Cargando…
Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses
OBJECTIVE: Systemic lupus erythematosus (SLE) patients are at risk during the COVID‐19 pandemic, yet the underlying molecular mechanisms remain incompletely understood. This study sought to analyze the potential molecular connections between COVID‐19 and SLE, employing a bioinformatics approach to i...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659756/ https://www.ncbi.nlm.nih.gov/pubmed/38018597 http://dx.doi.org/10.1002/iid3.1087 |
_version_ | 1785148377481084928 |
---|---|
author | Chen, Chao Zhang, Hongjian Lin, Yanbin Lu, Meiqi Liao, Quan Zhang, Shichao Chen, Weibin Zheng, Xiongwei Li, Yunpeng Ding, Rui Wan, Zheng |
author_facet | Chen, Chao Zhang, Hongjian Lin, Yanbin Lu, Meiqi Liao, Quan Zhang, Shichao Chen, Weibin Zheng, Xiongwei Li, Yunpeng Ding, Rui Wan, Zheng |
author_sort | Chen, Chao |
collection | PubMed |
description | OBJECTIVE: Systemic lupus erythematosus (SLE) patients are at risk during the COVID‐19 pandemic, yet the underlying molecular mechanisms remain incompletely understood. This study sought to analyze the potential molecular connections between COVID‐19 and SLE, employing a bioinformatics approach to identify effective drugs for both conditions. METHODS: The data sets GSE100163 and GSE183071 were utilized to determine share differentially expressed genes (DEGs). These DEGs were later analyzed by various bioinformatic methods, including functional enrichment, protein–protein interaction (PPI) network analysis, regulatory network construction, and gene–drug interaction construction. RESULTS: A total of 50 common DEGs were found between COVID‐19 and SLE. Gene ontology (GO) functional annotation revealed that “immune response,” “innate immune response,” “plasma membrane,” and “protein binding” were most enriched in. Additionally, the pathways that were enriched include “Th1 and Th2 cell differentiation.” The study identified 48 genes/nodes enriched with 292 edges in the PPI network, of which the top 10 hub genes were CD4, IL7R, CD3E, CD5, CD247, KLRB1, CD40LG, CD7, CR2, and GZMK. Furthermore, the study found 48 transcription factors and 8 microRNAs regulating these hub genes. Finally, four drugs namely ibalizumab (targeted to CD4), blinatumomab (targeted to CD3E), muromonab‐CD3 (targeted to CD3E), and catumaxomab (targeted to CD3E) were found in gene–drug interaction. CONCLUSION: Four possible drugs that targeted two specific genes, which may be beneficial for COVID‐19 patients with SLE. |
format | Online Article Text |
id | pubmed-10659756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106597562023-11-20 Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses Chen, Chao Zhang, Hongjian Lin, Yanbin Lu, Meiqi Liao, Quan Zhang, Shichao Chen, Weibin Zheng, Xiongwei Li, Yunpeng Ding, Rui Wan, Zheng Immun Inflamm Dis Original Articles OBJECTIVE: Systemic lupus erythematosus (SLE) patients are at risk during the COVID‐19 pandemic, yet the underlying molecular mechanisms remain incompletely understood. This study sought to analyze the potential molecular connections between COVID‐19 and SLE, employing a bioinformatics approach to identify effective drugs for both conditions. METHODS: The data sets GSE100163 and GSE183071 were utilized to determine share differentially expressed genes (DEGs). These DEGs were later analyzed by various bioinformatic methods, including functional enrichment, protein–protein interaction (PPI) network analysis, regulatory network construction, and gene–drug interaction construction. RESULTS: A total of 50 common DEGs were found between COVID‐19 and SLE. Gene ontology (GO) functional annotation revealed that “immune response,” “innate immune response,” “plasma membrane,” and “protein binding” were most enriched in. Additionally, the pathways that were enriched include “Th1 and Th2 cell differentiation.” The study identified 48 genes/nodes enriched with 292 edges in the PPI network, of which the top 10 hub genes were CD4, IL7R, CD3E, CD5, CD247, KLRB1, CD40LG, CD7, CR2, and GZMK. Furthermore, the study found 48 transcription factors and 8 microRNAs regulating these hub genes. Finally, four drugs namely ibalizumab (targeted to CD4), blinatumomab (targeted to CD3E), muromonab‐CD3 (targeted to CD3E), and catumaxomab (targeted to CD3E) were found in gene–drug interaction. CONCLUSION: Four possible drugs that targeted two specific genes, which may be beneficial for COVID‐19 patients with SLE. John Wiley and Sons Inc. 2023-11-20 /pmc/articles/PMC10659756/ /pubmed/38018597 http://dx.doi.org/10.1002/iid3.1087 Text en © 2023 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Chen, Chao Zhang, Hongjian Lin, Yanbin Lu, Meiqi Liao, Quan Zhang, Shichao Chen, Weibin Zheng, Xiongwei Li, Yunpeng Ding, Rui Wan, Zheng Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title | Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title_full | Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title_fullStr | Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title_full_unstemmed | Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title_short | Identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (SLE) and coexisting COVID‐19: Insights from bioinformatic analyses |
title_sort | identification of potential therapeutic drugs targeting core genes for systemic lupus erythematosus (sle) and coexisting covid‐19: insights from bioinformatic analyses |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659756/ https://www.ncbi.nlm.nih.gov/pubmed/38018597 http://dx.doi.org/10.1002/iid3.1087 |
work_keys_str_mv | AT chenchao identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT zhanghongjian identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT linyanbin identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT lumeiqi identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT liaoquan identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT zhangshichao identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT chenweibin identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT zhengxiongwei identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT liyunpeng identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT dingrui identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses AT wanzheng identificationofpotentialtherapeuticdrugstargetingcoregenesforsystemiclupuserythematosussleandcoexistingcovid19insightsfrombioinformaticanalyses |