从序列共变异中预测的 de novo CACNA1D Ca2+通道变异的致病性
Xuechen Tang1, Nadine J Ortner2, Yuliia V Nikonishyna2
1Department of General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck, University of Innsbruck, A-6020, Innsbruck, Austria.
European journal of human genetics : EJHG
|March 30, 2024
概括
一种新的进化分析方法预测了CACNA1D基因变异的致病性,有助于诊断自闭症谱系障碍和相关的神经疾病. 这种方法有助于澄清与遗传突变相关的风险.
科学领域:
- 遗传学和分子生物学
- 神经科学是一个神经科学.
- 生物物理学的生物物理.
背景情况:
- 电压控制的L型Cav1.3 Ca2+通道对神经元刺激,心律,听力和荷尔蒙分泌至关重要.
- 编码Cav1.3α1亚单元的CACNA1D基因的突变会导致与自闭症谱系障碍和其他神经系统疾病相关的严重门缺陷.
- 鉴定到的CACNA1D变种的数量越来越多,需要可靠的方法来预测它们的致病性,因为功能性测试通常是不可用的或耗时的.
研究的目的:
- 开发和验证一种生物信息学工具,使用进化分析来预测人类CACNA1D误解变异的病原性.
- 提供一种独立于临床诊断和电生理学数据的方法来评估变异病原性.
主要方法:
- 在动物王国中使用了Cav1.3α1-亚单元序列的进化分析.
- 利用共同变异分析来识别残留物-残留物合并生成病原性预测得分.
- 通过将其与已知的致病变体进行比较并重新检查现有的分类来验证预测得分.
主要成果:
- 共同变异模型准确地预测了先前识别的致病性CACNA1D变异.
- 该得分支持以前被归类为可能致病的变体的致病性.
- 在80种变异中,有18种被重新分类或标记为基于进化分析的重新审查.
- 对V584I变种的电生理学测试证实了显著的门变化和致病风险.
结论:
- 进化共同变异分析提供了一种有价值的,独立的方法来评估CACNA1D变异的致病性.
- 这种生物信息方法可以帮助疑似CACNA1D相关疾病的患者在临床决策中.
- 这项研究强调了进化数据在理解遗传变异的功能影响方面的有用性.
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