Association of the X-chromosomal hsa_circ_0140271 with Female Rheumatoid Arthritis

doi:10.21203/rs.3.rs-98324/v1

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Association of the X-chromosomal hsa_circ_0140271 with Female Rheumatoid Arthritis

https://doi.org/10.21203/rs.3.rs-98324/v1

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Background:Rheumatoid arthritis (RA) commonly affects women. Circular RNAs (circRNAs) have been reported to be related RA progress. However, it is still unknown the role of circRNA in female RA.

Methods: In this study, we extracted total RNA of peripheral blood mononuclear cells (PBMC) from four RA patients and four healthy control donors, then performed RNA sequencing analysis. To validation, we recruited PBMC samples from 47 RA patients and 47 healthy control donors. The diagnosis ability of candidate circRNA in female RA was explored by Receiver Operating Characteristic (ROC) curve analysis. Levels of inflammation factors in serum, such as IL-1α, IL-1β, IL-6, IL-8,TNF-α and INF-γ, were detected in female RA patients and female healthy donors to analysis the correlation between those factors and candidate circRNA. KEGG pathway enrichment analyses were also performed to predict function of candidate circRNA.

Resuluts: By analyzing circRNA expression profiles, we identified hsa_circ_0140271, generated from X chromosome gene-MED14, was specifically expressed in female RA patients. We verified hsa_circ_0140271 expression in PBMC samples from a cohort of 47 RA patients and 47 healthy control subjects via RT-qPCR and found hsa_circ_0140271 was also specifically highly expressed in female RA. In addition, ROC curve analysis indicated that the specificity of hsa_circ_0140271 in female RA patients was 1 comparing to female healthy subjects, osteoarthritis (OA) patients or Ankylosing spondylitis (AS) patients. Levels of IL-6, IL-8 and TNF-α was higher in serum from female RA patients than that from female healthy subjects. Furthermore, KEGG analysis indicated that hsa_circ_0140271 might regulate fatty acid metabolism in female RA patients.

Conclusion:Our results suggested that hsa_circ_0140271 has a potential role in detect female RA and may contribute RA progress by fatty acid metabolism.

Rheumatology

rheumatoid arthritis

circular RNA

female

X-chromosome

fatty acid

Rheumatoid arthritis is a systemic autoimmune disease characterized by chronic inflammation and erosive arthrosynovitis, with a prevalence of 0.5-1% in the worldwide[1] [2]. Like other autoimmune diseases, RA is more prevalent among women, with some studies suggesting as high as 3:1 female to male ratio. The etiology of RA is not fully elucidated, however, hormonal change and genetic factors are related to high incidence of female RA[3]. Women with early menopause are more susceptible to RA[4]. Besides hormone, genes from X chromosome are also closely associated with RA. A higher rate of a skewed X chromosome inactivation has been observed in female RA patients[5]. And interleukin 1 receptor associated kinase (IRAK1) from X chromosome has been reported to be related to female predominant in RA[6]. Thus, researches on X-chromosomal genes might be a good way to elucidate the mechanism of female RA etiology.

Circular RNA is a class of endogenous RNA, which is characterized by a covalently closed loop structure without a 5’ end cap structure and 3’ end poly (A) tail[7]. Circular RNA is widely presented in eukaryotic cells and showed cell or tissue specific expression pattern[8]. Due to loop structure, circular RNA is resistant to degradation, and this feature has been applied to clarify the potential pathogenesis of diseases[9]. Recently, several studies have been demonstrated that circular RNAs are highly relevant to RA[10]. Those studies have explored various roles of circRNAs in RA, however, there is few concerned about association between X chromosome generated circRNAs and female predominance in RA. In this study, we aimed to explore X-chromosomal circRNA and its role in female RA. Furthermore, we also evaluated the clinical potential of the candidate circRNA as a biomarker of female RA.

Patient variables

Peripheral blood was collected from a total of 127 participants who were recruited consecutively for this study: 47 patients with RA, 47 healthy controls, 23 female osteoarthritis (OA) and 7 female Ankylosing spondylitis (AS) patients. All RA, OA and AS patients were diagnosed at the Department of Rheumatology and Immunology, and Department of Orthopedics at The Fifth Affiliated Hospital of Sun-Yat-Sen University in 2020. Age and sex-matched patients without RA, OA or AS from the same hospital were recruited as healthy controls. All RA patients fulfilled the American College of Rheumatology criteria for the classification of RA. Among these, 5 patients were new onset rheumatoid arthritis (< 6 months of disease duration) .The disease activity was evaluated by Disease Activity Score 28 (DAS28) using C-reactive protein (CRP). The characteristics of RA patients and healthy controls and controls are shown in Table 1. All study protocols were approved by the ethics committee of The Fifth Affiliated Hospital of Sun-Yat-Sen University. All participants in this study were informed and signed written consent.

