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Methods
Study Design
This study included heart transplant recipients from Pompidou Hospital (Paris, France) between January 2004 and October 2010 who had a diagnosis of biopsy-proven allograft rejection (n = 43). Thirteen patients were excluded because of a lack of suitable material for miRNA biopsy assessment, leaving 30 rejecting heart allograft patients as the study sample. This group of patients was compared with a matched control group of 30 patients transplanted during the same period of time but without allograft rejection. These patients were matched based on the following criteria: recipient age, donor age, cold ischaemia time, time from transplantation to index biopsy and maintenance immunosuppressive regimen. All the patients had conventional graft histopathology together with concomitant assessment of microRNA expression in the allograft and serum taken at the time of biopsy.
We used an additional independent validation sample of 53 patients from three heart transplant centres [Necker (n = 25), Rouen (n = 19), and Pitié-Salpétrière hospitals (n = 9)].
All of the transplants were ABO compatible and had current negative IgG T cell and B cell complement-dependent cytotoxicity cross-matching at the time of transplantation. The transplantation allocation system was identical for all four centres and followed the rules of the French national agency for organ procurement (Agence de la Biomédecine).
Clinical Data
Clinical data for the donors and recipients in the development and validation cohorts were obtained from reviews of the patients' charts. We recorded the data for all the patients regarding donor age, donor gender, recipient age, recipient gender, primary heart disease, date of transplantation, follow-up, severe bacterial infection, CMV-related disease, cold ischaemia time, and immunosuppressive drug regimen.
Histology and Immunohistochemistry
Endomyocardial biopsies were formalin-fixed, paraffin-embedded, and routinely stained with haematoxylin-eosin. Immunohistochemistry was performed on tissue sections with specific antibodies: rabbit monoclonal anti-C4d (DB Biotech, Kosice, Slovac Republic) and monoclonal anti-CD68 (DakoCytomation, Glostrup, Denmark) using an immunoperoxidase method as previously described.
Definition of Heart Allograft Rejection
Endomyocardial biopsies were carefully examined for the presence of rejection by three trained pathologists (P.B., P.R., and J.P.D.V.H.) according to updated international classification criteria. T-cell-mediated rejection was defined according to the International Society for Heart and Lung transplantation (ISHLT) 2004 classification. Antibody-mediated rejection was defined according to the last recommendation of the pathology task force of the ISHLT as follows: pAMR0: no features of ABMR; pAMR1: suspicious ABMR subdivided into pAMR1(H+) with histopathology positive and immunohistochemistry negative and pAMR1(I+) with histopathology negative and immunohistochemistry positive; pAMR2: histopathology and immunohistochemistry both positive; pAMR3: severe ABMR. The rejection episodes were considered in both test and validation cohorts as early (occurring before 1-year post-transplant) and late (occurring after 1-year post-transplant), Supplementary material online, Table S1.
Detection of Antibodies Against Donor-specific HLA Molecules
Patients with available serum at the time of biopsy were screened for the presence of circulating anti-HLA antibodies. Antibodies against the HLA-A, HLA-B, HLA-DR, HLA-DQ, and HLA-DP epitopes were tested using single-antigen flow bead assays (One Lambda, Inc., Canoga Park, CA, USA) on a Luminex platform as previously described.
MicroRNA Analysis
Extraction of total RNA from frozen EMBs and serum was conducted anonymously. Sample information was replaced by numbers, and the technician was blinded to clinical information regarding allograft rejection status.
Extractions were performed with the Ambion Extraction Kit (Ambion, Austin, TX, USA) and the Qiagen miRNeasy Serum/Plasma kit (Qiagen, Venlo, The Netherlands) according to the manufacturer's recommendations. The yield and purity of RNA were measured using a NanoDrop ND-1000 spectrophotometer. RNAs were then individually retro-transcribed using the microRNA reverse transcription kit (Applied Biosystems). Each reverse transcription was performed with 5 μL of a 1 ng/μL RNA solution, 7 μL of master mix [containing 100 U of transcriptase Superscript II (Invitrogen, Carlsbad, CA, USA) and a mix of dNTP], 3 μL of specific miRNAs probes (Ambion, Austin, TX, USA) in a BioRad Thermal Cycler using the following parameter values: 16°C for 30 min, 42°C for 30 and 85°C for 5 min. MicroRNAs were then quantified by real-time PCR using specific probes of the cDNA obtained from RT. Real-time PCR was performed with 2,5 μl of RT product mixed with 15 μl of ABsoluteTM QPCR Mix (ABgene, Epsom, UK) in a 385-well plate in a ABI 7500FAST real-time PCR system. miRNA with more than half of the cycle threshold (Ct) values >35 per group were excluded from the analysis.
