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Germline Mutations for Kidney Volume in ADPKD
INTRODUCTION: Valid prediction models or predictors of disease progression in children and young patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Although total kidney volume (TKV) and Mayo imaging classification are generally used to predict disease progression in pat...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897295/ https://www.ncbi.nlm.nih.gov/pubmed/35257066 http://dx.doi.org/10.1016/j.ekir.2021.12.012 |
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author | Kataoka, Hiroshi Yoshida, Rie Iwasa, Naomi Sato, Masayo Manabe, Shun Kawachi, Keiko Makabe, Shiho Akihisa, Taro Ushio, Yusuke Teraoka, Atsuko Tsuchiya, Ken Nitta, Kosaku Mochizuki, Toshio |
author_facet | Kataoka, Hiroshi Yoshida, Rie Iwasa, Naomi Sato, Masayo Manabe, Shun Kawachi, Keiko Makabe, Shiho Akihisa, Taro Ushio, Yusuke Teraoka, Atsuko Tsuchiya, Ken Nitta, Kosaku Mochizuki, Toshio |
author_sort | Kataoka, Hiroshi |
collection | PubMed |
description | INTRODUCTION: Valid prediction models or predictors of disease progression in children and young patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Although total kidney volume (TKV) and Mayo imaging classification are generally used to predict disease progression in patients with ADPKD, it remains unclear whether germline mutation types are associated with these factors. We therefore investigated the association between mutation type and TKV and Mayo imaging classification among patients with ADPKD. METHODS: A total of 129 patients with ADPKD who underwent genetic analyses were enrolled in the study. The associations between the severity of PKD (TKV ≥ 1000 ml and Mayo classes 1C–1E) and the PKD1 mutation types (nonsense mutation, frameshift or splicing mutation, and substitution) were evaluated. RESULTS: Among the mutation types, only PKD1 splicing/frameshift mutation had significant associations with TKV ≥ 1000 ml in sex-adjusted and multivariable logistic analyses. Similarly, only the PKD1 splicing/frameshift mutation was significantly associated with Mayo 1C–1E in sex-adjusted and multivariable logistic analyses. PKD1 nonsense mutation, PKD1 substitution, or PKD1 mutation position had no significant association with TKV ≥ 1000 ml or Mayo 1C–1E. CONCLUSION: Kidney cyst severity differs according to the mutation types in PKD1. Patients with PKD1 splicing mutations or PKD1 frameshift mutations are associated with TKV ≥ 1000 ml or Mayo 1C–1E. Detailed assessment of mutation types may be useful for predicting renal prognosis in patients with ADPKD and may especially contribute to the care of a high-risk group of children with ADPKD. |
format | Online Article Text |
id | pubmed-8897295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88972952022-03-06 Germline Mutations for Kidney Volume in ADPKD Kataoka, Hiroshi Yoshida, Rie Iwasa, Naomi Sato, Masayo Manabe, Shun Kawachi, Keiko Makabe, Shiho Akihisa, Taro Ushio, Yusuke Teraoka, Atsuko Tsuchiya, Ken Nitta, Kosaku Mochizuki, Toshio Kidney Int Rep Clinical Research INTRODUCTION: Valid prediction models or predictors of disease progression in children and young patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Although total kidney volume (TKV) and Mayo imaging classification are generally used to predict disease progression in patients with ADPKD, it remains unclear whether germline mutation types are associated with these factors. We therefore investigated the association between mutation type and TKV and Mayo imaging classification among patients with ADPKD. METHODS: A total of 129 patients with ADPKD who underwent genetic analyses were enrolled in the study. The associations between the severity of PKD (TKV ≥ 1000 ml and Mayo classes 1C–1E) and the PKD1 mutation types (nonsense mutation, frameshift or splicing mutation, and substitution) were evaluated. RESULTS: Among the mutation types, only PKD1 splicing/frameshift mutation had significant associations with TKV ≥ 1000 ml in sex-adjusted and multivariable logistic analyses. Similarly, only the PKD1 splicing/frameshift mutation was significantly associated with Mayo 1C–1E in sex-adjusted and multivariable logistic analyses. PKD1 nonsense mutation, PKD1 substitution, or PKD1 mutation position had no significant association with TKV ≥ 1000 ml or Mayo 1C–1E. CONCLUSION: Kidney cyst severity differs according to the mutation types in PKD1. Patients with PKD1 splicing mutations or PKD1 frameshift mutations are associated with TKV ≥ 1000 ml or Mayo 1C–1E. Detailed assessment of mutation types may be useful for predicting renal prognosis in patients with ADPKD and may especially contribute to the care of a high-risk group of children with ADPKD. Elsevier 2021-12-13 /pmc/articles/PMC8897295/ /pubmed/35257066 http://dx.doi.org/10.1016/j.ekir.2021.12.012 Text en © 2021 International Society of Nephrology. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Clinical Research Kataoka, Hiroshi Yoshida, Rie Iwasa, Naomi Sato, Masayo Manabe, Shun Kawachi, Keiko Makabe, Shiho Akihisa, Taro Ushio, Yusuke Teraoka, Atsuko Tsuchiya, Ken Nitta, Kosaku Mochizuki, Toshio Germline Mutations for Kidney Volume in ADPKD |
title | Germline Mutations for Kidney Volume in ADPKD |
title_full | Germline Mutations for Kidney Volume in ADPKD |
title_fullStr | Germline Mutations for Kidney Volume in ADPKD |
title_full_unstemmed | Germline Mutations for Kidney Volume in ADPKD |
title_short | Germline Mutations for Kidney Volume in ADPKD |
title_sort | germline mutations for kidney volume in adpkd |
topic | Clinical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897295/ https://www.ncbi.nlm.nih.gov/pubmed/35257066 http://dx.doi.org/10.1016/j.ekir.2021.12.012 |
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