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When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
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血液中的T细胞受体 (TCR) 多样性与晚发性阿尔茨海默病 (LOAD) 或轻度认知障碍 (MCI) 有边际联系. 较低的TCR多样性可能表明发展LOAD或MCI的风险更高.

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科学领域:

  • 免疫学 免疫学 免疫学
  • 神经科学是一个神经科学.
  • 遗传学 遗传学 是一个

背景情况:

  • 晚发性阿尔茨海默氏症 (LOAD) 是老年人中常见的一种痴呆症.
  • 风险因素包括年龄,性别,轻度认知障碍 (MCI) 和APOE e4基因型.
  • 适应性免疫系统,特别是T细胞,在粉样β清除中发挥作用,潜在的基于血液的免疫特征与LOAD相关.

研究的目的:

  • 研究血液中的T细胞受体 (TCR) 序列多样性作为LOAD的潜在生物标志物.
  • 使用机器学习探索TCR多样性和LOAD/MCI状态之间的关联.

主要方法:

  • 使用自适应生物技术的immunoSEQ分析了体内TCRβ链序列多样性.
  • 辛普森的生产性克隆性和莫里西塔-霍恩指数被用来衡量TCR多样性和曲目相似性.
  • 模糊的C-means集群,一种无监督的机器学习方法,用于识别疾病特异性模式.

主要成果:

  • 与LOAD+MCI参与者相比,在非LOAD参与者中观察到较高的TCR序列多样性的显著趋势 (p=0.027).
  • 在调整年龄和性别后,这种关联在统计学上没有显著意义.
  • 机器学习聚类显示了与临床诊断的适度一致,通过结合APOE基因型得到改善.

结论:

  • 降低TCR多样性表明与LOAD或MCI的边际关联.
  • 未来的研究将利用TCR序列的机器学习来识别特定疾病的克隆类型,并开发LOAD的诊断模型.