Department of Biomedical Engineering, Stony Brook University, New York, New York, United States of America.
Biological Basis of Behavior Program, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2013 Dec 31;8(12):e85190. doi: 10.1371/journal.pone.0085190. eCollection 2013.
There is significant clinical and prognostic heterogeneity in the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), despite a common immunohistological signature. Consistent extra-motor as well as motor cerebral, spinal anterior horn and distal neuromuscular junction pathology supports the notion of ALS a system failure. Establishing a disease biomarker is a priority but a simplistic, coordinate-based approach to brain dysfunction using MRI is not tenable. Resting-state functional MRI reflects the organization of brain networks at the systems-level, and so changes in of motor functional connectivity were explored to determine their potential as the substrate for a biomarker signature. Intra- as well as inter-motor functional networks in the 0.03-0.06 Hz frequency band were derived from 40 patients and 30 healthy controls of similar age, and used as features for pattern detection, employing multiple kernel learning. This approach enabled an accurate classification of a group of patients that included a range of clinical sub-types. An average of 13 regions-of-interest were needed to reach peak discrimination. Subsequent analysis revealed that the alterations in motor functional connectivity were widespread, including regions not obviously clinically affected such as the cerebellum and basal ganglia. Complex network analysis showed that functional networks in ALS differ markedly in their topology, reflecting the underlying altered functional connectivity pattern seen in patients: 1) reduced connectivity of both the cortical and sub-cortical motor areas with non motor areas 2)reduced subcortical-cortical motor connectivity and 3) increased connectivity observed within sub-cortical motor networks. This type of analysis has potential to non-invasively define a biomarker signature at the systems-level. As the understanding of neurodegenerative disorders moves towards studying pre-symptomatic changes, there is potential for this type of approach to generate biomarkers for the testing of neuroprotective strategies.
尽管存在共同的免疫组织化学特征，但神经退行性疾病肌萎缩侧索硬化症 (ALS) 的临床表现和预后存在显著异质性。一致的运动外以及运动大脑、脊髓前角和远端神经肌肉连接处病理学支持 ALS 是一种系统衰竭的观点。建立疾病生物标志物是当务之急，但使用 MRI 对大脑功能进行简单的、基于坐标的方法是不可行的。静息态功能磁共振成像反映了大脑网络在系统水平上的组织，因此探索运动功能连接的变化，以确定其作为生物标志物特征的潜在基础。从 40 名患者和 30 名年龄相似的健康对照中得出了 0.03-0.06 Hz 频率范围内的内源性和内源性运动功能网络，并将其用作模式检测的特征，采用多核学习。这种方法能够准确地对一组包括多种临床亚型的患者进行分类。需要平均 13 个感兴趣区域才能达到最佳区分度。随后的分析表明，运动功能连接的改变是广泛的，包括一些明显没有临床影响的区域，如小脑和基底节。复杂网络分析表明，ALS 中的功能网络在拓扑上有很大的差异，反映了患者中观察到的潜在改变的功能连接模式：1）皮质和皮质下运动区与非运动区的连接减少 2）皮质下-皮质运动连接减少和 3）观察到皮质下运动网络内的连接增加。这种类型的分析有可能在系统水平上无创地定义生物标志物特征。随着对神经退行性疾病的理解向研究无症状前的变化发展，这种方法有可能产生生物标志物，用于测试神经保护策略。
