Department of Neurology, University of California-San Francisco4Center for Neuroimmunology, Service of Neurology, Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Department of Epidemiology and Biostatistics, University of California-San Francisco.
JAMA Neurol. 2014 Jul 1;71(7):840-7. doi: 10.1001/jamaneurol.2014.895.
Predicting disease evolution is becoming essential for optimizing treatment decision making in multiple sclerosis (MS). Multiple sclerosis pathologic damage typically includes demyelination, neuro-axonal loss, and astrogliosis.
To evaluate the potential of magnetic resonance markers of central nervous system injury to predict brain-volume loss and clinical disability in multiple sclerosis.
DESIGN, SETTING, AND PARTICIPANTS: Participants were selected from the Multiple Sclerosis Center at the University of California-San Francisco. The preliminary data set included 59 patients with MS and 43 healthy control individuals. The confirmatory data set included 220 patients from an independent, large genotype-phenotype research project.
Baseline N-acetylaspartate (NAA) level, myo-inositol (mI) in normal-appearing white and gray matter, myelin water fraction in normal-appearing white matter, markers of axonal damage, astrogliosis, and demyelination were evaluated as predictors in a preliminary data set. Potential predictors were subsequently tested for replication in a confirmatory data set. Clinical scores and percentage of brain-volume change were obtained annually over 4 years as outcomes. Predictors of outcomes were assessed using linear models, linear mixed-effects models, and logistic regression.
N-acetylaspartate and mI both had statistically significant effects on brain volume, prompting the use of the mI:NAA ratio in normal-appearing white matter as a predictor. The ratio was a predictor of brain-volume change in both cohorts (annual slope in the percentage of brain-volume change/unit of increase in the ratio: -1.68; 95% CI, -3.05 to -0.30; P = .02 in the preliminary study cohort and -1.08; 95% CI, -1.95 to -0.20; P = .02 in the confirmatory study cohort). Furthermore, the mI:NAA ratio predicted clinical disability (Multiple Sclerosis Functional Composite evolution: -0.52 points annually, P < .001; Multiple Sclerosis Functional Composite sustained progression: odds ratio, 2.76/SD increase in the ratio; 95% CI, 1.32 to 6.47; P = .01) in the preliminary data set and predicted Multiple Sclerosis Functional Composite evolution (-0.23 points annually; P = .01), Expanded Disability Status Scale evolution (0.57 points annually; P = .04), and Expanded Disability Status Scale sustained progression (odds ratio, 1.46; 95% CI, 1.10 to 1.94; P = .009) in the confirmatory data set. Myelin water fraction did not show predictive value.
The mI:NAA ratio in normal-appearing white matter has consistent predictive power on brain atrophy and neurological disability evolution. The combined presence of astrogliosis and axonal damage in white matter has cardinal importance in disease severity.
预测疾病的演变对于优化多发性硬化症（MS）的治疗决策变得至关重要。多发性硬化症的病理损伤通常包括脱髓鞘、神经轴突丢失和星形胶质增生。
评估中枢神经系统损伤的磁共振标志物在预测多发性硬化症脑容量损失和临床残疾方面的潜力。
设计、地点和参与者：参与者是从加利福尼亚大学旧金山分校的多发性硬化症中心选择的。初步数据集包括 59 名 MS 患者和 43 名健康对照个体。验证数据集包括来自独立的大型基因型-表型研究项目的 220 名患者。
基线时的 N-乙酰天冬氨酸（NAA）水平、正常表现的白质和灰质中的肌醇（mI）、正常表现的白质中的髓鞘水分数、轴突损伤、星形胶质增生和脱髓鞘的标志物被评估为初步数据集中的预测因子。随后在验证数据集中对潜在预测因子进行了复制测试。在 4 年内每年获得临床评分和脑容量变化百分比作为结果。使用线性模型、线性混合效应模型和逻辑回归评估了结果的预测因子。
NAA 和 mI 对脑体积均有统计学显著影响，促使在正常表现的白质中使用 mI：NAA 比值作为预测因子。该比值在两个队列中均为脑容量变化的预测因子（脑容量变化的年斜率/比值增加单位：-1.68；95%CI，-3.05 至 -0.30；P=0.02 在初步研究队列和-1.08；95%CI，-1.95 至 -0.20；P=0.02 在验证研究队列）。此外，mI：NAA 比值预测临床残疾（多发性硬化症功能综合进展：每年 -0.52 分，P<0.001；多发性硬化症功能综合持续进展：比值每增加 1 个标准差，几率增加 2.76；95%CI，1.32 至 6.47；P=0.01）在初步数据集中，并且预测多发性硬化症功能综合进展（每年 -0.23 分；P=0.01）、扩展残疾状况量表进展（每年 0.57 分；P=0.04）和扩展残疾状况量表持续进展（比值，1.46；95%CI，1.10 至 1.94；P=0.009）在验证数据集中。髓鞘水分数没有显示出预测价值。
正常表现的白质中的 mI：NAA 比值在脑萎缩和神经功能残疾演变方面具有一致的预测能力。白质中星形胶质增生和轴突损伤的共同存在对疾病严重程度具有重要意义。