MicroRNA copy numbers were normalized using RNU48 small nucleolar RNA copy numbers to obtain ΔCt values. ΔΔCt was then obtained by subtracting the average of ΔCt to each ΔCt values. Finally, we determined fold values for each sample (2).
Selection Strategy of Relevant miRNAs Related to Allograft Rejection
Selection of miRNAs was first conducted by careful in silico analysis, studying the literature for relevant miRNAs associated with allograft rejection. We also screened for miRNAs related to cardiovascular pathogenesis including endothelial injury, endothelial activation, and vascular inflammation.
We then performed a database screening (TargetScan.org, miRBase.org, microRNA.org) to determine relevant miRNA biomarker candidates according to their predicted interactions with molecules of interest (VCAM, ICAM, eNOS, heparan sulfate, CD68, and CD40) and signalling pathways (inflammatory, ischaemic and endothelial activation pathways, such as mTOR or NFkappaB).
Following this analysis, we identified 14 miRNAs of interest for heart transplant rejection (Supplementary material online, Table S2): (i) miRNAs predominantly expressed in endothelium and associated with endothelial activation (miR-92a, miR-126, miR-221, and miR-296); (ii) miRNAs expressed in cardiomyocytes and associated with cardiovascular tissue remodelling (miR-21, mi-R31, and miR-208); (iii) miRNAs related with inflammation (miR-10a, miR-142-3p, miR-155, miR-181a, miR-181b, miR-182, and miR-451).
In Situ Hybridization
MicroRNA in situ hybridization (ISH) was performed on FFPE tissue as previously described. After deparaffinization of the tissue sections, the tissue was incubated with PFA 4%, washed with PBS-DEPC and bathed with the acetylation solution. Sections were then washed and incubated with proteinase K (5 μg/mL) at 37°C. After washing, saturation followed with the incubation of sections with the hybridization buffer for 5 h. The probe for each miRNA (miRCURY LNA, microRNA detection probes from ExiKon, Vedbaek, Denmark) was then added to a preparation containing the hybridization buffer, CHAPS 10% and Tween 20%. Sections were incubated with this solution overnight at 56°C and rinsed afterward with SSC buffers. Sections were then incubated with B1 solution and with the blocking solution. Anti-DIG was added to the blocking solution and sections were incubated overnight. Sections were then washed with B1 solution and a NTMT/Levamisole solution. Sections were then revealed with NBT/BCIP mix for 3 h to 5 days depending on the specific miRNA. Sections were washed, incubated with PFA 4% and mounted. The negative control of ISH was performed using scrambled probe control (Supplementary material online, Figure S1).
Statistical Methods
Continuous variables are reported as median, min max, and inter-quartile range. We compared means and proportions with Student's t-test and the χ test (or Fisher's exact test if appropriate). Non-parametric analysis (Kruskal–Wallis and Mann–Whitney tests) was performed when appropriate. We used a conventional receiver-operating characteristic (ROC) curve to analyse miRNA levels to determine the cut-off points that yielded the highest combined sensitivity and specificity with respect to distinguishing subjects with acute rejection from subjects with normal biopsy results. We calculated the area under the curve (AUC) and 95% confidence intervals for the AUC. The association between intragraft miRNAs and serum levels of miRNAs was analysed using Pearson correlation coefficient.
The association of miRNAs of interest with rejection patterns was investigated using unsupervised methods such as hierarchical cluster analysis and principal component analysis based on the combination of the expression of the 14 miRNAs [fold values (2] obtained from the ΔΔCt value for each patient and each miRNA (ΔCt of the miRNA for a patient – mean ΔCt of the population)]. Hierarchical cluster analysis and dendrograms were performed with the hcluster module of the amap package of the R software, while principal component analysis was carried out using the dudi.pca module of 12 the ade4 package of the R software (version 2.10.1). Other statistical analyses were performed using the STATA 11.0 software (Stata Corporation, College Station, TX, USA) and the Graphpad PRISM 5 software.
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