美国宾夕法尼亚大学Katalin Susztak小组利用表观基因组和转录组分析确定肾脏疾病的核心细胞类型、基因和可靶向机制。相关论文于2022年6月16日在线发表在《自然—遗传学》杂志上。

研究人员在150万个体中定义了与肾脏功能的遗传关系，并确定了878个（126个新）基因座。研究人员绘制了443个肾脏的甲基组、686个样本的转录组和57229个肾脏细胞的单细胞开放染色质的基因型效应图。遗传性分析显示，甲基化变异对遗传性的解释比基因表达大。研究人员提出了一个多阶段的优先排序策略，并对87%的肾脏功能位点的目标基因进行优先排序。分析结果强调了近端肾小管和新陈代谢在肾脏功能调节中的关键作用。此外，SLC47A1在肾脏疾病中的因果作用在SLC47a1遗传性缺失的小鼠和携带功能缺失变体的人类个体中得到了界定。

这些研究结果强调了大量和单细胞表观基因组信息在将全基因组关联研究，转化为识别复杂性状的因果基因、细胞起源和机制方面的关键作用。

据悉，全世界有超过8亿人患有肾脏疾病，然而对肾脏功能障碍的机制却知之甚少。

附：英文原文

Title: Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease

Author: Liu, Hongbo, Doke, Tomohito, Guo, Dong, Sheng, Xin, Ma, Ziyuan, Park, Joseph, Vy, Ha My T., Nadkarni, Girish N., Abedini, Amin, Miao, Zhen, Palmer, Matthew, Voight, Benjamin F., Li, Hongzhe, Brown, Christopher D., Ritchie, Marylyn D., Shu, Yan, Susztak, Katalin

Issue&Volume: 2022-06-16

Abstract: More than 800 million people suffer from kidney disease, yet the mechanism of kidney dysfunction is poorly understood. In the present study, we define the genetic association with kidney function in 1.5 million individuals and identify 878 (126 new) loci. We map the genotype effect on the methylome in 443 kidneys, transcriptome in 686 samples and single-cell open chromatin in 57,229 kidney cells. Heritability analysis reveals that methylation variation explains a larger fraction of heritability than gene expression. We present a multi-stage prioritization strategy and prioritize target genes for 87% of kidney function loci. We highlight key roles of proximal tubules and metabolism in kidney function regulation. Furthermore, the causal role of SLC47A1 in kidney disease is defined in mice with genetic loss of Slc47a1 and in human individuals carrying loss-of-function variants. Our findings emphasize the key role of bulk and single-cell epigenomic information in translating genome-wide association studies into identifying causal genes, cellular origins and mechanisms of complex traits. Genome-wide analyses identify hundreds of loci associated with kidney function. Integrated analyses of expression, methylation and single-cell open chromatin and expression data derived from human kidney samples prioritize genes and mechanisms underlying renal disease.

DOI: 10.1038/s41588-022-01097-w

Source: https://www.nature.com/articles/s41588-022-01097-w