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Peer-reviewedCC BY 4.0BMC Cardiovascular Disorders

Transcriptome expression profiles and regulatory networks in patients with heart failure following myocardial infarction

  1. 1Department of Cardiology, Anning First People’s Hospital Affiliated to Kunming University of Science and Technology, No.2 Ganghe Rd, Kunming, Yunnan 650300 China
  2. 2Department of Endocrinology and Metabolic Diseases, Anning First People’s Hospital Affiliated to Kunming University of Science and Technology, No.2 Ganghe Rd, Kunming, Yunnan 650300 China

Abstract

Background: The molecular mechanisms underlying heart failure (HF) following myocardial infarction (MI) (HF-MI) remain incompletely understood, and discoveries from whole-transcriptome profiling hold significant promise for disease prevention and treatment.

Methods: Whole-transcriptome sequencing was performed on whole blood from post-MI patients with and without HF to analyze differentially expressed mRNAs, lncRNAs, and circRNAs, along with functional enrichment analysis. Co-expression networks linking lncRNA-mRNA and circRNA-mRNA pairs, as well as ceRNA networks involving lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA interactions, were constructed for differentially expressed (DE) RNAs. Candidate lncRNAs were validated by RT-qPCR. Transcriptional factor-lncRNA networks were constructed, and candidate relationships were verified using RIP-PCR.

Results: Patients with HF-MI exhibited marked elevation of NT-proBNP and significant reduction in LVEF%. Transcriptome-wide analysis revealed 228 DE-mRNAs, 700 DE-lncRNAs, and 1188 DE-circRNAs in HF-MI compared to non-heart failure patients (NHF-MI). Construction of the ceRNA network identified hsa-miR-6089 and hsa-miR-6771-5p as candidate miRNAs in the lncRNA-miRNA-mRNA network, while hsa-miR-1207-5p and hsa-miR-10392-3p were candidate miRNAs in the circRNA-miRNA-mRNA network. PVT1, SNHG5, TTN-AS1, HCP5, and OIP5-AS1 were identified as the five candidate DE-lncRNAs, with PVT1/SNHG5 showing upregulation and TTN-AS1/HCP5/OIP5-AS1 exhibiting downregulation. The transcription factor-lncRNA network primarily involves GLIS3-HCP5 and ZNF135-PVT1, with validated associative interactions.

Conclusion: This study systematically mapped the regulatory network of HF-MI, suggesting potential involvement of the GLIS3-HCP5 and ZNF135-PVT1 axes in HF-MI, thereby providing a basis for exploring novel therapeutic strategies.

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BibTeX
@article{yuan2026transcriptome,
  title = {{Transcriptome expression profiles and regulatory networks in patients with heart failure following myocardial infarction}},
  author = {Yangyang Yuan and Rong Long and Zewen Wei and Lin Ye and Jianying Sun and Shouguo Zhu and Zhi Zhang and Jian Li},
  journal = {BMC Cardiovascular Disorders},
  year = {2026},
  month = aug,
  doi = {10.1186/s12872-026-06424-1},
  url = {https://doi.org/10.1186/s12872-026-06424-1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Transcriptome expression profiles and regulatory networks in patients with heart failure following myocardial infarction
AU  - Yangyang Yuan
AU  - Rong Long
AU  - Zewen Wei
AU  - Lin Ye
AU  - Jianying Sun
AU  - Shouguo Zhu
AU  - Zhi Zhang
AU  - Jian Li
PY  - 2026
DA  - 2026/08/12
JO  - BMC Cardiovascular Disorders
DO  - 10.1186/s12872-026-06424-1
UR  - https://doi.org/10.1186/s12872-026-06424-1
AB  - Background: The molecular mechanisms underlying heart failure (HF) following myocardial infarction (MI) (HF-MI) remain incompletely understood, and discoveries from whole-transcriptome profiling hold significant promise for disease prevention and treatment.  Methods: Whole-transcriptome sequencing was performed on whole blood from post-MI patients with and without HF to analyze differentially expressed mRNAs, lncRNAs, and circRNAs, along with functional enrichment analysis. Co-expression networks linking lncRNA-mRNA and circRNA-mRNA pairs, as well as ceRNA networks involving lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA interactions, were constructed for differentially expressed (DE) RNAs. Candidate lncRNAs were validated by RT-qPCR. Transcriptional factor-lncRNA networks were constructed, and candidate relationships were verified using RIP-PCR.  Results: Patients with HF-MI exhibited marked elevation of NT-proBNP and significant reduction in LVEF%. Transcriptome-wide analysis revealed 228 DE-mRNAs, 700 DE-lncRNAs, and 1188 DE-circRNAs in HF-MI compared to non-heart failure patients (NHF-MI). Construction of the ceRNA network identified hsa-miR-6089 and hsa-miR-6771-5p as candidate miRNAs in the lncRNA-miRNA-mRNA network, while hsa-miR-1207-5p and hsa-miR-10392-3p were candidate miRNAs in the circRNA-miRNA-mRNA network. PVT1, SNHG5, TTN-AS1, HCP5, and OIP5-AS1 were identified as the five candidate DE-lncRNAs, with PVT1/SNHG5 showing upregulation and TTN-AS1/HCP5/OIP5-AS1 exhibiting downregulation. The transcription factor-lncRNA network primarily involves GLIS3-HCP5 and ZNF135-PVT1, with validated associative interactions.  Conclusion: This study systematically mapped the regulatory network of HF-MI, suggesting potential involvement of the GLIS3-HCP5 and ZNF135-PVT1 axes in HF-MI, thereby providing a basis for exploring novel therapeutic strategies.
SN  - 1471-2261
ER  -