. migraine suggesting differences in the neuromechanism and clinical features underlying both headache disorders.

Thalamic subfield iron accumulation after acute mild traumatic brain injury as a marker of future post-traumatic headache intensity

OBJECTIVE

To explore alterations in thalamic subfield volume and iron accumulation in individuals with post-traumatic headache (PTH) relative to healthy controls.

BACKGROUND

The thalamus plays a pivotal role in the pathomechanism of pain and headache, yet the role of the thalamus in PTH attributed to mild traumatic brain injury (mTBI) remains unclear.

METHODS

A total of 107 participants underwent multimodal T1-weighted and T2* brain magnetic resonance imaging. Using a clinic-based observational study, thalamic subfield volume and thalamic iron accumulation were explored in 52 individuals with acute PTH (mean age = 41.3; standard deviation [SD] = 13.5), imaged on average 24 days post mTBI, and compared to 55 healthy controls (mean age = 38.3; SD = 11.7) without history of mTBI or migraine. Symptoms of mTBI and headache characteristics were assessed at baseline (0-59 days post mTBI) (n = 52) and 3 months later (n = 46) using the Symptom Evaluation of the Sports Concussion Assessment Tool (SCAT-5) and a detailed headache history questionnaire.

RESULTS

Relative to controls, individuals with acute PTH had significantly less volume in the lateral geniculate nucleus (LGN) (mean volume: PTH = 254.1, SD = 43.4 vs. controls = 278.2, SD = 39.8; p = 0.003) as well as more iron deposition in the left LGN (PTH: T2* signal = 38.6, SD = 6.5 vs. controls: T2* signal = 45.3, SD = 2.3; p = 0.048). Correlations in individuals with PTH revealed a positive relationship between left LGN T2* iron deposition and SCAT-5 symptom severity score at baseline (r = -0.29, p = 0.019) and maximum headache intensity at the 3-month follow-up (r = -0.47, p = 0.002).

CONCLUSION

Relative to healthy controls, individuals with acute PTH had less volume and higher iron deposition in the left LGN. Higher iron deposition in the left LGN might reflect mTBI severity and poor headache recovery.

Headache classification and automatic biomarker extraction from structural MRIs using deep learning

Data-driven machine-learning methods on neuroimaging (e.g. MRI) are of great interest for the investigation and classification of neurological diseases. However, traditional machine learning requires domain knowledge to delineate the brain regions first, followed by feature extraction from the regions. Compared with this semi-automated approach, recently developed deep learning methods have advantages since they do not require such prior knowledge; instead, deep learning methods can automatically find features that differentiate MRIs from different cohorts. In the present study, we developed a deep learning-based classification pipeline distinguishing brain MRIs of individuals with one of three types of headaches [migraine (n = 95), acute post-traumatic headache (n = 48) and persistent post-traumatic headache (n = 49)] from those of healthy controls (n = 532) and identified the brain regions that most contributed to each classification task. Our pipeline included: (i) data preprocessing; (ii) binary classification of healthy controls versus headache type using a 3D ResNet-18; and (iii) biomarker extraction from the trained 3D ResNet-18. During the classification at the second step of our pipeline, we resolved two common issues in deep learning methods, limited training data and imbalanced samples from different categories, by incorporating a large public data set and resampling among the headache cohorts. Our method achieved the following classification accuracies when tested on independent test sets: (i) migraine versus healthy controls-75% accuracy, 66.7% sensitivity and 83.3% specificity; (2) acute post-traumatic headache versus healthy controls-75% accuracy, 66.7% sensitivity and 83.3% specificity; and (3) persistent post-traumatic headache versus healthy controls-91.7% accuracy, 100% sensitivity and 83.3% specificity. The most significant biomarkers identified by the classifier for migraine were caudate, caudal anterior cingulate, superior frontal, thalamus and ventral diencephalon. For acute post-traumatic headache, lateral occipital, cuneus, lingual, pericalcarine and superior parietal regions were identified as most significant biomarkers. Finally, for persistent post-traumatic headache, the most significant biomarkers were cerebellum, middle temporal, inferior temporal, inferior parietal and superior parietal. In conclusion, our study shows that the deep learning methods can automatically detect aberrations in the brain regions associated with different headache types. It does not require any human knowledge as input which significantly reduces human effort. It uncovers the great potential of deep learning methods for classification and automatic extraction of brain imaging-based biomarkers for these headache types.

