Identification of the key genes and long non‑coding RNAs in ankylosing spondylitis using RNA sequencing

The Mechanism of "Treating Different Diseases with the Same Treatment" by Qiangji Jianpi Decoction in Ankylosing Spondylitis Combined with Inflammatory Bowel Disease: A Comprehensive Analysis of Multiple Methods

Background

Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are prevalent autoimmune disorders that often co-occur, posing significant treatment challenges. This investigation adopts a multidisciplinary strategy, integrating bioinformatics, network pharmacology, molecular docking, and Mendelian randomization, to elucidate the relationship between AS and IBD and to investigate the potential mechanisms of traditional Chinese medicine formulations, represented by Qiangji Jianpi (QJJP) decoction, in treating these comorbid conditions.

Methods

We utilized databases to pinpoint common targets among AS, IBD, and QJJP decoction's active compounds through intersection analysis. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we mapped a network in Cytoscape, isolating critical targets. Molecular docking with AutoDock validated the affinity between targets and compounds. ROC analysis and dataset validation assessed diagnostic performance, while Gene Set Enrichment Analysis (GSEA) offered pathway insights. Mendelian randomization explored the AS-IBD causal relationship.

Results

Screening identified 105 targets for QJJP decoction, 414 for AS, and 2420 for IBD, with 85 overlapping. These targets predominantly participate in organismal responses and DNA transcription factor binding, with a significant cellular presence in the endoplasmic reticulum and vesicle lumen. Molecular docking, facilitated by Cytoscape, confirmed IL1A, IFNG, TGFB1, and EDN1 as critical targets, with IFNG demonstrating diagnostic potential through GEO dataset validation. The integration of GSEA with network pharmacology highlighted the therapeutic significance of the relaxin, osteoclast differentiation, HIF-1, and AGE-RAGE signaling pathways in QJJP decoction's action. Mendelian randomization analysis indicated a positive causal relationship between IBD and AS, pinpointing rs2193041 as a key SNP influencing IFNG.

Conclusion

Based on the principle of "treating different diseases with the same method" in traditional Chinese medicine theory, we explored the intricate mechanisms through which QJJP decoction addresses AS and IBD comorbidity. Our research spotlighted the pivotal role of the IFNG gene. IFNG emerges not only as a key therapeutic target but also assumes significance as a potential diagnostic biomarker through its genetic underpinnings. This investigation establishes a solid base for subsequent experimental inquiries. Our findings introduce novel approaches for incorporating traditional Chinese medicine into the treatment of AS-IBD comorbidity, setting the stage for groundbreaking research directions.

Study on the Expression and Potential Function of LncRNA in Peripheral Blood of Patients with Ankylosing Spondylitis

BACKGROUND

Ankylosing spondylitis (AS) is an autoimmune disease that has the characteristics of difficult early diagnosis and a high disability rate.

OBJECTIVE

The objective of this study was to further explore the possible mechanism and potential function of lncRNA in AS.

METHODS

We used lncRNA microarray technology to detect the expression of lncRNA and mRNA in patients with active AS, stable patients, and healthy controls (HC). Afterward, bioinformatics analysis was conducted on differentially expressed genes. Seven differentially expressed lncRNAs were screened out for real-time fluorescent quantitative PCR (RT-qPCR), combined with various clinical indicators for correlation analysis, and the receiver operating characteristic (ROC) curve was used to analyze the potential of lncRNA as a diagnostic marker for AS.

RESULTS

The results showed that the expression levels of NR-037662 and ENST00000599316 in the AS subgroups were significantly higher than those in the HC group, while the expression levels of ENST00000577914 and ENST00000579003 were lower than those in the HC group. The expression levels of NR-003542 and ENST00000512051 in the ASA group were significantly higher than those in the ASS and HC groups, while NR-026756 was just the opposite. Spearman's correlation analysis showed that the expression level of NR-003542 was positively correlated with Bath Ankylosing Spondylitis Functional Index (BASFI), Erythrocyte Sedimentation Rate (ESR), and high sensitivity C-Reactive Protein (hsCRP). The expression level of NR-026756 was negatively correlated with the Bath Ankylosing Spine Inflammatory Disease Activity Index (BASDAI), BASFI, ESR, hsCRP, and globulin (GLOB). In addition, it was also found that the ROC curve analysis of the 4 lncRNAs between the AS group (ASA group and ASS group) and the HC group were statistically significant, and the area under the curve (AUC) of NR-037662, ENST00000599316, ENST00000577914, and ENST00000579003 was 0.804, 0.812, 0.706, and 0.698, respectively.

