Integrating circadian, neuroimaging and genetic data to investigate major depression and bipolar disorder

整合昼夜节律、神经影像学和遗传数据来研究重度抑郁症和双相情感障碍

• 批准号: 2284218
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2284218
• 关键词: Integrating; circadian; neuroimaging; genetic; data

Studentship strategic priority area:Basic and Clinical ResearchKeywords: Circadian rhythms, depression, bipolar disorder, genetics, brain imaging.Disruption to daily circadian rhythms is associated with greater risk of mood disorder and impaired cognitive ability. However, so far most studies have used subjective measures of rhythmicity, small or cross-sectional samples, and haven't examined potential mediators and moderators of effects. This interdisciplinary project will use chronobiological, neuroimaging and genetic data from the landmark UK Biobank cohort. The cohort includes lifestyle, sociodemographic and genetic data for over 500,000 individuals and brain MRI for over 30,000; and our group has already derived objective accelerometry-based measures of circadian rest-activity rhythms for 100,000 individuals. Using this wealth of data, machine learning and regression methods can help determine which objective rhythmicity variables best predict mood disorder and related outcomes; and whether the influence of circadian disruption on mood and cognition is partly due to effects on brain structure, or is moderated by genetic factors. Using data from linked health records of UK Biobank participants, models will be developed to assess whether mood disorder episodes can be predicted from a combination of circadian rhythmicity, neuroimaging, genetic, sociodemographic and lifestyle factors. This project will provide training in a wide range of research skills relevant to precision medicine, including epidemiology, genomics, neuroimaging and machine learning.

学生奖学金战略优先领域：基础和临床研究关键词：昼夜节律，抑郁症，双相情感障碍，遗传学，脑成像。日常昼夜节律的破坏与情绪障碍和认知能力受损的风险增加有关。然而，到目前为止，大多数研究都使用了主观测量的节奏，小样本或横截面样本，并没有检查潜在的介质和调节效果。这个跨学科的项目将使用时间生物学，神经成像和遗传数据从具有里程碑意义的英国生物库队列。该队列包括超过500，000人的生活方式，社会人口统计学和遗传数据以及超过30，000人的大脑MRI;我们的团队已经为100，000人获得了基于加速度计的昼夜休息活动节律的客观测量。利用这些丰富的数据，机器学习和回归方法可以帮助确定哪些客观的节律性变量最能预测情绪障碍和相关结果;以及昼夜节律中断对情绪和认知的影响是否部分归因于对大脑结构的影响，或者受遗传因素的调节。使用来自英国生物银行参与者的相关健康记录的数据，将开发模型来评估是否可以从昼夜节律，神经成像，遗传，社会人口和生活方式因素的组合中预测情绪障碍发作。该项目将提供与精准医学相关的广泛研究技能培训，包括流行病学，基因组学，神经成像和机器学习。