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罕见的结构变异 (SVs) 可能在阿尔茨海默病 (AD) 中发挥作用. 这项研究在多种人群中确定了SVs,在欧洲,非洲和拉丁美洲亚组的特定基因中发现了暗示性关联. 需要使用更大的样本大小进行进一步的研究来确认.

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科学领域:

  • 基因组学就是基因组学.
  • 神经退行性疾病 神经退行性疾病
  • 生物信息学是一种生物信息学.

背景情况:

  • 结构变异 (SV) 是影响基因功能的大型基因组变异 (>50 bp),但它们在阿尔茨海默氏症 (AD) 中的作用尚不清楚.
  • 调查罕见的SVs (<1%MAF) 提供了一种新的方法来发现AD的遗传贡献.

研究的目的:

  • 来自阿尔茨海默氏病测序项目 (ADSP) 的一个大而多样化的队列中识别和描述罕见的结构变异 (SV).
  • 调查这些罕见的SVs与阿尔茨海默氏病 (AD) 的基因相关性.

主要方法:

  • 在ADSP的17K全基因组序列上使用了一种新的SV调用管道 (Biograph).
  • 在11,890个个体中对194,744个删除,151,858个插入和10,388个反转进行了基因关联分析 (5,585个AD病例,6,305个对照).
  • 使用后勤混合效应模型 (GMMAT) 结合负担测试和SKAT,调整人口结构和共变量,以本费罗尼对显著性进行校正 (p < 6 x 10^-6).

主要成果:

  • 确定了不同人口子组 (欧洲,非洲,拉丁美洲) 的罕见SVs和AD之间的暗示性,但不具有统计意义的关联.
  • 在诸如ACLY (EUR),PARP10 (AFR),ENDOV (LAT),RPL8 (元分析) 和SSPN (聚合分析) 等基因中观察到潜在的关联.
  • 没有基因基因测试达到严格的Bonferroni-corrected显著性值.

结论:

  • 罕见的结构变异 (SVs) 可能有助于阿尔茨海默病 (AD) 的遗传结构.
  • 暗示性关联突出显示了潜在的候选基因,需要进一步调查.
  • 较大的样本大小对于验证这些发现和证实SVs在AD病变发生中的作用至关重要.