Collections / MALADAPTIVE IMMUNE-FIBROTIC AXIS DRIVES IMPAIRED LONG BONE REGENERATION UNDER MECHANICAL INSTABILITY

MALADAPTIVE IMMUNE-FIBROTIC AXIS DRIVES IMPAIRED LONG BONE REGENERATION UNDER MECHANICAL INSTABILITY

Delayed and non-healing fractures, affecting 5–10% of cases, are associated with prolonged disability and diminished quality of life. Although acute inflammation is required to initiate repair, persistent mechanical instability can sustain maladaptive immune and fibrotic responses that impede regeneration. Existing animal models do not adequately recapitulate mechanical instability, the principal driver of hypertrophic nonunion in clinical settings, thereby limiting translational relevance. In this study, we developed a murine model of delayed fracture healing using tunable intramedullary fixation to impose controlled interfragmentary strain. High-strain conditions (low-stiffness nail, 15-30% strain) produced enlarged calluses characterized by delayed ossification, increased fibrotic tissue (2.9-fold, p = 0.0099), and reduced biomechanical integrity (1.6-fold decrease in stiffness, p = 0.024) relative to low-strain controls (high-stiffness nail, <5% strain). Spatial transcriptomic analysis identified persistent fibrotic niches in high-strain calluses enriched with fibroblast-associated genes (e.g., Pdgfrb, Lgals3) and dysregulated macrophage-fibroblast signaling (Spp1, Mmp9). These findings identify mechanical instability as a driver of pathological immune-stromal interactions and establish a preclinical platform for investigating mechanobiology-informed therapeutic strategies. This work supports a conceptual framework in which hypertrophic nonunion is understood as a disorder arising from dysregulated interactions between mechanical cues and immune responses.

Datasets2
Size~34 MB
AssayVisium
Samplemouse · long bone
KindComparison
PMID:42664332 ↗
Python · lamindb
import lamindb as ln
import spatialdata as sd

coll = ln.Collection.get(key="geo-gse338404")
coll.ordered_artifacts.df()                 # the 2 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]

# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()}
Open in Vitessce
Visium
Mouse long bone
GSM9873160
mouse long bone 21 MB 3,249 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuelong bone
Size21 MB
Obs3,249
Magnificationother · 7.036 µm/px
bronze H&E Open in Vitessce
Open in Vitessce
Visium
Mouse long bone
GSM9873161
mouse long bone 13 MB 2,031 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuelong bone
Size13 MB
Obs2,031
bronze H&E Open in Vitessce

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