Upregulation of long non-coding RNA myocardial infarction-associated transcription is correlated with coronary artery stenosis and elevated inflammation in patients with coronary atherosclerotic heart disease.

INTRODUCTION

Coronary atherosclerotic heart disease (CAD) is induced by precipitating coronary artery stenosis or occlusion, exacerbating to myocardial ischemia, hypoxia, or necrosis. 1 CAD is characterized by predominant formation of arterial plaques composing of lipid, calcium, and inflammatory cells, where plaque rupture facilitates the formation of thrombus and consequently leads to myocardial infarction (MI) with cessation of blood flow as the cause of death. 2 The notable risk factors for CAD include smoking, hyperlipidemia, hypertension, diabetes mellitus, psychological stress, and family history. 3 Currently, revascularization remains as the conventional treatment for CAD patients, which can ameliorate the clinical symptoms of patients and improve the quality of life and survival rate. 4 CAD is associated with significant morbidity and mortality in chronic non‐communicable diseases worldwide, and notably, an increasing prevalence of CAD over the past decades in China poses serious risk to the health of patients with vast medical burdens on society. 5 , 6 Therefore, the exploration of early screening and gene diagnosis protocols is of great significance for early diagnosis, timely intervention, and prognosis improvement of CAD.

Dysregulation of long non‐coding RNAs (lncRNAs) distinctively classified the transcriptome profiles of CAD from healthy control and is concerned with the pathogeny of CAD through immune‐related molecular functions and biological processes. 7 Accumulating evidence has ascertained the expression pattern, biological function, and diagnostic value of lncRNAs in CAD. 8 , 9 LncRNA MI‐associated transcription (MIAT) gene is located on the long arm of chromosome 22 (22q12.1) and transcript five exons. 10 A functional analysis identified the presence of a susceptible variant to MI in exon 5 of MIAT, thus speculating the potential function of MIAT in MI. 11 A study by Zhu et al. has determined an elevated lncRNA MIAT expression in the blood samples of patients with ischemic stroke and, thus, supported the functionality of MIAT as an independent diagnostic and prognostic indicator of ischemic stroke. 12 Compared with healthy donors, serum lncRNA‐MIAT is evidently increased in CAD patients. 9 Currently, the clinical research results of lncRNA MIAT in CAD are controversial, and whether MIAT can function as a biomarker of CAD ascertains further investigation. This study, herein, investigated the expression pattern and clinic significance of lncRNA MIAT in CAD patients, along with its potential regulatory mechanism, which shall provide a certain reference value and identify a novel target for the management of CAD.

MATERIALS AND METHODS

Subject and grouping

A total of 231 consecutive patients with unexplained chest pain or suspected symptoms of CAD who underwent coronary angiography in the department of cardiology of The Affiliated Hospital of Qingdao University from June 2016 to June 2018 were selected as study subjects. Inclusion criteria were as follows: (a) unidentified chest pain or suspected CAD symptoms, (b) over 18 years of age, and (c) provided written informed consent prior to participation. Exclusion criteria were as follows: (a) an existing congenital heart disease, cardiomyopathy (invasive cardiomyopathy, hypertrophic cardiomyopathy, dilated cardiomyopathy, etc.), or vasospasm angina pectoris; (b) contraindications to coronary angiography; (c) undergone immunosuppressive therapy within 3 months; (d) severe infection, inflammation, or autoimmune disease; (e) underwent revascularization before; (f) hematologic tumor or solid tumor; (g) inability to regular follow up; and (h) pregnant or lactating women. All subjects received coronary angiography, and the coronary angiograms were evaluated based on the American Heart Association (AHA)/American College of Cardiology (ACC) classification. Definitive CAD was signified by over 50% stenosis of at least one major epicardial vessel. All subjects were assigned into the CAD group ( N = 155) and the non‐CAD control group ( N = 76) based on coronary angiograms. The fasting peripheral venous blood was withdrawn prior to coronary angiography in the morning, anticoagulated using ethylene diamine tetraacetic acid, and centrifuged at a high speed at 3 h after collection (at 4°C, 3000 g, 20 min). The separated plasma was preserved at −80°C for subsequent experimentation.

