CLB-09013; No. of pages: 5; 4C: Clinical Biochemistry xxx (2015) xxx–xxx
Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
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Wenwen Zhang, Tao Shang, Chen Huang, Tong Yu, Chen Liu, Tong Qiao, Dian Huang, Zhao Liu ⁎, Changjian Liu ⁎
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Department of Vascular Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, PR China
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Article history: Received 28 January 2015 Received in revised form 26 March 2015 Accepted 20 April 2015 Available online xxxx
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Keywords: Abdominal aortic aneurysm miRNAs Biomarkers
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Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm
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Objectives: Abdominal aortic aneurysm (AAA) is often asymptomatic until rupture occurs. Although ultrasound screening has significantly improved the early diagnosis of AAA, the timely biomarker-based diagnosis of AAA remains a major clinical challenge. In this study, we aimed to assess plasma microRNAs (miRNAs) as promising novel biomarkers in patients with AAA. Methods: Pooled plasma samples from 10 AAA and 10 healthy controls were profiled by microarray. The differentially expressed miRNAs were evaluated in a separate cohort of 120 subjects, including 60 AAA patients and 60 normal controls. Results: The initial profiling study identified 151 miRNAs that showed more than two-fold change. Among them, three miRNAs, miR-191-3p, miR-455-3p and miR-1281 exhibited the largest increase in the patient group (fold change N 5). A subsequent validation study confirmed the elevation of these three miRNAs. Receiver operator characteristic curve analysis using the expression ratio of miR-191-3p, miR-455-3p and miR-1281 showed an area under the curve of 0.9700, 0.9825 and 0.9206, respectively. Conclusion: Our results suggest that plasma miR-191-3p, miR-455-3p and miR-1281 may be used as potential diagnosis biomarkers for AAA. © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
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Introduction
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Abdominal aortic aneurysm (AAA) is a common degenerative disease, with a prevalence of 8% in elderly men [1]. It is characterized by leukocyte inflammation, vascular smooth cell depletion and extracellular matrix degradation, resulting in gradual weakening wall and enlargement of aorta [2]. AAA is often asymptomatic until rupture occurs. Rupture of AAA is a devastating event and carries a high mortality rate [3]. The development of noninvasive methods is therefore urgently needed to detect at-risk AAA and facilitate early intervention. Screening programs by ultrasound conducted in several centers have proved to substantially reduce AAA-related deaths [4]. However, the diagnosis results are largely dependent on physician experience and further complicated by various methods of measurement utilized. Bloodbased tests appear to represent an attractive option as they are minimally invasive and able to achieve steady results. The key issue is to identify potential biomarkers with high accuracy for AAA. MicroRNAs (miRNAs) are endogenous, small non-coding RNAs that are involved in post-transcription regulation of gene expression [5,6].
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⁎ Corresponding authors. E-mail addresses: [email protected] (W. Zhang), [email protected] (T. Shang), [email protected] (C. Huang), [email protected] (T. Yu), [email protected] (C. Liu), [email protected] (T. Qiao), [email protected] (D. Huang), [email protected] (Z. Liu), [email protected] (C. Liu).
Aberrant miRNA expression pattern has been implicated in the pathogenesis of various cardiovascular conditions [7]. Recent studies reveal that miRNAs play a crucial role in AAA development [8]. For instance, miR-21 inhibits aneurysm growth by altering vascular smooth cell proliferation and apoptosis [9], whereas miR-29b limits aneurysm rupture via inducing extracellular matrix deposition [10]. Circulating miRNAs are found to be stable in human blood and detectable with high sensitivity and specificity [11], indicating that they could be effective biomarkers for AAA. Although miR-24 and miR-195 have been suggested as potential AAA biomarkers in previous studies, they are selected based on murine tissue specimen and function relevance, rather than human circulating miRNA expression signature [12,13]. In the current study, we employed microarray analysis of AAA patients and healthy control plasma miRNAs, followed by confirmation with a quantitative reversetranscription PCR (qRT-PCR) assay to uncover promising AAA biomarkers.
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Materials and methods
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Participants
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We recruited 70 AAA patients who were admitted to the 71 Department of Vascular Surgery at the Drum Tower Hospital, Medical 72 School of Nanjing University from 2013 to 2014. AAA was diagnosed 73
http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016 0009-9120/© 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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Plasma preparation
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Peripheral blood was collected in EDTA tubes from all participants. All samples were processed within 3 h after collection. Blood samples were centrifuged (3000 g, 5 min, 4 °C) to remove cells and debris. The supernatant fluids were transferred to ribonuclease-free tubes and stored at −80 °C.
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MicroRNA microarray assay
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For the microarray analysis, equal volumes of plasma from 10 AAA patients and 10 controls (200 μL each) were pooled separately to form the case and control sample pools (each pool contained 2 mL). Total RNA was extracted from pooled plasma samples using miRNeasy (Qiagen) according to the manufacturer's instructions. Affymetrix miRNA 2.0 Array, which targeted 1105 human miRNAs, was utilized to profile the plasma. Briefly, 1 mg of total RNA was labeled using the Flash Tag Biotin Labelling Kit (Affymetrix). The labeling product was hybridized with the miRNA Array in an Affymetrix Hybridization Oven 640 (Affymetrix) at 48 °C at 60 rpm for 16 h. The arrays were stained in the Fluidics Station 450 (Affymetrix) and then scanned on the GeneChip1 Scanner 3000 (Affymetrix).
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qRT-PCR validation
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Synthetic cel-miR-39 (50 pmol) was added to 300 μL of each plasma sample, and total RNA was extracted using miRNeasy (Qiagen). TaqMan probe-based qRT-PCR (Applied Biosystems) was performed according to the manufacturer's protocol. Briefly, 2 μL of total RNA was reversed transcribed to complementary DNA (cDNA) using PrimeScript RT reagent Kit (Takara) and a stem-loop primer (Applied Biosystems). Real-time PCR was carried out using a TaqMan PCR kit and was run on the StepOnePlus System (Applied Biosystems). The cycling conditions were 10 min at 95 °C, followed by 40 cycles of 15 s at 15 s at 95 °C and 1 min at 60 °C. The Ct was determined as the fractional cycle number at which the fluorescence exceeded the given threshold. Delta Ct was calculated by subtracting the Ct values of cel-miR-39 from the Ct values of the targeted miRNAs. All samples were analyzed in triplicate.