CONCLUSION

It was found that these differentially expressed lncRNAs of AS may be involved in the occurrence and development of the disease. Among them, NR-037662, ENST00000599316, ENST00000577914, and ENST00000579003 might have the potential to become AS diagnostic molecular markers. Moreover, NR -003542, ENST00000512051, and NR-026756 might have the potential to be indicators of disease activity.

A Group of Long Non-coding RNAs in Blood Acts as a Specific Biomarker of Alzheimer's Disease

Long non-coding RNAs (lncRNAs) have been identified to be involved in the pathogenesis of Alzheimer's disease (AD). In this study, we evaluated whether lncRNAs can be used to discriminate AD patients from controls and patients with other dementias, such as vascular, Parkinson's disease, behavioral variant frontotemporal, and dementia with Lewy body. In this study, we used three datasets to measure the blood lncRNA levels. A pilot study (dataset 1, n = 40; controls, 20; AD, 20) was used to screen for differentially expressed lncRNAs. Dataset 2 (n = 174; controls, 86; AD, 88) was used to identify a lncRNA panel for the diagnostic model. Dataset 3 (n = 333; control, 60; AD, 54; vascular dementia, 53; Parkinson's disease dementia, 55; behavioral variant frontotemporal dementia, 56; and dementia with Lewy body, 55) was used to validate the diagnostic model. In dataset 1, 12 upregulated and 15 downregulated lncRNAs were identified. In dataset 2, a panel of seven lncRNAs was found to have the ability to differentiate AD patients from controls. Finally, this panel was applied to dataset 3 to successfully distinguish AD from other dementias. This study proposes a panel of seven lncRNAs as specific and promising biomarker for AD diagnosis.

Bioinformatics Analysis of Immune Cell Infiltration and Diagnostic Biomarkers between Ankylosing Spondylitis and Inflammatory Bowel Disease

Background

Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are both autoimmune diseases, and they often occur together in clinical practice, but the pathogenesis is unclear. This study is aimed at identifying the hub genes and explore the related immune molecular mechanisms between AS and IBD by bioinformatics analysis.

Methods

From the public Gene Expression Omnibus (GEO) database, the AS and IBD datasets (GSE73754, GSE59071, GSE25101, and GSE36807) were obtained. The immune cell infiltration in the peripheral blood tissues of GSE73754 and GSE59071 was assessed using the CIBERSORT algorithm. Then, we used the Weighted Gene Coexpression Network Analysis (WGCNA) to identify the Differentially Expressed Genes (DEGs) related to AS and IBD. Then, the immune genes from the ImmPort database intersected with the DEGs to obtain hub genes. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzed the functional correlation of hub genes. Then, hub genes were verified in GSE25101 and GSE36807. The clusterProfiler software and Gene Set Enrichment Analysis (GSEA) were used to conduct functional enrichment and pathway enrichment studies. Finally, the diagnostic efficacy was assessed using Receiver Operating Characteristic (ROC) curve analysis.

Results

The analysis of immune characteristics showed that both AS and IBD were related to immunity, and neutrophils were positively correlated in both diseases. Nine coexpressed genes, including FCGRT, S100A11, IFNGR1, NFKBIZ, JAK2, LYN, PLAUR, ADM, and IL1RN, were linked to immune cells. The GO and KEGG analyses results showed that enrichment analysis was mainly related to cell transport and migration. Finally, the ROC curve was verified with the validation set, and it was found that PLAUR has clinical diagnostic significance and the most excellent specificity and sensitivity, respectively.

Conclusions

PLAUR (uPAR) is a promising biomarker and will be an underlying genetic biomarker for diagnosing AS comorbid IBD. Inflammation and immunological modulation mediated by neutrophil infiltration were important in the development of AS and IBD and may be diagnostic and therapeutic targets.

Differential regulation of mRNAs and lncRNAs related to lipid metabolism in Duolang and Small Tail Han sheep

The function of long non-coding RNA (lncRNA) can be achieved through the regulation of target genes, and the deposition of fat is regulated by lncRNA. Fat has an important effect on meat quality. However, there are relatively few studies on lncRNAs in the subcutaneous adipose tissue of Duolang sheep and Small Tail Han sheep. In this study, RNA-Seq technology and bioinformatics methods were used to identify and analyze the lncRNA and mRNA in the subcutaneous adipose tissue of the two breeds of sheep. The results showed that 107 lnRNAs and 1329 mRNAs were differentially expressed. The differentially expressed genes and lncRNA target genes were significantly enriched in the biosynthesis of unsaturated fatty acids signaling pathway, fatty acid metabolism, adipocyte differentiation and other processes related to fat deposition. Among them, LOC105616076, LOC114118103, LOC105607837, LOC101116622, and LOC105603235 target FADS1, SCD, ELOVL6, HSD17B12 and HACD2, respectively. They play a key regulatory role in the biosynthesis of unsaturated fatty acids. This study lays a foundation for the study of the molecular mechanism of lncRNA on fat development, and has reference value for studying the differences in fat deposition between Duolang sheep and Small Tail Han sheep.