Detection of clinicopathological indicators

The included clinical data were as follows: parameters of demographic data (age, gender, and body mass index [BMI]), risk factors of CAD (smoking, family history of CAD, hypertension, hyperlipidemia, and diabetes), and biochemical indicators (fasting blood glucose [FBG], triglyceride [TG], total cholesterol [TC], high‐density lipoprotein‐cholesterol [HDL‐C], low‐density lipoprotein‐cholesterol [LDL‐C], serum creatinine [Scr], serum uric acid [SUA], C‐react protein [CRP], and Gensini score). Automatic biochemical analyzer (2700, Olympus, Tokyo, Japan) was used to detect the levels of various biochemical indicators. Gensini score was employed to evaluate the degree of coronary artery stenosis. 13 Gensini score included of a lumen stenosis score and a lesion site score. Lumen stenosis was scored as follows: 1, <25%; 2, ≥25% to <50%; 4, ≥50% to <75%; 8, ≥75% to <90%; 16, ≥90% to <99%; 32, 99% to 100%. For estimating the lesion site score, the proliferation factors of the main vascular segment were measured in reference to the functional significance of the blood supply area by that segment. The product of the stenosis score and lesion site score was calculated as the total Gensini score. Moreover, hypertension was defined based on the Chinese Guidelines for the Prevention and Treatment of Hypertension 2010, while the degrees of hyperlipidemia and diabetes were defined in strict accordance with the Standards of Medical Care in Diabetes 2010 by the American Diabetes Association.

Reverse transcription quantitative polymerase chain reaction

The total RNA content was extracted using the TRIzol reagent (Invitrogen Inc., Carlsbad, CA, USA) and reverse transcribed into cDNA using the PrimeScript RT reagent kit (Takara, Dalian, China). The quantitative polymerase chain reaction was performed on the ABI 7900HT fast PCR real‐time system (Applied Biosystems, Foster City, CA, USA) using SYBR® Premix Ex Taq™ II (Takara). The reaction conditions were as follows: pre‐denaturation at 95°C for 10 min, and 40 cycles of denaturation at 95°C for 10 s, annealing at 60°C for 20 s, and extension at 72°C for 34 s. The relative expression of miR and mRNA was calculated based on the 2 −ΔΔCt method, with U6 or glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH) serving as internal reference. Primers (Table 1 ) were synthesized by Sangon Biotech Co., Ltd (Shanghai, China).

Enzyme‐linked immunosorbent assay

Levels of tumor necrosis factor α (TNF‐α), IL‐6, IL‐8, and IL‐10 and expression of pregnancy‐associated plasma protein A (PAPPA) were detected using the enzyme‐linked immunosorbent assay (ELISA) kits (R&D Systems, Minneapolis, MN, USA). The coated ELISA plates were supplemented with 10‐μL serum samples and 40‐μL sample diluents. After sealing, the plates were incubated at 37°C for 20 min. After the reaction plates were rinsed five times, 50 μL of the ELISA reagent was added, and the plates were sealed and incubated at 37°C for 30 min. Following a rinse, the reaction plates were supplemented with 50‐μL chromogenic agent A and 50‐μL chromogenic agent B, mixed, and developed at 37°C for 15 min in conditions devoid of light. Next, 50 μL of the termination reagent was supplemented to each well, with evident color change from blue to yellow. The absorbance value at the wavelength of 450 nm was evaluated using Multiskan™ Fibre Channel (FC) microplate reader (Thermo Fisher Scientific Inc., Waltham, MA, USA). The level of each index was calculated by plotting the standard curve.

Dual‐luciferase reporter gene assay

The binding sits between lncRNA MIAT and miR‐29b‐3p, and miR‐29b‐3p and PAPPA were predicted by Starbase ( http://starbase.sysu.edu.cn/index.php ). 14 The binding sequence and mutation sequence of miR‐29b‐3p with lncRNA MIAT and PAPPA were amplified and cloned into the pmirGLO Dual‐Luciferase miRNA Target Expression vector (Promega, Madison, WI, USA). Next, the wild‐type plasmids (lncRNA MIAT‐WT/PAPPA‐WT) and mutant‐type plasmids (lncRNA MIAT‐MUT/PAPPA‐MUT) were constructed. The constructed vectors were co‐transfected with negative control of mir‐29b‐3p mimic (mimic NC) or miR‐29b‐3p mimic (Gene Pharma, Shanghai, China) into the human aortic smooth muscle cells (HA‐VSMC) (American Type Culture Collection, Manassas, VA, USA). The luciferase activity was detected after 48 h.

