Mouse genetic background controls the severity of kidney injury
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA922542 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23041900.fastq.gz | Fastqsanger.gz | |||
| SRR23042000.fastq.gz | Fastqsanger.gz | |||
| SRR23041901.fastq.gz | Fastqsanger.gz | |||
| SRR23042001.fastq.gz | Fastqsanger.gz | |||
| SRR23041902.fastq.gz | Fastqsanger.gz |
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Project description:Acute kidney failure and chronic kidney disease are global health issues steadily rising in incidence and prevalence. Animal models are critically needed to better understand these diseases and develop new therapies. These models are typically restricted to a single genetic background, thus fail to recapitulate the hallmarks of human nephropathies and the diversity of their associated clinical presentations. Here, we used a simple model of folic acid-induced kidney injury in 7 highly diverse mouse strains. We measure plasma and urine parameters, as well as renal histopathology and mRNA expression data at 1-, 2- and 6-weeks after folic acid administration, covering the early response and subsequent recovery from injury. We observe an extensive strain-specific response ranging from complete resistance of the CAST/EiJ to high sensitivity of the C57BL/6J, DBA/2J, and PWK/PhJ strains. We show that in these susceptible strains, the severe early kidney injury is accompanied by the induction of mitochondrial stress genes, which is associated with delayed healing and a prolonged inflammatory and adaptive immune responses 6 weeks after the insult, heralding a transition to chronic kidney disease. Our data catalogue the variability in predisposition to acute kidney injury, recovery, and transition to chronic kidney disease in laboratory strains, enabling better selection of mouse strains to study kidney disease.
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Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers. AKI biopsies sample names and CEL files are from GSE21374. All consenting renal transplant patients undergoing biopsies for cause as standard of care between 09/2004 and 10/2007 at the university of Alberta or between 11/2006 and 02/2007 at the University of Illinois were included in the analysis. In addition to the cores required for standard histopathology, we collected one core for gene expression studies. the relationship between gene expression in the biopsy and subsequent graft loss was analyzed. This dataset is part of the TransQST collection.
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