Serum Expression of Mir-488-3p Serves as a Non-Invasive Diagnostic Biomarker in Patients with Rheumatoid Arthritis

Summary

miR-488-3p may serve as a novel non-invasive diagnostic marker for RA. miR-488-3p modulates the biological function of synoviocytes via ROCK1. It exhibited a significant negative correlation with disease severity in RA patients.

Abstract

The diagnosis of rheumatoid arthritis (RA) remains challenging because of the limitations of existing biomarkers. The purpose of the study was to investigate the potential of miR-488-3p in serum as a biomarker for RA and to reveal its potential mechanism of action. The study included 135 RA patients, 130 osteoarthritis (OA) patients, and 125 healthy controls. miR-488-3p expression levels were examined by RT-qPCR. The mechanism of action was analyzed by functional tests (CCK-8, flow cytometry, ELISA) and target validation experiments (luciferase reporter gene, RIP). Serum miR-488-3p expression levels were significantly lower in RA patients than in osteoarthritis (OA) patients and healthy controls (p < 0.001). ROC curve analysis showed that miR-488-3p had a high diagnostic accuracy in distinguishing RA from healthy controls and OA patients. miR-488-3p negatively correlated with erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), rheumatoid factor (RF), and DAS28 scores. Functional validation revealed that overexpression of miR-488-3p inhibited the proliferation and inflammatory response of synoviocytes while inducing apoptosis. Mechanistic studies showed that miR-488-3p could directly target Rho-associated coiled-coil containing protein kinase 1 (ROCK1), which mediates its protective effects. Serum miR-488-3p holds promise as a novel non-invasive diagnostic marker for RA and protects synoviocyte from injury.

Introduction

Rheumatoid arthritis (RA) is a common autoimmune disease characterized by synovial inflammation, joint erosion, and destruction^1,2. The global prevalence of RA is about 0.5%–1%³, which seriously affects patients' quality of life and ability to work. The disease has an insidious onset, and early symptoms are often atypical and easily misdiagnosed or missed⁴. As the disease progresses, it can lead to joint deformity, loss of function, and even increase the risk of complications such as cardiovascular disease⁵ placing a substantial burden on patients, their families, and healthcare systems..

At present, a combination of clinical symptoms, signs, laboratory tests, and imaging evaluation is required for the diagnosis of RA⁶. Commonly used laboratory indicators include the erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), which are non-specific markers of systemic inflammation, as well as rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) antibodies, which are important serological biomarkers for RA^7,8. However, these traditional biomarkers have limitations: RF can be positive in some healthy people and patients with other autoimmune diseases (false-positive rate of about 5%); anti-CCP, although highly specific (>95%), has limited sensitivity in the early stages of the disease (about 60–70%)^4,9, and some patients with RA remain seronegative¹⁰. Therefore, it is important to find more sensitive and specific biomarkers for early diagnosis, disease monitoring, and prognosis assessment of RA¹¹.

MicroRNAs (miRNAs) are a group of endogenous non-coding regulatory RNA molecules approximately 22–25 bases in length^12,13. It has been found that miRNAs act as key regulator in the development of a variety of diseases, and their aberrant expression is closely related with disease pathogenesis^13,14,15, making miRNAs promising biomarkers for disease diagnosis and therapeutic monitoring. In the past few years, the role of miRNAs in RA has received increasing attention¹⁶. Studies have shown that multiple miRNAs are associated with dysregulated expression (e.g., miR-146a, miR-155, etc.) in serum, synovial tissues, and peripheral blood mononuclear cells (PBMCs) of RA patients^17,18,19. These miRNAs contribute to RA pathogenesis by regulating inflammatory cytokine production, promoting synovial cell proliferation and invasion, and influencing osteoclast differentiation²⁰. Among them, miR-488 is mapped to the human chromosome 1q25.2 region²¹, and previous studies have confirmed its neuroprotective effects: it plays a regulatory role in the progression of gliomas²² and neuroblastomas²³, and notably, miR-488-3p promotes apoptosis of osteoarthritic chondrocytes in osteoarthritis (OA)²⁴. Although OA and RA are different joint diseases, they share common mechanisms in the pathological processes of synovial inflammation and cartilage destruction²⁵. We hypothesized that miR-488-3p may play a role in RA by regulating similar target pathways. However, the specific role and potential mechanisms of miR-488-3p in RA have not been elucidated.