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Statistical analysis
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Statistical analyses were conducted using SPSS software, version 19.0 (Chicago). Demographic and clinical data between AAA and control
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Participant characteristics
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The demographic and clinical characteristics between AAA and control subjects recruited in this study were shown in Table 1. Diabetes mellitus was significantly lower in the AAA group of validation stage (p b 0.05). Except diabetes, no significant difference was observed between study groups with regard to other predisposing risk factors in both stages.
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Results of the miRNA microarray analysis
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By profiling the pooled samples of AAA and controls (n = 10 each), we demonstrated that patients with AAA had a plasma miRNA signature that was significantly different from that of controls. Of 151 miRNAs that showed more than two-fold change, the majority of them showed a decrease in the AAA group plasma (Table 2). Among them, we focused on three miRNAs, miR-191-3p, miR-455-3p and miR-1281, whose expression showed the largest increase in the patient group (fold change N5).
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Confirmation of the results yielded from the miRNA array by qRT-PCR
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We then attempted to confirm the three miRNA expression changes in an extended cohort of participants (n = 60 each). As shown in Fig. 1, a significant increase of miRNA levels was observed in AAA patients for miR-191-3p (1.728, 1.134 to 2.110 vs −0.049, −0.178 to 0.209), miR455-3p (1.664, 0.803 to 1.941 vs 0.026, − 0.065 to 0.140) and miR1281 (0.975, 0.679 to 1.487 vs 0.044, − 0.328 to 0.277), as compared with controls (p b 0.001). The mean fold changes of miR-191-3p, miR455-3p and miR-1281 were 5.90, 5.44 and 3.09, respectively.
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ROC analysis
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ROC curves for each of the three miRNAs analyzed were constructed to discriminate between AAA and controls. The AUC of miR-191-3p was 0.9700 with 93.3% sensitivity and 96.7% specificity (confidence interval = 0.9352–1.0048). The AUC of miR-455-3p was 0.9825 with
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In the initial screening stage, we employed microarray assay and pooled plasma samples from 10 AAA patients and 10 healthy controls to identify plasma miRNAs that demonstrated significant change between them. Given its low abundance of miRNAs in plasma, elevated miRNAs with fold change N5 were selected for further validation. In the validation stage, we confirmed miRNA upregulation by Taqman probebased qRT-PCR using plasma samples from a larger cohort of 60 patients and 60 controls.
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groups were compared with Student's t test and the χ test. Average fold changes (log2− ΔΔCt) of miRNA levels were used to evaluate the expression level. Expression levels between groups were compared using the Mann–Whitney U test (presented as median with interquartile range). The receiver operating characteristic (ROC) was generated to calculate the area under the curve (AUC) and the diagnosis value, including sensitivity and specificity. Statistical significance was defined as p b 0.05 for all tests. All p values are two-sides.
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based on computer tomography image, with a focal dilation of the abdominal aorta exceeding the normal diameter by more than 50%. Inflammatory aneurysm, pseudo-aneurysm and aneurysm caused by dissection were excluded in this study. The healthy controls consisted of 70 age and sex-matched participants who underwent health checkups in our hospital. Ultrasound was routinely performed to exclude AAA existence. Medical records were reviewed to determine participants' age, sex and other risk factors. This study was performed in accordance with the Declaration of Helsinki and was approved by the local ethics committee. Signed informed consent forms were obtained from all participants.
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Table 1 t1:1 Demographic and clinical data of abdominal aortic aneurysm (AAA) patients and control t1:2 Q1 subjects. t1:3 Characteristics
Age, years Sex (male) Smoking habit Hypertension Diabetes Dyslipidemia CAD COPD
Screening stage
t1:4
Validation stage
AAA (n = 10)
Controls (n = 10)
AAA (n = 60)
Controls (n = 60)
t1:5 t1:6
70.6 ± 8.0 7 5 8 4 6 2 3
70.8 ± 6.8 8 4 9 4 7 2 2
72.2 ± 9.5 47 40 46 11⁎
71.9 ± 8.6 47 37 45 20 31 5 4
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CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease. Continuous data are presented as the mean ± standard deviation and categoric data as number. ⁎ p b 0.05.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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W. Zhang et al. / Clinical Biochemistry xxx (2015) xxx–xxx Table 2 Plasma miRNAs with fold change N2 in AAA patients as identified by microarray analysis.
