Suppr超能文献

脑连接的超级变体识别。

Super-variants identification for brain connectivity.

机构信息

Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.

出版信息

Hum Brain Mapp. 2021 Apr 1;42(5):1304-1312. doi: 10.1002/hbm.25294. Epub 2020 Nov 24.

Abstract

Identifying genetic biomarkers for brain connectivity helps us understand genetic effects on brain function. The unique and important challenge in detecting associations between brain connectivity and genetic variants is that the phenotype is a matrix rather than a scalar. We study a new concept of super-variant for genetic association detection. Similar to but different from the classic concept of gene, a super-variant is a combination of alleles in multiple loci but contributing loci can be anywhere in the genome. We hypothesize that the super-variants are easier to detect and more reliable to reproduce in their associations with brain connectivity. By applying a novel ranking and aggregation method to the UK Biobank databases, we discovered and verified several replicable super-variants. Specifically, we investigate a discovery set with 16,421 subjects and a verification set with 2,882 subjects, where they are formed according to release date, and the verification set is used to validate the genetic associations from the discovery phase. We identified 12 replicable super-variants on Chromosomes 1, 3, 7, 8, 9, 10, 12, 15, 16, 18, and 19. These verified super-variants contain single nucleotide polymorphisms that locate in 14 genes which have been reported to have association with brain structure and function, and/or neurodevelopmental and neurodegenerative disorders in the literature. We also identified novel loci in genes RSPO2 and TMEM74 which may be upregulated in brain issues. These findings demonstrate the validity of the super-variants and its capability of unifying existing results as well as discovering novel and replicable results.

摘要

识别与大脑连接性相关的遗传生物标志物有助于我们了解遗传对大脑功能的影响。在检测大脑连接性与遗传变异体之间的关联时,一个独特且重要的挑战是,该表型是一个矩阵而不是一个标量。我们研究了一种用于遗传关联检测的新的超级变异体概念。类似于但不同于经典的基因概念,超级变异体是多个基因座中等位基因的组合,但贡献的基因座可以位于基因组中的任何位置。我们假设超级变异体在与大脑连接性的关联中更容易检测和更可靠地重现。通过应用一种新的排序和聚合方法对英国生物银行数据库进行分析,我们发现并验证了几个可重复的超级变异体。具体来说,我们研究了一个包含 16421 名受试者的发现集和一个包含 2882 名受试者的验证集,它们是根据发布日期形成的,验证集用于验证发现阶段的遗传关联。我们在染色体 1、3、7、8、9、10、12、15、16、18 和 19 上鉴定了 12 个可重复的超级变异体。这些经过验证的超级变异体包含单核苷酸多态性,这些多态性位于 14 个基因中,这些基因在文献中已被报道与大脑结构和功能以及神经发育和神经退行性疾病有关。我们还在基因 RSPO2 和 TMEM74 中发现了新的基因座,这些基因座在大脑问题中可能被上调。这些发现证明了超级变异体的有效性,以及它将现有结果统一并发现新的可重复结果的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1849/7927294/81f8c750d170/HBM-42-1304-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验