Atrial fibrillation alters the microRNA expression profiles of the left atria of patients with mitral stenosis
- Hai Liu†1,
- Guang-xian Chen†1,
- Meng-ya Liang1,
- Han Qin1,
- Jian Rong2,
- Jian-ping Yao1 and
- Zhong-kai Wu1Email author
© Liu et al.; licensee BioMed Central Ltd. 2014
Received: 20 October 2013
Accepted: 22 January 2014
Published: 25 January 2014
Structural changes of the left and right atria associated with atrial fibrillation (AF) in mitral stenosis (MS) patients are well known, and alterations in microRNA (miRNA) expression profiles of the right atria have also been investigated. However, miRNA changes in the left atria still require delineation. This study evaluated alterations in miRNA expression profiles of left atrial tissues from MS patients with AF relative to those with normal sinus rhythm (NSR).
Sample tissues from left atrial appendages were obtained from 12 MS patients (6 with AF) during mitral valve replacement surgery. From these tissues, miRNA expression profiles were created and analyzed using a human miRNA microarray. Results were validated via reverse-transcription and quantitative PCR for 5 selected miRNAs. Potential miRNA targets were predicted and their functions and potential pathways analyzed via the miRFocus database.
The expression levels of 22 miRNAs differed between the AF and NSR groups. Relative to NSR patients, in those with AF the expression levels of 45% (10/22) of these miRNAs were significantly higher, while those of the balance (55%, 12/22) were significantly lower. Potential miRNA targets and molecular pathways were identified.
AF alters the miRNA expression profiles of the left atria of MS patients. These findings may be useful for the biological understanding of AF in MS patients.
KeywordsAtrial fibrillation Microrna Mitral stenosis Microarray Mirfocus
Atrial fibrillation (AF) is characterized as an irregular and sometimes rapid heart rate, with symptoms that include palpitations and shortness of breath. AF is the most common cardiac arrhythmia observed in clinical practice and constitutes a risk factor for ischemic stroke . Despite recent significant advances in the understanding of the mechanisms associated with AF, complexities in the etiology of atrial electrical dysfunction (including a genetic component ) and the subsequent associated arrhythmia have prevented definitive elucidation .
The progression from acute to persistent and then chronic AF is accompanied by changes in gene expression that lead to differences in protein expression and activity. MicroRNAs (miRNAs) are regulators of gene expression at the post-transcriptional level , and appear to have regulatory roles that underlie the pathophysiology of AF. Many studies have shown that miRNAs regulate key genetic functions in cardiovascular biology and are crucial to the pathogenesis of cardiac diseases such as cardiac development , hypertrophy/heart failure , remodeling , acute myocardial infarction , and myocardial ischemia-reperfusion injury . Currently, there is a growing body of literature that indicates that many miRNAs are involved in AF through their target genes [7, 10, 11].
AF can be an isolated condition, but it often occurs concomitantly with other cardiovascular diseases such as hypertension, congestive heart failure, coronary artery disease, and valvular heart disease . AF is also prevalent in mitral stenosis (MS; a consequence of rheumatic fever), affecting approximately 40% of all MS patients . MS is among the major cardiovascular diseases in developing countries where rheumatic fever is less well controlled, and 50% or more of patients with severe MS have AF. Patients with both AF and MS have a 17.5-fold greater risk of stroke and a four-fold higher incidence of embolism compared with people with normal sinus rhythm (NSR) [14, 15].
Structural changes of the left atria (LA) and right atria (RA) associated with AF in MS patients are well established [13, 14]. Recently, reports suggest that AF also alters the miRNA expression profiles in RA of MS patients [16, 17]. However, miRNA changes in LA from MS patients with AF are still unknown. Given the complexity of the pathophysiology that may be associated with AF, we need a better understanding of the miRNA changes in the LA, which may help in designing and developing new therapeutic interventions. This study investigated alterations of miRNA expression profiles in LA tissues of MS patients with AF relative to MS patients with NSR.