Emerging Roles of Long Non-Coding RNAs in Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a chronic systemic autoimmune disease characterized by inflammation, bone erosion, spur formation of the spine and the sacroiliac joints. However, the etiology and molecular pathogenesis of AS remain largely unclear. Recently, a growing number of studies showed that long non-coding RNAs (lncRNAs) played critical roles in the development and progression of autoimmune and orthopedic conditions, including AS. Studies demonstrated that a myriad of lncRNAs (e.g. H19, MEG3, LOC645166) pertinent to regulation of inflammatory signals were deregulated in AS. A number of lncRNAs might also serve as new biomarkers for the diagnosis and predicting the outcomes of AS. In this review, we summarize lncRNA profiling studies on AS and the functional roles and mechanism of key lncRNAs relevant to AS pathogenesis. We also discuss their potential values as biomarkers and druggable targets for this potentially disabling condition.

Integrative analysis of long non-coding RNA and messenger RNA expression in toll-like receptor 4-primed mesenchymal stem cells of ankylosing spondylitis

Background

The precise pathogenesis of ankylosing spondylitis (AS) is still largely unknown at present. Our previous study found that toll-like receptor 4 (TLR4) downregulated and performed immunoregulatory dysfunction in mesenchymal stem cells from AS patients (AS-MSCs). The aim of this study was to explore the expression profiles of long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in TLR4-primed AS-MSCs, and to clarify the potential mechanisms.

Methods

The immunoregulatory effects of MSCs were determined after TLR4 activation. Next, the differentially-expressed (DE) lncRNAs and mRNAs between AS-MSCs and TLR4-primed AS-MSCs [stimulated by lipopolysaccharide (LPS)] were identified via high-throughput sequencing followed by quantitative real-time PCR (qRT-PCR) confirmation. Finally, bioinformatics analyses were performed to identify the critical biological functions, signaling pathways, and associated functional networks involved in the TLR4-primed immunoregulatory function of AS-MSCs.

Results

A total of 147 DE lncRNAs and 698 DE mRNAs were identified between TLR4-primed AS-MSCs and unstimulated AS-MSCs. Of these, 107 lncRNAs were upregulated and 40 were downregulated (fold change ≥2, P<0.05), while 504 mRNAs were upregulated and 194 were downregulated (fold change ≥2, P<0.05). Five lncRNAs and five mRNAs with the largest fold changes were respectively verified by qRT-PCR. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that the DE mRNAs and lncRNAs were highly associated with the inflammatory response, such as NOD-like receptor (NLR) signaling pathway, the TNF signaling pathway and the NF-κB signaling pathway. Cis-regulation prediction revealed eight novel lncRNAs, while trans-regulation prediction revealed 15 lncRNAs, respectively. Eight core pairs of lncRNA and target mRNA in the lncRNA-transcription factor (TF)-mRNA network were as follows: PACERR-PTGS2, LOC105378085-SOD2, LOC107986655-HIVEP2, MICB-DT-MICB, LOC105373925-SP140L, LOC107984251-IFIT5, LOC112268267-GBP2, and LOC101926887-IFIT3, respectively.

Conclusions

TLR4 activation in AS can enhance the immunoregulatory ability of MSCs. Eight core pairs of lncRNA and target mRNA were observed in TLR4-primed AS-MSCs, which could contribute to understanding the potential mechanism of AS-MSC immunoregulatory dysfunction.

The Potential Regulatory Mechanism of lncRNA 122K13.12 and lncRNA 326C3.7 in Ankylosing Spondylitis

