Related Experiment Video
Updated: Jan 13, 2026

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level
Published on: November 2, 2020
Identification of key genes for heart failure in dilated cardiomyopathy in different populations
Yue Yu1,2, Chentian Xue2, Dong Ji1,2
1Nantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, Jiangsu, China.
Insights
This study identified key biomarkers for heart failure (HF) in dilated cardiomyopathy, revealing significant variations across diverse populations and genders. MYH6, ASPN, and COL14A1 emerged as potential predictive markers for HF.
Area of Science:
- Cardiovascular Disease Research
- Genomics and Bioinformatics
- Biomarker Discovery
Background:
- Heart failure (HF) is a critical end-stage cardiovascular disease and a leading cause of mortality.
- Understanding HF mechanisms and identifying biomarkers is crucial for diverse populations and genders.
Purpose of the Study:
- To identify potential biomarkers for heart failure (HF).
- To elucidate the underlying mechanisms of HF development across diverse populations and genders.
Main Methods:
- Utilized five heart failure with dilated cardiomyopathy datasets for validation.
- Performed differential gene expression analysis and weighted gene co-expression network analysis.
- Employed machine learning models (LASSO, SVM-REF, RF) for Hub gene identification and nomogram construction.
Main Results:
- Functional enrichment revealed HF pathogenesis is linked to inflammation, immune response, Wnt signaling, and metabolism.
- Immune infiltration analysis showed distinct cell abundance differences in HF patients.
- Identified MYH6, ASPN, and COL14A1 as key Hub genes, with several gender- and ethnicity-specific biomarkers detected.
Conclusions:
- Heart failure biomarkers exhibit significant variability across different populations and genders.
- MYH6, ASPN, and COL14A1 show promise as potential biomarkers for heart failure in dilated cardiomyopathy.
Background:
Heart failure (HF) represents the end stage of cardiovascular disease and is the leading cause of mortality. The objective of this study was to identify potential biomarkers and elucidate the mechanisms underlying the development of HF across diverse populations and among different genders.
Methods:
This study strictly included five datasets of HF with dilated cardiomyopathy: GSE141910 (African American and Caucasian), GSE57345 (USA), GSE21610 (Germany), GSE17800 (Germany), and GSE42955 (Spain). These datasets were merged and normalized as the validation set. Differentially expressed genes (DEGs) were identified through differential expression analysis, and module genes were identified using weighted gene co-expression network analysis. Subsequent stratification by gender and ethnicity (African American, Caucasian, German, and Spanish) was performed, followed by immune infiltration analysis. Finally, the least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-REF), and random forest (RF) models were used to screen for Hub genes and to construct a nomogram predicting the occurrence of HF in different populations based on these Hub genes. Additionally, GSE3585, GSE120895, GSE5406, and GSE1145 serve as the validation set.
Results:
A total of 650 samples were included (323 controls and 327 HF samples), including 122 African American samples (44 controls and 78 HF samples), 238 Caucasian samples (122 controls and 116 HF samples), 55 German samples (16 controls and 39 HF samples), and 17 Spanish samples (5 controls and 12 HF samples). Functional enrichment analysis demonstrated that the pathogenesis of HF is closely related to the inflammatory response, immune response, vascular regulation, the Wnt signaling pathway, glutathione metabolism, sphingolipid metabolism, and apoptosis. Immune infiltration analysis showed that HF patients exhibited a high abundance of resting mast cells, resting NK cells, CD8T cells, resting memory CD4 T cells, activated memory CD4 T cells, M1 Macrophages, naive CD4 T cells, M0 Macrophages, regulatory T cells (Tregs), follicular helper T cells, Monocytes, and activated NK cells, and a lower abundance of plasma cells, neutrophils, and eosinophils. Multiple machine learning analyses identified MYH6, ASPN, and COL14A1 as Hub genes, NAP1L3, PLEKHH2, MOXD1, CCDC80, CA14, and SERPINE2 as male-specific, CX3CR1, SYN2, and SLC25A18 as female-specific, and NQO1, KAZALD1, and UBASH3A as African American male-specific, SYN2 as African American female-specific, CD83, C1QTNF3, GRB14, and MOXD1 as Caucasian male-specific, CD83, VIT, and PODXL2 as Caucasian female-specific, LSAMP and C14orf132 as German male-specific, and LSAMP and BMP4 as German female-specific, CIART and SNORA80E as Spanish-specific DEGs. Hub genes are strongly associated with M1 macrophages.
Conclusion:
The biomarkers of HF vary significantly across different populations and genders. MYH6, ASPN, and COL14A1 may be potential biomarkers for HF in dilated cardiomyopathy.
Related Concept Videos
Cardiomyopathy II: Dilated Cardiomyopathy
Pathophysiology of Heart Failure
Cardiomyopathy III: Hypertrophic Cardiomyopathy
Heart Failure I: Introduction
Heart Failure II: Pathophysiology
Cardiomyopathy V: Interprofessional Care

