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Not all controls are made equal: Definition of human kidney reference samples by single cell gene expression profiles
Medrxiv : the Preprint Server for Health Sciences
|April 1, 2025
Summary
Reference kidney tissue sample types significantly impact research findings. Accounting for procurement method and donor age is crucial for accurate kidney disease mechanism identification.
Area of Science:
- Renal pathology and molecular biology
- Single-cell genomics and transcriptomics
- Biomarker discovery in kidney disease
Background:
- Identifying kidney disease mechanisms relies on comparing diseased tissues with healthy references.
- The influence of sample procurement, storage, and donor characteristics on reference tissues is poorly understood.
- Variations in reference samples can confound differential gene expression analyses.
Purpose of the Study:
- To evaluate three distinct kidney reference sample types for integrity and injury biomarkers.
- To assess the impact of reference sample variations on identifying differentially expressed genes (DEGs) in diabetic kidney disease (DKD).
- To develop tools for controlling age and tissue procurement effects in molecular analyses.
Main Methods:
- Analysis of single-cell gene expression profiles from three reference tissue types: tumor nephrectomies (TN), living donor biopsies (LD), and healthy control biopsies (HC).
- Evaluation of injury/disease markers and cell state proportions.
- Identification of gene sets associated with procurement effects and age-related transcriptional signatures.
Main Results:
- Distinct transcriptional profiles were observed across TN, LD, and HC samples, influenced by procurement method and age.
- TN samples showed higher expression of stress response genes and underlying pathology compared to LD.
- Procurement and age-associated gene sets were identified, impacting DEG analysis in DKD comparisons.
Conclusions:
- Kidney reference sample type critically influences molecular profiling and disease association studies.
- Accounting for age and tissue procurement effects is essential for accurate interpretation of DEGs in kidney diseases like DKD.
- Standardized reference sample selection and data normalization are vital for robust molecular evaluation of kidney pathologies.
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