The Human Ethics Committee of First Affiliated Hospital of Sun Yat-sen University approved this study, and the investigation complied with the principles that govern the use of human tissues outlined in the Declaration of Helsinki. All patients gave informed consent before participating in the study.
Human tissue preparation
Left atrial appendage (LAA) tissue samples were obtained from MS patients, both in NSR (n = 6, without history of AF) and with AF (n = 6, documented arrhythmia >6 months before surgery). The tissue samples were obtained at the time of mitral valve surgery, immediately snap frozen in liquid nitrogen, and stored at -80°C until used. The diagnosis of AF was reached by evaluating medical records and 12-lead electrocardiogram findings. NSR patients had no history of using antiarrhythmic drugs and were screened to ensure that they had never experienced AF . Preoperative 2-dimensional color transthoracic echocardiography was performed routinely on the patients. Preoperative functional status was recorded according to New York Heart Association (NYHA) classifications.
The total RNA from human LAA tissue samples was extracted using TRIzol reagent (Invitrogen) in accordance with the protocol of the manufacturer. The RNA quality of each sample was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and immediately stored at -80°C.
Microarray processing and analysis
The miRNA microarray expression analysis was performed by LC Sciences (Houston, TX, USA) as described previously . In brief, the assay began with a total RNA sample (2 to 5 μg). The total RNA was size-fractionated using a YM-100 Microcon centrifugal filter (Millipore, Billerica, MA). RNA sequences of <300 nt were isolated. These small RNAs were then extended at the 3′ end with a poly(A) tail using poly(A) polymerase, and then by ligation of an oligonucleotide tag to the poly(A) tail for later fluorescent dye staining.
Hybridization was performed overnight on a μParaflo microfluidic chip using a micro-circulation pump (Atactic Technologies, Houston, TX). Each microfluidic chip contained detection probes and control probes. The detection probes were made in situ by photogenerated reagents. These probes consisted chemically of modified nucleotide coding sequences complementary to target miRNA (all 1921 human miRNAs listed in the Sanger’s miRNA miRBase, Release 18.0, http://microrna.sanger.ac.uk/sequences/) and a spacer segment of polyethylene glycol to extend the coding sequences away from the substrate. The hybridization melting temperatures were balanced by chemical modifications of the detection probes. Hybridization was performed using 100 μL of 6× saline-sodium phosphate-EDTA (SSPE) buffer (0.90 M NaCl, 60 mM Na2HPO4, 6 mM EDTA, pH 6.8) containing 25% formamide at 34°C.
Fluorescence labeling with tag-specific Cy5 dye was used for after-hybridization detection. An Axon GenePix 4000B Microarray Scanner (Molecular Device, Union City, CA) was used to collect the fluorescent images, which were digitized using Array-Pro image analysis software (Media Cybernetics, Bethesda, MD). Each miRNA was analyzed two times and the controls were repeated 4-16 times.
Analysis of the microarray data was also performed at LC Sciences (see Additional file 1). The microarray data was analyzed by subtracting the background, and then the signals were normalized using a locally weighted regression scatterplot smoothing (LOWESS) filter as reported previously . Detectable miRNAs were selected based on the following criteria: signal intensity >3-fold the background standard deviation, and spot coefficient of variation (CV) < 0.5, where CV = standard deviation/signal intensity. When repeating probes were present on the array, the transcript was listed as detectable only if the signals from at least 50% of the repeating probes were above detection level. To identify miRNAs whose expression differed between the AF and NSR groups, statistical analysis was performed. The ratio of two samples was calculated and expressed in log2 scale (balanced) for each miRNA. The miRNAs were then sorted according to their differential ratios. The P-values of the t-test were also calculated. miRNAs with P-values < 0.05 were considered significantly differentially expressed.