This work aims to analyze and construct a novel competing endogenous RNA (ceRNA) network in ankylosing spondylitis (AS) with bone bridge formation, lncRNA. Using RNA sequencing and bioinformatics, we analyzed expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in whole blood cells from 5 AS patients and 3 healthy individuals. Next, we verified the expression levels of candidate lncRNAs in 97 samples using the ΔΔCt value of real-time quantitative polymerase chain reaction (qRT-PCR). We used multivariate logistic regression analysis to screen lncRNAs and clinical indicators for use in the prediction model. Both SPSS 24.0 and R software were used for data analysis and prediction model construction. The results showed that compared with the normal controls, 205 long noncoding RNAs (lncRNAs), 961 microRNAs (miRNAs), and 200 mRNAs (DEmRNAs) were differentially expressed in the AS patients. We identified lncRNA 122K13.12 and lncRNA 326C3.7 among 205 lncRNAs differentially expressed between AS patients and healthy humans. Then, we noted that 30 miRNAs and five mRNAs formed a ceRNA network together with these two lncRNAs. These ceRNA networks might regulate the tumor necrosis factor (TNF) signaling pathway in AS development. In addition, the expression level of lncRNA 122K13.12 and lncRNA 326C3.7 correlated with various structural damage indicators in AS. Specifically, the lncRNA 326C3.7 expression level was an independent risk factor in bone bridge formation [area under the ROC curve (AUC) = 0.739 (0.609–0.870) and p = 0.003], and the best Youden Index was 0.405 (sensitivity = 0.800 and specificity = 0.605). Moreover, we constructed a lncRNA-based nomogram that could effectively predict bone bridge formation [AUC = 0.870 (0.780–0.959) and p < 0.001, and the best Youden Index was 0.637 (sensitivity = 0.900 and specificity = 0.737)]. In conclusion, we uncovered a unique ceRNA signaling network in AS with bone bridge formation and identified novel biomarkers and prediction models with the potential for clinical applications.

Identification of immune related cells and crucial genes in the peripheral blood of ankylosing spondylitis by integrated bioinformatics analysis

Background

Ankylosing spondylitis (AS) is a progressive rheumatic disease and studies reveal that the immune system is critical for the pathogenesis of AS. In the present study, various bioinformatics analysis methods were comprehensively applied, designed to identify potential key genes and inflammation states of AS.

Methods

The transcriptome profiles of GSE25101 and GSE73754 obtained from the Gene Expression Omnibus (GEO) database were merged for subsequent analyses. The differentially expressed genes (DEGs) were identified using the Bioconductor package Limma and threshold values. Functional enrichment and pathway enrichment analyses were performed using the clusterProfiler package and Gene Set Enrichment Analysis (GSEA). Next, protein-protein interaction (PPI) network of the identified DEGs was constructed by the online database, the Search Tool for the Retrieval of Interacting Genes (STRING), visualization and analysis were performed through Cytoscape software. Subsequently, we applied CIBERSORT algorithm to identify subpopulation proportions of immune cells in peripheral blood samples. Finally, we validated the hub genes with the GSE18781 dataset. Samples were collected from patients to validate gene and protein expression using qRT-PCR and ELISA.

Results

A total of 334 DEGs were identified, including 182 upregulated and 152 downregulated DEGs, between AS patients and normal human controls, which were primarily involved in immune response, autophagy, and natural killer cell-mediated cytotoxicity. The most prominent module and candidate biomarkers were identified from the PPI network. Biomarkers were selected for validation and their expressions were significantly decreased in peripheral blood samples which was consistent with transcriptome sequencing results. Nine genes with AUC > 0.70 were considered to be AS hub genes for ROC curve analysis, including GZMA, GZMK, PRF1, GNLY, NKG7, KLRB1, KLRD1, IL2RB and CD247. Furthermore, CIBERSORT results suggest that AS contained a higher proportion of CD8+ T cells, naive CD4+ T cells, neutrophils, and lower levels of gamma delta T cells compared with the normal controls.

Conclusion

In this study, we identified DEGs combined with their closely related biological functions and propose that granule-associated proteins and immune infiltration maybe involved in the progression of ankylosing spondylitis. These validated hub genes may provide new perspectives for understanding the molecular mechanisms of ankylosing spondylitis.

Transcriptome Analysis of In Vitro Fertilization and Parthenogenesis Activation during Early Embryonic Development in Pigs

Parthenogenesis activation (PA), as an important artificial breeding method, can stably preserve the dominant genotype of a species. However, the delayed development of PA embryos is still overly severe and largely leads to pre-implantation failure in pigs. The mechanisms underlying the deficiencies of PA embryos have not been completely understood. For further understanding of the molecular mechanism behind PA embryo failure, we performed transcriptome analysis among pig oocytes (meiosis II, MII) and early embryos at three developmental stages (zygote, morula, and blastocyst) in vitro fertilization (IVF) and PA group. Totally, 11,110 differentially expressed genes (DEGs), 4694 differentially expressed lincRNAs (DELs) were identified, and most DEGs enriched the regulation of apoptotic processes. Through cis- and trans-manner functional prediction, we found that hub lincRNAs were mostly involved in abnormal parthenogenesis embryonic development. In addition, twenty DE imprinted genes showed that some paternally imprinted genes in IVF displayed higher expression than that in PA. Notably, we identified that three DELs of imprinted genes (MEST, PLAGL1, and DIRAS3) were up regulated in IVF, and there was no significant change in PA group. Disordered expression of key genes for embryonic development might play key roles in abnormal parthenogenesis embryonic development. Our study indicates that embryos derived from different production techniques have varied in vitro development to the blastocyst stage, and they also affect the transcription level of corresponding genes, such as imprinted genes. This work will help future research on these genes and molecular-assisted breeding for pig parthenotes.