The study investigated the changes in serum miR-488-3p expression levels in RA patients and its relationship with disease activity and clinical indicators, aiming to evaluate its potential value as a non-invasive diagnostic marker for RA. This study provides a novel insight into the early screening and prediction of disease progression in RA, thereby improving the prognosis of patients with RA.

Protocol

The study was approved by the Ethics Committee of Hefei BOE Hospital (Approval no. 2021–1), and written informed consent was obtained from all participants prior to enrollment.

Patients and specimens

This study recruited 135 patients with RA (diagnosed according to the 2010 ACR/EULAR classification criteria) from the Department of Rheumatology and Immunology of Hefei BOE Hospital, 130 patients with OA from the Department of Orthopedics (diagnosed according to the 2018 Chinese Medical Association OA diagnostic criteria), and 125 age- and sex-matched healthy controls from the same hospital's medical examination center. Participants were aged 30–80 years. Healthy controls were confirmed to be free of autoimmune diseases, joint disorders, and acute infections by a comprehensive history review, physical examination, and laboratory tests. Participants were excluded if they had comorbid autoimmune diseases, a history of infection or trauma within the previous 3 months, malignancy, or were pregnant or lactating.

Sampling and preparation

Fasting venous blood was collected from all study subjects. After coagulation at room temperature for 30 min, serum samples were isolated by centrifugation at 1500 × g for 15 min. Serum was stored at -80°C until further analysis.

Detection of clinical and serological markers

To comprehensively evaluate disease status and inflammatory activity, clinical and serological biomarkers were measured using standardized clinical laboratory methods. ESR was measured using the Westergren method to assess nonspecific systemic inflammation. CRP was quantified using an immunoturbidimetric assay (normal reference value: <10 mg/L) to evaluate the acute-phase inflammatory response. RF was measured using an enzyme-linked immunosorbent assay (ELISA) with a normal reference value of ≤20 IU/mL. Anti-CCP antibodies were measured using a second-generation ELISA to provide serological evidence for the diagnosis of RA.

Cell lines and culture

Human fibroblast-like synoviocytes affected by RA (HFLS-RA) cells were grown in Dulbecco's Modified Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. The cells were maintained in an incubator at 37 °C with 5% CO₂, and cells between the third and sixth passages were used for all experiments.

RNA extraction and quantitative real-time RT-PCR

Total RNA was extracted from serum samples using an RNA extraction reagent. Reverse transcription was performed using a miRNA first-strand synthesis kit for miRNAs and a reverse transcription kit for messenger RNA (mRNA) target genes according to the manufacturer's instructions. Quantitative real-time-polymerase chain reaction (RT-qPCR) was performed using a real-time PCR system with a SYBR Green-based PCR master mix. The thermocycle program was set to 95 °C pre-denaturation for 30 s; followed by 40 cycles of amplification (95 °C denaturation for 5 s and 60 °C annealing/extension for 30 s). Each sample was analyzed in triplicate. U6 small nuclear RNA (U6 snRNA) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as endogenous reference genes for miRNA and mRNA normalization, respectively. Primer sequences have been summarized in Supplementary Table 1. The relative expression levels of miR-488-3p and its target genes were calculated using the 2^−ΔΔCt method. The changes in mRNA levels of target genes after overexpression or inhibition of miR-488-3p were also analyzed to verify their regulatory relationships.

