OMIBONE: Omics-driven computer model of bone regeneration for personalized treatment

Treatment of bone fractures are standardized according to the AO classification, which mainly refers to the mechanical stabilization required in a given situation but neglect individual differences due to patient's healing potential or accompanying diseases. Specially in elderly or immune-compromised patients, the complexity of individual constrains on a biological as well as mechanical level are hard to account for. Here, we introduce a novel framework that allows to predict bone regeneration outcome using combined proteomic and mechanical analyses in a computer model. The framework uses Ingenuity Pathway Analysis (IPA) software to link protein changes to alterations in biological processes and integrates these in an Agent-Based Model (ABM) of bone regeneration. This combined framework allows to predict bone formation and the potential of an individual to heal a given fracture setting. The performance of the framework was evaluated by replicating the experimental setup of a mouse femur fracture stabilized with an intramedullary pin. The model was informed by serum derived proteomics data. The tissue formation patterns were compared against experimental data based on x-ray and histology images. The results indicate the framework potential in predicting an individual's bone formation potential and hold promise as a concept to enable personalized bone healing predictions for a chosen fracture fixation.

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Publication Details

Journal
Bone
Published
2024-10-18
DOI
https://doi.org/10.1016/j.bone.2024.117288
Citations
2
Primary Topic
Orthopaedic implants and arthroplasty
Type
article
Field-Weighted Citation Impact
1.15

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article

OMIBONE: Omics-driven computer model of bone regeneration for personalized treatment

Sara Checa, Johannes R. Schmidt, Stefan Kalkhof, Georg N. Duda et al.
2 citations
Bone
Orthopaedic implants and arthroplasty
1.15
article

OMIBONE: Omics-driven computer model of bone regeneration for personalized treatment

Sara Checa, Johannes R. Schmidt, Stefan Kalkhof, Georg N. Duda, Mahdi Jaber, Louis C. Gerstenfeld
article en
2 citations

Abstract

Treatment of bone fractures are standardized according to the AO classification, which mainly refers to the mechanical stabilization required in a given situation but neglect individual differences due to patient's healing potential or accompanying diseases. Specially in elderly or immune-compromised patients, the complexity of individual constrains on a biological as well as mechanical level are hard to account for. Here, we introduce a novel framework that allows to predict bone regeneration outcome using combined proteomic and mechanical analyses in a computer model. The framework uses Ingenuity Pathway Analysis (IPA) software to link protein changes to alterations in biological processes and integrates these in an Agent-Based Model (ABM) of bone regeneration. This combined framework allows to predict bone formation and the potential of an individual to heal a given fracture setting. The performance of the framework was evaluated by replicating the experimental setup of a mouse femur fracture stabilized with an intramedullary pin. The model was informed by serum derived proteomics data. The tissue formation patterns were compared against experimental data based on x-ray and histology images. The results indicate the framework potential in predicting an individual's bone formation potential and hold promise as a concept to enable personalized bone healing predictions for a chosen fracture fixation.

BoneVol. 190
Boston University (US), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Fraunhofer Institute for Cell Therapy and Immunology (DE)
Bundesministerium für Bildung und Forschung
Zero hunger
Openalex Percentile: Top 20%
Orthopaedic implants and arthroplasty
1.15
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