Plasma CircANKRD36 as an Epigenetic Diagnostic Marker of Coronary Artery Disease in Patients with Type 2 Diabetes Mellitus
Nearmeen M. Rashad 1, Gehan A Ibrahem1, Ayman A.M.
Nsrallah1, Marwa A.E. Ahmed
1Internal Medicine Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
Corresponding author:Nearmeen M. Rashad
Tel.: +20 1224248642; E-mail address: [email protected], [email protected]
https://orcid.org/0000-0002-8587-0616
Marwa Ahmed Elsayed Ahmed: [email protected] Ayman A.M. Nsrallah:mailto:[email protected]
Gehan A Ibrahim:[email protected]
Abstract
Background:Cardiovascular diseases (CVD) remain the leading cause of death worldwide. Among cardiovascular diseases, coronary artery disease (CAD) is the single largest cause of death.The epigenetic regulatory role of ncRNAs in CAD is still evolving. We aimed to investigate theplasma level of circ. ankyrin repeat domain36 (circANKRD36) in patients with CAD and type 2 diabetes mellitus(T2DM)
Methods: A total number of 40 subjects with T2DM and 20 age and sex matched healthy controls were enrolled for the study. T2DM patients subdivided to T2DM without CAD (n=20) andT2DM with CAD (n=20)All patients were subjected to general and cardiological examination and investigation. Theplasma of circANKRD36 was measured using quantitative real-time (qRT) PCR.
Results: The plasma levels of circANKRD36 were significantly increased in patients with CAD and T2DM compared to control. p˂0.001*. The plasma levels of circANKRD36 were significantly positive correlated with cardio metabolic risk
factors and linear regression test revealed thatthat waist /hip ratio as well as SYNTAX score were independently correlated with epigenetic marker. Our results revealed that the cutoff values plasma levels of circANKRD36 were 1.735 and the AUC was 0 .877 (95% CI =0.790-0.963) additionally, the sensitivities and the specificities were 85%
and 70%,
Conclusion:T2DM groups had statistically significant higher values of circANKRD36 compared to control group. Plasma levels of circANKRD36 were significantly increased in T2DM patients with CAD compared with T2DM patients without CAD.Thus, it could be an epigenetic marker for prediction of CAD inpatients with T2DM.
Keywords:coronary artery disease;T2DM; CAD; circRNAs; epigenetic.
Introduction
Coronary artery disease (CAD) is the leading cause of mortality and morbidity in the world [1],accounting for almost 110 million affected people in 2015 [3] and generating nearly 7.6 million deaths [2].
Although the precise mechanisms responsible for the onset of CAD are still unknown, it is a multifactorial disease, which is influenced by interacting endogenous and exogenous factors [4,5]. CAD has a complex etiology, which initiates with chronic inflammation and endothelial dysfunction in coronary arteries. Subsequently, atherosclerotic plaques are formed in the intima of coronary arteries [6], where they can decrease or even prevent the blood supply to the heart, thus leading to myocardial ischemia, unstable angina, acute myocardial infarction (AMI) and sudden coronary death, which are the major clinical manifestations of CAD [7].
It has been postulated that the development of CAD is determined by genetics and epigenetics also plays an influential role. The most significant risk factors for CAD are hypertension, dyslipidemia, diabetes, smoking, sedentary life, obesity, depression and excessive alcohol intake [8]. Growing evidence highlights the evidence that CAD is a starting point for other cardiovascular diseases such as AMI, therefore investigating new biomarkers for early diagnosis and prediction play an essential role to prevent progression. Currently, the most common biomarkers in CAD are inflammatory proteins, being C-reactive protein (CRP) the best studied [9].
Mounting evidence showed that noncoding RNAs (ncRNAs) are major components of epigenetic regulation, including microRNA (miRNAs), long noncoding RNA (lncRNA) and circular RNA (circRNA), [10] ncRNAs can also act controlling the expression of other ncRNAs [11].
