Abstract
Left atrial remodeling, characterized by enlargement and hypertrophy of
the left atrium and increased fibrosis, was accompanied by an increased
incidence of atrial fibrillation. While before morphological changes at
the early stage of hypertension, how overloaded hypertension influences
the transcriptomic profile of the left atrium remains unclear.
Therefore, RNA-sequencing was performed to define the RNA expressing
profiles of left atrium in spontaneously hypertensive rats (SHRs) and
normotensive Wistar-Kyoto (WKY) rats as a control group. We also
compared the changes in the RNA expression profiles in SHRs treated
with an angiotensin receptor blocker (ARB) and angiotensin
receptor-neprilysin inhibitor (ARNI) to assess the distinct effects on
the left atrium. In total, 1,558 differentially expressed genes were
found in the left atrium between WKY rats and SHRs. Bioinformatics
analysis showed that these mRNAs could regulate upstream pathways in
atrial remodeling through atrial fibrosis, inflammation, electrical
remodeling, and cardiac metabolism. The regulated transcripts detected
in the left atrial tissue in both the ARB-treated and ARNI-treated
groups were related to metabolism. In contrast to the ARB-treated
rates, the transcripts in ARNI-treated rats were mapped to the cyclic
guanosine monophosphate-protein kinase G signaling pathway.
Keywords: hypertension, left atrium, transcriptome, atrial fibrosis,
cardiac metabolism changes
1 Introduction
Hypertension is the most important controllable risk factor in
cardiovascular disease ([40]Mills et al., 2020). Persistent blood
pressure overload in hypertensive patients may induce left ventricle
hypertrophy, heart failure, enlargement of the left atrium, arrhythmia
(especially atrial fibrillation, AF), and cardiovascular death
([41]Kamioka et al., 2018; [42]Parker et al., 2020; [43]Kario and
Williams, 2021). Hypertension can rapidly induce atrial remodeling,
including left atrial hypertrophy, fibrosis, and an inflammatory
response ([44]Gumprecht et al., 2019; [45]Kim et al., 2019; [46]Wu et
al., 2021). Short-term and moderate stress overload pressure results in
ultrastructural changes in left atrial cells before structural
remodeling of the left ventricle ([47]Aguas et al., 1981). Hypertension
is the most significant population-attributable risk factor for AF that
is independent and potentially controllable ([48]Rahman et al., 2016).
However, the mechanism that allows hypertension to lead to AF remains
unclear. Therefore, identifying the transcriptional characteristics of
the left atrium in the early stage of hypertension may help to reveal
the atrial arrhythmia substrate induced by overloaded pressure.
Single-cell RNA-seq and bulk RNA-seq were used to delineate the
transcriptomic profiles of heart and aorta in hypertensive animal
models, systematically revealing the mechanisms of cardiac vascular
remodeling, including activation of fibroblasts and vascular smooth
muscle cells, dysregulation of interactions between macrophages and T
cells, which were linked to multiple signaling pathways, such as TGF-β
signaling pathway, cytokine, MAPK Signaling pathway ([49]Costa Ade and
Franco, 2015; [50]Li et al., 2016; [51]Xu et al., 2018; [52]Cheng et
al., 2021). Heart failure model, the most typical cardiac remodeling
model, revealed multiple mechanisms involved in cardiac remodeling by
transcriptome sequencing, including activation of myofibroblast
([53]Chothani et al., 2019; [54]Ramanujam et al., 2021) and immune
cells ([55]Martini et al., 2019; [56]Abplanalp et al., 2021),
mitochondrial dysfunction ([57]Sweet et al., 2018; [58]Zhuang et al.,
2022), proinflammatory signaling ([59]Costa Ade and Franco, 2015;
[60]Hahn et al., 2021) and TGF-β signaling pathway ([61]Stratton et
al., 2019). Although there have been many studies on RNA-seq in
exploring the mechanism in target organ remodeling in hypertension, the
transcriptomic characteristics of hypertension-induced atrial
remodeling are still lacking.
Given the close link between hypertension and AF, antihypertensive
drugs may potentially reduce the risk of AF, especially the
renin–angiotensin–aldosterone system inhibitor because of its
anti-myocardial remodeling effect ([62]Rahman et al., 2016; [63]Seccia
et al., 2017). Both angiotensin II type 1 receptor antagonists and
sacubitril/valsartan were demonstrated to attenuate adverse cardiac
remodeling by reversing cardiac fibroblasts and hypertrophy ([64]Kusaka
et al., 2015; [65]Garvin et al., 2021). Sacubitril/valsartan was proven
to be superior in reducing left ventricular hypertrophy because it
targets both the renin–angiotensin system and neprilysin, and thus this
therapy has an advantageous cardiovascular prognosis in patients with
hypertension compared with unitary treatment using olmesartan
([66]Schmieder et al., 2017). However, the specific mechanisms
associated with reverse cardiac remodeling under angiotensin receptor
blocker (ARB) or sacubitril/valsartan treatment remain unclear.
