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.

精神疾病是全世界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，影响着全球250多万人。在世卫组织最近的报告中，强迫症连同相关疾病被列为全球健康损失的第六大原因，并出现在残疾损失年数的十大原因之列。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，但将其转化为临床环境却明显停滞不前。一个障碍是，我们没有认知和精神疾病的模型，可以用于个别患者。此外，我们倾向于只在单个时间点进行测量，这只提供了个人当前状态的快照，并且对观察到的影响是随时间稳定还是依赖于状态的理解有限。这是一个主要的限制，因为精神障碍在受试者内部表现出几天/几个月的症状波动，并且在进行干预治疗时。该项目利用新的方法来阐明在学科水平上治疗干预的机制和潜在目标。就像咳嗽有很多不同的原因一样，强迫症也有很多不同的原因。例如，强迫症患者可能表现出越来越倾向于形成重复行为（例如，习惯性洗手），难以将注意力从思维模式中转移（例如，认为会发生不好的事情），或者在处理不确定信息时出现问题（例如，触摸门把手可能会感染细菌）。我的研究旨在阐明哪一种认知过程可能与特定患者更相关，从而实现量身定制的干预。为此，我将使用数学模型来构建所谓的“增长图表”。这些是儿科保健的基石，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建立图表，我的目标是提供工具来确定一个人是否在预期的轨迹上，从而检测出具有高度非典型性的个体，并在治疗反应方面进行预测。由于重复的行为和僵化的思维模式在长时间内会成为习惯，我的研究还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，利用神经成像技术，我发现群体平均值不能代表单一主体的网络组织，这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的可塑性，并确定神经回路在数周/数月的时间过程中是如何变化的。两个不同的强迫症患者可能都生病了，但原因却截然不同。识别与每个病人最相关的认知机制可以用来表明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结合可能对具有特定神经回路变化的特定分数的人有效。然后，临床医生可以利用这些信息，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治疗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，本研究还旨在确定旨在诱导大脑和行为改变的治疗机制和潜在靶点。