LncRNA HOTTIP promotes inflammatory response in acute gouty arthritis via miR-101-3p/BRD4 axis

Identification of Key lncRNAs in Gout Under Copper Death and Iron Death Mechanisms: A Study Based on ceRNA Network Analysis and Random Forest Algorithm

This study focused on identifying potential key lncRNAs associated with gout under the mechanisms of copper death and iron death through ceRNA network analysis and Random Forest (RF) algorithm, which aimed to provide new insights into the molecular mechanisms of gout, and potential molecular targets for future therapeutic strategies of gout. Initially, we conducted an in-depth bioinformatics analysis of gout microarray chips to screen the key cuproptosis-related genes (CRGs) and key ferroptosis-related genes (FRGs). Using these data, we constructed a key ceRNA network for gout. Finally, key lncRNAs associated with gout were identified through the RF algorithm combined with ROC curves, and validated using the Comparative Toxicogenomics Database (CTD). We successfully identified NLRP3, LIPT1, and DBT as key CRGs associated with gout, and G6PD, PRKAA1, LIG3, PHF21A, KLF2, PGRMC1, JUN, PANX2, and AR as key FRGs associated with gout. The key ceRNA network identified four downregulated key lncRNAs (SEPSECS-AS1, LINC01054, REV3L-IT1, and ZNF883) along with three downregulated mRNAs (DBT, AR, and PRKAA1) based on the ceRNA theory. According to CTD validation inference scores and biological functions of target mRNAs, we identified a potential gout-associated lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis. This study identified the key lncRNA ZNF883 in the context of copper death and iron death mechanisms related to gout for the first time through the application of ceRNA network analysis and the RF algorithm, thereby filling a research gap in this field and providing new insights into the molecular mechanisms of gout. We further found that lncRNA ZNF883 might function in gout patients by regulating PRKAA1, the mechanism of which was potentially related to uric acid reabsorption in the proximal renal tubules and inflammation regulation. The proposed lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis might represent a potential RNA regulatory pathway for controlling the progression of gout disease. This discovery offered new molecular targets for the treatment of gout, and had significant implications for future therapeutic strategies in managing the gout.

The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model

Background

Sepsis is a life-threatening organ dysfunction condition produced by dysregulation of the host response to infection. It is now characterized by a high clinical morbidity and mortality rate, endangering patients' lives and health. The purpose of this study was to determine the value of Long chain non-coding RNA (LncRNA) RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 in the diagnosis of adult sepsis patients and to develop a Nomogram prediction model.

Methods

We screened adult sepsis microarray datasets GSE57065 and GSE95233 from the GEO database and performed differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), and machine learning methods to find the genes by random forest (Random Forest), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), respectively, with GSE95233 as the training set and GSE57065 as the validation set. Differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), boxplot statistical analysis, and ROC analysis by Random Forest, Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine (SVM) machine learning methods were used to identify characteristic genes and build the Nomogram Prediction model.

Results

GSE95233 yielded a total of 1069 genes, 102 of which were sepsis-related and 22 of which were non-sepsis controls. GSE57065 yielded a total of 899 genes, with 467 up-regulated and 432 down-regulated, including 82 sepsis-related genes and 25 non-sepsis control genes. WGCNA analysis excluded outlier samples, leaving 2,029 genes for relationship analysis between sepsis- and non-sepsis patient-associated LncRNA network representation modules, as well as Wein plots of differential genes versus genes in key modules of weighted co-expression network analysis to analyze gene intersections. Machine Learning found the sepsis-related characteristic LncRNAs RP3-508I15.21, RP11-295G20.2, LDLRAD4-AS1, and CTD-2542L18.1. The datasets GSE95233 and GSE57065 were analyzed using Boxplot against the screened genes listed above, respectively. The p-value between the sepsis and non-sepsis groups was less than 0.05, indicating that anomalies were statistically significant. CTD-2542L18.1 in dataset GSE57065 had an AUC value of 0.638, which was less than 0.7 and did not indicate diagnostic significance, but RP3-508I15.21, RP11-295G20.2, and LDLRAD4-AS1 had AUC values more than 0.7 after ROC analysis. All four sepsis-associated LncRNA ROC analyses in dataset GSE95233 exhibited AUC values more than 0.7, indicating diagnostic significance.

Conclusion

LncRNAs RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 have some utility in the diagnosis and treatment of adult sepsis patients, as well as some reference importance in guiding the diagnosis and treatment of clinical sepsis.

