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The progression rate of spinocerebellar ataxia type 3 varies with disease stage

BACKGROUND: In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. METHODS: Data were derived from the longest longitudinal study, with 642 examinati...

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Autores principales: Peng, Linliu, Peng, Yun, Chen, Zhao, Wang, Chunrong, Long, Zhe, Peng, Huirong, Shi, Yuting, Shen, Lu, Xia, Kun, Leotti, Vanessa B., Jardim, Laura Bannach, Tang, Beisha, Qiu, Rong, Jiang, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107762/
https://www.ncbi.nlm.nih.gov/pubmed/35568848
http://dx.doi.org/10.1186/s12967-022-03428-1
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author Peng, Linliu
Peng, Yun
Chen, Zhao
Wang, Chunrong
Long, Zhe
Peng, Huirong
Shi, Yuting
Shen, Lu
Xia, Kun
Leotti, Vanessa B.
Jardim, Laura Bannach
Tang, Beisha
Qiu, Rong
Jiang, Hong
author_facet Peng, Linliu
Peng, Yun
Chen, Zhao
Wang, Chunrong
Long, Zhe
Peng, Huirong
Shi, Yuting
Shen, Lu
Xia, Kun
Leotti, Vanessa B.
Jardim, Laura Bannach
Tang, Beisha
Qiu, Rong
Jiang, Hong
author_sort Peng, Linliu
collection PubMed
description BACKGROUND: In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. METHODS: Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models. RESULTS: An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available. CONCLUSIONS: We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03428-1.
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spelling pubmed-91077622022-05-16 The progression rate of spinocerebellar ataxia type 3 varies with disease stage Peng, Linliu Peng, Yun Chen, Zhao Wang, Chunrong Long, Zhe Peng, Huirong Shi, Yuting Shen, Lu Xia, Kun Leotti, Vanessa B. Jardim, Laura Bannach Tang, Beisha Qiu, Rong Jiang, Hong J Transl Med Research BACKGROUND: In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions. METHODS: Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models. RESULTS: An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available. CONCLUSIONS: We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03428-1. BioMed Central 2022-05-14 /pmc/articles/PMC9107762/ /pubmed/35568848 http://dx.doi.org/10.1186/s12967-022-03428-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Peng, Linliu
Peng, Yun
Chen, Zhao
Wang, Chunrong
Long, Zhe
Peng, Huirong
Shi, Yuting
Shen, Lu
Xia, Kun
Leotti, Vanessa B.
Jardim, Laura Bannach
Tang, Beisha
Qiu, Rong
Jiang, Hong
The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title_full The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title_fullStr The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title_full_unstemmed The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title_short The progression rate of spinocerebellar ataxia type 3 varies with disease stage
title_sort progression rate of spinocerebellar ataxia type 3 varies with disease stage
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107762/
https://www.ncbi.nlm.nih.gov/pubmed/35568848
http://dx.doi.org/10.1186/s12967-022-03428-1
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