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. 2019 Dec;111(6):1404-1411.
doi: 10.1016/j.ygeno.2018.09.013. Epub 2018 Sep 21.

Molecular pathology of adverse local tissue reaction caused by metal-on-metal implants defined by RNA-seq

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Molecular pathology of adverse local tissue reaction caused by metal-on-metal implants defined by RNA-seq

Christopher G Salib et al. Genomics. 2019 Dec.

Abstract

Total hip arthroplasty (THA) alleviates hip pain and improves joint function. Current implant design permits long-term survivorship of THAs, but certain metal-on-metal (MoM) articulations can portend catastrophic failure due to adverse local tissue reactions (ALTR). Here, we identified biological and molecular differences between periacetabular synovial tissues of patients with MoM THA failure undergoing revision THA compared to patients undergoing primary THA for routine osteoarthritis (OA). Analysis of tissue biopsies by RNA-sequencing (RNA-seq) revealed that MoM patient samples exhibit significantly increased expression of immune response genes but decreased expression of genes related to extracellular matrix (ECM) remodeling. Thus, interplay between local tissue inflammation and ECM degradation may account for the pathology and compromised clinical outcomes in select patients with MoM implants. We conclude that adverse responses of host tissues to implant materials result in transcriptomic modifications in patients with MoM implants that permit consideration of strategies that could mitigate ECM damage.

Keywords: Adverse local tissue reaction; Cell biology; Metal-on-metal; Metallosis; Molecular genetics; Total hip arthroplasty.

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Conflict of interest statement

No other authors have conflicts of interest to disclosure.

Figures

Figure 1.
Figure 1.
Overview of the patient cohort and tissue biopsies used for RNA-seq (samples analyzed by RNA-seq are presented in bold font) (A-B). Surgical photograph of periacetabular tissue sampling in diseased patient (C) and surgical photograph of removed tissue sent for tissue processing and RNA-seq analysis (D). Intraoperative photograph of metal corrosion from metal-on-metal cobalt-chromium implant from acetabular component (E) and from explanted femoral head component (F) at the time of revision THA.
Figure 2.
Figure 2.
Synovial tissue derived from metallosis patients has a distinct gene expression profile. Unsupervised principal component analysis (A) and hierarchical clustering (B) was performed using expression profiles of genes expressed > 0.3 RPKM (n= 15,158) across all six specimens. Comparative analysis of expression data in metallosis patients (n=3) versus normal control (n=3) yields sets of upregulated (red) and downregulated (blue) genes (C) as summarized in (D).
Figure 3.
Figure 3.
Inflammatory and immune response genes are upregulated in tissue derived from metallosis patients. Gene set enrichment analysis was performed on the 1,212 upregulated genes identified in Fig. 1D. Overlap of this gene set with curated gene sets was calculated and the 10 most enriched gene lists are displayed with false discover rate (FDR) q-value shown (A). Hierarchical clustering was performed using the RPKM values for the genes associated with the “Inflammatory Response” gene set (n=454 genes) (B). Average RPKM value (n=3) for control (pTHA) and metallosis (MoM) tissues for general inflammatory response genes (C) and specific M1 macrophage markers (D). Statistical significance of MoM compared to pTHA is indicated when appropriate (*: p<0.05, **: p<0.01, ***: p<0.001, n.s.: not significant).
Figure 4 A-C.
Figure 4 A-C.
Metallosis patients demonstrate downregulation of extracellular matrix proteins and maintenance enzymes. Gene set enrichment analysis was performed on the 667 downregulated genes identified in Fig. 1D. Overlap of this gene set with curated gene sets was calculated and the 10 most enriched gene lists are displayed with false discover rate (FDR) q-value shown (A). STRING protein-protein interaction analysis was conducted with a subset of genes (n=69) associated with the “Extracellular Matrix” gene list (B). All collagen genes within this gene list were extracted, and hierarchical clustering was performed using the RPKM values for these genes after a log2 adjustment (C).
Figure 5 A-C.
Figure 5 A-C.
mRNA expression levels of the metallothionein (MT) proteins determined by RNA-Seq (A). Box and whisker plot of the mRNA expression levels for the four MTs with the highest RPKM value for each sample (n=3 in each group) (B). Box and whisker plot of the mRNA expression levels for ferritin heavy chain 1 (FTH1) and ferritin light chain (FTL) for each sample (n=3 in each group) (C). Statistical significance of MoM compared to pTHA is indicated when appropriate (*: p<0.05, **: p<0.01, ***: p<0.001)

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