Sepsis Biomarkers: Advancements and Clinical Applications-A Narrative Review

Sepsis is now defined as a life-threatening syndrome of organ dysfunction triggered by a dysregulated host response to infection, posing significant challenges in critical care. The main objective of this review is to evaluate the potential of emerging biomarkers for early diagnosis and accurate prognosis in sepsis management, which are pivotal for enhancing patient outcomes. Despite advances in supportive care, traditional biomarkers like C-reactive protein and procalcitonin have limitations, and recent studies have identified novel biomarkers with increased sensitivity and specificity, including circular RNAs, HOXA distal transcript antisense RNA, microRNA-486-5p, protein C, triiodothyronine, and prokineticin 2. These emerging biomarkers hold promising potential for the early detection and prognostication of sepsis. They play a crucial role not only in diagnosis but also in guiding antibiotic therapy and evaluating treatment effectiveness. The introduction of point-of-care testing technologies has brought about a paradigm shift in biomarker application, enabling swift and real-time patient evaluation. Despite these advancements, challenges persist, notably concerning biomarker variability and the lack of standardized thresholds. This review summarizes the latest advancements in sepsis biomarker research, spotlighting the progress and clinical implications. It emphasizes the significance of multi-biomarker strategies and the feasibility of personalized medicine in sepsis management. Further verification of biomarkers on a large scale and their integration into clinical practice are advocated to maximize their efficacy in future sepsis treatment.

Peripheral Blood miRNA Expression in Patients with Essential Hypertension in the Han Chinese Population in Hefei, China

Primary hypertension is a significant risk factor for cardiovascular diseases. However, the pathogenesis of primary hypertension involves multiple biological processes, including the nervous system, circulatory system, endocrine system, and more. Despite extensive research, there is no clear understanding of the regulatory mechanism underlying its pathogenesis. In recent years, miRNAs have gained attention as a regulatory factor capable of modulating the expression of related molecules through gene silencing. Therefore, exploring differentially expressed miRNAs in patients with essential hypertension (EH) may offer a novel approach for future diagnosis and treatment of EH. This study included a total of twenty Han Chinese population samples from Hefei, China. The samples consisted of 10 healthy individuals and 10 patients with EH. Statistical analysis was conducted to analyze the general information of the two-sample groups. High-throughput sequencing and base identification were performed to obtain the original sequencing sequences. These sequences were then annotated using various databases including Rfam, cDNA sequences, species repetitive sequences library, and miRBase database. The number of miRNA species contained in the samples was measured. Next, TPM values were calculated to determine the expression level of each miRNA. The bioinformatics of the differentiated miRNAs were analyzed using the OECloud tool, and RPM values were calculated. Furthermore, the reliability of the expression was analyzed by calculating the area under the Roc curve using the OECloud tools. Statistical analysis revealed no significant differences between the two samples in terms of age distribution, gender composition, smoking history, and alcohol consumption history (P > 0.05). However, there was a notable presence of family genetic history and high BMI in the EH population (P < 0.05). The sequencing results identified a total of 245 miRNAs, out of which 16 miRNAs exhibited differential expression. Among the highly expressed miRNAs were let-7d-5p, miR-101-3p, miR-122-5p, miR-122b-3p, miR-192-5p, and miR-6722-3p. On the other hand, the lowly expressed miRNAs included miR-103a-3p, miR-16-5p, miR-181a-2-3p, miR-200a-3p, miR-200b-3p, miR-200c-3p, miR-221-3p, miR-30d-5p, miR-342-5p, and miR-543. This study initially identified 16 miRNAs that are aberrantly expressed and function in various processes associated with the onset and progression of essential hypertension. These miRNAs have the potential to be targeted for future diagnosis and treatment of EH. However, further samples are required to provide additional support for this study.

BRD4 promotes gouty arthritis through MDM2-mediated PPARγ degradation and pyroptosis

BACKGROUND

Gouty arthritis (GA) is characterized by monosodium urate (MSU) crystal accumulation that instigates NLRP3-mediated pyroptosis; however, the underlying regulatory mechanisms have yet to be fully elucidated. The present research endeavors to elucidate the regulatory mechanisms underpinning this MSU-induced pyroptotic cascade in GA.

METHODS

J774 cells were exposed to lipopolysaccharide and MSU crystals to establish in vitro GA models, whereas C57BL/6 J male mice received MSU crystal injections to mimic in vivo GA conditions. Gene and protein expression levels were evaluated using real-time quantitative PCR, Western blotting, and immunohistochemical assays. Inflammatory markers were quantified via enzyme-linked immunosorbent assays. Pyroptosis was evaluated using immunofluorescence staining for caspase-1 and flow cytometry with caspase-1/propidium iodide staining. The interaction between MDM2 and PPARγ was analyzed through co-immunoprecipitation assays, whereas the interaction between BRD4 and the MDM2 promoter was examined using chromatin immunoprecipitation and dual-luciferase reporter assays. Mouse joint tissues were histopathologically evaluated using hematoxylin and eosin staining.