MicroRNA let-7i-3p affects osteoblast differentiation in ankylosing spondylitis via targeting PDK1

Ankylosing spondylitis (AS) is a chronic autoimmune disease in which let-7i has been studied to involved. But, whether let-7i-3p could regulate osteoblast differentiation in AS remains unclear. This research targeted to decipher the impact of let-7i-3p on AS progression by modulating pyruvate dehydrogenase kinase 1 (PDK1). The bone mineral density of femur and lumbar vertebra and the maximum loading and bending elastic modulus of tibia, tumor necrosis factor-α (TNF-α), matrix metalloproteinase (MMP)-3, osteoprotegerin (OPG) and receptor activator of nuclear factor-κB ligand (RANKL) in serum of AS mice, the pathological condition of synovial tissue were determined via let-7i-3p inhibitor and OE-PDK1 in animal experiment. Also, the cell viability and ALP activity were measured by let-7i-3p inhibitor and OE-PDK1 in cell experiments. let-7i-3p and PDK1 expression were detected. Let-7i-3p raised and PDK1 declined in AS mice. Depleted let-7i-3p and restored PDK1 increased bone mineral density and maximum loading and bending elastic modulus of tibia, reduced TNF-α, MMP-3 and RANKL contents, attenuated the pathological condition of synovial tissue and raised OPG content in AS mice. In cell experiments, up-regulating PDK1 and down-regulating let-7i-3p enhanced cell viability and ALP activity in AS mice. Low expression of let-7i-3p could enhance osteoblast differentiation in AS by up-regulating PDK1.Abbreviations: AS: Ankylosing spondylitis; PDK1: pyruvate dehydrogenase kinase 1; TNF-α: tumor necrosis factor-α MMP: matrix metalloproteinase; OPG: osteoprotegerin; RANKL: receptor activator of nuclear factor-κB ligand; miRNAs: MicroRNAs; BMD: bone mineral density; PFA: paraformaldehyde; NC: negative control; OE: overexpression; HE: Hematoxylin-eosin; PBS: phosphate-buffered saline; EDTA: ethylene diamine tetraacetic acid; DMEM: Dulbecco's Modified Eagle Medium; RT-qPCR: Reverse transcription quantitative polymerase chain reaction; GAPDH: glyceraldehyde phosphate dehydrogenase; UTR: untranslated region; WT: wild type; MUT: mutant type.

Comparative transcriptome analysis of transcripts of uncertain coding potential in septic myocardial depression

BACKGROUND

Septic shock with myocardial depression is very common in intensive care units. However, the exact molecular mechanisms underlying sepsis-induced myocardial depression remain unclear. Whether the profiles of transcripts of uncertain coding potential (TUCPs) differ between patients with and without myocardial depression is also unknown. Our study aimed to find expression differences between groups of TUCPs and determine their potential functions in a preclinical model.

METHODS

We generated rat models of hypodynamic septic shock induced by lipopolysaccharide. A total of 12 rats were established and left ventricular tissue from each was collected. We performed RNA-seq to identify TUCPs in each sample. Transcripts with an corrected P value of < 0.05 were defined as differentially expressed (DE). We also performed GO terms and KEGG analysis to identify the potential functions of DE TUCPs.

RESULTS

A total of 4,851 TUCPs were identified in heart samples, 85 of which were expressed differently between the sepsis and control groups. Further bioinformatic analyses suggested that TUCPs play important roles in myocardial contraction, energy regulation, and metabolic processes, and are also involved in the regulation of several pathways.

CONCLUSION

Our results demonstrate that TUCPs both participate in and mediate the pathological process of myocardial depression. Our study improves the understanding of the basic molecular mechanisms underlying myocardial depression from a novel perspective.

Identification of lncRNAs associated with the pathogenesis of ankylosing spondylitis

Background

Ankylosing spondylitis (AS) is a chronic autoimmune disease affecting the sacroiliac joint. To date, few studies have examined the association between long non-coding RNAs (lncRNAs) and AS pathogenesis. As such, we herein sought to characterize patterns of AS-related lncRNA expression and to evaluate the potential role played by these lncRNAs in this complex autoimmune context.

