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. 2025 Nov 19;107(22):2561-2573.
doi: 10.2106/JBJS.24.01559. Epub 2025 Nov 19.

Synovial Fluid MicroRNA Biomarkers Enable Accurate Diagnosis of Hip and Knee Periprosthetic Joint Infections

Bernhard J H Frank  1   2 , Teresa L Krammer  3 , Jakob Pfeiffer-Vogl  3 , Thi Thu Huong Nguyen  3 , Andreas B Diendorfer  3 , Matthias Hackl  3 , Jochen G Hofstaetter  1   4
Affiliations

Synovial Fluid MicroRNA Biomarkers Enable Accurate Diagnosis of Hip and Knee Periprosthetic Joint Infections

Bernhard J H Frank et al. J Bone Joint Surg Am. .

Abstract

Background: Diagnosing hip and knee periprosthetic joint infections (PJIs) is challenging, necessitating sensitive and specific biomarkers for accurate diagnosis. Cell-free microRNAs (miRNAs) are emerging as noninvasive biomarkers. We hypothesized that hip and knee PJIs are associated with unique cell-free miRNA profiles in synovial fluid, which can be used for the diagnosis of infection.

Methods: Synovial fluid samples from 173 Caucasian patients undergoing septic or aseptic revision total joint replacement (TJR) of the hip or knee, as well as samples from 6 osteoarthritic knees, were analyzed. The samples were divided into a discovery group (40 samples; 50% septic) and a validation cohort (133 samples; 35% septic). Small RNA next-generation sequencing (NGS) was used to screen miRNAs in the discovery samples, with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) used to confirm the NGS findings and to validate results in the independent, larger cohort. Logistic regression and cross-validation were applied to assess the diagnostic power of individual and combined miRNAs.

Results: NGS identified 132 miRNAs with significant differences (false discovery rate < 0.05) between the septic and aseptic synovial fluid samples. Of these, 18 miRNAs were further analyzed with use of RT-qPCR in the independent cohort, with miR-223-3p and miR-338-5p showing the highest increases in septic synovial fluid (log2 fold change >4) and miR-151a-3p and miR-214-3p showing the most substantial reductions. To investigate the performance of the multivariable models, logistic regression was performed by dividing the cohort into a training set (60%) and a test set (40%), which showed improved performance relative to that of the univariate models (median area under the curve [AUC] for the multivariable models, 0.96). A subgroup analysis by joint type, gender, and synovial fluid sample preparation confirmed robust miRNA biomarker performance for PJI.

Conclusions: Cell-free miRNA levels in the synovial fluid of patients undergoing septic hip or knee TJR were altered in response to infection, indicating immune cell activity in the joint. These miRNAs offer sensitive and specific pathogen-independent biomarkers with potential clinical applications in the diagnosis of hip and knee PJI.

Level of evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

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Conflict of interest statement

Disclosure: No external funding was received for this work. T.L.K., A.B.D., and M.H. are employees of TAmiRNA, a microRNA biomarker company. The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJS/I836).

