Background Headache is an adverse event of coronavirus 2019 (COVID-19) vaccination. Whether patients with history of headache suffer more from vaccination-induced headaches is unknown. We aimed to uncover if headache patients develop more headaches after COVID-19 mRNA vaccination than healthy controls. Methods We performed a questionnaire survey for nursing staff in our hospital from April to May 2021. Based on baseline characteristics, we divided the participants into migraine, non-migrainous headache, and healthy control, and examined the occurrence and features of headache after COVID-19 vaccinations. Results We included 171 participants (15.2% migraine and 24.6% non-migrainous headache). Headache incidence after vaccinations was significantly higher in the migraine (69.2%) and non-migrainous headache (71.4%) groups than in the healthy control (37.9%) group. The incidence of headaches was significantly higher after the second dose compared to the first (45.6% vs. 20.5%). Conclusion Migraineurs and non-migrainous headache participants developed more headaches compared to the healthy controls after COVID-19 vaccination.

Background Anti-calcitonin gene-related peptide monoclonal antibodies (CGRPmAbs) are a favourable option for patients with migraine who experience distressful headache disability and fail to respond to traditional preventive treatment options. However, since CGRPmAb has been available for only 2 years in Japan, the difference between good and poor responders remains unknown. We aimed to investigate the clinical characteristics of patients with migraine in Japan who responded well to CGRPmAb based on real-world data. Methods We analysed patients who visited Keio University Hospital, Tokyo, Japan, between the 12th of August 2021 and 31st of August 2022, and were prescribed one of three CGRPmAbs (erenumab, galcanezumab, and fremanezumab) for more than 3 months. We recorded the patients’ basic migraine characteristics, such as pain quality, monthly migraine days (MMD)/monthly headache days (MHD), and the number of prior treatment failures. We defined good responders as patients whose MMDs decreased by more than 50% after 3 months of treatment and other patients as poor responders. We compared the baseline migraine characteristics between the two groups and performed logistic regression analysis based on the items that showed statistically significant differences. Results In total, 101 patients were considered eligible for the responder analysis (galcanezumab: 57 (56%), fremanezumab: 31 (31%), and erenumab: 13 (13%)). After 3 months of treatment, 55 (54%) patients achieved ≥ 50% reduction in MMDs. Comparisons between ≥ 50% responders and non-responders revealed that age was significantly higher (p = 0.003), and MHD and total prior treatment failures were significantly lower (p = 0.027, 0.040, respectively), in responders than in non-responders. Age was a positive predictive factor, and the total number of prior treatment failures and past medical history of immuno-rheumatologic diseases were negative predictive factors of CGRPmAb responsiveness in Japanese patients with migraine. Conclusions Patients with migraine who are older, with fewer prior treatment failures and no past history of immuno-rheumatologic disease, may respond well to CGRPmAbs.

Objective To evaluate the efficacy and safety of galcanezumab in patients with migraine in a real-world setting in Japan. Background Galcanezumab is the first anti-calcitonin gene-related peptide monoclonal antibody approved in Japan. To the best of our knowledge, no real-world studies on galcanezumab have been published in any international journal from Japan. Methods We retrospectively examined patients with migraine who received three doses of galcanezumab between August 2021 and February 2022 at the Keio University Hospital. We assessed changes in monthly migraine days, responder rate, and migraine-associated and premonitory symptoms. We also investigated injection site reactions and adverse events. Results Fifty-two patients received three doses of galcanezumab during the study period. Compared with those at baseline, the monthly migraine days decreased by 5.9 days (95% confidence interval, 4.2–7.7) at 3 months. The 50% responder rate was 61.5% at 3 months. A total of 64.9%, 50.0%, and 63.9% of patients showed improvement in the severity of photophobia, phonophobia, and nausea/vomiting, respectively. Premonitory symptoms without subsequent headache were reported in 62.5% of patients. Moreover, injection site reaction was the most common adverse event (34.6%). Conclusion This study revealed the efficacy and safety of galcanezumab for migraineurs in Japan. Galcanezumab also improved migraine-associated symptoms. However, despite a reduction in headaches, premonitory symptoms without subsequent headache were reported in > 50% of the patients at 3 months.

BackgroundMigraine is one of the most common neurological disorders worldwide. Clinical characteristics of migraine may be somewhat different across ethnic groups. Although factors such as stress, lack of sleep, and fasting are known as migraine triggers, the discussion about geographical differences of migraine triggers in Asia is lacking.MethodsIn this study, we performed a narrative review on migraine triggers in Asia. We searched PubMed for relevant papers published between January 2000 and February 2022.ResultsForty-two papers from 13 Asian countries were included. Stress and sleep are the most frequently reported migraine triggers in Asia. There were some differences in migraine triggers in Asian countries: fatigue and weather common in Eastern Asia and fasting common in Western Asia.ConclusionMajority of the common triggers reported by patients with migraine in Asia were stress and sleep, similar to those reported globally, thus showing they are universally important. Some triggers linked to internal homeostasis are influenced by culture (e.g., alcohol, food/eating habit), and triggers related to environmental homeostasis, such as weather, are highly heterogenous between regions.

MotivationVirtual screening, which can computationally predict the presence or absence of protein-compound interactions, has attracted attention as a large-scale, low-cost, and short-term search method for seed compounds. Existing machine learning methods for predicting protein-compound interactions are largely divided into those based on molecular structure data and those based on network data. The former utilize information on proteins and compounds, such as amino acid sequences and chemical structures, and the latter utilize interaction network data, such as data on protein-protein interactions and compound-compound interactions. However, few attempts have been made to combine both types of data in molecular information and interaction networks.ResultsWe developed a deep learning-based method that integrates protein features, compound features, and heterogeneous interactome data to predict protein-compound interactions. The interactome data consist of protein-protein interactions and compound-compound interactions. The performance evaluations show that our deep learning framework for integrating molecular structure data and interactome data outperforms state-of-the-art machine learning methods for protein-compound interaction prediction tasks. This reveals that protein-protein interaction and compound-compound interaction networks capture different perspectives than amino acid sequence homology and chemical structure similarity, and they have a synergistic effect in improving prediction accuracy. Furthermore, experiments on three datasets of different difficulties show that this method is more robust than existing methods in accurately predicting interactions between proteins and compounds that are unseen in the training samples.