Reverse transcription-real time quantitative PCR (RT-qPCR) validation of selected miRNAs
To validate the microarray results in the present study, a stem-loop RT-qPCR based on SYBR Green I was performed on selected differentially expressed miRNAs. The primers used are listed in Additional file 2. Total RNA was isolated using TRIzol reagent (Invitrogen) as described above. A single-stranded cDNA for each specific miRNA was generated by reverse transcription (RT) of 250 ng of total RNA using a miRNA-specific stem-looped RT primer. Briefly, an RT reaction mixture contained 250 ng of total RNA, 0.5 μL of 2 μM stem-loop RT primer, 1.0 μL of 5× RT buffer, 0.25 μL of 10 mM of each dNTP, 0.25 μL of 40 U/μL RNase inhibitor, and 0.5 μL of 200 U/μL Moloney murine leukemia virus (M-MLV) reverse transcriptase. An Eppendorf Mastercycler (Eppendorf, Hamburg, Germany) was used to perform the RT reaction under the following conditions: 42°C for 60 min, 70°C for 15 min, and finally, held at 4°C.
After the RT reaction, qPCR was performed using an ABI PRISM 7900HT sequence-detection system (Applied Biosystems, Foster City, CA, USA) with the Platinum SYBR Green qPCR SuperMix-UDG (Invitrogen). In accordance with the manufacturer’s instructions, a 20-μL PCR reaction mixture contained 0.5 μL of RT product, 10 μL of 2× SYBR Green Mix, 0.4 μL of ROX, 0.8 μL of 10 μM primer mix, and 8.3 μL of nuclease-free water. The reaction protocol was: 95°C for 2 min, and then 40 amplification cycles of 95°C for 15 s, and 60°C for 30 s.
All reactions were run in triplicate. To account for possible differences in the amount of starting RNA, miRNA expressions were normalized to small nuclear RNA RNU6B [21, 22]. RT-qPCR data were represented by the cycle threshold (Ct) value. The relative expression level (i.e., fold change) for each miRNA was calculated using the comparative cycle threshold 2-ΔΔCt method .
Target prediction and function analysis
We used the database miRFocus (http://mirfocus.org/) to predict potential human miRNA target genes. The website describes miRFocus as a human miRNA information database, and is an open-source web tool developed for rapid analysis of miRNAs. It also provides comprehensive information concerning human miRNAs, including not only miRNA annotations but also miRNA and target gene interactions, correlations between miRNAs and diseases and signaling pathways, and more. The miRFocus provides a full gene description and functional analysis for each target gene by combining the predicted target genes from other databases (TargetScan, miRanda, PicTar, MirTarget and microT). In this study, only those genes that were predicted by two or more databases were considered candidates; the greater the number of databases that predicted that a given gene would be a target, the more likely the miRNA-mRNA interaction would be relevant . The miRFocus program also identifies miRNA-enriched pathways, incorporating those from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Biocarta, and Gene Ontology (GO) databases, with Fisher’s exact test.
All data are presented as mean ± standard deviation and analyzed with the paired t-test. Spearman’s correlation coefficients were used to examine the association between validated miRNAs and left atrial size. P < 0.05 was considered statistically significant.
Clinical characteristics of the NSR and AF patients
Clinical characteristics of the NSR and AF patients (n = 6, each)
NSR (n = 6)
AF (n = 6)
47.51 ± 8.36
49.42 ± 11.87
LA size (mm)
38.31 ± 5.32
56.35 ± 6.08*
42.35 ± 4.43
44.13 ± 5.17
62.54 ± 5.16
60.73 ± 4.04
miRNA expression profiles of LAA tissue from MS patients with and without AF
Differences in miRNA expression profiles of LAA tissues from MS patients with and without AF
MiRNAs differentially expressed in LAA tissues between MS patients with AF or NSR
Validation of the miRNA microarray data with RT-qPCR
Association between LA size and changes in miRNA expression
We investigated whether the changes observed in the expression levels of the 5 validated miRNAs between the LAA tissues of NSR and AF patients correlated with LA size.
