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在 190,000 个外显子组中,利用基于功能信息核的测试,识别可解释的基因 - 生物标志物关联。

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes.

机构信息

Digital Health - Machine Learning, Hasso Plattner Institute, University of Potsdam, Digital Engineering Faculty, 14482, Potsdam, Germany.

Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), 13125, Berlin, Germany.

出版信息

Nat Commun. 2022 Sep 10;13(1):5332. doi: 10.1038/s41467-022-32864-2.

DOI:10.1038/s41467-022-32864-2
PMID:36088354
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9464252/
Abstract

Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene-based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for missense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood-ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.

摘要

在这里,我们对英国生物库中的 191971 个人的 30 个血液生物标志物进行了外显子范围的罕见遗传变异关联研究。我们比较了单独功能变异类别的基于基因的关联测试,以提高可解释性,并确定了 193 个显著的基因-生物标志物关联。与生物标志物相关的基因在赋予孟德尔疾病方面的富集度约为 4.5 倍。除了进行加权基于基因的变异连锁测试外,我们还设计并应用了特定于变异类别的基于核的测试,这些测试整合了错义变异、剪接和 RNA 结合蛋白结合的定量功能变异效应预测。对于这些测试,我们提出了似然比和得分测试的计算效率组合,与单独的得分测试相比,发现了 36%的更多关联,同时还控制了第一类错误。基于核的测试比它们的基于基因连锁的对应测试识别出了 13%的更多关联,并且在存在功能获得性错义变异时具有优势。我们为错义变异引入了基于氨基酸位置的局部连锁,并使用它来解释关联并识别 PIEZO1 中的潜在新功能获得性变异。我们的结果表明,在进行罕见变异关联测试时,研究不同功能机制的好处,并证明罕见变异对生物标志物变异性的普遍贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/c0bdb8939bb1/41467_2022_32864_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/cec43682f570/41467_2022_32864_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/6e7c6ae21f61/41467_2022_32864_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/c3796d0ffcaa/41467_2022_32864_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/149590a33c6d/41467_2022_32864_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/c0bdb8939bb1/41467_2022_32864_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/cec43682f570/41467_2022_32864_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/6e7c6ae21f61/41467_2022_32864_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/c3796d0ffcaa/41467_2022_32864_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/149590a33c6d/41467_2022_32864_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40da/9464252/c0bdb8939bb1/41467_2022_32864_Fig5_HTML.jpg

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