Urinary metabolite profiling provides potential differentiation to explore the mechanisms of adjuvant-induced arthritis in rats

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning

INTRODUCTION

Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.

OBJECTIVES

To identify metabolites capable of classifying patients with PsA according to their disease activity.

METHODS

An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.

RESULTS

The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.

CONCLUSION

Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

Comprehensive Analysis of Long Non-Coding RNAs N4-Acetylcytidine in Alzheimer's Disease Mice Model Using High-Throughput Sequencing

BACKGROUND

N4-acetylcytidine (ac4C), an important posttranscriptional modification, is involved in various disease processes. Long noncoding RNAs (lncRNAs) regulate gene expression mainly through epigenetic modification, transcription, and posttranscriptional modification. Alzheimer's disease (AD) is a neurodegenerative disease characterized by amyloidosis of the brain. However, the role of lncRNA ac4C modification in AD remains unclear.

OBJECTIVE

In this study, we investigated the association between ac4C modification and AD, and the underlying mechanisms of ac4C modification in AD.

METHODS

The male 9-month-old APP/PS1 double transgenic mice, age- and sex-matched wild type (WT) mice were used in this study. Then, ac4C-RIP-seq and RNA-seq were used to comprehensively analyze lncRNA ac4C modification in AD mice. The lncRNA-miRNA-mRNA regulatory networks using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed the regulatory relationships among these three lncRNAs and AD.

RESULTS

The results showed that there were 120 significantly different ac4C peaks located on 102 lncRNAs in AD, of which 55 were hyperacetylated and 47 were hypoacetylated. Simultaneously, 231 differentially expressed lncRNAs were identified, including 138 upregulated lncRNAs and 93 downregulated lncRNAs. Moreover, 3 lncRNAs, lncRNA Gm26508, lncRNA A430046D13Rik, and lncRNA 9530059O14Rik, showed significant changes in both the ac4C and RNA levels using conjoint analysis.

CONCLUSION

The abundance of lncRNA ac4C modification is significantly different in AD and indicates that lncRNA ac4C is associated with the occurrence and development of AD, which could provide a basis for further exploration of the related regulatory mechanisms.

Gut microbiota-derived metabolites in inflammatory diseases based on targeted metabolomics

The gut microbiota plays an important role in inflammatory diseases. Metabolites in the three metabolic pathways of tryptophan (Trp), histidine (His), and phenylalanine (Phe) can affect various inflammatory conditions, such as obesity, diabetes, arthritis, colitis, atherosclerosis, and neuroinflammation. We established an LC–MS/MS method to measure 17 metabolites—Trp, 3-indole-acetic acid (Iaa), 3-indole-lactate (Ila), 3-indole-propionic acid (Ipa), 3-indole formaldehyde (Iald), kynurenine (Kn), kynurenic acid (Kyna), 3-Hydroxyanthranilic acid (3-Haa), His, 3-methylhistidine (3-Mhis), histamine (Hist), imidazole propionic acid (Imp), 4-imidazoacetic acid (Imaa), urocanic acid (Ua), Phe, phenylethylamine (Pea), and hippuric acid (Ha)—in the three metabolic pathways. The method exhibited high sensitivity and good selectivity, linearity, accuracy, precision, stability; and recovery rate; all met the requirements of biological sample analysis. By establishing a rheumatoid arthritis (RA) model of Sprague–Dawley rats and performing 16S rRNA sequencing on their feces, it was found that there was dysbiosis, including changes in phylum level, genus level, and α biodiversity of gut bacteria. The contents of the microbiota metabolites Iaa and Ipa in the model group were significantly decreased, and those of Iald, Kn, Kyna, Ha, and Imp were significantly increased. The common therapeutic drugs Tripterygium glycosides, total glucosides of peony, and their main active ingredients were screened by in vitro incubation with gut bacteria: it was found that Tripterygium glycosides and their active ingredients could lead to a variation in metabolites in the Trp and Phe pathways. Total glucosides and active components of peony could lead to a variation in metabolites in the Phe pathway of the gut microbiota.

Hippuric acid: Could became a barometer for frailty and geriatric syndromes?