Prediction of putative target genes and pathways of the differentially expressed miRNAs
To determine the probable biological function of the differentially expressed miRNAs, we predicted the putative targets and pathways of 5 validated miRNAs (hsa-miR-1, hsa-miR-26a-5p, hsa-miR-466, hsa-miR-574-3p, and hsa-miR-3613-3p) using the miRFocus database.
Prediction of putative target genes and pathways of selected miRNAs
Target prediction database
miRanda, MirTarget, microT, PicTar, TargetScan
miRanda, MirTarget, microT, PicTar, TargetScan
MirTarget, microT, PicTar, TargetScan
Biological processes of the predicted miRNA targets
GO:0003723: RNA binding
DDX5 SFRS9 HNRNPU TRA2B CPEB1 SFRS1 HNRNPA3 HNRNPK SFRS3
GO:0006397: mRNA processing
ISY1 DDX5 SFRS9 DHX15 HNRNPU CPEB1 SFRS1 HNRNPA3 HNRNPK SFRS3
GO:0007179: transforming growth factor beta receptor signaling pathway
TGFBR2 MAP3K1 NLK
GO:0051301: cell division
CCNE2 CCNE1 CDK6 CCND2
GO:0003700: transcription factor activity
ARNT2 GLI3 SMAD2 RUNX1T1 TCF7L2 MECOM
GO:0005515: protein binding
CCDC6 KIT CYCS EIF4E COL4A1 PTGS2 RUNX1T1 ULK2 MECOM RICTOR
GO:0006468: protein amino acid phosphorylation
PRKAA2 RPS6KA3 SMAD2 ULK2 DAPK1
GO:0046872: metal ion binding
CYCS GLI3 PTGS2 RUNX1T1 MECOM
GO:0031625: ubiquitin protein ligase binding
GO:0051384: response to glucocorticoid stimulus
GO:0003700: transcription factor activity
NFATC3 NFAT5 EP300 RARA CREBBP RUNX1T1 RUNX1 ETS1 TCF7L2 NKX3-1 HDAC2 STAT3 CTNNB1 SMAD4
GO:0004842: ubiquitin-protein ligase activity
UBE2J1 UBE2H UBE2Z BIRC6 MAP3K1 UBE2N UBE2D3 UBE2B NEDD4L LMO7 UBE2R2 HUWE1 UBE2E2 UBE2G1
GO:0006355: regulation of transcription, DNA dependent
NFAT5 EP300 RARA CREBBP ABL1 RUNX1T1 RUNX1 NKX3-1 CREB1
GO:0008134: transcription factor binding
PPARGC1A ETS1 TCF7L2 NKX3-1 HDAC2 PIM1 STAT3 CTNNB1
GO:0008284: positive regulation of cell proliferation
FGFR2 FGFR1 ADAM17 INSR KIT BIRC6 HDAC2 IGF1R CCND1 KRAS
GO:0046872: metal ion binding
PRKCI EP300 ACACB RARA CREBBP RUNX1T1 MID1 ADAM17 INSR PPP1CB PIM1 XIAP EGLN1 IGF1R LMO7 TRAF3
GO:0051246: regulation of protein metabolic process
UBE2J1 UBE2H UBE2Z BIRC6 UBE2N UBE2D3 UBE2B UBE2R2 UBE2E2 UBE2G1
Pathway analysis of the selected miRNAs
ISY1 DDX5 SFRS9 DHX15 HNRNPU TRA2B SFRS1 HNRNPA3 HNRNPK SFRS3
hsa4320: Dorso-ventral axis formation
NOTCH2 EGFR NOTCH3 CPEB1 ETS1
hsa4115: p53 signaling pathway
CCNE2 CCNE1 PTEN CDK6 CCND2 IGF1 ATM
hsa4010: MAPK signaling pathway
TGFBR2 MYC PPP3R1 CACNA1C PPP3CB MAP3K1 NLK PAK2
hsa4150: mTOR signaling pathway
PRKAA2 RPS6KA3 EIF4E ULK2 RICTOR
hsa5200: Pathways in cancer
CCDC6 ARNT2 KIT CYCS COL4A1 GLI3 PTGS2 SMAD2 RUNX1T1 TGFB2 TCF7L2 DAPK1 MECOM
hsa5200: Pathways in cancer
CUL2 EP300 ACVR1B RXRA
hsa5016: Huntington's disease
hsa5211: Renal cell carcinoma
hsa4520: Adherens junction
TCF7 EP300 CREBBP ACTN4 FGFR1 PTPRJ INSR TCF7L2 ACVR1C IGF1R CTNNB1 CTNND1 WASL LMO7 SMAD4
hsa4310: Wnt signaling pathway
NFATC3 TCF7 NFAT5 EP300 CREBBP AXIN2 GSK3B PPP3CA VANGL2 TCF7L2 PPP2R5A WNT5A CCND2 PPP3R1 CCND1 CTNNB1 CSNK1A1 CSNK1E WNT4 SMAD4
hsa4720: Long-term potentiation
