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Genomic Disorders in CKD across the Lifespan.
J Am Soc Nephrol. 2023 Apr 01; 34(4):607-618.JA

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.

Links

Publisher Full Text (DOI)

Authors+Show Affiliations

Verbitsky M
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Krishnamurthy S
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Krithivasan P
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Hughes D
Institute for Genomic Medicine, Columbia University Medical Center, New York, New York.
Khan A
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Marasà M
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Vena N
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Khosla P
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Zhang J
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Lim TY
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Glessner JT
Center for Applied Genomics and Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania.
Weng C
Department of Biomedical Informatics, Columbia University, New York, New York.
Shang N
Division of Nephrology, Department of Medicine, Columbia University, New York, New York. Department of Biomedical Informatics, Columbia University, New York, New York.
Shen Y
Department of Systems Biology and Columbia Genome Center, Columbia University, New York, New York.
Hripcsak G
Department of Biomedical Informatics, Columbia University, New York, New York.
Hakonarson H
Center for Applied Genomics and Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania.
Ionita-Laza I
Department of Biostatistics, Columbia University, New York, New York.
Levy B
Department of Pathology and Cell Biology, Columbia University, New York, New York.
Kenny EE
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.
Loos RJF
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.
Kiryluk K
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Sanna-Cherchi S
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
Crosslin DR
Division of Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana.
Furth S
Departments of Pediatrics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
Warady BA
Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri.
Igo RP
Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio.
Iyengar SK
Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio.
Wong CS
Division of Pediatric Nephrology, University of New Mexico Children's Hospital, Albuquerque, New Mexico.
Parsa A
Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland.
Feldman HI
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.
Gharavi AG
Division of Nephrology, Department of Medicine, Columbia University, New York, New York.

MeSH

HumansCohort StudiesLongevityCopperProspective StudiesRenal Insufficiency, ChronicGenomicsDisease ProgressionRisk Factors

Pub Type(s)

Journal Article

Language

eng

PubMed ID

36302597

Citation

Verbitsky, Miguel, et al. "Genomic Disorders in CKD Across the Lifespan." Journal of the American Society of Nephrology : JASN, vol. 34, no. 4, 2023, pp. 607-618.
Verbitsky M, Krishnamurthy S, Krithivasan P, et al. Genomic Disorders in CKD across the Lifespan. J Am Soc Nephrol. 2023;34(4):607-618.
Verbitsky, M., Krishnamurthy, S., Krithivasan, P., Hughes, D., Khan, A., Marasà, M., Vena, N., Khosla, P., Zhang, J., Lim, T. Y., Glessner, J. T., Weng, C., Shang, N., Shen, Y., Hripcsak, G., Hakonarson, H., Ionita-Laza, I., Levy, B., Kenny, E. E., ... Gharavi, A. G. (2023). Genomic Disorders in CKD across the Lifespan. Journal of the American Society of Nephrology : JASN, 34(4), 607-618. https://doi.org/10.1681/ASN.2022060725
Verbitsky M, et al. Genomic Disorders in CKD Across the Lifespan. J Am Soc Nephrol. 2023 Apr 1;34(4):607-618. PubMed PMID: 36302597.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Genomic Disorders in CKD across the Lifespan. AU - Verbitsky,Miguel, AU - Krishnamurthy,Sarathbabu, AU - Krithivasan,Priya, AU - Hughes,Daniel, AU - Khan,Atlas, AU - Marasà,Maddalena, AU - Vena,Natalie, AU - Khosla,Pavan, AU - Zhang,Junying, AU - Lim,Tze Y, AU - Glessner,Joseph T, AU - Weng,Chunhua, AU - Shang,Ning, AU - Shen,Yufeng, AU - Hripcsak,George, AU - Hakonarson,Hakon, AU - Ionita-Laza,Iuliana, AU - Levy,Brynn, AU - Kenny,Eimear E, AU - Loos,Ruth J F, AU - Kiryluk,Krzysztof, AU - Sanna-Cherchi,Simone, AU - Crosslin,David R, AU - Furth,Susan, AU - Warady,Bradley A, AU - Igo,Robert P,Jr AU - Iyengar,Sudha K, AU - Wong,Craig S, AU - Parsa,Afshin, AU - Feldman,Harold I, AU - Gharavi,Ali G, Y1 - 2022/10/27/ PY - 2022/06/27/received PY - 2022/09/15/accepted PY - 2023/4/4/medline PY - 2022/10/28/pubmed PY - 2022/10/27/entrez SP - 607 EP - 618 JF - Journal of the American Society of Nephrology : JASN JO - J Am Soc Nephrol VL - 34 IS - 4 N2 - 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. SN - 1533-3450 UR - https://www.unboundmedicine.com/medline/citation/36302597/Genomic_Disorders_in_CKD_across_the_Lifespan_ DB - PRIME DP - Unbound Medicine ER -