Using computational modelling to characterise and plan treatments for schizophrenia

使用计算模型来描述和规划精神分裂症的治疗

• 批准号: MR/W011751/1
• 负责人: Rick Adams
• 金额: $ 186.1万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW011751%2F1
• 关键词: Using; computational; modelling; characterise; plan

Schizophrenia is a mental disorder that involves symptoms such as hallucinations, delusions, and cognitive and motivational impairments. It affects a large number of people - more than 500,000 in the UK alone - and can cause lifelong disability.We currently only have one family of drugs that can treat psychotic symptoms (delusions and hallucinations). These were discovered in the 1950s, and they block a receptor found in nerve cells in the brain: the dopamine 2 receptor. They help two thirds of people suffering from psychosis, but the remainder have ongoing symptoms. Despite intensive research, we have not found any alternative treatments for psychosis, and no treatment at all for cognitive impairment. Lots of evidence indicates that dysfunction in another receptor also makes a major contribution to psychosis: the NMDA receptor. The NMDA receptor exists all over the brain, on various kinds of cells - some excitatory (E cells), some inhibitory (I cells). Slightly different subtypes of the NMDA receptor exist on these different cells, and in different parts of the brain. Different strands of evidence from psychosis research indicate that the primary problem in schizophrenia might be NMDA receptor dysfunction on either E or I cells specifically. There might be different groups of patients with E or I cell dysfunction, for example. Or I cells might try to compensate for NMDA receptor dysfunction on E cells, by reducing their activity.Pharmaceutical companies have produced many drugs that can act at NMDA receptors, and despite some promising early results, all these drugs have failed large scale clinical trials. One likely reason is that not all patients with the same diagnosis have the same underlying causes of those symptoms. For example, there are many causes of breathlessness (asthma, pneumonia, heart failure, lung fibrosis, etc), and all require different treatments. There may well be numerous underlying causes of psychosis symptoms: for example, E cell problems in some, I cell problems in others. These groups would need treatments specifically targeted to E or I cells respectively.The aim of this project is to find ways of identifying these subgroups with 'low E' or 'low I' function, and at what stage they might best be targeted. I will do this using a variety of methods, but all are based around the use of simple tasks (e.g. listening to tones) whilst electrical signals in the brain are recorded using electroencephalography (EEG). I will use computational models to estimate E and I cell function from these recorded EEG signals.I will study datasets of participants with schizophrenia or psychosis at different stages of their illness and also a very large dataset of young people at risk of developing psychosis. I will also study mice who will undergo the same simple tasks, and who will be given low doses of drugs that cause either 'low E' or 'low I' states. The purpose of all these experiments is to establish i) which cells (E or I) would be the best to target with an existing NMDA receptor-based drug, and ii) when (at what illness stage) that drug should be given. In Part 2 of the project, I will test these predictions in a sample of 100 people with early schizophrenia. I will use computational models of their brain signals to estimate whether they have 'low E' and/or 'low I' pathology. I will then give them a drug boosting E cell function (for example) for 3 months, and measure its effects on symptoms and cognition. The key question is: can my model estimate of E or I function predict the effects of the drug? If so, this could mean we could use these models to assign treatments for psychosis, and test this approach in a large scale clinical trial.

精神分裂症是一种精神障碍，包括幻觉、妄想、认知和动机障碍等症状。它影响了大量的人-仅在英国就有50多万人-并可能导致终身残疾。我们目前只有一个家族的药物可以治疗精神病症状（妄想和幻觉）。这些物质是在20世纪50年代发现的，它们阻断了大脑神经细胞中的一种受体：多巴胺2受体。他们帮助三分之二的精神病患者，但其余的人有持续的症状。尽管进行了深入的研究，我们还没有发现任何替代治疗精神病的方法，也没有任何治疗认知障碍的方法。大量证据表明，另一种受体的功能障碍也对精神病做出了重要贡献：NMDA受体。NMDA受体存在于整个大脑中，存在于各种细胞上-一些兴奋性（E细胞），一些抑制性（I细胞）。NMDA受体的亚型略有不同，存在于这些不同的细胞和大脑的不同部位。来自精神病研究的不同证据表明，精神分裂症的主要问题可能是E或I细胞上的NMDA受体功能障碍。例如，可能有不同的E或I细胞功能障碍患者群体。或者I细胞可能试图通过降低E细胞上的NMDA受体的活性来弥补它们的功能障碍。制药公司已经生产了许多可以作用于NMDA受体的药物，尽管有一些有希望的早期结果，但所有这些药物都没有通过大规模的临床试验。一个可能的原因是，并非所有诊断相同的患者都有这些症状的相同潜在原因。例如，呼吸困难的原因有很多（哮喘，肺炎，心力衰竭，肺纤维化等），并且都需要不同的治疗方法。精神病症状可能有许多潜在的原因：例如，在某些情况下，E细胞问题，在其他情况下，I细胞问题。这些群体将需要分别针对E或I细胞的治疗。该项目的目的是找到识别这些具有“低E”或“低I”功能的亚群的方法，以及在什么阶段最适合靶向它们。我将使用多种方法来做到这一点，但所有方法都是基于使用简单任务（例如听音调），同时使用脑电描记术（EEG）记录大脑中的电信号。我将使用计算模型从这些记录的EEG信号中估计E细胞和I细胞的功能，我将研究处于不同疾病阶段的精神分裂症或精神病患者的数据集，以及具有发展精神病风险的年轻人的非常大的数据集。我还将研究小鼠，这些小鼠将进行相同的简单任务，并将被给予低剂量的药物，导致“低E”或“低I”状态。所有这些实验的目的是确定i）哪些细胞（E或I）最适合用现有的基于NMDA受体的药物靶向，以及ii）何时（在什么疾病阶段）应该给予该药物。在项目的第二部分，我将在100名早期精神分裂症患者的样本中测试这些预测。我将使用他们大脑信号的计算模型来估计他们是否有“低E”和/或“低I”的病理。然后，我会给他们一种增强E细胞功能的药物（例如）3个月，并测量其对症状和认知的影响。关键问题是：我的模型对E或I函数的估计能否预测药物的作用？如果是这样的话，这可能意味着我们可以使用这些模型来分配精神病的治疗方法，并在大规模的临床试验中测试这种方法。

项目成果

Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training.

• DOI: 10.1093/schbul/sbac029
• 发表时间: 2022-06-21
• 期刊: SCHIZOPHRENIA BULLETIN
• 影响因子: 6.6
• 作者: Hauke, D. J.;Roth, V;Karvelis, P.;Adams, R. A.;Moritz, S.;Borgwardt, S.;Diaconescu, A. O.;Andreou, C.
• 通讯作者: Andreou, C.