Single cell cortical bone transcriptomics define novel osteolineage gene sets altered in chronic kidney disease

Area of Science:

• Bone Biology
• Single-cell Genomics
• Skeletal Diseases

Background:

• The precise molecular mechanisms driving bone dysfunction in aging, osteoporosis, and chronic kidney disease (CKD) are poorly understood due to limitations in single-cell resolution.
• Understanding these mechanisms is crucial for developing effective treatments for bone diseases.

Purpose of the Study:

• To define distinct osteoblast and osteocyte populations at the single-cell level.
• To identify molecular defects in bone cells associated with CKD.
• To investigate the early skeletal pathology in a mouse model of CKD.

Main Methods:

• Single-cell RNA sequencing (scRNAseq) and flow cytometry were performed on mouse long bone cells.
• Clustering analysis identified specific gene expression profiles for osteoblast precursors, mature osteoblasts, and osteocytes.
• Integrative analyses including ATAC-seq and single-cell flux estimation analysis (scFEA) were used for validation and functional prediction.
• A mouse model of CKD was utilized to assess gene expression changes in osteolineage cells.

Main Results:

• Distinct transcriptional signatures were identified for osteoblast precursors (Tnc, Mmp13, Spp1), mature osteoblasts (Smpd3, Col1a1, Col11a1), and osteocytes (Cd109, Ptprz1, Ramp1, Bambi, Adamts14, Spns2, Bmp2, WasI, Phex).
• Trajectory analysis predicted osteoblast-to-osteocyte transitions linked to metabolic shifts.
• In the CKD mouse model, gene expression was disturbed across all osteolineage stages even before significant skeletal alterations were apparent.

Conclusions:

• This study successfully defined distinct osteoblast and osteocyte populations at the single-cell level.
• Molecular defects were identified in multiple bone cell populations in a CKD mouse model.
• The findings suggest that bone pathology in CKD may be more widespread and initiate earlier than previously recognized.