EP300 CREBBP PPP1R12A PPP3CA PPP1CB PPP3R1 RPS6KA2 RAP1A GRIA1 KRAS
hsa4330: Notch signaling pathway
JAG1 EP300 MAML3 CREBBP ADAM17 DLL1 NUMBL HDAC2
hsa4910: Insulin signaling pathway
PRKCI PPP1R3B PPARGC1A ACACB GSK3B PRKAA1 INSR SOCS3 IRS1 EIF4E PPP1CB KRAS IRS2
hsa4920: Adipocytokine signaling pathway
PPARGC1A ACACB PRKAA1 SOCS3 IRS1 STAT3 ACSL4 ACSL6 IRS2
More and more studies indicate that specific alterations in miRNA expression profiles are associated with specific disease pathophysiologies [8, 9, 19]. Xiao et al.  were the first to report miRNA alterations in the RA associated with AF in MS patients; 28 miRNAs were differentially expressed between MS patients with AF and those in NSR. However, miRNA changes due to AF in the LA of MS patients are still unknown. The present study is the first to create and compare miRNA profiles of the LA of MS patients with AF and those without AF. We found that in the LA of MS patients, 22 miRNAs were differentially expressed between those with AF and those in NSR.
The results of our study and that of Xiao et al.  were completely different, except for miR-26b. After eliminating the influences of the miRNA microarray technologies used in the two studies, we conclude that these differences, at least in part, may reflect different mechanisms involved in AF between the LA and RA. In MS patients, electrical remodeling of both the left and right atria  is intrinsic to the initiation, development, and maintenance of AF , and morphological differences have also been demonstrated between the two atria . Thus, it is not surprising that AF alters the miRNA expression profiles of the LA of MS patients, and that these alterations may differ from those of the RA. These differences may reflect different mechanisms involved in AF between LA and RA. Therefore, investigations into the differences in miRNA expression profiles associated with AF in MS patients should focus not only on the RA but also on the LA.
Cooley et al.  investigated the differences in miRNA expression profiles in LAA tissues from valvular heart disease patients, and found no detectable differences between patients with AF and those with NSR, a lack that these researchers attributed partially to problems with tissue availability. However, Girmatsion et al.  reported that miR-1 was downregulated in human LAA tissue from AF patients (relative to patients without AF who also underwent mitral valve repair or bypass grafting), which is consistent with our finding that miR-1 was downregulated in human LAA tissues in MS patients with AF. Unfortunately, Girmatsion et al.’s investigation did not utilize miRNA expression profiles. Recently, Luo et al.  found that miR-26 family members were significantly downregulated (>50%) in LAAs from a canine AF model (miR-26a) and in right atrial appendages from AF patients (miR-26a and miR-26b). This suggests the possible involvement of these miRNAs in AF pathophysiology, and is consistent with our finding that miR-26a-5p was downregulated in LAA tissues from MS patients with AF compared with those who remained in NSR.
