# Expression Profiles of Long Noncoding RNA and mRNA in Epicardial Adipose Tissue in Patients with Heart Failure

Authors: Meili Zheng; Lei Zhao; Xinchun Yang
Journal: BioMed Research International
 (2019)

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## Abstract

The expression profile of long noncoding RNA (lncRNA) in human epicardial adipose tissue (EAT) has not been widely studied. In the present study, we performed RNA sequencing to analyze the expression profiles of lncRNA and mRNA in EAT in coronary artery disease (CAD) patients with and without heart failure (HF). Our results showed RNA sequencing disclosed 35673 mRNA and 11087 lncRNA corresponding to 15554 genes in EAT in total, while 30 differentially expressed lncRNAs (17 upregulated and 13 downregulated) and 278 differentially expressed mRNAs (129 upregulated and 149 downregulated) were discriminated between CAD patients with and without HF (P<0.05; fold change>2); lncRNA ENST00000610659 drew specific attention for it was the top upregulated lncRNA with highest fold change and corresponded to UNC93B1 gene, which was proved to be related to HF and encoded UNC93B1 protein regulating toll-like receptor signaling, and both of them significantly increased in HF patients in qRT-PCR validation; the top significant upregulated enriched GO terms and KEGG pathway analysis were regulation of lymphocyte activation (GO:0051249) and T cell receptor signaling pathway (hsa04660), respectively. The current findings support the fact that EAT lncRNAs are involved in the inflammatory response leading to the development of HF.


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## Body

## 1. Introduction

Recent studies have reported on long noncoding RNA (lncRNA) expression profiling in various human tissues [1]; however, expression profile of lncRNA in human epicardial adipose tissue (EAT) has yet to be described in detail. It is known that a large proportion of the mammalian genome is transcribed as lncRNA, which resides within or between coding genes. In addition, many lncRNAs have been shown to be functional and involved in specific physiological and pathological processes, through transcriptional or posttranscriptional regulatory mechanisms [2, 3]. To date, however, lncRNAs have never been included in analyses of the human EAT transcriptome. EAT is a key cardiometabolic factor, where, by releasing various inflammatory factors [4], EAT can modulate cardiac function and correlate with heart failure (HF) [5, 6], independently of metabolic status or the presence of coronary artery disease (CAD).In the present study, we sought to supplement EAT lncRNA and mRNA expression profiles to provide a more complete picture of the myocardial transcriptional landscape in heart failure and also provide possible biomarkers for HF.


## 2. Materials and Methods

### 2.1. Study Participants

EAT samples were taken from 10 CAD patients who underwent coronary artery bypass graft surgery, in the Department of Heart Center, Beijing Chao-yang Hospital of Capital Medical University. Subjects were divided into two groups: HF group (n=5) and non-HF group (n=5). HF group included patients with Brain Natriuretic Peptide (BNP)>500ng/L and abnormal echocardiography finding (left ventricular end diastolic diameter [LVEDD]>50mm in female and >55mm in male and left ventricular ejection fraction [LVEF]<50%); non-HF group included patients with BNP<100 ng/L and normal views in echocardiography. The protocol was approved by the Ethics Committee of Beijing Chao-yang Hospital affiliated with Capital Medical University and written informed consent was obtained from participants before the study.


### 2.2. RNA Sequencing Procedure

Total RNA was extracted from the EAT and quantified using a NanoDrop ND-1000 instrument. 1-2μg total RNA was used to prepare the sequencing library in the following steps: (1) Total RNA is enriched by oligo (dT) magnetic beads (rRNA removed). (2) Using KAPA Stranded RNA-Seq Library Prep Kit (Illumina), RNA-seq library preparation incorporates dUTP into the second cDNA strand and makes the RNA-seq library strand-specific. (3) After completing, libraries were qualified with Agilent 2100 Bioanalyzer and quantified by absolute quantification qPCR method. (4) Sequence the libraries on the Illumina HiSeq 4000 instrument (we followed the methods of Wang et al. 2019 [7]).


### 2.3. Quantitative RT-PCR

qRT-PCR was used to measure selected lncRNA ENST00000610659 and UNC93B1 mRNA. Total RNA samples were extracted from the EAT samples using TRIzol (Invitrogen, Carlsbad, CA). The relative expression levels of mRNA and lncRNA were quantified using ViiA 7 Real-Time PCR System (Applied Biosystems, Foster City, USA) according to standard methods. lncRNA ENST00000610659: the forward primer was 5′ CGGCTTCAACAAGACGGTTC 3′, the reverse primer was 5′ AAGGCTCCACTCCGCACAAA 3′; UNC93B1 mRNA: the forward primer was 5′ GCTCACCTACGGCGTCTACC 3′, the reverse primer was 5′ CGGTAGGTCTCGT CGTAGTGC 3′.