Statistical analysis

Data were analyzed and introduced using the SPSS 22.0 software (IBM Corp., Armonk, NY, USA) and GraphPad Prism 7.01 (GraphPad Software Inc., San Diego, CA, USA). The normal distribution of continuous variables was verified by Shapiro–Wilk (W test). The variable data were presented as mean ± standard deviation (SD; normal distribution), or the median and interquartile range (IQR), or count and percentage (categorical variables). Comparison was performed using the t test, Wilcoxon rank‐sum test, or χ 2 test. Correlation analysis was performed using Pearson's correlation coefficient. Multivariate regression analysis was used to correct the confounding of other factors to identify the independent correlation between lncRNA MIAT and CAD, and Gensini score. The diagnostic value of MIAT in CAD was evaluated by plotting the receiver operating characteristic (ROC) curve. In all statistical references, a value of p < 0.05 was indicative of statistical significance.

RESULTS

Comparison of clinical characteristics between CAD patients and non‐CAD controls

A total of 231 subjects were included in this study, including 76 non‐CAD controls and 155 CAD patients. In terms of the demographic characteristics, the age of CAD patients was higher than that of the non‐CAD controls ( p < 0.001). In terms of evaluation of the risk factors of CAD, the prevalence of smoking, hypertension, and diabetes were all higher in CAD patients (all p < 0.05). In terms of biochemical indicators, the level of HDL‐C was markedly decreased while the content of CRP was increased (all p < 0.001) in CAD patients. No significant difference was evident in other clinical characteristics (all p > 0.05). The clinical characteristics are presented in Table 2 .

LncRNA MIAT was highly expressed in peripheral blood of CAD patients and had high clinical diagnostic efficacy

LncRNA MIAT expression in the peripheral blood of CAD patients (median, 4.23 [1.22–6.50]) was notably higher than that in non‐CAD controls (median, 1.64 [0.05–2.93]; p < 0.01; Figure 1A ). To analyze whether MIAT level had an independent correlation with CAD, according to the results in Table 2 , we incorporated p < 0.1‐related indicators (including age, smoking, hypertension, diabetes, HDL‐C, and CRP) and lncRNA MIAT into a multifactor logistic regression model (Gensini score was a pathological indicator of coronary heart disease and was not included in the multivariate regression model). The results showed that after adjustment of age, smoking, hypertension, diabetes, HDL‐C, and CRP in the logistic regression model, the patients with a high expression pattern of lncRNA MIAT showed an elevated risk of CAD compared to patients with a low expression pattern of lncRNA MIAT (OR = 7.298, 95% CI: 3.173–16.788) (Table 3 ), thereby signifying the independent correlation between lncRNA MIAT and CAD. In addition, the ROC analysis was conducted to further evaluate the diagnostic and predictive ability of lncRNA MIAT in CAD. The area under the curve was calculated as 0.908, the specificity as 71.43%, and the sensitivity as 70.00% (Figure 1B ). Altogether, an elevated lncRNA MIAT in the peripheral blood of CAD patients was indicative of high clinical diagnostic efficacy.

Correlation analysis of lncRNA MIAT expression and clinical indicators in CAD patients

As shown in Table 2 , significant differences were identified in parameters, such as age, smoking habits, hypertension, diabetes, HDL‐C, and CRP between the CAD patients and non‐CAD controls. To further determine the role of lncRNA MIAT in CAD, we performed a correlation analysis between the lncRNA MIAT expression and the abnormal clinical indicators. The results revealed a positive correlation between the lncRNA MIAT expression pattern and the content of CRP ( r = 0.769, p < 0.0001; Figure 2A ) in peripheral blood samples. No correlation was evident between lncRNA MIAT and parameters, such as age, smoking, hypertension, diabetes, high HDL‐C, and any other abnormal clinical indicators (all p > 0.05). In addition, lncRNA MIAT expression elicited a positive correlation with the Gensini score in CAD patients ( r = 0.776, p < 0.0001; Figure 2B ), thereby indicating that the higher expression pattern of lncRNA MIAT in CAD patients corresponds with a higher degree of coronary artery stenosis.