Methods

We conducted a RNA-seq analysis of peripheral blood mononuclear cell (PBMC) samples isolated from five AS patients and corresponding controls. These data were then leveraged to characterize AS-related lncRNA expression patterns. We further conducted GO and KEGG enrichment analyses of the parental genes encoding these lncRNAs, and we confirmed the validity of our RNA-seq data by assessing the expression of six lncRNAs via qRT-PCR in 15 AS and control patient samples. Pearson correlation analyses were additionally employed to examine the associations between the expression levels of these six lncRNAs and patient clinical index values.

Results

We detected 56,575 total lncRNAs in AS and control patient samples during our initial RNA-seq analysis, of which 200 and 70 were found to be up- and down-regulated (FC > 2 or < 0.05; P < 0.05), respectively, in AS samples relative to controls. In qRT-PCR validation assays, we confirmed the significant upregulation of NONHSAT118801.2, ENST00000444046, and NONHSAT183847.1 and the significant downregulation of NONHSAT205110.1, NONHSAT105444.2, and NONHSAT051856.2 in AS patient samples. We further found the expression of NONHSAT118801.2 and NONHSAT183847.1 to be positively correlated with disease severity.

Conclusion

Overall, our findings highlight several lncRNAs that are specifically expressed in PBMCs of AS patients, indicating that they may play key functions in the pathogenesis of this autoimmune disease. Specifically, we determined that NONHSAT118801.2 and NONHSAT183847.1 may influence the occurrence and development of AS.

Identification of Five Immune-Related lncRNAs Predicting Survival and Tumor Microenvironment Characteristics in Breast Cancer

A common cancer in females, breast cancer (BRCA) mortality has been recently reduced; however, the prognosis of BRCA patients remains poor. This study attempted to develop prognostic immune-related long noncoding RNAs (lncRNAs) for BRCA and identify the effects of these lncRNAs on the tumor microenvironment (TME). Gene expression data from The Cancer Genome Atlas (TCGA) database were collected in order to select differentially expressed lncRNAs. Immune-related lncRNAs were downloaded from the ImmLnc database, where 316 immune-related lncRNAs were identified, 12 of which were found to be significantly related to the prognosis of BRCA patients. Multivariate cox regression analysis was then applied to construct prognostic immune-related lncRNAs as the risk model, including C6orf99, LINC00987, SIAH2-AS1, LINC01010, and ELOVL2-AS1. High-risk and low-risk groups were distinguished according to the median of immune-related risk scores. Accordingly, the overall survival (OS) in the high-risk group was observed to be shorter than that in the low-risk group. qRT-PCR analysis demonstrated that lncRNA expression levels in BRCA cell lines were in basic agreement with predictions except for LINC00987. By validating numerous clinical samples, lncRNA C6orf99 was shown to be highly expressed in the advanced stage, while LINC01010 and SIAH2-AS1 decreased in the advanced T-stage and M-stage. Moreover, the expression of LINC0098 was found to be significantly decreased among the groups (>50 years old). Gene set enrichment analysis (GSEA) was applied to analyze the cancer hallmarks and immunological characteristics of the high-risk and low-risk groups. Importantly, the TIMER database demonstrated that this immune-related lncRNA risk model for breast cancer is related to the infiltration of immune cells. In conclusion, the results indicated that five immune-related lncRNAs could be used as a prognostic model and may even accelerate immunotherapy for BRCA patients.

Autophagy dysfunction may be involved in the pathogenesis of ankylosing spondylitis

The present study aimed to investigate the expression and significance of the mRNA of genes associated with autophagy and long non-coding RNA (lncRNA) GAS5 in peripheral blood mononuclear cells (PBMCs) of patients with ankylosing spondylitis (AS). The mRNA levels of microtubule-associated protein light chain 3 (LC3), Beclin1, autophagy-related gene (ATG)3, ATG5, ATG12, ATG 16 ligand 1 (ATG16L1) and lncRNA growth arrest-specific 5 (GAS5) in PBMCs from 60 patients with AS and 30 healthy controls (HC) were examined by reverse transcription-quantitative PCR. The correlations between the levels of LC3, Beclin1, ATG3, ATG5, ATG12 and ATG16L1 mRNA as well as lncRNA GAS5 levels with disease activity and laboratory parameters in patients with AS were determined by Spearman correlation analysis. In addition, the diagnostic value of lncRNA GAS5 for AS was explored through establishing a receiver operating characteristic (ROC) curve. The results indicated that, compared to the HCs, patients with AS had lower expression levels of LC3, ATG5, ATG12, ATG16L1 and lncRNA GAS5 in their PBMCs. Compared with those in patients with inactive AS, the levels of ATG5 and ATG12 were lower than those in patients with active AS. Of note, ATG5 and ATG12 mRNA levels were negatively correlated with disease activity indexes. lncRNA GAS5 was positively correlated with the expression of Beclin1, ATG3, ATG5, ATG12 and ATG16L1. The area under the ROC curve for the use of lncRNA GAS5 expression to diagnose AS was 0.808 with a 95% CI of 0.714-0.902. In conclusion, patients with AS had decreased expression of genes associated with autophagy and lncRNA GAS5. The extent of the reduction in ATG5 and ATG12 expression levels in patients with AS was correlated with the disease severity and activity. Furthermore, lncRNA GAS5 was a diagnostic indicator of AS.