Aging is a natural biological event that has some downsides such as increased frailty, decline in cognitive and physical functions leading to chronical diseases, and lower quality of life. There is therefore a pressing need of reliable biomarkers to identify populations at risk of developing age-associated syndromes in order to improve their quality of life, promote healthy ageing and a more appropriate clinical management, when needed. Here we discuss the importance of hippuric acid, an endogenous co-metabolite, as a possible hallmark of human aging and age-related diseases, summarizing the scientific literature over the last years. Hippuric acid, the glycine conjugate of benzoic acid, derives from the catabolism by means of intestinal microflora of dietary polyphenols found in plant-based foods (e.g. fruits, vegetables, tea and coffee). In healthy conditions hippuric acid levels in blood and/or urine rise significantly during aging while its excretion drops in conditions related with aging, including cognitive impairments, rheumatic diseases, sarcopenia and hypomobility. This literature highlights the utility of hippuric acid in urine and plasma as a plausible hallmark of frailty, related to low fruit and vegetable intake and changes in gut microflora.

Astragaloside regulates lncRNA LOC100912373 and the miR‑17‑5p/PDK1 axis to inhibit the proliferation of fibroblast‑like synoviocytes in rats with rheumatoid arthritis

Previous studies have confirmed that astragaloside (AST) exerts a positive effect on alleviating synovial and joint injury in rheumatoid arthritis (RA). However, the precise mechanisms through which AST acts in the treatment of RA remain unclear. Long non-coding RNA (lncRNA) LOC100912373 was identified as a key gene related to RA and has been proven to interact with miR-17-5p, in order to regulate the pyruvate dehydrogenase kinase 1 and protein kinase B axis (PDK1/AKT axis). The present study aimed to determine whether AST may treat RA through the interaction between lncRNA LOC100912373 and the miR-17-5p/PDK1 axis. MTT assays and flow cytometry were used to detect the proliferation and cell cycle progression of AST-treated fibroblast-like synoviocytes (FLSs). The expression of lncRNA LOC100912373 and miR-17-5p, as well as relative the mRNA expression of the PDK1 and AKT genes following AST intervention was detected by reverse transcription-quantitative PCR (RT-qPCR), immunofluorescence and western blot analysis. The results revealed that AST inhibited FLS proliferation, reduced lncRNA LOC100912373 expression levels, increased miR-17-5p expression levels, and decreased the PDK1 and p-AKT expression levels. Additionally, consecutive rescue experiments revealed that AST counteracted the effects of lncRNA LOC100912373 overexpression on FLS proliferation and cell cycle progression. On the whole, the present study demonstrates that AST inhibits FLS proliferation by regulating the expression of lncRNA LOC100912373 and the miR-17-5p/PDK1 axis.

Screening the Q-markers of TCMs from RA rat plasma using UHPLC-QTOF/MS technique for the comprehensive evaluation of Wu-Wei-Wen-Tong Capsule

The appropriate selection of quality marker (Q-marker) for performing the comprehensive quality evaluation of traditional Chinese medicines (TCMs) has much more significance. Wu-Wei-Wen-Tong Capsule (WWWTC), a TCMs prescription, is mainly utilized to treat rheumatoid arthritis (RA) in China. However, the comprehensive quality control for WWWTC has not been achieved because of lacking system analysis for the Q-marker. In this study, a dual wavelength, 203 and 270 nm, was selected based on the feature of 15 Q-markers, and a reliable UHPLC-UV fingerprinting approach was established, achieving the comprehensive quality evaluation of WWWTC. First, we identified 91 prototypes in rat plasma after administering a set amount of WWWTC by using UHPLC-QTOF/MS technique and selected them as the candidate Q-markers. Next, based on the "five principles" of Q-marker selection, 15 absorbed components among them including coumarin, cinnamic acid, cinnamaldehyde, cinnamic alcohol, and 2-methoxycinnamaldehyde derived from Monarch medicine of Cmnamomi Mmulus; epimedin C, icariin, baohuoside I, and anhydroicaritin derived from Monarch medicine Epimedii Folium; germacrone, the sesquiterpene compound in Minister medicine Rhizoma Wenyujin Concisum; pachymic acid, the tetracyclic triterpenoid acids in Assistant medicine Poria; baicalin, baicalein, wogonin, and wogonoside in Guide medicine Scutellariae Radix, respectively, were seriously chosen as the Q-markers, indicating preferable pharmacological effect on RA, characterization of transitivity and traceability as well as measurable components in WWWTC. The effective and meaningful strategy displayed a unique perspective for the exploration of Q-markers in the quality evaluation and further ensured efficacy and safety of the TCMs.

