Verification of novel methods to identify migraines using genetic polymorphism analysis and spectral analysis of heart rate variability

Research Project

Project/Area Number	18K15413
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 52010:General internal medicine-related
Research Institution	Shinshu University
Principal Investigator	Taira Chiaki 信州大学, 学術研究院保健学系, 助教 (40779310)
Project Period (FY)	2018-04-01 – 2021-03-31
Project Status	Completed (Fiscal Year 2020)
Budget Amount *help	¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000) Fiscal Year 2020: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000) Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000) Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords	ASTN2 / PHACTR1 / 心拍変動解析 / LF/HF比 / 片頭痛 / 緊張型頭痛 / SNP genotyping / 頭痛 / SNP
Outline of Final Research Achievements	Two major causes of primary headache disorders are migraine and tension-type headache, and differentiating between them is particularly important for appropriate treatments. However, useful diagnostic methods to differentiate between them have not yet been developed. In this study, we assessed the usability of novel methods combining genetic analysis of migraine-associated single nucleotide polymorphisms and spectral analysis of heart rate variability to identify migraines. A family history of headache disorders and A allele of ASTN2 (rs6478241) and/or A allele of PHACTR1 (rs9349379) is associated with migraines. Moreover, the LF/HF ratio determined via spectral analysis may be a good diagnostic method to differentiate migraines. A decline in the LF/HF ratio reflects the predominant state of the parasympathetic nerve, and our data suggest that migraineurs may always be prone to induced cerebral vasodilation associated with parasympathetic activity.
Academic Significance and Societal Importance of the Research Achievements	頭痛鑑別では、血液検査所見や画像所見などのバイオマーカーに関する項目が含まれていないことが、他疾患の基準と比べ特徴的な点である。頭痛関連SNPsを用いて各オッズ比から片頭痛のかかりやすさを数値化し、心拍変動解析によるLF/HF比を定量的に検出することで、より客観的に、より正確性をもって、一次性頭痛を鑑別することが可能となる。本研究成果により、医師の熟練度や主観だけでなく、客観的検査データを伴った新規頭痛鑑別法の応用が期待される。