Lu et al.  found that levels of miR-328 were elevated 3.5- to 3.9-fold in LAAs from dogs with model AF and in right atrial appendages from AF patients, detected by both microarray and RT-qPCR. However, in the present study we found that the expressions of miR-328 were very low in both the NSR and AF group and were not significantly different between the two groups. This contradictory finding may reflect differences in the species (dogs in Lu et al., humans in the present study) and in tissues that were sampled (right atrial appendages from AF patients in Lu et al., LAAs from AF patients in the current study) and the heterogeneity of human myocardial samples .
Studies have shown that miRNAs may be involved directly or indirectly in AF by modulating atrial electrical remodeling (miR-1, miR-26, miR-328) [10, 27, 28] or structural remodeling (miR-30, miR-133, mir-590) [7, 30]. One study showed that miR-1 overexpression slowed conduction and depolarized the cytoplasmic membrane by post-transcriptionally repressing KCNJ2 (potassium inwardly-rectifying channel, subfamily J, member 2; which encodes the K+ channel subunit Kir2.1) and GJA1 (gap junction protein, alpha 1, 43 kDa; which encodes connexin 43), and this likely accounts at least in part for its arrhythmogenic potential . Another study indicated that miR-1 levels are greatly reduced in human AF, possibly contributing to upregulation of Kir2.1 subunits, leading to increased cardiac inward-rectifier potassium current I K1 . A recent study identified miR-26 as a potentially important regulator of KCNJ2 gene expression and, via IK1, a determinant of AF susceptibility . In addition, it also identified miR-26 as a potential mediator of the electrophysiological effects of Ca2+-dependent NFAT (nuclear factor of activated T cells) signaling, believed to be important in the perpetuation of AF.
Previously, the miR-466, miR-574, and miR-3613 have not been described as participating in cardiovascular pathology. The current study found that these miRNAs are potentially involved in several important biological processes and functional pathways associated with AF (e.g., mTOR, Wnt, and Notch signaling), based on the predictions of putative target genes and pathways determined via miRFocus. Our results may implicate these miRNAs in the pathogenesis of AF.
In MS, the association between LA size and AF is well established and LA dilatation is considered both a cause and consequence of AF . Our study found that the expression levels of three validated miRNAs (miR-1, miR-26a-5p, miR-466) correlated with LA size, while those of two others (miR-574-3p, miR-3613-3p) did not. This discrepancy is probably due to the multifactorial nature of AF in MS. For example, it is likely that persistent rheumatic inflammation and LA fibrosis also contribute to the etiology of AF in MS, as well as LA size and hypertension .
The main limitation of this study was the small number of patients included. This was due, in part, to the difficulty of finding MS patients with NSR. In addition, because this study was performed with native human tissues, we could not conduct experiments to modulate miRNA levels. Accordingly, the evidence presented here is indirect. Furthermore, the exact targets and pathways by which alterations in miRNAs cause AF in MS patients remain elusive and deserve further investigation . Finally, the patients in this study were a specific cohort with preserved systolic left ventricular function and little comorbidity; they were undergoing mitral valve replacement surgery. Thus, changes identified in this population may not be representative of other cohort populations .
This study shows that AF alters the miRNA expression profiles in LA from MS patients. These findings may be useful for the biological understanding of AF in MS patients and provide potential therapeutic targets for AF .
Coefficient of variation
Kyoto Encyclopedia of Genes and Genomes
Left atrial appendage
Normal sinus rhythm
New York Heart Association
Reverse-transcription quantitative PCR
Transforming growth factor beta receptor.
This research project was supported by the National Basic Research Program of China (973 Program; NO. 2010CB5295007), the Pearl River Scholar Program (80000-3210003), and the National Science Fund for Young Scholars (81000061).
We would like to acknowledge Gang Dai and Rong Fang (Key Laboratory on Assisted Circulation) for experimental assistance. We are grateful to Junming Yao of LC-Bio for technical assistance.
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