### 2.4. Statistical Analysis

R package was used to calculate the FPKM value and differential expression for gene and transcript level and perform hierarchical clustering, GO enrichment, pathway analysis, scatter plots, and volcano plots with the differentially expressed genes. Descriptive statistics for each variable were determined. Continuous variables were expressed as the mean ± SD and compared using unpaired Student’s t-test, and categorical variables were expressed as percentages and numbers and were compared using the chi-squared test. Significant GO enrichment and pathways were selected by Fisher’s exact test, and p<0.05.


## 2.1. Study Participants

EAT samples were taken from 10 CAD patients who underwent coronary artery bypass graft surgery, in the Department of Heart Center, Beijing Chao-yang Hospital of Capital Medical University. Subjects were divided into two groups: HF group (n=5) and non-HF group (n=5). HF group included patients with Brain Natriuretic Peptide (BNP)>500ng/L and abnormal echocardiography finding (left ventricular end diastolic diameter [LVEDD]>50mm in female and >55mm in male and left ventricular ejection fraction [LVEF]<50%); non-HF group included patients with BNP<100 ng/L and normal views in echocardiography. The protocol was approved by the Ethics Committee of Beijing Chao-yang Hospital affiliated with Capital Medical University and written informed consent was obtained from participants before the study.


## 2.2. RNA Sequencing Procedure

Total RNA was extracted from the EAT and quantified using a NanoDrop ND-1000 instrument. 1-2μg total RNA was used to prepare the sequencing library in the following steps: (1) Total RNA is enriched by oligo (dT) magnetic beads (rRNA removed). (2) Using KAPA Stranded RNA-Seq Library Prep Kit (Illumina), RNA-seq library preparation incorporates dUTP into the second cDNA strand and makes the RNA-seq library strand-specific. (3) After completing, libraries were qualified with Agilent 2100 Bioanalyzer and quantified by absolute quantification qPCR method. (4) Sequence the libraries on the Illumina HiSeq 4000 instrument (we followed the methods of Wang et al. 2019 [7]).


## 2.3. Quantitative RT-PCR

qRT-PCR was used to measure selected lncRNA ENST00000610659 and UNC93B1 mRNA. Total RNA samples were extracted from the EAT samples using TRIzol (Invitrogen, Carlsbad, CA). The relative expression levels of mRNA and lncRNA were quantified using ViiA 7 Real-Time PCR System (Applied Biosystems, Foster City, USA) according to standard methods. lncRNA ENST00000610659: the forward primer was 5′ CGGCTTCAACAAGACGGTTC 3′, the reverse primer was 5′ AAGGCTCCACTCCGCACAAA 3′; UNC93B1 mRNA: the forward primer was 5′ GCTCACCTACGGCGTCTACC 3′, the reverse primer was 5′ CGGTAGGTCTCGT CGTAGTGC 3′.


## 2.4. Statistical Analysis

R package was used to calculate the FPKM value and differential expression for gene and transcript level and perform hierarchical clustering, GO enrichment, pathway analysis, scatter plots, and volcano plots with the differentially expressed genes. Descriptive statistics for each variable were determined. Continuous variables were expressed as the mean ± SD and compared using unpaired Student’s t-test, and categorical variables were expressed as percentages and numbers and were compared using the chi-squared test. Significant GO enrichment and pathways were selected by Fisher’s exact test, and p<0.05.


## 3. Results

### 3.1. Characteristics of Participants

The present study comprised 10 CAD patients (5 with HF and 5 without). The main clinical characteristics of the two groups are summarized in Table1. There were no significant differences in subject characteristics between the two groups; they were well balanced with regard to main clinical and laboratory characteristics. The CAD patients with HF had higher BNP level and LVEDD and lower LVEF.Table 1
Participants Characteristics.
CAD with HF CAD without HF P value (N=5) (N=5) Male, n(%) 2(40) 3(60) 0.999 Age, years 67.8±5.0 60.8±8.1 0.139 BMI, kg/m2 23.8±4.6 25.0±5.5 0.718 Diabetes, n(%) 2(40) 2(40) 1.000 Hypertension, n(%) 4(80) 5(100) 1.000 HbA1c, % 6.85±0.87 7.00±1.81 0.871 Total cholesterol, mmol/L 3.67±3.07 3.60±1.52 0.965 LDL-C, mmol/L 2.34±2.52 2.24±1.46 0.941 HDL-C, mmol/L 0.84±0.53 0.70±0.12 0.580 Triglyceride, mmol/L 0.89±0.38 1.86±0.89 0.055 Creatinine,μmol/L 88.2±25.2 76.8±16.8 0.424 Uric acid,μmol/L 363.2±82.4 357.0±69.3 0.901 BNP, pg/ml 1795.4±1053.3 76.4±22.6 0.006 LVEDD, mm 60.0±5.9 47.5±5.2 0.007 LVEF, % 44.2±10.2 62.0±4.8 0.008 Notes: BMI, body mass index; HbA1c, glycosylated hemoglobin; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; BNP, brain natriuretic peptide; LVEDD, left ventricular end diastolic diameter; LVEF, left ventricular ejection fraction.


