Previous researches demonstrated the aetiology of stable CAD and MI, however, the predictive biomarkers and treatment targets are still limited [5, 18]. Previous researches demonstrated that CAD progression, including healthy subjects to stable CAD and stable CAD to STEMI, can induce plaques progression and plaques progression can, in turn, deteriorate CAD progression [6,7,8]. In the current study, the datasets GSE56885 and GSE59867 were used to screen new potential biomarkers for unstable plaques and CAD progression. The dataset GSE56885 discussed the difference of peripheral blood samples between stable CAD patients and healthy subjects, while the dataset GSE59867 discussed the difference of peripheral blood samples between stable CAD patients and STEMI patients. Because the former expression difference was higher than that of later, the fold change cutoff value of the latter was also lower. Although the GSE59867 dataset contained 436 samples, out of which 390 samples from patients (n = 111) with STEMI at four time points (admission, discharge, 1 month after MI, and 6 months after MI) and 46 samples from patients (n = 46) with stable CAD and without a history of MI were included in the study, we only chose admission patients data with STEMI and stable CAD because MI can accelerate atherosclerosis at 1d after MI, thus inducing recurrent event due to status changing of coronary artery walls or plaques [6]. The dataset GSE12521 was analyzed for the further validation of seed genes. After that, KLRD1, FOSL2 and LILRB3 were demonstrated to serve as a novel biomarker for plaques progression and CAD progression.
In this study, by reanalyzing GSE56885, the results of GO and KEGG analysis demonstrated that with the CAD progression, cell immune response and cytokines interaction activated, mainly due to the progression of the plaque, which is consistent with previous reports [19, 20]. PPI network construction unravelled 9 seed genes using NTA. On the other hand, by reanalyzing GSE59867, the results demonstrated that immune system responses, especially innate immune response, were activated in STEMI patients compared to stable CAD patients, which may be due to the lipid accumulation and further deterioration of coronary vessel status [21,22,23]. The status can be partly reversed by β-blockers not calcium antagonists [24]. PPI network construction in GSE59867 showed 10 seed genes which can be applied to further validation. After validation, three genes were screened. ROC curve and linear regression demonstrated that the combination of KLRD1, FOSL2 and LILRB3 can be applied as a potential biomarker for CAD progression. The AUC was 0.938, suggesting the clinical value in plaques progression and CAD progression. Then the three genes were also validated in mice MI model, demonstrating that KLRD1 and LILRB3 were high-expressed at 1d after MI and FOSL2 expression was low-expressed at 1d and 1w after MI compared to SHAM group. The AUCs of protein KLRD1, FOSL2 and LILRB3, were 0.771, 0.938 and 0.972, respectively. So, KLRD1, FOSL2 and LILRB3 may be the diagnostic and prognostic biomarkers in MI progression period (from stable CAD to unstable CAD) and MI recurrence for plaques progression.
The mRNA expressions of KLRD1 and LILRB3 increased in unstable plaques compared to stable plaques, while the mRNA expression of FOSL2 decreased. KLRD1 (CD94) forms heterodimers with NKG2 resulting in a receptor complex expressed on NK cells and some CD8+ T cells [25]. The mRNA expression of KLRD1 often increased in the inflammatory response, for instance, HIV infection, trachoma, and gut dysbiosis [25,26,27]. Its expression is always with an elevation of Interleukin(IL)-17 and IL-17-related cytokines expression and inhibited by IL-15 [28]. In this study, the mRNA expressions of KLRD1 raised in STEMI patients compared to stable CAD patients and also increased in unstable plaques compared to stable plaques. Leukocyte immunoglobulin-like receptors (LILRBs), associated with MHC class I and microglobulin, activated the JAK/STAT signalling pathway [29] and regulated the suppressive function and fate of MDSCs [30]. In addition, LILRA3 can also induce Takayasu’s arteritis (P < 1 × 10−5) [31, 32]. In this study, LILRB3 may also play a critical role in the status changing of coronary artery wall and plaques in atherogenesis and CAD progression. Fos-like antigen 2 (FOSL2), as an AP-1 transcription factor, can promote the progenitor to cardiomyocyte transition [33] and FOSL2 over-expression reversed the miR-155 effects on promoting the persistence of exhausted T cells [34]. FOSL2 was also observed to interact with lipid-metabolism-related gene and Fatty acid elongase 4, thus regulating lipid metabolism [35]. In our study, FOSL2 expression declined in unstable plaques compared to stable plaques, which may be due to the lipid metabolic disturbance and response to cell-mediated immunity.
Other seed genes, such as FOS, SOCS3 and MCL1, should also be mentioned due to their special clinical value in cardiovascular diseases. MI can result in the expression change of early response gene FOS, which might be correlated to the neural activity disorders induced by MI [36, 37]. In this study, FOS was both the seed gene in GSE56885 and GSE59867. In other words, FOS is a key biomarker about neural activity for CAD progression and MI occurrence. The suppressor of cytokine signalling 3 (SOCS3), a negative-feedback regulator of the JAK/STAT signaling [38], was enriched as a seed gene in STEMI patients and as a top30 ranking neighbour in stable CAD patients, which may be associated with platelet activity and inflammation. Platelet-induced SOCS3 expression regulated macrophage reprogramming in plaque by increasing IL-6, IL-1β, TNF-αexpression and declined phagocytic capacity that cannot resolve inflammation and maintain plaque growth. A second cohort also indicated that SOCS1: SOCS3 ratio was associated with inflammation and platelet activity [39]. Therefore, SOCS3 may be a potential diagnosis and treatment target for myocardial injury under stress [40]. In addition, myeloid cell leukaemia sequence 1 (MCL1) is critical for mitochondrial function and autophagy in the heart [41]. In this study, MCL1 was enriched in stable CAD and its expression also elevated in STEMI patients with recurrent events compared to those without recurrent events. Rac1 impeded apoptosis through AKT2/MCL1 and increased cell proliferation through JNK/c-JUN/Cyclin-D1 in myocardial hypoxia [42]. MCL1 can also inhibit the mitochondrial apoptosis and maintain cell viability, however, this process was impeded by FBW7. FBW7 can participate in ROS-induced myocardial injury by degrading MCL1 [43]. Therefore, MCL1 may serve as a biomarker of myocardial cell injury in CAD progression.
There are some limitations which should be mentioned. Firstly, only three seed genes were validated for plaques progression. There may be some false negatives because of the enrichment methods and validation methods. More researches are still needed to proceed with integrated bioinformatic analysis about plaques progression. Secondly, we aimed to investigate the potential targets to status changing of plaques and coronary wall to treat CAD progression and MI recurrence. So, we can only discuss a few significant seed genes and their neighbours in this paper. Maybe we can discuss others later. Lastly, the sample sizes of dataset GSE56885 and GSE120521 were not too large, however, after the calculation of sample sizes, they still met the further enrichment analysis and other statistical methods.