Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Köttgen, Anna; Gall, Emilie Cornec-Le; Halbritter, Jan; Kiryluk, Krzysztof; Mallett, Andrew; Parekh, Rulan S.; Rasouly, Hila Milo; Sampson, Matthew G.; Tin, Adrienne; Antignac, Corinne; Ars, Elisabet; Bergmann, Carsten; Bleyer, Anthony J.; Böckenhauer, Detlef; Devuyst, Olivier; Florez, José C.; Fowler, Kevin; Franceschini, Nora; Fukagawa, Masafumi; Gale, Daniel P.; Gbadegesin, Rasheed; Goldstein, David; Grams, Morgan E.; Greka, Anna; Groß, Oliver; Guay‐Woodford, Lisa M.; Harris, Peter C.; Hoefele, Julia; Hung, Adriana M.; Knoers, Nine V A M; Kopp, Jeffrey B.; Kretzler, Matthias; Lanktree, Matthew B.; Lipska‐Ziętkiewicz, Beata S.; Nicholls, Kathleen; Nozu, Kandai; Ojo, Akinlolu; Parsa, Afshin; Pattaro, Cristian; Pei, York; Pollak, Martin R.; Rhee, Eugene P.; Sanna‐Cherchi, Simone; Savige, Judy; Sayer, John A.; Scolari, Francesco; Sedor, John R.; Sim, Xueling; Somlo, Stefan; Suszták, Katalin; Tayo, Bamidele O.; Torra, Roser; Eerde, Albertien M. van; Weinstock, André; Winkler, Cheryl A.; Wuttke, Matthias; Zhang, Hong; King, Jennifer; Cheung, Michael; Jadoul, Michel; Winkelmayer, Wolfgang C.; Gharavi, Ali G.

doi:10.1016/j.kint.2022.03.019

Cited by 68 publications

(44 citation statements)

References 165 publications

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“…These include digital health approaches to case identification [ 70 ], transcriptomic or RNA sequencing [ 71 , 72 ], which can reclassify variants otherwise not considered as being disease-related [ 73 ], and globally calibrated and verified gene–phenotype curation for monogenic CKD, such as ClinGen [ 74 ] and PanelApp [ 75 ] within the Gene Curation Coalition [ 76 ▪ ]. Already key global consensus policy recommendations including from the European Renal Association (ERA) and European Rare Kidney Disease Reference Network (ERKNet) [ 77 ▪ ] and Kidney Diseases: Improving Global Outcomes (KDIGO) [ 78 ▪ ] are helping to consolidate and bring together experiences and learnings across countries and regions to guide ongoing implementation of genomics in CKD.…”

Section: Towards Implementationmentioning

confidence: 99%

Which patients with CKD will benefit from genomic sequencing? Synthesizing progress to illuminate the future

Mallett

2022

Current Opinion in Nephrology &Amp; Hypertension

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Purpose of reviewThis review will summarize and synthesize recent findings in regard to monogenic kidney disorders, including how that evidence is being translated into practice. It will add to existing key knowledge to provide context for clinicians in consolidating existing practice and approaches.Recent findingsWhilst there are long established factors, which indicate increased likelihood of identifying a monogenic cause for kidney disease, these can now be framed in terms of the identification of new genes, new indications for genomic testing and new evidence for clinical utility of genomic testing in nephrology. Further, inherent in the use of genomics in nephrology are key concepts including robust informed consent, variant interpretation and return of results. Recent findings of variants in genes related to complex or broader kidney phenotypes are emerging in addition to understanding of de novo variants. Phenocopy phenomena are indicating a more pragmatic use of broader gene panels whilst evidence is emerging of a role in unexplained kidney disease. Clinical utility is evolving but is being successfully demonstrated across multiple domains of outcome and practice.SummaryWe provide an updated framework of evidence to guide application of genomic testing in chronic kidney disease (CKD), building upon existing principles and knowledge to indicate how the practice and implementation of this can be applied today. There are clearly established roles for genomic testing for some patients with CKD, largely those with suspected heritable forms, with these continuing to expand as new evidence emerges.

