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从 gnomAD 数据库分析人类 FTO 基因的编码变异。

Analysis of coding variants in the human FTO gene from the gnomAD database.

机构信息

Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Federal University of Pará, Belém, PA, Brazil.

Federal Rural University of Amazon, Capanema Campus, PA, Brazil.

出版信息

PLoS One. 2022 Jan 6;17(1):e0248610. doi: 10.1371/journal.pone.0248610. eCollection 2022.

Abstract

Single nucleotide polymorphisms (SNPs) in the first intron of the FTO gene reported in 2007 continue to be the known variants with the greatest effect on adiposity in different human populations. Coding variants in the FTO gene, on the other hand, have been little explored, although data from complete sequencing of the exomes of various populations are available in public databases and provide an excellent opportunity to investigate potential functional variants in FTO. In this context, this study aimed to track nonsynonymous variants in the exons of the FTO gene in different population groups employing the gnomAD database and analyze the potential functional impact of these variants on the FTO protein using five publicly available pathogenicity prediction programs. The findings revealed 345 rare mutations, of which 321 are missense (93%), 19 are stop gained (5.6%) and five mutations are located in the splice region (1.4%). Of these, 134 (38.8%) were classified as pathogenic, 144 (41.7%) as benign and 67 (19.5%) as unknown. The available data, however, suggest that these variants are probably not associated with BMI and obesity, but instead, with other diseases. Functional studies are, therefore, required to identify the role of these variants in disease genesis.

摘要

2007 年报道的 FTO 基因第一内含子中的单核苷酸多态性(SNPs)仍然是已知的对不同人群肥胖影响最大的变异。另一方面,FTO 基因中的编码变异很少被探索,尽管公共数据库中提供了各种人群外显子完整测序的数据,为研究 FTO 中的潜在功能变异提供了极好的机会。在这种情况下,本研究旨在利用 gnomAD 数据库追踪不同人群群体中 FTO 基因外显子中的非同义变异,并使用五个公开可用的致病性预测程序分析这些变异对 FTO 蛋白的潜在功能影响。研究结果显示,共有 345 个罕见突变,其中 321 个为错义突变(93%),19 个为终止获得(5.6%),5 个位于剪接区(1.4%)。其中,134 个(38.8%)被归类为致病性,144 个(41.7%)为良性,67 个(19.5%)为未知。然而,现有数据表明,这些变异可能与 BMI 和肥胖无关,而是与其他疾病有关。因此,需要进行功能研究来确定这些变异在疾病发病机制中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b83d/8735611/f4488814aab3/pone.0248610.g001.jpg

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