Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach

IF 2.9 3区医学 Q2 GENETICS & HEREDITY

Pharmacogenomics Journal Pub Date : 2022-09-28 DOI:10.1038/s41397-022-00289-1

Theodosia Charitou, Panagiota I. Kontou, Ioannis A. Tamposis, Georgios A. Pavlopoulos, Georgia G. Braliou, Pantelis G. Bagos

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引用次数: 0

Abstract

Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.

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药物基因与 COVID-19 表现的关联：一种数据挖掘和网络生物学方法

现有药物已通过临床试验作为一种紧急尝试，以尽量减少因冠状病毒病（COVID-19）住院的严重病例，然而，关于影响合并症患者同时用药反应的常见药物基因组学数据却很有限。为了确定影响 COVID-19 易感性的基因组决定因素，我们采用了一种计算、统计和网络生物学方法来分析无效并用药物与患者不良反应之间的关系。我们从统计学角度构建了一个药物基因/生物标记网络，该网络中的药物基因与疾病基因之间存在显著的相互作用。对包含基因-疾病-基因药物基因组学（PGx）网络的预测药物基因的研究表明，这些基因可能在 COVID-19 的临床表现中扮演重要角色，因为它们与自身免疫、代谢、神经、心血管和退行性疾病有关，其中一些已被报道为 COVID-19 患者的重要合并症。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Pharmacogenomics Journal 医学-药学

CiteScore

7.20

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Pharmacogenomics Journal is a print and electronic journal, which is dedicated to the rapid publication of original research on pharmacogenomics and its clinical applications. Key areas of coverage include: Personalized medicine Effects of genetic variability on drug toxicity and efficacy Identification and functional characterization of polymorphisms relevant to drug action Pharmacodynamic and pharmacokinetic variations and drug efficacy Integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics Clinical applications of genomic science Identification of novel genomic targets for drug development Potential benefits of pharmacogenomics.