Table 2 (continued)
Fold change
Style
miRNA
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hsa-miR-191-5p hsa-miR-103a-3p hsa-miR-92a-3p hsa-miR-122-5p hsa-miR-23a-3p hsa-miR-320b hsa-let-7c-5p hsa-miR-320d hsa-miR-486-5p hsa-miR-93-5p hsa-miR-26a-5p hsa-miR-25-3p hsa-let-7i-5p hsa-miR-221-3p hsa-miR-126-3p hsa-miR-320a hsa-miR-22-3p hsa-miR-320c hsa-miR-146a-5p hsa-miR-19b-3p hsa-let-7b-5p hsa-miR-151a-3p hsa-let-7d-5p hsa-miR-425-5p hsa-miR-107 hsa-miR-140-3p hsa-let-7a-5p hsa-miR-23b-3p hsa-miR-150-5p hsa-miR-16-5p hsa-miR-423-5p hsa-miR-17-5p hsa-miR-451a hsa-miR-1228-5p hsa-miR-181a-5p hsa-miR-222-3p hsa-miR-584-5p hsa-miR-15b-5p hsa-miR-652-3p hsa-miR-361-5p hsa-miR-744-5p hsa-miR-342-3p hsa-miR-30d-5p hsa-miR-762 hsa-miR-1237-5p hsa-let-7e-5p hsa-miR-106a-5p hsa-miR-24-3p hsa-miR-20a-5p hsa-miR-106b-5p hsa-miR-378a-3p hsa-miR-1246 hsa-miR-125a-5p hsa-miR-223-3p hsa-miR-151a-5p hsa-miR-1268a hsa-miR-378c hsa-miR-125b-5p hsa-miR-185-5p hsa-miR-27a-3p hsa-miR-423-3p hsa-miR-130b-3p hsa-miR-29a-3p hsa-miR-15a-5p hsa-miR-99b-5p hsa-miR-149-3p hsa-miR-152-3p hsa-miR-20b-5p hsa-miR-1268b hsa-let-7g-5p hsa-miR-151b hsa-miR-663a hsa-miR-155-5p hsa-miR-199a-3p hsa-miR-199b-3p
193.51 122.96 117.86 97.86 86.99 86.79 84.39 71.13 70.20 68.61 67.00 61.33 57.42 52.01 49.25 46.24 45.38 42.21 41.23 39.63 39.54 34.82 34.32 33.13 32.78 29.79 29.48 25.50 24.58 24.05 22.71 22.64 19.98 18.14 17.62 15.73 15.50 14.85 14.67 14.55 13.27 13.20 12.72 12.63 12.41 11.95 11.91 11.82 11.14 10.75 10.72 10.57 10.52 10.26 9.81 9.26 8.52 8.35 8.23 8.15 8.02 7.95 7.81 7.73 7.67 7.48 7.44 7.36 7.20 7.16 6.79 6.72 6.44 5.95 5.95
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hsa-miR-342-5p hsa-miR-1207-5p hsa-miR-139-5p hsa-miR-486-3p hsa-miR-500a-3p hsa-miR-629-5p hsa-miR-145-5p hsa-miR-106b-3p hsa-miR-328-5p hsa-miR-193a-5p hsa-miR-532-5p hsa-miR-130a-3p hsa-miR-134-5p hsa-miR-200c-3p hsa-miR-1227-5p hsa-miR-28-3p hsa-miR-27b-3p hsa-miR-409-3p hsa-miR-199a-5p hsa-let-7f-5p hsa-miR-937-5p hsa-miR-28-5p hsa-miR-181b-5p hsa-miR-30c-5p hsa-miR-30e-5p hsa-miR-1225-5p hsa-miR-363-3p hsa-miR-18a-5p hsa-miR-574-3p hsa-miR-339-3p hsa-miR-324-3p hsa-miR-324-5p hsa-miR-92b-5p hsa-miR-30a-5p hsa-miR-146b-5p hsa-miR-378d hsa-miR-210-3p hsa-miR-382-5p hsa-miR-100-5p hsa-miR-1275 hsa-miR-502-3p hsa-miR-21-5p hsa-miR-638 hsa-miR-194-5p hsa-miR-143-3p hsa-miR-297 hsa-miR-19a-3p hsa-miR-18b-5p hsa-miR-124-3p hsa-miR-345-5p hsa-miR-1290 hsa-miR-30b-5p hsa-miR-660-5p hsa-miR-93-3p hsa-miR-339-5p hsa-miR-574-5p hsa-miR-31-5p hsa-miR-23a-5p hsa-miR-501-5p hsa-miR-330-3p hsa-miR-192-5p hsa-miR-885-3p hsa-miR-206 hsa-miR-132-3p hsa-miR-127-3p hsa-miR-625-5p hsa-let-7f-1-3p hsa-miR-105-5p hsa-let-7b-3p hsa-miR-96-5p hsa-miR-425-3p hsa-miR-940 hsa-miR-933 hsa-miR-455-3p hsa-miR-1281 hsa-miR-191-3p
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Fold change 5.93 5.74 5.55 5.40 5.19 5.06 5.00 4.97 4.86 4.78 4.70 4.47 4.14 4.13 4.12 3.96 3.96 3.92 3.88 3.86 3.74 3.67 3.61 3.53 3.50 3.41 3.38 3.28 3.25 3.16 3.15 3.12 3.06 3.03 2.99 2.98 2.97 2.97 2.92 2.91 2.90 2.82 2.82 2.79 2.74 2.74 2.66 2.63 2.61 2.54 2.53 2.48 2.46 2.41 2.35 2.25 2.23 2.23 2.22 2.20 2.20 2.16 2.14 2.08 2.02 2.01 2.07 2.29 2.52 2.61 2.75 4.22 4.41 8.45 9.35 9.92
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Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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To the best of our knowledge, our study is the first to employ systemic approach to identify potential plasma miRNA biomarkers for AAA. In the present study, miRNA profiling using pooled samples revealed differently expressed plasma miRNA signatures between AAA and healthy controls. Among them, miR-191-3p, miR-455-3p and miR-1281 showed the largest increase (fold change N 5), which is confirmed in the subsequent qRT-PCR assays in an extended cohort. ROC analysis suggested that they could act as suitable biomarkers for AAA. In particularly, the discriminatory power of miR-455-3p was the highest, with an AUC of 0.9825. AAA formation is initiated by inflammation cell infiltration, followed by vascular smooth muscle cell depletion and extracellular matrix degradation [2]. Accumulating evidence suggests that miRNA plays an important role in AAA development by participating in these processes [8,14]. MiR-21 expression is induced by inflammation stimuli, which in turn suppresses AAA progression by inhibiting apoptosis and promoting proliferation of vascular smooth muscle cells [9]. MiR-29b is downregulated in AAA to prevent rupture by increasing collagen and elastin gene expression [10,15]. MiR-205 has been shown to influence AAA development by stimulating inflammation and matrix metalloproteinase activity. Among its targets are tissue inhibitor of metalloproteinase 3 (TIMP3) and reversion-inducing cysteine-rich protein with kazal motifs (RECK) [16]. MiR-195 plays similar role as miR-29b in AAA, but the effects it exerts are lower [13,17]. The newly identified miR-24 is a key regulator of vascular inflammation and AAA pathology. It regulates