Cell transfection

HFLS-RA cells were seeded into 6-well plates at a density of 5 × 10⁵ cells/well. The cells were transfected using a liposome-based transfection reagent following the manufacturer’s instructions. The transfection groups included single transfection and co-transfection groups. The single transfection groups were: 1) control—untransfected cells; 2) mimic negative control (NC)—cells transfected with negative control of miR-488-3p mimic; 3) miR-488-3p mimic—cells transfected with miR-488-3p mimic; 4) inhibitor NC—cells transfected with negative control of miR-488-3p inhibitor; 5) miR-488-3p inhibitor—cells transfected with miR-488-3p inhibitor. Co-transfection groups were: 1) miR-488-3p mimic + overexpression-NC (oe-NC) —cells co-transfected with miR-488-3p mimic and negative control of ROCK1 overexpression vectors; 2) miR-488-3p mimic + oe-ROCK1—cells co-transfected with miR-488-3p mimic and ROCK1 overexpression vectors. All transfection sequences have been summarized in Supplmentary Table 1. The overexpression vector of ROCK1 was established by cloning the coding sequence (CDS) region into pcDNA 3.1 plasmid. Transfected cells were available for the following experiments after 48 h of cell transfection.

Cell function assay

Cell proliferation assay (Cell Counting Kit-8 [CCK-8]): Transfected HFLS-RA cells were inoculated into 96-well plates at 5 × 10³ cells/well, with three replicate wells per group. At 0, 24, 48, and 72 h after transfection, 10 µL of CCK-8 solution was added to each well, followed by incubation at 37 °C for 2 h. The absorbance was measured at 450 nm (detection wavelength) and 630 nm (reference wavelength) using a microplate reader. The relative proliferation rate was calculated using 0 h as the baseline.

Apoptosis detection (flow cytometry): Apoptosis was assessed by analyzing with Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) apoptosis assay. Cells were transfected with the appropriate plasmids and then collected after trypsinization. Apoptosis rate was determined by flow cytometry.

Inflammatory factor assay (Enzyme-Linked Immunosorbent Assay [ELISA]): HFLS-RA cells were seeded into 24-well plates and transfected with the indicated miR-488-3p mimic, miR-488-3p inhibitor, or their corresponding negative controls for 48 h. The concentrations of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β) in the cell culture supernatants were quantified using ELISA kits.

Target validation

Target prediction: ROCK1 was predicted to be a downstream target of miR-488-3p using the TargetScan database²⁶. The predicted binding sites between miR-488-3p and the ROCK1 3′-untranslated region (3′UTR) were also identified.

Dual-Luciferase Reporter Gene Assay: The wild type or mutant 3′UTR of ROCK1 was cloned into the pGL3 plasmid. The predicted binding and mutant sites are shown in Figure 4. HEK- 293T cells were co-transfected with miR-488-3p mimic or inhibitor with constructed vectors²⁷. Luciferase activity was measured 48 h after transfection with miR-488-3p mimic or inhibitor.

RNA Immunoprecipitation (RIP): HFLS-RA cells were incubated with an anti-Argonaute 2 (Ago2) antibody (RRID: AB_2882071, 1:200 dilution) or an immunoglobulin G (IgG) control antibody (RRID: AB_2819160, 1:5000 dilution), followed by RNA extraction and quantitative PCR (qPCR) for ROCK1 mRNA enrichment according as described above.

Statistical analysis

The study was statistically analyzed using SPSS 23.0 (RRID: SCR_002865) and GraphPad Prism 9.0 (RRID: SCR_002798). Measurement data were expressed as mean ± standard deviation (SD). All experiments were performed with three biological replicates, and each biological replicate was analyzed in triplicate. Raw data have been attached in the supplementary material. Data was evaluated using a normal probability (P-P) plot before parametric statistical tests. The independent samples t-test was used to compare continuous baseline variables (e.g., age, body mass index [BMI], etc.) and the chi-square test was used for categorical variables (e.g., gender, etc.). Gene expression levels were compared using an independent-samples t-test. Changes in cell proliferation at different time points were analyzed using repeated-measures analysis of variance (ANOVA), whereas one-way ANOVA was used to compare apoptosis rates determined by flow cytometry. Correlation analysis was performed using Spearman (for variables not meeting normal distribution) and Pearson (for variables meeting normal distribution). Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. The optimal cutoff value, sensitivity, and specificity were determined using the maximum Youden index. All statistical tests were two-sided, and p < 0.05 was considered statistically significant.

