Biomarkers of osteoarthritis (OA) that can accurately diagnose the disease at the earliest stage would significantly support efforts to develop treatments for prevention and early intervention. We have sought to determine the time course of alterations in peripheral blood gene expression profile associated with the development of OA. Blood samples were collected from a tail vein of individual rats with monosodium iodoacetate- (MIA-) induced OA (2, 14, 21, and 28 days after the treatment). We used whole-genome microarrays to reveal OA-related transcriptional alterations of 72 transcripts. Three main groups of coexpressed genes revealed diverse time-dependent profiles of up- and downregulation. Functional links that connect expression of the gradually downregulated genes to the G13 signaling pathway were indicated. The mRNA abundance levels of the identified transcripts were further analyzed in publicly available gene expression dataset obtained from a GARP study cohort of OA patients. We revealed three-gene signature differentially expressed in both rat and human blood (TNK2, KCTD2, and WDR37). The alterations in expression of the selected transcripts in peripheral blood samples of the patients indicate heterogeneity of the OA profiles potentially related to disease progress and severity of clinical symptoms. Our study identifies several potential stage-specific biomarkers of OA progression.
Osteoarthritis (OA) is a common disease associated with damage to the cartilage and resulting in the development of bony spurs and cysts at the margins of the joints. It is characterized by progressive loss of function in the synovial joints. There are a variety of factors that play an important role in the pathogenesis of OA, including biomechanical factors, proinflammatory mediators, and proteases [
Blood-based gene expression profiling analysis is useful in discovering RNA biomarkers associated with diverse pathological conditions and disease subgroups [
The purpose of animal models of OA is to reproduce the pattern and progression of degenerative damage in a controlled fashion. The models provide unique possibility for sequential evaluation of the OA-related transcriptional alterations, including early and intermediate stages of disease [
Here, we report blood gene expression profiles associated with the development of OA in rat MIA model of OA. The dynamics in pattern alterations were monitored in each individual animal during the time course of OA progression [
Male Wistar rats (Charles River, Germany) initially weighing between 225 and 250 g were used for all the experiments. Animals were housed 5 per cage under a standard 12/12 h light/dark cycle and had free access to food and water. The procedures on animals were performed following the recommendations of the International Association of Studies on Pain and 3R policy. The study was approved by the Local Bioethics Committee of the Institute of Pharmacology PAS (approval number 938/2012). In the experiments, we compared nontreated (intact) and osteoarthritic animals. Our previous results showed no significant changes in joint hypersensitivity and DWB tests for saline-injected rats (unpublished data). Our study was aimed at the comprehensive comparison between healthy and OA-affected cartilage in respect to the “3R” rules. Rats were randomly allocated to the groups.
The rats were deeply anesthetized with 5% isoflurane (Forane®, Baxter Healthcare Corporation, USA) in 100% O2 (3 L/min) until the flexor withdrawal reflex was abolished. The skin covering the right knee joint was shaved and swabbed with 100% ethanol. A 27-gauge needle was introduced into the joint cavity through the patellar ligament, and 50
Blood samples were collected from the tail vein before (time point: 0) and 2, 14, 21, and 28 days post-MIA injection (time points: 2, 14, 21, and 28). Six replicate samples were analyzed per experimental group. Collected samples were placed in individual tubes and stored at −70°C until RNA isolation. RNA was isolated following the manufacturer’s protocol and further purified using the RNeasy Mini Kit (Qiagen Inc.). The total RNA concentration was measured using an ND-1000 Spectrometer (NanoDrop Technologies Inc., Montchanin, DE, USA).
The quality of RNA was determined by using RNA 6000 Nano LabChip Kit and Agilent Bioanalyzer 2100 (Agilent, Palo Alto, CA, USA). Preparation of cRNA was performed according to the protocol provided by Affymetrix (Santa Clara, CA). The total RNA from individual animal was further purified by using RNeasy Mini Kit (Qiagen Inc., Valencia, CA, USA). Total RNA (3
Microarray data was initially processed using GeneChip Operating Software (Affymetrix) with appropriate quality control. After background subtraction, data was normalized using quantile normalization and then log2-transformed. The obtained signal was taken as the measure of mRNA abundance derived from the level of gene expression. Microarray data were standardized using a z-score calculation. Statistical analysis was performed by dChip software using ANOVA filtering and followed by correction for multiple testing (estimation of expected false positives). Hierarchical clustering was performed using the measure of Euclidian distance and average distance linkage methods. Cluster visualization was performed using dChip software [
Gene annotation tool Enrichr was used to identify overrepresented ontological groups among the gene expression patterns and to group genes into functional classifications. Overrepresented terms (WikiPathways 2016 category) were defined by using
The microarray data set (series accession number GSE48556) was downloaded from the Gene Expression Omnibus (GEO) databases (
We used whole-genome Affymetrix Rat Gene 2.0 ST microarrays to analyze the time course of gene expression alterations in rat peripheral blood following MIA treatment (1 mg, i.a.). The early, intermediate, and relatively late changes in mRNA abundance were analyzed at four time points (2, 14, 21, and 28 days following MIA injection) and compared to day 0 before MIA treatment (Figure
Gene expression patterns in blood associated with OA progression in the rat model of the knee joint arthritis. Hierarchical clustering of MIA-induced transcriptional alterations in whole blood. Microarray results are shown as a heat map and include 41 transcripts with significantly different levels of transcript abundance. Colored rectangles represent transcript abundance 2, 14, 21, and 28 days after the intra-articular injection of the MIA of the gene labeled on the right. The intensity of the color is proportional to the standardized values (between −3 and 3) from each microarray, as indicated on the bar below the heat map image. Hierarchical clustering was performed with the dChip software using Euclidean distance and average linkage method. Major MIA-induced gene transcription patterns are arbitrarily described as A–C. The regulated genes from gene clusters A–C were labeled on the right.
