PROFILING CIRCULATING MICRORNAS IN EARLY OSTEOARTHRITIS AND EARLY RHEUMATOID ARTHRITIS

Document Type

Conference Proceeding

Publication Date

4-1-2024

Publication Title

Osteoarthritis Cartilage

Abstract

Purpose (the aim of the study): In clinical settings, osteoarthritis (OA) and rheumatoid arthritis (RA) can present similarly and therefore can be difficult to distinguish, especially at early stages of single-joint disease when symptoms overlap. OA is most often assessed through radiography [e.g., Kellgren-Lawrence (KL) grading] by changes in bone (e.g., osteophytes) and joint space narrowing, features that are less obvious in early stages. Meanwhile, RA is diagnosed through symptom duration and serological factors which can overlap with other inflammatory conditions, especially in early stages. These limitations in current diagnostic methods for early stages of OA and RA can lead to delays in timely diagnosis and management, which is particularly problematic for RA since treatments are available. Accordingly, there is a need to identify biomarkers that can reliably differentiate early OA from early RA. A promising group of candidate biomarkers are circulating microRNAs (miRNAs) given their specificity, stability, and ease of detection in liquid biopsies. Here we aim to use microRNA-sequencing (miRNA-seq) to profile circulating miRNAs that can distinguish early OA patients from early RA patients. Methods: We collected plasma samples that were carefully matched for sex, age, and BMI, utilizing our Henry Ford Health Arthritis Biobank and the Nashville VA Medical Center Biobank. Early OA was defined as individuals with knee pain and radiographic KL 0 or 1, and early RA was defined as treatment-naïve individuals with <6 months of symptoms and anti-citrullinated protein antibodies within 24-2613.5 U/mL. We subjected these samples to miRNA-seq according to our previously published protocols. Briefly, RNA isolated from plasma was sequenced on an Illumina NextSeq2000 system using a 75-bp single-end read protocol at a depth of approximately 12 million reads/sample. Analysis through our previously optimized pipeline involved alignment to reference databases (miRBase v22.1 and human genome vGRCh38), filtering out low count miRNAs, and principal component analysis (PCA) to assess potential confounding variables. Following normalization by total counts, differentially expressed (DE) miRNAs were identified using a quasi-likelihood F-test with trended dispersion. The list of DE miRNAs was filtered by FDR <0.05 to identify statistically significant miRNAs in early OA versus early RA. Results: We performed miRNA-seq on plasma samples obtained from N=12 early OA individuals [6 female, 49 years (SD 11), BMI 28 kg/m2(SD 5)] and N=6 early RA individuals [2 female, 56 years (SD 8), BMI 27 kg/m2 (SD 5)]. Following initial filtering for abundance (miRNAs with >10 counts/million in more than 2 samples), we identified 285 miRNAs that were present in all 18 samples. These included three miRNAs previously reported in literature: hsa-miR-199a-5p and hsa-miR-671-3p in early OA by Ali et al. (2020) and hsa-miR-361-5p for early RA by Romo-Garcia et al. (2019). PCA with 285 miRNAs showed distinct clustering between early OA and early RA [Fig. 1A], while clustering was not observed when samples were coded by sex, age, and BMI [Fig. 2B]. DE analysis identified 100 miRNAs that were significantly dysregulated between early OA and early RA at p-value <0.05, including hsa-miR-671-3p (p=0.02). More stringent analysis using FDR <0.05 identified 24 upregulated and 19 downregulated miRNAs in early OA compared to early RA. Conclusions: Utilizing miRNA-seq as the current gold-standard approach for profiling circulating miRNAs, we found a distinct profile differentiating early OA and early RA samples. Our findings also support previously reported miRNAs identified in early OA and early RA. Ongoing experiments seek to first validate the top DE miRNAs filtered based on FDR in independent samples, and second construct a predictive model to determine their accuracy in distinguishing early OA from early RA. We expect findings from this study to pave the way for developing diagnostic blood tests to reliably distinguish early OA and early RA patients in primary car settings, thereby expediting delivery of interventions at stages of disease when opportunities for mitigation still exist. [Formula presented]

Volume

32

First Page

S140

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