### 3.2. RNA Sequencing Data

Using RNA sequencing, we detected 46760 transcripts (including 35673 protein-coding and 11087 non-protein-coding with linear structure and length>200bp) corresponding to 15554 genes in EAT in total. The top 30 highly expressed protein-coding and non-protein-coding transcripts are summarized in Table2.Table 2
The 30 highly expressed protein-coding and non protein-coding transcripts in EAT in CAD patients.
Track ID Gene Name Transcript Type Length(bp) Protein ENST00000165086.8 NPIPB4 Processed transcript 464 No ENST00000173785.4 KLF6 Processed transcript 925 No ENST00000214893.9 ERMP1 Processed transcript 4974 No ENST00000216463.8 TIMM9 Processed transcript 1075 No ENST00000216520.6 ERH Processed transcript 668 No ENST00000217890.10 ARSD Processed transcript 2160 No ENST00000230914.4 MRPS30 Processed transcript 4331 No ENST00000233699.8 POLE4 Processed transcript 602 No ENST00000237177.10 CASP8AP2 Processed transcript 6719 No ENST00000244070.7 PPP4R1L Processed transcript 1474 No ENST00000253320.8 TXLNGY Retained intron 7299 No ENST00000254109.9 CLUHP3 Processed transcript 1812 No ENST00000254299.8 GCH1 Processed transcript 2901 No ENST00000256692.5 PLEKHA8P1 Processed transcript 1839 No ENST00000263511.8 CROCCP3 Processed transcript 5368 No ENST00000264785.11 WDR1 Processed transcript 549 No ENST00000265450.5 TSPAN14 Processed transcript 2588 No ENST00000265870.7 SLC25A16 Processed transcript 2295 No ENST00000267869.8 GTF2A2 Processed transcript 518 No ENST00000267918.9 ANP32A Processed transcript 1084 No ENST00000273411.2 RPL39P5 Processed transcript 449 No ENST00000274820.7 RPL13P5 Processed transcript 349 No ENST00000276096.10 EBP Processed transcript 904 No ENST00000282943.9 ADGRA3 Processed transcript 3534 No ENST00000286777.6 RWDD2B Processed transcript 1625 No ENST00000294661.8 C1orf52 Processed transcript 3391 No ENST00000295549.8 LINC01116 lincRNA 1407 No ENST00000295748.7 AZI2 Processed transcript 3127 No ENST00000296031.4 CXCL2 Processed transcript 577 No ENST00000296325.9 LRPAP1 Processed transcript 1078 No ENST00000361624.2 MT-CO1 Protein coding 1542 513aa ENST00000362079.2 MT-CO3 Protein coding 784 261aa ENST00000361390.2 MT-ND1 Protein coding 956 318aa ENST00000361381.2 MT-ND4 Protein coding 1378 459aa ENST00000361453.3 MT-ND2 Protein coding 1042 347aa ENST00000361789.2 MT-CYB Protein coding 1141 380aa ENST00000361739.1 MT-CO2 Protein coding 684 227aa ENST00000361851.1 MT-ATP8 Protein coding 207 68aa ENST00000331825.11 FTL Protein coding 871 175aa ENST00000361335.1 MT-ND4L Protein coding 297 98aa ENST00000361567.2 MT-ND5 Protein coding 1812 603aa ENST00000361227.2 MT-ND3 Protein coding 346 115aa ENST00000361899.2 MT-ATP6 Protein coding 681 226aa ENST00000320868.9 HBA1 Protein coding 577 142aa ENST00000331523.6 EEF1A1 Protein coding 1923 462aa ENST00000327726.10 CFD Protein coding 1201 253aa ENST00000302754.5 JUNB Protein coding 1830 347aa ENST00000239938.4 EGR1 Protein coding 3137 543aa ENST00000356524.9 SAA1 Protein coding 518 122aa ENST00000633942.1 PLIN4 Protein coding 6484 1372aa ENST00000367029.5 G0S2 Protein coding 876 103aa ENST00000309311.7 EEF2 Protein coding 3158 858aa ENST00000251595.11 HBA2 Protein coding 576 142aa ENST00000335295.4 HBB Protein coding 628 147aa ENST00000256104.4 FABP4 Protein coding 941 132aa ENST00000451311.7 TMSB4X Protein coding 622 44aa ENST00000233143.6 TMSB10 Protein coding 461 44aa ENST00000330871.3 SOCS3 Protein coding 2734 225aa ENST00000336615.9 PNPLA2 Protein coding 2416 504aa ENST00000300055.10 PLIN1 Protein coding 2916 522aa Note: EAT, epicardial adipose tissue; CAD, coronary artery disease; Track ID, The transcript name in Ensembl database; Gene Name, The corresponding gene name of transcript; Transcript Type, the biotype of transcript; Protein, the residue number of protein.Scatter plot (Figure1) was performed to group lncRNA and mRNA and display the levels of lncRNA and mRNA in CAD patients with and without HF according to their expression levels among samples, and the results indicated that the lncRNA and mRNA expression profiles in CAD patients with HF were distinctly different from those in CAD patients without HF. 85 lncRNA and 866 mRNA whose levels changed significantly (p<0.05) were identified, including 45 upregulated and 40 downregulated lncRNA, as well as 404 upregulated and 462 downregulated mRNA.Figure 1
