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Early systemic immune biomarkers predict bone regeneration after trauma.

ABSTRACT: Severe traumatic injuries are a widespread and challenging clinical problem, and yet the factors that drive successful healing and restoration of function are still not well understood. One recently identified risk factor for poor healing outcomes is a dysregulated immune response following injury. In a preclinical model of orthopedic trauma, we demonstrate that distinct systemic immune profiles are correlated with impaired bone regeneration. Most notably, elevated blood levels of myeloid-derived suppressor cells (MDSCs) and the immunosuppressive cytokine interleukin-10 (IL-10) are negatively correlated with functional bone regeneration as early as 1 wk posttreatment. Nonlinear multivariate regression also implicated these two factors as the most influential in predictive computational models. These results support a significant relationship between early systemic immune responses to trauma and subsequent local bone regeneration and indicate that elevated circulating levels of MDSCs and IL-10 may be predictive of poor functional healing outcomes and represent novel targets for immunotherapeutic intervention.

SUBMITTER: Cheng A

PROVIDER: S-EPMC7923361 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Early systemic immune biomarkers predict bone regeneration after trauma.

Cheng Albert A Vantucci Casey E CE Krishnan Laxminarayanan L Ruehle Marissa A MA Kotanchek Theresa T Wood Levi B LB Roy Krishnendu K Guldberg Robert E RE

Proceedings of the National Academy of Sciences of the United States of America 20210201 8

Severe traumatic injuries are a widespread and challenging clinical problem, and yet the factors that drive successful healing and restoration of function are still not well understood. One recently identified risk factor for poor healing outcomes is a dysregulated immune response following injury. In a preclinical model of orthopedic trauma, we demonstrate that distinct systemic immune profiles are correlated with impaired bone regeneration. Most notably, elevated blood levels of myeloid-derive ...[more]

PMID: 33597299

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Project description:Bone non-unions resulting from severe traumatic injuries pose significant clinical challenges, and the biological factors that drive progression towards and healing from these injuries are still not well understood. Recently, a dysregulated systemic immune response following musculoskeletal trauma has been identified as a contributing factor for poor outcomes and complications such as infections. In particular, myeloid-derived suppressor cells (MDSCs), immunosuppressive myeloid-lineage cells that expand in response to traumatic injury, have been highlighted as a potential therapeutic target to restore systemic immune homeostasis and ultimately improve functional bone regeneration. Previously, we have developed a novel immunomodulatory therapeutic strategy to deplete MDSCs using Janus gold nanoparticles that mimic the structure and function of antibodies. Here, in a preclinical delayed treatment composite injury model of bone and muscle trauma, we investigate the effects of these nanoparticles on circulating MDSCs, systemic immune profiles, and functional bone regeneration. Unexpectedly, treatment with the nanoparticles resulted in depletion of the high side scatter subset of MDSCs and an increase in the low side scatter subset of MDSCs, resulting in an overall increase in total MDSCs. This overall increase correlated with a decrease in bone volume (P = 0.057) at 6 weeks post-treatment and a significant decrease in mechanical strength at 12 weeks post-treatment compared to untreated rats. Furthermore, MDSCs correlated negatively with endpoint bone healing at multiple timepoints. Single cell RNA sequencing of circulating immune cells revealed differing gene expression of the SNAb target molecule S100A8/A9 in MDSC sub-populations, highlighting a potential need for more targeted approaches to MDSC immunomodulatory treatment following trauma. These results provide further insights on the role of systemic immune dysregulation for severe trauma outcomes in the case of non-unions and composite injuries and suggest the need for additional studies on targeted immunomodulatory interventions to enhance healing.

Project description:BackgroundEffectively predicting the risk of adverse pregnancy outcome (APO) in women with systemic lupus erythematosus (SLE) during early and mid-pregnancy is a challenge. This study was aimed to identify potential markers for early prediction of APO risk in women with SLE.MethodsThe GSE108497 gene expression dataset containing 120 samples (36 patients, 84 controls) was downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed, and differentially expressed genes (DEGs) were screened to define candidate APO marker genes. Next, three individual machine learning methods, random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator, were combined to identify feature genes from the APO candidate set. The predictive performance of feature genes for APO risk was assessed using area under the receiver operating characteristic curve (AUC) and calibration curves. The potential functions of these feature genes were finally analyzed by conventional gene set enrichment analysis and CIBERSORT algorithm analysis.ResultsWe identified 321 significantly up-regulated genes and 307 down-regulated genes between patients and controls, along with 181 potential functionally associated genes in the WGCNA analysis. By integrating these results, we revealed 70 APO candidate genes. Three feature genes, SEZ6, NRAD1, and LPAR4, were identified by machine learning methods. Of these, SEZ6 (AUC = 0.753) showed the highest in-sample predictive performance for APO risk in pregnant women with SLE, followed by NRAD1 (AUC = 0.694) and LPAR4 (AUC = 0.654). After performing leave-one-out cross validation, corresponding AUCs for SEZ6, NRAD1, and LPAR4 were 0.731, 0.668, and 0.626, respectively. Moreover, CIBERSORT analysis showed a positive correlation between regulatory T cell levels and SEZ6 expression (P < 0.01), along with a negative correlation between M2 macrophages levels and LPAR4 expression (P < 0.01).ConclusionsOur preliminary findings suggested that SEZ6, NRAD1, and LPAR4 might represent the useful genetic biomarkers for predicting APO risk during early and mid-pregnancy in women with SLE, and enhanced our understanding of the origins of pregnancy complications in pregnant women with SLE. However, further validation was required.

Dataset Information

Early systemic immune biomarkers predict bone regeneration after trauma.

Publications

Early systemic immune biomarkers predict bone regeneration after trauma.

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