Headache · 2026
A phenome-wide association study reveals novel phenotypic determinants of migraine risk in the UK Biobank.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Shi Changhe, Li Shuangjie, Liang Yuanyuan, Ma Dongrui, Hu Zhengwei, Wang Yunchao, Wang Zhiyun, Qi Shasha, Hao Xiaoyan, Li Mengjie, Zuo Chunyan, Hao Chenwei, Feng Yanmei, Sun Yuemeng, Wang Chen, Yang Ruwei, Yang De, Wang Yonggang, Mao Chengyuan, Sun Shilei
Аннотация
OBJECTIVE: To identify genetic and phenotypic determinants of migraine susceptibility and progression using a large-scale, hypothesis-free approach.
BACKGROUND: Migraine is a common neurological disorder with a substantial individual and societal burden. While risk factors are known, hypothesis-driven approaches may overlook contributors.
METHODS: We analyzed data from 502,364 UK Biobank participants (aged 37-73 years; recruited 2006-2010) to assess associations between migraine and 2824 phenotypes, including observational associations and associations with migraine polygenic risk scores. Time-dependent associations were evaluated, and causality was assessed. Follow-up extended from baseline through to November 30, 2024, with a median of ~14.7 years.
RESULTS: Our analyses identified 253 phenotypes significantly associated with migraine risk, 191 phenotypes associated with migraine PRS, and 87 overlapping between the two approaches. Cox regression analysis confirmed 84 robust time-dependent associations and highlighted novel risk factors, such as oral ulcers (adjusted hazard ratio [aHR] = 1.14, 95% confidence interval [CI]: 1.02-1.28, q = 2.54 × 10-2), lower limb obesity (aHR = 1.01, 95% CI: 1.00-1.02, q = 3.52 × 10-4), and hormone replacement therapy (aHR = 1.39, 95% CI: 1.29-1.50, q = 1.95 × 10-17). MR analysis also revealed causal associations with emotional fluctuations (inverse-variance weighting odds ratio [IVW OR] 4.10, 95% CI = 1.76-9.53, q = 1.00 × 10-2), neuroticism (IVW OR = 1.12, 95% CI = 1.07-1.08, q = 1.24 × 10-5), general health ratings (IVW OR = 1.81, 95% CI = 1.43-2.29, q = 3.30 × 10-2), and fatigue (IVW OR = 1.94, 95% CI = 1.35-2.79, q = 5.73 × 10-36). However, the association with paracetamol use (IVW OR = 9.65 × 104, 95% CI = 1.67 × 104-5.57 × 105, q = 5.73 × 10-36) had uncertain directionality on Steiger testing and should be interpreted cautiously. In total, 87 genetic and phenotypic determinants of migraine were identified, offering new therapeutic targets involving inflammatory and insulin-like growth factor 1 (IGF-1) -related pathways.
CONCLUSIONS: This comprehensive analysis provides new insights into the genetic and phenotypic factors that influence migraine. The findings suggest new targets for therapeutic intervention and provide a basis for the development of precision prevention and clinical management strategies.
BACKGROUND: Migraine is a common neurological disorder with a substantial individual and societal burden. While risk factors are known, hypothesis-driven approaches may overlook contributors.
METHODS: We analyzed data from 502,364 UK Biobank participants (aged 37-73 years; recruited 2006-2010) to assess associations between migraine and 2824 phenotypes, including observational associations and associations with migraine polygenic risk scores. Time-dependent associations were evaluated, and causality was assessed. Follow-up extended from baseline through to November 30, 2024, with a median of ~14.7 years.
RESULTS: Our analyses identified 253 phenotypes significantly associated with migraine risk, 191 phenotypes associated with migraine PRS, and 87 overlapping between the two approaches. Cox regression analysis confirmed 84 robust time-dependent associations and highlighted novel risk factors, such as oral ulcers (adjusted hazard ratio [aHR] = 1.14, 95% confidence interval [CI]: 1.02-1.28, q = 2.54 × 10-2), lower limb obesity (aHR = 1.01, 95% CI: 1.00-1.02, q = 3.52 × 10-4), and hormone replacement therapy (aHR = 1.39, 95% CI: 1.29-1.50, q = 1.95 × 10-17). MR analysis also revealed causal associations with emotional fluctuations (inverse-variance weighting odds ratio [IVW OR] 4.10, 95% CI = 1.76-9.53, q = 1.00 × 10-2), neuroticism (IVW OR = 1.12, 95% CI = 1.07-1.08, q = 1.24 × 10-5), general health ratings (IVW OR = 1.81, 95% CI = 1.43-2.29, q = 3.30 × 10-2), and fatigue (IVW OR = 1.94, 95% CI = 1.35-2.79, q = 5.73 × 10-36). However, the association with paracetamol use (IVW OR = 9.65 × 104, 95% CI = 1.67 × 104-5.57 × 105, q = 5.73 × 10-36) had uncertain directionality on Steiger testing and should be interpreted cautiously. In total, 87 genetic and phenotypic determinants of migraine were identified, offering new therapeutic targets involving inflammatory and insulin-like growth factor 1 (IGF-1) -related pathways.
CONCLUSIONS: This comprehensive analysis provides new insights into the genetic and phenotypic factors that influence migraine. The findings suggest new targets for therapeutic intervention and provide a basis for the development of precision prevention and clinical management strategies.