Transcriptome-Wide High-Throughput m6A Sequencing of Differential m6A Methylation Patterns in the Human Rheumatoid Arthritis Fibroblast-Like Synoviocytes Cell Line MH7A

Introduction

N6-methyladenosine (m6A) is the most frequent internal modification in eukaryotic mRNAs and is closely related to the occurrence and development of many diseases, especially tumors. However, the relationship between m6A methylation and rheumatoid arthritis (RA) is still a mystery.

Methods

Two high-throughput sequencing methods, namely, m6A modified RNA immunoprecipitation sequence (m6A-seq) and RNA sequence (RNA-seq) were performed to identify the differentially expressed m6A methylation in human rheumatoid arthritis fibroblast-like synoviocytes cell line MH7A after stimulation with TNF-α. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to obtain enriched GO terms and significant KEGG pathways. Then, four candidate genes, Wilms tumor 1-associating protein (WTAP), receptor-interacting serine/threonine protein kinase 2 (RIPK2), Janus kinase 3 (JAK3) and tumor necrosis factor receptor SF10A (TNFRSF10A) were selected to further validate the m6A methylation, mRNA and protein expression levels in MH7A cells and synovial tissues of adjuvant arthritis (AA) rats by RT-qPCR and Western blot.

Results

Using m6A-seq, we identified a total of 206 genes with differentially expressed m6A methylation, of which 118 were significantly upregulated and 88 genes were significantly downregulated. Likewise, 1207 differentially mRNA expressed mRNAs were obtained by RNA-seq, of which 793 were upregulated and 414 downregulated. Further joint analysis showed that the m6A methylation and mRNA expression levels of 88 genes changed significantly, of which 30 genes displayed increased m6A methylation and decreased mRNA expression, 57 genes displayed decreased m6A methylation and increased mRNA expression increased, and 1 gene displayed increased m6A methylation and increased mRNA expression. GO and KEGG analyses indicated that these unique genes were mainly enriched in inflammation-related pathways, cell proliferation and apoptosis. In addition, the validations of WTAP, RIPK2, JAK3 and TNFRSF10A were in accordance with the m6A and RNA sequencing results.

Conclusion

This study established the transcriptional map of m6A in MH7A cells and revealed the potential relationship between RNA methylation modification and RA related genes. The results suggested that m6A modification was associated with the occurrence and course of RA to some extent.

lncRNAS56464.1 as a ceRNA promotes the proliferation of fibroblast‑like synoviocytes in experimental arthritis via the Wnt signaling pathway and sponges miR‑152‑3p

Rheumatoid arthritis (RA) is an autoimmune disease that occurs in approximately 1.0% of the general population. In RA patients, physical disability and joint damage are the major prognostic factors, which are associated with a reduction in the quality of life and early mortality. At present, the exact molecular mechanism of RA remains elusive. Long noncoding RNAs (lncRNAs) have been revealed to play a regulatory role in the pathogenesis of RA. To reveal the function of lncRNAs in rheumatoid arthritis, lncRNAS56464.1 was screened to verify its targeting of the microRNA (miR)-152-3p/Wnt pathway and its effect on the proliferation of fibroblast-like synoviocytes (FLS). In the present study, based on the competing endogenous RNA (ceRNA) theory, siRNA was designed for transfection into FLS to calculate the lncRNAS56464.1 interference efficiency and then the effect of lncRNAS56464.1 interference on FLS proliferation was detected by MTT assay. Then, lncRNAS56464.1 targeting of the miR-152-3p/Wnt pathway was detected by a dual-luciferase reporter assay. In addition, RT-qPCR, immunofluorescence and western blotting techniques were employed to detect the expression of lncRNAS56464.1, miR-152-3p and some key genes of the Wnt signaling pathway in FLS after lncRNAS56464.1 interference. The results revealed that lncRNAS56464.1 could combine with miR-152-3p and promoted the proliferation of FLS. In addition, lncRNAS56464.1 interference could not only decrease the proliferation of FLS and the expression of Wnt1, β-catenin, c-Myc, cyclin D1, and p-GSK-3β/GSK-3β, but it also increased the expression of SFRP4. The present data indicated that lncRNAS56464.1 could target the miR-152-3p/Wnt pathway to induce synovial cell proliferation and then participate in the pathogenesis of RA.

