Spinal Muscular Atrophy Foundation, New York, New York, United States of America.
PLoS One. 2013;8(4):e60113. doi: 10.1371/journal.pone.0060113. Epub 2013 Apr 2.
Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS).
BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores.
12 of the 35 putative SMA biomarkers were significantly associated (p<0.05) with motor function, with a 13(th) analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures.
Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients.
脊髓性肌萎缩症(SMA)在以下方面存在挑战:(i)监测疾病活动和预测进展;(ii)设计允许快速评估候选疗法的试验;以及(iii)了解疾病的分子原因和后果。SMA 运动和非运动功能的验证生物标志物将有助于解决这些挑战。我们的目标是:(i)使用免疫测定平台从“SMA 生物标志物研究(BforSMA)”中发现更多的标志物;(ii)在来自多地点自然史研究(NHS)的 SMA 患者的独立队列中验证这些假定的生物标志物。
通过免疫测定分析 BforSMA 研究的血浆样本(N = 129),以鉴定与 SMA 运动功能相关的新分析物。这些免疫测定包括先前通过色谱法鉴定的最强候选生物标志物。我们选择了 35 种生物标志物,以验证来自 SMA NHS 的 1 型、2 型和 3 型 SMA 样本(N = 158)。将假定的生物标志物与多个运动量表以及肺功能、神经生理学、力量和生活质量指标进行了关联测试。我们实施了 Tobit 模型来预测 SMA 运动功能评分。
在 35 种假定的 SMA 生物标志物中,有 12 种(p<0.05)与运动功能显著相关,其中有 1 种(p<0.05)接近显著。其他一些分析物与 SMA 的非运动结果指标相关。在这 35 种生物标志物中,有 27 种被选择纳入用于与运动和其他功能测量相关的商业面板(SMA-MAP)。
使用独立队列进行发现和验证,产生了一组与运动功能和 SMA 疾病活动的其他测量显著相关的 SMA 生物标志物。生成了用于在其他 SMA 收集和干预试验中进一步测试的商业 SMA-MAP 生物标志物面板。未来的工作包括在其他神经肌肉疾病中评估该面板,评估其对实验性 SMA 疗法的药效动力学反应,以及预测 SMA 患者随时间的功能变化。