Developing multivariable models for predicting headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury: A preliminary study

OBJECTIVES/BACKGROUND

Post-traumatic headache (PTH) is a common symptom after mild traumatic brain injury (mTBI). Although there have been several studies that have used clinical features of PTH to attempt to predict headache recovery, currently no accurate methods exist for predicting individuals' improvement from acute PTH. This study investigated the utility of clinical questionnaires for predicting (i) headache improvement at 3 and 6 months, and (ii) headache trajectories over the first 3 months.

METHODS

We conducted a clinic-based observational longitudinal study of patients with acute PTH who completed a battery of clinical questionnaires within 0-59 days post-mTBI. The battery included headache history, symptom evaluation, cognitive tests, psychological tests, and scales assessing photosensitivity, hyperacusis, insomnia, cutaneous allodynia, and substance use. Each participant completed a web-based headache diary, which was used to determine headache improvement.

RESULTS

Thirty-seven participants with acute PTH (mean age = 42.7, standard deviation [SD] = 12.0; 25 females/12 males) completed questionnaires at an average of 21.7 (SD = 13.1) days post-mTBI. The classification of headache improvement or non-improvement at 3 and 6 months achieved cross-validation area under the curve (AUC) of 0.72 (95% confidence interval [CI] 0.55 to 0.89) and 0.84 (95% CI 0.66 to 1.00). Sub-models trained using only the top five features still achieved 0.72 (95% CI 0.55 to 0.90) and 0.77 (95% CI 0.52 to 1.00) AUC. The top five contributing features were from three questionnaires: Pain Catastrophizing Scale total score and helplessness sub-domain score; Sports Concussion Assessment Tool Symptom Evaluation total score and number of symptoms; and the State-Trait Anxiety Inventory score. The functional regression model achieved R = 0.64 for modeling headache trajectory over the first 3 months.

CONCLUSION

Questionnaires completed following mTBI have good utility for predicting headache improvement at 3 and 6 months in the future as well as the evolving headache trajectory. Reducing the battery to only three questionnaires, which assess post-concussive symptom load and biopsychosocialecologic factors, was helpful to determine a reasonable prediction accuracy for headache improvement.

Longitudinal changes in functional connectivity and pain-induced brain activations in patients with migraine: a functional MRI study pre- and post- treatment with Erenumab

Abstract

Background

Migraine involves central and peripheral nervous system mechanisms. Erenumab, an anti-calcitonin gene-related peptide (CGRP) receptor monoclonal antibody with little central nervous system penetrance, is effective for migraine prevention. The objective of this study was to determine if response to erenumab is associated with alterations in brain functional connectivity and pain-induced brain activations.

Methods

Adults with 6–25 migraine days per month during a 4-week headache diary run-in phase underwent pre-treatment brain functional MRI (fMRI) that included resting-state functional connectivity and BOLD measurements in response to moderately painful heat stimulation to the forearm. This was followed by two treatments with 140 mg erenumab, at baseline and 4 weeks later. Post-treatment fMRI was performed 2 weeks and 8 weeks following the first erenumab treatment. A longitudinal Sandwich estimator analysis was used to identify pre- to post-treatment changes in resting-state functional connectivity and brain activations in response to thermal pain. fMRI findings were compared between erenumab treatment-responders vs. erenumab non-responders.

Results

Pre- and post-treatment longitudinal imaging data were available from 32 participants. Average age was 40.3 (+/− 13) years and 29 were female. Pre-treatment average migraine day frequency was 13.8 (+/− 4.7) / 28 days and average headache day frequency was 15.8 (+/− 4.4) / 28 days. Eighteen of 32 (56%) were erenumab responders. Compared to erenumab non-responders, erenumab responders had post-treatment differences in 1) network functional connectivity amongst pain-processing regions, including higher global efficiency, clustering coefficient, node degree, regional efficiency, and modularity, 2) region-to-region functional connectivity between several regions including temporal pole, supramarginal gyrus, and hypothalamus, and 3) pain-induced activations in the middle cingulate, posterior cingulate, and periaqueductal gray matter.

Conclusions

Reductions in migraine day frequency accompanying erenumab treatment are associated with changes in resting state functional connectivity and central processing of extracranial painful stimuli that differ from erenumab non-responders.

Trial registration

clinicaltrials.gov (NCT03773562).

