In-depth analysis of retinal RNA transcriptome sequencing in a rat model of hypertensive retinopathy

Hypertensive retinopathy is a microvascular complication caused by systemic hypertension and can lead to severe visual impairment. At present, the molecular mechanisms of this disease remain incompletely understood, particularly the global expression profiles and regulatory networks of non-coding RNA (ncRNA). This study aims to comprehensively analyze the genome-wide differential expression profiles of messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA) in retinal tissues from a spontaneously hypertensive rat (SHR) model of hypertensive retinopathy, and to observe transcriptomic changes after treatment with the calcium channel blocker lacidipine, thereby revealing their potential roles in disease pathogenesis and identifying possible therapeutic targets.

SHRs were used as a model of hypertensive retinopathy, and normotensive Wistar-Kyoto (WKY) rats were used as controls. Rats were divided into 3 groups: A control group (WKY), a model group (SHR), and a treatment group (SHR+lacidipine). Rats in the treatment group received lacidipine by gavage at 0.5 mg/(kg·d) for 8 consecutive weeks. At the end of the experiment, retinal tissues were collected for histopathological examination by hematoxylin and eosin (HE) staining and for high-throughput sequencing. The lncRNA library was used to analyze mRNA, lncRNA, and circRNA expression profiles, and the small RNA (sRNA) library was used to analyze miRNA expression profiles. Differential expression analysis was performed using DESeq2. The screening criteria were |log₂ fold change (FC)|≥1 and false discovery rate (FDR) significance criteria for mRNAs and lncRNAs, and |log₂FC|≥1 and P<0.05 for miRNAs and circRNAs as exploratory candidates. Differentially expressed RNAs were subjected to Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Competing endogenous RNA (ceRNA) regulatory networks involving lncRNA/circRNA-miRNA-mRNA were constructed through target prediction and co‑expression analysis. Ten mRNAs whose expression changes were reversed after treatment were selected for validation by real-time reverse transcription polymerase chain reaction (real-time RT-PCR; n=6 per group). Comparisons among multiple groups were performed using one-way analysis of variance and post hoc multiple-comparison tests.

1) Verification of the animal model: Blood pressure was significantly higher in the model group than in the control group. The model group exhibited edema of the retinal nerve fiber layer, dilation of vascular lumens, and increased retinal thickness. Lacidipine treatment reduced blood pressure and alleviated these pathological changes. 2) Differential expression of mRNAs: Compared with the control group, 870 mRNAs were significantly downregulated and 1 018 mRNAs were significantly upregulated in the model group. Compared with the model group, 2 644 mRNAs were significantly downregulated and 186 mRNAs were significantly upregulated in the treatment group. GO analysis showed that upregulated mRNAs in the model group were enriched in immune-inflammatory processes, such as leukocyte activation, chemotaxis, defense response, and regulation of tumor necrosis factor (TNF) production, whereas downregulated mRNAs were enriched in G protein-coupled receptor (GPCR) signaling, glycoprotein synthesis, ion channel activity, and related processes. KEGG analysis revealed that upregulated mRNAs in the model group were enriched in interleukin-17 (IL-17), TNF, oxidative stress, and lipid inflammatory mediator metabolic pathways, whereas downregulated mRNAs were enriched in phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) signaling, vascular smooth muscle contraction, extracellular matrix (ECM)-receptor interaction, and related pathways. In the treatment group, the downregulated mRNAs were mainly enriched in pathways related to immune-inflammatory activation, such as mast cell degranulation and leukocyte degranulation. 3) Treatment-reversed mRNAs: A total of 67 genes that were upregulated in the model group and downregulated after treatment were identified; these genes were mainly enriched in endoplasmic reticulum stress-associated apoptotic signaling, mitophagy, ubiquitin ligase activity, and related processes. In addition, 54 genes that were downregulated in the model group and upregulated after treatment were identified; these genes were mainly enriched in amino acid transport, integrin complex, focal adhesion, glutamate transport activity, and related processes. Real-time RT-PCR validated the expression changes of Med22, Rmt1, Sytl3, Itgb7, and Slc1a3 which were decreased in the model group and increased after treatment, as well as Rnf183, Lrrc29, Lat2, Hist1h4m, and Dpm3, which were increased in the model group and decreased after treatment. These findings were consistent with the sequencing results. 4) Differential expression of miRNAs: Compared with the control group, 30 miRNAs were downregulated and 26 miRNAs were upregulated in the model group. Compared with the model group, 14 miRNAs were downregulated and 53 miRNAs were upregulated in the treatment group. Treatment-reversed miRNAs were identified: Rno-miR-1-3p, novel_miR_1203, and novel_miR_1417 were upregulated in the model group and downregulated after treatment, whereas novel_miR_107 and novel_miR_905 were downregulated in the model group and upregulated after treatment. Their target genes were enriched in regulation of retinal cone/rod cell differentiation, ECM remodeling, the Notch pathway, fatty acid synthesis, and related processes. 5) Differential expression of lncRNAs: Compared with the control group, 786 lncRNAs were downregulated and 764 lncRNAs were upregulated in the model group. Compared with the model group, 217 lncRNAs were downregulated and 230 lncRNAs were upregulated in the treatment group. A total of 55 lncRNAs that were upregulated in the model group and downregulated after treatment, and 76 lncRNAs that were downregulated in the model group and upregulated after treatment, were identified. Their target genes were enriched in immune regulation, wound healing, vascular remodeling, retinol metabolism related to rod-mediated scotopic vision, glutamatergic neuron differentiation, the forkhead box O (FoxO) pathway, retinoic acid-inducible gene I (RIG-I)-like receptor signaling, and related processes. 6) Differential expression of circRNAs: Compared with the control group, 45 circRNAs were downregulated and 47 circRNAs were upregulated in the model group. Compared with the model group, 25 circRNAs were downregulated and 22 circRNAs were upregulated in the treatment group. Eleven circRNAs that were downregulated in the model group and upregulated after treatment, and 10 circRNAs that were upregulated in the model group and downregulated after treatment, were identified. Their host genes were enriched in regulation of synaptic neural signaling, second messenger transmission, calcium signaling, and vascular endothelial growth factor (VEGF) signaling pathways. 7) Construction of ceRNA networks: Based on expression patterns and target prediction, multiple lncRNA/circRNA-miRNA-mRNA regulatory networks were constructed. For example, the networks composed of rno_circ_Rims2_10, rno-miR-1-3p, and related mRNAs, such as Mmp14 and Fasn, as well as the novel_miR_1417 related network, may be involved in retinal stress responses, inflammatory regulation, and neurovascular remodeling.

This study is the first to integrate and analyze retinal transcriptomic profiles of mRNAs, miRNAs, lncRNAs, and circRNAs in an SHR model of hypertensive retinopathy, and it reveals RNA expression changes associated with lacidipine treatment. The results suggest that immune-inflammatory activation, neurovascular dysfunction, and ncRNA-mediated ceRNA regulatory networks may participate in the pathogenesis of hypertensive retinopathy. The identified differentially expressed molecules and predicted regulatory axes provide a candidate molecular basis for further mechanistic validation and screening of potential therapeutic targets.