Circulating miRNAs reflect early myocardial injury and recovery after heart transplantation

From July 6^th to August 27^th, 2011, 7 consecutive patients underwent heart transplantation in Fuwai Hospital (Beijing, China) were included in our study (Table 1). 14 healthy people were also included as a control group. The protocol of this study was carried out according to the principles of the Declaration of Helsinki and approved by the Medical Ethics Committee of Cardiovascular Institute and Fu Wai Hospital. Written informed consent was obtained from all the participants before enrolment.

6 ml venous blood samples were drawn from each patient immediately after transferred to ICU (day 0) and then at 6:00 am on the 1^st, 2^nd, 3^rd, 7^th and 14^th day after transplantation respectively. For serum separation, 3 ml of each blood sample was put into a common test tube containing polyolefin resin (Greiner Bio-One, Frickenhausen, Germany) for at least 10 minutes at room temperature. Then the tube was centrifuged at 3000g for 20 minutes to obtain serum. The left 3 ml was put into a K₂-EDTA-coated tubes (BD Biosciences, California, USA) and centrifuged at 1600 g for 10 minutes. The plasma was carefully transferred into a new RNA-free tube for second centrifugation at 16,000 g for 10 min to further eliminate cell debris. Then the plasma was aliquot into RNase-free tubes and stored at −80°C before RNA extraction.

Total RNA was extracted from 400 ul plasma, using the mirVana PARIS kit (Ambion, Warrington, United Kingdom) according to the modification of manufacturer’s instructions (as detailed in ref [3]), and subsequently eluted in 30 ul nuclease-free water. To date, several miRNAs such as miR-16 [18], or synthetic C. elegans miRNAs [3, 6, 19] have been established and validated to normalize for the miRNAs content in different body fluid. However, for detection of miRNA in plasma, synthetic C. elegans miRNAs were broadly used [3, 6, 19]. So in our experiment cel-miR-39, cel-miR-54, and cel-miR-238 were chosen and spiked in the plasma samples after combining the sample with 2 × Denaturing Solution (as a mixture of 25 fmol of each oligonucleotide in a 5 ul total volume) [3].

5 ul RNA was put into 15 ul reverse transcribed (RT) reaction to generate cDNA using the TaqMan miRNAs Reverse Transcription Kit and miRNAs-specific stem-loop primers (Applied Biosystems, Foster City, USA). Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed on ABI 7300 real-time PCR instrument (Applied Biosystems, Foster City, USA). The TaqMan 2× Universal PCR Master Mix (No AmpErase UNG) and TaqMan miRNAs Assay (Applied Biosystems, Foster City, USA) was used for quantification of miRNAs at 95°C for 10 min, followed by 95°C for 15 s (40 cycles) and 60°C for 1 min (40 cycles). The Ct value was defined as the cycle number at which the fluorescence exceeded the threshold. In our experiment the detection limit of Ct value was defined as 40. All PCR results were duplicated to evaluate the miRNAs’ expression level. cTnI levels in the serum were measured by the electrochemiluminescence method (Roche, Basel, Switzerland).

Synthetic single-stranded RNA oligonucleotides miR-133a, miR-208a, and miR-133b (miRBase Release v.19.0) were purchased from Shanghai GenePharma, China. Sequence information was provided in Table 2. Synthetic miRNAs were input into the RT reaction according to range of copies from reference [3, 20]. The standard curves for miR133a, miR-208a, and miR-133b were plotted by Ct values versus copy number of the synthetic miRNAs as shown in Figure 1. Copies of endogenous miRNAs in plasma were then approximated according to their Ct values and the standard curve. A Normalization Factor was calculated by the Ct values of the three synthetic spiked-in C. elegans miRNAs [3, 20]. Then the copies of a given miRNAs in each sample (calculated by the standard curves described earlier) were multiplied by the normalization factor corresponding to the sample to obtain a normalized copy number [3, 20].

Swan-Ganz Catheter (Edwards Lifesciences, California, USA) was implanted through external jugular vein of patients before operation. Hemodynamic parameters such as central venous pressure (CVP), pulmonary capillary wedge pressure (PCWP) and cardiac output (CO) were measured on 0 day, the 1^st day, 2^nd day, or 3^rd day postoperation (within 48–72 hous after catherization). A score adapted from Wernovsky and his colleagues was used to quantify inotrope use for our patients [21]. Inotrope score is a reliable index of postoperative cardiac function; higher scores indicate poorer cardiac function. The score was calculated by obtaining the total amount of inotropic support the patients received at each sampling point (on 0 day, the 1^st day, 2^nd day, and 3^rd day postoperation) and then entering the data into the equation as follows: Inotrope score = Dopamine + Dobutamine + ([Epinephrine + Norepinephrine + Phenylephrine] × 100) + Milrinone × 10. Units of inotrope dosage used in this equation were in micrograms per kilogram per minute.

All statistical data were presented as mean ± standard deviation (SD) unless indicated otherwise. Pearson correlation analyses were used for miRNAs themselves or miRNAs versus cTnI and clinical parameters. Comparisons between 2 groups were performed with Student’s t-tests for Gaussian data or Mann–Whitney tests for non-Gaussian data. For comparisons of more than 2 groups, one-way ANOVA was used, followed by post hoc testing using Bonferroni correction for more groups. The sensitivity and specificity of each miRNAs was calculated by receiver operating characteristic curve (ROC) analyses. All p values were two-sided and p values <0.05 were considered statistically significant. All analyses were performed using SPSS version 17.0.0 (SPSS Inc, Chicago, USA).