Guidelines of the International Headache Society for Clinic-Based Headache Registries, 1st edition

Clinic-based headache registries collect data for a wide variety of purposes including delineating disease characteristics, longitudinal natural disease courses, headache management approaches, quality of care, treatment safety and effectiveness, factors that predict treatment response, health care resource utilization, clinician adherence to guidelines, and cost-effectiveness. Registry data are valuable for numerous stakeholders, including individuals with headache disorders and their caregivers, healthcare providers, scientists, healthcare systems, regulatory authorities, pharmaceutical companies, employers, and policymakers. This International Headache Society document may serve as guidance for developing clinic-based headache registries. Use of registry data requires a formal research protocol that includes: 1) research aims; 2) methods for data collection, harmonization, analysis, privacy, and protection; 3) methods for human subject protection; and 4) publication and dissemination plans. Depending upon their objectives, headache registries should include validated headache-specific questionnaires, patient reported outcome measures, data elements that are used consistently across studies (i.e., "common data elements"), and medical record data. Amongst other data types, registries may be linked to healthcare and pharmacy claims data, biospecimens, and neuroimaging data. Headache diagnoses should be made according to the International Classification of Headache Disorders diagnostic criteria. The data from well-designed headache registries can provide wide-ranging and novel insights into the characteristics, burden, and treatment of headache disorders and ultimately lead to improvements in the management of patients with headache.

Magnetic resonance spectroscopy studies in migraine

This review summarizes major findings and recent advances in magnetic resonance spectroscopy (MRS) of migraine. A multi database search of PubMed, EMBASE, and Web of Science was performed with variations of magnetic resonance spectroscopy and headache until 20th September 2021. The search generated 2897 studies, 676 which were duplicates and 1836 were not related to headache. Of the remaining 385 studies examined, further exclusions for not migraine (n = 114), and not MRS of human brain (n = 128), and non-original contributions (n = 51) or conferences (n = 24) or case studies (n = 11) or non-English (n = 3), were applied. The manuscripts of all resulting reports were reviewed for their possible inclusion in this manuscript (n = 54). The reference lists of all included reports were carefully reviewed and articles relevant to this review were added (n = 2).Included are 56 studies of migraine with and without aura that involve magnetic resonance spectroscopy of the human brain. The topics are presented in the form of a narrative review. This review aims to provide a summary of the metabolic changes measured by MRS in patients with migraine. Despite the variability reported between studies, common findings focused on regions functionally relevant to migraine such as occipital cortices, thalamic nuclei, cerebellum and cingulate. The most reproducible results were decreased N-acetyl-aspartate (NAA) in cerebellum in patients with hemiplegic migraine and in the thalamus of chronic migraine patients. Increased lactate (Lac) in the occipital cortex was found for migraine with aura but not in subjects without aura. MRS studies support the hypothesis of impaired energetics and mitochondrial dysfunction in migraine. Although results regarding GABA and Glu were less consistent, studies suggest there might be an imbalance of these important inhibitory and excitatory neurotransmitters in the migraine brain. Multinuclear imaging studies in migraine with and without aura, predominantly investigating phosphorous, report alterations of PCr in occipital, parietal, and posterior brain regions. There have been too few studies to assess the diagnostic relevance of sodium imaging in migraine.

The Characteristics of White Matter Hyperintensities in Patients With Migraine

Background

The presence of white matter hyperintensities (WMHs) in migraine is well-documented, but the location of WMH in patients with migraine is insufficiently researched. This study assessed WMH in patients with migraine using a modified version of the Scheltens visual rating scale, a semiquantitative scale for categorizing WMH in periventricular, lobar, basal ganglia, and infratentorial regions.

Methods

In total, 263 patients with migraine (31 men and232 women) enrolled in the American Registry for Migraine Research (ARMR) from Mayo Clinic Arizona and who had clinical brain magnetic resonance imaging (MRI) were included in this study. Those with imaging evidence for gross anatomical abnormalities other than WMHs were excluded. A board-certified neuroradiologist identified WMHs on axial T2 and fluid-attenuated inversion recovery (FLAIR) sequences. WMHs were characterized via manual inspection and categorized according to the scale's criteria.

