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COVID-19 is a new coronavirus that constitutes a great challenge to human health. At this stage, there are still cases of COVID-19 infection in some countries and regions, in which ischemic stroke (IS) is a risk factor for new coronavirus pneumonia, and patients with COVID-19 infection have a dramatically elevated risk of stroke. At the same time, patients with long-term IS are vulnerable to COVID-19 infection and have more severe disease, and carotid atherosclerosis is an early lesion in IS. This study used human induced pluripotent stem cell (hiPSC)-derived monolayer brain cell dataset and human carotid atherosclerosis genome-wide dataset to analyze COVID-19 infection and carotid atherosclerosis patients to determine the synergistic effect of new coronavirus infection on carotid atherosclerosis patients, to clarify the common genes of both, and to identify common pathways and potential drugs for carotid atherosclerosis in patients with COVID-19 infection RESULTS: Using several advanced bioinformatics tools, we present the causes of COVID-19 infection leading to increased mortality in carotid atherosclerosis patients and the susceptibility of carotid atherosclerosis patients to COVID-19. Potential therapeutic agents for COVID-19 -infected patients with carotid atherosclerosis are also proposed. With COVID-19 being a relatively new disease, associations have been proposed for its connections with several ailments and conditions, including IS and carotid atherosclerosis. More patient-based data-sets and studies are needed to fully explore and understand the relationship. Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Citation

Liang Yanchao, Zhang Sibin, Ilgiz Gareev, Xiang Huan, Zhao Junfei, Liu Chunyang, Ozal Beylerli, Albert Sufianov, Yuan Chao, Gai Yuyan, Xu Xun, Aamir Ahmad, Liang Peng, Yang Guang. Bioinformatics analysis of potential therapeutic targets for COVID-19 infection in patients with carotid atherosclerosis. Journal of infection and public health. 2022 Apr;15(4):437-447

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PMID: 35344771

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