The levels of circulating miR-133a, miR-208a, and miR-133b were elevated to peak just after the transplantation (Day 0) (Figure 2A, 2C and 2E). MiR-133a increased to 11675 ± 3481 copies/ul (p = 0.001), miR-208a to 5544 ± 1757 copies/ul (p < 0.001), while miR-133b to 1173 ± 227 copies/ul(p < 0.05) as compared to healthy controls. After that the expression levels of all three miRNAs in plasma declined gradually from Day 0 to Day 14. However, miR-133a on Day 1 was 8198 ± 1363 copies/ul, which was still higher (p < 0.05) than those in controls, so was miR-208a (3966 ± 1580 copies/ul, p = 0.001). There seemed to be no difference for miRNAs in patients compared to controls after 2 days since heart transplantation except miR-208a, which was still significant at Day 2 (2852 ± 550 copies/ul, p < 0.05). Whereas, miR-133a, miR-208a, and miR-133b all showed a trend to decline gradually from Day 0 to Day 14, which was similar to serum cTnI (Figure 2B, 2D and 2F). Fold changes of miR-133a, miR-208a and cTnI on Day 0 or Day 1 was significantly higher compared to Day 14 (p < 0.05), although there were no significance on other time points. Of the 3 miRNA in plasma, miR-133a was the most abundant on Day 0, then followed by miR-208a and miR-133b. In all samples, concentration of miR-133a and miR-208a was statistically higher than that of miR-133b (p < 0.05 and p = 0.001 respectively), while there was no difference between miR-133a and miR-208a. So we infer that circulating miR-133a and miR-208a are more enriched than miR-133b in plasma of patients after heart transplantation.

To evaluate whether circulating miRNAs can reflect the myocardial injury after heart transplantation, correlations between circulating miRNAs and cTnI were analyzed. We can see that all of these three circulating miRNAs in plasma correlated well with serum cTnI (p < 0.001) (Figure 3). MiR-133b had the stronger correlation with cTnI (R² = 0.813, p < 0.001; Figure 3E) compared with the correlations between miR-133a/miR-208a and cTnI (R² = 0.567, p < 0.001 and R² = 0.498, p < 0.001 respectively; Figure 3A and 3C). For correlations among miRNAs themselves, miR-133a, miR-208a and miR-133b correlated strongly with each other (p < 0.001) (Figure 3B, 3D and 3F). However, miR-208a which was expressed exclusively in heart, had a 100% sensitivity and specificity (Figure 4B), but it couldn’t be detected in all patient samples (57.14%), and not existed in healthy controls at all. Although miR-133a was found in all samples and miR-133b could only be detected in 71.42% samples and 56.25% controls, miR-133b had a better sensitivity than miR-133a (90% sensitivity and 100% specificity vs. 85.71% sensitivity and 100% specificity; Figure 4A and 4C).

To evaluate the reason for rising of circulating miRNAs after transplantation and whether these miRNAs could predict the recent prognosis of patients, correlations of cirulating miRNAs at different time points with perioperative parameters were analyzed (Table 3 and Table 4). Neither circulating miRNAs nor cTnI had relationships with cold ischemia time of donor heart. However, miR-133b from Day 0-Day 2, cTnI from Day 1- Day 3, and miR-133a on Day 2 did have strong correlations with bypass time. The correlation coefficients of both miR-133a and miR-133b were over 0.98, which is higher than cTnI (Table 3). It seemed that length of bypass time contribute to elevations of miR-133b, cTnI and miR-133a. Next we divided bypass time into 2 parts: the aortic clamping time and parallel bypass time when there was a low level of reperfusion despite of persistent ischemia of heart. Interestingly, only miR-133a on Day 3 negatively correlated with the aortic clamping time, and miR-133b had a stronger association with parallel bypass time than cTnI from Day 0 to Day 2 (Table 3).

CVP, PCWP, CO, and inotrope score are indices of heart function. Higher CVP, PCWP, inotrope score and lower CO indicate worse dysfunction of heart. MiR-133a, miR-208a, miR-133b, and cTnI had positive correlations with CVP and inotrope support (Table 4). However, only miR-133b and miR-208a had positive correlations with PCWP; there were negative correlations between miR-133b/cTnI and CO (Table 4). So miR-133b was the only one that had the correlations with CVP, PCWP, CO, and inotrope score at the same time.

To evaluate recent prognosis, ventilation time and length of ICU stay were included. Ventilation time was strongly correlated with miR-133b from Day 0-Day 2, cTnI from Day 0-Day 3, and miR-133a on Day 2 (p < 0.05) (Table 3). The correlation coefficients of miR-133b were over 0.99, still the highest of all. MiR-133b from Day 1-Day 2, cTnI from Day 0-Day 3 showed correlationship with length of ICU stay (p < 0.05) (Table 3). The correlation coefficent of miR-133b at each time point was higher than that of cTnI.