Genomic Disorders in CKD across the Lifespan

Authors

Miguel Verbitsky, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Sarathbabu Krishnamurthy, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Priya Krithivasan, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Daniel Hughes, Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
Atlas Khan, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Maddalena Marasà, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Natalie Vena, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Pavan Khosla, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Junying Zhang, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Tze Y. Lim, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Joseph T. Glessner, Center for Applied Genomics and Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania
Chunhua Weng, Department of Biomedical Informatics, Columbia University, New York, New York
Ning Shang, Division of Nephrology, Department of Medicine, Columbia University, New York, New York; Department of Biomedical Informatics, Columbia University, New York, New York
Yufeng Shen, Department of Systems Biology and Columbia Genome Center, Columbia University, New York, New York
George Hripcsak, Department of Biomedical Informatics, Columbia University, New York, New York
Hakon Hakonarson, Center for Applied Genomics and Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania
Iuliana Ionita-Laza, Department of Biostatistics, Columbia University, New York, New York
Brynn Levy, Department of Pathology and Cell Biology, Columbia University, New York, New York
Eimear E. Kenny, Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
Ruth JF Loos, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
Krzysztof Kiryluk, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
Simone Sanna-Cherchi, Division of Nephrology, Department of Medicine, Columbia University, New York, New York
David R. Crosslin, Division of Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana
Susan Furth, Departments of Pediatrics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
Bradley A. Warady, Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri
Robert P. Igo, Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio
Sudha K. Iyengar, Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio
Craig S. Wong, Division of Pediatric Nephrology, University of New Mexico Children's Hospital, Albuquerque, New Mexico
Afshin Parsa, Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
Harold I. Feldman, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, Philadelphia, Pennsylvania; Department of Medicine, Perelman School of Medicine, Philadelphia, Pennsylvania; Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, Philadelphia, Pennsylvania
Ali G. Gharavi, Division of Nephrology, Department of Medicine, Columbia University, New York, New York

Document Type

Article

Publication Date

4-1-2023

Abstract

SIGNIFICANCE STATEMENT: Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis.

BACKGROUND: Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility.

METHODS: We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort.

RESULTS: We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk.

CONCLUSION: Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Publisher

American Society of Nephrology

Publication Title

Journal of the American Society of Nephrology : JASN

ISSN

1533-3450

Volume

34

Issue

4

First Page

607

Last Page

618

DOI

10.1681/ASN.2022060725

Recommended Citation

Verbitsky M, Krishnamurthy S, Krithivasan P, Hughes D, Khan A, Marasà M, Vena N, Khosla P, Zhang J, Lim TY, Glessner JT, Weng C, Shang N, Shen Y, Hripcsak G, Hakonarson H, Ionita-Laza I, Levy B, Kenny EE, Loos RJF, Kiryluk K, Sanna-Cherchi S, Crosslin DR, Furth S, Warady BA, Igo RP Jr, Iyengar SK, Wong CS, Parsa A, Feldman HI, Gharavi AG. Genomic Disorders in CKD across the Lifespan. J Am Soc Nephrol. 2023 Apr 1;34(4):607-618. doi: 10.1681/ASN.2022060725. Epub 2022 Oct 27. PMID: 36302597.