Identification of crucial genes involved in pathogenesis of regional weakening of the aortic wall

The mitochondrial protease ClpP is a druggable target that controls VSMC phenotype by a SIRT1-dependent mechanism

Vascular smooth muscle cells (VSMCs), known for their remarkable lifelong phenotypic plasticity, play a pivotal role in vascular pathologies through their ability to transition between different phenotypes. Our group discovered that the deficiency of the mitochondrial protein Poldip2 induces VSMC differentiation both in vivo and in vitro. Further comprehensive biochemical investigations revealed Poldip2's specific interaction with the mitochondrial ATPase caseinolytic protease chaperone subunit X (CLPX), which is the regulatory subunit for the caseinolytic protease proteolytic subunit (ClpP) that forms part of the ClpXP complex - a proteasome-like protease evolutionarily conserved from bacteria to humans. This interaction limits the protease's activity, and reduced Poldip2 levels lead to ClpXP complex activation. This finding prompted the hypothesis that ClpXP complex activity within the mitochondria may regulate the VSMC phenotype. Employing gain-of-function and loss-of-function strategies, we demonstrated that ClpXP activity significantly influences the VSMC phenotype. Notably, both genetic and pharmacological activation of ClpXP inhibits VSMC plasticity and fosters a quiescent, differentiated, and anti-inflammatory VSMC phenotype. The pharmacological activation of ClpP using TIC10, currently in phase III clinical trials for cancer, successfully replicates this phenotype both in vitro and in vivo and markedly reduces aneurysm development in a mouse model of elastase-induced aortic aneurysms. Our mechanistic exploration indicates that ClpP activation regulates the VSMC phenotype by modifying the cellular NAD+/NADH ratio and activating Sirtuin 1. Our findings reveal the crucial role of mitochondrial proteostasis in the regulation of the VSMC phenotype and propose the ClpP protease as a novel, actionable target for manipulating the VSMC phenotype.

Aortic disease and cardiomyopathy in patients with a novel DNMT3A gene variant causing Tatton-Brown-Rahman syndrome

Tatton-Brown-Rahman syndrome (TBRS) is a rare congenital genetic disorder caused by autosomal dominant pathogenic variants in the DNA methyltransferase DNMT3A gene. Typical TBRS clinical features are overgrowth, intellectual disability, and minor facial anomalies. However, since the syndrome was first described in 2014, a widening spectrum of abnormalities is being described. Cardiovascular abnormalities are less commonly reported but can be a major complication of the syndrome. This article describes a family of three individuals diagnosed with TBRS in adulthood and highlights the variable expression of cardiovascular features. A 34-year-old proband presented with progressive aortic dilatation, mitral valve (MV) regurgitation, left ventricular (LV) dilatation, and ventricular arrhythmias. The affected family members (mother and brother) were diagnosed with MV regurgitation, LV dilatation, and arrhythmias. Exome sequencing and computational protein analysis suggested that the novel familial DNMT3A mutation Ser775Tyr is located in the methyltransferase domain, however, distant from the active site or DNA-binding loops. Nevertheless, this bulky substitution may have a significant effect on DNMT3A protein structure, dynamics, and function. Analysis of peripheral blood cfDNA and transcriptome showed shortened mononucleosome fragments and altered gene expression in a number of genes related to cardiovascular health and of yet undescribed function, including several lncRNAs. This highlights the importance of epigenetic regulation by DNMT3A on cardiovascular system development and function. From the clinical perspective, we suggest that new patients diagnosed with congenital DNMT3A variants and TBRS require close examination and follow-up for aortic dilatation and valvular disease because these conditions can progress rapidly. Moreover, personalized treatments, based on the specific DNMT3A variants and the different pathways of their function loss, can be envisioned in the future.

ARG1 as a promising biomarker for sepsis diagnosis and prognosis: evidence from WGCNA and PPI network

Background

Sepsis is a life-threatening multi-organ dysfunction caused by the dysregulated host response to infection. Sepsis remains a major global concern with high mortality and morbidity, while management of sepsis patients relies heavily on early recognition and rapid stratification. This study aims to identify the crucial genes and biomarkers for sepsis which could guide clinicians to make rapid diagnosis and prognostication.