There is increasing evidence that these ncRNAs are largely implicated in cardiovascular disorders [12]. circANKRD36 has been reported to be related to inflammatory response in type 2 diabetes. Up to now, no Egyptian studies have specifically exploited the role of circANKRD36 in CAD-T2DM settings, but this scenario will likely change in the future as alterations in many circRNAs in association with CAD have been noticed.Early detection of epigenetic dysregulation may help in the design of new strategies to alleviate CAD complications, as these epigenetic markers could enable early prediction of subclinical atherosclerosis. Thus, this study aimed to measure plasma levelcircANKRD36 in T2DM patients with or without CAD.
2. Subjects and methods 2.1. Subjects
This study included 60 unrelated subjects. 40 patients with T2DM recruited from diabetes and endocrinology outpatient clinic of Internal Medicine Department of Zagazig University Hospitals and 20 healthy control subjects, who were matched to cases by gender and ethnic origin. The diagnosis of diabetes
.
according to ADA 2020The enrolled diabetic patients classified into two groups:20 patients without CAD and 20 patients with CAD. Patients with CAD were defined as those having severe angiostenosis (>50 %) in at least one major coronary artery determined by angiography based on WHO criteria. CAD cases were selected retrospectively from patients admitted to outpatient clinic of Internal Medicine Department of Zagazig University Hospitals and who fulfilled the inclusion criteria.
Coronary arteriography was performed for all patients by the Judkins technique for assessment of the lesion’s distribution and description and assessment of the severity of atherosclerotic CAD by using SYNTAX score.
All patients were subjected to thorough history taking and subjected to general and cardiological examination and investigation. None of the participants had liver, kidney, thyroid, or any active inflammatory diseases. The ethical committee of Faculty of Medicine, Zagazig University approved our study protocol, and all participants assigned written informed consent and the reference number was IRB (Ethics number. 6321).
2.2. Blood samples and biochemical Analysis
Fasting plasma glucose (FPG), total cholesterol (TC), and triglycerides (TG) were measured by routine enzymatic methods (Spinreact). HDLc was determined after precipitation of apo B-containing lipoproteins. LDLc was calculated using the Friedewald formula [8]. Total RNA was extracted by using a total RNA Extraction Kit (Cat. No. BSC52S1); supplied by Bioer Technology Co., China. The RNA reverse transcription kit is HiSenScript kit (Cat. No. 25014); supplied by iNtRON Biotechnology, Inc., South Korea and it was used for cDNA synthesis from total RNA. The RNA quality was quantified by A260 using UV/spectrophotometer. RT- PCR technique was applied by using StepOnePlusTM System (Applied Biosystems Inc., USA) as documented in Livakand Schmittgen study [13].
Statistical analysis evaluations were conducted using the Statistical Package for Social Sciences (SPSS), version 26 Descriptive statistics included the mean (±) and standard deviation (SD) for continuous values and the number )%(for categorical values test was used to compare between two groups of studied patients Pearson’s correlation was calculated to detect relations between variables and levels of plasma circANKRD36 level. P <0.05 was considered statistically significant.
3. Results
The diabetic and control groups were matched for age and sex. The registered diabetic patients classified into two groups: 20 patients without CAD [8 males and 12 females, their mean age 59.3±14.1 year]and 20 patients with CAD [ 12 males and 8 females, their mean age 58.4±11.6 year]. Patients with CAD had higher values of metabolic risk factors compared topatients without CAD The metabolic risk factors for example systolic blood pressure, diastolic blood pressure, BMI, waist /hip ratio,
total cholesterol and triglycerides fasting plasma glucose, HbA1c, HDL cholesterol and LDL cholesterol compared to the control group, p ˂0.001. as shown in table 1.
Table 1: The primer sequences of circANKRD36 and ANKRD36
Gene Forward primer (5'-3') Reverseprimer (5'-3')
circANKRD36 GGAGGCCACAAGTGATGAGA CCTGGTGGTTTCTCAGAAGAC β-actin TTCCTTCCTGGGCATGGA GAGGAGCAATGATCTTGA
The plasma circANKRD36 level in the studied groups.
