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通过系统的治疗和注释,提高多基因评分在阿尔茨海默病中的有用性

Savannah Mwesigwa¹, Yulin Dai¹, Nitesh Enduru¹

¹Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.

Frontiers in genetics

|February 19, 2025

概括

我们开发了一种方法来策划和协调阿尔茨海默病 (AD) 的多基因分数 (PGS),改进遗传风险评估. 我们的R包自动化了变体优先级,为研究人员提供了一个强大的工具.

科学领域:

遗传学遗传学是一种遗传学.
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

多遗传分数 (PGSs) 汇总了复杂疾病风险的遗传变异,但PGS目录缺乏针对阿尔茨海默氏症 (AD) 等特定疾病的标准化.
整合和协调PGS数据对于准确的遗传风险评估和研究至关重要.
对于复杂特征的大规模PGS数据集的策划和优先级设置存在挑战.

研究的目的:

从PGS目录中策划,协调和优先考虑阿尔茨海默病 (AD) 的多基因评分 (PGS) 数据集.
开发一种自动化框架,用于使用等级聚合 (RA) 的变量注释和优先级.
为AD研究人员提供灵活和强大的资源来选择PGS并探索遗传变异.

主要方法:

策划了44个AD PGS数据集,注释了813,257个变体,并从方法上对它们进行了分类.
使用"GWAS显著变体" (GWAS-SV) 方法与GWAS目录对齐得分.
采用了等级聚合 (RA) 技术,包括强大的"Dowdall"方法,并为自动化开发了一个R包"PgsRankRnnotatR".

主要成果:

识别并完善了44个AD PGS数据集,标记了冗余或范围有限的条目.
"多德尔"RA方法在六种评估方法中表现最强.
精心策划的数据集和自动化的R包增强了与AD相关的遗传变异的选择和探索.

结论:

开发的框架提供了一种标准化的方法来策划,协调和优先考虑PGS数据集,提高它们在AD研究中的实用性.
通过多个RA选项自动化PGS数据处理为研究人员提供了灵活的工具.
该框架可扩展到其他复杂疾病,推进遗传风险评估应用.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.PGS 产品目录产品目录遗传变异遗传变异是一种遗传变异.多基因分数的多基因分数排名聚合排名聚合

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