Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities
Abstract
:1. Introduction
2. MicroRNAs: Basic Concepts
2.1. MicroRNA Biogenesis and Biological Roles
2.2. The Roles of miRNAs in Bone Development
2.3. The Roles of miRNAs in OA Pathogenesis
3. The Potential of Circulating miRNA as Biomarkers for Osteoarthritis
3.1. Challenges in Using c-miRNAs as Biomarkers for OA: Why Are c-miRNAs Not Being Used in Clinical Applications Yet?
3.1.1. Strengths
3.1.2. Weaknesses
- (i)
- Study design and cohort selection: For clinical application, the most critical evaluation criteria for c-miRNAs as diagnostic and prognostic biomarkers are high sensitivity and specificity to avoid false-positive or false-negative diagnoses. To this end, it is essential to have a larger sample size to be able to discriminate OA patients from healthy controls or assess the severity of the disease [28]. Given the numerous criteria used in clinical applications, such as age, gender, ethnicity, lifestyle, and medical history, it is essential to avoid studies with limited sample sizes. The severity of OA is another factor that should be taken into account. As mentioned in the Introduction, the severity of KOA is assessed using a scale that categorizes the severity of KOA into five grades, ranging from grade 0 (normal) to grade 4 (severe) through visual inspection of X-ray or MRI images [5].
- (ii)
- Preanalytical stage: Several preanalytical factors may affect the profiles and levels of c-miRNAs. We recently reviewed the main preanalytical factors affecting the profile and concentration of miRNAs in circulation when they are examined as potential biomarkers for cardiovascular diseases (CVDs) [163], which are also summarized herein. One of the most critical factors is the selection of the blood fraction (whole blood, plasma, or serum), sample collection (e.g., needle gauge), anticoagulant (for plasma collection), centrifugation conditions, and handling/storage conditions of the samples (Figure 2). These factors significantly impact miRNA profiles and are usually overlooked. Furthermore, based on the results of this work and our previous work [163] and that of others [68], the sample source is one of the most critical aspects in determining c-miRNA concentrations [164] for various diseases, including OA. Plasma is often favored over serum as a source of c-mRNAs, since the coagulation process can release RNA molecules, potentially altering the genuine profile of c-miRNAs. However, plasma may contain cellular components such as apoptotic or lysed cells (e.g., red blood cells-RBCs and platelets) that may contribute miRNAs. Furthermore, anticoagulants like citrate and heparin citrate, which are used to isolate plasma, can inhibit downstream methodologies, including RT-qRCR. Therefore, serum is often deemed the optimal fraction for detecting c-miRNAs [165,166]. Furthermore, using whole blood as a source of miRNAs should be avoided because cellular fraction could also contribute miRNAs [167]. Therefore, we suggest that results from studies employing different blood fractions and types of blood tubes not be compared directly. Most crucially, only miRNAs that are not marginally up- or downregulated are likely to be suitable as clinical biomarkers. However, as presented in Table 1 and Table 2, various blood fractions have been used in different studies investigating the potential of c-miRNAs as biomarkers for OA. Furthermore, in some studies, the type of collection tube used and the centrifugation conditions were not reported (Table 1 and Table 2).
- (iii)
- Analytical stage: The platform used for miRNA evaluation introduces a notable source of error in the analytical phase. Common platforms include next-generation sequencing (NGS), microarrays, and RT-qPCR, each with unique pros and cons [174,175]. As illustrated in Table 1 and Table 2, most studies aimed at validating miRNAs as biomarkers for OA have employed RT-qPCR, which is cost-effective and fast but limited by low throughput. Moreover, the efficiency of each method depends on the quality of the starting material. Notably, c-miRNA levels isolated with different protocols vary significantly, and direct comparisons should be avoided [176]. Therefore, the analytical protocols and platform must be unchanged [146].
