Long non-coding RNA HOTAIR knockdown alleviates gouty arthritis through miR-20b upregulation and NLRP3 downregulation

Analysis of the effectiveness and safety of Jiedu Xiezhuo Yishen Tang in the treatment of gouty arthritis: An observational study

This study is for exploring the effectiveness and security of Jiedu Xiezhuo Yishen Tang in the treatment of gouty arthritis. This retrospective study collected 100 patients with gouty arthritis between February 2022 and February 2023. According to the different treatment methods, the data of patients were divided into control group and experimental group. The control group received routine treatment with benzbromarone, while the experimental group received additional treatment with Xuedu Xiezhuo Yishen Tang on the basis of the control group. The evaluation indicators for the effectiveness of treatment include serum levels of 8-hydroxydeoxyguanosine, 3-NT, interleukin-6, interleukin-10, interleukin-1β, tumor necrosis factor-α, C-reactive protein, erythrocyte sedimentation rate, urea nitrogen, creatinine, evaluation of knee joint function and pain level, traditional Chinese medicine syndrome score, and safety evaluation. After treatment, the overall treatment effect of the experimental group reached 98%, while the control group was 78%. After treatment, the differences in various indicators possessed statistical significance (SS) (P < .05). In the Lysholm score, the improvement in the experimental group was markedly more excellent than the control group, and the difference possessed SS (P < .05). In the NRS score, the experimental group's NRS score decreased from 8.39 to 1.08 before and after treatment, while the control group only decreased to 3.61. In addition, both groups of patients showed significant improvement in the joint score in the Traditional Chinese medicine syndrome sub-items. The experimental group was able to effectively improve symptoms such as joint pain, joint redness and swelling, joint fever, and limited joint mobility. After treatment, the incidence of adverse reactions in the experimental group was only 8%, while the incidence of adverse reactions in the control group was 24%. After statistical analysis of the incidence of adverse reactions during treatment among the participants, it was found that the difference possessed SS (P < .001). The combination treatment of Jiedu Xiezhuo Yishen Tang and benbromarone can effectively improve oxidative stress response and significantly reduce blood uric acid levels. Meanwhile, this combination therapy can effectively inhibit inflammatory reactions, significantly alleviate knee joint pain, and promote the recovery of knee joint function. This treatment regimen has lower toxic side effects and higher safety.

Stefin B alleviates the gouty arthritis in mice by inducing the M2 polarization of macrophages

The present study aims to explore the therapeutic effect of Stefin B on gouty arthritis (GA) and the polarization of macrophages in mice. Stefin B-overexpressed or knockdown M0 macrophages were constructed. The GA model was established in mice by injecting 25 mg/mL MSU, followed by a single injecting of Stefin B-overexpressing adenovirus vector (GA model + Stefin B OE) or an empty vector (GA model + Stefin B OE NC). Stefin B was found lowly expressed in M1 macrophages. CD206 was markedly upregulated and IL-10 release was signally increased in Stefin B-overexpressed macrophages. In gouty arthritis mice, marked redness and swelling were observed in the ankle joint. Dramatical infiltration of inflammatory cells was observed in the GA model and GA model + Stefin B OE NC groups, which was suppressed in the Stefin B OE group. Increased proportion of F4/80+CD86+ cells observed in GA mice was markedly repressed by Stefin B overexpression, accompanied by the declined level of Caspase-1 and IL-17. Collectively, Stefin B alleviated the GA in mice by inducing the M2 polarization of macrophages.

Total Saponin Fraction of Dioscorea Nipponica Makino Improves Gouty Arthritis Symptoms in Rats via M1/M2 Polarization of Monocytes and Macrophages Mediated by Arachidonic Acid Signaling

OBJECTIVE

To explore the mechanism of effects of total saponin fraction from Dioscorea Nipponica Makino (TSDN) on M1/M2 polarization of monocytes/macrophages and arachidonic acid (AA) pathway in rats with gouty arthritis (GA).

METHODS

Seventy-two Sprague Dawley rats were randomly divided into 4 groups (n=18 in each): normal, model, TSDN at 160 mg/kg, and celecoxib at 43.3 mg/kg. Monosodium urate crystal (MSU) was injected into the rats' ankle joints to induce an experimental GA model. Blood and tissue samples were collected on the 3rd, 5th, and 8th days of drug administration. Histopathological changes in the synovium of joints were observed via hematoxylin and eosin (HE) staining. The expression levels of arachidonic acid (AA) signaling pathway were assessed via real-time polymerase chain reaction (qPCR) and Western blot. Flow cytometry was used to determine the proportion of M1 and M2 macrophages in the peripheral blood. An enzyme-linked immunosorbent assay (ELISA) was used to detect interleukine (IL)-1 β, tumor necrosis factor-alpha (TNF-α), IL-4, IL-10, prostaglandin E2 (PGE2), and leukotriene B4 (LTB4).

