Evidence map›Paper›PMID 40865271›Full record

ArticleBiomaterials advances2026

Genomechanical modeling of delayed fracture healing integrating transcriptomics and tissue mechanics.

Nazanin Nafisi, Ahmad Hedayatzadeh Razavi, Mohammad Sadegh Ghiasi, Patrick Minassians, Philip Hanna, Aron Lechtig, Kaveh Momenzadeh, Abraham Mahjoob, Samantha Perez, Mario Keko and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomaterials advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Nazanin NafisiMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Department of Mechanical Engineering, Boston University, Boston, MA, USA.
Ahmad Hedayatzadeh RazaviMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Department of Mechanical Engineering, Boston University, Boston, MA, USA.
Mohammad Sadegh GhiasiMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Patrick MinassiansMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Philip HannaMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Aron LechtigMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Harvard Combined Orthopaedic Residency Program, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Kaveh MomenzadehMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Abraham MahjoobMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Samantha PerezMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Mario KekoCarl J. Shapiro Department of Orthopaedics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Ramin OftadehMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Mahboubeh R RostamiDepartment of Genetic Medicine, Weill Cornell Medicine, New York, NY, USA.
Ashkan VaziriBiosensics, LLC, Newton, MA, USA.
Rosalynn M NazarianPathology Service, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Louis GerstenfeldDepartments of Orthopaedic Surgery and Biochemistry, Chobanian and Avedissian Boston University School of Medicine, Division of Graduate Medical Sciences Research Professor, Boston University School of Medicine, Department of Biochemistry, USA.
Marc N WeinEndocrine Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Fatemeh MirzamohammadiDepartment of Orthopedic and Plastic Surgery, Wright State University, Dayton, OH, USA.
Ara NazarianMusculoskeletal Translational Innovation Initiative, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Department of Mechanical Engineering, Boston University, Boston, MA, USA; Department of Orthopaedic Surgery, Yerevan State Medical University, Yerevan, Armenia. Electronic address: anazaria@bidmc.harvard.edu.

Funding

A Systems Genetics Approach to Identify BMD GenesR01AR071657 · NIAMS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI FARBER, CHARLES R, GERSTENFELD, LOUIS CHARLES · 2018 to 2022
$3.9M
The role of salt inducible kinases in parathyroid hormone action in boneR01DK116716 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Marc Nathan Wein · 2018 to 2026
$3.8M
A Systems Genetics Approach to Fracture HealingR01AR059741 · NIAMS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI GERSTENFELD, LOUIS CHARLES · 2012 to 2016
$1.8M
An Evaluation of Serum Based Indices to Assess Fracture HealingR21AR067900 · NIAMS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI GERSTENFELD, LOUIS CHARLES · 2015 to 2016
$397k
NIAMS NIH HHS R01 AR059741NIAMS NIH HHS R01 AR071657NIAMS NIH HHS R21 AR067900NIDDK NIH HHS R01 DK116716
6 · The paper itself

Abstract

Fracture healing is a complex biological process that involves a coordinated interplay of immune responses, gene regulation, and mechanical forces. This study integrates advanced transcriptomic (RNA sequencing) and biomechanical modeling approaches to uncover the key molecular pathways and mechanical properties that drive bone repair. Using a rat femoral delayed fracture model, researchers analyzed gene expression changes, immune cell dynamics, and tissue mechanics at different healing stages. The findings reveal critical shifts in inflammation, cartilage formation, and bone remodeling, highlighting the role of signaling pathways such as Wnt and TGF-β in regulating these transitions. Additionally, the study introduces a genomechanical (GM) model that incorporates gene expression data into predictive biomechanical simulations. This approach allows for a more accurate prediction of tissue differentiation and mechanical strength changes over time. The study demonstrates how genetic and mechanical factors work together to optimize healing and identifies potential therapeutic targets to improve fracture recovery, especially in conditions such as diabetes, aging, and obesity, where healing is impaired. Importantly, this work introduces an integrative modeling framework that incorporates dynamic upstream regulator activity into a mechanoregulatory framework, enabling time-resolved simulation of gene-driven tissue transitions. The GM model provides a biologically informed platform for predicting healing trajectories and identifying optimal therapeutic windows, setting the stage for future applications in personalized and condition-specific treatment planning. By bridging molecular biology with mechanical modeling, this research provides new insights into the biological mechanisms of bone repair, paving the way for personalized treatment strategies. The GM model offers a powerful tool for predicting healing outcomes and designing targeted interventions, ultimately improving patient care in orthopaedic medicine. These findings contribute to a growing body of knowledge that seeks to enhance fracture healing through precision medicine and advanced computational modeling.

Indexed as

Fracture HealingModels, BiologicalTranscriptomeAnimalsBiomechanical PhenomenaRatsBiomechanical modelingFracture healingGene expressionImmune modulationTranscriptomics

Identifiers

PMID40865271
PMCPMC13138257

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.