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cytokine synthesis and macrophage survive by targeting chitinase 3like 1 (Chi3l1) [12]. miRNA expression profiling of AAA has also been performed in previous studies [18,19]. By comparing infrarenal abdominal aortic aneurysm and corresponding normal tissues, Pahl et al. identified eight miRNAs with significantly different expression levels [19]. A study by Kin demonstrated high expression levels of miRNA related to fibrosis (miR-29b), inflammation (miR-124a, miR-146a, miR-155, and miR-223), and endothelium (miR-126, let-7 family members, and miR-21) in AAA tissues. Intriguingly, those miRNAs that showed increased expression in AAA tissues were significantly reduced in plasma [18]. This is in line with our findings that the majority of miRNAs that showed fold change N 2 is down-regulated in AAA plasma. It is noteworthy that conflicting results could be obtained in different studies. For example, miR-155 expression was reported to be elevated in AAA serum in the study by Biros [20]. These inconsistencies justify further research on circulating miRNA expression patterns related to AAA development. AAA occurs most often in people age 65 and older. AAA patients are thus more likely to carry multiple comorbidities, such as high blood pressure, diabetes mellitus, and coronary artery disease. These comorbidities have their unique miRNA expression profiles and therefore could complicate our efforts to identify miRNAs specific to AAA [21, 22]. In this study, we utilized sample pooling technique to minimize such effects. The samples used to make a pool were comparable regarding comorbidities. Several limitations of our study merit consideration. Because of the relatively small validation sample size, the diagnosis value of plasma miR-191-3p, miR-455-3p and miR-1281 may be overestimated. Largescale studies in different centers are needed to validate our results. Second, the function of these miRNAs, and their specific roles in AAA development, is largely unknown. To decipher the mechanism
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95.0% sensitivity and 100.0% specificity (confidence interval = 0.9613– 1.0037). The AUC of miR-1281 was 0.9206 with 76.7% sensitivity and 98.3% specificity (confidence interval = 0.9613–1.0037) (Fig. 2).
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Fig. 1. Fold differences (log2−ΔΔCt) in plasma-derived miR-191-3p, miR-45-3p, and miR-1281 expression between AAA patients (n = 60) and controls (n = 60) (Mann–Whitney U-test).
Fig. 2. ROC curves for plasma-derived miR-191-3p, miR-455-3p and miR-1281 to discriminate between AAA and controls. The AUC values were given on the graph.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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Funding
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This study was supported by grants from National Natural Science Foundation of China (81270396), National Natural Science Foundation of Jiangsu Province, China (BK20140103), Nanjing Municipal Science and Technology Commission (BL2012035).
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The authors thanked Haiyan Min for her excellent technical guidance.
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[6] Engelhardt S. Small RNA biomarkers come of age. J Am Coll Cardiol 2012;60:300–3. [7] Small EM, Frost RJ, Olson EN. MicroRNAs add a new dimension to cardiovascular disease. Circulation 2010;121:1022–32. [8] Maegdefessel L, Spin JM, Adam M, Raaz U, Toh R, Nakagami F, et al. Micromanaging abdominal aortic aneurysms. Int J Mol Sci 2013;14:14374–94. [9] Maegdefessel L, Azuma J, Toh R, Deng A, Merk DR, Raiesdana A, et al. MicroRNA-21 blocks abdominal aortic aneurysm development and nicotine-augmented expansion. Sci Transl Med 2012;4(122):ra22. [10] Maegdefessel L, Azuma J, Toh R, Merk DR, Deng A, Chin JT, et al. Inhibition of microRNA-29b reduces murine abdominal aortic aneurysm development. J Clin Invest 2012;122:497–506. [11] Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;18:997–1006. [12] Maegdefessel L, Spin JM, Raaz U, Eken SM, Toh R, Azuma J, et al. Mir-24 limits aortic vascular inflammation and murine abdominal aneurysm development. Nat Commun 2014;5:5214. [13] Zampetaki A, Attia R, Mayr U, Gomes RS, Phinikaridou A, Yin X, et al. Role of mir-195 in aortic aneurysmal disease. Circ Res 2014;115:857–66. [14] Adam M, Raaz U, Spin JM, Tsao PS. MicroRNAs in abdominal aortic aneurysm. Curr Vasc Pharmacol 2013. [15] Milewicz DM. MicroRNAs, fibrotic remodeling, and aortic aneurysms. J Clin Invest 2012;122:490–3. [16] Kim CW, Kumar S, Son DJ, Jang IH, Griendling KK, Jo H. Prevention of abdominal aortic aneurysm by anti-microRNA-712 or anti-microRNA-205 in angiotensin IIinfused mice. Arterioscler Thromb Vasc Biol 2014. [17] Spin JM, Tsao PS. Battle of the bulge: mir-195 versus mir-29b in aortic aneurysm. Circ Res 2014;115:812–3. [18] Kin K, Miyagawa S, Fukushima S, Shirakawa Y, Torikai K, Shimamura K, et al. Tissueand plasma-specific microRNA signatures for atherosclerotic abdominal aortic aneurysm. J Am Heart Assoc 2012;1:e000745. [19] Pahl MC, Derr K, Gabel G, Hinterseher I, Elmore JR, Schworer CM, et al. MicroRNA expression signature in human abdominal aortic aneurysms. BMC Med Genomics 2012;5:25. [20] Biros E, Moran CS, Wang Y, Walker PJ, Cardinal J, Golledge J. MicroRNA profiling in patients with abdominal aortic aneurysms: the significance of mir-155. Clin Sci (Lond England : 1979) 2013. [21] Li S, Zhu J, Zhang W, Chen Y, Zhang K, Popescu LM, et al. Signature microRNA expression profile of essential hypertension and its novel link to human cytomegalovirus infection. Circulation 2011;124:175–84. [22] Guay C, Regazzi R. Circulating microRNAs as novel biomarkers for diabetes mellitus. Nat Rev Endocrinol 2013;9:513–21.