Table 1

Characteristics of healthy controls and patients with rheumatoid arthritis.
Characteristics	RA	HC
Number	47	47
Age(years)^a	57.13 ± 12.27	60.70 ± 10.89
Sex (M/F)	16/31	16/31
Disease duration (Month)^b	1008.00(158.40,1872.00)	NA
Anti-CCP(U/ml)^a	40.28 ± 15.20	32.34 ± 10.86
DAS28^a	4.06 ± 1.14	NA
CRP(mg/L)^b	25.14(5.10,73.40)	3.1(1.00,42.65)
ESR(mm/h)^a	61.17 ± 34.13	33.12 ± 27.18
Swollen joints^b	6.00(2.00,10.00)	NA
Tender joints^b	6.00(3.00,10.00)	NA
ILD positive(%)	17.02%	NA
In the groups providing PBMCs, there was no significant difference in age (p = 0.139 ,Student's t-test) and sex (p = 1.000, Chi-square) between RA patients and HC. Abbreviations: RA: rheumatoid arthritis;HC:healthy controls;M/F: male/female;Anti-CCP:anti-cyclic citrullinated peptide antibodies;DAS28:disease activity score in 28 joints;CRP:C-reactive protein;ESR: erythrocyte sedimentation rate;ANA: antinuclear antibody;ILD:interstitial lung disease;NA: not available.
^aExpressed as mean ± standard deviation.
^bExpressed as the median (25th to 75th percentile).

Preparation of Peripheral Blood Samples and Isolation of RNA and plasma

Peripheral blood samples (6 ml) were collected from each patient and control subjuect into EDTA-2K-containing tubes. Plasma and peripheral blood mononuclear cells (PBMCs) were extracted as soon as possible by using the Histopaque-1077 (Sigma-Aldrich, UK) according to the manufacturer’s protocol. Then the plasma was immediately separated and transferred to a fresh RNase free tube and stored at − 80 °C for Elisa. Total RNA was isolated from freshly obtained PBMCs using the Total RNA Kit I (Omega Bio-tek, USA). The concentration and quality of the RNA were assessed by absorbance spectrometry measuring absorbance ratios of A260/A280 and a 260/A230 using a NanoDrop ND-1000 spectrophotometer (ThermoFisher Scientifc, USA). Total RNA were kept at -80 °C or immediately used for reverse transcription.

RNA-seq analysis

Before RNA-sequencing, the quality of RNA was tested by Agilent 2100 Bioanalyzer (Agilent Technology). 2 µg of RNA sample was taken for RNA-sequencing. RNase R digested and rRNA depleted RNAs were taken to generated the sequencing libraries by using Total RNA-seq (H/M/R) Library Prep Kit for Illumina (Vazyme Biotech) following manufacturer’s recommendations. The library preparations were sequenced on Hiseq X Ten (Illumina).

Differential expression analysis

The reads were first mapped to the latest UCSC transcript set using Bowtie2 version 2.1.0[11] and the gene expression level was estimated using RSEM v1.2.15[12]. For circRNA expression analysis, the reads were to mapped genome using the STAR[13] and DCC[14] was used to identify the circRNA and to estimate the circRNA expression.TMM (trimmed mean of M-values) was used to normalize the gene expression. Differentially expressed genes were identified using the edgeR program[15]. Genes showing altered expression with p < 0.05 and more than 1.5 fold changes were considered differentially expressed.

Real time- quantitative PCR (RT-qPCR) analysis.