In the present study, we conducted RNA-seq to compare the
transcriptional differences in the left atrium in spontaneously
hypertensive rats (SHRs) and Wistar-Kyoto (WKY) rats ([67]Figure 1).
Furthermore, we characterized the biological functions of these
differentially expressed genes (DEGs) by bioinformatics analysis to
further understand the effects of hypertension on the left atrium. In
addition, transcriptome analysis was performed for the left atrium
tissues of SHRs fed saline, ARB, and sacubitril/valsartan.
Bioinformatics analysis was also performed to demonstrate the changes
in gene expression associated with the different treatments in order to
elucidate the mechanisms responsible for atrial remodeling under
treatment with ARB and sacubitril/valsartan. Furthermore, we compared
the transcriptional differences in rats under different treatments to
identify their distinct effects on the left atrium of ARB and
sacubitril/valsartan. This transcriptomic profile of left atrium
enables a more furtherly understand its mechanism of development of
left atrial transcriptional remodeling in early hypertension.
FIGURE 1.
[68]FIGURE 1
[69]Open in a new tab
An overall flow chart of the experimental design. WKY, Wistar-Kyoto;
SHR, spontaneously hypertensive rat; ARB, angiotensin receptor blocker;
ARNI, angiotensin receptor/neprilysin inhibitor; DEGs, differentially
expressed genes; IHC, immunohistochemistry.
2 Materials and methods
2.1 Experimental animals
Fourteen-week-old male SHRs (N = 9) and WKY rats (N = 3) were purchased
from Vital River Laboratory Animal Technology Co. Ltd. (Beijing,
China). The first group comprising the normotensive control (WKY, N =
3), was fed with saline (7.5 ml/kg/day) routinely and independently for
4 weeks. The SHRs were randomly divided into three groups: which were
fed with saline (7.5 ml/kg/day, N = 3), valsartan (30 mg/kg/day, N = 3)
and sacubitril/valsartan (60 mg/kg/day, N = 3) for 4 weeks. All animal
protocols were approved by the Animal Research Ethics Committee of
Chongqing Medical University.
2.2 Histological analysis
Immediately after anesthetizing the rats by intraperitoneal injection
of 20% ethyl carbamate, the left atrium was ablated through thoracotomy
and a portion was immersed in ice-cold isolation buffer, which was
rapidly frozen at −80°C to prepare for RNA-seq. Other parts of the
atrial tissue were fixed in 8% neutral formaldehyde and embedded in
paraffin. After dewaxing, the paraffin sections were stained with
hematoxylin and eosin (H&E) and Masson’s trichrome. The sections were
observed under a microscope at 200× lens ([70]Zhu et al., 2018).
H&E staining was conducted for histological determination of myocardial
injury by quantifying the ratio of the inflammatory cell infiltration
and necrosis area relative to the entire field as described in previous
studies ([71]Rezkalla et al., 1988), as follows: score 0 = 0 (no
myocardial damage observed); score 1 = 0%–25%; score 2 = 25%–50%; score
3 = 50%–75%; score 4 = 75%–100% ([72]Supplementary Table S1).
Similarly, the extent of myocardial fibrosis was quantified by Media
Cybernetics (United States) using the Masson’s trichrome. The ratio of
the collagen fiber area was calculated as the area with positive
staining for collagen relative to the entire visual field of the
section ([73]Takemoto et al., 1997). The area density was defined as
the integral optical density (IOD) divided by the pixel area. One
section was randomly selected from each rat in the four groups. Three
different fields in each section were selected for scoring according to
the criteria above.
2.3 RNA sequencing
Total RNA was extracted from the left atrium using TRIzol (Invitrogen,
Carlsbad, CA, United States) according to the manufacturer’s
instructions, and then quality controlled and quantified using a
NanoDrop and Agilent 2100 bioanalyzer (Thermo Fisher Scientific, MA,
United States), respectively. RNA-seq was conducted by a commercially
available service (service ID: F21FTSCCWLJ1374_MOUmpqzN, BGI-Shenzhen,
China). Briefly, after breaking the total RNA into short fragments,
mRNA was enriched using oligo (dT) magnetic beads, followed by cDNA
synthesis. Double-stranded cDNA was purified and enriched by PCR
amplification, after which the library products were sequenced using a
BGIseq-500. The sequencing data were filtered with SOAPnuke (v1.5.2).
