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Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics

AIMS: Heart failure with preserved ejection fraction (HFpEF) and non‐alcoholic fatty liver disease (NAFLD) are related conditions with an increasing incidence. The mechanism of their relationship remains undefined. Here, we aimed to explore the potential mechanisms, diagnostic markers, and therapeut...

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Autores principales: Wang, Anzhu, Li, Zhendong, Sun, Zhuo, Wang, Yifei, Fu, Shuangqing, Zhang, Dawu, Ma, Xiaochang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871724/
https://www.ncbi.nlm.nih.gov/pubmed/36266995
http://dx.doi.org/10.1002/ehf2.14211
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author Wang, Anzhu
Li, Zhendong
Sun, Zhuo
Wang, Yifei
Fu, Shuangqing
Zhang, Dawu
Ma, Xiaochang
author_facet Wang, Anzhu
Li, Zhendong
Sun, Zhuo
Wang, Yifei
Fu, Shuangqing
Zhang, Dawu
Ma, Xiaochang
author_sort Wang, Anzhu
collection PubMed
description AIMS: Heart failure with preserved ejection fraction (HFpEF) and non‐alcoholic fatty liver disease (NAFLD) are related conditions with an increasing incidence. The mechanism of their relationship remains undefined. Here, we aimed to explore the potential mechanisms, diagnostic markers, and therapeutic options for HFpEF and NAFLD. METHODS AND RESULTS: HFpEF and NAFLD datasets were downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (DEGs) were screened for functional annotation. A protein–protein interaction network was constructed based on the STRING database, and hub genes were analysed using GeneMANIA annotation. ImmuCellAI (Immune Cell Abundance Identifier) was employed for analysis of immune infiltration. We also used validation datasets to validate the expression levels of hub genes and the correlation of immune cells. To screen for diagnostic biomarkers, we employed the least absolute shrinkage and selection operator and support vector machine‐recursive feature elimination. Drug signature database was used to predict potential therapeutic drugs. Our analyses identified a total of 33 DEGs. Inflammation and immune infiltration played important roles in the development of both diseases. The data showed a close relationship between chemokine signalling pathway, cytokine–cytokine receptor interaction, calcium signalling pathway, neuroactive ligand–receptor interaction, osteoclast differentiation, and cyclic guanosine monophosphate‐protein kinase G signalling pathway. We demonstrated that PRF1 (perforin 1) and IL2RB (interleukin‐2 receptor subunit beta) proteins were perturbed by the diseases and may be the hub genes. The analysis showed that miR‐375 may be a potential diagnostic marker for both diseases. Our drug prediction analysis showed that bosentan, eldecalcitol, ramipril, and probucol could be potential therapeutic options for the diseases. CONCLUSIONS: Our findings revealed common pathogenesis, diagnostic markers, and therapeutic agents for HFpEF and NAFLD. There is need for further experimental studies to validate our findings.
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spelling pubmed-98717242023-01-27 Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics Wang, Anzhu Li, Zhendong Sun, Zhuo Wang, Yifei Fu, Shuangqing Zhang, Dawu Ma, Xiaochang ESC Heart Fail Original Articles AIMS: Heart failure with preserved ejection fraction (HFpEF) and non‐alcoholic fatty liver disease (NAFLD) are related conditions with an increasing incidence. The mechanism of their relationship remains undefined. Here, we aimed to explore the potential mechanisms, diagnostic markers, and therapeutic options for HFpEF and NAFLD. METHODS AND RESULTS: HFpEF and NAFLD datasets were downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (DEGs) were screened for functional annotation. A protein–protein interaction network was constructed based on the STRING database, and hub genes were analysed using GeneMANIA annotation. ImmuCellAI (Immune Cell Abundance Identifier) was employed for analysis of immune infiltration. We also used validation datasets to validate the expression levels of hub genes and the correlation of immune cells. To screen for diagnostic biomarkers, we employed the least absolute shrinkage and selection operator and support vector machine‐recursive feature elimination. Drug signature database was used to predict potential therapeutic drugs. Our analyses identified a total of 33 DEGs. Inflammation and immune infiltration played important roles in the development of both diseases. The data showed a close relationship between chemokine signalling pathway, cytokine–cytokine receptor interaction, calcium signalling pathway, neuroactive ligand–receptor interaction, osteoclast differentiation, and cyclic guanosine monophosphate‐protein kinase G signalling pathway. We demonstrated that PRF1 (perforin 1) and IL2RB (interleukin‐2 receptor subunit beta) proteins were perturbed by the diseases and may be the hub genes. The analysis showed that miR‐375 may be a potential diagnostic marker for both diseases. Our drug prediction analysis showed that bosentan, eldecalcitol, ramipril, and probucol could be potential therapeutic options for the diseases. CONCLUSIONS: Our findings revealed common pathogenesis, diagnostic markers, and therapeutic agents for HFpEF and NAFLD. There is need for further experimental studies to validate our findings. John Wiley and Sons Inc. 2022-10-20 /pmc/articles/PMC9871724/ /pubmed/36266995 http://dx.doi.org/10.1002/ehf2.14211 Text en © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Wang, Anzhu
Li, Zhendong
Sun, Zhuo
Wang, Yifei
Fu, Shuangqing
Zhang, Dawu
Ma, Xiaochang
Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title_full Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title_fullStr Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title_full_unstemmed Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title_short Heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
title_sort heart failure with preserved ejection fraction and non‐alcoholic fatty liver disease: new insights from bioinformatics
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871724/
https://www.ncbi.nlm.nih.gov/pubmed/36266995
http://dx.doi.org/10.1002/ehf2.14211
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