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Chronic kidney disease involves disturbances in iron metabolism including anemia caused by insufficient erythropoietin (EPO) production. However, underlying mechanisms responsible for the dysregulation of cellular iron metabolism are incompletely defined. Using the unilateral ureteral obstruction (UUO) model in Irp1(+/+) and Irp1(−/−) mice, we asked if iron regulatory proteins (IRPs), the central regulators of cellular iron metabolism and suppressors of EPO production, contribute to the etiology of anemia in kidney failure. We identified a significant reduction in IRP protein level and RNA binding activity that associates with a loss of the iron uptake protein transferrin receptor 1 (TfR1), increased expression of the iron storage protein subunits H- and L-ferritin, and a low but overall variable level of stainable iron in the obstructed kidney. This reduction in IRP RNA binding activity and ferritin RNA levels suggests the concomitant rise in ferritin expression and iron content in kidney failure is IRP dependent. In contrast, the reduction in the Epo mRNA level in the obstructed kidney was not rescued by genetic ablation of IRP1, suggesting disruption of normal hypoxia-inducible factor (HIF)-2α regulation. Furthermore, reduced expression of some HIF-α target genes in UUO occurred in the face of increased expression of HIF-α proteins and prolyl hydroxylases 2 and 1, the latter of which is not known to be HIF-α mediated. Our results suggest that the IRP system drives changes in cellular iron metabolism that are associated with kidney failure in UUO but that the impact of IRPs on EPO production is overridden by disrupted hypoxia signaling. NEW & NOTEWORTHY This study demonstrates that iron metabolism and hypoxia signaling are dysregulated in unilateral obstructive nephropathy. Expression of iron regulatory proteins (IRPs), central regulators of cellular iron metabolism, and the iron uptake (transferrin receptor 1) and storage (ferritins) proteins they target is strongly altered. This suggests a role of IRPs in previously observed changes in iron metabolism in progressive renal disease. Hypoxia signaling is disrupted and appeared to dominate the action of IRP1 in controlling erythropoietin expression.

Purpose of review More than one hundred loci have been identified from human genome-wide association studies (GWAS) for blood lipids. Despite the success of GWAS in identifying loci, subsequent prioritization of causal genes related to these loci remains a challenge. To address this challenge, recent work suggests that candidate causal genes within loci can be prioritized through cross-species integration using genome-wide data from the mouse. Recent findings Mouse model systems provide unparalleled access to primary tissues, like the liver, that are not readily available for human studies. Given the key role the liver plays in controlling blood lipid levels and the wealth of liver genome-wide transcript and protein data available in the mouse, these data can be leveraged. Using coexpression network analysis approaches with mouse genome-wide data, coupled with cross-species analysis of human lipid GWAS, causal genes within lipid loci can be prioritized. Prioritization through both mouse and human along with biochemical validation provide a systematic and valuable method to discover lipid metabolism genes. Summary The prioritization of causal lipid genes within GWAS loci is a challenging process requiring a multidisciplinary approach. Integration of data types across species, such as the mouse, can aid in causal gene prioritization.

Identifying the causal gene(s) that connect genetic variation to a phenotype is a challenging problem in genome-wide association studies (GWASs). Here, wse develop a systematic approach that integrates mouse liver co-expression networks with human lipid GWAS data to identify regulators of cholesterol and lipid metabolism. Through our approach, we identified 48 genes showing replication in mice and associated with plasma lipid traits in humans and six genes on the X chromosome. Among these 54 genes, 25 have no previously identified role in lipid metabolism. Based on functional studies and integration with additional human lipid GWAS datasets, we pinpoint Sestrin1 as a causal gene associated with plasma cholesterol levels in humans. Our validation studies demonstrate that Sestrin1 influences plasma cholesterol in multiple mouse models and regulates cholesterol biosynthesis. Our results highlight the power of combining mouse and human datasets for prioritization of human lipid GWAS loci and discovery of lipid genes.