Bone protein analysis via label-free quantitative proteomics in patients with periprosthetic joint infection

Bone and periosteum protein analysis via tandem mass tag quantitative proteomics in pediatric patients with osteomyelitis

Bone healing is crucial in managing osteomyelitis after fracture fixation. Understanding the mechanism of extensive callus formation in pediatric osteomyelitis is highly important. This study aims to analyze bone and periosteum samples from pediatric patients to elucidate the essential processes involved in callus formation during osteomyelitis. The study included eight patients from our hospital: four with positive microbial culture who underwent osteomyelitis debridement and four who had osteotomy surgery as contral. We used tandem mass tag quantitative proteomics to investigate proteomic changes in bone and periosteum tissues obtained from these patients. Differential expression proteins were analyzed for their pathways through Gene Ontology (GO) annotation, GO enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction networks. A total of 4737 proteins were successfully identified. About 2224 differentially expressed proteins were detected in the bone tissues group and periosteum tissues group. Among the differentially expressed proteins, 10 protein genes in the bone group were associated with inflammation and osteogenesis, while in the periosteum group were nine. Cytochrome b-245, beta polypeptide (CYBB), nicotinamide phosphoribosyltransferase (NAMPT), tissue inhibitor of metalloproteinases 1 (TIMP-1), Raf-1 proto-oncogene, serine/threonine kinase (RAF-1), RELA proto-oncogene, NF-KB subunit (RELA), and sphingomyelin synthase 2 (SGMS2) may play an important role in callus formation in patients with osteomyelitis. This study provides novel clues for understanding callus formation in pediatric patients with osteomyelitis.

Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Differences in the Synovial Fluid Proteome of Septic and Aseptic Implant Failure

Implant loosening is a severe complication after total joint replacement. Here, differential diagnosis between septic and aseptic cases is crucial for further surgical treatment, but low-grade periprosthetic joint infections (PJIs) in particular remain a challenge. In this study, we analyzed the synovial fluid proteome of 21 patients undergoing revision surgery for septic (eight cases) or aseptic (thirteen cases) implant failure using LC-MS/MS to identify potential new biomarkers as future diagnostic tools. Staphylococci were found in four cases, Streptococci in two cases, Serratia marcescens and Cutibacterium acnes in one case. Proteomic analysis of the synovial fluid resulted in the identification of 515 different proteins based on at least two peptides. A statistical comparison revealed 37 differentially abundant proteins (p < 0.05), of which 17 proteins (46%) showed a higher abundance in the septic group. The proteins with the highest fold change included the known marker proteins c-reactive protein (7.57-fold) and the calprotectin components protein S100-A8 (4.41-fold) and protein S100-A9 (3.1-fold). However, the protein with the highest fold change was leucine-rich alpha-2-glycoprotein 1 (LRG1) (9.07-fold), a currently discussed new biomarker for inflammatory diseases. Elevated LRG1 levels could facilitate the diagnosis of PJI in the future, but their significance needs to be further investigated.

Proteomic Analyses of Plasma From Patients With Fracture-Related Infection Reveals Systemic Activation of the Complement and Coagulation Cascades

OBJECTIVES

The objective of this study was to compare plasma proteomes of patients with confirmed fracture-related infections (FRIs) matched to noninfected controls using liquid chromatography-mass spectrometry.

METHODS

DESIGN

This was a prospective case-control study.

SETTING

The study was conducted at a single, academic, Level 1 trauma center.

PATIENT SELECTION CRITERIA

Patients meeting confirmatory FRI criteria were matched to controls without infection based on fracture region, age, and time after surgery from June 2019 to January 2022. Tandem mass tag liquid chromatography-mass spectrometry analysis of patient plasma samples was performed.

OUTCOME MEASURES AND COMPARISONS

Protein abundance ratios in plasma for patients with FRI compared with those for matched controls without infection were calculated.

RESULTS

Twenty-seven patients meeting confirmatory FRI criteria were matched to 27 controls. Abundance ratios for more than 1000 proteins were measured in the 54 plasma samples. Seventy-three proteins were found to be increased or decreased in patients with FRI compared with those in matched controls (unadjusted t test P < 0.05). Thirty-two of these proteins were found in all 54 patient samples and underwent subsequent principal component analysis to reduce the dimensionality of the large proteomics dataset. A 3-component principal component analysis accounted for 45.7% of the variation in the dataset and had 88.9% specificity for the diagnosis of FRI. STRING protein-protein interaction network analysis of these 3 PCs revealed activation of the complement and coagulation cascades through the Reactome pathway database (false discovery rates <0.05).

CONCLUSIONS

Proteomic analyses of plasma from patients with FRI demonstrate systemic activation of the complement and coagulation cascades. Further investigation along these lines may help to better understand the systemic response to FRI and improve diagnostic strategies using proteomics.

LEVEL OF EVIDENCE

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