Uncovering biomarkers for potential therapeutic targeting for COVID-19-related acute kidney injury: A bioinformatic approach

Author:

Gong Rui1,Long Gangyu2,Wang Qian2,Wang Qiongya2345,Huang Chaolin2345ORCID,Zhang Dingyu12345ORCID

Affiliation:

1. The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China

2. Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430023, Hubei Province, China

3. Hubei Clinical Research Center for Infectious Diseases, Wuhan 430023, Hubei Province, China

4. Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Wuhan 430023, Hubei Province, China

5. Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan 430023, Hubei Province, China

Abstract

ABSTRACT Objective: The Coronavirus Disease 2019 (COVID-19) is a recently-emerging infectious disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), posing a significant threat to public health around the world. In patients with COVID-19, acute kidney injury (AKI) is a common complication associated with poor prognoses. We analyzed co-expressed genes to explore relationships between SARS-CoV2 infection and AKI, and revealed potential biomarkers and therapeutic targets of the COVID-19-associated AKI (COVID-19-AKI). Methods: We utilized the GSE147507 and GSE139061 datasets from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in SARS-CoV-2 infection and AKI, respectively. This was followed by analyzing protein-protein interaction networks, Gene Ontology, and pathway enrichment to uncover the relationship between DEGs. DEGs in common (co-DEGs), as well as corresponding interactive transcription factors (TFs) and microRNAs, were identified from the above results, followed by drug molecules uncovered for managing COVID-19-AKI. Aims: To reveal potential biomarkers and therapeutic targets for COVID-19-AKI by bioinformatic approach. Results: We discovered 345 DEGs in the lung and 310 DEGs AKI samples from COVID-19 patients, respectively. IFIT1, ISG15, MX1, IFIT3, and IFIT2 were involved in SARS-CoV-2 pulmonary infection, while hub genes such as RPL23, EIF4A1, RPS8, RPL13, and UPF2 were associated with AKI. We further derived co-DEGs including ERRFI1, KLK10, NR4A1, PODXL, RASGEF1C, RNU11, SNORA12, SNORA74B, and VTRNA1-1 coupled with their predicted transcription factors, including BACH2, HNF4A, MYC, and microRNAs containing miR-637, miR-542-3p, and miR-224. These targets may correlate with COVID-19-AKI, for which candidate drugs were identified. Conclusions: ERRFI1, KLK10, NR4A1, PODXL, RASGEF1C, RNU11, SNORA12, SNORA74B, and VTRNA1-1 may be associated with COVID-19-AKI and serve as novel markers.

Publisher

Medknow

Subject

General Engineering,Electrical and Electronic Engineering,Building and Construction

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3