To further study whether there was an independent correlation between lncRNA MIAT and Gensini score, we analyzed the correlation between the Gensini score and LDL, HDL, hypertension, and diabetes and successfully identified a correlation between Gensini score with HDL, LDL, and CRP (all p < 0.01), but not with other indicators. Next, the patients were assigned into two groups according to the Gensini score (<40 points; ≥40 points). Multivariate regression was performed with the Gensini score as a dependent variable, and lncRNA MIAT, MIAT, HDL, LDL, and CRP significantly correlated with Gensini score as independent variables. The results showed that after adjusting HDL, LDL, and CRP, the Gensini score of patients with high lncRNA MIAT expression was higher relative to the patients with a low lncRNA MIAT expression (OR = 1.974, 95% CI: 1.199–3.251; Table 4 ), thereby suggesting the independent association between lncRNA MIAT and Gensini score.

Correlation analysis of lncRNA MIAT expression and inflammatory markers in CAD patients

Inflammation may be implicated in the initiation and progression of CAD. 15 The levels of pro‐inflammatory cytokines TNF‐α, IL‐6, IL‐8, and anti‐inflammatory cytokine IL‐10 in the peripheral blood of non‐CAD controls and CAD patients were detected. CAD patients showed elevated levels of TNF‐α, IL‐6, and IL‐8 ( t = 12.56, t = 16.79, t = 9.77, all p < 0.01) with a reduced IL‐10 level in the peripheral blood ( t = 8.22, p < 0.01; Figure 3A ). Then, we analyzed the correlation between lncRNA MIAT and inflammatory markers in the peripheral blood of CAD patients. The LncRNA MIAT expression pattern was positively correlated with the levels of TNF‐α, IL‐6, and IL‐8 ( r = 0.549, r = 0.587, r = 0.511, all p < 0.0001; Figure 3B–D ) and negatively correlated with the IL‐10 level ( r = −0.678, p < 0.0001; Figure 3E ).

Correlation analysis of lncRNA MIAT, miR‐29b‐3p, and PAPPA expression in CAD patients

MIAT can function as a ceRNA of miR to regulate the proliferation and migration of aortic smooth muscle cells induced by ox‐LDL. 16 Starbase identified a binding relationship between lncRNA MIAT and multiple miRs, including miR‐29b‐3p. Existing literature has documented evident upregulation of miR‐29b‐3p in endothelial dysfunction induced by various cardiovascular risk factors. 17 Hence, we detected the miR‐29b‐3p expression pattern in the peripheral blood of CAD patients and analyzed the correlation between miR‐29b‐3p and lncRNA MIAT. The miR‐29b‐3p expression pattern was downregulated in the peripheral blood of CAD patients compared with the non‐CAD controls ( t = 25.85, p < 0.01; Figure 4A ), with identification of a negative correlation with the lncRNA MIAT expression pattern ( r = −0.665, p < 0.0001; Figure 4B ). The binding relationship between miR‐29b‐3p and lncRNA MIAT was verified in HA‐VSMCs using the dual‐luciferase reporter gene assay. HA‐VSMCs co‐transfected with PGL‐MIAT‐WT and miR‐320a mimic showed lowered luciferase activity ( p < 0.05; Figure 4E ). To determine the downstream genes modulated by lncRNA MIAT/miR‐29b‐3p, we predicted the target genes of miR‐29b‐3p through Starbase. The pro‐atherosclerotic properties of PAPPA have been validated by modulation of various pathological processes of atherosclerosis, including lipid accumulation, vascular inflammation, endothelial dysfunction, proliferation, and migration of vascular smooth muscle cells, plaque stability, and thrombosis. 18 Therefore, we detected the PAPPA expression pattern in the peripheral blood of CAD patients and analyzed the correlation between PAPPA and lncRNA MIAT and miR‐29b‐3p. An upregulated PAPPA expression pattern was evident in the peripheral blood of CAD patients compared with the non‐CAD controls ( t = 26.34, p < 0.01; Figure 4A ) and signified its positive correlation with lncRNA MIAT expression pattern ( r = 0.676, p < 0.0001; Figure 4C ) and negative correlation with miR‐29b‐3p expression pattern ( r = −0.556, p < 0.0001; Figure 4D ). Meanwhile, the binding relationship between miR‐29b‐3p and PAPPA was verified in HA‐VSMCs using dual‐luciferase reporter gene assay ( p < 0.05; Figure 4F ). These results speculated the ability of lncRNA MIAT to competitively bind to miR‐29b‐3p with PAPPA serving as a ceRNA, thereby eliciting functionality in CAD.

