Hypertrophic cardiomyopathy (HCM) is a hereditary heart disease that is defined as unexplained, isolated, progressive myocardial hypertrophy, usually accompanied by heart failure or arrhythmia. It is considered the primary underlying condition in sudden cardiac death in young adults and athletes. Mutations in the genes encoding proteins of the cardiomyocytic contractile apparatus are considered the main cause of HCM. However, the relationship between sarcomere mutations and clinical outcomes remains unpredictable in patients with HCM, largely because of genetic and phenotypic heterogeneity (1, 2). During the past two decades, the continuous improvement of gene sequencing technology has enabled the diagnosis of HCM among populations with a family history and in asymptomatic patients through genetic testing to avoid sudden death. This has become a class I recommendation for supplementary testing according to the European Society of Cardiology and American Heart Association/American College of Cardiology guidelines (3, 4).

Sarcomere protein gene (such as MYBPC3, MYH7, TNNT2, TNNI3, TPM1, MYL2, MYL3, and ACTC) mutations have become targets in the genetic testing of HCM. Unfortunately, in the genetic testing of different HCM cohorts, up to 50–68% of patients were negative for sarcomere protein gene mutations (5). The signaling pathways and regulatory networks underlying the pathogenesis of HCM remain unclear to date. Thus, a systematic analysis of its transcriptional map might provide useful information about the overall underlying molecular mechanisms and pathological processes of HCM and aid in the diagnosis and treatment of HCM.

As the flowchart showed in Figure 1, this study aimed to explore the high-throughput sequencing gene expression data of HCM patients and normal samples, construct the differential gene expression profile of HCM, annotate the gene ontology and potential signal pathways, and identify valuable biomarkers that may further the gene test diagnosis of HCM.

HCM is a common inherited cardiovascular disease that occurs in one of 500 people in the general population and leads to heart failure, fatal arrhythmia, and stroke. Mutations in genes encoding proteins of the cardiomyocytic contractile apparatus are considered the main cause of HCM. Genetic tests focusing on sarcomere protein genes have been recommended in current guidelines and experience widespread adoption. However, with the accumulation of experimental data (24–26), approximately two-thirds of HCM patients were shown not to have sarcomere protein mutations. Therefore, it is necessary to explore alternative molecular mechanisms and identify more valuable biomarkers of HCM by utilizing contemporary methods to analyze biological complexity with an emphasis on network medicine (27).

According to bioinformatics analysis, the GO annotation and KEGG enrichment analysis of the DEGs in GSE160997 were dominated by immune and inflammatory response mechanisms, such as neutrophil and macrophage activation, neutrophil degranulation, regulation of leukocyte-mediated immunity, and immune effector processes. Currently, inflammation and immunity attract substantial interest with regard to their role in the pathophysiology of cardiovascular diseases. Some previous studies (28–31) suggested that immune and inflammatory response mechanisms may play an important role in myocardial hypertrophy and remodeling. In contrast, most research has focused on heart failure and myocardial remodeling after acute myocardial infarction, with extremely limited evidence on HCM.

The preliminary results of bioinformatics analysis enabled further exploration of IRGs as biomarkers of HCM. A dataset with 1,793 unique IRGs was downloaded from the IMMPORT database and used to identify the IRGs among the DEGs in GSE160997. A total of 121 IGRs were selected from the 1,079 DEGs, and 5 feature IRGs were identified as candidate biomarkers by both the LASSO and Boruta arithmetic. Finally, four feature IRGs were confirmed as biomarkers with an excellent AUC score using the GSE36961 dataset of HCM patients and 39 healthy controls. Our novel diagnosis model of HCM constructed based on these four feature IRGs showed high discrimination ability (C-index = 0.925) and favorable calibration. This pioneering research offers a new perspective on the identification of potential biomarkers that might aid in the diagnosis of HCM.