Figures

Fig. 1
Fig. 1
Figs. 1-A, 1-B, and 1-C: NGS-based analysis of miRNA biomarkers in the synovial fluid of aseptic and septic knees undergoing revision arthroplasty. Fig. 1-A: Volcano plot depicting the log2 fold change (FC) (x axis) and –log10 of the false discovery rate (FDR) (y axis) for the comparison of miRNA levels in synovial fluid between septic (n = 20) and aseptic (n = 20) knee arthroplasties. MiRNAs with an FDR of <0.05 are depicted in red. A subset of 18 miRNAs selected for further validation is depicted in green. Fig. 1-B: MA plot depicting average (A) synovial fluid abundance (log10CPM; x axis) versus log2 fold change (M; y axis). MiRNAs with an FDR of <0.05 are depicted in red. A subset of 18 miRNAs selected for further validation is depicted in green. Fig. 1-C: Heatmap based on NGS data (RPM values) for 18 miRNAs that were selected for further validation. Septic (n = 20), aseptic (n = 20), and osteoarthritic (n = 6) synovial fluid samples are shown. RPM values were ln(x + 1)-transformed. The rows are centered, and unit variance scaling was applied to the rows. Imputation was used for missing-value estimation. Rows and columns were clustered using the Pearson correlation distance and complete linkage.
Fig. 2
Fig. 2
RT-qPCR replication of the NGS results for 18 candidate miRNA biomarkers. AUC values obtained by RT-qPCR (y axis) are plotted against those obtained by NGS data (x axis) for the differentiation of septic from aseptic synovial fluid samples.
Fig. 3
Fig. 3
Heatmap showing the expression (log10CPM) of the selected miRNA panel in cell types present in joint tissue (bone, cartilage, tendon), as well as in adaptive and innate immune cell types. PJI miRNA biomarker candidates showed enriched expression in either hematopoietic or mesenchymal-derived cell types. PBMC = peripheral blood mononuclear cells.
Fig. 4
Fig. 4
Figs. 4-A and 4-B: Development of multivariable miRNA models for the diagnosis of PJIs in the knee and hip. Fig. 4-A: A flowchart illustrating the process for the development of the classification models. For each univariate or multivariable model, the data were partitioned into a training set (∼60%, or 105 samples) and a test set (∼40%, or 68 samples). The training set was used to develop a logistic regression model using cross-validation to increase the robustness for parameter selection. The model parameters were then fixed and applied to the independent test set to assess model performance based on ROC analysis. Fig. 4-B: Box-and-whisker plot depicting the performance (AUC value) obtained from univariate (single miRNA) and multivariable (2, 3, or 4 miRNAs) models in the test data set. A nonparametric Kruskal-Wallis test was performed to compare the observed performance (AUC values) between the univariate and multivariable models. The whiskers represent the range, the bounds of the boxes represent the 1st and 3rd quartiles, and the horizontal lines represent the median.
Fig. 5
Fig. 5
Figs. 5-A through 5-E: Diagnostic performance of bivariable miRNA models for PJIs. Fig. 5-A: Model performance in the form of AUC values, which were determined from the test set of bivariable miRNA classification models, is shown. For each miRNA, its individual AUC value (blue dot, single miRNA) as well as the AUC values obtained from pairing the miRNA with each of the 17 remaining miRNAs (red box, paired model) are shown. Figs. 5-B through 5-E: The diagnostic performance of the logistic regression model, expressed as the probability of being septic (P | septic), derived from miR-338-5p and miR-214-3p in the validation cohort (n = 133) (Fig. 5-B) and total cohort (n = 173) (Fig. 5-C), as well as in the subgroups of total knee arthroplasties (n = 151) (Fig. 5-D) and total hip arthroplasties (n = 22) (Fig. 5-E).
Fig. 6
Fig. 6
Diagnostic performance of miR-338-5p and miR-214-3p by subgroup. The diagnostic performance of the logistic regression model, expressed as the probability of being septic (P | septic), derived from miR-338 and miR-214 in female patients (n = 106) (Fig. 6-A), male patients (n = 67) (Fig. 6-B), synovial fluid (SF) samples collected by centrifugation (n = 127) (Fig. 6-C), and native SF samples (n = 46) (Fig. 6-D), as well as in culture-negative versus culture-positive PJIs (Fig. 6-E) and across early acute, late acute, and chronic infections (Fig. 6-F).
Fig. 7
Fig. 7
Proposed mechanism of action for miRNA biomarkers of PJIs in synovial fluid. During PJI, 2 main mechanisms may contribute to the observed increase or decrease in miRNA levels in synovial fluid: (1) the infiltration and activation of specific immune cell types, reflecting innate (granulocyte) and adaptive (T, B, or NK cell) immunity, results in the release of cell type-enriched miRNAs into synovial fluid, and (2) the exposure of joint-tissue cells to cytokines or pathogen-associated molecular patterns activates inflammatory response pathways and results in altered transcription and, consequently, the release of miRNAs into synovial fluid. EV = extracellular vesicle, RISC = RNA-induced silencing complex. Created in BioRender. Hackl, M. (2025) https://BioRender.com/a60j396.
See this image and copyright information in PMC

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