The scatter plot of the differential expressed (p<0.05) lncRNA (a) and mRNA (b) in patients with heart failure (HF) and without heart failure (non-HF) (red or green represented upregulated or downregulated genes, respectively); 85 lncRNA and 866 mRNA were identified, including 45 upregulated and 40 downregulated lncRNA, as well as 404 upregulated and 462 downregulated mRNA.
(a) (b)Using a 2-fold expression difference as a cutoff, a total of 30 differentially expressed lncRNAs (17 upregulated and 13 downregulated) (Figure2, Table 3) and 278 differentially expressed mRNAs (129 upregulated and 149 downregulated) were discriminated between CAD patients with and without HF (Figure 2). Among them, lncRNA ENST00000610659 was the top upregulated lncRNA with highest fold change and corresponded to UNC93B1 gene, which was proved to be related to HF and encoded UNC93B1 protein regulating toll-like receptor signaling. lncRNA ENST00000610659 and UNC93B1 mRNA were both significantly increased in HF patients in qRT-PCR validation (p=0.040 for lncRNA ENST00000610659 and p=0.019 for UNC93B1 mRNA) (Figure 3). lncRNA ENST00000610659 might be a potential biomarker for HF.Table 3
Differentially expressed lncRNA in EAT in CAD patients with HF compared with CAD patients without HF.
lncRNA Type Regulation Gene Name Fold Change P Value ENST00000610659 exon sense-overlapping Up UNC93B1 4.778 0.0118 ENST00000379935 natural antisense Up RBL2 3.711 0.0347 ENST00000603195 exon sense-overlapping Up ZSWIM8 3.329 0.0039 ENST00000439904 exon sense-overlapping Up SLC25A16 2.955 0.0179 ENST00000622120 intergenic Up LINC00963 2.952 0.0000 ENST00000514805 exon sense-overlapping Up TRIM52 2.901 0.0294 ENST00000492356 exon sense-overlapping Up RPS21 2.869 0.0461 ENST00000394225 exon sense-overlapping Up NDUFC1 2.840 0.0331 ENST00000548989 exon sense-overlapping Up CRIP2 2.247 0.0248 ENST00000465589 exon sense-overlapping Up OBSL1 2.229 0.0067 ENST00000398078 exon sense-overlapping Up PDXK 2.111 0.0157 ENST00000476113 exon sense-overlapping Up TCEA2 2.111 0.0223 ENST00000421064 natural antisense Up AP000347.2 2.099 0.0220 ENST00000470322 exon sense-overlapping Up ACTR1A 2.083 0.0304 ENST00000587762 intergenic Up AC020916.1 2.054 0.0443 ENST00000512955 exon sense-overlapping Up AMOTL2 2.052 0.0164 ENST00000508948 exon sense-overlapping Up ARRDC3 2.012 0.0289 ENST00000543826 exon sense-overlapping Down ADGRD1 0.161 0.0021 ENST00000467318 exon sense-overlapping Down DDX56 0.243 0.0126 ENST00000556961 exon sense-overlapping Down FBLN5 0.251 0.0033 ENST00000505923 exon sense-overlapping Down WDFY3 0.283 0.0221 ENST00000578571 exon sense-overlapping Down PTPRM 0.305 0.0360 ENST00000427261 intergenic Down RP11-640M9.2 0.331 0.0051 ENST00000319685 exon sense-overlapping Down TMTC1 0.370 0.0256 ENST00000493951 exon sense-overlapping Down TACC2 0.391 0.0341 ENST00000480603 exon sense-overlapping Down PPIA 0.414 0.0048 ENST00000345896 exon sense-overlapping Down CERS2 0.453 0.0391 ENST00000498053 exon sense-overlapping Down LRRFIP1 0.475 0.0350 ENST00000467178 exon sense-overlapping Down CIZ1 0.486 0.0448 ENST00000468975 exon sense-overlapping Down ARFGAP1 0.495 0.0128 Note: EAT, epicardial adipose tissue; CAD, coronary artery disease; HF, heart failure; lncRNA, The lncRNA name in Ensembl database; Type, the type of lncRNA; Regulation, the regulation expression of lncRNA; Gene Name, The corresponding gene name of lncRNA.Figure 2
The hierarchical clustering and volcano plot of the substantially differential expressed (P<0.05; fold change>2) lncRNA ((a1) and (a2)) and mRNA ((b1) and (b2)) in patients with and without heart failure (red or green represented upregulated or downregulated genes, respectively); 30 lncRNA and 278 mRNA were identified, including 17 upregulated and 13 downregulated lncRNA, as well as 129 upregulated and 149 downregulated mRNA.Figure 3
qRT-PCR analysis of expression of lncRNA ENST00000610659 (left) and UNC93B1 mRNA (right) in patients with heart failure (HF) and without heart failure (non-HF) (n=5 in each group),∗∗p<0.05.