The clean reads were mapped to the reference genome using HISAT2
(v2.0.4). Bowtie2 (v2.2.5) was applied to align the clean reads to the
reference coding gene set, and the expression levels of genes were then
calculated using RSEM (v1.2.12). All RNA-seq data has been uploaded to
the GEO database and can be queried through [74]GSE207283.
2.4 Data analysis
The raw counts were used to calculate the expression level of each
gene, and DESeq2 (v1.4.5) was employed to compare the expression levels
of genes between different samples. DEGs were filtered using the
following criteria: log2FC ≥ 1 and Q value ≤ 0.05. The DAVID online
analysis tool was used to perform functional cluster analysis for the
DEGs between the WKY and SHR groups. The biological functions of DEGs
were determined according to the significantly enriched Gene Ontology
(GO) terms ([75]http://www.geneontology.org/). Fisher’s exact and
multiple comparison tests were used to calculate the significance level
(p-value) and false positive rate (FDR) for each function, and the
significant functions of DEGs were screened using the threshold of p <
0.05. Pathway analysis was conducted based on the Kyoto Encyclopedia of
Genes and Genomes (KEGG; [76]http://www.genome.jp/kegg/) to explore the
significant pathways. Pathways with FDR ≤ 0.5 were defined as
significantly enriched. Gene set enrichment analysis (GSEA) was
performed using software (Subramanian et al., 2005) to quantify the
normalized enrichment score and FDR. Principal component analysis,
volcano plot and protein–protein interaction network analysis were
performed in BGI online system (Dr.Tom).
Key driver gene analysis (KDA) was carried out using BGI online system
(Dr.Tom). Specifically, KDA analysis takes as input a set of genes (G)
and a directed gene network (N), aiming at identifying the key
regulators of the gene set associated with a given network ([77]Rual et
al., 2005; [78]Tran et al., 2011). The size of h-layer neighborhood
(HLN) for each node was calculated. The value of HLN is equal to the
number of downstream nodes in the range h away from the specific nodes.
The nodes are selected as candidate drivers if their HLN values are
greater than
[MATH: μ- :MATH]
+ σ (μ), where μ is defined as the composite set of HLNS of all nodes,
[MATH: μ- :MATH]
is the mean value of μ, and σ(μ) is the standard deviation of μ. The
candidate drivers without any root node are global drivers, which is
defined as key driver genes, while the rest were local drivers. Nodes
with out-degree above
[MATH: d- :MATH]
+2σ (d) are global driver genes, where d is defined as the set of
out-degrees of all nodes,
[MATH: d- :MATH]
is the mean of d, and σ (d) as the standard deviation of d.
2.5 Immunohistochemistry analysis
Immunohistochemistry techniques were used to study the expression of
transforming growth factor-β (TGF-β). Specimens were incubated
overnight with primary antibodies at 4°C and then incubated with
horseradish peroxidase-labeled secondary antibodies at room temperature
for 1 h. DAB color developing solution was used for the chromogenic
reaction. The antibodies comprised the primary antibody anti-TGF-β1
rabbit antiserum (Servicebio, China) and secondary antibody horseradish
peroxidase-conjugated goat anti-rabbit immunoglobulin G (Servicebio,
China). Sections were then processed by microscopy (Nikon) and analyzed
with Aipathwell digital pathology image analysis software. The mean
density was defined as the integrated optical density divided by the
quantity of positive cells. Six different fields were selected for
quantitative analysis in each group.
3 Result
3.1 Expression profiling
PCA showed a closer distance on the scatter plot among groups than
between groups, thereby indicating that there were significant
differences between the atrial tissues from normotensive and
spontaneous hypertension rats ([79]Figure 2A). The transcriptional
differences in the four groups are shown in [80]Figure 2B and
[81]Supplementary Figure S1.
FIGURE 2.
[82]FIGURE 2
[83]Open in a new tab
An overview of the transcriptomic landscape profile in the rats’ left
atrium. (A) PCA analyse of transcriptome profiles between the four
groups: the abscissa and ordinate represent different principal
components and their contribution proportions. (B) Heatmap indicating
the atlas of dysregulated genes in the four groups: the abscissa
represents different groups of rats, the ordinate represents different
genes, red represents up-regulated genes, and blue represents
down-regulated genes. PCA, principal component analysis; WKY,
Wistar-Kyoto; SHR, spontaneously hypertensive rat; ARB, angiotensin
receptor blocker; ARNI, angiotensin receptor/neprilysin inhibitor;
FPKM, fragments per kilobase of exon per million reads mapped.
