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Genomic Disorders in CKD across the Lifespan.
Verbitsky, Miguel; Krishnamurthy, Sarathbabu; Krithivasan, Priya; Hughes, Daniel; Khan, Atlas; Marasà, Maddalena; Vena, Natalie; Khosla, Pavan; Zhang, Junying; Lim, Tze Y; Glessner, Joseph T; Weng, Chunhua; Shang, Ning; Shen, Yufeng; Hripcsak, George; Hakonarson, Hakon; Ionita-Laza, Iuliana; Levy, Brynn; Kenny, Eimear E; Loos, Ruth J F; Kiryluk, Krzysztof; Sanna-Cherchi, Simone; Crosslin, David R; Furth, Susan; Warady, Bradley A; Igo, Robert P; Iyengar, Sudha K; Wong, Craig S; Parsa, Afshin; Feldman, Harold I; Gharavi, Ali G.
Afiliação
  • 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.
  • Shen Y; Department of Biomedical Informatics, Columbia University, New York, New York.
  • Hripcsak G; Department of Systems Biology and Columbia Genome Center, Columbia University, New York, New York.
  • Hakonarson H; Department of Biomedical Informatics, Columbia University, New York, New York.
  • Ionita-Laza I; Center for Applied Genomics and Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania.
  • Levy B; Department of Biostatistics, Columbia University, New York, New York.
  • Kenny EE; Department of Pathology and Cell Biology, Columbia University, New York, New York.
  • Loos RJF; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Kiryluk K; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Sanna-Cherchi S; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Crosslin DR; Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
  • Furth S; Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
  • Warady BA; Division of Nephrology, Department of Medicine, Columbia University, New York, New York.
  • Igo RP; Division of Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana.
  • Iyengar SK; Departments of Pediatrics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Wong CS; Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri.
  • Parsa A; Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio.
  • Feldman HI; Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland, Ohio.
  • Gharavi AG; Division of Pediatric Nephrology, University of New Mexico Children's Hospital, Albuquerque, New Mexico.
J Am Soc Nephrol ; 34(4): 607-618, 2023 04 01.
Article em En | MEDLINE | ID: mdl-36302597
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 1252 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article