Our results show that patients with CAD (2.1 ±1.44) had statistically significant higher values of plasma level of circANKRD36 compared topatients without CAD(1.8±0.9) andcontrol group (0.519±0.262) p ˂0.001*. as shown in figure 1
Figure (1): Comparison between the studied groups as regard the relative expression levels of circANKRD36.
SYNTAX score of the coronary artery disease group
We estimated the severity of CAD using syntax score according to coronary angiography findings, and we used a syntax score. The mean and standard deviation of syntax score in patients with CAD was 26.12±4.11. 5 patients had a low score (0–
22), 7 patients had an intermediate score (23–32), and 8 had a high score (≥33) p
˂0.001*. as shown in figure 2
Figure (2): SYNTAX score of the coronary artery disease group
.
Correlations between plasma circANKRD36 level in patients with CAD
Our results demonstrated that the plasma circANKRD36 level was significantly positively correlatedwith. waist/hip ratio BMI, TC, TG,FPG: SYNTAX score, and HbA1c, (P<0.001), Table2.
linear regression analyses in patients with T2DM.
Linear regression analysis test was done to assess the main independent parameters associated with relative expression of circANKRD36 levels. Our results showed that waist /hip ratio as well as SYNTAX score, were independently correlated with both epigenetic biomarkers, P<0.001, table 4).
Table 2: Laboratory and anthropometric parameters within patients with T2DM.
subgroups.
Variables Patients without CAD Patients with CAD P value
(n=20) (n=20)
Body mass index (kg/m2) 33.73± 2.3 38.63± 4.9 ˂0.001*
Waist/hip ratio 0.96±0.12 1.27±0.34 ˂0.001*
Systolic blood pressure (mmHg) 155.8±27.7 156.1±16.9 0.905
Diastolic blood pressure (mmHg) 84.52± 11.22 102.84±12.21 ˂0.001*
Total cholesterol (mg/dl) 216.7±27.64 233.6±22.16 ˂0.001*
Triacylglycerol (mg/dl) 230.86±34.98 275.4± 73.011 ˂0.001*
LDL cholesterol (mg/dl) 117.8±29.3 143.95±34.7 ˂0.001*
HDL cholesterol (mg/dl) 37.8± 5.4 36.79± 5. 0.168
Fasting plasma glucose (mg/dl) 227.8±22.3 259.76±36.6 ˂0.001*
HbA1c (%) 8.1±0.25 9.9±2.26 ˂0.001*
circANKRD36 1.46±0.27 2.17±0.28 ˂0.001*
Table 3: Correlations between relative expression of circANKRD36 and other studied parameter in patients with CAD
Variables circANKRD36
r p
Waist/hip ratio 0.612 ˂0.001*
BMI 0.511 ˂0.001*
TG 0.178 0.077
LDL 0.525 0.01*
HDL -0.112 0.684
FPG 0.771 ˂0.001*
HbA1c 0.756 ˂0.001*
SYNTAX score 0.633 ˂0.001*
The accuracy of plasma circANKRD36 for discriminating patients with CAD from patients without CAD by ROC analysis.
We investigated the potential diagnostic value of the plasma of circANKRD36 by the ROC test. When we discriminate patients with T2DM from the control group, the cutoff values were 1.735 and the AUC was 0. .877 (95% CI =0.790-0.963) additionally, the sensitivities and the specificities were 85% and 70%, P<0.001, figure.3.
Figure (3): The accuracy of the relative expression levels of circANKRD36for discriminating diabetic patients with CAD from others without CAD by ROC analysis
Table 4: Linear regression analyses to test the influence of the main independent variables against relative expression of circANKRD36 levels (dependent variable) in patients with CAD.
Model Standardiz t p 95% C.I.