lncRNA MEG3 Suppresses the Progression of Ankylosis Spondylitis by Regulating the Let-7i/SOST Axis

Ankylosis spondylitis (AS) is a disease mainly characterized by sacroiliac joint and spinal attachment point inflammation. Long non-coding RNA (lncRNA) plays a key role in the progression of many diseases. However, few studies have been conducted on the function of lncRNA maternally expressed gene 3 (MEG3) in AS. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure the relative levels of MEG3, microRNA let-7i, sclerostin (SOST), and inflammatory cytokines. Dual-luciferase reporter assay, RNA immunoprecipitation (RIP) assay and biotin-labeled RNA pull-down assay were used to confirm the interaction between MEG3 and let-7i or let-7i and SOST. In addition, western blot (WB) analysis was performed to detect the protein levels of osteogenesis markers and SOST. The expression levels of MEG3 and SOST were decreased and let-7i was increased in AS patients. MEG3 could interact with let-7i in AS fibroblasts, and let-7i overexpression reversed the suppressive effect of MEG3 upregulation on the inflammation and bone formation of AS. Additionally, let-7i could target SOST, and SOST silencing reversed the inhibitory effect of let-7i inhibitor or MEG3 overexpression on the inflammation and bone formation of AS. Furthermore, SOST expression was positively regulated by MEG3, while was negatively regulated by let-7i. Our results revealed that lncRNA MEG3 promoted SOST expression to restrain the progression of AS by sponging let-7i, which provided a treatment target for AS.

Profiling and Bioinformatics Analysis of Differentially Expressed circRNAs in Spinal Ligament Tissues of Patients with Ankylosing Spondylitis

Recent studies have reported that circular RNAs (circRNAs) play a crucial regulatory role in a variety of human diseases. However, the roles of circRNAs in ankylosing spondylitis (AS) remain unclear. In this study, we conducted circRNA expression profiling of the spinal ligament tissues of patients with AS by RNA sequencing (RNA-seq) and analyzed the potential functions of differentially expressed circRNA by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to investigate the potential mechanisms associated with AS. The results showed that a total of 1,172 circRNAs were detected in the spinal ligament tissue samples, of which 123 circRNAs were significantly differentially expressed by a fold change ≥ 1.5 and p value < 0.05. Among these, 57 circRNAs were upregulated, and 66 were downregulated. GO and KEGG analyses demonstrated that the differentially expressed circRNAs were mainly involved in the regulation of biological processes of peptidyl-serine phosphorylation and human immune system that may be related to AS. In addition, the circRNA/miRNA interaction networks were established to predict the potential roles of differentially expressed circRNAs by bioinformatics analysis. Taken together, these results revealed the expression profiles of circRNAs and the potential functions of the differentially expressed circRNAs in the spinal ligament tissue of patients with AS, which may provide new clues for understanding the mechanisms associated with AS, and proceed to identify novel potential molecular targets for the diagnoses and treatment of AS.

Long non-coding RNA MEG3 is involved in osteogenic differentiation and bone diseases (Review)

Osteogenic differentiation originating from mesenchymal stem cells (MSCs) requires tight co-ordination of transcriptional factors, signaling pathways and biomechanical cues. Dysregulation of such reciprocal networks may influence the proliferation and apoptosis of MSCs and osteoblasts, thereby impairing bone metabolism and homeostasis. An increasing number of studies have shown that long non-coding (lnc)RNAs are involved in osteogenic differentiation and thus serve an important role in the initiation, development, and progression of bone diseases such as tumors, osteoarthritis and osteoporosis. It has been reported that the lncRNA, maternally expressed gene 3 (MEG3), regulates osteogenic differentiation of multiple MSCs and also acts as a critical mediator in the development of bone formation and associated diseases. In the present review, the proposed mechanisms underlying the roles of MEG3 in osteogenic differentiation and its potential effects on bone diseases are discussed. These discussions may help elucidate the roles of MEG3 in osteogenic differentiation and highlight potential biomarkers and therapeutic targets for the treatment of bone diseases.

