Bioinformatic Exploration of Hub Genes and Potential Therapeutic Drugs for Endothelial Dysfunction in Hypoxic Pulmonary Hypertension

Association between A/G ratio and arterial stiffness among Chinese type 2 diabetics: A cross-sectional study

BACKGROUND

The android-to-gynoid fat ratio (A/G ratio), an emerging indicator of obesity independent of body mass index (BMI), has yet to be conclusively associated with arterial stiffness in type 2 diabetes mellitus (T2DM). This study aimed to construct a nomogram to estimate arterial stiffness risk in diabetics and explore the interaction effect between A/G ratio and traditional obesity indicators on arterial stiffness.

METHODS

1313 diabetics were divided into 2 groups based on arterial stiffness identified by brachial ankle pulse wave velocity (baPWV), and demographic and clinical features were measured. The LASSO and multivariate logistics regression were used to develop the nomogram. Calibration curve, decision curve analysis (DCA) and receiver operating characteristic (ROC) were applied to assess calibration and clinical usefulness. Interaction effect analysis was performed to quantify the interactive relationship of A/G ratio and obesity indicators on arterial stiffness.

RESULTS

6 independent predictors (age, gender, A/G ratio, SBP, LDL-C and HbA1C) were screened to construct a nomogram prediction model. The calibration curve demonstrated satisfactory agreement between predicted and actual probability, and the nomogram exhibited clinical beneficial at the threshold between 8 % and 95 % indicated by DCA. The area under curve (AUC) was 0.918 and 0.833 for training and external set, respectively. Further investigation revealed A/G ratio and BMI acted positively synergistically towards arterial stiffness, and in BMI-based subgroup analysis, elevated A/G ratio was a significant risk factor for arterial stiffness, especially in normal BMI.

CONCLUSIONS

A/G ratio showed a substantial association with arterial stiffness, and the nomogram, incorporating age, gender, A/G ratio, SBP, LDL-C, and HbA1c, exhibited high predictive value. A/G ratio measurement in BMI-normal individuals assisted in identifying cardiovascular diseases early.

New genetic drivers in hemorrhagic hereditary telangiectasia

BACKGROUND

Hereditary hemorrhagic telangiectasia (HHT) is a rare vascular disease inherited in an autosomal dominant manner. Disease-causing variants in endoglin (ENG) and activin A receptor type II-like 1 (ACVRL1) genes are detected in around 90% of the patients; also 2% of patients harbor pathogenic variants at SMAD4 and GDF2. Importantly, the genetic cause of 8% of patients with clinical HHT remains unknown. Here, we present new putative genetic drivers of HHT.

METHODS

To identify new HHT genetic drivers, we performed exome sequencing of 19 HHT patients and relatives with unknown HHT genetic etiology. We applied a multistep filtration strategy to catalog deleterious variants and prioritize gene candidates based on their known relevance in endothelial cell biology. Additionally, we performed in vitro validation of one of the identified variants.

RESULTS

We identified variants in the INHA, HIF1A, JAK2, DNM2, POSTN, ANGPTL4, FOXO1 and SMAD6 genes as putative drivers in HHT. We have identified the SMAD6 p.(Glu407Lys) variant in one of the families; this is a loss-of-function variant leading to the activation of the BMP/TGFβ signaling in endothelial cells.

CONCLUSIONS

Variants in these genes should be considered for genetic testing in patients with HHT phenotype and negative for ACVRL1/ENG mutations.

Transcriptomic Analysis of Tight Junction Proteins Demonstrates the Aberrant Expression and Function of Zona Occludens 2 (ZO-2) Protein in Stanford Type A Aortic Dissection

OBJECTIVE

Thoracic aortic aneurysm dissection (TAAD) represents a cardiac surgery emergency characterized by the disrupted integrity of the aortic wall and is associated with poor prognosis. In this context, the identification of biomarkers implicated in the pathobiology of TAAD is crucial. Our aim in the present original in silico study is to assess the differential gene expression profile of the tight junction proteins (TJPs) in patients with TAAD and to propose novel biomarkers for the diagnosis and prognosis of this disease.

METHODS

We implemented bioinformatics methodology in order to construct the gene network of the TJPs family, identify the differentially expressed genes (DEGs) in pathologic aortic tissue excised from patients with TAAD as compared to healthy aortic tissue, and assess the related biological functions and the associated miRNA families.

RESULTS

Data regarding the transcriptomic profile of selected genes were retrieved and incorporated from three microarray datasets, including 23 TAAD and 20 healthy control samples. A total of 32 TJPs were assessed. The zona occludens 2 (ZO-2) protein encoded by the gene TJP2 was significantly under-expressed in patients with TAAD compared to the control group (p = 0.009). ZO-2 was associated with fair discrimination and calibration traits in predicting the TAAD presentation. CpG islands of ZO-2 were demonstrated. No important difference was found regarding ZO-2 expression between aneurysmal non-dissected and healthy control aortic tissue. Finally, we performed gene set enrichment analysis (GSEA) and uncovered the major biological functions and miRNA families (hsa-miR-155-5p, hsa-miR-1-3p, hsa-miR-2118-5p, hsa-miR-4691-3p, and hsa-miR-1229-3p) relevant to ZO-2.

CONCLUSIONS

These outcomes demonstrated the important role of ZO-2 in the pathobiology of TAAD.