A total of 500 ng of each RNA sample was used for reverse transcription using a RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientifc, Lithuana). The relative expression of circRNA (Forward Primer:5'-atcggcttgtaaccacagat-3', Reverse Primer: 5'-ctcataaagttgttctctcctg-3') and MED14 (Forward Primer:5'-cgccaactcttcgttcgatta-3', Reverse Primer: 5'-gtccacaaacaggatggcttg-3') was determined on an CFX96TM Touch Real-Time PCR Detection System (BIO-RAD,USA ) using EverGreen® Forget-Me-Not qPCR Master Mix (Biotium, USA), as the following PCR thermocycler protocol: Initial Enzyme activation step at 95˚C for 2 min, followed by 40 cycles of 95˚C for 5 sec (denaturation), 60˚C for 10 sec (annealing) and 72˚C for 10 sec (extension). GAPDH (Forward Primer:5'-agccacatcgctcagca-3', Reverse Primer: 5'-gcccaatacgaccaaatcc-3') was used as an internal control.

ELISA

Plasma concentrations of IL-1α, IL-1β,IL-6,IL-8,TNF-α and IFN-γ were measured by commercially available enzyme linked immunosorbent assay (ELISA) kits (Saicheng Bio-tek, China) according to the manufacturer’s instruction.

miRNA prediction and KEGG pathway analysis

The miRNAs, potentially related to candidate circRNA, were predicted by circBank database (http://www.circbank.cn/) and circular RNA Interactome database (https://circinteractome.nia.nih.gov/). Based on predicted miRNAs, KEGG pathway enrichment analyses were performed by DIANA-mirPath (http://www.microrna.gr/miRPathv2). The KEGG pathway analysis was also performed to represent the knowledge on the molecular interaction and reaction networks of the target gene. The KEGG pathway with a p < 0.05 was considered the significance of the pathway correlations.

Statistical Analysis.

Data were statistically described in terms of mean ± standard deviation, medians (quartiles), or proportions when appropriate. All experimental data were analyzed using SPSS software 22.0 (IBM,USA) and GraphPad Prism 8.0 (GraPhpad Software, CA). Student’s t-test and Mann-Whitney’s U test were employed to compare normally distributed parameters and those with skewed distribution, the Pearson method or the nonparametric Spearman method was used for correlation analysis, and logistic regression analysis were used, as appropriate. Receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic value of circRNA. The area under curve (AUC) was calculated with SPSS software22.0. p < 0.05 was considered to be statistically significant.

Screening of female rheumatoid arthritis associated circRNA

To explore female RA associated circRNAs, we firstly collected total RNA of PBMC samples from four RA patients and control healthy subjects with gender and age matched. Then, we performed RNA sequencing analysis and compared circRNAs expression between rheumatoid arthritis patients and healthy control group. We identified 162 significantly differentially expressed circRNAs with a fold change ≥ 1.5 and a p-value ≤ 0.05 (Fig. 1A, Supplemental Table 1). Next, we used cluster screening to analyze the effect of gender against the background of female healthy samples and male rheumatoid arthritis samples (Fig. 1B,C, Supplemental Table 2,3). This enabled us to further identify female RA associated circRNAs. As shown in the Venn diagram, we identified three circRNAs (hsa_circ_0140271, hsa_circ_0105101 and hsa_circ_0010474) (Fig. 1D). Among those circRNAs, we were interested in hsa_circ_0140271, which were generated from MED14 gene located on X chromosome and highly expressed in three paired comparisons (Supplemental Table 4). To further explore the role of hsa_circ_0140271 in female RA, we designed specific primer to target hsa_circ_0140271, and then performed Sanger sequencing analysis and RT-qPCR. As the results shown, we identified the back-splice junction of hsa_circ_0140271 through Sanger sequencing analysis, and also found hsa_circ_0140271 was resistant to RNase R. While the liner RNA of MED14 was significantly decreased (Fig. 1E,F). These results confirmed the primer correctly amplified hsa_circ_0140271.

hsa_circ_0140271 was highly expressed in female rheumatoid arthritis patients’ PBMC

In order to further analyze hsa_circ_0140271 expression in female rheumatoid arthritis patients’ PBMC, we recruited PBMC totally from 47 RA patients and 47 healthy control donors. These two cohorts were also gender and age matched. The total RNA was also extracted and quantified hsa_circ_0140271 expression by RT-qPCR. As expected, hsa_circ_0140271 was significantly highly expressed in RA samples (Fig. 2A). To assess whether hsa_circ_0140271 would be specifically expressed in female RA samples, we stratified RA and healthy control samples according to gender. Consistent with previous results, hsa_circ_0140271 was also significantly highly expressed in female RA samples comparing to that in female healthy samples or male RA samples (Fig. 2B). However, it was not observed any difference in expression of mRNA of MED14 between RA and control group (Fig. 2C).