### 3.3. GO and KEGG Pathway Analysis of Differentially Expressed mRNAs

The Gene Ontology (GO) project (Figure4) provided a controlled vocabulary to describe gene and gene product attributes in any organism. The ontology covered three domains: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). For upregulated genes, the top enriched GO terms in three domains were regulation of lymphocyte activation (GO:0051249) in BP, T cell receptor complex (GO:0042101) in CC, and phosphotyrosine residue binding (GO:0001784) in MF; for downregulated genes, those were oxidation reduction process (GO:0055114) in BP, extracellular space (GO:0005615) in CC, and oxidoreductase activity (GO:0016491) in MF, respectively.Figure 4
Enriched GO terms analysis for differentially expressed mRNAs. Top 10 significantly upregulated GO terms-Biological Process (a) and Molecular Function (c); all significantly upregulated GO terms-Cellular Component (b); top 10 significantly downregulated GO terms-Biological Process (d) and Molecular Function (f); all significantly downregulated GO terms-Cellular Component (e).Pathway analysis (Figure5) showed that, when comparing to controls, 17 pathways were significantly upregulated while 4 pathways were significantly downregulated. The top 3 significantly upregulated pathways were T cell receptor signaling pathway (hsa04660), primary immunodeficiency (hsa05340), and endometrial cancer (hsa05213). Meanwhile, the significantly downregulated pathways were drug metabolism cytochrome P450 (hsa00982), tyrosine metabolism (hsa00350), complement and coagulation cascades (hsa04610), and Jak-STAT signaling pathway (hsa04630).Figure 5
KEGG pathway analysis of differentially expressed mRNAs. Top 10 significantly upregulated pathways (a) and all significantly downregulated pathways (b).
(a) (b)


## 3.1. Characteristics of Participants

The present study comprised 10 CAD patients (5 with HF and 5 without). The main clinical characteristics of the two groups are summarized in Table1. There were no significant differences in subject characteristics between the two groups; they were well balanced with regard to main clinical and laboratory characteristics. The CAD patients with HF had higher BNP level and LVEDD and lower LVEF.Table 1
Participants Characteristics.
CAD with HF CAD without HF P value (N=5) (N=5) Male, n(%) 2(40) 3(60) 0.999 Age, years 67.8±5.0 60.8±8.1 0.139 BMI, kg/m2 23.8±4.6 25.0±5.5 0.718 Diabetes, n(%) 2(40) 2(40) 1.000 Hypertension, n(%) 4(80) 5(100) 1.000 HbA1c, % 6.85±0.87 7.00±1.81 0.871 Total cholesterol, mmol/L 3.67±3.07 3.60±1.52 0.965 LDL-C, mmol/L 2.34±2.52 2.24±1.46 0.941 HDL-C, mmol/L 0.84±0.53 0.70±0.12 0.580 Triglyceride, mmol/L 0.89±0.38 1.86±0.89 0.055 Creatinine,μmol/L 88.2±25.2 76.8±16.8 0.424 Uric acid,μmol/L 363.2±82.4 357.0±69.3 0.901 BNP, pg/ml 1795.4±1053.3 76.4±22.6 0.006 LVEDD, mm 60.0±5.9 47.5±5.2 0.007 LVEF, % 44.2±10.2 62.0±4.8 0.008 Notes: BMI, body mass index; HbA1c, glycosylated hemoglobin; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; BNP, brain natriuretic peptide; LVEDD, left ventricular end diastolic diameter; LVEF, left ventricular ejection fraction.


