The Body-wide Transcriptome Landscape of Disease Models

Area of Science:

• Genomics
• Systems Biology
• Translational Medicine

Background:

• Most diseases impact multiple organs, yet comprehensive body-wide effects are poorly understood.
• Understanding systemic disease manifestations is crucial for effective diagnosis and treatment.

Purpose of the Study:

• To create a body-wide transcriptome landscape across diverse organs in mouse models of major diseases.
• To identify novel disease biomarkers, inter-organ communication pathways, and cross-species disease relationships.

Main Methods:

• Transcriptome profiling across 13-23 organs in mouse models of myocardial infarction, diabetes, kidney diseases, cancer, and premature aging.
• Bioinformatic analysis to identify differential gene expression and gene-expression network activities.
• Development of a cross-species map correlating organ-to-organ and model-to-disease relationships between humans and mice.

Main Results:

• Identified differential gene expression in diverse organs across all disease models.
• Characterized the skin as a "disease-sensor" organ via disease-specific gene expression network activities.
• Discovered a bone-skin crosstalk mediated by FGF23 in response to phosphate dysregulation, linked to kidney disease.
• Proposed candidate pathways for numerous inter-organ communications in disease states.
• Generated a cross-species map of organ-to-organ and model-to-disease relationships.

Conclusions:

• Body-wide transcriptome datasets from mouse models offer a valuable resource for biological and medical research.
• The findings provide insights into systemic disease effects and potential targets for diagnosis and therapeutic strategies.
• This research highlights the potential for leveraging multi-organ data to advance understanding and management of complex diseases.