The related mechanism of complete Freund's adjuvant-induced chronic inflammation pain based on metabolomics analysis

Chronic inflammation pain is a debilitating disease, and its mechanism still remains poorly understood. This study attempted to illuminate the metabolic mechanism of chronic inflammation pain induced by complete Freund’s adjuvant (CFA) injection, especially at spinal level. The chronic inflammation pain model was established by CFA administration. Behavioral testing including mechanical allodynia and thermal hyperalgesia was performed. Meanwhile, a liquid chromatography–mass spectrometry‐based metabolomics approach was applied to analyze potential metabolic biomarkers. The orthogonal partial least squares discrimination analysis mode was employed for determining metabolic changes, and a western blot was performed to detect the protein expression change. The results showed that 27 metabolites showed obviously abnormal expression and seven metabolic pathways were significantly enriched, comprising aminoacyl‐tRNA biosynthesis, arginine and proline metabolism, histidine metabolism, purine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, glutathione metabolism, and phenylalanine metabolism. Meanwhile, the results showed that the expression of arginase I and nitric oxide levels were elevated in the CFA group compared with the control group, while the argininosuccinate synthetase and argininosuccinatelyase proteins were not significantly different between the groups. These findings demonstrate that metabolic changes of the spinal cord may be implicated in neurotransmitter release and pain conductivity following CFA administration.

Tartronic acid promotes de novo lipogenesis and inhibits CPT-1β by upregulating acetyl-CoA and malonyl-CoA

As a dicarboxylic acid with the structural formula HOOCCH (OH) COOH, tartronic acid is considered as an inhibitor of the transformation of carbohydrates into fat under fat-deficient diet conditions. However, the effect of tartronic acid on lipogenesis under high-fat diet conditions has yet to be established. In this work, we investigated the regulatory role of tartronic acid in lipogenesis in 3T3-L1 adipocytes and C57BL/6J mice. The results confirmed that tartronic acid promoted weight gain (without affecting food intake) and induced adipocyte hypertrophy in epididymal white adipose tissue and lipid accumulation in the livers of high-fat diet-induced obese mice. In vitro, tartronic acid promoted 3T3-L1 adipocyte differentiation by increasing the protein expression of FABP-4, PPARγ and SREBP-1. Moreover, the contents of both acetyl-CoA and malonyl-CoA were significantly upregulated by treatment with tartronic acid, while the protein expression of CPT-1β were inhibited. In summary, we proved that tartronic acid promotes lipogenesis by serving as substrates for fatty acid synthesis and inhibiting CPT-1β, providing a new perspective for the study of tartronic acid.

A blood metabolomics study of metabolic variations in Inner Mongolia white cashmere goats under shortened and natural photoperiod conditions

This study investigated metabolic variations by using gas chromatography – mass spectrometry (GC–MS)-based metabolomics in the blood of Inner Mongolia white cashmere goats under shortened and natural photoperiod conditions. Twenty-four female (non-pregnant) Inner Mongolia white cashmere goats aged 1–1.5 yr with similar live weights (mean, 20.36 ± 2.63 kg) were randomly allocated into two groups: a natural daily photoperiod group (NDPP group: 10–16 h light, n = 12) and a short daily photoperiod group (SDPP group: 7 h light:17 h dark, n = 12). In this study, we found that a SDPP promoted the blood metabolic perturbations based on the GC–MS-based metabolomics investigation, and nine metabolites were related to a SDPP. Compared with the NDPP group, the contents of serine, oxaloacetic acid, xylose, l-3,4-dihydroxyphenylalanine, and xanthosine significantly were up-regulated, whereas the contents of carnitine, 1,3-diaminopropane, indole-3-acetic acid, and l-kynurenine were significantly down-regulated in the SDPP group. The different metabolites could contribute to the regulation mechanisms of promoting cashmere growth of goats in the SDPP group.

Effect of astragalosides on long non-coding RNA expression profiles in rats with adjuvant-induced arthritis