## 3.2. RNA Sequencing Data

Using RNA sequencing, we detected 46760 transcripts (including 35673 protein-coding and 11087 non-protein-coding with linear structure and length>200bp) corresponding to 15554 genes in EAT in total. The top 30 highly expressed protein-coding and non-protein-coding transcripts are summarized in Table2.Table 2
The 30 highly expressed protein-coding and non protein-coding transcripts in EAT in CAD patients.
Track ID Gene Name Transcript Type Length(bp) Protein ENST00000165086.8 NPIPB4 Processed transcript 464 No ENST00000173785.4 KLF6 Processed transcript 925 No ENST00000214893.9 ERMP1 Processed transcript 4974 No ENST00000216463.8 TIMM9 Processed transcript 1075 No ENST00000216520.6 ERH Processed transcript 668 No ENST00000217890.10 ARSD Processed transcript 2160 No ENST00000230914.4 MRPS30 Processed transcript 4331 No ENST00000233699.8 POLE4 Processed transcript 602 No ENST00000237177.10 CASP8AP2 Processed transcript 6719 No ENST00000244070.7 PPP4R1L Processed transcript 1474 No ENST00000253320.8 TXLNGY Retained intron 7299 No ENST00000254109.9 CLUHP3 Processed transcript 1812 No ENST00000254299.8 GCH1 Processed transcript 2901 No ENST00000256692.5 PLEKHA8P1 Processed transcript 1839 No ENST00000263511.8 CROCCP3 Processed transcript 5368 No ENST00000264785.11 WDR1 Processed transcript 549 No ENST00000265450.5 TSPAN14 Processed transcript 2588 No ENST00000265870.7 SLC25A16 Processed transcript 2295 No ENST00000267869.8 GTF2A2 Processed transcript 518 No ENST00000267918.9 ANP32A Processed transcript 1084 No ENST00000273411.2 RPL39P5 Processed transcript 449 No ENST00000274820.7 RPL13P5 Processed transcript 349 No ENST00000276096.10 EBP Processed transcript 904 No ENST00000282943.9 ADGRA3 Processed transcript 3534 No ENST00000286777.6 RWDD2B Processed transcript 1625 No ENST00000294661.8 C1orf52 Processed transcript 3391 No ENST00000295549.8 LINC01116 lincRNA 1407 No ENST00000295748.7 AZI2 Processed transcript 3127 No ENST00000296031.4 CXCL2 Processed transcript 577 No ENST00000296325.9 LRPAP1 Processed transcript 1078 No ENST00000361624.2 MT-CO1 Protein coding 1542 513aa ENST00000362079.2 MT-CO3 Protein coding 784 261aa ENST00000361390.2 MT-ND1 Protein coding 956 318aa ENST00000361381.2 MT-ND4 Protein coding 1378 459aa ENST00000361453.3 MT-ND2 Protein coding 1042 347aa ENST00000361789.2 MT-CYB Protein coding 1141 380aa ENST00000361739.1 MT-CO2 Protein coding 684 227aa ENST00000361851.1 MT-ATP8 Protein coding 207 68aa ENST00000331825.11 FTL Protein coding 871 175aa ENST00000361335.1 MT-ND4L Protein coding 297 98aa ENST00000361567.2 MT-ND5 Protein coding 1812 603aa ENST00000361227.2 MT-ND3 Protein coding 346 115aa ENST00000361899.2 MT-ATP6 Protein coding 681 226aa ENST00000320868.9 HBA1 Protein coding 577 142aa ENST00000331523.6 EEF1A1 Protein coding 1923 462aa ENST00000327726.10 CFD Protein coding 1201 253aa ENST00000302754.5 JUNB Protein coding 1830 347aa ENST00000239938.4 EGR1 Protein coding 3137 543aa ENST00000356524.9 SAA1 Protein coding 518 122aa ENST00000633942.1 PLIN4 Protein coding 6484 1372aa ENST00000367029.5 G0S2 Protein coding 876 103aa ENST00000309311.7 EEF2 Protein coding 3158 858aa ENST00000251595.11 HBA2 Protein coding 576 142aa ENST00000335295.4 HBB Protein coding 628 147aa ENST00000256104.4 FABP4 Protein coding 941 132aa ENST00000451311.7 TMSB4X Protein coding 622 44aa ENST00000233143.6 TMSB10 Protein coding 461 44aa ENST00000330871.3 SOCS3 Protein coding 2734 225aa ENST00000336615.9 PNPLA2 Protein coding 2416 504aa ENST00000300055.10 PLIN1 Protein coding 2916 522aa Note: EAT, epicardial adipose tissue; CAD, coronary artery disease; Track ID, The transcript name in Ensembl database; Gene Name, The corresponding gene name of transcript; Transcript Type, the biotype of transcript; Protein, the residue number of protein.Scatter plot (Figure1) was performed to group lncRNA and mRNA and display the levels of lncRNA and mRNA in CAD patients with and without HF according to their expression levels among samples, and the results indicated that the lncRNA and mRNA expression profiles in CAD patients with HF were distinctly different from those in CAD patients without HF. 85 lncRNA and 866 mRNA whose levels changed significantly (p<0.05) were identified, including 45 upregulated and 40 downregulated lncRNA, as well as 404 upregulated and 462 downregulated mRNA.Figure 1
