TY - JOUR
T1 - Genomics Integration Into Nephrology Practice
AU - Pinto e Vairo, Filippo
AU - Prochnow, Carri
AU - Kemppainen, Jennifer L.
AU - Lisi, Emily C.
AU - Steyermark, Joan M.
AU - Kruisselbrink, Teresa M.
AU - Pichurin, Pavel N.
AU - Dhamija, Rhadika
AU - Hager, Megan M.
AU - Albadri, Sam
AU - Cornell, Lynn D.
AU - Lazaridis, Konstantinos N.
AU - Klee, Eric W.
AU - Senum, Sarah R.
AU - El Ters, Mireille
AU - Amer, Hatem
AU - Baudhuin, Linnea M.
AU - Moyer, Ann M.
AU - Keddis, Mira T.
AU - Zand, Ladan
AU - Sas, David J.
AU - Erickson, Stephen B.
AU - Fervenza, Fernando C.
AU - Lieske, John C.
AU - Harris, Peter C.
AU - Hogan, Marie C.
N1 - Funding Information:
This work was supported by an unrestricted research grant from the Mayo Clinic’s Center for Individualized Medicine. The funders of this study had no role in the study design, data collection, data analysis, or interpretation, writing of the report, or the decision to submit the report for publication.
Publisher Copyright:
© 2021 The Authors
PY - 2021/9/1
Y1 - 2021/9/1
N2 - 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.
AB - 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.
KW - Genomics
KW - individualized medicine
KW - nephrology
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U2 - 10.1016/j.xkme.2021.04.014
DO - 10.1016/j.xkme.2021.04.014
M3 - Article
AN - SCOPUS:85117228207
SN - 2590-0595
VL - 3
SP - 785
EP - 798
JO - Kidney Medicine
JF - Kidney Medicine
IS - 5
ER -