RESULTS

HE staining showed that TSDN improved the synovial tissue. qPCR and Western blot showed that on the 3rd, 5th and 8th days of drug administration, TSDN reduced the mRNA and protein expressions of cyclooxygenase (COX)2, microsomal prostaglandin E synthase-1 derived eicosanoids (mPGES-1), 5-lipoxygenase (5-LOX), recombinant human mothers against decapentaplegic homolog 3 (Smad3), nucleotide-binding oligomerization domain-like receptor protein 3 (NALP3), and inducible nitric oxide synthase (iNOS) in rats' ankle synovial tissues (P<0.01). TSDN decreased COX1 mRNA and protein expression on 3rd and 5th day of drug administration and raised it on the 8th day (both P<0.01). It lowered CD68 protein expression on days 3 (P<0.01), as well as mRNA and protein expression on days 5 and 8 (P<0.01). On the 3rd, 5th, and 8th days of drug administration, TSDN elevated the mRNA and protein expression of Arg1 and CD163 (P<0.01). Flow cytometry results showed that TSDN decreased the percentage of M1 macrophages while increasing the percentage of M2 in peripheral blood (P<0.05 or P<0.01). ELISA results showed that on the 3rd, 5th, and 8th days of drug administration, TSDN decreased serum levels of IL-1 β, TNF-α, and LTB4 (P<0.01), as well as PGE2 levels on days 3rd and 8th days (P<0.05 or P<0.01); on day 8 of administration, TSDN increased IL-4 serum levels and enhanced IL-10 contents on days 5 and 8 (P<0.05 or P<0.01).

CONCLUSION

The anti-inflammatory effect of TSDN on rats with GA may be achieved by influencing M1/M2 polarization through AA signaling pathway.

lncRNA HOTAIR promotes ROS generation and NLRP3 inflammasome activation by inhibiting Nrf2 in diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is a microvascular complication associated with damage to the retina due to inflammation induced by high glucose. Activation of the NLRP3 inflammasome plays a critical role in DR and its prevention is beneficial to patients. However, the regulation of long non-coding RNA (lncRNA) in NLRP3 inflammasome activation of DR is incompletely understood. So, this study aimed to uncover the functional and regulatory mechanism of the lncRNA HOTAIR in NLRP3 inflammasome activation in Dr.

METHODS

The vitreous humor was collected from the patients and detected the inflammatory and oxidative stress makers. Human retinal endothelial cells (HRECs) were cultured and stimulated in low D-glucose (5 mmol/L) or high D-glucose (20 mmol/L). Additionally, HRECs were knocked down HOTAIR with a si-RNA. Then, the NLRP3 inflammasome activation was analyzed by western blotting and pyroptosis cell imaging. The ROS was measured by specific probe. The activation of Nrf2 measured by Immunofluorescent staining. The interaction between HOTAIR and Nrf2 was evaluated by co-immunoprecipitation and RNA immunoprecipitation.

RESULTS

The expression of HOTAIR was significantly increased in the vitreous of patients with DR and in HRECs stimulated with high glucose. Furthermore, HOTAIR knockdown relieved NLRP3 inflammasome activation. More specifically, HOTAIR knockdown suppressed the expression of NLRP3, pro-caspase-1, and pro-IL-1β, as well as IL-1β maturation and pyroptosis. HOTAIR knockdown also interfered with the ROS generation induced by high glucose. Moreover, HOTAIR promoted the interaction between Nrf2 and Keap1 by binding and inactivating Nrf2.

CONCLUSION

The lncRNA HOTAIR promotes NLRP3 inflammasome activation and ROS generation by inhibiting Nrf2 in Dr.

New drug targets for the treatment of gout arthritis: what's new?

INTRODUCTION

Gout arthritis (GA) is an intermittent inflammatory disease affecting approximately 10% of the worldwide population. Symptomatic phases (acute flares) are timely spaced by asymptomatic periods. During an acute attack, redness, joint swelling, limited movement, and excruciating pain are common symptoms. However, the current available therapies are not fully effective in reducing symptoms and offer numerous side effects. Therefore, unveiling new drug targets and effector molecules are required in developing novel GA therapeutics.

