A Non-invasive Digital Biomarker for the Detection of Rest Disturbances in the SOD1G93A Mouse Model of ALS
A Non-invasive Digital Biomarker for the Detection of Rest Disturbances in the SOD1G93A Mouse Model of ALS
复制标题
DOI：
10.3389/fnins.2020.00896
复制
发表时间：
2020-09-01
影响因子：
4.3
通讯作者：
Mandillo, Silvia
中科院分区：
文献类型：
--
作者：
Golini, Elisabetta;Rigamonti, Mara;Mandillo, Silvia
肌萎缩性侧索硬化症（Amyotrophic Lateral Sclerosis，ALS）是一种严重的神经退行性疾病，可累及中枢和外周神经系统，导致运动神经元变性，最终导致肌肉萎缩、瘫痪和死亡。睡眠障碍在ALS患者中很常见，导致生活质量进一步恶化。因此，在ALS动物模型中潜在地评估睡眠和休息障碍的研究方法是至关重要的。我们使用自动化的家庭笼监测系统（DVC（R））来捕获可能与睡眠和休息障碍相关的不规则活动模式，从而在SOD 1G 93 A小鼠模型中与ALS的进展相关。DVC（R）能够实现非侵入性的24/7长期动物活动监测，我们对7至24周龄的雄性和雌性小鼠进行了体重下降和神经肌肉功能退化的评估，这些指标是通过网格悬挂和握力测试测量的。我们发现，随着SOD 1G 93 A小鼠ALS的进展，活动模式开始变得不规则，特别是在白天，频繁的活动发作在对照小鼠和年轻的SOD 1G 93 A中都没有观察到。通过设计一种新的数字生物标志物，称为规则性破坏指数（RDI），定量捕获活动模式的不规则性。我们表明，RDI是一个强大的措施，能够检测家庭笼活动模式，可能与疾病进展期间的休息/睡眠相关的干扰。此外，RDI上升在早期症状阶段平行网格挂和体重下降。通过DVC（R）实现的对动物活动的非侵入性长期连续监测有助于发现新的活动模式，一旦验证，该模式可能与ALS疾病的SOD 1G 93 A小鼠模型中的睡眠和休息障碍相关。
Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease that affects both central and peripheral nervous system, leading to the degeneration of motor neurons, which eventually results in muscle atrophy, paralysis, and death. Sleep disturbances are common in patients with ALS, leading to even further deteriorated quality of life. Investigating methods to potentially assess sleep and rest disturbances in animal models of ALS is thus of crucial interest. We used an automated home cage monitoring system (DVC(R)) to capture irregular activity patterns that can potentially be associated with sleep and rest disturbances and thus to the progression of ALS in the SOD1G93A mouse model. DVC(R)enables non-intrusive 24/7 long term animal activity monitoring, which we assessed together with body weight decline and neuromuscular function deterioration measured by grid hanging and grip strength tests in male and female mice from 7 until 24 weeks of age. We show that as the ALS progresses over time in SOD1G93A mice, activity patterns start becoming irregular, especially during day time, with frequent activity bouts that are neither observed in control mice nor in SOD1G93A at a younger age. The increasing irregularities of activity pattern are quantitatively captured by designing a novel digital biomarker, referred to as Regularity Disruption Index (RDI). We show that RDI is a robust measure capable of detecting home cage activity patterns that could be related to rest/sleep-related disturbances during the disease progression. Moreover, the RDI rise during the early symptomatic stage parallels grid hanging and body weight decline. The non-intrusive long-term continuous monitoring of animal activity enabled by DVC(R)has been instrumental in discovering novel activity patterns potentially correlated, once validated, with sleep and rest disturbances in the SOD1G93A mouse model of the ALS disease.