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Prediction and analysis of a regulatory SNP map of Major Depressive Disorder

Prediction and analysis of a regulatory SNP map of Major Depressive Disorder
重度抑郁症调节性 SNP 图谱的预测与分析
批准号:
G0701003/1
负责人:
Alasdair MacKenzie
金额:
$128.37万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2008
资助国家:
英国
项目状态:
已结题
起止时间:
2008 至 --

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中文摘要
翻译
重度抑郁症(MDD)是世界上最常见的心理健康问题,在我们的一生中会影响多达25%的人。令人担忧的是,MDD正在增加。 这项研究将通过检查更容易患抑郁症的人的DNA序列的变化来寻找抑郁症的遗传原因。此外,这项研究将确定为什么某些MDD患者对目前的治疗没有反应。以前的这类研究已经检查了基因组中制造蛋白质的区域的可能变化。然而,最近已经证明,个体之间的大多数差异,包括疾病易感性,可能不是由基因本身的变化引起的,而是由对这些基因的开关作用知之甚少的DNA序列引起的。这些开关确保了健康大脑功能所必需的基因只在正确的时间和正确的剂量下用于大脑的正确部位。与基因不同,人们对这些开关知之甚少,因为到目前为止,它们很难找到。然而,由麦肯齐博士领导的团队在识别负责驱动已知与抑郁症、成瘾和炎性疼痛有关的基因表达的开关方面取得了相当大的成功。该项目将把联合收割机麦肯齐博士检测重要开关序列的能力与我们检测这些开关中有害突变的新能力结合起来,这些开关序列占基因组的不到5%。McGuffin教授和Breen博士将分析1000多名患有MDD的人的DNA,以确定特定开关差异的发生是否与MDD的易感性有关。麦肯齐博士和奎因教授将对这些开关差异进行分子生物学研究,以确定受影响的生化途径。此外,Quinn教授将评估这些开关的变体的活性如何受到一些已知抗抑郁药物的影响,以确定MDD药物治疗中变异的遗传原因。通过结合一些新开发的基于计算机的,这项研究具有真实的潜力,可以极大地扩展我们对大脑中关键基因使用的调节机制的理解。以及这些机制的变化如何导致MDD易感性。此外,这项研究将使我们能够研究为什么许多MDD患者对目前的抗抑郁药物没有反应。
英文摘要
Major depressive disorder (MDD) constitutes the most frequently occurring mental health problem in the world and will affect up to 25% of us during our lifetimes. Worryingly, MDD is on the increase. This study will set out to find the genetic causes of MDD by examining changes in the DNA sequence of people who are more susceptible to depression. In addition, this study will determine why certain MDD sufferers do not respond to current treatments.Previous studies of this type have examined possible changes in the regions the genome that make protein. Recently, however, it has been demonstrated that the majority of differences between individuals, including disease susceptibility, may be caused by changes, not in the genes themselves, but in the poorly understood DNA sequences that act as switches for these genes. These switches ensure that genes essential to healthy brain function are only used in the correct parts of the brain at the proper times and in the right dose. Unlike genes, little is known of these switches as, up to now they have been very hard to find. However, teams led by Dr. MacKenzie have had considerable success in identifying switches responsible for driving the expression of genes known to be involved in depression, addiction and inflammatory pain.This project will combine Dr. Mackenzies ability to detect important switch sequences, that make up less than 5% of the genome, with our new ability to detect harmful mutations within these switches. Professor McGuffin and Dr. Breen will then analyse the DNA of over 1000 individuals suffering MDD to determine whether the occurrence of particular switch differences can be associated with susceptibility to MDD. Dr MacKenzie and Prof. Quinn will then carry out molecular biological studies of these switch differences to determine the biochemical pathways affected. In addition, Prof Quinn will evaluate how the activity of variants of these switches are affected by a number of known antidepressant drugs to determine the genetic causes of variation in MDD drug treatments.By combining a number of newly developed computer based, patent sample based and molecular biology techniques this study has the real potential of hugely expanding our understanding of the mechanisms regulating the use of key genes in the brain and how changes on these mechanisms may contribute to susceptibility to MDD. Furthermore, this study will allow us to examine why many MDD sufferers do not respond to current anti-depressive medications.
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How do genetics and epigenetics interact to influence the activity of a context-dependent enhancer?
  • 批准号:
    BB/W017598/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $74.69万
  • 财政年份:
    2023
  • 负责人:
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  • 依托单位:
Determining the effects of genetic variation and early life stress on the regulation of the galanin gene in fat and alcohol selection.
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    BB/N017544/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $53.38万
  • 财政年份:
    2016
  • 负责人:
    Alasdair MacKenzie
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A computer array approach to accelerating the functional prediction of biological systems
  • 批准号:
    BB/D524932/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $5.59万
  • 财政年份:
    2006
  • 负责人:
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  • 依托单位:
国内基金
海外基金
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
    2024
  • 负责人:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
    24.0万元
  • 批准年份:
    2019
  • 负责人:
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  • 依托单位: