A comparison of gene expression profiles in patients with coronary artery disease, type 2 diabetes, and their coexisting conditions

Type 2 diabetes (T2D) and coronary artery disease (CAD) often coexist and cause substantial public health and economic burden world-wide. CAD has long been established as a complication of T2D. The plaque formation in T2D patients may narrow the coronary arteries and thus predispose the occurrence of heart attack. It is assumed that there is an intrinsic interplay between T2D and CAD, in the form of shared etiology and pathophysiological mechanisms. The two diseases have shared common risk factors such as, age, gender, anthropometric, metabolic, socioeconomic and lifestyle variables, as well as psychosocial stress and environmental pollutant exposure. In addition, both diseases are characterized by a chronic inflammatory process [1, 2] and disorders of the coagulation system [3].

T2D has been associated with increased risk of cardiovascular disease and death [4, 5]. The underlying mechanisms may involve a complex interplay between genes predisposing to insulin resistance and those independently regulating lipid metabolism, coagulation processes and biological responses of the arterial wall [6]. The shared susceptibility regions (bin 9.3 and 6.5) were observed across T2D, obesity and CAD by Wu et al, suggesting the possibility of shared pathophysiology and risk through genetic pleiotropy [7], which may account for their frequent coexistence. However, there has been limited success in correlating T2D with CAD in terms of pathophysiologic changes up to now [8].

Peripheral blood gene expression profile has been used to reflect pathological conditions in a variety of diseases [9–14]. The increasing genomic information has provided an opportunity to better understand the complex biological processes of diseases, especially after the emergence of high throughput technologies. Previous studies have reported the gradual change in circulating gene expression profiles in patients with different extent of CAD [14].

Therefore, to support a hypothesis of an intrinsic interplay between T2D and CAD, we compared the peripheral blood gene expression profiles of T2D, CAD and coexisting conditions, to better understand the association of the three metabolic disorders.

In this study, we used RNA-seq to identify unique peripheral blood gene expression signatures of T2D, CAD, and coexisting condition. Previous literature have revealed that there is an intrinsic interplay between T2D and CAD, while the detailed mechanism remains unclear. Toward this end, we compared the gene expression profiles of T2D, CAD and coexisting condition to show the association in-between them, and tried to explain the shared pathophysiology.

Here, PBMCs are usually selected to monitor posttranslational modifications relevant to many diseases [24], updating the underlying molecular events of diseases. Furthermore, the feature of minimal invasion makes differentially expressed genes in PBMCs suitable as predictive biomarkers in clinical studies. Some studies that analyzed gene expression profile in peripheral blood cell of CAD or T2D have already been performed [25–27]. There were common features and characteristic differences between the current study and previous studies. T2D and CAD both manifest disordered coagulation system, local inflammatory process, or lipid-related disorder. The shared pathophysiology between T2D and CAD may be explained by the common genetic variant, such as CDKN2A/2B, ADIPOR1 [28] and TCF7L2 variants [29]. In our study, many differentially expressed genes from the individual comparisons of T2D, CAD and coexisting condition to control was also found to be overlapped among the three disorders, suggesting shared pathophysiology. Also Spearman’s test for gene expression correlation revealed the significant correlation of the three disorders, among which the correlation between T2D and T2D + CAD was the most significant.

The overlapping genes were mainly enriched in GO terms of viral infectious cycle, anti-apoptosis, endocrine pancreas development, innate immune response, and blood coagulation, etc. Those overlapping genes were mainly involved in pathways of Ribosome (RPS3A, UBA52, RSL24D1, RPL7, RPL39, RPL21, RPS24, and RPS12). Ribosomal proteins are involved in cell growth and proliferation, differentiation and apoptosis. Ribosome biogenesis disruption could activate the p53 signaling pathway, resulting in cell cycle arrest and apoptosis. Moreover, it has been correlated to clinical manifestations in pathological states, such as cardiovascular diseases and metabolic disorders. RpL17 inhibited vascular smooth muscle cell growth, and limits carotid intima thickening in mice [30]. Animal study has shown that ribosomal protein S6kinase4 plays a crucial role in pancreatic β-cell function and glucose homeostasis [31]. Ribosomes dysfunction may be applied in the early diagnosis of chronic diseases, such as cancer and cardiovascular diseases.

Besides the common signatures among T2D, CAD and coexisting condition, we also analyzed the gene sets which functioned specially in the development of T2D or CAD. In the T2D-specific PPI networks, the significant hub proteins were TCF4 (Degree = 169), SKP1 (Degree = 164) and UBE2W (Degree = 75). TCF4, also named transcription factor 7-like 2 (TCF7L2), encodes a transcription factor involved in the Wnt signaling pathway. TCF4 stimulates the proliferation of pancreatic β-cells, regulates embryonic development of the pancreatic mass, and induces the production of the insulinotropic hormone glucagon-like peptide-1 (GLP-1) in intestinal endocrine cells [32]. It plays a critical role in blood glucose homeostasis. Recently, numerous studies have demonstrated an association between TCF7L2 genotype and T2D [33–37]. In a meta-analysis by Wang J et al., the TCF7L2 rs7903146 polymorphism was found to be associated with increased T2D risk in the Chinese population [38]. There were also evidences for a strong interplay between TCF7L2 polymorphisms and CAD [29, 39]. In another study on nine hundred subjects referred for cardiac catheterization for CAD diagnosis by Sousa AG et al., a significant association was identified between the TCF7L2 rs7903146 polymorphism and the prevalence and severity of CAD [40].

Interestingly, differentially expressed genes between T2D and normal controls were significantly enriched in Parkinson’s disease, suggesting that a shared pathophysiology of Parkinson’s disease and T2D. The link has been confirmed in several epidemiological studies [41, 42]. The mechanism behind this association may be that there was a reciprocal regulation between insulin and dopamine [43].

In case of CAD-specific PPI networks, the significant hub proteins were HIF1A, SMAD1 and SKIL. In the provided expression data from GSE23561, we found that SMAD1 and SKIL were specifically up-regulated in CAD with no change in T2D, while HIF1A was both differentially expressed in CAD and T2D, but with opposite trends. In CAD patients, oxygen supply was limited as a result of reduced blood flow brought about by atherosclerotic plaque formation and inflammatory processes taking place within the vascular endothelium [44]. As a consequence of oxidative stress in hypoxic conditions, hypoxia-inducible factor-1 alpha (HIF-1α) was produced to involve in adaptive and repair mechanisms. HIF-1α is a transcriptional factor encoded by the HIF1A gene, functioning in the preservation of oxygen homeostasis. HIF-1α may participate in the occurrence and progression of CAD through activating various genes such as VEGF, HO-1, and ET-1. HIF-1α mRNA was found to be markedly up-regulated in both monocytes and lymphocytes of CAD patients than that of controls, and the expression level of HIF-1α was highly correlated with severity of atherosclerosis and higher level of collateral score [45, 46]. In addition, other studies have investigated the correlation between HIF1A polymorphism and CAD. A recent study showed that HIF-1α polymorphisms (rs11549465 and rs11549467) were associated with clinical type and formation of coronary collaterals [47]. The rs2057482 SNP of HIF1A was showed to be associated with increased susceptibility to premature CAD, which may be applied in clinical diagnostics as a susceptibility marker of premature CAD [48].

However, there were some evidences showing that the HIF1A was crucial for first phase insulin secretion and glucose homeostasis. Nagy et al. revealed that polymorphism (g.C45035TSNP, rs11549465) of HIF1A were associated with T1D and T2D in a Caucasian population [49]. Cheng et al. identified that HIF1A could play an important role in β cell function via binding to ARNT promoter in a mouse with β cell–specific Hif1a disruption [50]. Besides, hyperglycaemia appeared to down-regulated HIF-1α mRNA expression in ischaemic myocardium, and inhibited the defective response of HIF-1α to ischaemia [51, 52], explaining a positive association between hyperglycaemia at the time of the event and subsequent mortality from myocardial infarction. The dual role of HIF1A connects the pathogenesis of T2D with that of CAD. For this study, we determined the up-regulation of HIF1A in CAD, but didn’t detect the expression of down-regulation of HIF1A in T2D in RNA-seq results. The limited sample may explain the inconsistency between RNA-seq results and that of published studies. Further large-sample studies are needed to confirm these results.

In our study, SMAD1 and SKIL were both significantly up-regulated in CAD, remained unchangeable in T2D, which were involved in SMAD pathway. SMAD1 polymorphism was reported to be associated with sudden cardiac arrest in CAD patients [53]. In a transgenic mice model with cardiac-specific overexpression of smad1, Masaki M found that transgenic mice had significantly smaller myocardial infarctions and fewer apoptotic deaths of cardiomyocytes after ischemia-reperfusion (I/R) injury, suggesting a role of SMAD1 in cardioprotection against I/R injury [54]. SKIL, a component of the SMAD pathway, was showed to be involved in cardiac fibrosis [55, 56]. There remained no reports on the association with CAD.

In summary, our data showed that the gene expression profile of T2D, CAD, and coexisting condition were all distinguishable from controls, and displayed common and specific gene expression pattern in each disordered state. To note, viral infectious cycle, anti-apoptosis, endocrine pancreas development, innate immune response and blood coagulation were common biological processes among the three conditions. This study provides some evidences in the transcript level to show the association of T2D, CAD and coexisting condition. For this study, the number of sample for RNA-seq was small, which is a limitation of this study, so studies of large sample size need to be conducted to confirm this conclusion.