Results

Results showed that 95 patients (36.1%, mean age: 41.8 years) had no WMHs on axial T2 and FLAIR imaging and 168 patients (63.9%, mean age: 51.4 year) had WMHs. Of those with WMHs, 94.1% (n = 158) had lobar hyperintensities (frontal: 148/158, 93.7%; parietal: 57/158, 36.1%; temporal: 35/158, 22.1%; and occipital: 9/158, 5.7%), 13/168, 7.7% had basal ganglia WMHs, 49/168, 29.1% had periventricular WMHs, and 17/168, 10.1% had infratentorial WMHs. In addition, 101/168 patients (60.1%) had bilateral WMHs and 67/168 (39.9%) had unilateral WMHs (34 right hemisphere/33 left hemisphere).

Discussion

Among ARMR participants who were enrolled by Mayo Clinic Arizona and who had clinical brain MRIs, nearly two-thirds had WMHs. The WMHs were the most common in the frontal lobes. Describing the features of WMHs in those with migraine, and comparing them with WMHs attributable to other etiologies, might be useful for developing classifiers that differentiate between migraine-specific WMH and other causes of WMH.

Preclinical assessment of onabotulinumtoxinA for the treatment of mild traumatic brain injury-related acute and persistent post-traumatic headache

Objective

Investigation of onabotulinumtoxinA in a murine model of acute and persistent post-traumatic headache.

Methods

Mild traumatic brain injury was induced with a weight drop method. Periorbital and hindpaw cutaneous allodynia were measured for 14 days. Mice were then exposed to bright light stress and allodynia was reassessed. OnabotulinumtoxinA (0.5 U) was injected subcutaneously over the cranial sutures at different post-injury time points.

Results

After milt traumatic brain injury, mice exhibited periorbital and hindpaw allodynia that lasted for approximately 14 days. Allodynia could be reinstated on days 14–67 by exposure to stress only in previously injured mice. OnabotulinumtoxinA administration at 2 h after mild traumatic brain injury fully blocked both transient acute and stress-induced allodynia up to day 67. When administered 72 h post-mild traumatic brain injury, onabotulinumtoxinA reversed acute allodynia, but only partially prevented stress-induced allodynia. OnabotulinumtoxinA administration at day 12, when initial allodynia was largely resolved, produced incomplete and transient prevention of stress-induced allodynia. The degree of acute allodynia correlated positively with subsequent stress-induced allodynia.

Conclusion

Mild traumatic brain injury induced transient headache-like pain followed by long lasting sensitization and persistent vulnerability to a normally innocuous stress stimulus, respectively modeling acute and persistent post-traumatic headache.. Administration of onabotulinumtoxinA following the resolution of acute post-traumatic headache diminished persistent post-traumatic headache but the effects were transient, suggesting that underlying persistent mild traumatic brain injury-induced maladaptations were not reversed. In contrast, early onabotulinumtoxinA administration fully blocked both acute post-traumatic headache as well as the transition to persistent post-traumatic headache suggesting prevention of neural adaptations that promote vulnerability to headache-like pain. Additionally, the degree of acute post-traumatic headache was predictive of risk of persistent post-traumatic headache.

Patient-Centered Treatment of Chronic Migraine With Medication Overuse: A Prospective, Randomized, Pragmatic Clinical Trial

BACKGROUND AND OBJECTIVES

Overuse of symptomatic (i.e., acute) medications is common among those with chronic migraine. It is associated with developing frequent headaches, medication side effects, and reduced quality of life. The optimal treatment strategy for patients who have chronic migraine with medication overuse (CMMO) has long been debated. The study objective was to determine whether migraine preventive therapy without switching or limiting the frequency of the overused medication was noninferior to migraine preventive therapy with switching from the overused medication to an alternative medication that could be used on ≤2 d/wk.

METHODS

The Medication Overuse Treatment Strategy (MOTS) trial was an open-label, pragmatic clinical trial, randomizing adult participants 1:1 to migraine preventive medication and (1) switching from the overused medication to an alternative used ≤2 d/wk or (2) continuation of the overused medication with no maximum limit. Participants were enrolled between February 2017 and December 2020 from 34 clinics in the United States, including headache specialty, general neurology, and primary care clinics. The primary outcome was moderate to severe headache day frequency during weeks 9 to 12 and subsequently during weeks 1 to 2 after randomization.