Methods

Preliminary analysis of multiple global datasets, including 170 samples from patients with sepsis and 110 healthy control samples, revealed common differentially expressed genes (DEGs) in peripheral blood of patients with sepsis. After Gene Oncology (GO) and pathway analysis, the Weighted Gene Correlation Network Analysis (WGCNA) was used to screen for genes most related with clinical diagnosis. Also, the Protein-Protein Interaction Network (PPI Network) was constructed based on the DEGs and the hub genes were found. The results of WGCNA and PPI network were compared and one shared gene was discovered. Then more datasets of 728 experimental samples and 355 control samples were used to prove the diagnostic and prognostic value of this gene. Last, we used real-time PCR to confirm the bioinformatic results.

Results

Four hundred forty-four common differentially expressed genes in the blood of sepsis patients from different ethnicities were identified. Fifteen genes most related with clinical diagnosis were found by WGCNA, and 24 hub genes with most node degrees were identified by PPI network. ARG1 turned out to be the unique overlapped gene. Further analysis using more datasets showed that ARG1 was not only sharply up-regulated in sepsis than in healthy controls, but also significantly high-expressed in septic shock than in non-septic shock, significantly high-expressed in severe or lethal sepsis than in uncomplicated sepsis, and significantly high-expressed in non-responders than in responders upon early treatment. These all demonstrate the performance of ARG1 as a key biomarker. Last, the up-regulation of ARG1 in the blood was confirmed experimentally.

Conclusions

We identified crucial genes that may play significant roles in sepsis by WGCNA and PPI network. ARG1 was the only overlapped gene in both results and could be used to make an accurate diagnosis, discriminate the severity and predict the treatment response of sepsis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00240-1.

Interleukin 2 receptor subunit beta as a novel hub gene plays a potential role in the immune microenvironment of abdominal aortic aneurysms

BACKGROUND

Abdominal aortic aneurysm (AAA) is potentially life threatening and characterized by immune-inflammatory cell infiltration and extracellular matrix degradation. Currently, pharmacotherapy mainly aims to control risk factors without reversion of the dilated aorta. This study analyzed the immune-inflammatory response and identified the immune-related hub genes of AAA.

METHOD

Gene Expression Omnibus datasets (GSE57691, GSE47472 and GSE7084) were downloaded. After identification of GSE57691 differentially expressed genes (DEGs), weighted gene co-expression network analysis of the DEGs was performed. Through enrichment analysis of each module and screening in Immunology Database and Analysis Portal, immune-related hub genes were identified via protein-protein interaction (PPI) network construction and lasso regression. CIBERSORT was utilized to analyze AAA immune infiltration. The correlations between the immune-related hub genes and infiltrating immune cells were investigated. Receiver operating characteristic (ROC) curve analysis was performed to determine immune-related hub gene cutoff values, which were validated in GSE47472 and GSE7084.

RESULT

In GSE57691, 1,018 DEGs were identified. Five modules were identified in the co-expression network. The blue and green modules were found to be related to immune-inflammatory responses, and 61 immune-related genes were identified. PPI and lasso regression analyses identified FOS, IL-6 and IL2RB as AAA immune-related hub genes. CIBERSORT analysis indicated significantly increased infiltration of naive B cells, memory activated CD4 T cells, follicular helper T cells, monocytes and M1 macrophages and significantly decreased infiltration of M2 macrophages in AAA compared with normal samples. IL2RB was more strongly associated with immune infiltration in AAA than were FOS and IL6. The IL2RB area under the ROC curve (AUC) value was > 0.9 in both the training and validation set, demonstrating its strong, stable diagnostic value in AAA.

CONCLUSION

AAA and normal samples had different immune infiltration statuses. IL2RB was identified as an immune-related hub gene and a potential hub gene with significant diagnostic value in AAA.