AREAS COVERED

This review discusses the pathophysiological mechanisms of GA and explores potential pharmacological targets to ameliorate disease outcome. In addition, we listed promising pre-clinical studies demonstrating effector molecules with therapeutical potential. Among those, we emphasized the importance of natural products, including traditional Chinese medicine formulas and their multitarget mechanisms of action.

EXPERT OPINION

In our search, we observed that there is a massive gap between pre-clinical and clinical knowledge. Only a minority (4.4%) of clinical trials aimed to intervene by applying natural products or current hot targets described herein. In this sense, we envisage four possibilities for GA therapeutics, which include the repurposing of existing therapies, ALX/FPR2 agonism for improvement in disease outcome, the use of multitarget drugs (e.g. natural products), and targeting the neuroinflammatory component of GA.

Genetic and Epigenetic Regulation of the Innate Immune Response to Gout

Gout is a disease caused by uric acid (UA) accumulation in the joints, causing inflammation. Two UA forms - monosodium urate (MSU) and soluble uric acid (sUA) have been shown to interact physically with inflammasomes, especially with the nod-like receptor (NLR) family pyrin domain containing 3 (NLRP3), albeit the role of the immune response to UA is poorly understood, given that asymptomatic hyperuricemia does also exist. Macrophage phagocytosis of UA activate NLRP3, lead to cytokines release, and ultimately, lead to chemoattract neutrophils and lymphocytes to the gout flare joint spot. Genetic variants of inflammasome genes and of genes encoding their molecular partners may influence hyperuricemia and gout susceptibility, while also influencing other comorbidities such as metabolic syndrome and cardiovascular diseases. In this review, we summarize the inflammatory responses in acute and chronic gout, specifically focusing on innate immune cell mechanisms and genetic and epigenetic characteristics of participating molecules. Unprecedently, a novel UA binding protein - the neuronal apoptosis inhibitor protein (NAIP) - is suggested as responsible for the asymptomatic hyperuricemia paradox.Abbreviation: β2-integrins: leukocyte-specific adhesion molecules; ABCG2: ATP-binding cassete family/breast cancer-resistant protein; ACR: American college of rheumatology; AIM2: absent in melanoma 2, type of pattern recognition receptor; ALPK1: alpha-protein kinase 1; ANGPTL2: angiopoietin-like protein 2; ASC: apoptosis-associated speck-like protein; BIR: baculovirus inhibitor of apoptosis protein repeat; BIRC1: baculovirus IAP repeat-containing protein 1; BIRC2: baculoviral IAP repeat-containing protein 2; C5a: complement anaphylatoxin; cAMP: cyclic adenosine monophosphate; CARD: caspase activation and recruitment domains; CARD8: caspase recruitment domain-containing protein 8; CASP1: caspase 1; CCL3: chemokine (C-C motif) ligand 3; CD14: cluster of differentiation 14; CD44: cluster of differentiation 44; Cg05102552: DNA-methylation site, usually cytosine followed by guanine nucleotides; contains arbitrary identification code; CIDEC: cell death-inducing DNA fragmentation factor-like effector family; CKD: chronic kidney disease; CNV: copy number variation; CPT1A: carnitine palmitoyl transferase - type 1a; CXCL1: chemokine (CXC motif) ligand 1; DAMPs: damage associated molecular patterns; DC: dendritic cells; DNMT(1): maintenance DNA methyltransferase; eQTL: expression quantitative trait loci; ERK1: extracellular signal-regulated kinase 1; ERK2: extracellular signal-regulated kinase 2; EULAR: European league against rheumatism; GMCSF: granulocyte-macrophage colony-stimulating factor; GWAS: global wide association studies; H3K27me3: tri-methylation at the 27th lysine residue of the histone h3 protein; H3K4me1: mono-methylation at the 4th lysine residue of the histone h3 protein; H3K4me3: tri-methylation at the 4th lysine residue of the histone h3 protein; HOTAIR: human gene located between hoxc11 and hoxc12 on chromosome 12; IκBα: cytoplasmatic protein/Nf-κb transcription inhibitor; IAP: inhibitory apoptosis protein; IFNγ: interferon gamma; IL-1β: interleukin 1 beta; IL-12: interleukin 12; IL-17: interleukin 17; IL18: interleukin 18; IL1R1: interleukin-1 receptor; IL-1Ra: interleukin-1 receptor antagonist; IL-22: interleukin 22; IL-23: interleukin 23; IL23R: interleukin 23 receptor; IL-33: interleukin 33; IL-6: interleukin 6; IMP: inosine monophosphate; INSIG1: insulin-induced gene 1; JNK1: c-jun n-terminal kinase 1; lncRNA: long non-coding ribonucleic acid; LRR: leucine-rich repeats; miR: mature non-coding microRNAs measuring from 20 to 24 nucleotides, animal origin; miR-1: miR followed by arbitrary identification code; miR-145: miR followed by arbitrary identification code; miR-146a: miR followed by arbitrary identification code, "a" stands for mir family; "a" family presents similar mir sequence to "b" family, but different precursors; miR-20b: miR followed by arbitrary identification code; "b" stands for mir family; "b" family presents similar mir sequence to "a" family, but different precursors; miR-221: miR - followed by arbitrary identification code; miR-221-5p: miR followed by arbitrary identification code; "5p" indicates different mature miRNAs generated from the 5' arm of the pre-miRNA hairpin; miR-223: miR followed by arbitrary identification code; miR-223-3p: mir followed by arbitrary identification code; "3p" indicates different mature miRNAs generated from the 3' arm of the pre-miRNA hairpin; miR-22-3p: miR followed by arbitrary identification code, "3p" indicates different mature miRNAs generated from the 3' arm of the pre-miRNA hairpin; MLKL: mixed lineage kinase domain-like pseudo kinase; MM2P: inductor of m2-macrophage polarization; MSU: monosodium urate; mTOR: mammalian target of rapamycin; MyD88: myeloid differentiation primary response 88; n-3-PUFAs: n-3-polyunsaturated fatty-acids; NACHT: acronym for NAIP (neuronal apoptosis inhibitor protein), C2TA (MHC class 2 transcription activator), HET-E (incompatibility locus protein from podospora anserina) and TP1 (telomerase-associated protein); NAIP: neuronal apoptosis inhibitory protein (human); Naip1: neuronal apoptosis inhibitory protein type 1 (murine); Naip5: neuronal apoptosis inhibitory protein type 5 (murine); Naip6: neuronal apoptosis inhibitory protein type 6 (murine); NBD: nucleotide-binding domain; Nek7: smallest NIMA-related kinase; NET: neutrophil extracellular traps; Nf-κB: nuclear factor kappa-light-chain-enhancer of activated b cells; NFIL3: nuclear-factor, interleukin 3 regulated protein; NIIMA: network of immunity in infection, malignancy, and autoimmunity; NLR: nod-like receptor; NLRA: nod-like receptor NLRA containing acidic domain; NLRB: nod-like receptor NLRA containing BIR domain; NLRC: nod-like receptor NLRA containing CARD domain; NLRC4: nod-like receptor family CARD domain containing 4; NLRP: nod-like receptor NLRA containing PYD domain; NLRP1: nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing 1; NLRP12: nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing 12; NLRP3: nod-like receptor family pyrin domain containing 3; NOD2: nucleotide-binding oligomerization domain; NRBP1: nuclear receptor-binding protein; Nrf2: nuclear factor erythroid 2-related factor 2; OR: odds ratio; P2X: group of membrane ion channels activated by the binding of extracellular; P2X7: p2x purinoceptor 7 gene; p38: member of the mitogen-activated protein kinase family; PAMPs: pathogen associated molecular patters; PBMC: peripheral blood mononuclear cells; PGGT1B: geranylgeranyl transferase type-1 subunit beta; PHGDH: phosphoglycerate dehydrogenase; PI3-K: phospho-inositol; PPARγ: peroxisome proliferator-activated receptor gamma; PPARGC1B: peroxisome proliferative activated receptor, gamma, coactivator 1 beta; PR3: proteinase 3 antigen; Pro-CASP1: inactive precursor of caspase 1; Pro-IL1β: inactive precursor of interleukin 1 beta; PRR: pattern recognition receptors; PYD: pyrin domain; RAPTOR: regulatory associated protein of mTOR complex 1; RAS: renin-angiotensin system; REDD1: regulated in DNA damage and development 1; ROS: reactive oxygen species; rs000*G: single nuclear polymorphism, "*G" is related to snp where replaced nucleotide is guanine, usually preceded by an id number; SLC2A9: solute carrier family 2, member 9; SLC7A11: solute carrier family 7, member 11; SMA: smooth muscular atrophy; Smac: second mitochondrial-derived activator of caspases; SNP: single nuclear polymorphism; Sp3: specificity protein 3; ST2: serum stimulation-2; STK11: serine/threonine kinase 11; sUA: soluble uric acid; Syk: spleen tyrosine kinase; TAK1: transforming growth factor beta activated kinase; Th1: type 1 helper T cells; Th17: type 17 helper T cells; Th2: type 2 helper T cells; Th22: type 22 helper T cells; TLR: tool-like receptor; TLR2: toll-like receptor 2; TLR4: toll-like receptor 4; TNFα: tumor necrosis factor alpha; TNFR1: tumor necrosis factor receptor 1; TNFR2: tumor necrosis factor receptor 2; UA: uric acid; UBAP1: ubiquitin associated protein; ULT: urate-lowering therapy; URAT1: urate transporter 1; VDAC1: voltage-dependent anion-selective channel 1.

