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Structural brain correlates of an operationally defined high-risk phenotype for schizophrenia: a population based study

Structural brain correlates of an operationally defined high-risk phenotype for schizophrenia: a population based study
大脑结构与精神分裂症高风险表型的相关性:一项基于人群的研究
批准号:
G0901885/1
负责人:
Anthony David
金额:
$115.18万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2010
资助国家:
英国
项目状态:
已结题
起止时间:
2010 至 --

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中文摘要
翻译
精神分裂症是一种主要的精神疾病,它在一生中影响着大约1%的人口,造成毁灭性的影响。钥匙?精神错乱?症状包括幻觉、妄想以及情绪、动机和智力方面的问题。最近的研究表明,许多人都有类似的症状,但只有少数人会发展成全面的疾病。研究那些单独有症状的人?谁处于危险之中?精神分裂症的研究可能会教会我们很多关于是什么导致了这种疾病。要做到这一点,一种方法是利用一项名为雅芳父母和子女纵向研究(ALSPAC)的大型人口调查。我们一直在追踪数千名出生在雅芳的人,看看他们可能会出现什么健康问题。ALSPAC的患者现在大约17岁,正在接受研究,看看他们中哪些人有这些精神病样症状。我们建议在这项工作的基础上,选择一组具有代表性的有症状和无症状的患者,并要求他们进行核磁共振扫描。核磁共振是一种常用且非常安全的脑部扫描技术。它显示了大脑的详细结构,包括灰质和白质。然后,可以应用统计技术,找出两组之间的任何不同领域。我们预测某些区域将出现异常,如果是这样的话,这将极大地增加我们对这种疾病的了解,甚至可能导致新的治疗方法或方法来预防这种临床疾病的显现。
英文摘要
Schizophrenia is THE major psychiatric disorder and it affects around 1% of the population in their lifetime with devastating effects. Key ?psychotic? symptoms include hallucinations, and delusions as well as problems with emotions, motivation and intellect. It has recently been shown that many people have similar symptoms but only a few go on to develop the full-blown illness. Studying people with symptoms alone who are ?at risk? of schizophrenia is likely to teach us a lot about what it is that causes the illness. One way of doing this is to make use of a large survey of the population known as the Avon Longitudinal Study of Parents and Children (ALSPAC). This has been following several thousand people born in Avon to see what health problems they might develop. The people in ALSPAC are now about 17 years old and are being studied to see which of them has these psychotic-like symptoms. We propose to build on this work by selecting a representative group of those with and those without symptoms and asking them to have an MRI scan. MRI is a commonly used and very safe brain scanning technique. It shows up the detailed structured of the brain, both grey and white matter. Statistical techniques can then be applied which will pick out any areas that are different between the two groups. We predict that certain areas will be abnormal and if so this will greatly increase our understanding of the illness and may even lead to new treatments or ways of preventing the clinical disorder manifesting itself.
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