Next, we analyzed whether hsa_circ_0140271 expression was correlated with clinical status of female RA patients. According to DAS28 scores, we divided female RA patients into Remission group (DAS28 < 2.6) and Active group (DAS28 > 2.6). RT-qPCR results showed hsa_circ_0140271 expression was significantly higher in the Remission group and Active group comparing to that in female healthy group, while there was no difference between Remission group and Active group (Fig. 2C). We also analyzed effect of RA duration on hsa_circ_0140271 expression. We found that hsa_circ_0140271 expression was significantly higher in the female early RA (ERA) group (< 6 months) and RA group (> 6 months), but there was also no difference between ERA and RA group (Fig. 2D). Finally, we examined hsa_circ_0140271 expression in female RA-associated interstitial lung disease (ILD). Among female RA patients, there were four patients who suffered ILD. And hsa_circ_0140271 expression from those patients was not different to that from non-ILD patients (Fig. 2E). These data confirmed that hsa_circ_0140271 was specifically expressed in PBMC from female RA patients and its expression was independent with disease activity, duration and ILD.

hsa_circ_0140271 serves as a potential diagnostic biomarker for female RA

Based on the results showing that hsa_circ_0140271 was specifically highly expressed in PBMC of female RA patients, we established ROC curve analysis to explore the potential utility of hsa_circ_0140271 as a diagnostic biomarker of female RA. According to ROC analysis, the area under curve (AUC) for hsa_circ_0140271 was up to 0.704 (sensitivity = 0.419, specificity = 1), respectively (Fig. 3A, Table 2). We also performed ROC analysis by combining hsa_circ_0140271 and anti-cyclic citrullinated peptide (anti-CCP). The data suggested that the AUC and sensitivity were increased to 0.818 and 0.806, while the specificity was decreased to 0.742 (Fig. 3B, Table 2). These results implied that hsa_circ_0140271 was highly specificity for female RA and combination with anti-CCP improved its predictive value.

Table 2

ROC curve Validates the diagnostic value of differentially expressed hsa_circ_0140271 from female patients with RA.
Variables	AUC	SEM	P value	95%CI	Sensitivity	Specificity	Cutoff value
hsa_circ_0140271	0.704	0.067	0.006	0.572–0.837	0.419	1.000	0.110
Anti-CCP	0.738	0.738	0.001	0.609–0.867	0.581	0.903	40.719
Anti-CCP + hsa_circ_0140271	0.818	0.054	< 0.001	0.699–0.904	0.806	0.742	NA

Since some cytokines, like IL-1α, IL-1β, IL-6, IL-8, TNF-α and INF-γ and so on, were contributed to pathology of RA[16], we analyzed the relation between hsa_circ_0140271 and those cytokines. Based on Cutoff values of hsa_circ_0140271 ROC analysis, we divided female RA patients into hsa_circ_0140271 positive group (> 0.110) and negative group (< 0.110). Then we detected IL-1α, IL-1β, IL-6, IL-8, TNF-α and INF-γ expression in serum from both groups. Unfortunately, there was no difference in the level of those factors between two groups (Supplemental Fig. 1). However, when dividing female RA and female healthy donors according to Cutoff values, the results showed that IL-6, IL-8 and TNF-α expression were higher in hsa_circ_0140271 positive group (Fig. 4 ).

hsa_circ_0140271 possibly regulates fatty acid metabolism in female RA patients

Accumulating evidences have been shown that circRNAs play a role in pathogenesis of diseases through function of miRNA sponge[17, 18]. To elucidate the role of hsa_circ_0140271 in RA, we predicted hsa_circ_0140271 related miRNA using circBank database (http://www.circbank.cn/) and circular RNA Interactome database (https://circinteractome.nia.nih.gov/) (Fig. 5A). By analyzing those two databases, it was shown eight miRNAs might be closely related to hsa_circ_0140271, which were has-miR-600, has-miR-1244, has-miR-576-5p, hsa-miR-941, has-miR-657, has-miR-635, has-miR-574-5p, and has-miR-1305. Then, to further predict function of hsa_circ_0140271, we performed KEGG analysis based on predicted miRNAs using DIANA-mirPath (http://www.microrna.gr/miRPathv2) (Fig. 5B). According to analysis, we found 9 enriched KEGG terms. Among those terms, we found 3 terms were related to lipid metabolism, which were “Fatty acid biosynthesis”, “Pantothenate and CoA biosynthesis” and “Fatty acid metabolism”. This analysis indicated function of hsa_circ_0140271 might be associated with lipid metabolism. To verify our hypothesis, we checked laboratory characteristics of female RA patients. Although there was no correlation between hsa_circ_0140271 and lipid associated categories, such as TG, TC, HDL-C and LDL-C, it was found that expression of TG from female RA patients was lower than that from female control groups (Fig. 5C-F, Supplemental Table 5). Taken together, hsa_circ_0140271 might play a role in lipid metabolism in female RA patients through function of miRNA sponge.