DISCUSSION

CAD occurs due to gradual accumulation of fatty substances in the coronary artery, leading to coronary artery stenosis and in severe cases interrupting the blood supply to the heart. 19 LncRNA MIAT by modulation of microvascular dysfunction can radically facilitate lncRNA‐based diagnosis and therapies for vascular diseases. 20

LncRNAs have been extensively adopted as crucial regulatory factors in numerous pathophysiological pathways of cardiovascular system. 21 Qu et al. have identified a significantly elevated lncRNA MIAT expression in a mouse model of MI and speculated that knockdown of MIAT contributes to improving cardiac function and suppressing interstitial fibrosis. 22 Notably, Tan et al. have elicited an elevated lncRNA MIAT expression in the serum of patients with CAD, which is considered as an independent risk factor for CAD. 9 In consistency with existing studies, our findings denoted the diagnostic significance of lncRNA MIAT upregulation in CAD. Then, the correlation analysis between lncRNA MIAT expression and abnormal clinical indicators was conducted to further determine the role of lncRNA MIAT in CAD. CRP, a plasma protein predominantly secreted by the liver, emerges as a sensitive and dynamic inflammatory marker, and the level of CRP serves as a competent indicator to predict any residual cardiovascular risk. 23 , 24 Gensini score is an angiographic tool used to evaluate the severity of CAD, which can also predict the future cardiovascular risk. 25 Our results revealed a positive correlation of lncRNA MIAT expression in peripheral blood with the level of CRP and the Gensini score in CAD patients. In brief, a higher the expression of lncRNA MIAT in CAD patients corresponds with the higher degree of coronary artery stenosis. An existing study explicitly implicated the upstream markers of inflammation in the pathophysiology of CAD as they can regulate the inflammatory cascade. 26 Indeed, the levels of the pro‐inflammatory cytokines such as TNF‐α, IL‐6, and IL‐8 have been validated as independent predictors for the risk of CAD and coronary events. 27 As an anti‐inflammatory cytokine, IL‐10 fundamentally prevents host damage by inhibition of the immune response to pathogens; 28 thus, the reduction of IL‐10 is associated with the treatment of inflammation and pathogenesis of CAD. 29 Consistently, the CAD patients demonstrated with elevated levels of TNF‐α, IL‐6, IL‐8, and a reduced IL‐10 level in the peripheral blood. Moreover, a notably elevated lncRNA MIAT expression in the patients with type‐2 diabetes is related with increase in the levels of pro‐inflammatory markers. 30 Our results also exhibited a positive correlation between the lncRNA MIAT expression and the levels of pro‐inflammatory cytokines (TNF‐α, IL‐6, and IL‐8), while a negative correlation was apparent with the level of anti‐inflammatory cytokine (IL‐10).