- (iv)
- Data analysis and normalization: In the post-analytical stage, reference gene selection and normalization strategy are key challenges in miRNA quantification due to the lack of a standardized methodology. RT-qPCR data for miRNA expression can be normalized using single or multiple endogenous or exogenous reference genes or the averaged expression value of all measured miRNAs (reviewed in [68,163]). As illustrated in Table 1 and Table 2, studies aimed at validating miRNA as biomarkers for OA have used a variety of normalization strategies. Given the variables affecting miRNA quantification in the preanalytical, analytical, and post-analytical stages, it is vital to establish detailed, standardized guidelines for consistent and comparable miRNA expression data across studies and labs. Establishing universal guidelines and protocols is critical for c-miRNAs to become clinically valid biomarkers. Overall, normalization is crucial when determining c-miRNAs expression levels. Although various reference genes have been proposed, further studies are needed to identify the most reliable normalization method. This might vary depending on the miRNA release route (e.g., microparticles or protein-bound) [177]. Establishing an optimal endogenous control for each type of cardiovascular disease is essential, as specific c-miRNA expression profiles and/or levels may vary. Several studies suggest the use of multiple reference genes or a suitable combination thereof and a standard concentration of spike-in miRNAs for normalization. All samples should be simultaneously processed using identical starting volumes [178].
3.1.3. Opportunities
3.1.4. Threats
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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miRNA | Contribution in OA | Studies on the Role of miRNA in OA a | |||
---|---|---|---|---|---|
Source/ Extraction | Detection/ Normalization | Main Findings/Regulation | Ref | ||
9 | Involved in chondrocyte hypertrophy and matrix degradation | Bone and cartilage/ TRIzol | RT-qPCR/ 18S RNA | Upregulated in OA bone and cartilage tissue | [116] |
Involved in the development of KOA through the NF-kB1 pathway in chondrocytes | KOA b cartilage/ TRIzol | RT-qPCR/ U6 snRNA | Downregulated in KOA compared to the control group | [117] | |
16 | Involved in cartilage homeostasis and structure | Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Upregulated in KOA patients | [118] |
Articular cartilage from hip or KOA/N.A. c | Northern Blot & RT-qPCR/U6 snRNA | Upregulated in chondrocytes of OA (KL d grades 3 and 4) | [119] | ||
SF e and plasma/ Phenol chloroform and High Pure miRNA Isolation Kit | RT-qPCR/ cel-miR-39 | Downregulated in KOA patients | [120] | ||
16-5p | Controls the development of osteoarthritis by targeting SMAD3 in chondrocytes | Cartilage/ TRIzol | RT-qPCR/ U6 snRNA | Upregulated | [121] |
21 |
| Articular chondrocytes/ TRIzol | RT-qPCR/ U6 snRNA | Upregulated in KOA patients | [122] |
27 | Associated with chondrocyte degradation | SF and serum (animal model)/miRNeasy Mini Kit | RT-qPCR/ cel-miR-39 | Upregulated in both serum and synovial fluid | [123] |
27a-3p 27b-3p 27a-5p | SF/miRCURY RNA isolation kit | RT-qPCR/ mean Cq values of all detected miRNAs detected | Increased levels of miR27a-3p and 27b-3p and decreased levels of miR27a-5p in late-stage OA (compared to early-stage OA) | [124] | |
29a |
| Articular cartilage from hip or knee OA/N.A. | Northern blot & RT-qPCR/ U6 snRNA | Downregulated | [119] |
29c | Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Upregulated in the plasma of KOA patients compared to healthy controls | [118] | |
30a | Members of the miR-30 family:
| Cartilage/ TRIzol | RT-qPCR/ U6 snRNA | Upregulated in primary AC f cells from KOA patients compared to healthy controls | [125] |