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Section: Towards Implementationmentioning

confidence: 99%

Which patients with CKD will benefit from genomic sequencing? Synthesizing progress to illuminate the future

Mallett

2022

Current Opinion in Nephrology &Amp; Hypertension

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“…A large number of genetic conditions present in nephrology practice, including but not limited to polycystic kidney disease, Alport syndrome, thrombotic microangiopathies, tubulointerstitial disease, and other glomerular diseases [ 2 , 7 ]. Genetic conditions contribute to a significant proportion of chronic kidney disease and are often underrecognized as a cause [ 8 ]. The potential benefits from routinely integrating genomic testing into nephrology are high, with multiple studies demonstrating high diagnostic and clinical utility [ 2 , 3 , 9 ], as well as cost-effectiveness [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Theory Designed Strategies to Support Implementation of Genomics in Nephrology

Kansal

Quinlan

Stark

et al. 2022

Genes

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Background: (1) Background: Genomic testing is increasingly utilized as a clinical tool; however, its integration into nephrology remains limited. The purpose of this study was to identify barriers and prioritize interventions for the widespread implementation of genomics in nephrology. (2) Methods: Qualitative, semi-structured interviews were conducted with 25 Australian adult nephrologists to determine their perspectives on interventions and models of care to support implementation of genomics in nephrology. Interviews were guided by a validated theoretical framework for the implementation of genomic medicine—the Consolidated Framework of Implementation Research (CFIR). (3) Results: Nephrologists were from 18 hospitals, with 7 having a dedicated multidisciplinary kidney genetics service. Most practiced in the public healthcare system (n = 24), a large number were early-career (n = 13), and few had genomics experience (n = 4). The top three preferred interventions were increased funding, access to genomics champions, and education and training. Where interventions to barriers were not reported, we used the CFIR/Expert Recommendations for Implementing Change matching tool to generate theory-informed approaches. The preferred model of service delivery was a multidisciplinary kidney genetics clinic. (4) Conclusions: This study identified surmountable barriers and practical interventions for the implementation of genomics in nephrology, with multidisciplinary kidney genetics clinics identified as the preferred model of care. The integration of genomics education into nephrology training, secure funding for testing, and counselling along with the identification of genomics champions should be pursued by health services more broadly.

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“…The proteins encoded by these genes are expressed in different segments of the nephron: glomerulus, proximal tubule (PT), thick ascending limb (TAL), distal convoluted tubule (DCT), and collecting duct (CD) (Figure 1) [8]. In most cases, the presence of a mutation in one of these genes is sufficient to generate the disease, that is, most GKDs are monogenic (also termed "Mendelian"), with a strong genotype-phenotype correlation, a clear pattern of inheritance and where environmental factors have limited influence [9]. The opposite situation happens with complex or polygenic diseases, where multiple genetic variants (mostly common risk variants) at different locus and environmental factors contribute to the pathology, with a lack of simple patterns of inheritance.…”

Section: Introductionmentioning

confidence: 99%

“…The opposite situation happens with complex or polygenic diseases, where multiple genetic variants (mostly common risk variants) at different locus and environmental factors contribute to the pathology, with a lack of simple patterns of inheritance. Common genetic variants have been shown to contribute to several kidney diseases, such as IgA nephropathy, membranous nephropathy, or nephrotic syndrome [9].…”

Section: Introductionmentioning

confidence: 99%

Genetic Kidney Diseases (GKDs) Modeling Using Genome Editing Technologies

Gómez-García

Martínez-Pulleiro

Carrera

et al. 2022

Cells

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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.

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Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Cited by 68 publications

References 165 publications

Which patients with CKD will benefit from genomic sequencing? Synthesizing progress to illuminate the future

Which patients with CKD will benefit from genomic sequencing? Synthesizing progress to illuminate the future

Theory Designed Strategies to Support Implementation of Genomics in Nephrology

Genetic Kidney Diseases (GKDs) Modeling Using Genome Editing Technologies

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