3.2 Morphology of the left atrium in different groups
H&E was used to evaluate histological cardiac damage and inflammation
([84]Supplementary Table S2). The results of H and E results indicated
no apparent necrosis or inflammatory infiltration in the left atrial
tissue under light microscopy in any group. Further quantitative
analysis detected no significant differences among the four groups
([85]Figure 3A). Masson’s trichrome was used to estimate the degree of
myocardial fibrosis ([86]Supplementary Tables S3, S4). The mean area
density values did not differ significantly in the SHR, ARB-treated,
and ARNI-treated groups compared with the WKY group ([87]Figure 3B).
The area ratio of collagen fibers was slightly elevated in SHRs
compared with WKY rats ([88]Figure 3C). These results suggest that the
hypertension overloading pressure did not lead to significant
histological changes manifested as inflammation and fibrosis in the
left atrium in the early development stage of hypertension development.
Early administration of inhibitors of the renin–angiotensin system did
not influence the histology of the left atrium.
FIGURE 3.
[89]FIGURE 3
[90]Open in a new tab
Morphology of the left atrium in different groups. (A) The left atriums
were harvested for H&E and Masson’s trichrome. (B) Quantitative
analyses of areal density (IOD/area) in Masson’s trichrome in four
groups. (C) Quantitative analyses of the area ratio of collagen fibers
in Masson’s trichrome in four groups. H&E, hematoxylin-eosin; WKY,
Wistar-Kyoto; SHR, spontaneously hypertensive rat; ARB, angiotensin
receptor blocker; ARNI, angiotensin receptor/neprilysin inhibitor; IOD,
integral optical density; ns, no significance. *: p ≤ 0.05.
3.3 Distinct transcriptomic changes in the atrial tissues of SHRs
The gene expression profiles for the left atrium tissue were compared
in the normotensive and spontaneously hypertensive groups to
characterize the effects of hypertension overload pressure on the
transcription levels ([91]Figures 4A–C). In total, 1,558 DEGs were
observed in the SHR group compared with the WKY group, where 873 genes
were upregulated and 685 were downregulated.
FIGURE 4.
[92]FIGURE 4
[93]Open in a new tab
GO and KEGG pathway analysis of DEGs between SHR and WKY rat left
atrium. (A) Histogram of the numbers of DEGs: the abscissa represents
the direction of gene change, the ordinate represents the number of
genes, red represents up-regulation, blue represents down-regulation;
(B) volcano Plot: X-axis represents the fold change of log2, Y-axis
represents −log10 (p-value), red represents up-regulated genes, blue
represents down-regulated genes, and gray represents insignificant
genes; (C) heatmap: X-axis represents different groups of rats, Y-axis
represents different genes, red represents up-regulated genes, blue
represents down-regulated genes. (D,E) Ten GO enriched terms in the
upregulated (D) and downregulated (E) DEGs, were analyzed for
biological process (BP), cellular component (CC), and molecular
function (MF). The X-axis shows different pathways, and the Y-axis
shows enrichment scores, BP in green, CC in orange, and MF in blue.
(F,G) 10 KEGG pathways were identified in the downregulated (F) and
upregulated (G) DEGs. The X-axis represents the enrichment ratio, the
Y-axis represents the different pathways enriched, the size of the dots
represents the number of genes enriched to the pathway, and the change
of color from blue to red represents the change of p value from small
to large. GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and
Genomes. TGF-beta, transforming growth factor beta; MAPK,
mitogen-activated protein kinase; PPAR, peroxisome
proliferator-activated receptor; TCA, tricarboxylic acid; HIF-1,
hypoxia-inducible factor-1.
GO assignments were used to classify the genes associated with the
transformation of the left atrium in the SHRs. As shown in [94]Figures
4D,E, compared with the WKY rats, the upregulated transcripts in SHRs
were enriched in 1) biological process (BP): calcium ion transmembrane
transport, noncanonical Wnt signaling pathway, cell adhesion and SMAD
protein signal transduction; 2) molecular function (MF): calcium
channel activity, Wnt-protein binding, voltage-gated ion channel
activity, and I-SMAD binding; and 3) cellular component (CC):
voltage-gated calcium channel complex, cell junction, and
collagen-containing extracellular matrix. The downregulated transcripts
were enriched in: 1) BP: fatty acid metabolic process, lipid metabolic
process, oxidation–reduction process, and intracellular distribution of
mitochondria; 2) MF: fatty-acyl-CoA binding, calmodulin binding, and
extracellular matrix structural constituent; and 3) CC: mitochondrion,
extracellular matrix, cell junction, and mitochondrial membrane.
We performed pathway enrichment analysis with KEGG to further
characterize the DEGs. As shown in [95]Figures 4F,G, in the left atrial
tissues of these hypertensive rats, compared with the WKY group, the
upregulated transcripts were related to the TGF-β signaling pathway,
calcium signaling pathway, MAPK signaling pathway, and NF-kappa B
signaling pathway, whereas the downregulated transcript were related to
the PPAR signaling pathway, fatty acid metabolism, carbon metabolism,
PI3K-Akt signaling pathway, and apelin signaling pathway.