RESULTS

Seven hundred twenty participants were randomized; average age was 44 (SD 13) years; and 87.5% were female. At baseline, participants averaged 22.5 (SD 5.1) headache days over 4 weeks, including 12.8 (SD 6.7) moderate to severe headache days and 21.4 (SD 5.8) days of symptomatic medication use. Migraine preventive medication without switching of the overused medication was not inferior to preventive medication with switching for moderate to severe headache day frequency during weeks 9 to 12 (switching 9.3 [SD 7.2] vs no switching 9.1 [SD 6.8]; p = 0.75, 95% CI -1.0 to 1.3). The treatment strategies also provided similar outcomes during the first 2 weeks (switching 6.6 [SD 3.7] moderate to severe headaches days vs no switching 6.4 [SD 3.6]; p = 0.57, 95% CI -0.4 to 0.7).

DISCUSSION

When reduction in moderate to severe headache days was used as the outcome of interest for the management of CMMO, migraine preventive medication without switching or limiting symptomatic medication is not inferior to migraine preventive medication with switching to a different symptomatic medication with a maximum limit of 2 treatment days per week.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov identifier NCT02764320.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that, for patients who have CMMO, migraine preventive medication without switching or limiting the overused medication is noninferior to migraine preventive medication with switching and limiting symptomatic medication.

Differentiating Between Migraine and Post-traumatic Headache Using a Machine Learning Classifier

OBJECTIVE

The objective was to develop classification models differentiating persistent PTH (PPTH) and migraine using clinical data and MRI-based measures of brain structure and functional connectivity.

BACKGROUND

PTH and migraine commonly have similar phenotypes. Furthermore, migraine is a risk factor for developing PTH, sometimes making it difficult to differentiate PTH from exacerbation of migraine symptoms.

DESIGN/METHODS

Thirty-four individuals with migraine without history of TBI and 48 individuals with mild TBI attributed to PPTH but without history of migraine or prior frequent tension type headache were included. Subjects completed questionnaires assessing headache characteristics, mood, sensory hypersensitivities and cognitive function and underwent MRI imaging during the same day. Clinical features and structural brain measures from T1-weighted imaging, diffusion tensor imaging and functional resting-state measures were included as potential variables. A classifier using ridge logistic regression of principal components (PC) was fit. Since PCs can hinder identification of significant variables in a model, a second regression model was fit directly to the data. In the non-PC based model, input variables were selected based on lowest t-test or chi-square p-value by modality. Average accuracy was calculated using leave-one-out cross validation. The importance of variables to the classifier were examined.

RESULTS

The PC-based classifier achieved an average classification accuracy of 85%. The non-PC based classifier achieved an average classification accuracy of 74.4%. Both classifiers were more accurate at classifying migraine subjects than PPTH. The PC-based model incorrectly classified 9/48 (18.8%) PPTH subjects compared to 3/34 (8.8%) migraine patients, whereas the non-PC classifier incorrectly classed 16/48 (33.3%) vs 5/34 (14.7%) of migraine subjects. Important variables in the non-PC model included static and dynamic functional connectivity values, several questions from the Beck Depression Inventory, and worsening symptoms and headaches with mental activity.

CONCLUSIONS

Multivariate models including clinical characteristics, functional connectivity, and brain structural data accurately classify and differentiate PPTH vs migraine.

A History of Mild Traumatic Brain Injury Is Associated With a a More Severe Long-term Migraine Phenotype

OBJECTIVE

This study aimed to investigate the effect of prior mTBI on the clinical features and disability in patients presenting with migraine.

BACKGROUND

Head injury is a risk factor for chronic migraine (CM) and migraine is a risk factor for persistent headache after mild traumatic brain injury (mTBI).

DESIGN/METHODS

Of 2,161 migraine patients without a diagnosis of post-traumatic headache (PTH) who participated in the American Registry for Migraine Research (ARMR) between February 2016 and March 2020, 1,120 answered questions about a history of mTBI. After controlling for age, gender, and having CM, demographics, headache characteristics, Patient Health Questionnaire-2 (PHQ-2) score, General Anxiety Disorder-7 (GAD-7) grade, and Migraine Disability Assessment Scale (MIDAS) scores were compared between those with a history of mTBI to those without.

RESULTS

Among 1,098 migraine patients, 37.6% (n = 413) had a history of mTBI. The patients with mTBI were more likely to have CM (p = 0.004), dizziness (p = 0.003), vertigo (p = 0.009), and difficulty finding words (p < 0.001). Patients with mTBI had significantly greater scores on the MIDAS (58.6 ± 52.6 vs 50.0 ± 47.8, p = 0.034) and PHQ-2 (1.6 ± 1.8 vs 1.3 ± 1.6, p = 0.012), and had significantly higher proportion of moderate to severe GAD-7 grade (21.7% vs 17.1%, p = 0.017) compared to those without mTBI.