Role of NLRP3 in the pathogenesis and treatment of gout arthritis

Gout arthritis (GA) is a common and curable type of inflammatory arthritis that has been attributed to a combination of genetic, environmental and metabolic factors. Chronic deposition of monosodium urate (MSU) crystals in articular and periarticular spaces as well as subsequent activation of innate immune system in the condition of persistent hyperuricemia are the core mechanisms of GA. As is well known, drugs for GA therapy primarily consists of rapidly acting anti-inflammatory agents and life-long uric acid lowering agents, and their therapeutic outcomes are far from satisfactory. Although MSU crystals in articular cartilage detected by arthrosonography or in synovial fluid found by polarization microscopy are conclusive proofs for GA, the exact molecular mechanism of NLRP3 inflammasome activation in the course of GA still remains mysterious, severely restricting the early diagnosis and therapy of GA. On the one hand, the activation of Nod-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome requires nuclear factor kappa B (NF-κB)-dependent transcriptional enhancement of NLRP3, precursor (pro)-caspase-1 and pro-IL-1β, as well as the assembly of NLRP3 inflammasome complex and sustained release of inflammatory mediators and cytokines such as IL-1β, IL-18 and caspase-1. On the other hand, NLRP3 inflammasome activated by MSU crystals is particularly relevant to the initiation and progression of GA, and thus may represent a prospective diagnostic biomarker and therapeutic target. As a result, pharmacological inhibition of the assembly and activation of NLRP3 inflammasome may also be a promising avenue for GA therapy. Herein, we first introduced the functional role of NLRP3 inflammasome activation and relevant biological mechanisms in GA based on currently available evidence. Then, we systematically reviewed therapeutic strategies for targeting NLRP3 by potentially effective agents such as natural products, novel compounds and noncoding RNAs (ncRNAs) in the treatment of MSU-induced GA mouse models. In conclusion, our present review may have significant implications for the pathogenesis, diagnosis and therapy of GA.

Epigenetic regulation in metabolic diseases: mechanisms and advances in clinical study

Epigenetics regulates gene expression and has been confirmed to play a critical role in a variety of metabolic diseases, such as diabetes, obesity, non-alcoholic fatty liver disease (NAFLD), osteoporosis, gout, hyperthyroidism, hypothyroidism and others. The term 'epigenetics' was firstly proposed in 1942 and with the development of technologies, the exploration of epigenetics has made great progresses. There are four main epigenetic mechanisms, including DNA methylation, histone modification, chromatin remodelling, and noncoding RNA (ncRNA), which exert different effects on metabolic diseases. Genetic and non-genetic factors, including ageing, diet, and exercise, interact with epigenetics and jointly affect the formation of a phenotype. Understanding epigenetics could be applied to diagnosing and treating metabolic diseases in the clinic, including epigenetic biomarkers, epigenetic drugs, and epigenetic editing. In this review, we introduce the brief history of epigenetics as well as the milestone events since the proposal of the term 'epigenetics'. Moreover, we summarise the research methods of epigenetics and introduce four main general mechanisms of epigenetic modulation. Furthermore, we summarise epigenetic mechanisms in metabolic diseases and introduce the interaction between epigenetics and genetic or non-genetic factors. Finally, we introduce the clinical trials and applications of epigenetics in metabolic diseases.