Results

Basic characteristics of study participants

This study included 125 healthy controls, 130 patients with OA, and 135 patients with RA for systematic analysis (Table 1). There were no significant differences in the baseline characteristics of the three groups in terms of age (p = 0.191), sex ratio (p = 0.203), and BMI (p = 0.562), which ensured the comparability of the study population. In terms of disease characteristics, ESR (82.63 ±...

Discussion

As emphasized by Smolen et al¹ in the latest guidelines for the diagnosis and treatment of RA, the development of novel biomarkers has significant clinical value. In this study, we confirmed that serum miR-488-3p was significantly downregulated in patients with RA and showed promising diagnostic performance, with relatively satisfactory sensitivity and specificity. Early diagnosis of RA has always been a clinical difficulty, and existing biomarkers are not sufficiently sensitive for the diagnosis ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Annexin V-FITC Apoptosis Detection Kit	BD Bioscience	556547	cell apoptosis
anti-Ago2 antibody	Proteintech	66720-1-Ig	RNA Immunoprecipitation
CCK-8 solution	Dojindo	CK04	cell proliferation
Dulbecco's Modified Eagle Medium (DMEM)	Thermo Fisher	121000146	cell culture
Fetal bovine serum	Thermo Fisher	10437028	cell culture
Flow cytometer	BD Bioscience	FACSCalibur	cell apoptosis
Human anti-CCP antibody ELISA Kit	Cusabio	CSB-E09077h	anti-CCP detection
Human RF-IgA ELISA Kit	Feien Biotechnology	EH4270	RF detection
Human rheumatoid arthritis fibroblast-like synoviocytes (HFLS-RA)	Cell Applications	HFLS-RA-200	in vitro validatio for the function of miR-488-3p
IgG control antibody	Abcam	ab205718	RNA Immunoprecipitation
Interleukin-1β (IL-1β)ELISA Kit	R&D Systems	DY201-05	cellular IL-1β concentration
Interleukin-6 (IL-6) ELISA Kit	R&D Systems	D6050B	cellular IL-6 concentration
Liposome Transfection Reagent 3000	Ingenuity Life Technologies	L3000015	cell transfection
Microplate reader	BioTek	ELx808	ELISA assay
Mir-XTM miRNA First-Strand Synthesis Kit	Nihonbao Bioengineering Co., Ltd.	638313	reverse transcription
Opti-MEM medium	Ingenuity Life Technologies, Inc	31985070	cell transfection
pcDNA 3.1	Invitrogen	V790-20	overexpression of ROCK1
Penicillin-streptomycin	Thermo Fisher	15140122	cell culture
Phadia 250 Laboratory System	Thermo Fisher	Phadia 250	blood analysis
PrimeScriptTM Reverse Transcription Kit	Nihonbao Bioengineering Co., Ltd.	RR037A	reverse transcription
Propidium iodide (PI)/ ribonuclease (RNase)	BD Bioscience	550825	cell apoptosis
QuantStudio 5 system	Applied Biosystems, Inc.	A28138	PCR assay
RNAiso Plus reagent	Nihonbao Bioengineering Co., Ltd.	9108	RNA isolation
SYBR Green Premix Ex Taq	Nippon Poh Bio-Engineering Co., Ltd.	RR420A	PCR amplification
TargetScan database	TargetScan	N/A	binding sites prediction, (https://www.targetscan.org/)
Tina-quant C-Reactive Protein IV	Roche Diagnostics	7876033190	CRP detection
Tumor necrosis factor-α (TNF-α) ELISA Kit	R&D Systems	DY210-05	cellular TNF-α concentration