CONCLUSIONS

In patients presenting with migraine, a prior history of mTBI was associated with a diagnosis of chronic migraine, disability, anxiety and depression severity, as well as dizziness, vertigo, and word finding difficulty. A history of mTBI should be assessed in patients presenting with migraine, and people with migraine who have a high exposure risk to mTBI, should be aware of the potential for migraine progression and psychiatric symptoms after mTBI.

Discriminant Subgraph Learning from Functional Brain Sensory Data

The human brain is a complex system with many functional units interacting with each other. This interacting relationship, known as the functional connectivity network (FCN), is critical for brain functions. To learn the FCN, machine learning algorithms can be built based on brain signals captured by sensing technologies such as EEG and fMRI. In neurological diseases, past research has revealed that the FCN is altered. Also, focusing on a specific disease, some part of the FCN, i.e., a sub-network, can be more susceptible than other parts. However, the current knowledge about disease-specific sub-networks is limited. We propose a novel Discriminant Subgraph Learner (DSL) to identify a functional sub-network that best differentiates patients with a specific disease from healthy controls based on brain sensory data. We develop an integrated optimization framework for DSL to simultaneously learn the FCN of each class and identify the discriminant sub-network. Further, we develop tractable and converging algorithms to solve the optimization. We apply DSL to identify a functional sub-network that best differentiates patients with episodic migraine (EM) from healthy controls based on a fMRI dataset. DSL achieved the best accuracy compared to five state-of-the-art competing algorithms.

T2* reduction in patients with acute post-traumatic headache

OBJECTIVES

Although iron accumulation in pain-processing brain regions has been associated with repeated migraine attacks, brain structural changes associated with post-traumatic headache have yet to be elucidated. To determine whether iron accumulation is associated with acute post-traumatic headache, magnetic resonance transverse relaxation rates (T2*) associated with iron accumulation were investigated between individuals with acute post-traumatic headache attributed to mild traumatic brain injury and healthy controls.

METHODS

Twenty individuals with acute post-traumatic headache and 20 age-matched healthy controls underwent 3T brain magnetic resonance imaging including quantitative T2* maps. T2* differences between individuals with post-traumatic headache versus healthy controls were compared using age-matched paired t-tests. Associations of T2* values with headache frequency and number of mild traumatic brain injuries were investigated using multiple linear regression in individuals with post-traumatic headache. Significance was determined using uncorrected p-value and cluster size threshold.

RESULTS

Individuals with post-traumatic headache had lower T2* values compared to healthy controls in cortical (bilateral frontal, bilateral anterior and posterior cingulate, right postcentral, bilateral temporal, right supramarginal, right rolandic, left insula, left occipital, right parahippocampal), subcortical (left putamen, bilateral hippocampal) and brainstem regions (pons). Within post-traumatic headache subjects, multiple linear regression showed a negative association between T2* in the right inferior parietal/supramarginal regions and number of mild traumatic brain injuries and a negative association between T2* in bilateral cingulate, bilateral precuneus, bilateral supplementary motor areas, bilateral insula, right middle temporal and right lingual areas and headache frequency.

CONCLUSIONS

Acute post-traumatic headache is associated with iron accumulation in multiple brain regions. Correlations with headache frequency and number of lifetime mild traumatic brain injuries suggest that iron accumulation is part of the pathophysiology or a marker of mild traumatic brain injury and post-traumatic headache.

Time course of efficacy of atogepant for the preventive treatment of migraine: Results from the randomized, double-blind ADVANCE trial

Background

Atogepant is an oral, small-molecule, calcitonin gene–related peptide receptor antagonist for the preventive treatment of migraine.

Methods

In the double-blind, phase 3 ADVANCE trial, participants with 4–14 migraine days/month were randomized to atogepant 10 mg, 30 mg, 60 mg, or placebo once daily for 12 weeks. We evaluated the time course of efficacy of atogepant for the preventive treatment of migraine. Analyses included change from baseline in mean monthly migraine days during each of the three 4-week treatment periods, change in weekly migraine days during weeks 1–4, and proportion of participants with a migraine on each day during the first week.

