New candidate genes for ST-elevation myocardial infarction

miR-31-5p suppresses myocardial hypertrophy by targeting Nfatc2ip

Cardiac hypertrophy, worldwide known as an adaptive functional compensatory state of myocardial stress, is mainly believed to proceed to severe heart diseases, even to sudden death. Emerging studies have explored the microRNA alteration during hypertrophy. However, the mechanisms of microRNAs involved in cardiac hypertrophy are still uncertain. We studied young rats to establish abdominal aorta coarctation (AAC) for 4 weeks. With the significant downregulated cardiac function and upregulated hypertrophic biomarkers, AAC-induced rats showed enlarged myocardiocytes and alterations in microRNAs, especially downregulated miR-31-5p. miR-31-5p targets the 3'UTR of Nfatc2ip and inhibits myocardial hypertrophy in vitro and in vivo. Furthermore, we verified that Nfatc2ip is necessary and sufficient for cardiac hypertrophy in neonatal rat cardiomyocytes. Moreover, we found miR-31-5p inhibited the colocalization of Nfatc2ip and hypertrophic gene β-Mhc. Luciferase assay and ChiP-qPCR test demonstrated that Nfatc2ip binded to the core-promoter of β-Mhc and enhanced its transcriptional activity. Above all, our study found a new pathway, mir-31-5p/Nfatc2ip/β-Mhc, which is involved in cardiac hypertrophy, suggesting a potential target for intervention of cardiac hypertrophy.

Myocardial infarction complexity: A multi-omics approach

Myocardial infarction (MI), a prevalent cardiovascular disease, is fundamentally precipitated by thrombus formation in the coronary arteries, which subsequently decreases myocardial perfusion and leads to cellular necrosis. The intricacy of MI pathogenesis necessitates extensive research to elucidate the disease's root cause, thereby addressing the limitations present in its diagnosis and prognosis. With the continuous advancement of genomics technology, genomics, proteomics, metabolomics and transcriptomics are widely used in the study of MI, which provides an excellent way to identify new biomarkers that elucidate the complex mechanisms of MI. This paper provides a detailed review of various genomics studies of MI, including genomics, proteomics, transcriptomics, metabolomics and multi-omics studies. The metabolites and proteins involved in the pathogenesis of MI are investigated through integrated protein-protein interactions and multi-omics analysis by STRING and Metascape platforms. In conclusion, the future of omics research in myocardial infarction offers significant promise.

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.

Revealing Potential Spinal Cord Injury Biomarkers and Immune Cell Infiltration Characteristics in Mice

Spinal cord injury (SCI) is a disabling condition with significant morbidity and mortality. Currently, no effective SCI treatment exists. This study aimed to identify potential biomarkers and characterize the properties of immune cell infiltration during this pathological event. To eliminate batch effects, we concurrently analyzed two mouse SCI datasets (GSE5296, GSE47681) from the GEO database. First, we identified differentially expressed genes (DEGs) using linear models for microarray data (LIMMA) and performed functional enrichment studies on those DEGs. Next, we employed bioinformatics and machine-learning methods to identify and define the characteristic genes of SCI. Finally, we validated them using immunofluorescence and qRT-PCR. Additionally, this study assessed the inflammatory status of SCI by identifying cell types using CIBERSORT. Furthermore, we investigated the link between key markers and infiltrating immune cells. In total, we identified 561 robust DEGs. We identified Rab20 and Klf6 as SCI-specific biomarkers and demonstrated their significance using qRT-PCR in the mouse model. According to the examination of immune cell infiltration, M0, M1, and M2 macrophages, along with naive CD8, dendritic cell-activated, and CD4 Follicular T cells may have a role in the progression of SCI. Therefore, Rab20 and Klf6 could be accessible targets for diagnosing and treating SCI. Moreover, as previously stated, immune cell infiltration may significantly impact the development and progression of SCI.

DNA methylation pattern of hypertriglyceridemic subjects

BACKGROUND

Chylomicronemias are generally diagnosed genetically by genomic sequencing or screening for mutations in causal genes with a large phenotypic effect. This strategy has allowed to improve the characterization of these patients, but we still have 30% of the patients without a conclusive genetic diagnosis. This is why we hypothesize that by adding the epigenetic component we can improve the genetic diagnosis, and for this we have explored the degree of methylation in the DNA of hypertriglyceridemic patients.