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underling their elevation in AAA plasma could aid their clinical application and interpretation. In conclusion, using microarray assay, we identified three miRNAs with the highest increase in AAA plasma. Subsequent qRT-PCR validation confirmed the elevation and demonstrated high diagnosis values of these miRNAs, especially miR-455-3p. Our results suggested that they may act as promising biomarkers for the early diagnosis of AAA.
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Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
3Q3
Wenwen Zhang, Tao Shang, Chen Huang, Tong Yu, Chen Liu, Tong Qiao, Dian Huang, Zhao Liu ⁎, Changjian Liu ⁎
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Department of Vascular Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, PR China
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Article history: Received 28 January 2015 Received in revised form 26 March 2015 Accepted 20 April 2015 Available online xxxx
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Keywords: Abdominal aortic aneurysm miRNAs Biomarkers
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Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm
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Objectives: Abdominal aortic aneurysm (AAA) is often asymptomatic until rupture occurs. Although ultrasound screening has significantly improved the early diagnosis of AAA, the timely biomarker-based diagnosis of AAA remains a major clinical challenge. In this study, we aimed to assess plasma microRNAs (miRNAs) as promising novel biomarkers in patients with AAA. Methods: Pooled plasma samples from 10 AAA and 10 healthy controls were profiled by microarray. The differentially expressed miRNAs were evaluated in a separate cohort of 120 subjects, including 60 AAA patients and 60 normal controls. Results: The initial profiling study identified 151 miRNAs that showed more than two-fold change. Among them, three miRNAs, miR-191-3p, miR-455-3p and miR-1281 exhibited the largest increase in the patient group (fold change N 5). A subsequent validation study confirmed the elevation of these three miRNAs. Receiver operator characteristic curve analysis using the expression ratio of miR-191-3p, miR-455-3p and miR-1281 showed an area under the curve of 0.9700, 0.9825 and 0.9206, respectively. Conclusion: Our results suggest that plasma miR-191-3p, miR-455-3p and miR-1281 may be used as potential diagnosis biomarkers for AAA. © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
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Introduction
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Abdominal aortic aneurysm (AAA) is a common degenerative disease, with a prevalence of 8% in elderly men [1]. It is characterized by leukocyte inflammation, vascular smooth cell depletion and extracellular matrix degradation, resulting in gradual weakening wall and enlargement of aorta [2]. AAA is often asymptomatic until rupture occurs. Rupture of AAA is a devastating event and carries a high mortality rate [3]. The development of noninvasive methods is therefore urgently needed to detect at-risk AAA and facilitate early intervention. Screening programs by ultrasound conducted in several centers have proved to substantially reduce AAA-related deaths [4]. However, the diagnosis results are largely dependent on physician experience and further complicated by various methods of measurement utilized. Bloodbased tests appear to represent an attractive option as they are minimally invasive and able to achieve steady results. The key issue is to identify potential biomarkers with high accuracy for AAA. MicroRNAs (miRNAs) are endogenous, small non-coding RNAs that are involved in post-transcription regulation of gene expression [5,6].
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⁎ Corresponding authors. E-mail addresses: [email protected] (W. Zhang), [email protected] (T. Shang), [email protected] (C. Huang), [email protected] (T. Yu), [email protected] (C. Liu), [email protected] (T. Qiao), [email protected] (D. Huang), [email protected] (Z. Liu), [email protected] (C. Liu).
Aberrant miRNA expression pattern has been implicated in the pathogenesis of various cardiovascular conditions [7]. Recent studies reveal that miRNAs play a crucial role in AAA development [8]. For instance, miR-21 inhibits aneurysm growth by altering vascular smooth cell proliferation and apoptosis [9], whereas miR-29b limits aneurysm rupture via inducing extracellular matrix deposition [10]. Circulating miRNAs are found to be stable in human blood and detectable with high sensitivity and specificity [11], indicating that they could be effective biomarkers for AAA. Although miR-24 and miR-195 have been suggested as potential AAA biomarkers in previous studies, they are selected based on murine tissue specimen and function relevance, rather than human circulating miRNA expression signature [12,13]. In the current study, we employed microarray analysis of AAA patients and healthy control plasma miRNAs, followed by confirmation with a quantitative reversetranscription PCR (qRT-PCR) assay to uncover promising AAA biomarkers.
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Materials and methods
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Participants
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We recruited 70 AAA patients who were admitted to the 71 Department of Vascular Surgery at the Drum Tower Hospital, Medical 72 School of Nanjing University from 2013 to 2014. AAA was diagnosed 73
http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016 0009-9120/© 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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Plasma preparation
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Peripheral blood was collected in EDTA tubes from all participants. All samples were processed within 3 h after collection. Blood samples were centrifuged (3000 g, 5 min, 4 °C) to remove cells and debris. The supernatant fluids were transferred to ribonuclease-free tubes and stored at −80 °C.
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MicroRNA microarray assay
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For the microarray analysis, equal volumes of plasma from 10 AAA patients and 10 controls (200 μL each) were pooled separately to form the case and control sample pools (each pool contained 2 mL). Total RNA was extracted from pooled plasma samples using miRNeasy (Qiagen) according to the manufacturer's instructions. Affymetrix miRNA 2.0 Array, which targeted 1105 human miRNAs, was utilized to profile the plasma. Briefly, 1 mg of total RNA was labeled using the Flash Tag Biotin Labelling Kit (Affymetrix). The labeling product was hybridized with the miRNA Array in an Affymetrix Hybridization Oven 640 (Affymetrix) at 48 °C at 60 rpm for 16 h. The arrays were stained in the Fluidics Station 450 (Affymetrix) and then scanned on the GeneChip1 Scanner 3000 (Affymetrix).
