| Literature DB >> 30718561 |
Liangxi Yuan1, Jian Dong1, Guanglang Zhu1, Junmin Bao2, Qingsheng Lu1, Jian Zhou3, Zaiping Jing4.
Abstract
In-stent restenosis (ISR) is still a major cause of failure of endovascular stenting treatment in patients with lower extremity arterial occlusive disease (LEAOD). Sensitive and reliable biomarkers for early diagnosis to predict ISR should be considered. This study was conducted to explore the diagnostic value of microRNA in predicting ISR in patients with LEAOD after endovascular stenting treatment. From March 2014 to July 2016, 208 patients (170 males and 38 females) with LEAOD undergoing interventional treatment were enrolled in this research. Patients were divided into the restenosis and non-restenosis groups according to routine postoperative angiography. Circulating microRNAs expression were detected in 208 participants, including 78 ISR patients, 68 non-ISR patients and 62 healthy volunteers. We selected 6 microRNAs from microarray screening as candidates for further testing via qRT-PCR. A receiver operating characteristic (ROC) curve was generated to assess the diagnostic value of circulating microRNAs in predicting ISR for LEAOD patients. The results showed that circulating microRNA-320a and microRNA-572 in patients with ISR (n = 78) had significantly higher expression levels than it from non-ISR and healthy volunteers. By receiver operating characteristic curve analysis, the sensitivity was 82.1% and the specificity was 63.8% for microRNA-320a; the sensitivity was 69.2% and the specificity was 68.9% for microRNA-572, and the AUC was 0.766 and 0.690 for detection of ISR, respectively. Furthermore, 78 patients with ISR had significantly higher circulating expression levels of microRNA-3937 and microRNA-642a-3p and lower circulating expression levels of microRNA-4669 and microRNA-3138 compared with 68 non-ISR patients and 62 healthy volunteers, but they have no significant difference. We found that differential circulating microRNA expression in patients after stenting with ISR, and the data indicate that circulating microRNA-320a and microRNA-572 have promising value in diagnosing ISR in patients with LEAOD.Entities:
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Year: 2019 PMID: 30718561 PMCID: PMC6361988 DOI: 10.1038/s41598-018-36295-2
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Patient Characteristics.
| Characteristics | ISR (n = 78) | Control(n = 130) | χ2/t | P | |
|---|---|---|---|---|---|
| non-ISR (n = 68) | Healthy (n = 62) | ||||
| Gender male | 67(85.9%) | 53(77.9%) | 50(80.6%) | 1.451 | 0.228 |
| Age, years | 66.32 ± 7.70 | 65.46 ± 13.80 | 67.01 ± 4.80 | 0.035 | 0.851 |
| Smoking | 30(38.5%) | 35(51.5%) | 20(32.3%) | 0.298 | 0.585 |
| Diabetes | 56(71.8%) | 47(69.1%) | 31(50%) | 2.959 | 0.085 |
| Hypertension | 46(59.0%) | 40(58.8%) | 37(59.7%) | 0.001 | 0.971 |
| Atrial fibrillation | 4(5.1%) | 3(4.4%) | 3(4.8%) | 0.028 | 0.867 |
| CAD | 18(23.1%) | 16(23.5%) | 12(19.4%) | 0.067 | 0.796 |
| Cerebral infarction | 10(12.8%) | 3(4.4%) | 8(12.9%) | 1.020 | 0.312 |
| COPD | 5(6.4%) | 3(4.4%) | 2(3.2%) | 0.700 | 0.403 |
| Cholesterol, mmol/L | 4.31 ± 1.05 | 4.47 ± 1.12 | 4.57 ± 1.54 | 0.972 | 0.325 |
| LDL, mmol/L | 2.38 ± 0.85 | 2.49 ± 0.99 | 2.21 ± 0.85 | 0.713 | 0.399 |
| HDL, mmol/L | 1.03 ± 0.40 | 1.10 ± 0.26 | 1.12 ± 0.38 | 2.896 | 0.090 |
Abbreviations: CAD, Coronary artery disease; COPD, Chronic Obstructive Pulmonary Disease; LDL, Low Density Lipoprotein; HDL, High Density Lipoprotein.
Continuous data are presented as the means ± standard deviation;
Categorical data are given as the counts (percentage).
Figure 1Microarray results of different microRNAs in the peripheral blood of enrolled patients.
Figure 2Process for Selection of Candidate MicroRNAs, and 6 candidate microRNAs discovered via microarrays were selected for the further validation.
Characteristics of the Subjects by Real-Time PCR.
| Characteristics | ISR (2−△Ct) (n = 78) | Control (2−△Ct) (n = 130) | χ2/t | P | |
|---|---|---|---|---|---|
| non-ISR (n = 68) | Healthy (n = 62) | ||||
| miR-642a-3p | 4.45 ± 2.39 | 3.77 ± 2.19 | 3.94 ± 2.51 | 1.666 | 0.192 |
| miR-3937 | 3.79 ± 1.99 | 3.56 ± 2.05 | 3.50 ± 2.27 | 0.379 | 0.685 |
| miR-4669 | 3.86 ± 2.33 | 4.15 ± 2.58 | 4.45 ± 2.23 | 1.081 | 0.341 |
| miR-3138 | 3.60 ± 2.25 | 3.63 ± 2.46 | 3.97 ± 2.76 | 0.459 | 0.633 |
| miR-320a | 4.80 ± 1.90 | 3.26 ± 1.58 | 3.06 ± 1.70 | 21.858 | <0.001 |
| miR-572 | 4.85 ± 1.90 | 3.30 ± 1.80 | 3.92 ± 2.05 | 12.152 | <0.001 |
ROC Analysis for MicroRNA.
| microRNA | ROC analysis | ||
|---|---|---|---|
| Sensitivity | Specificity | AUC | |
| miR-642a-3p | 0.705 | 0.500 | 0.591 |
| miR-3937 | 0.667 | 0.469 | 0.554 |
| miR-4669 | 0.949 | 0.115 | 0.439 |
| miR-3138 | 1.000 | 0.069 | 0.487 |
| miR-320a | 0.821 | 0.638 | 0.766 |
| miR-572 | 0.692 | 0.689 | 0.690 |
Figure 3Receiver operating characteristic (ROC) curve analysis with respect to microRNA-642a-3p (A), microRNA-3937 (B), microRNA-4669 (C), microRNA-3138 (D), microRNA-320a (E), microRNA-572 (F).