Thereafter, we explored the underlying mechanism of MIAT in CAD. Existing evidence indicates the functionality of lncRNA to serve as a miR sponge to reduce the abundance of target miRs and indirectly modulate the function of genes or mRNA. 31 For instance, knockdown of lncRNA MIAT can diminish the necrotic core size and improve the atherosclerosis plaque stability by sponging miR‐149‐5p. 32 LncRNA MIAT has elicited carcinogenic functionality in multiple myeloma by repressing the miR‐29b expression. 33 An existing study validated the participation of the miR‐29 family in the pathological changes of cardiovascular diseases. 34 Essentially, the miR‐29b expression can serve as a novel biomarker for the identification of atherosclerosis. 35 miR‐29b‐3p is downregulated in coronary sinus samples and participates in pathways related to heart disease. 36 However, limited information about the role of miR‐29b‐3p in CAD could be obtained. Our study was the first to show that miR‐29b‐3p was downregulated in the peripheral blood of CAD patients, and was negatively correlated with lncRNA MIAT expression.

Subsequently, we aimed to investigate the downstream target of lncRNA MIAT/miR‐29b‐3p. PAPPA was selected among the target genes of miR‐29b‐3p predicted by Starbase. Existing literature has identified the effect of lncRNA MIAT/miR‐148b/PAPPA axis on the proliferation and migration of HA‐VSMC induced by ox‐LDL. 16 Principally, PAPPA serves as a vital regulator of the cardiovascular system, where overexpressing PAPPA facilitates the formation of atherosclerotic lesion in mouse arterial smooth muscle. 37 Therefore, we detected the PAPPA expression in the peripheral blood of CAD patients and analyzed the correlation between PAPPA and lncRNA MIAT and miR‐29b‐3p. The results revealed an increased PAPPA expression in the peripheral blood of CAD patients, with an evident positive correlation with lncRNA MIAT expression and a negative correlation with the miR‐29b‐3p expression. The elevation in PAPPA is related to age‐related diseases, and PAPPA knockout mice is associated with longer survival time span and increased resistance to the formation of atherosclerotic plaques. 38 , 39 Altogether, lncRNA MIAT played a role in CAD via the miR‐29b‐3p/PAPPA axis, which might provide a novel target for the diagnosis and treatment of CAD.

To conclude, findings uncovered in our study demonstrated that lncRNA MIAT was upregulated in the peripheral blood of CAD patients, and possessed clinical diagnostic significance. In addition, lncRNA MIAT might be functional in CAD via the miR‐29b‐3p/PAPPA axis. Our results may bear a certain reference value for the early diagnosis of CAD and provide a novel target for management of CAD. However, we simply verified the effect of lncRNA MIAT in CAD by sponging miR‐29b‐3p, and the specific regulatory mechanism warrant further investigation. Furthermore, we did not explore changes in lncRNA MIAT in the course of disease and treatment. Due to the limitation of the design of this study, the information about intervention and statin use in some included patients was missing, so we failed to conduct a multivariate regression analysis on the prognostic factors of major adverse cardiovascular events (MACE) to elucidate the independent association between lncRNA MIAT and MACE. Multivariate analysis of MACE prognostic factors will be more significant for the study of lncRNA MIAT in the prognosis of CAD. In the future, we shall conduct comprehensive investigations on the underlying mechanisms of lncRNA MIAT, miR‐29b‐3p, and PAPPA in CAD from the perspective of epigenetics.

CONFLICT OF INTEREST

All authors declare no conflict of interest.

Yan Z‐S, Zhang N‐C, Li K, Sun H‐X, Dai X‐M, Liu G‐L. Upregulation of long non‐coding RNA myocardial infarction‐associated transcription is correlated with coronary artery stenosis and elevated inflammation in patients with coronary atherosclerotic heart disease. Kaohsiung J Med Sci. 2021;37:1038–1047. 10.1002/kjm2.12444

REFERENCES

1. Sanchis‐Gomar F, Perez‐Quilis C, Leischik R, Lucia A. Epidemiology of coronary heart disease and acute coronary syndrome. Ann Transl Med. 2016;4:256.

2. Li H, Sun K, Zhao R, Hu J, Hao Z, Wang F, et al. Inflammatory biomarkers of coronary heart disease. Front Biosci (Schol Ed). 2018;10:185–96.

3. Ades PA, Gaalema DE. Coronary heart disease as a case study in prevention: potential role of incentives. Prev Med. 2012;55 (Suppl:S75–9.

