生物信息学 之 计算表观遗传学分享 http://blog.sciencenet.cn/u/hongbo919 森罗万象是表观, 追根溯源系遗传。 计算精研千淘漉, 生物殿堂乐其间。

博文

[转载]新研究揭示肾病的潜在分子病因

已有 2143 次阅读 2022-7-6 11:54 |个人分类:科研杂谈|系统分类:科研笔记|文章来源:转载

PHILADELPHIA – After mapping the genetic underpinning of kidney function in 1.5 million people and about 60,000 kidney cells that are the microscopic mechanisms of gene regulation, over 500 genes likely contribute to kidney disease development, according to researchers at the Perelman School of Medicine at the University of Pennsylvania. Multiple genes that play a key role in kidney detoxification, including SLC47A1, have been identified. The good news is that close to 100 of the 500 genes might be able to be targeted by various pharmaceuticals already approved by the Food and Drug Administration (FDA). The findings point to the underlying genetics of kidney function and can lead to future research into possible therapeutic targets to treat kidney disease and the development of it. The research was published in Nature Genetics.

640.png

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

“Single cell level analytical tools now allow us to dive deeper into the mechanisms at play by uncovering genetic variation in all cells in the body, and then we can look for links to genetics of diseases and illnesses,” said Katalin Susztak, MD, PhD, lead investigator and a professor of Nephrology and Genetics at Penn. “Highlighting the links and exploring cause and effect will offer greater understanding of the human kidney and uncover potential ways to treat those who struggle with kidney issues.”

An estimated 37 million people in the United States have kidney disease, and mortality from kidney disease has risen by more than 40 percent in the last two decades, making it one of the fastest-growing causes of death. Roughly a million people die of kidney failure worldwide each year. Despite the major personal and economic burden, few new therapeutics have been registered to treat or cure kidney disease over the last 40 years.

Using genetic information from more than 1.5 million participants around the world and a basic-science technique of mapping cells known as single-cell sequencing, scientists at Penn implicated important cell types for different disease conditions such as the proximal tubules for kidney disease and collecting duct principal cells for high blood pressure.

Next, the researchers characterized gene expression and gene regulation in hundreds of human kidney samples and analyzed changes in more than 60,000 human kidney cells. The team used sophisticated computational and statistical methods to generate the most comprehensive maps to uncover the genes, cell types and mechanism of kidney dysfunction.

“While there may be many origins of kidney dysfunction in human kidneys, our studies specifically highlight the role of SLC471A gene,” said Hongbo Liu, PhD, a postdoctoral fellow in Susztak’ s lab. “This gene carries different toxins. Changes in SLC47 might make the kidneys of people more or less sensitive to toxin mediated injury and kidney disease.”

The study authors want to continue to look into specific genes to understand their role in kidney diseases and say that their study serves as a springboard for researchers to test different pharmaceuticals against these genetic variants and their deleterious effects.

“There may come a time many years from now when patients who have these genetic variants can receive treatment before kidney disorders arise,” Susztak said.

This research was supported by the National Institutes of Health (R01DK087653, R01DK076077, and R01DK105821). Datasets produced in this study are available at https://susztaklab.com.

原文来自:https://www.pennmedicine.org/news/news-releases/2022/july/new-research-maps-possible-molecular-origins-of-kidney-disease

中文详情报道:https://mp.weixin.qq.com/s/7pH6SAKkELGj2Mv1Rb-YmA (BioArt)




https://blog.sciencenet.cn/blog-97949-1346098.html

上一篇:简单实用的在线维恩图绘制方法
下一篇:美国罗切斯特大学刘洪波课题组招收博士后和博士生
收藏 IP: 165.123.66.*| 热度|

0

该博文允许注册用户评论 请点击登录 评论 (0 个评论)

数据加载中...
扫一扫,分享此博文

Archiver|手机版|科学网 ( 京ICP备07017567号-12 )

GMT+8, 2024-12-22 13:56

Powered by ScienceNet.cn

Copyright © 2007- 中国科学报社

返回顶部