The scatter plot of the differential expressed (p<0.05) lncRNA (a) and mRNA (b) in patients with heart failure (HF) and without heart failure (non-HF) (red or green represented upregulated or downregulated genes, respectively); 85 lncRNA and 866 mRNA were identified, including 45 upregulated and 40 downregulated lncRNA, as well as 404 upregulated and 462 downregulated mRNA.
(a) (b)Using a 2-fold expression difference as a cutoff, a total of 30 differentially expressed lncRNAs (17 upregulated and 13 downregulated) (Figure2, Table 3) and 278 differentially expressed mRNAs (129 upregulated and 149 downregulated) were discriminated between CAD patients with and without HF (Figure 2). Among them, lncRNA ENST00000610659 was the top upregulated lncRNA with highest fold change and corresponded to UNC93B1 gene, which was proved to be related to HF and encoded UNC93B1 protein regulating toll-like receptor signaling. lncRNA ENST00000610659 and UNC93B1 mRNA were both significantly increased in HF patients in qRT-PCR validation (p=0.040 for lncRNA ENST00000610659 and p=0.019 for UNC93B1 mRNA) (Figure 3). lncRNA ENST00000610659 might be a potential biomarker for HF.Table 3
Differentially expressed lncRNA in EAT in CAD patients with HF compared with CAD patients without HF.
lncRNA Type Regulation Gene Name Fold Change P Value ENST00000610659 exon sense-overlapping Up UNC93B1 4.778 0.0118 ENST00000379935 natural antisense Up RBL2 3.711 0.0347 ENST00000603195 exon sense-overlapping Up ZSWIM8 3.329 0.0039 ENST00000439904 exon sense-overlapping Up SLC25A16 2.955 0.0179 ENST00000622120 intergenic Up LINC00963 2.952 0.0000 ENST00000514805 exon sense-overlapping Up TRIM52 2.901 0.0294 ENST00000492356 exon sense-overlapping Up RPS21 2.869 0.0461 ENST00000394225 exon sense-overlapping Up NDUFC1 2.840 0.0331 ENST00000548989 exon sense-overlapping Up CRIP2 2.247 0.0248 ENST00000465589 exon sense-overlapping Up OBSL1 2.229 0.0067 ENST00000398078 exon sense-overlapping Up PDXK 2.111 0.0157 ENST00000476113 exon sense-overlapping Up TCEA2 2.111 0.0223 ENST00000421064 natural antisense Up AP000347.2 2.099 0.0220 ENST00000470322 exon sense-overlapping Up ACTR1A 2.083 0.0304 ENST00000587762 intergenic Up AC020916.1 2.054 0.0443 ENST00000512955 exon sense-overlapping Up AMOTL2 2.052 0.0164 ENST00000508948 exon sense-overlapping Up ARRDC3 2.012 0.0289 ENST00000543826 exon sense-overlapping Down ADGRD1 0.161 0.0021 ENST00000467318 exon sense-overlapping Down DDX56 0.243 0.0126 ENST00000556961 exon sense-overlapping Down FBLN5 0.251 0.0033 ENST00000505923 exon sense-overlapping Down WDFY3 0.283 0.0221 ENST00000578571 exon sense-overlapping Down PTPRM 0.305 0.0360 ENST00000427261 intergenic Down RP11-640M9.2 0.331 0.0051 ENST00000319685 exon sense-overlapping Down TMTC1 0.370 0.0256 ENST00000493951 exon sense-overlapping Down TACC2 0.391 0.0341 ENST00000480603 exon sense-overlapping Down PPIA 0.414 0.0048 ENST00000345896 exon sense-overlapping Down CERS2 0.453 0.0391 ENST00000498053 exon sense-overlapping Down LRRFIP1 0.475 0.0350 ENST00000467178 exon sense-overlapping Down CIZ1 0.486 0.0448 ENST00000468975 exon sense-overlapping Down ARFGAP1 0.495 0.0128 Note: EAT, epicardial adipose tissue; CAD, coronary artery disease; HF, heart failure; lncRNA, The lncRNA name in Ensembl database; Type, the type of lncRNA; Regulation, the regulation expression of lncRNA; Gene Name, The corresponding gene name of lncRNA.Figure 2
The hierarchical clustering and volcano plot of the substantially differential expressed (P<0.05; fold change>2) lncRNA ((a1) and (a2)) and mRNA ((b1) and (b2)) in patients with and without heart failure (red or green represented upregulated or downregulated genes, respectively); 30 lncRNA and 278 mRNA were identified, including 17 upregulated and 13 downregulated lncRNA, as well as 129 upregulated and 149 downregulated mRNA.Figure 3
qRT-PCR analysis of expression of lncRNA ENST00000610659 (left) and UNC93B1 mRNA (right) in patients with heart failure (HF) and without heart failure (non-HF) (n=5 in each group),∗∗p<0.05.


