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具有共济失调的神经退行性疾病小鼠模型的表型评估及其在尼曼-匹克病 C1 型中的应用。

Phenotype assessment for neurodegenerative murine models with ataxia and application to Niemann-Pick disease, type C1.

机构信息

Eunice Kennedy Shriver National Institute of Child Health and Human Development, Section on Molecular Dysmorphology, NIH, Bethesda, MD, 20892, USA.

National Human Genome Research Institute, Genetic Disease Research Branch, NIH, Bethesda, MD 20892, USA.

出版信息

Biol Open. 2022 Apr 15;11(4). doi: 10.1242/bio.059052. Epub 2022 May 3.

Abstract

Identifying meaningful predictors of therapeutic efficacy from preclinical studies is challenging. However, clinical manifestations occurring in both patients and mammalian models offer significant translational value. Many neurological disorders, including inherited, metabolic Niemann-Pick disease, type C (NPC), exhibit ataxia. Both individuals with NPC and murine models manifest ataxia, and investigational therapies impacting this phenotype in mice have been reported to slow disease progression in patients (e.g. miglustat, intrathecal 2-hydroxypropyl-beta-cyclodextrin, and acetyl-L-leucine). Reproducible phenotypic scoring of animal models can facilitate comparisons between genotypes, sexes, disease course, and therapies. Previously, other groups have developed a composite phenotypic scoring system (CPSS), which was subsequently used to distinguish strain-dependent phenotypes and, with modifications, to evaluate potential therapies. However, high inter-rater reliability is paramount to widespread use. We have created a comprehensive, easy-to-follow phenotypic assessment based on the CPSS and have verified its reproducibility using murine models of NPC disease. Application of this scoring system is not limited to NPC disease and may be applicable to other models of neurodegeneration exhibiting motor incoordination, thereby increasing its utility in translational studies.

摘要

从临床前研究中确定治疗效果的有意义预测因子具有挑战性。然而,在患者和哺乳动物模型中出现的临床表现具有重要的转化价值。许多神经退行性疾病,包括遗传性、代谢性尼曼-匹克病 C 型(NPC),都表现出共济失调。NPC 患者和小鼠模型都表现出共济失调,并且已经报道了影响这种表型的研究性治疗方法可以减缓患者的疾病进展(例如,米格列醇、鞘内 2-羟丙基-β-环糊精和乙酰-L-亮氨酸)。动物模型的可重现表型评分可以促进基因型、性别、疾病进程和治疗方法之间的比较。以前,其他研究小组已经开发出一种综合表型评分系统(CPSS),随后该系统用于区分依赖于菌株的表型,并经过修改后用于评估潜在的治疗方法。然而,高的评分者间可靠性是广泛应用的关键。我们根据 CPSS 制定了一个全面、易于遵循的表型评估方法,并使用 NPC 疾病的小鼠模型验证了其可重复性。该评分系统的应用不仅限于 NPC 疾病,也可能适用于其他表现出运动不协调的神经退行性疾病模型,从而增加了其在转化研究中的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d12e/9096702/916c56adf196/biolopen-11-059052-g1.jpg

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