3.4 Network analysis of DEGs and enriched pathways between the WKY and SHR
groups
Based on the protein–protein interaction network analysis of all the
dysregulated genes (1,558 genes) in SHRs and the WKY rats, we selected
15 key driver genes in the prominent regulatory position ([96]Figures
5A,B). We performed KEGG pathway analysis for further characterize the
key genes. The interaction network obtained between the significantly
enriched KEGG pathways and the genes determined by KDA is shown in
[97]Figure 5C. The key genes were enriched in pathways including fatty
acid metabolism, and PPAR signaling pathway.
FIGURE 5.
[98]FIGURE 5
[99]Open in a new tab
Network analysis of DEGs and enriched pathways between THE WKY and SHR
groups. (A) KDA analysis identified 15 key driver genes in the DEGs
between SHR and WKY rat atria: Key driver genes are shown in red,
initial genes are shown in blue, and extended genes are shown in gray.
(B) Heatmap of the 15 key driver genes. (C) Network analysis between
key driver genes and enriched KEGG pathways: Dots represent genes,
squares represent KEGG pathways, and lines between genes and squares
indicate that the gene can be enriched into the corresponding pathway.
(D) The top 20 hub genes were selected by the cytoHubba app in
Cytoscape 3.8.2 software. The node color changed gradually from yellow
to red in ascending order according to the score of hub genes. (E) GO
and enrichment network of the top 20 hub genes between SHR and WKY rat
atrium. (F) The enrichment network of top 20 hub genes was identified
in the rat atrium. Nodes represent functions enriched for an annotated
ontology term and node size indicates the number of genes that fall
into that term. KDA, key driver gene analysis; WKY, Wistar-Kyoto; SHR,
spontaneously hypertensive rat; KEGG, kyoto encyclopedia of genes and
genomes; BP, biological process; CC, cellular component; MF, molecular
function; MAPK, mitogen-activated protein kinase.
The CytoHubba app in Cytoscape 3.8.2 software was used to select the
hub genes among the 1558 dysregulated genes in the left atrium in
hypertensive rats. Twenty hub genes were selected, including Hadha,
Hadhb, Eci2, and Acadl ([100]Figure 5D). As shown in [101]Figure 5E, GO
analyses were conducted and they identified, GO-BP terms: fatty acid
metabolic process, fatty acid beta-oxidation and lipid metabolic
process; GO-MF terms: fatty-acyl-CoA binding and enoyl-CoA hydratase
activity; GO-CC terms: mitochondrion, peroxisome and mitochondrial
matrix. In addition, the top 20 GO and KEGG pathways of the 30 hub
genes were identified by Metascape ([102]Figure 5F) included the fatty
acid catabolic process, fatty acid degradation and PPAR signaling
pathway.
3.5 Sacubitril/valsartan and ARB modulate the transcriptomes in atrial tissue
with spontaneous hypertension
Gene set enrichment analysis (GSEA) was performed to assess the
concentration of genes regulated by sacubitril/valsartan and ARB in
different gene sets in the KEGG pathways. As shown in [103]Figure 6A,
after the 4 weeks of treatment with ARB, the atrial tissues were mainly
regulated in ribosome, proteasome, oxidative phosphorylation, and
biosynthesis of amino acids. In the sacubitril/valsartan-treated group,
the changes were mainly in the citrate cycle, AMPK signaling pathway,
fatty acid elongation, propanoate metabolism, carbon metabolism, and
PPAR signaling pathway ([104]Figure 6B). We note that the pathways
enriched in the ARB and ARNI groups were both involved in
cardiometabolic pathways, thereby suggesting that the two drugs may
contribute to repairing damage to the left atrium through this common
mechanism.
FIGURE 6.
[105]FIGURE 6
[106]Open in a new tab
GSEA between the ARB-treated group and the SHR (A),
sacubitril/valsartan-treated group and the SHR (B), and the ARB-treated
and sacubitril/valsartan-treated groups (C) TCA, tricarboxylic acid;
AMPK, AMP-activated protein kinase; PPAR, peroxisome
proliferator-activated receptor; ECM, extracellular matrix; MAPK,
mitogen-activated protein kinase.
Furthermore, GSEA was performed to compare the different mRNAs between
the ARB- and sacubitril/valsartan-treated groups to identify the
differences in atrial remodeling reversal mechanisms. As shown in
[107]Figure 6C, compared with ARB, mRNAs regulated in the
sacubitril/valsartan-treated group were mainly enriched in the PPAR
signaling pathway, ECM-receptor interaction, cGMP-PKG signaling
pathway, and MAPK signaling pathway.
