<- Back to digest

JBJS - 2026-06-11 - Journal Article

Comparative Analysis of Immune Cell-Type Abundances in Periprosthetic Tissues Across Arthroplasty Failure Etiologies: Use of Transcriptomic Deconvolution.

Li Y, Wang F, Li Y, Mu W, Ji B, Zhang X, Cao L

retrospective cohortLOE IIIn = 185 (135 PJI, 50 aseptic failure)N/A if not reported.

Topics

arthroplasty
PMID: 42275484DOI: 10.2106/JBJS.25.01505View on PubMed ->

Key Takeaway

CIBERSORTx transcriptomic deconvolution identified 5 immune cell types significantly elevated in PJI versus aseptic failure, and a CD8+/Treg ratio above the median predicted lower infection recurrence (log-rank p=0.0252).

Summary Depth

Choose how much analysis to show on this article page.

Summary

This study applied CIBERSORTx bulk RNA-seq deconvolution to 185 periprosthetic tissue samples to determine whether transcriptomic immune cell profiling could distinguish PJI from aseptic failure and provide prognostic data. PJI tissues showed significantly elevated plasma cells, resting memory CD4+ T cells, CD8+ T cells, activated mast cells, and M1 macrophages, while aseptic failure tissues were enriched for M0/M2 macrophages and gamma delta T cells (all p<0.05 after Benjamini-Hochberg correction). Among PJI patients, those with a CD8+/Treg ratio above the median had significantly lower infection recurrence on Kaplan-Meier analysis (log-rank p=0.0252).

Key Limitation

The CD8+/Treg prognostic threshold was derived and tested within the same cohort without external validation, making the cutoff susceptible to overfitting and inapplicable to clinical decision-making until independently confirmed.

Original Abstract

BACKGROUND

Although cellularity is traditionally evaluated morphologically, an emerging transcriptome-sequencing-based algorithm enables simultaneous inference of cellular information. We studied whether cellularity profiles predicted using CIBERSORTx would (1) depict immune cell-type abundances in periprosthetic tissues across arthroplasty failure etiologies, and (2) provide prognostic value for identifying cases of periprosthetic joint infection (PJI).

METHODS

CIBERSORTx-derived cellularity profiles were evaluated in 185 periprosthetic tissue samples, including 135 from patients with PJI (64 males; median age, 66 years) and 50 from those with aseptic failure (AF) (36 males; median age, 62.5 years), that had been subjected to bulk RNA sequencing. Kaplan-Meier survival analysis was performed to assess prognostic outcomes in PJI.

RESULTS

Of the 22 evaluated cell types, 5 were significantly elevated in PJI cases: plasma cells, resting memory CD4+ T cells, CD8+ T cells, activated mast cells, and M1 macrophages (all p < 0.05 after Benjamini-Hochberg [BH] correction). Conversely, 3 cell types were significantly elevated in AF cases: gamma delta T cells, M0 macrophages, and M2 macrophages (all p < 0.05 after BH correction). Of the combined immune cell populations, total B cells, total T cells, and natural killer cells were significantly elevated in PJI cases, while total macrophages/monocytes were significantly elevated in AF cases (all p < 0.05 after BH correction). Patients with PJI who had a CD8+/regulatory T cell (Treg) ratio above the median had a significantly lower rate of infection recurrence than those below the median (log-rank p = 0.0252).

CONCLUSIONS

CIBERSORTx analysis of samples from periprosthetic tissues predicted distinct immune cell profiles that differed between PJI and aseptic arthroplasty failure modes, and also identified a high CD8+/Treg ratio as a potential prognostic marker. This transcriptomic approach provides a novel, single-assay strategy for evaluating local immune cell responses across arthroplasty failure etiologies.

CLINICAL RELEVANCE

The comparative analysis of immune cell-type abundances in periprosthetic tissues across arthroplasty failure etiologies revealed distinct immune microenvironment signatures that differentiate PJI from AF. Additionally, the finding that a higher CD8+/Treg cell ratio is associated with a lower rate of infection recurrence offers a potential prognostic marker to help identify patients with PJI who are at a lower risk for treatment failure.