hsa_circ_0140271 was a potential biomarkers in discriminating female RA from OA or AS

Since female is predominant in autoimmune diseases[3], we also analyzed hsa_circ_0140271 expression in PBMC from female osteoarthritis (OA) and Ankylosing spondylitis (AS) patients. We recruited 24 female OA patients and 7 female As patients and PBMC of those patients was also extracted to perform RT-qPCR. RT-qPCR analysis demonstrated that hsa_circ_0140271 expression from OA and AS was significantly lower than that from RA, even lower than that from healthy control (Fig. 6A). Then, we performed ROC curve analysis to evaluate the potential value of hsa_circ_0140271 discriminating RA from OA or AS. ROC curve from patients with RA and AS showed AUC area was 0.922 (sensitivity = 0.806, specificity = 1). When distinguish RA patients from OA patients, AUC area was 0.868 (sensitivity = 0.645, specificity = 1). It was also analyzed by combining OA and AS. By combination, AUC area was 0.881 (sensitivity = 0.645, specificity = 1) (Fig. 6B,C, Table 3). Those analyses implied that hsa_circ_0140271 was specifically expressed in female RA patients and might discriminate RA from OA or AS.

Table 3

ROC curve analysis of the confirmed hsa_circ_0140271 as RA female specific diagnosis.
Variables	AUC	SEM	P value	95%CI	Sensitivity	Specificity	Cutoff value
hsa_circ_0140271(RA vs AS)	0.922	0.045	< 0.001	0.787–0.984	1	0.806	0.034
hsa_circ_0140271(RA vs OA)	0.868	0.048	< 0.001	0.748–0.945	1	0.645	0.072
hsa_circ_0140271(RA vs AS + OA)	0.881	0.045	< 0.001	0.772–0.950	1	0.645	0.072

RA is a chronic autoimmune disease characterized by rheumatoid nodules, pulmonary involvement or vasculitis, and systemic comorbidities[19]. Currently, increasing studies have been demonstrated that circRNAs are involved in or related to RA progress[10]. In this study, we found hsa_circ_0140271 was highly expressed in PBMC from female RA patients comparing to that from female healthy control or male RA patients.

Like other autoimmune disease, women are more frequently to be affected by RA than men, with a female to male ratio of about 3:1[3]. Genes from X chromosome is one factors contribute to predominance of RA in women[20]. Normally, a female karyotype is comprised of two X chromosomes, which are originated from each parent. During early stage of embryogenesis, one of X chromosomes is randomly silenced. However, 15% of gene would be escaped from silencing and X chromosomes inactivation (XCI) is associated with female RA[5, 20, 21]. One of mechanism of XCI is DNA methylation, which is potential related to circular RNA biogenesis and RA[21–23]. And generation of circRNAs was also regulated by DNA methylation[22]. In this study, we performed RNA sequencing analysis and found hsa_circ_0140271 expression might be related to female RA. We also detected X chromosomal gene-MED14 expression, from which hsa_circ_0140271 was generated. However, there was no difference in MED14 mRNA expression between female RA group and female healthy group. These results indicated that the difference of hsa_circ_0140271 expression was not caused by gene of MED14 itself, while it may be closely associated with female RA or other things, like DNA methylation. And it is needed to further explore the mechanism of generation of hsa_circ_0140271 in female RA.

