Mechanism and therapeutic strategies of depression after myocardial infarction

Investigation of the shared molecular mechanisms and hub genes between myocardial infarction and depression

Background

The pathogenesis of myocardial infarction complicating depression is still not fully understood. Bioinformatics is an effective method to study the shared pathogenesis of multiple diseases and has important application value in myocardial infarction complicating depression.

Methods

The differentially expressed genes (DEGs) between control group and myocardial infarction group (M-DEGs), control group and depression group (D-DEGs) were identified in the training set. M-DEGs and D-DEGs were intersected to obtain DEGs shared by the two diseases (S-DEGs). The GO, KEGG, GSEA and correlation analysis were conducted to analyze the function of DEGs. The biological function differences of myocardial infarction and depression were analyzed by GSVA and immune cell infiltration analysis. Four machine learning methods, nomogram, ROC analysis, calibration curve and decision curve were conducted to identify hub S-DEGs and predict depression risk. The unsupervised cluster analysis was constructed to identify myocardial infarction molecular subtype clusters based on hub S-DEGs. Finally, the value of these genes was verified in the validation set, and blood samples were collected for RT-qPCR experiments to further verify the changes in expression levels of these genes in myocardial infarction and depression.

Results

A total of 803 M-DEGs, 214 D-DEGs, 13 S-DEGs and 6 hub S-DEGs (CD24, CSTA, EXTL3, RPS7, SLC25A5 and ZMAT3) were obtained in the training set and they were all involved in immune inflammatory response. The GSVA and immune cell infiltration analysis results also suggested that immune inflammation may be the shared pathogenesis of myocardial infarction and depression. The diagnostic models based on 6 hub S-DEGs found that these genes showed satisfactory combined diagnostic performance for depression. Then, two molecular subtypes clusters of myocardial infarction were identified, many differences in immune inflammation related-biological functions were found between them, and the hub S-DEGs had satisfactory molecular subtypes identification performance. Finally, the analysis results of the validation set further confirmed the value of these hub genes, and the RT-qPCR results of blood samples further confirmed the expression levels of these hub genes in myocardial infarction and depression.

Conclusion

Immune inflammation may be the shared pathogenesis of myocardial infarction and depression. Meanwhile, hub S-DEGs may be potential biomarkers for the diagnosis and molecular subtype identification of myocardial infarction and depression.

Formononetin improves cardiac function and depressive behaviours in myocardial infarction with depression by targeting GSK-3β to regulate macrophage/microglial polarization

BACKGROUND

Depression is a common complication after myocardial infarction (MI) that can seriously affect the prognosis of MI.

PURPOSE

To investigate whether formononetin could ameliorate MI injury and depressive behaviours in a mouse model of MI with depression and elucidate its underlying molecular mechanisms.

METHODS

Haemodynamic measurements (systolic blood pressure (SYS), the maximum rate of rise of LV pressure (± dp/dtmax)) and behavior tests (tail suspension test, sucrose preference test, forced swimming test) were used to evaluate the effects of formononetin on male C57BL/6N mice after left anterior descending (LAD) coronary artery ligation and chronic unpredictable stress. RT-qPCR, immunohistochemistry, immunofluorescence analysis, western blotting, molecular docking technology, surface plasmon resonance and gene-directed mutagenesis were used to clarify the underlying mechanism.

RESULTS

Formononetin significantly suppressed the depressive behaviours and improved cardiac dysfunction in MI with depression mice model. Formononetin inhibited M1 polarization in macrophages/microglia, while promoting M2 polarization. Importantly, elevated serum IL-6 and IL-17A levels were found in patient with MI, and the patient serum induced M1 microglial polarization; however, formononetin reversed the polarization. Further mechanistic studies showed that formononetin inhibited GSK-3β activity and downstream Notch1 and C/EBPα signaling pathways. Covalent molecular docking showed that formononetin bound to Cys199 of GSK-3β and it has a high affinity for GSK-3β. When Cys199 was mutation, the inhibitory effect of formononetin on GSK-3β activity and M1 polarization in macrophages/microglia were also partly blocked.

CONCLUSIONS

Our results firstly uncovered that formononetin improved cardiac function and suppressed depressive behaviours in mice after MI with depression by targeting GSK-3β to regulate macrophage/microglial polarization. More importantly, IL-6 and IL-17A produced after MI may cause neuroinflammation, which might be the key factors for depression. Formononetin may be a potential drug for treating MI with depression.