30b | Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Increased in the plasma of KOA patients compared to healthy controls | [118] | |
34a and 34b |
| Bone and cartilage/ TRIzol | RT-qPCR/ 18S RNA | Both are overexpressed in the AC of KOA patients | [116] |
126 |
| Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Upregulated in the plasma of KOA patients compared to healthy controls | [118] |
132 | Downregulation of miR-132:
| SF and Plasma/ Phenol & High Pure miRNA Isolation Kit (Roche) | RT-qPCR/ cel-miR-39 | Downregulated:
| [120] |
Serum/TRIzol | RT-qRCT/ U6 snRNA | Downregulated | [126] | ||
140 | Influences chondrocyte differentiation and cartilage homeostasis and suppresses catabolic gene expression | SF and cartilage/microRNA Kit (Norgen) | RT-qRCT/ U6 snRNA | Downregulated: Expression levels correlated with OA severity | [127] |
146a | Regulates inflammatory and catabolic gene expression | Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Upregulated | [118] |
146a-5p | Regulates the expression of inflammatory cytokines | Serum and cartilage/ miRCURY RNA Isolation Kit | RT-qRCR/hsa-miR-103a-3p, -423-5p, and -191- 5p | Upregulated | [87] |
Serum/ miRCURY Kit | NGS g/N.A. | Upregulated | [128] | ||
186 | Overexpression of miR-186 inhibits chondrocyte apoptosis in OA (see Ref. [129]) | Plasma/ miRNeasy kit | RT-qPCR/ MammU6s | Upregulated | [118] |
186-5p | Regulates chondrocyte apoptosis | Serum/ miRCURY Kit | NGS h/ N.A. | Upregulated and significantly associated with incident KOA in women | [128] |
miRNAs | OA 1 Type | Cohort | Sample/ Collection Tube/ Centrifugation (×g/Time/Temp) | Extraction/ Quantification/ Normalization | Ref |
---|---|---|---|---|---|
146-5p | HOA 2 |
| Serum Collection tube 4: N.A. 5 2000 g/10 min/N.A. | miRCURY RNA Kit/ RT-qRCR/ hsa-miR-103a-3p, -423-5p, & -191-5p | [87] |
380 miRNAs | KOA 6 |
| Plasma ETDA Tube 1800 g/10 min/RT | miRNeasy kit/ RT-qPCR/ MammU6s | [118] |
132 | N.A | Cohort of 16 men:
| Serum/ Collection tube: N.A/ 2000 g/10 min/4 °C | TRIzol/ RT-qRCT/ U6 snRNA | [126] |
140 | KOA |
| SF 7 & cartilage The collection and centrifugation conditions are not described | microRNA Kit (Norgen)/ RT-qPCR/ U6 snRN | [127] |
19 miRNAs (Validation) | KOA | PM women: Screening: KL 2–3 = 10, control group: n = 10 Validation: KL 2–3 = 43, control group: n = 42 | Serum The collection and centrifugation conditions are not described | miRCURY Kit/ NGS/ N.A | [128] |
136 | ΚOA |
| Plasma Sodium Citrate Centrifugation conditions are not available | RNAVzol LS/ RT-qPCR/ U6 snRNA | [142] |
2578 miRNAs (Validation) | KOA | KOA who received celecoxib treatment for six weeks Screening KL 2: n = 4 & KL 3: n = 2 Validation KL 2: n = 159 & KL 3: n = 59 | Plasma The collection and centrifugation conditions are not described | TRIzol/ RT-qPCR U6 snRNA | [148] |
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Felekkis, K.; Pieri, M.; Papaneophytou, C. Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities. Int. J. Mol. Sci. 2023, 24, 13144. https://doi.org/10.3390/ijms241713144
Felekkis K, Pieri M, Papaneophytou C. Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities. International Journal of Molecular Sciences. 2023; 24(17):13144. https://doi.org/10.3390/ijms241713144
Chicago/Turabian StyleFelekkis, Kyriacos, Myrtani Pieri, and Christos Papaneophytou. 2023. "Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities" International Journal of Molecular Sciences 24, no. 17: 13144. https://doi.org/10.3390/ijms241713144
APA StyleFelekkis, K., Pieri, M., & Papaneophytou, C. (2023). Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities. International Journal of Molecular Sciences, 24(17), 13144. https://doi.org/10.3390/ijms241713144