Precision Psychiatry for Compulsivity

强迫症的精准精神病学

• 批准号: MR/Y011384/1
• 负责人: Matilde Vaghi
• 金额: $ 185.15万
• 依托单位: University of East Anglia
• 依托单位国家: 英国
• 项目类别: Fellowship
• 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%2FY011384%2F1
• 关键词: Precision; Psychiatry; Compulsivity

Psychiatric disorders are a leading cause of morbidity and mortality worldwide. Among those, obsessive-compulsive disorder (OCD) is the 4th most common psychiatric condition, affecting more than 2.5 million people worldwide. In recent WHO reports, OCD, together with related disorders, is listed as the 6th largest contribution of health loss globally and appears in the top 10 causes of years lost to disability. Unfortunately, even though a substantial body of work has documented cognitive and biological factors that contribute to this debilitating disease, translation to clinical settings has significantly stalled. One barrier is that we don't have models of cognition and mental illness that can be used in individual patients. Additionally, we tend to get measurements only at single timepoints, which provide only a snapshot of the individual's current state and limited understanding of whether observed effects are stable over time or state dependent. This is a major limitation as psychiatric disorders show within-subject large symptomatic fluctuations over days/months and when intervening therapeutically. This project leverages new approaches to shed light on mechanisms of and potential targets for therapeutic intervention at the subject level. Much like a cough can have many different causes, OCD can result from a variety of different sources. For example, OCD patients can show increased propensity to form repetitive behaviours (e.g., habitual hand washing), difficulties in shifting attention away from patterns of thoughts (e.g., thinking that something bad will happen) or problems in dealing with uncertain information (e.g., chances of getting germs if touching a door handle). My research aims at clarifying which cognitive process might be more relevant for a given patient to enable tailored intervention. To this aim, I will use mathematical models to build the equivalent of the so-called "growth charts". These are a cornerstone of pediatric healthcare and are routinely used to identify whether a child height or weight is on the expected trajectory with respect to a reference population. Similarly, by building charts for different cognitive domains, I aim at providing tools to identify whether a person is on the expected trajectory enabling detection of individuals with high atypicality and prediction in terms of treatment response.Because repetitive behaviours and rigid patterns of thinking become habitual over a prolonged period, my research will also investigate how neural circuits change while forming these inflexible patterns of behavior and thinking. Recently, using neuroimaging techniques, I found that group averages are not representative of single subject network organization, which might carry idiosyncratic information. Therefore, I will use the same neuroimaging approach, centered on a highly sampled and longitudinal methodology, to measure use-driven plasticity in each individual and identify how neural circuits change over the time course of weeks/months. Two different individuals with OCD may both be sick but for very different reasons. Identifying the cognitive mechanism most relevant for each patient can be used to indicate that a certain treatment is likely to be most effective. For example, a combination of a medication and a specific cognitive behavioural therapy may be effective in people with a certain set of scores reflecting alterations of specific neural circuits. A clinician could then use that information, in combination with their expert clinical evaluation, to make a better treatment decision. In this way, the project aims to establish the evidence base for the efficacy of individually tailored approaches and provide clinicians with data grounded in biology to improve treatment of OCD and related disorders. By investigating use-driven brain plasticity, this research also aims at identifying mechanisms and potential targets of therapies aimed at inducing brain and behavioural changes.

精神疾病是世界范围内发病率和死亡率的主要原因。其中，强迫症（OCD）是第四大最常见的精神疾病，影响全球超过250万人。在最近的世界卫生组织报告中，强迫症与相关疾病一起被列为全球健康损失的第六大贡献，并出现在因残疾而损失的十大原因中。不幸的是，尽管大量的工作已经记录了导致这种使人衰弱的疾病的认知和生物因素，但转化为临床环境已显着停滞。一个障碍是我们没有可以用于个体患者的认知和精神疾病模型。此外，我们倾向于只在单个时间点进行测量，这只提供了个体当前状态的快照，并且对观察到的效应是否随时间稳定或依赖于状态的理解有限。这是一个主要的局限性，因为精神疾病在几天/几个月内以及在进行治疗干预时显示出受试者内的大的症状波动。该项目利用新的方法来阐明在受试者水平上进行治疗干预的机制和潜在靶点。就像咳嗽可以有许多不同的原因一样，强迫症可以由各种不同的来源引起。例如，强迫症患者可以表现出形成重复行为的倾向增加（例如，习惯性洗手），难以将注意力从思维模式转移开（例如，认为会发生不好的事情）或处理不确定信息的问题（例如，如果触摸门把手，可能会感染细菌）。我的研究旨在澄清哪种认知过程可能与特定患者更相关，以便进行量身定制的干预。为此，我将使用数学模型来构建所谓的“增长图”。这些是儿科医疗保健的基石，通常用于确定儿童身高或体重是否在参考人群的预期轨迹上。同样，通过为不同的认知领域构建图表，我的目标是提供工具来识别一个人是否在预期的轨迹上，从而能够检测出具有高重复性的个体并预测治疗反应。由于重复行为和僵化的思维模式在很长一段时间内会成为习惯，我的研究也将探讨神经回路在形成这些僵化的行为和思维模式时是如何变化的。最近，我使用神经成像技术发现，群体平均值并不能代表单个受试者的网络组织，它可能携带特殊的信息。因此，我将使用相同的神经成像方法，以高度采样和纵向方法为中心，测量每个人的使用驱动可塑性，并确定神经回路如何在数周/数月的时间过程中变化。两个不同的强迫症患者可能都生病了，但原因完全不同。识别与每个患者最相关的认知机制可以用于指示某种治疗可能是最有效的。例如，药物和特定认知行为疗法的组合可能对具有反映特定神经回路改变的特定分数集的人有效。然后，临床医生可以使用这些信息，结合他们的专家临床评估，做出更好的治疗决定。通过这种方式，该项目旨在为个性化方法的有效性建立证据基础，并为临床医生提供基于生物学的数据，以改善强迫症和相关疾病的治疗。通过研究使用驱动的大脑可塑性，这项研究还旨在确定旨在诱导大脑和行为变化的治疗机制和潜在靶点。