Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis.

Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis.
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通过计算机模拟饱和诱变鉴定克隆造血驱动突变。

DOI:
10.1101/2023.12.13.23299893
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发表时间:
2023
期刊:
medRxiv : the preprint server for health sciences
影响因子:
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通讯作者:
González-Pérez,Abel
González-Pérez,Abel
中科院分区:
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文献类型:
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作者:
Demajo,Santiago;Ramis-Zaldivar,JoanEnric;Muiños,Ferran;Grau,MiguelL;Andrianova,Maria;López-Bigas,Núria;González-Pérez,Abel

文献摘要

相似文献

克隆造血是一种由影响某些基因的体细胞突变驱动的造血干细胞克隆扩增的现象。最近,CH与血液恶性肿瘤、心血管疾病和其他疾病的发展有关。虽然最常突变的CH驱动基因已经被确定,但能够启动这一现象的突变的系统景观仍然缺乏。在这项研究中,我们训练了12个最常见的CH基因的机器学习模型,以识别它们的驱动突变。这些模型优于基于这些基因功能的先验知识的专家策划的规则。此外,他们在英国生物银行近50万供体中识别CH驱动突变的应用再现了CH驱动突变与年龄以及几种疾病和病症流行之间的已知关联。因此,我们建议这些模型支持在健康个体中准确识别CH。意义:我们开发并验证了基因特异性机器学习模型来识别CH驱动突变,显示了它们在专家策划规则方面的优势。这些模型可以支持新测序个体中CH突变的鉴定和临床解释。见Arends和Jaiswal的相关评论,第1581页
Clonal hematopoiesis (CH) is a phenomenon of clonal expansion of hematopoietic stem cells driven by somatic mutations affecting certain genes. Recently, CH has been linked to the development of hematologic malignancies, cardiovascular diseases, and other conditions. Although the most frequently mutated CH driver genes have been identified, a systematic landscape of the mutations capable of initiating this phenomenon is still lacking. In this study, we trained machine learning models for 12 of the most recurrent CH genes to identify their driver mutations. These models outperform expert-curated rules based on prior knowledge of the function of these genes. Moreover, their application to identify CH driver mutations across almost half a million donors of the UK Biobank reproduces known associations between CH driver mutations and age, and the prevalence of several diseases and conditions. We thus propose that these models support the accurate identification of CH across healthy individuals.Significance:We developed and validated gene-specific machine learning models to identify CH driver mutations, showing their advantage with respect to expert-curated rules. These models can support the identification and clinical interpretation of CH mutations in newly sequenced individuals.See related commentary by Arends and Jaiswal, p. 1581