Angiotensin II receptor type 1 (AGTR1) is a significant effector of the renin-angiotensin-aldosterone system, which is associated with cardiovascular diseases, especially cardiac remodeling. The system consists of two regulatory pathways: a pathological pro-inflammatory pathway and a protective anti-inflammatory pathway. AGTR1, involved in the former, can promote vasoconstriction, cell proliferation, inflammation, oxidative stress, hypertrophy, and fibrosis, and angiotensin II–type 1 receptor blockers are widely used to prevent cardiac remodeling after acute myocardial infarction and heart failure (32, 33).

Atypical chemokine receptor 3 (ACKR3) (34), previously known as C-X-C chemokine receptor type 7 (CXCR7), has emerged as a potential hub gene in cardiac development in animal experiments (35–37). Nevertheless, animal studies have focused on the effects of ACKR3 knockout on cardiac development. In this study, the expression of ACKR3 in HCM patients was significantly higher than that in the normal controls in both GSE160997 and GSE36961. At present, no study has explored the effect of a high expression of ACKR3 on cardiac development or structural remodeling, which may be a promising area of research going forward.

CCR1 gene encodes a protein that acts as a chemokine receptor. This protein and its ligands macrophage inflammatory protein 1 (MIP-1, CCL3) and regulated on activation normal T expressed and secreted protein (RANTES, CCL5) can be expressed in monocytes/macrophages/T lymphocytes, whose signaling is the key to recruit effector immune cells to inflammatory sites. Liehn et al. proved that in model mice with myocardial infarction, the deletion of CCR1 can reduce tissue inflammatory injury and protect the myocardium (38). Data from animal and human studies show that CCR1 and its ligands are central mediators of a variety of inflammatory diseases, making the receptor an attractive candidate for therapeutic intervention. At present, CCR1 receptor antagonists are mainly used in clinical trials for the treatment of rheumatoid arthritis (39). Batis et al. selectively blocks the CCR1 receptor through met RANTES therapy, confirming that a treatment strategy based on regulating CCR1/CCR5 mediated cell migration and/or effector function may help limit cardiac tissue damage during chronic Chagas disease (40).

The protein encoded by cytochrome b-245 beta chain (CYBB) gene, also named NOX-2, is a component of cytochrome b-245, which plays an important role in the development of phagocytic microbicidal oxidase system. A consensus has been reached that the deficiency of CYBB leads to decreased NADPH oxidase activity in phagocytes, and neutrophils phagocytize bacteria but do not effectively kill bacteria, and that this might be the potential pathogenesis of chronic granulomatous disease (41). In addition, the gene has also been reported to be associated with ventricular hypertrophy and arrhythmia caused by hypoxia and high-fat diet (42–44).

The strengths of this study are (a) the innovative perspective that immune and inflammation may underlie the molecular mechanism of HCM and (b) the identification of IRGs as diagnostic biomarkers using bioinformatics analysis of transcriptome datasets of HCM patients and healthy controls. Nonetheless, some limitations of this study need to be recognized. First, the study was a retrospective data analysis and lacked detailed clinical or prognostic information, such as the thickness of the ventricular septum and the occurrence of major adverse cardiovascular events in patients with HCM. This limited the further exploration of the relevant genes determining these clinical features or outcomes. Second, although the four feature biomarkers were verified by an independent dataset of sufficient size and achieved excellent discrimination, a larger dataset is essential for verification in the future. Third, the different transcriptome datasets were detected by different sequencing platforms. The baselines of the different transcriptome datasets were inconsistent, indicating that they may only determine whether the expression of characteristic genes is abnormal without the ability to identify a generally applicable reference range.

The systematic analysis of the transcriptional profiles of HCM and exploration of the potential underlying molecular mechanisms led to the identification of four feature IRGs as biomarkers of HCM. Based on these, a diagnosis model of HCM was developed that brings a novel aspect to the current understanding of the pathological processes and required genetic testing in HCM.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.

XZ and GL were involved in the conception and design of the study. XZ was responsible for visualization and article writing. RH provided scientific supervision. All authors reviewed and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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