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首页> 外文期刊>Brain: A journal of neurology >Disease progression in patients with single, large-scale mitochondrial DNA deletions
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Disease progression in patients with single, large-scale mitochondrial DNA deletions

机译:单个,大规模线粒体DNA缺失患者的疾病进展

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Single, large-scale deletions of mitochondrial DNA are a common cause of mitochondrial disease and cause a broad phenotypic spectrum ranging from mild myopathy to devastating multi-system syndromes such as Kearns-Sayre syndrome. Studies to date have been inconsistent on the value of putative predictors of clinical phenotype and disease progression such as mutation load and the size or location of the deletion. Using a cohort of 87 patients with single, large-scale mitochondrial DNA deletions we demonstrate that a variety of outcome measures such as COX-deficient fibre density, age-at-onset of symptoms and progression of disease burden, as measured by the Newcastle Mitochondrial Disease Adult Scale, are significantly (P < 0.05) correlated with the size of the deletion, the deletion heteroplasmy level in skeletal muscle, and the location of the deletion within the genome. We validate these findings with re-analysis of 256 cases from published data and clarify the previously conflicting information of the value of these predictors, identifying that multiple regression analysis is necessary to understand the effect of these interrelated predictors. Furthermore, we have used mixed modelling techniques to model the progression of disease according to these predictors, allowing a better understanding of the progression over time of this strikingly variable disease. In this way we have developed a new paradigm in clinical mitochondrial disease assessment and management that sidesteps the perennial difficulty of ascribing a discrete clinical phenotype to a broad multi-dimensional and progressive spectrum of disease, establishing a framework to allow better understanding of disease progression.
机译:线粒体DNA的单次大规模缺失是线粒体疾病的常见原因,并引起广泛的表型谱,范围从轻度肌病到破坏性的多系统综合征,例如Kearns-Sayre综合征。迄今为止,关于临床表型和疾病进展的假定预测因子(例如突变负荷和缺失的大小或位置)的价值一直不一致。使用一组87位单次大规模线粒体DNA缺失的患者,我们证明了各种结局指标,例如纽卡斯尔线粒体所测量的COX缺乏纤维密度,症状发作年龄和疾病负担进展疾病成人量表与缺失的大小,骨骼肌中的缺失异质性水平以及基因组中缺失的位置显着相关(P <0.05)。我们通过对公开发表的数据中的256个案例进行重新分析来验证这些发现,并阐明以前与这些预测变量的价值存在冲突的信息,从而确定多元回归分析对于理解这些相互关联的预测变量的影响是必要的。此外,我们已经使用混合建模技术根据这些预测因子对疾病的进展进行建模,从而更好地了解了这种惊人变化的疾病随时间的进展。通过这种方式,我们在临床线粒体疾病评估和治疗中开发了一种新的范例,从而避免了将离散的临床表型归因于广泛的疾病的多维和渐进性谱系的长期困难,建立了一个框架以更好地了解疾病的进展。

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