Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
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GROUP CONDITION SAMPLES
plastic adherent bone marrow stromal progenitor
GSM5464033 GSM5464034
GSM5464031 GSM5464032
GSM5464029 GSM5464030
Description

Submission Date: Jul 20, 2021

Summary: The mechanisms of obesity and type 2 diabetes (T2D)-associated impaired fracture healing are poorly studied. In a murine model of T2D reflecting both hyperinsulinemia induced by high fat diet (HFD) and insulinopenia induced by treatment with streptozotocin (STZ), we examined bone healing in a tibia cortical bone defect. A delayed bone healing was observed during hyperinsulinemia as newly formed bone was reduced by – 28.4±7.7% and was associated with accumulation of marrow adipocytes at the defect site +124.06±38.71%, and increased density of SCA1+ (+74.99± 29.19%) but not Runx2+osteoprogenitor cells. We also observed increased in reactive oxygen species production (+101.82± 33.05%), senescence gene signature (≈106.66± 34.03%) and LAMIN B1- senescent cell density (+225.18± 43.15%), suggesting accelerated senescence phenotype. During insulinopenia, a more pronounced delayed bone healing was observed with decreased newly formed bone to -34.9± 6.2% which was inversely correlated with glucose levels (R2=0.48, p<0.004) and callus adipose tissue area (R2=0.3711, p<0.01). Finally, to investigate the relevance to human physiology, we observed that sera from obese and T2D patients exerted inhibitory effects on osteoblastic and enhanced adipocyte differentiation of human bone marrow stromal stem cells. Our data demonstrate that T2D exerts negative effects on bone healing through inhibition of osteoblast differentiation of skeletal stem cells and induction of accelerated bone senescence and that the hyperglycaemia per se and not just insulin levels is detrimental for bone healing.

GEO Accession ID: GSE180504

PMID: 35257177

Description

Submission Date: Jul 20, 2021

Summary: The mechanisms of obesity and type 2 diabetes (T2D)-associated impaired fracture healing are poorly studied. In a murine model of T2D reflecting both hyperinsulinemia induced by high fat diet (HFD) and insulinopenia induced by treatment with streptozotocin (STZ), we examined bone healing in a tibia cortical bone defect. A delayed bone healing was observed during hyperinsulinemia as newly formed bone was reduced by – 28.4±7.7% and was associated with accumulation of marrow adipocytes at the defect site +124.06±38.71%, and increased density of SCA1+ (+74.99± 29.19%) but not Runx2+osteoprogenitor cells. We also observed increased in reactive oxygen species production (+101.82± 33.05%), senescence gene signature (≈106.66± 34.03%) and LAMIN B1- senescent cell density (+225.18± 43.15%), suggesting accelerated senescence phenotype. During insulinopenia, a more pronounced delayed bone healing was observed with decreased newly formed bone to -34.9± 6.2% which was inversely correlated with glucose levels (R2=0.48, p<0.004) and callus adipose tissue area (R2=0.3711, p<0.01). Finally, to investigate the relevance to human physiology, we observed that sera from obese and T2D patients exerted inhibitory effects on osteoblastic and enhanced adipocyte differentiation of human bone marrow stromal stem cells. Our data demonstrate that T2D exerts negative effects on bone healing through inhibition of osteoblast differentiation of skeletal stem cells and induction of accelerated bone senescence and that the hyperglycaemia per se and not just insulin levels is detrimental for bone healing.

GEO Accession ID: GSE180504

PMID: 35257177

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

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Perturbation Condition

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Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.