3.6 Immunohistochemistry analysis
The TGF-β-positive cells manifested as brown and the nucleus was
stained blue by immunohistochemical staining ([108]Supplementary Table
S5). As shown in [109]Figure 7, the expression level of TGF-β was
higher in the left atrium of SHRs compared with normotensive rats,
which was consistent with the changes in the gene expression levels.
FIGURE 7.
[110]FIGURE 7
[111]Open in a new tab
(A) Immunohistochemical analysis of the left atrium in different
groups: the TGF-beta-positive cells manifested as buffy, and the
nucleus was stained blue. (B) Expression levels of TGF beta in SHR and
WKY: the X-axis represents different groups, and the Y-axis represents
FPKM. (C) Mean density of Immunofluorescence staining: the X-axis
represents different groups, and the Y-axis represents the mean
density. WKY, Wistar-Kyoto; SHR, spontaneously hypertensive rat; FPKM,
fragments per kilobase of exon per million reads mapped.
4 Discussion
4.1 Influence of hypertension on the left atrium
Complex changes in the atrium increase the susceptibility and
progression to AF, and stimulate AF-associated diseases, and thus they
are defined as “atrial cardiomyopathy” according to a recent consensus
study ([112]January et al., 2019). The multidirectional association
between elevated blood pressure and AF has not been elucidated, and the
main theories currently focus on complex associations such as
structural remodeling, electrophysiology, neuroendocrine, inflammation,
and autonomic mechanisms ([113]Dzeshka et al., 2017). Transcriptome and
proteome analyses were used to comprehensively understand the changes
caused by hypertension and to further study the AF substrate in
hypertension ([114]Alvarez-Franco et al., 2021). In a previous study,
Julio et al. observed 15 altered proteins in the early stage of left
ventricular hypertrophy in SHRs compared with normotensive rats by
proteomic analysis, and they mediated hypertension-induced cardiac
hypertrophy ([115]Gallego-Delgado et al., 2006). In this study, we
first determined the transcriptomic features of the left atrium in
SHRs. GO, GSEA, and KEGG pathway analysis suggested that the regulated
transcripts were attributed to multiple functions, such as TGF-beta
signaling pathway, SMAD signaling pathway, fatty acid metabolism,
oxidative phosphorylation, the citrate cycle, propanoate metabolism,
NF-κB pathway, MAPK, and calcium signaling pathway, which could be
associated with atrial fibrosis, inflammation, electrical remodeling,
and metabolic changes. According to the KDA analysis of DEGs and
further relation network with KEGG pathway analysis, most key driver
genes were involved in cardiac metabolism, such as fatty acid
metabolism, carbon metabolism, propanoate metabolism and PPAR signaling
pathway, suggesting these pathways may play pivotal roles in the
pathophysiology of atrial fibrillation in hypertension. Meanwhile, we
noticed that Hadha, Hadhb, and Eci2, the top three of the hub genes,
were both related to fatty acid metabolism. Cardiac remodeling is
characterized by metabolic remodeling, especially down-regulation of
fatty acid oxidation, which can further aggravate pathological
remodeling ([116]Kolwicz et al., 2013; [117]Mouton et al., 2020). Hadha
and Hadhb play a key role in fatty acid oxidation and cardiolipin
remodeling, and are involved in cardiac remodeling and systolic
dysfunction in heart failure ([118]Le et al., 2014; [119]Miklas et al.,
2019; [120]Dagher et al., 2021). The expression of PPAR and medium
chain Acyl CoA dehydrogenase was decreased in 4-month-old SHRs
([121]Purushothaman et al., 2011). PPAR activation and increased fatty
acid metabolism were observed in SHRs after 4 months treatment of
medium-chain triglycerides, accompanied by reduction of oxidative
stress and improvement of myocardial hypertrophy ([122]Saifudeen et
al., 2017). Our results proved that genes involved in fatty acid
metabolism were significantly dysregulated before the onset of heart
failure, even before cardiac structural changes, suggesting that fatty
acid metabolim may be involved in the structural remodeling of left
atrium at the early stage of hypertension.
The following contents will describe the transcriptional
characteristics of hypertensive left atrial in terms of atrial
fibrosis, cardiac metabolism, cardiac inflammation, and electrical
remodeling.
