Screening of Secretory Proteins Linking Major Depressive Disorder with Heart Failure Based on Comprehensive Bioinformatics Analysis and Machine Learning.

BACKGROUND: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD's involvement in HF pathogenesis and identify candidate biomarkers for the diagnosis of MDD with HF. METHODS: GWAS data for MDD and HF were collected, and Mendelian randomization (MR) analysis was performed to investigate the causal relationship between MDD and HF. Differential expression analysis (DEA) and WGCNA were used to detect HF key genes and MDD-associated secretory proteins. Protein-protein interaction (PPI), functional enrichment, and cMAP analysis were used to reveal potential mechanisms and drugs for MDD-related HF. Then, four machine learning (ML) algorithms (including GLM, RF, SVM, and XGB) were used to screen candidate biomarkers, construct diagnostic nomograms, and predict MDD-related HF. Furthermore, the MCPcounter algorithm was used to explore immune cell infiltration in HF, and MR analysis was performed to explore the causal effect of immunophenotypes on HF. Finally, the validation of the association of MDD with reduced left ventricular ejection fraction (LVEF) and the performance assessment of diagnostic biomarkers was accomplished based on animal models mimicking MDD. RESULTS: The MR analysis showed that the MDD was linked to an increased risk of HF (OR = 1.129, p < 0.001). DEA combined with WGCNA and secretory protein gene set identified 315 HF key genes and 332 MDD-associated secretory proteins, respectively. Through PPI and MCODE analysis, 78 genes were pinpointed as MDD-related pathogenic genes for HF. The enrichment analysis revealed that these genes were predominantly enriched in immune and inflammatory regulation. Through four ML algorithms, two hub genes (ISLR/SFRP4) were identified as candidate HF biomarkers, and a nomogram was developed. ROC analysis showed that the AUC of the nomogram was higher than 0.90 in both the HF combined dataset and two external cohorts. In addition, an immune cell infiltration analysis revealed the immune dysregulation in HF, with ISLR/SFRP4 displaying notable associations with the infiltration of B cells, CD8 T cells, and fibroblasts. More importantly, animal experiments showed that the expression levels of ISLR (r = -0.653, p < 0.001) and SFRP4 (r = -0.476, p = 0.008) were significantly negatively correlated with LVEF. CONCLUSIONS: The MR analysis indicated that MDD is a risk factor for HF at the genetic level. Bioinformatics analysis and the ML results suggest that ISLR and SFRP4 have the potential to serve as diagnostic biomarkers for HF. Animal experiments showed a negative correlation between the serum levels of ISLR/SFRP4 and LVEF, emphasizing the need for additional clinical studies to elucidate their diagnostic value.

Opioids-Induced Long QT Syndrome: A Challenge to Cardiac Health.

The challenge posed by opioid overdose has become a significant concern for health systems due to the complexities associated with drug prohibition, widespread clinical use, and potential abuse. In response, healthcare professionals have primarily concentrated on mitigating the hallucinogenic and respiratory depressant consequences of opioid overdose to minimize associated risks. However, it is crucial to acknowledge that most opioids possess the capacity to prolong the QT interval, particularly in cases of overdose, thereby potentially resulting in severe ventricular arrhythmias and even sudden death if timely intervention is not implemented. Consequently, alongside addressing the typical adverse effects of opioids, it is imperative to consider their cardiotoxicity. To enhance comprehension of the correlation between opioids and arrhythmias, identify potential targets for prompt intervention, and mitigate the hazards associated with clinical utilization, an exploration of the interaction between drugs and ion channels, as well as their underlying mechanisms, becomes indispensable. This review primarily concentrates on elucidating the impact of opioid drugs on diverse ion channels, investigating recent advancements in this domain, and attaining a deeper understanding of the mechanisms underlying the prolongation of the QT interval by opioid drugs, along with potential interventions.

The Advantages, Challenges, and Future of Human-Induced Pluripotent Stem Cell Lines in Type 2 Long QT Syndrome.

Type 2 long QT syndrome (LQT2) is the second most common subtype of long QT syndrome and is caused by mutations in KCHN2 encoding the rapidly activating delayed rectifier potassium channel vital for ventricular repolarization. Sudden cardiac death is a sentinel event of LQT2. Preclinical diagnosis by genetic testing is potentially life-saving.Traditional LQT2 models cannot wholly recapitulate genetic and phenotypic features; therefore, there is a demand for a reliable experimental model. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) meet this challenge. This review introduces the advantages of the hiPSC-CM model over the traditional model and discusses how hiPSC-CM and gene editing are used to decipher mechanisms of LQT2, screen for cardiotoxicity, and identify therapeutic strategies, thus promoting the realization of precision medicine for LQT2 patients.

Evaluating Membrane Electrical Properties of SMMC7721 Cells with TiO2 NPs Applications to Cytotoxicity by Dielectric Spectroscopy.

Titanium dioxide nanoparticles (TiO2 NPs) represent one of the most frequently applied nanomaterials in numerous areas of daily life. Recent studies show that TiO2 exposure increases the occupational risk of liver injury and inflammation, and even liver cancer to the workers of factories handling these NPs. However, the potential risks and biophysical effects of TiO2 on hepatic cells need extensive evaluation. To this end, we explored the electrophysiological changes in the human liver cancer cell line SMMC7721 following exposure to TiO2 NPs. TiO2 NPs decreased the first (Δε1) and second dielectric relaxation intensity (Δε2) of the SMMC7721 cells by 6.62% and 0.86% respectively, and significantly increased the first characteristic frequency (fc1, 4.82%) and the first Cole-Cole parameter (ß1, 1.24%). The double spherical-shell model showed that TiO2 NPs significantly lowered the permittivity of unit-membrane and capacitance, as well as the conductivity of extracellular fluid, cytoplasm, and nuclear contents compared to the untreated control. Conclusively, this study revealed that TiO2 NPs induce cytotoxic effects by disrupting the permeability and electrical conductivity of unit membranes. Further, we report that dielectric spectrum combined with model parameter analysis can evaluate the bioelectrical effects of TiO2 NPs on human liver cancer cells.