DOI QR코드

DOI QR Code

Aberrant Splicing in PKD2 in a Family of Korean Patients With Autosomal Dominant Polycystic Kidney Disease

  • Soo-Young Yoon (Division of Nephrology, Department of Internal Medicine, Kyung Hee University College of Medicine, Kyung Hee University Medical Center) ;
  • Jin Sug Kim (Division of Nephrology, Department of Internal Medicine, Kyung Hee University College of Medicine, Kyung Hee University Medical Center) ;
  • Kyung Sun Park (Department of Laboratory Medicine, Kyung Hee University College of Medicine, Kyung Hee University Medical Center)
  • 투고 : 2024.05.03
  • 심사 : 2024.08.08
  • 발행 : 2024.11.01

초록

키워드

과제정보

We thank Eun Chong Byun, RN (Rare Disease Center, Kyung Hee University Medical Center) and Haeran Jin, MT (Department of Laboratory Medicine, Kyung Hee University Medical Center) for their dedicated efforts in conducting the patient's family analysis and additional confirmatory tests.

참고문헌

  1. Borrego Utiel FJ and Espinósa Hernandez M. How to estimate kidney growth in patients with autosomal dominant polycystic kidney disease. J Am Soc Nephrol 2023;34:944-50. https://doi.org/10.1681/ASN.0000000000000130
  2. Lanktree MB, Haghighi A, di Bari I, Song X, Pei Y. Insights into autosomal dominant polycystic kidney disease from genetic studies. Clin J Am Soc Nephrol 2021;16:790-9. https://doi.org/10.2215/CJN.02320220
  3. Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, et al. Predicting splicing from primary sequence with deep learning. Cell 2019;176:535-48 e24. https://doi.org/10.1016/j.cell.2018.12.015
  4. Litchfield K, Reading JL, Lim EL, Xu H, Liu P, Al-Bakir M, et al. Escape from nonsense-mediated decay associates with anti-tumor immunogenicity. Nat Commun 2020;11:3800. https://doi.org/10.1038/s41467-020-17526-5
  5. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021;596:583-9. https://doi.org/10.1038/s41586-021-03819-2
  6. Meng EC, Goddard TD, Pettersen EF, Couch GS, Pearson ZJ, Morris JH, et al. UCSF ChimeraX: tools for structure building and analysis. Protein Sci 2023;32:e4792. https://doi.org/10.1002/pro.4792
  7. Shen PS, Yang X, DeCaen PG, Liu X, Bulkley D, Clapham DE, et al. The structure of the polycystic kidney disease channel PKD2 in lipid nanodiscs. Cell 2016;167:763-73 e11. https://doi.org/10.1016/j.cell.2016.09.048
  8. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015;17:405-24. https://doi.org/10.1038/gim.2015.30
  9. Walker LC, Hoya M, Wiggins GAR, Lindy A, Vincent LM, Parsons MT, et al. Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: recommendations from the ClinGen SVI Splicing Subgroup. Am J Hum Genet 2023;110:1046-67. https://doi.org/10.1016/j.ajhg.2023.06.002
  10. Biesecker LG, Byrne AB, Harrison SM, Pesaran T, Schaffer AA, Shirts BH, et al. ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification. Am J Hum Genet 2024;111:24-38. https://doi.org/10.1016/j.ajhg.2023.11.009
  11. Kim J, Yu J, Lee S, Kim S, Lee IS, Lee W, et al. Reverse transcription-PCR-based Sanger sequencing-confirmed exon-skipping effect of a novel GEN1 intronic variant (c.1408+4A>G). Ann Lab Med 2024;44:188-91. https://doi.org/10.3343/alm.2023.0163