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Pinto E Vairo F, Prochnow C, Kemppainen JL, et al. Genomics Integration Into Nephrology Practice. Kidney Med. 2021;3(5):785-798doi: 10.1016/j.xkme.2021.04.014.
Pinto E Vairo, F., Prochnow, C., Kemppainen, J. L., Lisi, E. C., Steyermark, J. M., Kruisselbrink, T. M., Pichurin, P. N., Dhamija, R., Hager, M. M., Albadri, S., Cornell, L. D., Lazaridis, K. N., Klee, E. W., Senum, S. R., El Ters, M., Amer, H., Baudhuin, L. M., Moyer, A. M., Keddis, M. T., Zand, L., Sas, D. J., Erickson, S. B., Fervenza, F. C., Lieske, J. C., Harris, P. C., & Hogan, M. C. (2021). Genomics Integration Into Nephrology Practice. Kidney medicine, 3(5), 785-798. https://doi.org/10.1016/j.xkme.2021.04.014
Pinto E Vairo, Filippo, et al. "Genomics Integration Into Nephrology Practice." Kidney medicine vol. 3,5 (2021): 785-798. doi: https://doi.org/10.1016/j.xkme.2021.04.014
Pinto E Vairo F, Prochnow C, Kemppainen JL, Lisi EC, Steyermark JM, Kruisselbrink TM, Pichurin PN, Dhamija R, Hager MM, Albadri S, Cornell LD, Lazaridis KN, Klee EW, Senum SR, El Ters M, Amer H, Baudhuin LM, Moyer AM, Keddis MT, Zand L, Sas DJ, Erickson SB, Fervenza FC, Lieske JC, Harris PC, Hogan MC. Genomics Integration Into Nephrology Practice. Kidney Med. 2021 Jun 29;3(5):785-798. doi: 10.1016/j.xkme.2021.04.014. eCollection 2021. PMID: 34746741; PMCID: PMC8551494.
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Kidney Med. 2021 Jun 29;3(5):785-798. doi: 10.1016/j.xkme.2021.04.014. eCollection 2021.

Genomics Integration Into Nephrology Practice.

Kidney medicine

Filippo Pinto E Vairo, Carri Prochnow, Jennifer L Kemppainen, Emily C Lisi, Joan M Steyermark, Teresa M Kruisselbrink, Pavel N Pichurin, Rhadika Dhamija, Megan M Hager, Sam Albadri, Lynn D Cornell, Konstantinos N Lazaridis, Eric W Klee, Sarah R Senum, Mireille El Ters, Hatem Amer, Linnea M Baudhuin, Ann M Moyer, Mira T Keddis, Ladan Zand, David J Sas, Stephen B Erickson, Fernando C Fervenza, John C Lieske, Peter C Harris, Marie C Hogan

Affiliations

  1. Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota.
  2. Department of Clinical Genomics, Mayo Clinic, Rochester, Minnesota.
  3. Division of Nephrology & Hypertension, Mayo Clinic, Rochester, Minnesota.
  4. Department of Clinical Genomics, Mayo Clinic, Scottsdale, Arizona.
  5. Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, Minnesota.
  6. Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota.
  7. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota.
  8. Division of Nephrology, Mayo Clinic, Scottsdale, Arizona.

PMID: 34746741 PMCID: PMC8551494 DOI: 10.1016/j.xkme.2021.04.014

Abstract

RATIONALE & OBJECTIVE: The etiology of kidney disease remains unknown in many individuals with chronic kidney disease (CKD). We created the Mayo Clinic Nephrology Genomics Clinic to improve our ability to integrate genomic and clinical data to identify the etiology of unexplained CKD.

STUDY DESIGN: Retrospective study.

SETTING & PARTICIPANTS: An essential component of our program is the Nephrology Genomics Board which consists of nephrologists, geneticists, pathologists, translational omics scientists, and trainees who interpret the patient's clinical and genetic data. Since September 2016, the Board has reviewed 163 cases (15 cystic, 100 glomerular, 6 congenital anomalies of kidney and urinary tract (CAKUT), 20 stones, 15 tubulointerstitial, and 13 other).

ANALYTICAL APPROACH: Testing was performed with targeted panels, single gene analysis, or analysis of kidney-related genes from exome sequencing. Variant classification was obtained based on the 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines.

RESULTS: A definitive genetic diagnosis was achieved for 50 families (30.7%). The highest diagnostic yield was obtained in individuals with tubulointerstitial diseases (53.3%), followed by congenital anomalies of the kidney and urological tract (33.3%), glomerular (31%), cysts (26.7%), stones (25%), and others (15.4%). A further 20 (12.3%) patients had variants of interest, and variant segregation, and research activities (exome, genome, or transcriptome sequencing) are ongoing for 44 (40%) unresolved families.

LIMITATIONS: Possible overestimation of diagnostic rate due to inclusion of individuals with variants with evidence of pathogenicity but classified as of uncertain significance by the clinical laboratory.

CONCLUSIONS: Integration of genomic and research testing and multidisciplinary evaluation in a nephrology cohort with CKD of unknown etiology or suspected monogenic disease provided a diagnosis in a third of families. These diagnoses had prognostic implications, and often changes in management were implemented.

© 2021 The Authors.

Keywords: Genomics; individualized medicine; nephrology

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