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从文献中治愈罕见疾病变体:评估与焦点中的肌酸运输缺陷的差距

Erica L Lyons¹, Daniel Watson¹, Mohammad S Alodadi¹

¹Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.

|August 16, 2023

概括

在研究中报告的许多罕见疾病变体并非公开可访问,阻碍了基因诊断和研究. 改善数据可访问性和变异解释对于促进罕见疾病的理解和治疗至关重要.

科学领域:

遗传学是一个遗传学.
生物信息学是一种生物信息学.
罕见疾病罕见疾病

背景情况:

罕见疾病影响全球人口的4-8%,经常带来诊断挑战,缺乏经批准的治疗方法.
基因测序为更快的诊断和治疗开发提供了潜力,但由于变异解释困难和数据可访问性问题而受到阻碍.
对于已公布的罕见疾病变异的公共可访问性程度仍然在很大程度上是未知的.

研究的目的:

调查公开数据库中已公布的罕见疾病变异的可访问性.
从科学文献中选和分析与X结合的肌酸载体缺乏症 (CTD) 相关的变异.
将策划变异的病原性赋值与计算预测进行比较.

主要方法:

对SLC6A8基因的变体,症状和功能数据的文献挖掘.
协调精选变体和评估它们在公共数据库中的存在.
变异性致病性赋值与影响算法的预测的比较.

主要成果:

从文献中发现的24%的致病变体在分析的公共数据库中没有被发现.
只有65%的已公布变体从至少一个算法获得了准确的致病性预测.
精选的数据包括详细的临床背景和变体的功能信息.

结论:

已公布的变种病原性数据可能无法获得,阻碍了诊断和研究.
从文献中获得的临床和功能细节对于准确的病原性评估至关重要.
文本挖掘和综合分析管道在改善罕见疾病的变异治愈和病原性赋值方面显示出前景.

关键词:

在CTD中,CTD是CTD.基因变异的基因变异文学策划文学策划罕见疾病是一种罕见的疾病.在 SLC6A8A8 中.文本挖掘 (Text Mining) 是一种文字挖掘方式.变体数据库变体数据库

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