Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.

Low-normal free triiodothyronine as a predictor of post-operative atrial fibrillation after surgical coronary revascularization.

Background: Recent studies have focused on the association between thyroid function within normal range and cardiovascular diseases, especially on free triiodothyronine (FT3) levels. This study aims to evaluate the effects of normal FT3 level on new-onset atrial fibrillation (AF) in patients with surgical coronary revascularization. Methods: The patients who underwent surgical coronary revascularization were enrolled in the retrospective study. Thyroid function was tested after an overnight fast on the first morning of hospitalization. Serum FT3 level was divided into quartile groups within the normal range. Hazards ratios (HRs) of FT3 level for AF were analyzed by COX proportional hazard model. Results: This study included 503 patients with a mean [standard deviation (SD)] age of 63 (±9) years, and 396 (78.73%) were male. Post-operative AF (POAF) occurred in 120 (23.86%) patients at a median of two days after surgical coronary revascularization. The cumulating incidence of AF was significantly higher in the FT3 quartile 1 (Q1) group especially in older patients as evidenced by Kaplan-Meier analysis. Additionally, the patients who experienced AF had longer hospital stays, the same result was also found in the FT3 Q1 group. Further study demonstrated that low-normal FT3 was an independent predictor of POAF [HR =1.52, 95% confidence interval (CI): 1.01, 2.28, P=0.045]. Conclusions: Low-normal FT3 is associated with an increased risk of POAF and is an independent predictor of POAF. Patients who experienced AF have longer hospital stays. The findings may help to identify patients with surgical coronary revascularization at a higher risk for the development of AF.

Research progress on predicting atrial fibrillation recurrence after radiofrequency ablation based on electrocardiogram-related parameters.

Atrial fibrillation (AF) is the most common arrhythmia. It is associated with increased stroke risks, thromboembolism, and other complications, which are great life and economic burdens for patients. In recent years, with the maturity of percutaneous catheter radiofrequency ablation (RFA) technology, it has become a first-line therapy for AF. However, some patients still experience AF recurrence (AFR) after RFA, which can cause serious consequences. Therefore, it is critical to identify appropriate parameters that are predictive of prognosis and to be able to translate the parameters easily into the clinical setting. Here, we reviewed possible predicting indicators for AFR, focusing on all the electrocardiogram indicators, such as P wave duration, PR interval and so on. It may provide valuable information for guiding clinical works.

Exploring an immune cells-related molecule in STEMI by bioinformatics analysis.

BACKGROUND: ST-elevated myocardial infarction (STEMI) is the leading cause of mortality worldwide. The mortality rate of heart attacks has decreased due to various preventive factors and the development of early diagnostic resuscitation measures, but the long-term prognosis remains poor. The present study aimed to identify novel serum biomarkers in STEMI patients and explored a possible new mechanism of STEMI from an immune molecular angle with bioinformatics analysis. METHODS: Gene expression profiles were obtained from Gene Expression Omnibus (GEO) database. Differential gene analysis, machine learning algorithms, gene set enrichment analysis, and immune cell infiltration analysis were conducted using R software. RESULTS: We identified 146 DEGs (differentially expressed genes) in the integrated dataset between the STEMI and CAD (coronary artery disease) groups. Immune infiltration analysis indicated that eleven cell types were differentially infiltrated. Through correlation analysis, we further screened 25 DEGs that showed a high correlation with monocytes and neutrophils. Afterwards, five genes consistently selected by all three machine learning algorithms were considered candidate genes. Finally, we identified a hub gene (ADM) as a biomarker of STEMI. AUC curves showed that ADM had more than 80% high accuracy in all datasets. CONCLUSIONS: In this study, we explored a potentially new mechanism of STEMI from an immune molecular perspective, which might provide insights into the pathogenesis of STEMI. ADM positively correlated with monocytes and neutrophils, suggesting its potential role in the immune response during STEMI. Additionally, we validated the diagnostic performance of ADM in two external datasets, which could help to develop new diagnostic tools or therapeutic strategies.

Incidence and risk factors for early and late reoperation following lumbar fusion surgery.

STUDY DESIGN: Retrospective cohort study. PURPOSE: The aim of our study was to determine the rates and indications of reoperations following primary lumbar fusion, as well as the independent risk factors for early and late reoperation. METHODS: We retrospectively reviewed patients who underwent lumbar fusion surgery between January 2017 and March 2020. All patients were followed up for more than 2 years. Characteristics, laboratory tests, primary diagnosis and surgery-related variables were compared among the early reoperation (< 3 months), the late reoperation (> 3 months) and the non-reoperation groups. Multivariable logistic regression analysis was used to identify independent risk factors for early and late reoperations. RESULTS: Of 821 patients included in our studies, 34 patients underwent early reoperation, and 36 patients underwent late reoperation. The cumulative reoperation rate was about 4.1% (95% CI 3.8-4.5%) at 3 months, 6.2% (95% CI 5.9-6.5%) at 1 year and 8.2% (95% CI 8.0-8.5%) at 3 years. Multivariable analysis indicated that osteoporosis (odds ratio [OR] 3.6, 95% CI 1.2-10.5, p = 0.02) and diabetes (OR 2.1, 95% CI 1.1-4.5, p = 0.04) were independently associated with early reoperation and multilevel fusion (OR 2.4, 95% CI 1.1-5.4, p = 0.03) was independently associated with late reoperation. CONCLUSIONS: The most common reasons for early reoperation and late operation were surgical site infection and adjacent segment diseases, respectively. Osteoporosis and diabetes were independent risk factors for early reoperation, and multilevel fusion was independent risk factor for late reoperation. Surgeons should pay more attention to these patients, and future studies should consider the effects of follow-up periods on results.