4.1.1 Fibroblast proliferation and atrial fibrosis
In the present study, genes involved in the TGF-β signaling pathway
were significantly dysregulated. The TGF-β1 pathway is involved in the
development and propagation of AF. The TGF-β1 pathway is linked to
atrial fibrosis, and the most common mechanisms involved include the
SMAD signaling pathway, the endothelial to mesenchymal transition, and
the CD44 signaling pathway ([123]Babapoor-Farrokhran et al., 2021). A
recent study showed that serum levels of TGF-β1 gradually increased in
the following four groups: control group, hypertensive patients,
paroxysmal AF secondary to hypertension, and chronic AF secondary to
hypertension, thereby demonstrating that TGF-β1 may contribute to the
initiation and sustainment of AF in hypertensive patients via atrial
remodeling and fibrosis ([124]Lin et al., 2015). The upregulated
expression of TGF-β in the atrium results in increased collagen I and
III fibrosis, and pirfenidone significantly reduces arrhythmogenic
atrial remodeling by suppressing TGF-β1 expression ([125]Lee et al.,
2006; [126]Kong et al., 2014). In summary, hypertension may lead to
left atrial fibrosis and structural remodeling, and further increase
the susceptibility to AF by upregulating TGF-β1.
4.1.2 Cardiac metabolic remodeling
The abnormal metabolic milieu is considered a critical amplifier in
cardiac injury during hypertension and it plays an essential role in AF
([127]Pfeffer et al., 2019). In a previous study of the early stage of
hypertension development, profound changes in metabolites were observed
before the impairment of cardiac function, which comprised increased
glucose uptake and oxidation, an increased substrate supply, and
elevated pyruvate and fatty acyl groups ([128]Li et al., 2019).
Abnormal myocardial fatty acid metabolism was shown to induce the
incidence and persistence of AF ([129]Shingu et al., 2020). Changes in
fatty acid metabolism, oxidative phosphorylation, and the citrate cycle
were also observed in our study. Mitochondrial dysfunction is a
significant feature of the heart in hypertensive patients and it leads
to the transformation of metabolism to glycolysis ([130]Zhang et al.,
2015). Nevertheless, insulin resistance reduces the utilization of
glucose, which further aggravates myocardial injury ([131]Mouton et
al., 2020). Similarly, in our study, we observed significant changes in
genes associated with mitochondria and insulin resistance.
4.1.3 Oxidative stress and inflammation
Both NF-κB and MAPK can be activated by toll-like receptors to increase
the expression of cytokines such as IL-6 and TNF, which induce
inflammation, which participates in atrial remodeling ([132]Kawano et
al., 2005; [133]Kawai and Akira, 2010). NF-κB may be involved in the
oxidative stress process through the phosphatidylinositol
3-kinase/protein kinase B pathway, which is a common signal that
cross-links with nuclear factor E2-related factor 2 (Nrf2)
([134]Jayasooriya et al., 2014). Inhibition of NF-κB has been shown to
activate Nrf2, which protects the cardiovascular system from
pathological cardiac remodeling by reducing oxidative stress responses
([135]Zhou et al., 2014). We found that genes associated with the NF-κB
pathway were significantly dysregulated in the left atrium of SHRs,
thereby suggesting that overloaded hypertension may induce atrial
remodeling through NF-κB and further increase the incidence of AF.
Hypertension-induced atrial remodeling activates hypoxia-inducible
factor-1(HIF-1), which further activates monocyte libraries and
proinflammatory cytokines ([136]Rius et al., 2008; [137]Fujisaka et
al., 2013).
4.1.4 Ion channel, cell junction, and electrical remodeling
High hydrostatic pressure has been shown to affect the expression of
potassium and calcium channels in the left auricle in SHRs and lead to
electrical remodeling of the left atrium ([138]Li et al., 2020).
Similarly, we found that genes related to ion channels were
significantly dysregulated in the left atrium of SHRs. The mechanisms
associated with AF include triggers that generate ectopic activity or
modifiers of substrate promoted re-entry ([139]Thomas and Abhayaratna,
2017). Electrical remodeling plays a crucial role in AF and its
molecular mechanism is based on ion channel expression and/or
phosphorylation ([140]Schotten et al., 2011). In particular, electrical
reconstruction promoted ion channel (decreased L-type Ca2+ current,
rectifier background K+ current) changes to result in a shortened
atrial effective refractory period, prolonged excitability interval,
and facilitated re-entry ([141]Wiedmann et al., 2018; [142]Dridi et
al., 2020).
4.2 Potential mechanisms of reversing atrial remodeling by ARB/ARNI
In the present study, we observed a common metabolism-related gene
change in the ARB-treated and ARNI-treated groups. Renin–angiotensin
system blockers can potentially improve cardiometabolic parameters,
such as insulin resistance, glucose metabolism, and adipose tissue
dysfunction ([143]Jahandideh and Wu, 2020). Interestingly, these
regulated pathways involved in cardiac metabolism, especially regulated
by ARNI, such as fatty acid elongation and propanoate metabolism, were
also dysregulated in the SHR. Therefore, we speculate that ARNI and ARB
may reverse atrial remodeling by uniformly alleviating cardiometabolic
dysfunction. Previous studies have shown that ARNI can improve cardiac
function in patients with heart failure by improving ventricular
fibrosis, reducing cardiac hypertrophy and cardiac inflammation
([144]Lara et al., 2012; [145]Pascual-Figal et al., 2021), while
cardiac metabolism was rarely mentioned. The main source of energy
consumed by healthy myocardium is fatty acid oxidation, whereas a shift
from free fatty acid to glucose utilization is observed in failing
heart ([146]Li et al., 2019). Our results provide a new insight for the
application of ARNI in the early prevention of heart failure caused by
overloaded pressure.
