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结合小鼠模型和全基因组关联研究,突出了与人类肾功能相关的新基因。

Combination of mouse models and genomewide association studies highlights novel genes associated with human kidney function.

机构信息

Division of Genetic Epidemiology, Medical Center, University of Freiburg, Freiburg, Germany; Genetics and Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Freiburg, Germany; Renal Division, Medical Center, University of Freiburg, Freiburg, Germany.

Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bolzano, Italy.

出版信息

Kidney Int. 2016 Oct;90(4):764-73. doi: 10.1016/j.kint.2016.04.004. Epub 2016 Jun 3.

Abstract

Genomewide association studies have identified numerous chronic kidney disease-associated genetic variants, but often do not pinpoint causal genes. This limitation was addressed by combining Mouse Genome Informatics with human genomewide association studies of kidney function. Genes for which mouse models showed abnormal renal physiology, morphology, glomerular filtration rate (GFR), or urinary albumin-to-creatinine ratio were identified from Mouse Genome Informatics. The corresponding human orthologs were then evaluated for GFR-associated single-nucleotide polymorphisms in 133,814 individuals and urinary albumin-to-creatinine ratio-associated SNPs in 54,451 individuals in genome-wide association studies meta-analysis of the CKDGen Consortium. After multiple testing corrections, significant associations with estimated GFR in humans were identified for single-nucleotide polymorphisms in 2, 7, and 17 genes causing abnormal GFR, abnormal physiology, and abnormal morphology in mice, respectively. Genes identified for abnormal kidney morphology showed significant enrichment for estimated GFR-associated single-nucleotide polymorphisms. In total, 19 genes contained variants associated with estimated GFR or the urinary albumin-to-creatinine ratio of which 16 mapped into previously reported genomewide significant loci. CYP26A1 and BMP4 emerged as novel signals subsequently validated in a large, independent study. An additional gene, CYP24A1, was discovered after conditioning on a published nearby association signal. Thus, our novel approach to combine comprehensive mouse phenotype information with human genomewide association studies data resulted in the identification of candidate genes for kidney disease pathogenesis.

摘要

全基因组关联研究已经确定了许多与慢性肾脏病相关的遗传变异,但通常无法确定致病基因。通过将 Mouse Genome Informatics 与人类肾功能全基因组关联研究相结合,解决了这一局限性。从 Mouse Genome Informatics 中确定了小鼠模型显示异常肾脏生理学、形态、肾小球滤过率 (GFR) 或尿白蛋白与肌酐比的基因。然后,在 CKDGen 联盟的全基因组关联研究荟萃分析中,对 133814 个人的 GFR 相关单核苷酸多态性和 54451 个人的尿白蛋白与肌酐比相关 SNPs 评估了相应的人类同源物。在多次测试校正后,在人类中发现了与估计的 GFR 相关的单核苷酸多态性与导致小鼠 GFR 异常、生理异常和形态异常的 2、7 和 17 个基因中的单核苷酸多态性显著相关。确定的异常肾脏形态基因显示出与估计的 GFR 相关的单核苷酸多态性显著富集。总共,有 19 个基因包含与估计的 GFR 或尿白蛋白与肌酐比相关的变体,其中 16 个映射到先前报道的全基因组显著位点。CYP26A1 和 BMP4 作为新的信号出现,并随后在一项大型独立研究中得到验证。在对已发表的附近关联信号进行条件处理后,发现了另一个基因 CYP24A1。因此,我们将综合小鼠表型信息与人类全基因组关联研究数据相结合的新方法导致了候选基因的确定用于肾脏疾病发病机制。

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