重新评估MUC5B与特发性肺纤维化患者生存的关系

IF 1 4区 生物学 Q4 GENETICS & HEREDITY Annals of Human Genetics Pub Date : 2023-08-03 DOI:10.1111/ahg.12522
Siyang Cai, Richard J. Allen, Louise V. Wain, Frank Dudbridge
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引用次数: 0

摘要

粘蛋白5B基因(MUC5B)的变异与特发性肺纤维化的风险密切相关。然而,相同的变异与延长的生存时间有关。先前的研究表明,这可以用指数事件偏差来解释,真正的影响是降低生存率。在这里,我们使用最新的方法和数据集重新评估了这一说法。我们发现先前分析的统计假设不成立,相反,我们将最近的修正加权最小二乘、MR-RAPS和Slope-hunter方法应用于先前的数据和更新的联合元分析。然而,这些分析并没有产生增加或减少生存率的有力证据。在对降低生存率的真实影响的模拟中,我们没有观察到指数事件偏差导致观察到的提高生存率的任何现实情况。因此,我们认为MUC5B确实会降低生存率的说法是不安全的。应该寻求其他解释来解释观察到的与生存率增加的关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Reassessing the association of MUC5B with survival in idiopathic pulmonary fibrosis

A variant in the mucin 5B gene (MUC5B) is strongly associated with the risk of idiopathic pulmonary fibrosis. However, the same variant is associated with increased survival time. Previous work suggested that this may be explained by index event bias, with the true effect being to decrease survival. Here, we reassessed this claim using more recent methods and datasets. We found that the statistical assumptions of the previous analysis did not hold, and instead, we applied recent methods of corrected weighted least squares, MR-RAPS and Slope-hunter to both the previous data and an updated consortium meta-analysis. However, these analyses did not yield robust evidence for increased or decreased survival. In simulations of a true effect of decreased survival, we did not observe any realistic scenario in which index event bias led to an observed effect of increased survival. We therefore regard as unsafe the claim that MUC5B has a true effect of decreased survival. Alternative explanations should be sought to explain the observed association with increased survival.

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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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