Hayne Cho Park1, Hyunjin Ryu2, Yong-Chul Kim2, Curie Ahn3, Kyu-Beck Lee4, Yeong Hoon Kim5, Yunmi Kim5, Seungyeup Han6, Yaerim Kim6, Eun Hui Bae7, Seong Kwon Ma7, Hee Gyung Kang8, Yo Han Ahn8, Eujin Park9, Kyungjo Jeong10, Jaewon Lee10, Jungmin Choi10, Kook-Hwan Oh2, Yun Kyu Oh11,12. 1. Department of Internal Medicine, Hallym University College of Medicine, Seoul, South Korea. 2. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea. 3. Department of Internal Medicine, National Medical Center, Seoul, South Korea. 4. Department of Internal Medicine, Kangbuk Samsung Hospital, Seoul, South Korea. 5. Department of Internal Medicine, Busan Paik Hospital, Busan, South Korea. 6. Department of Internal Medicine, Keimyung University School of Medicine, Daegu, South Korea. 7. Department of Internal Medicine, Chonnam National University Medical School, Gwangju, South Korea. 8. Department of Pediatrics, Seoul National University Children's Hospital, Seoul, South Korea. 9. Department of Pediatrics, Hallym University College of Medicine, Seoul, South Korea. 10. Department of Biomedical Sciences, Korea University College of Medicine, Seoul, South Korea. 11. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea. yoonkyuoh@gmail.com. 12. Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, South Korea. yoonkyuoh@gmail.com.
Abstract
BACKGROUND: Inherited cystic kidney disease is a spectrum of disorders in which clusters of renal cysts develop as the result of genetic mutation. The exact methods and pipelines for defining genetic mutations of inherited cystic kidney disease are not clear at this point. This 3-year, prospective, multicenter, cohort study was designed to set up a cohort of Korean patients with inherited cystic kidney disease, establish a customized genetic analysis pipeline for each disease subtype, and identify modifying genes associated with the severity of the disease phenotype. METHODS/ DESIGN: From May 2020 to May 2022, we aim to recruit 800 patients and their family members to identify pathogenic mutations. Patients with more than 3 renal cysts in both kidneys are eligible to be enrolled. Cases of simple renal cysts and acquired cystic kidney disease that involve cyst formation as the result of renal failure will be excluded from this study. Demographic, laboratory, and imaging data as well as family pedigree will be collected at baseline. Renal function and changes in total kidney volume will be monitored during the follow-up period. Genetic identification of each case of inherited cystic kidney disease will be performed using a targeted gene panel of cystogenesis-related genes, whole exome sequencing (WES) and/or family segregation studies. Genotype-phenotype correlation analysis will be performed to elucidate the genetic effect on the severity of the disease phenotype. DISCUSSION: This is the first nationwide cohort study on patients with inherited cystic kidney disease in Korea. We will build a multicenter cohort to describe the clinical characteristics of Korean patients with inherited cystic kidney disease, elucidate the genotype of each disease, and demonstrate the genetic effects on the severity of the disease phenotype. TRIAL REGISTRATION: This cohort study was retrospectively registered at the Clinical Research Information Service ( KCT0005580 ) operated by the Korean Center for Disease Control and Prevention on November 5th, 2020.
BACKGROUND: Inherited cystic kidney disease is a spectrum of disorders in which clusters of renal cysts develop as the result of genetic mutation. The exact methods and pipelines for defining genetic mutations of inherited cystic kidney disease are not clear at this point. This 3-year, prospective, multicenter, cohort study was designed to set up a cohort of Korean patients with inherited cystic kidney disease, establish a customized genetic analysis pipeline for each disease subtype, and identify modifying genes associated with the severity of the disease phenotype. METHODS/ DESIGN: From May 2020 to May 2022, we aim to recruit 800 patients and their family members to identify pathogenic mutations. Patients with more than 3 renal cysts in both kidneys are eligible to be enrolled. Cases of simple renal cysts and acquired cystic kidney disease that involve cyst formation as the result of renal failure will be excluded from this study. Demographic, laboratory, and imaging data as well as family pedigree will be collected at baseline. Renal function and changes in total kidney volume will be monitored during the follow-up period. Genetic identification of each case of inherited cystic kidney disease will be performed using a targeted gene panel of cystogenesis-related genes, whole exome sequencing (WES) and/or family segregation studies. Genotype-phenotype correlation analysis will be performed to elucidate the genetic effect on the severity of the disease phenotype. DISCUSSION: This is the first nationwide cohort study on patients with inherited cystic kidney disease in Korea. We will build a multicenter cohort to describe the clinical characteristics of Korean patients with inherited cystic kidney disease, elucidate the genotype of each disease, and demonstrate the genetic effects on the severity of the disease phenotype. TRIAL REGISTRATION: This cohort study was retrospectively registered at the Clinical Research Information Service ( KCT0005580 ) operated by the Korean Center for Disease Control and Prevention on November 5th, 2020.
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Authors: Binu Porath; Vladimir G Gainullin; Emilie Cornec-Le Gall; Elizabeth K Dillinger; Christina M Heyer; Katharina Hopp; Marie E Edwards; Charles D Madsen; Sarah R Mauritz; Carly J Banks; Saurabh Baheti; Bharathi Reddy; José Ignacio Herrero; Jesús M Bañales; Marie C Hogan; Velibor Tasic; Terry J Watnick; Arlene B Chapman; Cécile Vigneau; Frédéric Lavainne; Marie-Pierre Audrézet; Claude Ferec; Yannick Le Meur; Vicente E Torres; Peter C Harris Journal: Am J Hum Genet Date: 2016-06-02 Impact factor: 11.025
Authors: Curtis T Rueden; Johannes Schindelin; Mark C Hiner; Barry E DeZonia; Alison E Walter; Ellen T Arena; Kevin W Eliceiri Journal: BMC Bioinformatics Date: 2017-11-29 Impact factor: 3.169