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.

精神病是全球发病率和死亡率的主要原因。其中，强迫症（OCD）是第四大常见的精神病病，影响了全球超过250万人。在WHO最近的报道中，强迫症以及相关疾病被列为全球健康损失的第六大贡献，并出现在损失残疾的十大原因中。不幸的是，尽管大量工作已经证明了导致这种使人衰弱疾病的认知和生物学因素，但转化为临床环境的转化仍大大失速。一个障碍是，我们没有可以在个别患者中使用的认知和精神疾病模型。此外，我们倾向于仅在单个时间点上进行测量，这些时间点仅提供个人当前状态的快照，并且对观察到的效果是否稳定的时间或状态依赖性稳定。这是一个主要的局限性，因为精神疾病在几天/几个月内表现出受试者内部的大量症状波动，并且在治疗中进行介入时。该项目利用新的方法来阐明受试者在受试者水平上治疗干预的机制和潜在目标。就像咳嗽可能有许多不同的原因一样，OCD可能是由各种不同来源造成的。例如，强迫症患者可以表现出增加形成重复行为的倾向（例如习惯性手洗），将注意力转移到思想模式（例如，认为会发生不好的事情会发生）或处理不确定信息的问题（例如，如果碰到门柄，会发生细菌的机会）。我的研究旨在阐明哪种认知过程可能与给定患者进行量身定制干预更为相关。为此，我将使用数学模型来构建所谓的“增长图表”的等效物。这些是小儿医疗保健的基石，通常用于确定儿童身高还是体重是否相对于参考人群的预期轨迹。 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.最近，使用神经影像学技术，我发现组平均值不代表单一主题网络组织，这可能携带特质信息。因此，我将使用相同的神经影像学方法，以高度采样和纵向方法为中心，以测量每个个体的使用驱动式可塑性，并确定神经回路在几周/月的时间过程中如何变化。两个不同的强迫症患者可能病得很重，但出于截然不同的原因。确定与每个患者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，药物和特定的认知行为疗法的结合可能对反映特定神经回路改变的一定分数的人有效。然后，临床医生可以将这些信息与他们的专家临床评估结合使用，以做出更好的治疗决定。通过这种方式，该项目旨在为单独量身定制的方法的功效建立证据基础，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方法。通过研究使用驱动的大脑可塑性，该研究还旨在识别旨在诱导大脑和行为改变的疗法的机制和潜在靶标。