对英国生物库中罕见的预测功能缺失变体进行转录本感知分析,阐明新的同工酶-性状关联。

Q2 Computer Science
Rachel A Hoffing, Aimee M Deaton, Aaron M Holleman, Lynne Krohn, Philip J LoGerfo, Mollie E Plekan, Sebastian Akle Serrano, Paul Nioi, Lucas D Ward
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引用次数: 0

摘要

一个基因可以产生多种具有不同分子功能的转录本。罕见变异关联测试通常会汇总单个基因的所有编码变异,而不会考虑变异在转录本异构体中的存在或后果。为了评估转录本感知变异集的效用,我们使用 55558 个不同的转录本特异性变异集汇总了 17035 个蛋白编码基因的罕见预测功能缺失(pLOF)变异。这些变异集与英国生物库中 406921 人的 728 种循环蛋白和 188 种定量表型进行了关联测试。与基于基因的方法相比(pbinom ≤ 2x10-16),转录本特异性方法导致 pLOF 变体降低血清顺式蛋白水平的估计效应更大。此外,使用转录本特异性方法而非基于基因的方法,确定了 251 个数量性状关联具有显著性,包括 PCSK5 转录本 ENST00000376752 和站立高度(转录本特异性统计量,P = 1.3x10-16,效应 = 0.7 SD 下降;基于基因的统计量,P = 0.02,效应 = 0.05 SD 下降)和 LDLR 转录本 ENST00000252444 与脂蛋白 B(转录本特异性统计量,P = 5.7x10-20,效应 = 1.0 SD 增加;基于基因的统计量,P = 3.0x10-4,效应 = 0.2 SD 增加)。这种方法表明,在进行罕见变异关联研究时,考虑 pLOF 对特定转录本同工酶的影响非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transcript-aware analysis of rare predicted loss-of-function variants in the UK Biobank elucidate new isoform-trait associations.

A single gene can produce multiple transcripts with distinct molecular functions. Rare-variant association tests often aggregate all coding variants across individual genes, without accounting for the variants' presence or consequence in resulting transcript isoforms. To evaluate the utility of transcript-aware variant sets, rare predicted loss-of-function (pLOF) variants were aggregated for 17,035 protein-coding genes using 55,558 distinct transcript-specific variant sets. These sets were tested for their association with 728 circulating proteins and 188 quantitative phenotypes across 406,921 individuals in the UK Biobank. The transcript-specific approach resulted in larger estimated effects of pLOF variants decreasing serum cis-protein levels compared to the gene-based approach (pbinom ≤ 2x10-16). Additionally, 251 quantitative trait associations were identified as being significant using the transcript-specific approach but not the gene-based approach, including PCSK5 transcript ENST00000376752 and standing height (transcript-specific statistic, P = 1.3x10-16, effect = 0.7 SD decrease; gene-based statistic, P = 0.02, effect = 0.05 SD decrease) and LDLR transcript ENST00000252444 and apolipoprotein B (transcript-specific statistic, P = 5.7x10-20, effect = 1.0 SD increase; gene-based statistic, P = 3.0x10-4, effect = 0.2 SD increase). This approach demonstrates the importance of considering the effect of pLOFs on specific transcript isoforms when performing rare-variant association studies.

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