LncRNA UCA1 epigenetically suppresses APAF1 expression to mediate the protective effect of sevoflurane against myocardial ischemia-reperfusion injury

Myocardial ischemia-reperfusion injury (MI/RI) is a leading cause of death globally. Whereas some long noncoding RNAs (lncRNAs) are known to participate in the progression of MI/RI, the role of urothelial carcinoma associated 1 (UCA1) in conjunction with sevoflurane treatment remains largely unknown. H9C2 cardiomyocytes were subjected to hypoxia/reoxygenation (H/R) to establish an in vitro MI/RI model, and sevoflurane was then added. Cell viability, apoptosis, SOD activity, and MDA levels were measured. Levels of inflammatory cytokines and methylation of apoptosis protease-activating factor 1 (APAF1) were determined. Interactions among lncRNA UCA1, enhancer of zeste homologue 2 (EZH2), DNA methyltransferase-1 (DNMT1), and APAF1 were analyzed. After H/R treatment, the viability of H9C2 cardiomyocytes decreased and apoptosis rate, oxidative stress factor levels, inflammatory cytokine levels, and apoptosis-related protein levels all increased. Sevoflurane treatment reversed these changes. LncRNA UCA1 knockdown attenuated the therapeutic effect of sevoflurane on H/R-treated cardiomyocytes, and silencing of APAF1 reversed this role of UCA1 knockdown. Moreover, lncRNA UCA1 recruited DNMT1 through EZH2, thus promoting methylation of the APAF1 promoter region. LncRNA UCA1 recruits DNMT1 to promote methylation of the APAF1 promoter through EZH2, thus strengthening the protective effect of sevoflurane on H/R-induced cardiomyocyte injury.

Genotype Triad for HOTAIR rs10783618, LINC-ROR rs1942347, and MALAT1 rs3200401 as Molecular Markers in Systemic Lupus Erythematous

Accumulating evidence supports the implication of long non-coding RNAs (lncRNAs) in autoimmune diseases, including systemic lupus erythematosus (SLE). LncRNA variants could impact the development and/or outcome of the disease with variable diagnostic/prognostic utility in the clinic. We aimed to explore the contribution of HOTAIR (rs10783618), LINC-ROR (rs1942347), and MALAT1 (rs3200401) variants to SLE susceptibility and/or severity in 163 SLE patients and age-/sex-matched controls using real-time TaqMan allelic discrimination PCR. HOTAIR rs10783618*C/C was associated with a 77% increased risk of SLE (OR = 1.77, 95%CI = 1.09−2.87, p = 0.020) under the recessive model. Similarly, MALAT1 rs3200401*T/T carriers were three times more likely to develop SLE (OR = 2.89, 95%CI = 1.42−5.90) under the recessive model. While the rs3200401*T/C genotype was associated with a 49−57% decreased risk of SLE under codominant (OR = 0.51, 95%CI = 0.31−0.82, p < 0.001) and over-dominant (OR = 0.43, 95%CI = 0.27−0.68, p < 0.001) models. LINC-ROR rs1942347*A/A patients were more likely to have a positive family history of SLE. At the same time, HOTAIR rs10783618*C/C was associated with a higher frequency of arthritis (p = 0.001) and the presence of oral ulcers (p = 0.002), while patients carrying rs10783618*T/T genotype were more likely to develop hair loss (p < 0.001), weight loss (p = 0.001), and neurological symptoms (p = 0.003). In conclusion, the studied lncRNAs, HOTAIR, and MALAT1 gene polymorphisms confer susceptibility for SLE, providing a potential theoretical basis for their clinical translation in SLE disease.

Construction of lncRNA-miRNA-mRNA network based on ceRNA mechanism reveals the function of lncRNA in the pathogenesis of gout

Objective

To identify differentially expressed lncRNA, miRNA, and mRNA during the pathogenesis of gout, explore the ceRNA network regulatory mechanism of gout, and seek potential therapeutic targets.

Method

First, gout‐related chips were retrieved by GEO database. Then, the analysis of differentially expressed lncRNAs and mRNAs was conducted by R language and other software. Besides, miRNA and its regulated mRNA were predicted based on public databases, the intersection of differentially expressed mRNA and predicated mRNA was taken, and the lncRNA‐miRNA‐mRNA regulatory relationships were obtained to construct the ceRNA regulatory network. Subsequently, hub genes were screened by the STRING database and Cytoscape software. Then the DAVID database was used to illustrate the gene functions and related pathways of hub genes and to mine key ceRNA networks.

Results

Three hundred and eighty‐eight lncRNAs and 758 mRNAs were identified with significant differential expression in gout patient, which regulates hub genes in the ceRNA network, such as JUN, FOS, PTGS2, NR4A2, and TNFAIP3. In the ceRNA network, lncRNA competes with mRNA for miRNA, thus affecting the IL‐17 signaling pathway, TNF signaling pathway, Oxytocin signaling pathway, and NF‐κB signaling pathway through regulating the cell's response to chemical stress. The research indicates that five miRNAs (miR‐429, miR‐137, miR‐139‐5p, miR‐217, miR‐23b‐3p) and five lncRNAs (SNHG1, FAM182A, SPAG5‐AS1, HNF1A‐AS1, UCA1) play an important role in the formation and development of gout.