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qRT-PCR validation
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Synthetic cel-miR-39 (50 pmol) was added to 300 μL of each plasma sample, and total RNA was extracted using miRNeasy (Qiagen). TaqMan probe-based qRT-PCR (Applied Biosystems) was performed according to the manufacturer's protocol. Briefly, 2 μL of total RNA was reversed transcribed to complementary DNA (cDNA) using PrimeScript RT reagent Kit (Takara) and a stem-loop primer (Applied Biosystems). Real-time PCR was carried out using a TaqMan PCR kit and was run on the StepOnePlus System (Applied Biosystems). The cycling conditions were 10 min at 95 °C, followed by 40 cycles of 15 s at 15 s at 95 °C and 1 min at 60 °C. The Ct was determined as the fractional cycle number at which the fluorescence exceeded the given threshold. Delta Ct was calculated by subtracting the Ct values of cel-miR-39 from the Ct values of the targeted miRNAs. All samples were analyzed in triplicate.
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Statistical analysis
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Statistical analyses were conducted using SPSS software, version 19.0 (Chicago). Demographic and clinical data between AAA and control
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Result
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Participant characteristics
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The demographic and clinical characteristics between AAA and control subjects recruited in this study were shown in Table 1. Diabetes mellitus was significantly lower in the AAA group of validation stage (p b 0.05). Except diabetes, no significant difference was observed between study groups with regard to other predisposing risk factors in both stages.
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Results of the miRNA microarray analysis
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By profiling the pooled samples of AAA and controls (n = 10 each), we demonstrated that patients with AAA had a plasma miRNA signature that was significantly different from that of controls. Of 151 miRNAs that showed more than two-fold change, the majority of them showed a decrease in the AAA group plasma (Table 2). Among them, we focused on three miRNAs, miR-191-3p, miR-455-3p and miR-1281, whose expression showed the largest increase in the patient group (fold change N5).
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Confirmation of the results yielded from the miRNA array by qRT-PCR
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We then attempted to confirm the three miRNA expression changes in an extended cohort of participants (n = 60 each). As shown in Fig. 1, a significant increase of miRNA levels was observed in AAA patients for miR-191-3p (1.728, 1.134 to 2.110 vs −0.049, −0.178 to 0.209), miR455-3p (1.664, 0.803 to 1.941 vs 0.026, − 0.065 to 0.140) and miR1281 (0.975, 0.679 to 1.487 vs 0.044, − 0.328 to 0.277), as compared with controls (p b 0.001). The mean fold changes of miR-191-3p, miR455-3p and miR-1281 were 5.90, 5.44 and 3.09, respectively.
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ROC analysis
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ROC curves for each of the three miRNAs analyzed were constructed to discriminate between AAA and controls. The AUC of miR-191-3p was 0.9700 with 93.3% sensitivity and 96.7% specificity (confidence interval = 0.9352–1.0048). The AUC of miR-455-3p was 0.9825 with
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In the initial screening stage, we employed microarray assay and pooled plasma samples from 10 AAA patients and 10 healthy controls to identify plasma miRNAs that demonstrated significant change between them. Given its low abundance of miRNAs in plasma, elevated miRNAs with fold change N5 were selected for further validation. In the validation stage, we confirmed miRNA upregulation by Taqman probebased qRT-PCR using plasma samples from a larger cohort of 60 patients and 60 controls.
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groups were compared with Student's t test and the χ test. Average fold changes (log2− ΔΔCt) of miRNA levels were used to evaluate the expression level. Expression levels between groups were compared using the Mann–Whitney U test (presented as median with interquartile range). The receiver operating characteristic (ROC) was generated to calculate the area under the curve (AUC) and the diagnosis value, including sensitivity and specificity. Statistical significance was defined as p b 0.05 for all tests. All p values are two-sides.
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based on computer tomography image, with a focal dilation of the abdominal aorta exceeding the normal diameter by more than 50%. Inflammatory aneurysm, pseudo-aneurysm and aneurysm caused by dissection were excluded in this study. The healthy controls consisted of 70 age and sex-matched participants who underwent health checkups in our hospital. Ultrasound was routinely performed to exclude AAA existence. Medical records were reviewed to determine participants' age, sex and other risk factors. This study was performed in accordance with the Declaration of Helsinki and was approved by the local ethics committee. Signed informed consent forms were obtained from all participants.
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Table 1 t1:1 Demographic and clinical data of abdominal aortic aneurysm (AAA) patients and control t1:2 Q1 subjects. t1:3 Characteristics
Age, years Sex (male) Smoking habit Hypertension Diabetes Dyslipidemia CAD COPD
Screening stage
t1:4
Validation stage
AAA (n = 10)
Controls (n = 10)
AAA (n = 60)
Controls (n = 60)
t1:5 t1:6
70.6 ± 8.0 7 5 8 4 6 2 3
70.8 ± 6.8 8 4 9 4 7 2 2
72.2 ± 9.5 47 40 46 11⁎
71.9 ± 8.6 47 37 45 20 31 5 4
t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14
32 6 5
CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease. Continuous data are presented as the mean ± standard deviation and categoric data as number. ⁎ p b 0.05.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
t1:15 t1:16 t1:17 t1:18
W. Zhang et al. / Clinical Biochemistry xxx (2015) xxx–xxx Table 2 Plasma miRNAs with fold change N2 in AAA patients as identified by microarray analysis.