RESULTS

In GA, PPARγ was downregulated, whereas its overexpression mitigated NLRP3 inflammasome activation and pyroptosis. MDM2, which was upregulated in GA, destabilized PPARγ through the ubiquitin-proteasome degradation pathway, whereas its silencing attenuated NLRP3 activation by elevating PPARγ levels. Concurrently, BRD4 was elevated in GA and exacerbated NLRP3 activation and pyroptosis by transcriptionally upregulating MDM2, thereby promoting PPARγ degradation. In vivo experiments showed that BRD4 silencing ameliorated GA through this MDM2-PPARγ-pyroptosis axis.

CONCLUSION

BRD4 promotes inflammation and pyroptosis in GA through MDM2-mediated PPARγ degradation, underscoring the therapeutic potential of targeting this pathway in GA management.

LncRNA HOTTIP regulates TLR4 promoter methylation by recruiting H3K4 methyltransferase MLL1 to affect apoptosis and inflammatory response of fibroblast-like synoviocyte in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease, and the role of HOXA transcript at the distal tip (HOTTIP) in its pathogenesis remains underexplored. This study investigates the mechanism by which HOTTIP influences apoptosis and the inflammatory response of fibroblast-like synoviocytes (FLS). An RA mouse model was established, and clinical scores were analyzed. Pathological changes in synovial tissues, bone mineral density (BMD) of the paws, serum tartrate-resistant acid phosphatase (TRAP) activity, and TNF-α and IL-1β levels were assessed. FLS were transfected, and cell proliferation and apoptosis were examined. The RNA-pull-down assay determined HOTTIP's interaction with mixed-lineage leukemia 1 (MLL1), while RNA immunoprecipitation assay measured HOTTIP expression pulled down by MLL1. The levels of MLL1 and toll-like receptor 4 (TLR4) after MLL1 overexpression based on HOTTIP silencing were determined. Chromatin immunoprecipitation (ChIP) was performed with H3K4me3 as an antibody, followed by the evaluation of TLR4 expression. HOTTIP expression was elevated in RA mouse synovial tissues. Inhibition of HOTTIP led to reduced clinical scores, inflammatory infiltration, synovial hyperplasia, TRAP activity, and TNF-α and IL-1β levels, along with increased BMD. In vitro Interference with HOTTIP suppressed RA-FLS apoptosis and inflammation. HOTTIP upregulated TLR4 expression by recruiting MLL1 to facilitate TLR4 promoter methylation. MLL1 overexpression reversed HOTTIP silencing-mediated repression of RA-FLS apoptosis. Activation of H3K4 methylation counteracted HOTTIP knockout, ameliorating the inflammatory response. HOTTIP regulates TLR4 expression by recruiting MLL1, leading to TLR4 promoter methylation, thereby suppressing RA-FLS proliferation and inducing cell apoptosis and inflammatory response in RA.

LncRNA HOTTIP as a diagnostic biomarker for acute respiratory distress syndrome in patients with sepsis and to predict the short-term clinical outcome: a case-control study

BACKGROUND

The present research aims to investigate the clinical diagnostic value of LncRNA HOXA distal transcript antisense RNA (HOTTIP) in acute respiratory distress syndrome (ARDS) of sepsis and its predictive significance for mortality.

METHODS

One hundred eighteenth patients with sepsis and 96 healthy individuals were enrolled. RT-qPCR to examine HOTTIP levels. The incidence of ARDS and death was recorded. The diagnostic significance of HOTTIP in sepsis ARDS was examined using ROC and logistic regression analysis. The correlation between HOTTIP and disease severity was evaluated using Pearson's coefficients. Kaplan-Meier analysis and COX regression were employed to examine the predictive significance of mortality. Validation of HOTTIP target miRNA by dual-luciferase assay.

RESULTS

HOTTIP was persistently up-regulated in patients with ARDS sepsis than in patients without ARDS patients (P < 0.05). HOTTIP was a risk factor for the development of ARDS, which could be diagnosed in ARDS patients from non-ARDS patients (AUC = 0.847). Both the SOFA score (r = 0.6793) and the APACHE II score (r = 0.6384) were positively correlated with the HOTTIP levels. Furthermore, serum HOTTIP was an independent predictor of short-term mortality (HR = 4.813. 95%CI: 1.471-15.750, P = 0.009) and noticeably predicted the occurrence of short-term death (log rank = 0.020). miR-574-5p, a target miRNA for HOTTIP, was reduced in patients with sepsis ARDS and negatively correlated with HOTTIP.

CONCLUSIONS

The presence of HOTTIP serves as a diagnostic biomarker for the occurrence of ARDS, exhibits correlation with disease severity, and provides predictive value of short-term mortality in sepsis patients. HOTTIP may be involved in ARDS progression by targeting miR-574-5p.