Migraine/Headache

Migraine is heritable and formally diagnosed by structured criteria that require presence of some but not all possible migraine symptoms which include aura, several distinct manifestations of pain, nausea/vomiting, and sensitivity to light or sound. The most recent genome-wide genetic association study (GWAS) for migraine identified 38 loci. We investigated whether 46 single-nucleotide polymorphisms (SNPs), i.e., genetic variants, at these loci may have especially pronounced, i.e., selective, association with migraine presenting with individual symptoms compared to absence of migraine. Selective genetic associations of SNPs were evaluated through a likelihood framework in the Women's Genome Health Study (WGHS), a population-based cohort of middle-aged women including 3,003 experiencing migraine and 18,108 not experiencing migraine, all with genetic information. SNPs at 12 loci displayed significant selective association for migraine subclassified by specific symptoms, among which six selective associations are novel. Symptoms showing selective association include aura, nausea/vomiting, photophobia, and phonophobia. The selective associations were consistent whether the women met all formal criteria for diagnostic for migraine or lacked one of the diagnostic criteria, formally termed probable migraine. Subsequently, we performed latent class analysis of migraine diagnostic symptoms among 69,861 women experiencing migraine from the WGHS recruitment sample to assess whether there were clusters of specific symptoms that might also have a genetic basis. However, no globally robust latent migraine substructures of diagnostic symptoms were observed nor were there selective genetic associations with specific combinations of symptoms revealed among weakly supported latent classes. The findings extend previously reported selective genetic associations with migraine diagnostic symptoms while supporting models for shared genetic susceptibility across all qualifying migraine at many loci.

The aims of the present systematic review were to explore the prevalence of migraine with anxiety exclusively and determine if and why there are likely to be differences across genders. Migraine is a very common neurological disorder and cause of productive disability worldwide that is more frequent in women of childbearing age than males. Previous studies have frequently demonstrated comorbidity of migraine and other psychiatric disorders. Although the prevalence of migraine across gender is well-established there are few if any systematic reviews on the prevalence of migraine comorbidity with anxiety cross-genders. The present systematic review included prevalence studies, clinic-based and cohort studies that reported the frequency of migraine with anxiety within the study sample. Eleven studies were included in the review after screening by two independent reviewers. Studies included participants who were 16 years and older diagnosed with migraine. The main findings of this review indicated that anxiety is a major comorbidity of migraine worldwide, with a wide range (16-83%) of prevalence and a mean of ~43% of patients experiencing comorbid symptoms. Subjective anxiety symptoms appear to be greater among males with migraine than females which could be attributable to both environmental and/or hormonal and genetic predispositions. The results reemphasize the high prevalence of migraine and comorbid anxiety symptoms worldwide while showing that although migraine is far more prevalent among women in general co-morbidity of migraine with anxiety unfolds a different gender difference. The results highlight the significance of exploring the impact of existing and pre-existing comorbid conditions of patients with migraines and further consideration into their diagnostic and treatment strategies.

The present study aimed to investigate the use of imaging biomarkers to predict the outcome of acupuncture in patients with migraine without aura (MwoA). Forty-one patients with MwoA received 4 weeks of acupuncture treatment and two brain imaging sessions at the Beijing Traditional Chinese Medicine Hospital affiliated with Capital Medical University. Patients kept a headache diary for 4 weeks before treatment and during acupuncture treatment. Responders were defined as those with at least a 50% reduction in the number of migraine days. The machine learning method was used to distinguish responders from non-responders based on pre-treatment brain gray matter (GM) volume. Longitudinal changes in GM predictive regions were also analyzed. After 4 weeks of acupuncture, 19 patients were classified as responders. Based on 10-fold cross-validation for the selection of GM features, the linear support vector machine produced a classification model with 73% sensitivity, 85% specificity, and 83% accuracy. The area under the receiver operating characteristic curve was 0.7871. This classification model included 10 GM areas that were mainly distributed in the frontal, temporal, parietal, precuneus, and cuneus gyri. The reduction in the number of migraine days was correlated with baseline GM volume in the cuneus, parietal, and frontal gyri in all patients. Moreover, the left cuneus showed a longitudinal increase in GM volume in responders. The results suggest that pre-treatment brain structure could be a novel predictor of the outcome of acupuncture in the treatment of MwoA. Imaging features could be a useful tool for the prediction of acupuncture efficacy, which would enable the development of a personalized medicine strategy.