## 3.3. GO and KEGG Pathway Analysis of Differentially Expressed mRNAs

The Gene Ontology (GO) project (Figure4) provided a controlled vocabulary to describe gene and gene product attributes in any organism. The ontology covered three domains: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). For upregulated genes, the top enriched GO terms in three domains were regulation of lymphocyte activation (GO:0051249) in BP, T cell receptor complex (GO:0042101) in CC, and phosphotyrosine residue binding (GO:0001784) in MF; for downregulated genes, those were oxidation reduction process (GO:0055114) in BP, extracellular space (GO:0005615) in CC, and oxidoreductase activity (GO:0016491) in MF, respectively.Figure 4
Enriched GO terms analysis for differentially expressed mRNAs. Top 10 significantly upregulated GO terms-Biological Process (a) and Molecular Function (c); all significantly upregulated GO terms-Cellular Component (b); top 10 significantly downregulated GO terms-Biological Process (d) and Molecular Function (f); all significantly downregulated GO terms-Cellular Component (e).Pathway analysis (Figure5) showed that, when comparing to controls, 17 pathways were significantly upregulated while 4 pathways were significantly downregulated. The top 3 significantly upregulated pathways were T cell receptor signaling pathway (hsa04660), primary immunodeficiency (hsa05340), and endometrial cancer (hsa05213). Meanwhile, the significantly downregulated pathways were drug metabolism cytochrome P450 (hsa00982), tyrosine metabolism (hsa00350), complement and coagulation cascades (hsa04610), and Jak-STAT signaling pathway (hsa04630).Figure 5
KEGG pathway analysis of differentially expressed mRNAs. Top 10 significantly upregulated pathways (a) and all significantly downregulated pathways (b).
(a) (b)


## 4. Discussion

In the present study, we assessed the expression profiles of EAT lncRNA and mRNA in CAD patients with and without HF. The results showed a total of 35673 mRNA and 11087 lncRNA corresponding to 15554 genes in EAT were detected, and using a 2-fold expression difference as a cutoff, a total of 30 differentially expressed lncRNAs (17 upregulated and 13 downregulated) and 278 differentially expressed mRNAs (129 upregulated and 149 downregulated) were discriminated between CAD patients with and without HF.The differentially expressed lncRNAs corresponded to genes associated with inflammatory response or other factors which are involved in HF. UNC93B1, the top upregulated gene lncRNA corresponded to, encodes UNC93B1 protein that is involved in innate and adaptive immune response by regulating toll-like receptor signaling [8, 9] and is proved to be related to left ventricular diastolic function, heart failure morbidity, and mortality [10]. RBL2 is related to TGF-beta signaling [11]. LINC00963 encodes lncRNA963 playing an important role in chronic renal failure, which is closely associated with chronic diseases such as congestive heart failure [12]. TRIM52 encodes TRIM52 protein that positively regulates the nuclear factor-kappa B signaling pathway [13]. RPS21 (also known as HLDF) encodes HLDF protein that is involved in the mechanisms of blood pressure regulation [14]. AMOTL2 is required for migration and proliferation of endothelial cells during angiogenesis [15]. FBLN5 protein expression significantly decreases in human aneurysmatic aortas and may mediate cell-extracellular matrix interactions and elastic fibre assembly by inflammation [16]. TMTC1 is associated with the risk of incident HF [17]. LRRFIP1 is associated with adiposity and inflammation [18], and LRRFIP1 protein may regulate platelet function [19].EAT refers to the fat depot that exists on the surface of the myocardium and is contained entirely beneath the pericardium, which generates various inflammatory factors [20, 21]. Factors released from EAT have vasocrine and paracrine effects on the myocardium contributing to modulating properties on cardiac function [4, 22]. As our study showed, lncRNA can also be released from EAT and may be involved in HF; top upregulated lncRNA in HF corresponded to genes associated with inflammatory response and top upregulated enriched GO terms and KEGG pathway of mRNA were also about inflammatory cells activity.The present study showed the expression profiles of EAT lncRNA and mRNA in CAD patients and also characterized specific EAT lncRNA expression in HF. The EAT lncRNA may be important effector molecules for cardiovascular disease. Through the paracrine and vasocrine transmission, the EAT lncRNA may diffuse across the interstitial fluid or blood into the myocardium to be involved in the development of HF. Our data supplement lncRNA expression profiles in the EAT for lncRNA identifying in heart tissues and also provide possible biomarkers for HF, and further studies are needed to prove it.



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*Source: 3945475-2019-07-04.xml*