LncRNA MEG3 inhibits the inflammatory response of ankylosing spondylitis by targeting miR-146a

Ankylosing spondylitis (AS) is a progressive systemic disease characterized by chronic inflammation response of the sacroiliac joint and spine. Long non-coding RNAs (lncRNAs) are widely involved in the regulation of various diseases. However, the role of lncRNA maternally expressed gene 3 (MEG3) in the inflammatory response of AS has not been studied. Enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of inflammatory cytokines interleukin-1β (IL-1β) and interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in tissues and cells. The expression levels of MEG3, microRNA-146a (miR-146a), and inflammatory cytokines were measured by quantitative real-time PCR (qRT-PCR). Correlation between MEG3 or miR-146a and inflammatory cytokines was analyzed by Pearson analysis. Dual-luciferase reporter and RNA immunoprecipitation (RIP) assays were used to clarify the interaction between MEG3 and miR-146a. MEG3 was downregulated in AS patients, negatively correlated with the levels of IL-1β, IL-6, and TNF-α, and blocked the inflammatory response of AS. MiR-146a was upregulated in AS patients and could interact with MEG3. The expression of miR-146a was positively correlated with IL-1β, IL-6, and TNF-α levels. Overexpression of miR-146a reversed the inhibitory effect of abnormal MEG3 expression on inflammatory cytokines. LncRNA MEG3 plays an anti-inflammatory role in AS partially through targeting miR-146a, which provides a potential new means for the treatment of AS patients.

H19 Increases IL-17A/IL-23 Releases via Regulating VDR by Interacting with miR675-5p/miR22-5p in Ankylosing Spondylitis

Long non-coding RNA (lncRNA) H19 is associated with inflammatory diseases, but the molecular mechanism of H19 in the inflammatory process of ankylosing spondylitis (AS) is unclear. Here, we investigated the role of H19 and its downstream molecules in the inflammation of AS by microarray analysis, qRT-PCR, western blot, and dual-luciferase reporter assay. H19 small interfering RNA (siRNA) (Si-H19) and adenovirus (AD-H19) were used to decrease and increase H19 expression, respectively. 42 annotated lncRNAs were identified, and H19 was overexpressed. H19, vitamin D receptor (VDR), and transforming growth factor β (TGF-β) can bind to microRNA22-5p (miR22-5p) and miR675-5p. Si-H19 significantly downregulated miR22-5p and upregulated miR675-5p expression; Si-H19 decreased the protein and mRNA expression of VDR and decreased the cytokine and mRNA levels of interleukin-17A (IL-17A) and IL-23. These results were verified by AD-H19. In addition, miR22-5p and miR675-5p inhibitors increased the protein and mRNA expression of VDR and increased the cytokine and mRNA levels of IL-17A and IL-23. These results were also confirmed by miRNA mimics. Furthermore, H19 directly interfered with miR22-5p and miR675-5p expression, whereas the two miRNAs directly inhibited VDR expression. Overall, the H19-miR22-5p/miR675-5p-VDR-IL-17A/IL-23 signaling pathways have important roles in the pathogenesis of AS.

A Long Non-coding RNA Signature to Improve Prognostic Prediction of Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive solid malignant tumors worldwide. Increasing investigations demonstrate that long non-coding RNAs (lncRNAs) expression is abnormally dysregulated in cancers. It is crucial to identify and predict the prognosis of patients for the selection of further therapeutic treatment.

Methods: PDAC lncRNAs abundance profiles were used to establish a signature that could better predict the prognosis of PDAC patients. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to establish a multi-lncRNA signature in the TCGA training cohort (N = 107). The signature was then validated in a TCGA validation cohort (N = 70) and another independent Fudan cohort (N = 46).

Results: A five-lncRNA signature was constructed and it was significantly related to the overall survival (OS), either in the training or validation cohorts. Through the subgroup and Cox regression analyses, the signature was proven to be independent of other clinic-pathologic parameters. Receiver operating characteristic curve (ROC) analysis also indicated that our signature had a better predictive capacity of PDAC prognosis. Furthermore, ClueGO and CluePedia analyses showed that a number of cancer-related and drug response pathways were enriched in high risk groups.

Conclusions: Identifying the five-lncRNA signature (RP11-159F24.5, RP11-744N12.2, RP11-388M20.1, RP11-356C4.5, CTC-459F4.9) may provide insight into personalized prognosis prediction and new therapies for PDAC patients.