Hierarchical clustering revealed three major gene transcription patterns (arbitrarily described as A–C; Figure
We have analyzed a list of the transcripts (45 microarray probes) regulated by MIA treatment in the microarray dataset obtained from the GARP study [
Gene expression profiles of three genes regulated in both animal model and human blood samples. (a) Clustering of the OA patients based on the expression of three genes commonly regulated in the blood of rats and humans. mRNA abundance levels measured by the microarrays were obtained from the GARP study [
OA is an idiopathic disease with an urgent need for effective therapies and well established molecular biomarkers that can be applied more broadly from the very early to the end stages of knee OA [
We have monitored transcriptional alterations in the rat model that reproduce time course of OA development. We report a set of 72 transcripts (representing 42 genes) with changes in the mRNA abundance levels during the OA progression. Other studies reveal various numbers of genes with the disease-altered expression in the blood [
The first group of genes showed rapid downregulation in response to MIA-treatment. The abundance levels of the transcripts went back to control level after 28 days of the experiment. These genes may serve as potential biomarkers of the initial phase of the MIA-induced OA. Surprisingly, in response to MIA injection, we did not find activation in gene expression of factors involved in inflammatory or immunological processes. The genes from this group show heterogeneous biological functions, as for example,
With the aim to validate potential biomarkers of OA progression, we looked for the common molecular changes observed in both, the animal model and OA patients [
By using expression profiles of the three identified genes, it might be possible to distinguish potential subgroups of OA patients. WDR37 protein is a member of the WD repeat protein family involved in a variety of cellular processes, including cell cycle progression, signal transduction, apoptosis, and gene regulation [
Several potential limitations should be acknowledged in the current study. The transcriptional alterations detected in the blood provide indirect indicators of pathophysiological conditions linked to the development of knee OA. The limitations of our strategy also include potential differences in OA etiology between human and animal model. Still, it is necessary to identify biomarkers of OA in preclinical research that can be applied more broadly from the very early stage to the end stage of knee OA and to design better management systems for patients with knee OA. The molecular differences may occur even if the usability of the MIA-induced model of knee OA in rats has been already validated [44]. Our analysis of molecular changes in both rats and humans was based on publicly available gene expression dataset. The conclusions from this part of the results are limited by no access to the clinical description of the patients. Despite these limitations, the obtained results may provide new biomarkers associated with the development of knee OA. Genetic biomarkers have the potential to detect early changes or to prediagnose in OA and classify the OA itself as shown in cancer. Epigenetic mechanisms in cartilage and osteoarthritis include DNA methylation, histone modifications, and microRNAs [
Gene profiling in blood indicated three major patterns of expression associated with the development of OA in a rat model. The present results suggest that alterations in G13 signaling pathway activity in the blood might be associated with the progression of the disease. The expression changes of the three selected transcripts were also found in OA patients and suggest that the molecular stratification of the patients would be possible. The obtained results indicate heterogeneity of gene expression and potential connections with the clinical profiles of the OA patients. The identified genes may provide novel candidates for stage-specific molecular biomarkers of OA progression.
Microarray data are available in the NCBI Gene Expression Omnibus (GEO: GSE99021).
The study was approved by the Local Bioethics Committee of the Institute of Pharmacology PAS (Approval no. 938/2012).
The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or nonfinancial interest in the subject matter or materials discussed in this manuscript.
This work was supported by the National Science Centre, Poland, Grants SONATA BIS NCN/2012/07/E/NZ7/01269, OPUS 2014/13/B/NZ7/02311, and ETIUDA NCN/2015/16/T/NZ7/00052 and statutory funds of the Institute of Pharmacology PAS. Natalia Malek is a recipient of a scholarship from KNOW sponsored by the Ministry of Science and Higher Education, Republic of Poland.