Hub for Metabolic Psychiatry

代谢精神病学中心

• 批准号: MR/Z503563/1
• 负责人: Daniel Smith
• 金额: $ 475.08万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FZ503563%2F1
• 关键词: Hub; Metabolic; Psychiatry

Metabolic psychiatry is a critical but under-researched area. Individuals with severe mental illness (SMI) are at increased risk of obesity, diabetes, cardiovascular disease and premature mortality. There are established bidirectional mechanisms between SMI and metabolic disorders and recent research suggests that metabolic interventions may be therapeutic for SMI.The Hub for Metabolic Psychiatry will have three overarching objectives: a) to drive discovery science in metabolic psychiatry; b) to develop and test novel metabolism-based treatment approaches for SMI in collaboration with people with lived experience of SMI; and c) to build UK-wide capacity for future metabolic psychiatry research and clinical innovation.We will have four experimental workstreams:1. Genomics and causal inference: Data from genomics research has identified that adiposity traits are causally related to major depressive disorder. There are also positive genetic correlations between diabetes and SMI but the causal direction of these associations is unclear. Further, there may be important differences in these associations according to ethnicity/ancestry. This workstream will use causal inference methods such as Mendelian randomisation to better understand the shared biology of SMI and metabolic disorders.2. Health informatics and data science: We will use data linkage within multiple national and international datasets to investigate obesity/diabetes and SMI, with a focus on identifying patterns of comorbidity and predictors of both psychiatric and metabolic outcomes. These datasets include SCI-Diabetes data in Scotland, virtual patient cohorts from the NHS Information Services Division, Edinburgh DataLoch, UK-wide Clinical Practice Research Datalink, and multiple national-level datasets from Denmark.3. Metabolic biomarkers of clinical outcomes in SMI: We will identify metabolomic biomarkers of SMI and conduct a 12-month prospective study to assess how changes in metabolic profile relate to clinical and functional outcomes. This workstream will deploy several innovative data collection methods, including continuous monitoring of metabolic biomarkers, radar-based and actigraph assessments of sleep and circadian rhythms, ecological momentary assessments of mental state and state-of-the-art metabolomics analyses.4. Co-developing and testing novel metabolism-based interventions for SMI: Working closely with the James Lind alliance and The McPin Foundation, we will co-develop and assess the acceptability and therapeutic potential of a range of metabolic interventions as novel treatments for SMI, including digital approaches, chrononutrition (time restricted eating), the ketogenic diet, low carb diets, metformin and GLP1 receptor antagonists. This work will prioritise and co-design future clinical trials of metabolic interventions for SMI.Two additional cross-cutting workstreams will feed into the four experimental workstreams:5. Data analysis and open science workstream: We will develop and test statistical approaches - including dynamic structural equation modelling and machine learning - for each of the workstreams above and create a data curation and data sharing platform to maximise the open science opportunities of this work.6. Patient and public involvement, engagement and dissemination workstream: The McPin Foundation will help with each of the workstreams to ensure that people with lived experience of SMI are at the heart of this work, from experimental design to dissemination and knowledge exchange activities.Overall, the Hub for Metabolic Psychiatry represents an innovative programme of lived experience involvement, discovery science and clinical research within an area that is extremely high priority for people with SMI and their families. It fills an important gap in the current research landscape and will place the UK at the forefront of future metabolic psychiatry research and innovation.

代谢精神病学是一个关键但研究不足的领域。患有严重精神疾病（SMI）的人患肥胖症、糖尿病、心血管疾病和过早死亡的风险增加。代谢精神病学中心将有三个首要目标：a）推动代谢精神病学的科学发现; B）与有生活经验的人合作，开发和测试新的基于代谢的治疗方法，以治疗SMI;以及c）为未来的代谢精神病学研究和临床创新建立全英国的能力。基因组学和因果推理：基因组学研究的数据已经确定肥胖特征与重度抑郁症有因果关系。糖尿病和SMI之间也存在正的遗传相关性，但这些关联的因果方向尚不清楚。此外，根据种族/血统，这些关联可能存在重要差异。该工作流程将使用因果推理方法，如孟德尔随机化，以更好地了解SMI和代谢紊乱的共同生物学。健康信息学和数据科学：我们将使用多个国家和国际数据集内的数据链接来调查肥胖/糖尿病和重度精神病指数，重点是确定合并症的模式以及精神和代谢结果的预测因素。这些数据集包括苏格兰的SCI糖尿病数据、来自NHS信息服务部的虚拟患者队列、爱丁堡DataLoch、英国范围内的临床实践研究数据链以及丹麦的多个国家级数据集。SMI临床结局的代谢生物标志物：我们将确定SMI的代谢组学生物标志物，并进行为期12个月的前瞻性研究，以评估代谢特征的变化与临床和功能结局的关系。该工作流程将部署几种创新的数据收集方法，包括持续监测代谢生物标志物，基于雷达和活动仪的睡眠和昼夜节律评估，精神状态的生态瞬时评估和最先进的代谢组学分析。共同开发和测试针对SMI的新型代谢干预措施：与James Lind联盟和McPin基金会密切合作，我们将共同开发和评估一系列代谢干预措施作为SMI新型治疗方法的可接受性和治疗潜力，包括数字方法，时间限制饮食，生酮饮食，低碳饮食，二甲双胍和GLP 1受体拮抗剂。这项工作将优先考虑并共同设计未来的SMI代谢干预临床试验。数据分析和开放科学工作流程：我们将为上述每个工作流程开发和测试统计方法，包括动态结构方程建模和机器学习，并创建数据管理和数据共享平台，以最大限度地利用这项工作的开放科学机会。患者和公众参与、参与和传播工作流程：McPin基金会将帮助每一个工作流程，以确保具有SMI生活经验的人是这项工作的核心，从实验设计到传播和知识交流活动。总体而言，代谢精神病学中心代表了生活经验参与的创新计划，发现科学和临床研究领域，这是极高的优先级与SMI的人和他们的家庭。它填补了当前研究领域的一个重要空白，并将使英国处于未来代谢精神病学研究和创新的前沿。