Circular RNAs in Peripheral Blood Mononuclear Cells from Ankylosing Spondylitis

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Circular RNAs in Peripheral Blood Mononuclear Cells from Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis primarily affecting the axial skeleton, characterized by inflammatory back pain, enthesitis, and progressive spinal ankylosis. Despite advances in understanding its genetic predisposition—most notably the strong association with HLA-B27—the molecular mechanisms driving AS pathogenesis remain incompletely defined. Emerging evidence highlights the role of noncoding RNAs (ncRNAs) in autoimmune diseases, with circular RNAs (circRNAs) gaining attention for their regulatory functions. This study investigates the expression profile of circRNAs in peripheral blood mononuclear cells (PBMCs) of AS patients, identifies disease-associated circRNAs, and evaluates their diagnostic and prognostic potential.

Methodology and Experimental Design

The study enrolled 60 AS patients (44 males, 16 females; mean age 36.9 ± 10.6 years) diagnosed per the 1984 revised New York criteria and 30 healthy controls (HCs; 20 males, 10 females; mean age 35.8 ± 10.8 years). Active AS (ASA) was defined as a Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ≥6 or BASDAI >4 with elevated acute-phase reactants (erythrocyte sedimentation rate [ESR] >22 mm/h or high-sensitivity C-reactive protein [hsCRP] >9 mg/L). Stable AS (ASS) was defined as BASDAI ≤4. Clinical parameters, including BASDAI, Bath Ankylosing Spondylitis Functional Index (BASFI), and laboratory markers (blood counts, ESR, hsCRP, albumin [ALB], globulin [GLOB]), were recorded.

circRNA Microarray and Validation

Total RNA from PBMCs of 6 AS patients and 6 HCs was analyzed using the Arraystar Human circRNA Array v2 (8×15K). Differentially expressed circRNAs were identified using fold change (FC >1.5) and P <0.05. Validation via RT-qPCR was performed on 60 AS and 30 HC samples for four circRNAs: hsa_circRNA_001544, hsa_circRNA_102532, hsa_circRNA_008961, and hsa_circRNA_012732. Bioinformatic analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and circRNA-miRNA interaction predictions.

Key Findings

1. circRNA Expression Profiling in AS

Microarray analysis identified 1,369 differentially expressed circRNAs (675 upregulated, 694 downregulated) in AS patients compared to HCs (Figure 1A–B). Chromosomal distribution analysis revealed significant differences in circRNA expression on chromosomes 2, 4, 8, 17, 19, 21, and 22 (P <0.05), with most circRNAs originating from exons (Figure 1D).

2. Functional Enrichment of circRNAs

GO analysis highlighted distinct biological roles for upregulated and downregulated circRNAs:

  • Upregulated circRNAs were enriched in enzyme binding (GO:0019899), organelle organization (GO:0006996), and the MAPK signaling pathway (KEGG:hsa04010).
  • Downregulated circRNAs associated with adenosine ribonucleotide binding (GO:0032559) and pathways like endometrial cancer (KEGG:hsa05213).

3. Validation of circRNA Candidates

RT-qPCR confirmed significant upregulation of hsa_circRNA_001544 (U = 486.5, P <0.05) and hsa_circRNA_102532 (U = 645, P <0.05) in AS patients versus HCs. Subgroup analysis revealed:

  • hsa_circRNA_001544 was elevated in both ASA (U = 214, P <0.05) and ASS (U = 273, P <0.05) compared to HCs.
  • hsa_circRNA_102532 (U = 295, P <0.05) and hsa_circRNA_008961 (U = 250, P <0.05) were upregulated only in ASA.
  • hsa_circRNA_012732 differed significantly between ASA and ASS (U = 194, P <0.05), suggesting a role in disease activity.

4. Clinical Correlations

  • hsa_circRNA_012732: Negatively correlated with BASDAI (r = −0.284), BASFI (r = −0.279), hsCRP (r = −0.334), and GLOB (r = −0.431); positively correlated with lymphocyte count (r = 0.260), mean corpuscular volume (r = 0.367), and ALB (r = 0.307).
  • hsa_circRNA_008961: Negatively correlated with platelet count (r = −0.334).

5. Diagnostic Potential

ROC curve analysis demonstrated diagnostic utility for:

  • hsa_circRNA_001544: AUC = 0.720 (95% CI: 0.610–0.831).
  • hsa_circRNA_102532: AUC = 0.642 (95% CI: 0.521–0.762).

6. Predicted miRNA Interactions

Bioinformatic analysis identified target miRNAs for the four circRNAs, including hsa-miR-3681-5p (targeting hsa_circRNA_001544) and hsa-miR-144-5p (targeting hsa_circRNA_102532), which are implicated in inflammatory pathways.

Discussion

circRNAs as Regulators in AS Pathogenesis

The study highlights the dysregulation of circRNAs in AS PBMCs, with hsa_circRNA_001544 and hsa_circRNA_102532 emerging as potential diagnostic biomarkers. The parent gene of hsa_circRNA_001544, NR3C1 (nuclear receptor subfamily 3 group C member 1), encodes the glucocorticoid receptor, which modulates immune responses and has been linked to autoimmune diseases like rheumatoid arthritis. The upregulation of this circRNA in AS suggests a compensatory mechanism to regulate inflammation.

hsa_circRNA_012732, derived from MYSM1 (Myb-like SWIRM and MPN domain 1), exhibited dynamic expression tied to disease activity. MYSM1 is a known suppressor of innate immunity, and its downregulation in active AS aligns with heightened inflammatory states. The negative correlation of hsa_circRNA_012732 with hsCRP and BASDAI underscores its potential as a biomarker for monitoring disease progression.

Mechanistic Insights from Pathway Analysis

KEGG enrichment of upregulated circRNAs in MAPK and TNF signaling pathways aligns with the pro-inflammatory milieu of AS. Conversely, downregulated circRNAs in cancer-related pathways (e.g., endometrial cancer) suggest shared molecular mechanisms between AS and oncogenesis, warranting further exploration.

Clinical Implications

The diagnostic accuracy of hsa_circRNA_001544 (AUC = 0.720) positions it as a promising noninvasive biomarker for AS, complementing existing tools like HLA-B27 and imaging. Its elevation in both active and stable AS implies utility in early diagnosis, while hsa_circRNA_012732’s association with disease activity offers a tool for personalized treatment monitoring.

Conclusion

This study provides the first comprehensive profile of circRNA expression in AS PBMCs, revealing their involvement in disease pathogenesis and progression. hsa_circRNA_001544 and hsa_circRNA_012732 stand out as candidates for diagnostic and disease activity biomarkers, respectively. Future studies should explore their functional roles in AS immunopathology and validate their clinical applicability in larger cohorts.

doi.org/10.1097/CM9.0000000000001815

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