Genetic Kidney Diseases (GKDs) Modeling Using Genome Editing Technologies

Genetic kidney diseases (GKDs) are a group of rare diseases, affecting approximately about 60 to 80 per 100,000 individuals, for which there is currently no treatment that can cure them (in many cases). GKDs usually leads to early-onset chronic kidney disease, which results in patients having to undergo dialysis or kidney transplant. Here, we briefly describe genetic causes and phenotypic effects of six GKDs representative of different ranges of prevalence and renal involvement (ciliopathy, glomerulopathy, and tubulopathy). One of the shared characteristics of GKDs is that most of them are monogenic. This characteristic makes it possible to use site-specific nuclease systems to edit the genes that cause GKDs and generate in vitro and in vivo models that reflect the genetic abnormalities of GKDs. We describe and compare these site-specific nuclease systems (zinc finger nucleases (ZFNs), transcription activator-like effect nucleases (TALENs) and regularly clustered short palindromic repeat-associated protein (CRISPR-Cas9)) and review how these systems have allowed the generation of cellular and animal GKDs models and how they have contributed to shed light on many still unknown fields in GKDs. We also indicate the main obstacles limiting the application of these systems in a more efficient way. The information provided here will be useful to gain an accurate understanding of the technological advances in the field of genome editing for GKDs, as well as to serve as a guide for the selection of both the genome editing tool and the gene delivery method most suitable for the successful development of GKDs models.

Automated summary

This study discusses the genetic causes and phenotypic effects of genetic kidney diseases (GKDs) and describes and compares the application of site-specific nuclease systems (such as ZFNs, TALENs, and CRISPR-Cas9). It demonstrates that these systems can be used to edit the genes causing GKDs and generate models that reflect the genetic abnormalities, thus shedding light on many unknown aspects in the field of GKDs.