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Published on: July 3, 2018
Human Plasma Transcriptome Implicates Dysregulated S100A12 Expression: A Strong, Early-Stage Prognostic Factor in
Hu Zhai1,2,3,4, Lei Huang1,2,3,4, Yijie Gong5
1Department of Heart Center, The Tianjin Third Central Hospital, Tianjin, China.
Insights
Blood transcriptome analysis identified S100A12 as a key gene after myocardial infarction. Transcriptional S100A12 levels predict early mortality in ST-segment elevated myocardial infarction patients.
Area of Science:
- Cardiovascular Biology
- Molecular Diagnostics
- Genomics
Background:
- The utility of blood transcriptome analysis for identifying prognostic markers post-myocardial infarction is not well-established.
- Understanding gene expression changes is crucial for improving patient outcomes after ST-segment elevated myocardial infarction (STEMI).
Purpose of the Study:
- To identify dysregulated genes and pathways in plasma transcriptomes of STEMI patients.
- To evaluate the prognostic value of identified genes, particularly S100A12, for predicting mortality and adverse events.
Main Methods:
- Analysis of two public gene expression datasets (GSE60993, GSE61144) to identify differentially expressed genes (DEGs) in STEMI patients.
- Functional enrichment analysis (GO/KEGG) and protein-protein interaction networks to understand DEG roles.
- Verification of DEGs at transcriptional (GSE49925) and translational levels in patient samples.
Main Results:
- Identified 91 DEGs, including 15 downregulated and 76 upregulated genes.
- Discovered 12 hub genes within two key modules; six showed consistent transcriptional changes.
- S100A12 demonstrated strong predictive performance for in-hospital mortality and was an independent predictor of long-term death.
Conclusions:
- Plasma S100A12 transcriptional dysregulation is a robust early prognostic indicator in STEMI.
- While S100A12 protein levels showed lower expression in survivors, its predictive power for discharge survival and recurrent events requires further large-scale validation.
Abstract:
The ability of blood transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction remains unknown. Two gene expression datasets (GSE60993 and GSE61144) were downloaded from Gene Expression Omnibus (GEO) Datasets to identify altered plasma transcriptomes in patients with ST-segment elevated myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. GEO2R, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotations, protein-protein interaction analysis, etc., were adopted to determine functional roles and regulatory networks of differentially expressed genes (DEGs). Dysregulated expressomes were verified at transcriptional and translational levels by analyzing the GSE49925 dataset and our own samples, respectively. A total of 91 DEGs were identified in the discovery phase, consisting of 15 downregulated genes and 76 upregulated genes. Two hub modules consisting of 12 hub genes were identified. In the verification phase, six of the 12 hub genes exhibited the same variation patterns at the transcriptional level in the GSE49925 dataset. Among them, S100A12 was shown to have the best discriminative performance for predicting in-hospital mortality and to be the only independent predictor of death during follow-up. Validation of 223 samples from our center showed that S100A12 protein level in plasma was significantly lower among patients who survived to discharge, but it was not an independent predictor of survival to discharge or recurrent major adverse cardiovascular events after discharge. In conclusion, the dysregulated expression of plasma S100A12 at the transcriptional level is a robust early prognostic factor in patients with STEMI, while the discrimination power of the protein level in plasma needs to be further verified by large-scale, prospective, international, multicenter studies.
