Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction
IntroductionMyocardial infarction (MI) is a deadly medical condition leading to irreversible damage to the inflicted cardiac tissue. Elevated inflammatory response marks the severity of MI and is associated with the development of heart failure (HF), a long-term adverse outcome of MI. However, the e...
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Frontiers Media S.A.
2023-03-01
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Series: | Frontiers in Cardiovascular Medicine |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2023.1087721/full |
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author | Yujue Wang Yu Chen Yu Chen Yu Chen Teng Zhang Teng Zhang |
author_facet | Yujue Wang Yu Chen Yu Chen Yu Chen Teng Zhang Teng Zhang |
author_sort | Yujue Wang |
collection | DOAJ |
description | IntroductionMyocardial infarction (MI) is a deadly medical condition leading to irreversible damage to the inflicted cardiac tissue. Elevated inflammatory response marks the severity of MI and is associated with the development of heart failure (HF), a long-term adverse outcome of MI. However, the efficacy of anti-inflammatory therapies for MI remains controversial. Deciphering the dynamic transcriptional signatures in peripheral blood mononuclear cells (PBMCs) is a viable and translatable route to better understand post-MI inflammation, which may help guide post-MI anti-inflammatory treatments.MethodsIn this work, integrated whole-genome gene expression analysis was performed to explore dynamic immune landscapes associated with MI.ResultsGSEA and GSVA showed that pathways involved in the inflammatory response and metabolic reprogramming were significantly enriched in PBMCs from MI patients. Based on leukocyte profiles generated by xCell algorithm, the relative abundance of monocytes and neutrophils was significantly increased in PBMCs from MI patients and had positive correlations with typical inflammation-associated transcripts. Mfuzz clustering revealed temporal gene expression profiles of PBMCs during the 6-month post-MI follow-up. Analysis of DEGs and gene sets indicated that PBMCs from HF group were characterized by elevated and lasting expression of genes implicated in inflammation and coagulation. Consensus clustering generated 4 metabolic subtypes of PBMCs with molecular heterogeneity in HF patients.DiscussionIn summary, integrated whole-genome gene expression analysis here outlines a transcriptomic framework that may improve the understanding of dynamic signatures present in PBMCs, as well as the heterogeneity of PBMCs in MI patients with or without long-term clinical outcome of HF. Moreover, the work here uncovers the diversity and heterogeneity of PBMCs from HF patients, providing novel bioinformatic evidence supporting the mechanistic implications of metabolic reprogramming and mitochondrial dysfunction in the post-MI inflammation and HF. Therefore, our work here supports the notion that individualized anti-inflammatory therapies are needed to improve the clinical management of post-MI patients. |
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language | English |
last_indexed | 2024-04-10T06:02:32Z |
publishDate | 2023-03-01 |
publisher | Frontiers Media S.A. |
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series | Frontiers in Cardiovascular Medicine |
spelling | doaj.art-3f911091c8024b998e048b691ea1e3aa2023-03-03T06:08:33ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2023-03-011010.3389/fcvm.2023.10877211087721Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarctionYujue Wang0Yu Chen1Yu Chen2Yu Chen3Teng Zhang4Teng Zhang5Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaClinical Research Institute of Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, ChinaLaboratory of Clinical and Molecular Pharmacology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaYueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaClinical Research Institute of Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, ChinaIntroductionMyocardial infarction (MI) is a deadly medical condition leading to irreversible damage to the inflicted cardiac tissue. Elevated inflammatory response marks the severity of MI and is associated with the development of heart failure (HF), a long-term adverse outcome of MI. However, the efficacy of anti-inflammatory therapies for MI remains controversial. Deciphering the dynamic transcriptional signatures in peripheral blood mononuclear cells (PBMCs) is a viable and translatable route to better understand post-MI inflammation, which may help guide post-MI anti-inflammatory treatments.MethodsIn this work, integrated whole-genome gene expression analysis was performed to explore dynamic immune landscapes associated with MI.ResultsGSEA and GSVA showed that pathways involved in the inflammatory response and metabolic reprogramming were significantly enriched in PBMCs from MI patients. Based on leukocyte profiles generated by xCell algorithm, the relative abundance of monocytes and neutrophils was significantly increased in PBMCs from MI patients and had positive correlations with typical inflammation-associated transcripts. Mfuzz clustering revealed temporal gene expression profiles of PBMCs during the 6-month post-MI follow-up. Analysis of DEGs and gene sets indicated that PBMCs from HF group were characterized by elevated and lasting expression of genes implicated in inflammation and coagulation. Consensus clustering generated 4 metabolic subtypes of PBMCs with molecular heterogeneity in HF patients.DiscussionIn summary, integrated whole-genome gene expression analysis here outlines a transcriptomic framework that may improve the understanding of dynamic signatures present in PBMCs, as well as the heterogeneity of PBMCs in MI patients with or without long-term clinical outcome of HF. Moreover, the work here uncovers the diversity and heterogeneity of PBMCs from HF patients, providing novel bioinformatic evidence supporting the mechanistic implications of metabolic reprogramming and mitochondrial dysfunction in the post-MI inflammation and HF. Therefore, our work here supports the notion that individualized anti-inflammatory therapies are needed to improve the clinical management of post-MI patients.https://www.frontiersin.org/articles/10.3389/fcvm.2023.1087721/fullmyocardial infarctionheart failureperipheral blood mononuclear cellsinflammationintegrated whole-genome gene expression analysis |
spellingShingle | Yujue Wang Yu Chen Yu Chen Yu Chen Teng Zhang Teng Zhang Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction Frontiers in Cardiovascular Medicine myocardial infarction heart failure peripheral blood mononuclear cells inflammation integrated whole-genome gene expression analysis |
title | Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
title_full | Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
title_fullStr | Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
title_full_unstemmed | Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
title_short | Integrated whole-genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
title_sort | integrated whole genome gene expression analysis reveals an atlas of dynamic immune landscapes after myocardial infarction |
topic | myocardial infarction heart failure peripheral blood mononuclear cells inflammation integrated whole-genome gene expression analysis |
url | https://www.frontiersin.org/articles/10.3389/fcvm.2023.1087721/full |
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