Table 2 (continued)
Fold change
Style
miRNA
t2:4 t2:5 t2:6 t2:7 t2:8 t2:9 t2:10 t2:11 t2:12 t2:13 t2:14 t2:15 t2:16 t2:17 t2:18 t2:19 t2:20 t2:21 t2:22 t2:23 t2:24 t2:25 t2:26 t2:27 t2:28 t2:29 t2:30 t2:31 t2:32 t2:33 t2:34 t2:35 t2:36 t2:37 t2:38 t2:39 t2:40 t2:41 t2:42 t2:43 t2:44 t2:45 t2:46 t2:47 t2:48 t2:49 t2:50 t2:51 t2:52 t2:53 t2:54 t2:55 t2:56 t2:57 t2:58 t2:59 t2:60 t2:61 t2:62 t2:63 t2:64 t2:65 t2:66 t2:67 t2:68 t2:69 t2:70 t2:71 t2:72 t2:73 t2:74 t2:75 t2:76 t2:77 t2:78
hsa-miR-191-5p hsa-miR-103a-3p hsa-miR-92a-3p hsa-miR-122-5p hsa-miR-23a-3p hsa-miR-320b hsa-let-7c-5p hsa-miR-320d hsa-miR-486-5p hsa-miR-93-5p hsa-miR-26a-5p hsa-miR-25-3p hsa-let-7i-5p hsa-miR-221-3p hsa-miR-126-3p hsa-miR-320a hsa-miR-22-3p hsa-miR-320c hsa-miR-146a-5p hsa-miR-19b-3p hsa-let-7b-5p hsa-miR-151a-3p hsa-let-7d-5p hsa-miR-425-5p hsa-miR-107 hsa-miR-140-3p hsa-let-7a-5p hsa-miR-23b-3p hsa-miR-150-5p hsa-miR-16-5p hsa-miR-423-5p hsa-miR-17-5p hsa-miR-451a hsa-miR-1228-5p hsa-miR-181a-5p hsa-miR-222-3p hsa-miR-584-5p hsa-miR-15b-5p hsa-miR-652-3p hsa-miR-361-5p hsa-miR-744-5p hsa-miR-342-3p hsa-miR-30d-5p hsa-miR-762 hsa-miR-1237-5p hsa-let-7e-5p hsa-miR-106a-5p hsa-miR-24-3p hsa-miR-20a-5p hsa-miR-106b-5p hsa-miR-378a-3p hsa-miR-1246 hsa-miR-125a-5p hsa-miR-223-3p hsa-miR-151a-5p hsa-miR-1268a hsa-miR-378c hsa-miR-125b-5p hsa-miR-185-5p hsa-miR-27a-3p hsa-miR-423-3p hsa-miR-130b-3p hsa-miR-29a-3p hsa-miR-15a-5p hsa-miR-99b-5p hsa-miR-149-3p hsa-miR-152-3p hsa-miR-20b-5p hsa-miR-1268b hsa-let-7g-5p hsa-miR-151b hsa-miR-663a hsa-miR-155-5p hsa-miR-199a-3p hsa-miR-199b-3p
193.51 122.96 117.86 97.86 86.99 86.79 84.39 71.13 70.20 68.61 67.00 61.33 57.42 52.01 49.25 46.24 45.38 42.21 41.23 39.63 39.54 34.82 34.32 33.13 32.78 29.79 29.48 25.50 24.58 24.05 22.71 22.64 19.98 18.14 17.62 15.73 15.50 14.85 14.67 14.55 13.27 13.20 12.72 12.63 12.41 11.95 11.91 11.82 11.14 10.75 10.72 10.57 10.52 10.26 9.81 9.26 8.52 8.35 8.23 8.15 8.02 7.95 7.81 7.73 7.67 7.48 7.44 7.36 7.20 7.16 6.79 6.72 6.44 5.95 5.95
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hsa-miR-342-5p hsa-miR-1207-5p hsa-miR-139-5p hsa-miR-486-3p hsa-miR-500a-3p hsa-miR-629-5p hsa-miR-145-5p hsa-miR-106b-3p hsa-miR-328-5p hsa-miR-193a-5p hsa-miR-532-5p hsa-miR-130a-3p hsa-miR-134-5p hsa-miR-200c-3p hsa-miR-1227-5p hsa-miR-28-3p hsa-miR-27b-3p hsa-miR-409-3p hsa-miR-199a-5p hsa-let-7f-5p hsa-miR-937-5p hsa-miR-28-5p hsa-miR-181b-5p hsa-miR-30c-5p hsa-miR-30e-5p hsa-miR-1225-5p hsa-miR-363-3p hsa-miR-18a-5p hsa-miR-574-3p hsa-miR-339-3p hsa-miR-324-3p hsa-miR-324-5p hsa-miR-92b-5p hsa-miR-30a-5p hsa-miR-146b-5p hsa-miR-378d hsa-miR-210-3p hsa-miR-382-5p hsa-miR-100-5p hsa-miR-1275 hsa-miR-502-3p hsa-miR-21-5p hsa-miR-638 hsa-miR-194-5p hsa-miR-143-3p hsa-miR-297 hsa-miR-19a-3p hsa-miR-18b-5p hsa-miR-124-3p hsa-miR-345-5p hsa-miR-1290 hsa-miR-30b-5p hsa-miR-660-5p hsa-miR-93-3p hsa-miR-339-5p hsa-miR-574-5p hsa-miR-31-5p hsa-miR-23a-5p hsa-miR-501-5p hsa-miR-330-3p hsa-miR-192-5p hsa-miR-885-3p hsa-miR-206 hsa-miR-132-3p hsa-miR-127-3p hsa-miR-625-5p hsa-let-7f-1-3p hsa-miR-105-5p hsa-let-7b-3p hsa-miR-96-5p hsa-miR-425-3p hsa-miR-940 hsa-miR-933 hsa-miR-455-3p hsa-miR-1281 hsa-miR-191-3p
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Fold change 5.93 5.74 5.55 5.40 5.19 5.06 5.00 4.97 4.86 4.78 4.70 4.47 4.14 4.13 4.12 3.96 3.96 3.92 3.88 3.86 3.74 3.67 3.61 3.53 3.50 3.41 3.38 3.28 3.25 3.16 3.15 3.12 3.06 3.03 2.99 2.98 2.97 2.97 2.92 2.91 2.90 2.82 2.82 2.79 2.74 2.74 2.66 2.63 2.61 2.54 2.53 2.48 2.46 2.41 2.35 2.25 2.23 2.23 2.22 2.20 2.20 2.16 2.14 2.08 2.02 2.01 2.07 2.29 2.52 2.61 2.75 4.22 4.41 8.45 9.35 9.92
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Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
t2:79 t2:80 t2:81 t2:82 t2:83 t2:84 t2:85 t2:86 t2:87 t2:88 t2:89 t2:90 t2:91 t2:92 t2:93 t2:94 t2:95 t2:96 t2:97 t2:98 t2:99 t2:100 t2:101 t2:102 t2:103 t2:104 t2:105 t2:106 t2:107 t2:108 t2:109 t2:110 t2:111 t2:112 t2:113 t2:114 t2:115 t2:116 t2:117 t2:118 t2:119 t2:120 t2:121 t2:122 t2:123 t2:124 t2:125 t2:126 t2:127 t2:128 t2:129 t2:130 t2:131 t2:132 t2:133 t2:134 t2:135 t2:136 t2:137 t2:138 t2:139 t2:140 t2:141 t2:142 t2:143 t2:144 t2:145 t2:146 t2:147 t2:148 t2:149 t2:150 t2:151 t2:152 t2:153 t2:154
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To the best of our knowledge, our study is the first to employ systemic approach to identify potential plasma miRNA biomarkers for AAA. In the present study, miRNA profiling using pooled samples revealed differently expressed plasma miRNA signatures between AAA and healthy controls. Among them, miR-191-3p, miR-455-3p and miR-1281 showed the largest increase (fold change N 5), which is confirmed in the subsequent qRT-PCR assays in an extended cohort. ROC analysis suggested that they could act as suitable biomarkers for AAA. In particularly, the discriminatory power of miR-455-3p was the highest, with an AUC of 0.9825. AAA formation is initiated by inflammation cell infiltration, followed by vascular smooth muscle cell depletion and extracellular matrix