4. Kiaii B, Teefy P. Hybrid coronary artery revascularization: a review and current evidence. Innovations (Phila). 2019;14:394–404.

5. Johnson T. Reducing the prevalence and costs of heart disease. NCSL Legisbrief. 2015;23:1–2.

6. Zhu L, Ho SC, Sit JW. The experiences of Chinese patients with coronary heart disease. J Clin Nurs. 2012;21:476–84.

7. Liao J, Wang J, Liu Y, Li J, Duan L. Transcriptome sequencing of lncRNA, miRNA, mRNA and interaction network constructing in coronary heart disease. BMC Med Genomics. 2019;12:124.

8. Li L, Wang L, Li H, Han X, Chen S, Yang B, et al. Characterization of LncRNA expression profile and identification of novel LncRNA biomarkers to diagnose coronary artery disease. Atherosclerosis. 2018;275:359–67.

9. Tan J, Liu S, Jiang Q, Yu T, Huang K. LncRNA‐MIAT increased in patients with coronary atherosclerotic heart disease. Cardiol Res Pract. 2019;2019:6280194.

10. Cole CG, McCann OT, Collins JE, Oliver K, Willey D, Gribble SM, et al. Finishing the finished human chromosome 22 sequence. Genome Biol. 2008;9:R78.

11. Ishii N, Ozaki K, Sato H, Mizuno H, Susumu S, Takahashi A, et al. Identification of a novel non‐coding RNA, MIAT, that confers risk of myocardial infarction. J Hum Genet. 2006;51:1087–99.

12. Zhu M, Li N, Luo P, Jing W, Wen X, Liang C, et al. Peripheral blood leukocyte expression of lncRNA MIAT and its diagnostic and prognostic value in ischemic stroke. J Stroke Cerebrovasc Dis. 2018;27:326–37.

13. Gensini GG. A more meaningful scoring system for determining the severity of coronary heart disease. Am J Cardiol. 1983;51:606.

14. Li JH, Liu S, Zhou H, Qu LH, Yang JH. starBase v2.0: decoding miRNA‐ceRNA, miRNA‐ncRNA and protein‐RNA interaction networks from large‐scale CLIP‐Seq data. Nucleic Acids Res. 2014;42:D92–7.

15. Larsen SB, Grove EL, Wurtz M, Neergaard‐Petersen S, Hvas AM, Kristensen SD. The influence of low‐grade inflammation on platelets in patients with stable coronary artery disease. Thromb Haemost. 2015;114:519–29.

16. Zhou Y, Ma W, Bian H, Chen Y, Li T, Shang D, et al. Long non‐coding RNA MIAT/miR‐148b/PAPPA axis modifies cell proliferation and migration in ox‐LDL‐induced human aorta vascular smooth muscle cells. Life Sci. 2020;256:117852.

17. Wang F, Ma H, Liang WJ, Yang JJ, Wang XQ, Shan MR, et al. Lovastatin upregulates microRNA‐29b to reduce oxidative stress in rats with multiple cardiovascular risk factors. Oncotarget. 2017;8:9021–34.

18. Yu XH, He LH, Gao JH, Zhang DW, Zheng XL, Tang CK. Pregnancy‐associated plasma protein‐A in atherosclerosis: molecular marker, mechanistic insight, and therapeutic target. Atherosclerosis. 2018;278:250–8.

19. Mendes A. Coronary heart disease: self‐care, communication and quality of life. Br J Community Nurs. 2015;20:42.

20. Yan B, Yao J, Liu JY, Li XM, Wang XQ, Li YJ, et al. lncRNA‐MIAT regulates microvascular dysfunction by functioning as a competing endogenous RNA. Circ Res. 2015;116:1143–56.

21. Arslan S, Berkan O, Lalem T, Ozbilum N, Goksel S, Korkmaz O, et al. Long non‐coding RNAs in the atherosclerotic plaque. Atherosclerosis. 2017;266:176–81.

22. Qu X, Du Y, Shu Y, Gao M, Sun F, Luo S, et al. MIAT is a pro‐fibrotic long non‐coding RNA governing cardiac fibrosis in post‐infarct myocardium. Sci Rep. 2017;7:42657.