Unstandardized ed
Coefficients Coefficients
Lower
Upper
B SE Beta Bound Bound
http://annalsofrscb.ro 12849
Circankrd36 (Constant) 0.000 0.001 -0.229 00.819 - 0.031 0.001
Waist/hip 0.000 0.005 0.341 5.214 <0.001* 0.002 0.03
ratio
TG 4.618 0.009 0.013 0.351 0.73 0.005 0.7
SYNTAX 1.842 0.007 0.892 27.539 <0.001* 0.04 0.6
score
LDL 3.338 0.004 0.017 0.262 0.79 0.71 1.1
Discussion
Substantial evidence implicates T2DM as major independent risk factor for CAD.The increasingincidence of diabetes places increase the load on Egypt’s healthcare resources.In fact,identifying a successful biomarker depends certainly on fully understanding the pathophysiology underlying the disease. In T2DM and associated vascular complications, despite remarkable advances in the insight into the responsible mechanisms, the etiology remains mysterious. This obstacle makes the search for diagnostic or preclinical biomarkers is obligatory. Current research is therefore increasingly focusing on the discovery of novel epigenetic marker to further clarify the complex. Thus, this study aimed to measure plasma level ofcircANKRD36 in T2DM patients with or without CAD to explore the diagnostic power ofcircANKRD36 in predicting CAD among patients with T2DM.
A preponderance of evidence suggests thatcircRNAwhich are single stranded RNAs act as miRNA sponges since they possess binding sites for miRNA, so that they can finally modulate gene expression of miRNA targets [14,15].
The main finding of the present study is that plasma levels of circANKRD36 were significantly increased in patients with CAD and T2DM compared to control.
Interestingly, the plasma levels of circANKRD36 were significantly positive correlated with cardio metabolic risk factors.
A study done by Pan et al CAD and healthy control groups to investigate the role of circular RNAs in promoting TRPM3 expression by inhibiting hsa-miR-130a-3p in CAD patients. They detected that differentially expressed circRNAs were found (18 up-regulated and 6 down-regulated). Moreover, they assessed plasma miRNAs levels in an independent inhabitant of 648 CAD patients and 284 healthy subjects, and discovered 9 CAD-related miRNAs, 3 of which were downregulated in CAD subjects [16].
In agreement with the present study, Fang and his colleagues confirmed that the levels of circANKRD36 is increased in patients with T2DM and this level was associated withinflammation which could be the cause of subclinical atherosclerosis [17]. In agreement with our study, Zhanget al explored dysregulation of this epigenetic marker in T2DM group [18].
Also, the study conducted by Li and his coworkers suggested that circular
RNA ITCH has inhibitory effect on ESCC by suppressing the Wnt/β‑catenin pathway
[19]. Thus, the circ RNAs can positively regulate their paternal genes at the transcriptional level and post‑transcriptional level [20].
In study conducted byPrice et al observed that cardiometabolic risk factor including obesityis associated with epigenetic modulation of genes and protein cascades in insulin signaling [21].
To the best of our knowledge this study was the firstEgyptian studyinvestigatingcircANKRD36in both T2DM with or without CAD for early detection of CAD Accordingly, we can use preventive measures of CAD. The most important finding of our study that, waist /hip ratio as well as SYNTAX score were independently correlated with epigenetic marker by application of linear regression test,we in this study attempted to pierce out the predictive diagnostic power ofcircANKRD36in early prediction of CAD, according toour results, the sensitivities and the specificities were 85% and 70% thus it could be used as noninvasive epigenetic diagnostic marker of CAD
Conclusion
The results of the current study detected patients with T2DM had statistically significant higher values of circANKRD36 compared to control group. Plasma levels of circANKRD36 weresignificantly increased in T2DM patientswith CAD compared with T2DM patientswithout CAD. Thus, circANKRD36 couldbe considered a useful epigenetic marker for predictionof CAD events in T2DM patients. Morestudies on epigenetic markers are recommendedto explore the mechanisms thatmay be involved in vascular complicationsduring T2DM.
Declaration of conflicting interest
The authors declare that there is no conflict ofinterest.
Funding:This research received no specific grant from anyfunding agency in the public, commercial, or not-for-profit sectors.
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