Conclusion

The interaction in the ceRNA network can affect the formation and development of gout by regulating the body's inflammatory response as well as proliferation, differentiation, and apoptosis of chondrocytes and osteoclasts. The identification of potential therapeutic targets and signaling pathways through ceRNA network can provide a reference for further research on the pathogenesis of gout.

Identification of Tissue-Specific Expressed Hub Genes and Potential Drugs in Rheumatoid Arthritis Using Bioinformatics Analysis

Background: Rheumatoid arthritis (RA) is a common autoimmune disease characterized by progressive, destructive polyarthritis. However, the cause and underlying molecular events of RA are not clear. Here, we applied integrated bioinformatics to identify tissue-specific expressed hub genes involved in RA and reveal potential targeted drugs.

Methods: Three expression profiles of human microarray datasets involving fibroblast-like synoviocytes (FLS) were downloaded from the Gene Expression Omnibus (GEO) database, the differentially expressed mRNAs (DEGs), miRNAs (DEMs), and lncRNAs (DELs) between normal and RA synovial samples were screened using GEO2R tool. BioGPS was used to identified tissue-specific expressed genes. Functional and pathway enrichment analyses were performed for common DEGs using the DAVID database, and the protein-protein interaction (PPI) network of common DEGs was constructed to recognize hub genes by the STRING database. Based on receiver operating characteristic (ROC) curve, we further investigated the prognostic values of tissue-specific expressed hub genes in RA patients. Connectivity Map (CMap) was run to identify novel anti-RA potential drugs. The DEM–DEG pairs and ceRNA network containing key DEMs were established by Cytoscape.

Results: We obtain a total of 418 DEGs, 23 DEMs and 49 DELs. 64 DEGs were verified as tissue-specific expressed genes, most derive from the hematologic/immune system (20/64, 31.25%). GO term and KEGG pathway enrichment analysis showed that DEGs focused primarily on immune-related biological process and NF-κB pathway. 10 hub genes were generated via using MCODE plugin. Among them, SPAG5, CUX2, and THEMIS2 were identified as tissue-specific expressed hub genes, these 3 tissue-specific expressed hub genes have superior diagnostic value in the RA samples compared with osteoarthritis (OA) samples. 5 compounds (troleandomycin, levodopa, trichostatin A, LY-294002, and levamisole) rank among the top five in connectivity score. In addition, 5 miRNAs were identified to be key DEMs, the lncRNA–miRNA–mRNA network with five key DEMs was formed. The networks containing tissue-specific expressed hub genes are as follows: ARAP1-AS2/miR-20b-3p/TRIM3, ARAP1-AS2/miR-30c-3p/FRZB.

Conclusion: This study indicates that screening for identify tissue-specific expressed hub genes and ceRNA network in RA using integrated bioinformatics analyses could help us understand the mechanism of development of RA. Besides, SPAG5 and THEMIS2 might be candidate biomarkers for diagnosis of RA. LY-294002, trichostatin A, and troleandomycin may be potential drugs for RA.

Epigenetic Changes and Functions in Pneumoconiosis

Pneumoconiosis is one of the most common occupational diseases in the world, and specific treatment methods of pneumoconiosis are lacking at present, so it carries great social and economic burdens. Pneumoconiosis, coronavirus disease 2019, and idiopathic pulmonary fibrosis all have similar typical pathological changes-pulmonary fibrosis. Pulmonary fibrosis is a chronic lung disease characterized by excessive deposition of the extracellular matrix and remodeling of the lung tissue structure. Clarifying the pathogenesis of pneumoconiosis plays an important guiding role in its treatment. The occurrence and development of pneumoconiosis are accompanied by epigenetic factors (e.g., DNA methylation and noncoding RNA) changes, which in turn can promote or inhibit the process of pneumoconiosis. Here, we summarize epigenetic changes and functions in the several kinds of evidence classification (epidemiological investigation, in vivo, and in vitro experiments) and main types of cells (macrophages, fibroblasts, and alveolar epithelial cells) to provide some clues for finding specific therapeutic targets for pneumoconiosis and even for pulmonary fibrosis.