METHODOLOGY

Blood cell DNA was obtained from 16 hypertriglyceridemic patients and from 16 age- and sex-matched control subjects. The degree of methylation in genome-wide DNA was determined using the Illumina® Infinium Methylation EPIC Array Analysis.

RESULTS

We identified 31 differentially methylated cytosines by comparing the methylation patterns presented by hypertriglyceridemic patients vs. control subjects. The cg03636183 in the F2RL3 gene was 10% hypomethylated in hypertriglyceridemic patients, and has previously been associated with an increased cardiovascular risk. Cg13824500 is 10% hypomethylated in hypertriglyceridemic patients and is located in VTI1A, which is a limiting gene in the transit of chylomicrons in the enterocyte through the endoplasmic reticulum and the Golgi apparatus. Cg26468118 in the RAB20 gene (13% hypomethylated) and cg21560722 in the SBF2 gene (33% hypermethylated) are involved in the regulation of Golgi apparatus vesicles.

CONCLUSIONS

Our results suggest that there are differentially methylated regions related to the formation of chylomicrons in hypertriglyceridemic patients.

MIKB: A manually curated and comprehensive knowledge base for myocardial infarction

Myocardial infarction knowledge base (MIKB; http://www.sysbio.org.cn/mikb/; latest update: December 31, 2020) is an open-access and manually curated database dedicated to integrating knowledge about MI to improve the efficiency of translational MI research. MIKB is an updated and expanded version of our previous MI Risk Knowledge Base (MIRKB), which integrated MI-related risk factors and risk models for providing help in risk assessment or diagnostic prediction of MI. The updated MIRKB includes 9701 records with 2054 single factors, 209 combined factors, 243 risk models, 37 MI subtypes and 3406 interactions between single factors and MIs collected from 4817 research articles. The expanded functional module, i.e. MIGD, is a database including not only MI associated genetic variants, but also the other multi-omics factors and the annotations for their functional alterations. The goal of MIGD is to provide a multi-omics level understanding of the molecular pathogenesis of MI. MIGD includes 1782 omics factors, 28 MI subtypes and 2347 omics factor-MI interactions as well as 1253 genes and 6 chromosomal alterations collected from 2647 research articles. The functions of MI associated genes and their interaction with drugs were analyzed. MIKB will be continuously updated and optimized to provide precision and comprehensive knowledge for the study of heterogeneous and personalized MI.

Arginase 1 is upregulated at admission in patients with ST-elevation myocardial infarction

BACKGROUND

The mechanisms underlying rupture of a coronary atherosclerotic plaque and development of myocardial ischemia-reperfusion injury in ST-elevation myocardial infarction (STEMI) remain unresolved. Increased arginase 1 activity leads to reduced nitric oxide (NO) production and increased formation of reactive oxygen species due to uncoupling of the NO-producing enzyme endothelial NO synthase (eNOS). This contributes to endothelial dysfunction, plaque instability and increased susceptibility to ischemia-reperfusion injury in acute myocardial infarction.

OBJECTIVE

The purpose of this study was to test the hypothesis that arginase gene and protein expression are upregulated in patients with STEMI.

METHODS

Two cohorts of patients with STEMI were included. In the first cohort (n = 51), expression of arginase and NO-synthases as well as arginase 1 protein levels were determined and compared to a healthy control group (n = 45). In a second cohort (n = 68), plasma arginase 1 levels and infarct size were determined using cardiac magnetic resonance imaging.

RESULTS

Expression of the gene encoding arginase 1 was significantly elevated at admission and 24-48 h after STEMI but not 3 months post STEMI, in comparison with the control group. Expression of the genes encoding arginase 2 and endothelial NO synthase (NOS3) were unaltered. Arginase 1 protein levels were elevated at admission, 24 h post STEMI and remained elevated for up to 6 months. No significant correlation between plasma arginase 1 protein levels and infarct size was observed.

CONCLUSION

The markedly increased gene and protein expression of arginase 1 already at admission indicates a role of arginase 1 in the development of STEMI.