The impact of schizophrenia-associated copy number variants on cortical network dynamics

精神分裂症相关拷贝数变异对皮质网络动态的影响

• 批准号: MR/W028395/1
• 负责人: Jeremy Hall
• 金额: $ 255.1万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 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%2FW028395%2F1
• 关键词: impact; schizophrenia; associated; copy; number

Schizophrenia (SZ) is a disabling mental health disorder that affects approximately 1% of the UK population. The condition typically has its onset in adolescence or early adulthood and is associated with changes in how reality is perceived (reality distortion) and difficulties in thinking. SZ has significant long-term impacts on the sufferer and their family. Unfortunately, over the past decades we have made little progress in improving the treatment of this disorder. This is because we lack adequate understanding of the biological causes of schizophrenia.Recent major advances in research into the genetic basis of schizophrenia now offer hope of better understanding of the biological basis of SZ, potentially opening up new avenues for early diagnosis and treatment. One of the most striking genetic findings has been that changes in chromosomal structure, referred to as Copy Number Variants (CNVs), can significantly increase risk for schizophrenia. Studying people with these schizophrenia-associated CNVs (SZ-CNVs) therefore offers a new route to understanding the brain changes associated with risk for the disorder.In the current proposal we aim to investigate how some of the most common SZ-CNVs affect brain function. We hypothesise that these different SZ-CNVs have common effects on brain function by altering the regulation of specific types of neurons in the brain cortex. We further hypothesise that this affects the way different neurons communicate with each, contributing to the reality distortion and thinking difficulties seen in the disorder. The human brain is difficult to investigate directly because of its inaccessibility. We will therefore combine different methods to investigate the impact of SZ-CNVs on the brain. Firstly, we will use human brain imaging to determine changes in brain activity and connectivity in young people carrying SZ-CNVs. Secondly, we will study mice carrying similar chromosomal changes to allow us to investigate in more depth than is possible in humans. Finally, we will study the changes in firing and connectivity in human neurons derived from patients with SZ-CNVs.These different methods will enable us to build up a more complete picture of the way these SZ-CNVs affect the brain than any single technique alone could. However, it remains a challenge to compare and integrate data across these methods. To allow us to do this we will use computer modelling to combine and integrate our findings. We will subsequently investigate the ability of these computer models to predict cognitive difficulties and psychiatric symptoms in people with SZ-CNVs, including the early symptoms of schizophrenia. The refinement and testing of these models will represent a means of improving our understanding of the pathological effects of SZ-CNVs.Overall, this work will enable us to advance understanding of how SZ-CNVs impact on brain function and connectivity. The insights we will gain will represent an important step towards improving understanding of the biological causes of schizophrenia, with the aim of enhancing the early diagnosis and treatment of the condition.

精神分裂症（SZ）是一种致残性精神健康障碍，影响约1%的英国人口。这种情况通常在青春期或成年早期发作，并与如何感知现实（现实扭曲）和思维困难的变化有关。SZ对患者及其家庭有显著的长期影响。不幸的是，在过去的几十年里，我们在改善这种疾病的治疗方面几乎没有取得进展。这是因为我们对精神分裂症的生物学原因缺乏足够的了解。最近对精神分裂症遗传基础的研究取得了重大进展，现在有望更好地了解SZ的生物学基础，为早期诊断和治疗开辟新的途径。最引人注目的遗传学发现之一是染色体结构的变化（称为拷贝数变体（CNV））可以显着增加精神分裂症的风险。因此，研究患有这些精神分裂症相关CNVs（SZ-CNVs）的人提供了一条新的途径来了解与疾病风险相关的大脑变化。在目前的提议中，我们的目标是调查一些最常见的SZ-CNVs如何影响大脑功能。我们假设这些不同的SZ-CNV通过改变大脑皮层中特定类型神经元的调节对大脑功能有共同的影响。我们进一步假设，这会影响不同神经元之间的交流方式，导致现实扭曲和思维困难。人类的大脑很难直接研究，因为它是不可接近的。因此，我们将联合收割机不同的方法来研究SZ-CNVs对大脑的影响。首先，我们将使用人脑成像来确定携带SZ-CNVs的年轻人大脑活动和连接的变化。其次，我们将研究携带类似染色体变化的小鼠，使我们能够比人类更深入地研究。最后，我们将研究SZ-CNVs患者的神经元放电和连接的变化，这些不同的方法将使我们能够建立一个更完整的图片，这些SZ-CNVs影响大脑的方式比任何单一的技术可以。然而，在这些方法之间比较和整合数据仍然是一个挑战。为了让我们做到这一点，我们将使用计算机建模来联合收割机和整合我们的发现。随后，我们将研究这些计算机模型预测SZ-CNVs患者认知困难和精神症状（包括精神分裂症的早期症状）的能力。这些模型的完善和测试将代表一种手段，提高我们对SZ-CNVs的病理影响的理解。总的来说，这项工作将使我们能够推进对SZ-CNVs如何影响大脑功能和连接的理解。我们将获得的见解将是朝着提高对精神分裂症生物学原因的理解迈出的重要一步，目的是加强对这种疾病的早期诊断和治疗。

项目成果

Neurodevelopmental dimensional assessment of young children at high genomic risk of neuropsychiatric conditions.

• DOI: 10.1002/jcv2.12162
• 发表时间: 2023-06
• 期刊: JCPP advances