Role of microRNA alternation in the pathogenesis of gouty arthritis

Gouty arthritis is a common inflammatory disease. The condition is triggered by a disorder of uric acid metabolism, which causes urate deposition and gout flares. MicroRNAs are a class of conserved small non-coding RNAs that bind to the 3' untranslated region (UTR) of mRNA and regulate the expression of a variety of proteins at the post-transcriptional level. In recent years, attention has been focused on the role of miRNAs in various inflammatory diseases, including gouty arthritis. It is thought that miRNAs may regulate immune function and inflammatory responses, thereby influencing the onset and progression of the disease. This article mainly reviewed the roles of miRNAs in the pathogenesis of gouty arthritis and prospected their potential as diagnostic and prognostic relevant biomarkers and as possible therapeutic targets.

Long noncoding RNA SNHG8 accelerates acute gouty arthritis development by upregulating AP3D1 in mice

Gout can affect the quality of life of patients due to monosodium urate monohydrate (MSU) crystals. Numerous studies have proposed that long noncoding RNAs (lncRNAs) regulate gout. We aimed to reveal the function of lncRNA small nucleolar RNA host gene 8 (SNHG8) in acute gouty arthritis (GA). A GA mouse model was established by injection of MSU into footpads. The levels of SNHG8, miR-542-3p and adaptor-related protein complex 3 subunit delta 1 (AP3D1) in footpads were detected via polymerase chain reaction analysis. Hematoxylin–eosin staining revealed the paw swelling in mice. Enzyme-linked immunosorbent assay and western blot analysis were applied to determine the concentrations of proinflammatory cytokines. SNHG8 expression was identified to be upregulated after MSU treatment. Ablation of SNHG8 decreased the MSU-induced enhancement of paw swelling and foot thickness. In addition, SNHG8 depletion decreased the protein levels of proinflammatory factors in GA mice. Mechanically, SNHG8 was verified to be a sponge of miR-542-3p, and miR-542-3p targeted AP3D1 3ʹ untranslated region. SNHG8 competitively bound with miR-542-3p to upregulate AP3D1 expression. Finally, results of rescue assays illustrated that AP3D1 upregulation offset the SNHG8-mediated inhibition on paw swelling and protein levels of proinflammatory factors in GA mice. In conclusion, SNHG8 accelerates acute GA development by upregulating AP3D1 in an miR-542-3p-dependent way in mice, providing an effective therapeutic approach to treat acute GA.

LncRNAs as a new regulator of chronic musculoskeletal disorder

Objectives

In recent years, long non‐coding RNAs (lncRNAs) have been found to play a role in the occurrence, progression and prognosis of chronic musculoskeletal disorders.

Design and methods

Literature exploring on PubMed was conducted using the combination of keywords 'LncRNA' and each of the following: 'osteoarthritis', 'rheumatoid arthritis', 'osteoporosis', 'osteogenesis', 'osteoclastogenesis', 'gout arthritis', 'Kashin‐Beck disease', 'ankylosing spondylitis', 'cervical spondylotic myelopathy', 'intervertebral disc degeneration', 'human muscle disease' and 'muscle hypertrophy and atrophy'. For each disorder, we focused on the publications in the last five years (5/1/2016‐2021/5/1, except for Kashin‐Beck disease). Finally, we excluded publications that had been reported in reviews of various musculoskeletal disorders during the last three years. Here, we summarized the progress of research on the role of lncRNA in multiple pathological processes during musculoskeletal disorders.

Results

LncRNAs play a crucial role in regulating downstream gene expression and maintaining function and homeostasis of cells, especially in chondrocytes, synovial cells, osteoblasts, osteoclasts and skeletal muscle cells.

Conclusions

Understanding the mechanisms of lncRNAs in musculoskeletal disorders may provide promising strategies for clinical practice.

Non-coding RNAs: The key regulators in NLRP3 inflammasome-mediated inflammatory diseases

Inflammasomes are multiprotein complexes responding to various microbes and endogenous danger signals, contributing to initiating the innate protective response of inflammatory diseases. NLRP3 inflammasome is a crucial regulator of pro-inflammatory cytokines (IL-1β and IL-18) production through activating caspase-1. Non-coding RNAs (ncRNAs) are a class of RNA transcripts lacking the ability to encode peptides or proteins. Its dysregulation leads to the development and progression of inflammation in diseases. Recently, accumulating evidence has indicated that NLRP3 inflammasome activation could be modulated by ncRNAs (lncRNAs, miRNAs, and circRNAs) in a variety of inflammatory diseases. This review focuses on the substantial role and function of ncRNAs in the NLRP3 inflammasome activation, providing novel insight for the future therapeutic approach of inflammatory diseases.