degradation [2]. Accumulating evidence suggests that miRNA plays an important role in AAA development by participating in these processes [8,14]. MiR-21 expression is induced by inflammation stimuli, which in turn suppresses AAA progression by inhibiting apoptosis and promoting proliferation of vascular smooth muscle cells [9]. MiR-29b is downregulated in AAA to prevent rupture by increasing collagen and elastin gene expression [10,15]. MiR-205 has been shown to influence AAA development by stimulating inflammation and matrix metalloproteinase activity. Among its targets are tissue inhibitor of metalloproteinase 3 (TIMP3) and reversion-inducing cysteine-rich protein with kazal motifs (RECK) [16]. MiR-195 plays similar role as miR-29b in AAA, but the effects it exerts are lower [13,17]. The newly identified miR-24 is a key regulator of vascular inflammation and AAA pathology. It regulates
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cytokine synthesis and macrophage survive by targeting chitinase 3like 1 (Chi3l1) [12]. miRNA expression profiling of AAA has also been performed in previous studies [18,19]. By comparing infrarenal abdominal aortic aneurysm and corresponding normal tissues, Pahl et al. identified eight miRNAs with significantly different expression levels [19]. A study by Kin demonstrated high expression levels of miRNA related to fibrosis (miR-29b), inflammation (miR-124a, miR-146a, miR-155, and miR-223), and endothelium (miR-126, let-7 family members, and miR-21) in AAA tissues. Intriguingly, those miRNAs that showed increased expression in AAA tissues were significantly reduced in plasma [18]. This is in line with our findings that the majority of miRNAs that showed fold change N 2 is down-regulated in AAA plasma. It is noteworthy that conflicting results could be obtained in different studies. For example, miR-155 expression was reported to be elevated in AAA serum in the study by Biros [20]. These inconsistencies justify further research on circulating miRNA expression patterns related to AAA development. AAA occurs most often in people age 65 and older. AAA patients are thus more likely to carry multiple comorbidities, such as high blood pressure, diabetes mellitus, and coronary artery disease. These comorbidities have their unique miRNA expression profiles and therefore could complicate our efforts to identify miRNAs specific to AAA [21, 22]. In this study, we utilized sample pooling technique to minimize such effects. The samples used to make a pool were comparable regarding comorbidities. Several limitations of our study merit consideration. Because of the relatively small validation sample size, the diagnosis value of plasma miR-191-3p, miR-455-3p and miR-1281 may be overestimated. Largescale studies in different centers are needed to validate our results. Second, the function of these miRNAs, and their specific roles in AAA development, is largely unknown. To decipher the mechanism
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95.0% sensitivity and 100.0% specificity (confidence interval = 0.9613– 1.0037). The AUC of miR-1281 was 0.9206 with 76.7% sensitivity and 98.3% specificity (confidence interval = 0.9613–1.0037) (Fig. 2).
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Fig. 1. Fold differences (log2−ΔΔCt) in plasma-derived miR-191-3p, miR-45-3p, and miR-1281 expression between AAA patients (n = 60) and controls (n = 60) (Mann–Whitney U-test).
Fig. 2. ROC curves for plasma-derived miR-191-3p, miR-455-3p and miR-1281 to discriminate between AAA and controls. The AUC values were given on the graph.
Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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Funding
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This study was supported by grants from National Natural Science Foundation of China (81270396), National Natural Science Foundation of Jiangsu Province, China (BK20140103), Nanjing Municipal Science and Technology Commission (BL2012035).
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Conflict of interest
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The authors thanked Haiyan Min for her excellent technical guidance.
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Acknowledgment
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underling their elevation in AAA plasma could aid their clinical application and interpretation. In conclusion, using microarray assay, we identified three miRNAs with the highest increase in AAA plasma. Subsequent qRT-PCR validation confirmed the elevation and demonstrated high diagnosis values of these miRNAs, especially miR-455-3p. Our results suggested that they may act as promising biomarkers for the early diagnosis of AAA.
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Please cite this article as: Zhang W, et al, Plasma microRNAs serve as potential biomarkers for abdominal aortic aneurysm, Clin Biochem (2015), http://dx.doi.org/10.1016/j.clinbiochem.2015.04.016
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