It is well accepted that early diagnosis and assessment of disease activity are favorable outcome in RA[24–26]. In this study, we observed that there was no difference in hsa_circ_0140271 expression between Remission and Activity group in female RA patients. Furthermore, there was also no difference in hsa_circ_0140271 expression between early stage RA and RA group in female RA patients, which meant hsa_circ_0140271 expression might be independent of duration or activity in female RA. Comparing to female healthy control, AS or OA group, ROC curve analysis also indicated that the specificity of hsa_circ_0140271 was all 1, which implied that it might had a good diagnosis value for female RA. We also detected hsa_circ_0140271 expression in one of RA complications- interstitial lung disease (ILD). In this analysis, we also did not found any difference in hsa_circ_0140271 expression between ILD and non-ILD group. These analyses indicated that hsa_circ_0140271 could not serve as a biomarker for assessing disease activity in RA or identifying complications of RA like ILD, however, it might be a potential biomarker in female RA.

RA is a chronic inflammation disease and proinflammation factors play an important role in RA progress[16]. In this study, we detected IL-1α, IL-1β, IL-6, IL-8, TNF-α and INF-γ levels in serum among female RA patients and female healthy groups. Although there were no difference in those factors level between hsa_circ_0140271 positive and negative group among female RA patients, it was observed IL-6, IL-8 and TNF-α levels were higher in the hsa_circ_0140271 positive group when calculating female RA patients and female healthy subjects together. Regarding to this results, we estimated that the limited sample size affected the results in female patients, and with increasing sample size there would be also difference in those factors level between hsa_circ_0140271 positive and negative group among female RA patients. Interestingly, it have been found that level of IL-6, IL-8 and TNF-α in serum were associated with early stage of RA patients[27, 28].These results implied that hsa_circ_0140271 might be related to onset or pathology of early stage of RA. And combing those analysis and previous analysis of hsa_circ_0140271 expression in early stage RA and RA group, we estimated that hsa_circ_0140271 might be also a biomarker of early stage of female RA.

To further explore function of hsa_circ_0140271, we predicted some miRNAs related hsa_circ_0140271 based on miRNA sponge theory, and then performed KEGG pathway analysis to found some signaling pathways potentially regulated by hsa_circ_0140271. Among those pathways, we detected three fatty acid related pathways, such as Fatty acid biosynthesis, Pantothenate and CoA biosynthesis and Fatty acid metabolism. It has been demonstrated that fatty acids play a role in various of RA processes, such as inflammation and pain, by interacting with immune cells like Th17 cells[29, 30]. It has been demonstrated that fatty acid contributed synthesis of Th17 cells[31]. As a source of fatty acid, level of TG was decreased in female RA group comparing to female healthy subjects. Taken together, we hypothesize that hsa_circ_0140271 might regulate fatty acid metabolism in female RA.

In general, we suggested hsa_circ_0140271 as a potential candidate of female RA. However, there were some limitations should be considered in this study. The small sample size was the main and significant limitation. In this study, we recruited 31 female RA patients and 31 female healthy control subjects. As mentioned above, the level of inflammation factors, such as IL-6,IL-8 and TNF-α, were shown to be different when calculating female RA patients and female healthy subjects together, however, it was not seen any difference in female RA patients alone. Therefore, a large number cohort study would be needed to be performed in future study. Besides that, it is also needed more research on function of hsa_circ_0140271 in further study. In this study, we predicted function of hsa_circ_0140271 based on theory of miRNA sponge. Except function of miRNA sponge,circular RNA also interacts with functional protein to regulate transcription activity in cells[32]. Thus༌it should carefully explore the function of hsa_circ_0140271 via more relative experiments in future.

In this study, we aimed to explore X chromosomal circRNAs to elucidate its potential role in diagnosis and treatment of female RA. Our results have provided evidences that hsa_circ_0140271, generated from gene of X chromosome, was specifically highly expressed in female RA patients. Furthermore, hsa_circ_0140271 would present great potential to be a biomarker for female RA detection. In addition, we predicted hsa_circ_0140271 would play a role in regulating inflammation in RA via fatty acid metabolism.

circRNAs: circular RNAs; RA: Rheumatoid arthritis; PBMC: peripheral blood mononuclear cells; ROC: Receiver Operating Characteristic; OA:osteoarthritis; AS: Ankylosing spondylitis; IRAK1: interleukin 1 receptor associated kinase; DAS28: Disease Activity Score 28; CRP: C-reactive protein; ERA: early RA; ILD: interstitial lung disease; AUC: areas under ROC curve; anti-CCP: anti-cyclic citrullinated peptide; XCI: X chromosomes inactivation;

Ethics approval and consent to participate

The experimental protocol was established, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of The Fifth Affiliated Hospital of Sun-Yat-Sen University. Written informed consent was obtained from individual or guardian participants.