Given the superior prognosis when treating cardiovascular disease with
sacubitril/valsartan compared with ARB, we compared the differences in
the left atrium under treatment with these drugs. The results showed
that the regulated mRNAs were enriched in ECM-receptor interactions and
the cGMP-PKG signaling pathway. Notably, genes involved in cGMP-PKG
signaling pathway were up-regulated in SHR, but the expression changes
of these genes were reversed in the sacubitril/valsartan treated rats.
As an inhibitor of endopeptidase enzyme neprilysin,
sacubitril/valsartan reduces natriuretic peptides (NPs) degradation and
lead to enhanced NP action ([147]Ishii et al., 2017). NPs act as key
negative regulators during cardiac hypertrophy and remodeling by
activating cGMP-dependent PKG ([148]Takimoto, 2012; [149]Kong and
Blanton, 2013). A recent study has shown that sacubitril/valsartan can
significantly improve stress-induced myocardial fibrosis by regulating
atrial natriuretic peptide-induced PKG signaling in cardiac fibroblasts
and inhibiting the expression of fibroblast transformation-related
processes, which are not generated by treatment with the molar
equivalent of valsartan (Burke et al., 2019), and our results are
consistent with these changes. Besides, sacubitril valsartan was shown
to significantly increase circulating cGMP levels in beagles compared
with valsartan ([150]Mochel et al., 2019). Therefore, we hypothesized
that sacubitril/valsartan may reverse hypertension-induced left atrial
remodeling through cGMP-PKG signaling pathway, which need further in
vivo and in vitro experiments to confirm.
5 Conclusion
In this study, we employed transcriptomic analysis using RNA-seq to
determine the changes in the gene expression levels in the left atrium
in SHRs compared with WKY rats, and SHRs under treatment with
anti-hypertension drugs. Intensive bioinformatics analysis identified
atrial fibrosis, inflammation, electrical remodeling, and metabolism
changes as critical BPs, and essential pathways were also identified
under sacubitril/valsartan and ARB interventions. Meanwhile, we
emphasize the importance of cardiac metabolic remodeling and Rac1 in
inducing and reversing left atrial remodeling at the early stage of
hypertension. Overall, the results obtained in this study might provide
insights into the underlying mechanisms associated with the AF
substrate in spontaneous hypertension and potential treatment targets
for preventing the incidence of AF in hypertension.
Data availability statement
The datasets presented in this study can be found in online
repositories. The names of the repository/repositories and accession
number(s) can be found below: [151]https://www.ncbi.nlm.nih.gov;
[152]GSE207283.
Ethics statement
The animal study was reviewed and approved by the Animal Research
Ethics Committee of Chongqing Medical University.
Author contributions
QF, JW, and JW agreed to be accountable for all aspects of the work in
ensuring that questions related to the accuracy or integrity of any
part of the work are appropriately investigated and resolved and
drafted the manuscript. XY and JW made substantial contributions to the
conception and design. XL and YW made substantial contributions to the
acquisition of data. JD revised the manuscript critically and gave
final approval of the version to be published. All authors read and
approved the final manuscript.
Funding
This work was supported by grants from the National Natural Science
Foundation of China (NSFC) (81900631, 82270281), China Postdoctoral
Science Foundation Grant (2019M653354), Natural Science Foundation
Postdoctoral Program of Chongqing Science and Technology Bureau
(cstc2019jcyj-bsh0012), Natural Science Foundation of Chongqing Science
and Technology Commission (cstc2020jcyj-msxmX0210), and Chongqing
medical scientific research project (Joint project of Chongqing Health
Commission and Science and Technology Bureau) (2020FYYX047), Future
Medicine Youth Innovation Team Development Support Program of Chongqing
Medical University (W0133), and Kuanren Talents Program of the Second
Affiliated Hospital of Chongqing Medical University.
Conflict of interest
The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or claim
that may be made by its manufacturer, is not guaranteed or endorsed by
the publisher.
Supplementary material
The Supplementary Material for this article can be found online at:
[153]https://www.frontiersin.org/articles/10.3389/fphar.2022.989636/ful
l#supplementary-material
[154]Click here for additional data file.^ (23.9MB, docx)
References