Results

We analyzed 873 participants (n = 214 atogepant 10 mg, n = 223 atogepant 30 mg, n = 222 atogepant 60 mg, n = 214 placebo). For weeks 1–4, mean change from baseline in mean monthly migraine days ranged from −3.1 to −3.9 across atogepant doses vs −1.6 for placebo (p < 0.0001). For weeks 5–8 and 9–12, reductions in mean monthly migraine days ranged from −3.7 to −4.2 for atogepant vs −2.9 for placebo (p ≤ 0.012) and −4.2 to −4.4 for atogepant vs −3.0 for placebo (p < 0.0002), respectively. Mean change from baseline in weekly migraine days in week 1 ranged from −0.77 to −1.03 for atogepant vs −0.29 with placebo (p < 0.0001). Percentages of participants reporting a migraine on post-dose day 1 ranged from 10.8% to 14.1% for atogepant vs 25.2% with placebo (p ≤ 0.0071).

Conclusion

Atogepant demonstrated treatment benefits as early as the first full day after treatment initiation, and sustained efficacy across each 4-week interval during the 12-week treatment period.

Clinical trial registration: ClinicalTrials.gov identifier: NCT03777059

Medication Overuse and Headache Burden: Results From the CaMEO Study

Objective

To estimate the relative frequency of acute medication overuse (AMO) among people with episodic migraine and chronic migraine, to characterize the types of acute medications overused for migraine, and to identify factors associated with AMO.

Methods

We analyzed data from the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study (ClinicalTrials.gov, NCT01648530), a cross-sectional and longitudinal internet study that included a systematic sampling of the US population. From September 2012 to November 2013, the CaMEO Study respondents participated in different modules to collect data on the clinical course of migraine, family burden, barriers to care, endophenotypes, and comorbidities. Among people who met the criteria for migraine consistent with the International Classification of Headache Disorders, third edition (ICHD-3), we evaluated types and frequency of medications used for headache/migraine, selected comorbidities, and emergency department (ED) and urgent care (UC) use. AMO was defined by days per month of medication use as specified by ICHD-3 criteria for medication overuse headache (MOH) without the requirement for ≥15 monthly headache days (MHDs). Nested, multivariable binary logistic regression modeling was used to identify factors associated with an increased risk of AMO.

Results

Of 16,789 CaMEO respondents with migraine, 2,975 (17.7%) met the AMO criteria. Approximately 67.9% (2,021/2,975) of AMO respondents reported <15 MHDs. Simple analgesics, combination analgesics, and opioids were the medication classes most commonly overused. Factors associated with AMO in the final multivariable logistic regression model included ≥15 MHDs, moderate to severe disability, severe migraine interictal burden, use of preventive medication, and an ED/UC visit for headache within 6 months.

Conclusions

Approximately two-thirds of respondents with AMO reported <15 MHDs and therefore did not meet the criteria for MOH. Those with AMO had greater disease burden and increased ED/UC utilization relative to people with migraine but not AMO.

Structural aberrations of the brain associated with migraine: A narrative review

OBJECTIVE

To summarize major results from imaging studies investigating brain structure in migraine.

BACKGROUND

Neuroimaging studies, using several different imaging and analysis techniques, have demonstrated aberrations in brain structure associated with migraine. This narrative review summarizes key imaging findings and relates imaging findings with clinical features of migraine.

METHODS

We searched PubMed for English language articles using the key words "neuroimaging" AND/OR "MRI" combined with "migraine" through August 20, 2020. The titles and abstracts of resulting articles were reviewed for their possible inclusion in this manuscript, followed by examination of the full texts and reference lists of relevant articles.

RESULTS

Migraine is associated with structural brain aberrations within regions that participate in pain processing, the processing of other sensory stimuli, multisensory integration, and in white matter fiber tracts. Furthermore, migraine is associated with magnetic resonance imaging T2/fluid-attenuated inversion recovery white matter hyperintensities. Some structural aberrations are correlated with the severity and clinical features of migraine, whereas others are not. These findings suggest that some structural abnormalities are associated with or amplified by recurrent migraine attacks, whereas others are intrinsic to the migraine brain.

CONCLUSIONS

Migraine is associated with aberrant brain structure. Structural neuroimaging studies contribute to understanding migraine pathophysiology and identification of brain regions associated with migraine and its individual symptoms. Additional work is needed to determine the extent to which structural aberrations are a result of recurrent migraine attacks, and perhaps reversible with effective treatment or migraine resolution, versus being intrinsic traits of the migraine brain.