Consent for publication

Not applicable

Availability of data and material

All data generated or analysed during this study are included in this published article.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by grants from the National Natural Science Foundation of China (NO.81772384，81572174 and 81902242), Project funded by China Postdoctoral Science Foundation (NO. 2019M663268) and Medical Science and Technology planning Project of Zhuhai, China (NO. ZH2201200003HJL). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Authors’ contributions

Y.C and X.X designed experiments and analyzed data; Y.C and X.L performed experiments; J.S and N.J performed parts of Elisa experiments; W.B, W.B and J.Z collected clinical samples; S.Z and H.L provided techniques and discussion; Y.C and X.X wrote the manuscript.

Acknowledgements

Not applicable

Authors' information

1, Department of Orthopaedics, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai 519000, Guangdong, China

2, Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, Guangdong, China

3, Department of Rheumatology, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai 519000, Guangdong, China

Smolen JS, Aletaha D, McInnes IB: Rheumatoid arthritis. Lancet 2016, 388(10055):2023-2038.
Sparks JA: Rheumatoid Arthritis. Annals of internal medicine 2019, 170(1):ITC1-ITC16.
Amur S, Parekh A, Mummaneni P: Sex differences and genomics in autoimmune diseases. Journal of autoimmunity 2012, 38(2-3):J254-265.
Pikwer M, Bergstrom U, Nilsson JA, Jacobsson L, Turesson C: Early menopause is an independent predictor of rheumatoid arthritis. Annals of the rheumatic diseases 2012, 71(3):378-381.
Chabchoub G, Uz E, Maalej A, Mustafa CA, Rebai A, Mnif M, Bahloul Z, Farid NR, Ozcelik T, Ayadi H: Analysis of skewed X-chromosome inactivation in females with rheumatoid arthritis and autoimmune thyroid diseases. Arthritis research & therapy 2009, 11(4):R106.
Han TU, Cho SK, Kim T, Joo YB, Bae SC, Kang C: Association of an activity-enhancing variant of IRAK1 and an MECP2-IRAK1 haplotype with increased susceptibility to rheumatoid arthritis. Arthritis and rheumatism 2013, 65(3):590-598.
Xiao MS, Ai Y, Wilusz JE: Biogenesis and Functions of Circular RNAs Come into Focus. Trends in cell biology 2020, 30(3):226-240.
Li X, Yang L, Chen LL: The Biogenesis, Functions, and Challenges of Circular RNAs. Molecular cell 2018, 71(3):428-442.
Mumtaz PT, Taban Q, Dar MA, Mir S, Haq ZU, Zargar SM, Shah RA, Ahmad SM: Deep Insights in Circular RNAs: from biogenesis to therapeutics. Biological procedures online 2020, 22:10.
Zhou Z, Sun B, Huang S, Zhao L: Roles of circular RNAs in immune regulation and autoimmune diseases. Cell death & disease 2019, 10(7):503.
Langmead B, Salzberg SL: Fast gapped-read alignment with Bowtie 2. Nature methods 2012, 9(4):357-359.
Li B, Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC bioinformatics 2011, 12:323.
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR: STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29(1):15-21.
Cheng J, Metge F, Dieterich C: Specific identification and quantification of circular RNAs from sequencing data. Bioinformatics (Oxford, England) 2016, 32(7):1094-1096.
Robinson MD, McCarthy DJ, Smyth GK: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26(1):139-140.
McInnes IB, Liew FY: Cytokine networks--towards new therapies for rheumatoid arthritis. Nature clinical practice Rheumatology 2005, 1(1):31-39.
Kulcheski FR, Christoff AP, Margis R: Circular RNAs are miRNA sponges and can be used as a new class of biomarker. Journal of biotechnology 2016, 238:42-51.
Qu S, Zhong Y, Shang R, Zhang X, Song W, Kjems J, Li H: The emerging landscape of circular RNA in life processes. RNA biology 2017, 14(8):992-999.
Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, Kavanaugh A, McInnes IB, Solomon DH, Strand V et al: Rheumatoid arthritis. Nature reviews Disease primers 2018, 4:18001.
Krasselt M, Baerwald C: Sex, Symptom Severity, and Quality of Life in Rheumatology. Clinical reviews in allergy & immunology 2019, 56(3):346-361.
Selmi C, Brunetta E, Raimondo MG, Meroni PL: The X chromosome and the sex ratio of autoimmunity. Autoimmunity reviews 2012, 11(6-7):A531-537.
Liu C, Liu YC, Huang HD, Wang W: Biogenesis mechanisms of circular RNA can be categorized through feature extraction of a machine learning model. Bioinformatics 2019, 35(23):4867-4870.
Vecellio M, Wu H, Lu Q, Selmi C: The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases. Clinical rheumatology 2020.
Guo Q, Wang Y, Xu D, Nossent J, Pavlos NJ, Xu J: Rheumatoid arthritis: pathological mechanisms and modern pharmacologic therapies. Bone research 2018, 6:15.
van Nies JA, Krabben A, Schoones JW, Huizinga TW, Kloppenburg M, van der Helm-van Mil AH: What is the evidence for the presence of a therapeutic window of opportunity in rheumatoid arthritis? A systematic literature review. Annals of the rheumatic diseases 2014, 73(5):861-870.
Singh JA, Furst DE, Bharat A, Curtis JR, Kavanaugh AF, Kremer JM, Moreland LW, O'Dell J, Winthrop KL, Beukelman T et al: 2012 update of the 2008 American College of Rheumatology recommendations for the use of disease-modifying antirheumatic drugs and biologic agents in the treatment of rheumatoid arthritis. Arthritis care & research 2012, 64(5):625-639.
Cascao R, Moura RA, Perpetuo I, Canhao H, Vieira-Sousa E, Mourao AF, Rodrigues AM, Polido-Pereira J, Queiroz MV, Rosario HS et al: Identification of a cytokine network sustaining neutrophil and Th17 activation in untreated early rheumatoid arthritis. Arthritis research & therapy 2010, 12(5):R196.
Fox DA: Cytokine blockade as a new strategy to treat rheumatoid arthritis: inhibition of tumor necrosis factor. Archives of internal medicine 2000, 160(4):437-444.
Cas MD, Roda G, Li F, Secundo F: Functional Lipids in Autoimmune Inflammatory Diseases. International journal of molecular sciences 2020, 21(9).
Ryu H, Kim J, Kim D, Lee JE, Chung Y: Cellular and Molecular Links between Autoimmunity and Lipid Metabolism. Molecules and cells 2019, 42(11):747-754.
Berod L, Friedrich C, Nandan A, Freitag J, Hagemann S, Harmrolfs K, Sandouk A, Hesse C, Castro CN, Bahre H et al: De novo fatty acid synthesis controls the fate between regulatory T and T helper 17 cells. Nature medicine 2014, 20(11):1327-1333.
Bose R, Ain R: Regulation of Transcription by Circular RNAs. Advances in experimental medicine and biology 2018, 1087:81-94.