23. Emerging Risk Factors C, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, et al. C‐reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta‐analysis. Lancet. 2010;375:132–40.

24. Ridker PM. From C‐reactive protein to interleukin‐6 to interleukin‐1: moving upstream to identify novel targets for atheroprotection. Circ Res. 2016;118:145–56.

25. Battermann S, Milzi A, Dettori R, Burgmaier K, Marx N, Burgmaier M, et al. High cardiovascular risk of patients with type 2 diabetes is only partially attributed to angiographic burden of atherosclerosis. Diab Vasc Dis Res. 2020;17:1479164120953612.

26. Kaptoge S, Seshasai SR, Gao P, Freitag DF, Butterworth AS, Borglykke A, et al. Inflammatory cytokines and risk of coronary heart disease: new prospective study and updated meta‐analysis. Eur Heart J. 2014;35:578–89.

27. Madjid M, Fatemi O. Components of the complete blood count as risk predictors for coronary heart disease: in‐depth review and update. Tex Heart Inst J. 2013;40:17–29.

28. Saraiva M, O'Garra A. The regulation of IL‐10 production by immune cells. Nat Rev Immunol. 2010;10:170–81.

29. Bing XJ, Sun XJ, Shen GH, Xie H, Ma MY. Levels of IL‐8, IL‐10 in patients with chronic periodontitis and coronary heart disease. Shanghai Kou Qiang Yi Xue. 2015;24:598–601.

30. Sathishkumar C, Prabu P, Mohan V, Balasubramanyam M. Linking a role of lncRNAs (long non‐coding RNAs) with insulin resistance, accelerated senescence, and inflammation in patients with type 2 diabetes. Hum Genomics. 2018;12:41.

31. Zhao L, Hu K, Cao J, Wang P, Li J, Zeng K, et al. lncRNA miat functions as a ceRNA to upregulate sirt1 by sponging miR‐22‐3p in HCC cellular senescence. Aging (Albany NY). 2019;11:7098–122.

32. Ye ZM, Yang S, Xia YP, Hu RT, Chen S, Li BW, et al. LncRNA MIAT sponges miR‐149‐5p to inhibit efferocytosis in advanced atherosclerosis through CD47 upregulation. Cell Death Dis. 2019;10:138.

33. Fu Y, Liu X, Zhang F, Jiang S, Liu J, Luo Y. Bortezomib‐inducible long non‐coding RNA myocardial infarction associated transcript is an oncogene in multiple myeloma that suppresses miR‐29b. Cell Death Dis. 2019;10:319.

34. Yang Q, Wu F, Mi Y, Wang F, Cai K, Yang X, et al. Aberrant expression of miR‐29b‐3p influences heart development and cardiomyocyte proliferation by targeting NOTCH2. Cell Prolif. 2020;53:e12764.

35. Huang YQ, Li J, Chen JY, Zhou YL, Cai AP, Huang C, et al. The association of circulating MiR‐29b and interleukin‐6 with subclinical atherosclerosis. Cell Physiol Biochem. 2017;44:1537–44.

36. Marques FZ, Vizi D, Khammy O, Mariani JA, Kaye DM. The transcardiac gradient of cardio‐microRNAs in the failing heart. Eur J Heart Fail. 2016;18:1000–8.

37. Conover CA, Mason MA, Bale LK, Harrington SC, Nyegaard M, Oxvig C, et al. Transgenic overexpression of pregnancy‐associated plasma protein‐A in murine arterial smooth muscle accelerates atherosclerotic lesion development. Am J Physiol Heart Circ Physiol. 2010;299:H284–91.

38. Boldt HB, Bale LK, Resch ZT, Oxvig C, Overgaard MT, Conover CA. Effects of mutated pregnancy‐associated plasma protein‐A on atherosclerotic lesion development in mice. Endocrinology. 2013;154:246–52.

39. Conover CA, Bale LK, Mader JR, Mason MA, Keenan KP, Marler RJ. Longevity and age‐related pathology of mice deficient in pregnancy‐associated plasma protein‐A. J Gerontol A Biol Sci Med Sci. 2010;65:590–9.