Rheumatoid arthritis (RA) is an autoimmune disease of unknown etiology, which occurs in ~1.0% of the general population. Increasing studies have suggested that long non-coding RNAs (lncRNAs) may serve important roles in various biological processes and may be associated with the pathogenesis of different types of disease, including RA. Astragalosides (AST) has been used as a traditional Chinese medicine for the treatment of RA. However, the mechanism underlying its therapeutic effect has remained unclear to date. Thus, there is an urgent need to elucidate the possible mechanism of AST in the treatment of RA from the perspective of lncRNAs. In the present study, the lncRNAs and mRNAs of a vehicle group, animal model group and AST treatment (control) group were determined by Arraystar Rat lncRNA/mRNA microarray. The differentially expressed genes with a fold change >1.5 and P<0.05 were selected and analyzed. Gene Ontology (GO) and pathway analysis was performed using the Database for Annotation, Visualization and Integration Discovery, and the coding-non-coding gene co-expression network was drawn based on the correlation analysis between the differentially expressed lncRNAs and mRNAs. Based on node degree and the correlation between bioinformatics analysis and RA, the critical differentially expressed lncRNAs were selected, analyzed and verified by reverse transcription-quantitative PCR (RT-qPCR) analysis. The results showed that, following AST treatment, up to 75 lncRNAs and 247 mRNAs were found to be differentially expressed among the three groups. GO and pathway analysis manifested that 135 GO terms and 17 pathways were enriched by differentially expressed genes. Four lncRNAs (MRAK012530, MRAK132628, MRAK003448 and XR_006457) were selected as the critical lncRNAs and their trend in expression showed consistency between the RT-qPCR and microarray data. In conclusion, AST had a regulatory effect on differentially expressed lncRNAs during the development of RA, and four lncRNAs could be selected as critical therapeutic targets of AST.

Urinary metabolomics of complete Freund's adjuvant-induced hyperalgesia in rats

The aim of this study was to demonstrate the differences of metabolomics changes in a hyperalgesia model and find potent biomarkers of hyperalgesia. Seven rats were placed in metabolic cages. An emulsion containing 500 μg of Complete Freund's adjuvant (CFA) was used to induce hyperalgesia. Urine samples were collected prior to the injection of CFA and on post-injection days 1, 3 and 7. Ultraperformance liquid chromatography, coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS), was used for a quantitative analysis of urinary metabolic changes in the CFA-induced hyperalgesia model. Differences between the metabolic profiles of the rats in the four groups were analyzed using partial least squares discriminant analysis. Thirty-four potential urine metabolite biomarkers were identified, which changed in a trend similar to the pain threshold. These potential biomarkers were involved in 11 metabolic pathways, as follows: alanine, aspartate, and glutamate metabolism; ascorbate and aldarate metabolism; glycerolipid metabolism; glycerophospholipid metabolism; histidine metabolism; phenylalanine metabolism; sphingolipid metabolism; tryptophan metabolism; tyrosine metabolism; valine, leucine and isoleucine biosynthesis; and vitamin B6 metabolism. These results may improve our understanding of hyperalgesia and provide a basis for the clinical diagnosis of hyperalgesia.

Reconstruction and analysis of the lncRNA–miRNA–mRNA network based on competitive endogenous RNA reveal functional lncRNAs in rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease with an unknown etiology, occurring in approximately 1.0% of general population.

LncRNAs expression in adjuvant-induced arthritis rats reveals the potential role of LncRNAs contributing to rheumatoid arthritis pathogenesis

BACKGROUND

Long non-coding RNAs (LncRNAs) are an important class of widespread molecules involved in diverse biological functions, which are exceptionally expressed in numerous types of diseases. Currently, limited study on LncRNA in rheumatoid arthritis (RA) is available. In this study, we aimed to identify the specifically expressed LncRNA that are relevant to adjuvant-induced arthritis (AA) in rats, and to explore the possible molecular mechanisms of RA pathogenesis.

METHODS

To identify LncRNAs specifically expressed in rheumatoid arthritis, the expression of LncRNAs in synoviums of rats from the model group (n=3) was compared with that in the control group (n=3) using Arraystar Rat LncRNA/mRNA microarray and real-time polymerase chain reaction (RT-PCR).

RESULTS

Up to 260 LncRNAs were found to be differentially expressed (≥1.5-fold-change) in the synoviums between AA model and the normal rats (170 up-regulated and 90 down-regulated LncRNAs in AA rats compared with normal rats). Coding-non-coding gene co-expression networks (CNC network) were drawn based on the correlation analysis between the differentially expressed LncRNAs and mRNAs. Six LncRNAs, XR_008357, U75927, MRAK046251, XR_006457, DQ266363 and MRAK003448, were selected to analyze the relationship between LncRNAs and RA via the CNC network and GO analysis. Real-time PCR result confirmed that the six LncRNAs were specifically expressed in the AA rats.

CONCLUSIONS

These results revealed that clusters of LncRNAs were uniquely expressed in AA rats compared with controls, which manifests that these differentially expressed LncRNAs in AA rats might play a vital role in RA development. Up-regulation or down-regulation of the six LncRNAs might contribute to the molecular mechanism underlying RA. To sum up, our study provides potential targets for treatment of RA and novel profound understanding of the pathogenesis of RA.