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supplementalfigure11.tif
Determine levels of inflammatory factors in serum of female RA patients. 31 female RA patients were divided according to Cutoff levels of hsa_circ_0140271 ROC analysis. Detected levels of IL-1α (A), IL-1β (B), IL-6(C), IL-8(D), TNF-α (E) and IFN-γ (F) in hsa_circ_0140271 positive group (hsa_circ_0140271+) and hsa_circ_0140271 negative group (hsa_circ_0140271-) .

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Association of the X-chromosomal hsa_circ_0140271 with Female Rheumatoid Arthritis

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Abstract

Figures

Introduction

Material And Methods

Patient variables

Preparation of Peripheral Blood Samples and Isolation of RNA and plasma

RNA-seq analysis

Differential expression analysis

Real time- quantitative PCR (RT-qPCR) analysis.

ELISA

miRNA prediction and KEGG pathway analysis

Statistical Analysis.

Results

Screening of female rheumatoid arthritis associated circRNA

hsa_circ_0140271 was highly expressed in female rheumatoid arthritis patients’ PBMC

hsa_circ_0140271 serves as a potential diagnostic biomarker for female RA

hsa_circ_0140271 possibly regulates fatty acid metabolism in female RA patients

hsa_circ_0140271 was a potential biomarkers in discriminating female RA from OA or AS

Discussion

Conclusions

Abbreviations

Declarations

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Availability of data and material

Competing interests

Funding

Authors’ contributions

Acknowledgements

Authors' information

References

Supplementary Files

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