Dissecting Normal and Abnormal Human Kidney Development Using Multiomics

Congenital kidney anomalies frequently lead to development of CKD in children and adults, with limited possibility for accurate prognostication and successful intervention. Causal genetic variants are identified in a minority of individuals, while the biologic interpretation of putative genetic variants and their effect on kidney development and CKD remains incompletely understood. Advances in single-cell and spatial multiomics now enable a deeper biologic understanding and interpretation of disease-causing mechanisms of congenital kidney anomalies, holding promise for precise diagnoses, prognostication, and treatment for patients. In this review, we provide an overview of multiomics approaches, including transcriptomics, epigenomics, proteomics, and metabolomics, for characterizing and understanding the biology of human kidney development and disease. We will discuss the technical capabilities and challenges in mapping the spatial distribution of normal and abnormal developmental processes in the kidney. Moreover, we present three key multiomics case studies and discuss their experimental design considerations. Finally, future directions and the potential effect of multiomics approaches on the biologic understanding of kidney disease in development and adulthood are discussed. This review highlights that by integrating molecular insights, multiomics has the potential to transform our understanding of genetic (or variant-driven) and nongenetic kidney disease mechanisms and to advance precision diagnostics, prognostics, and therapies for congenital kidney anomalies.

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Publication Details

Journal
Journal of the American Society of Nephrology
Published
2025-11-10
DOI
https://doi.org/10.1681/asn.0000000951
Primary Topic
Renal and related cancers
Type
article
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article

Dissecting Normal and Abnormal Human Kidney Development Using Multiomics

Fanny Oliveira Arcolino, Lampros Mavrommatis, Hildo C. Lantermans, Elena Levtchenko et al.
Journal of the American Society of Nephrology
Renal and related cancers
article

Dissecting Normal and Abnormal Human Kidney Development Using Multiomics

Fanny Oliveira Arcolino, Lampros Mavrommatis, Hildo C. Lantermans, Elena Levtchenko, Luna S. Klomp, Christoph Kuppe, Rik Westland
article en

Abstract

Congenital kidney anomalies frequently lead to development of CKD in children and adults, with limited possibility for accurate prognostication and successful intervention. Causal genetic variants are identified in a minority of individuals, while the biologic interpretation of putative genetic variants and their effect on kidney development and CKD remains incompletely understood. Advances in single-cell and spatial multiomics now enable a deeper biologic understanding and interpretation of disease-causing mechanisms of congenital kidney anomalies, holding promise for precise diagnoses, prognostication, and treatment for patients. In this review, we provide an overview of multiomics approaches, including transcriptomics, epigenomics, proteomics, and metabolomics, for characterizing and understanding the biology of human kidney development and disease. We will discuss the technical capabilities and challenges in mapping the spatial distribution of normal and abnormal developmental processes in the kidney. Moreover, we present three key multiomics case studies and discuss their experimental design considerations. Finally, future directions and the potential effect of multiomics approaches on the biologic understanding of kidney disease in development and adulthood are discussed. This review highlights that by integrating molecular insights, multiomics has the potential to transform our understanding of genetic (or variant-driven) and nongenetic kidney disease mechanisms and to advance precision diagnostics, prognostics, and therapies for congenital kidney anomalies.

Journal of the American Society of NephrologyVol. 37(3)
Emma Kinderziekenhuis (NL), University of Amsterdam (NL), RWTH Aachen University (DE)
Openalex Percentile: Top 70%
Renal and related cancers
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