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dc.contributor.authorPeng, Linliupt_BR
dc.contributor.authorPeng, Yunpt_BR
dc.contributor.authorChen, Zhaopt_BR
dc.contributor.authorWang, Chunrongpt_BR
dc.contributor.authorLong, Zhept_BR
dc.contributor.authorPeng, Huirongpt_BR
dc.contributor.authorShi, Yutingpt_BR
dc.contributor.authorShen, Lupt_BR
dc.contributor.authorXia, Kunpt_BR
dc.contributor.authorLeotti, Vanessa Bielefeldtpt_BR
dc.contributor.authorJardim, Laura Bannachpt_BR
dc.contributor.authorTang, Beishapt_BR
dc.contributor.authorQiu, Rongpt_BR
dc.contributor.authorJiang, Hongpt_BR
dc.date.accessioned2023-04-05T03:47:58Zpt_BR
dc.date.issued2022pt_BR
dc.identifier.issn1479-5876pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/256725pt_BR
dc.description.abstractBackground: 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.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofJournal of translational medicine. London. Vol. 20 (May 2022), artigo 226, 12 p.pt_BR
dc.rightsOpen Accessen
dc.subjectAtaxias espinocerebelarespt_BR
dc.subjectSpinocerebellar ataxia type 3en
dc.subjectProgressão da doençapt_BR
dc.subjectCAG repeatsen
dc.subjectProgression predictionen
dc.subjectModelo de previsãopt_BR
dc.subjectGrowth modelen
dc.titleThe progression rate of spinocerebellar ataxia type 3 varies with disease stagept_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001165522pt_BR
dc.type.originEstrangeiropt_BR


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