Development of a peptide-based diagnostic for amyotrophic lateral sclerosis

摘要/摘要 肌萎缩侧索硬化症(即ALS或Lou Gehrig病)是最常见的成人起病运动神经元 紊乱，以进行性虚弱为临床特征。术后2-5年的平均存活率。 但由于进展率变化很大，10%的人可以存活≥10年。没有治愈的方法 对于ALS，但有治疗和干预可以限制症状和不必要的并发症，以及 提高生活质量。不幸的是，对于肌萎缩侧索硬化症没有单一的明确诊断或有效的生物标记物。 疾病的发展。大多数患者从第一次出现症状到确诊ALS需要近一年的时间 使用目前的方法(例如核磁共振、神经功能分析、多项血液和尿液测试以排除模拟 紊乱)。此外，唯一有效的疾病进展标志是死亡时间和修改后的ALS 功能评定量表(ALSFRS-R)，这是对残疾和呼吸的主观衡量。尽管ALS 是一种罕见的疾病(在美国影响大约20,000人)，更多的流行疾病可以模仿 ALS包括但不限于周围神经病、多发性硬化症、神经肌肉传递 紊乱和甲状腺机能亢进症。值得注意的是，多达61%的肌萎缩侧索硬化症患者被误诊为拟态障碍 最初，这可能会对患者的预后产生负面影响。在早期诊断肌萎缩侧索硬化症有一个紧急的未得到满足的需求 通过快速和非侵入性的方法预测时间点，并客观地预测ALS的进展，特别是在 临床试验设置。肌萎缩侧索硬化症相关抗体为肌萎缩侧索硬化症的诊断和疾病监测提供了新途径。 虽然以前测量体液抗体类型(免疫球蛋白G、免疫球蛋白A和免疫球蛋白M)的总水平的研究已经 不一致的是，最近的研究发现特定的免疫球蛋白自身抗体，与绝对免疫球蛋白水平无关，是 散发性肌萎缩侧索硬化症发病和进展的潜在新标记物。根据这些最新发现，我们建议 识别敏感和选择性的免疫标记，我们将把它开发成可靠的、非侵入性的、 用于ALS早期检测的体外芯片。此阵列还可能用于监视和 预测疾病的进展。 在这个第一阶段的应用中，我们将使用噬菌体展示生物扫描和下一代测序来识别 结合散发性肌萎缩侧索硬化症患者特异性抗体的多肽并形成多肽阵列 能够从血清中重复性地检测这种免疫特征。在第二阶段，我们将完善 用于在基线和其他时间点早期检测ALS的免疫签名，评估阵列的实用性 以确定疾病的进展，并扩大阵列生产。这一简单的基于多肽的测试将 为初级保健医生和神经科医生提供明确和可操作的结果，使最终和 肌萎缩侧索硬化症的快速诊断，从而提高了早期发现、诊断和适当处理的比率。这 检测还有可能使基于血清的疾病进展预测成为可能。

SUMMARY/ABSTRACT Amyotrophic lateral sclerosis (i.e. ALS or Lou Gehrig's disease) is the most common adult-onset motor neuron disorder, with progressive weakness being the clinical hallmark. The average survival rate is 2-5 years post- diagnosis, but 10% of individuals survive ≥10 years, due to highly variable rates of progression. There is no cure for ALS, but there are treatments and interventions that can limit symptoms and unnecessary complications, and improve quality of life. Unfortunately, there is no single definitive diagnostic for ALS or validated biomarker for disease progression. It takes nearly a year from the first occurrence of symptoms to confirm ALS in most patients using current approaches (e.g. MRI, nerve function analyses, multiple blood and urine tests to rule out mimic disorders). Also, the only validated markers of disease progression are time to death and the Revised ALS Functional Rating Scale (ALSFRS-R), which is a subjective measure of disability and breathing. Although ALS is a rare disease (affecting approximately 20,000 people in the US), many more prevalent diseases can mimic ALS including but not limited to peripheral neuropathies, multiple sclerosis, neuromuscular transmission disorders, and hyperthyroidism. Significantly, up to 61% of ALS patients are misdiagnosed with a mimic disorder initially, which can negatively impact patient outcomes. There is an urgent unmet need to diagnose ALS at earlier timepoints via rapid and non-invasive methods, and to objectively predict ALS progression, particularly in the clinical trial setting. ALS-associated antibodies offer a new avenue for ALS diagnostics and disease monitoring. While previous studies measuring total levels of humoral antibody types (IgG, IgA, and IgM) have been inconsistent, recent studies have identified specific IgG autoantibodies, independent of absolute IgG level, as potential new markers of sporadic ALS onset and progression. Based on these recent findings, we propose to identify a sensitive and selective immunosignature, which we will develop into a reliable, non-invasive, in vitro array for the early detection of ALS. This array may also have potential for monitoring and predicting disease progression. In this Phase 1 application, we will use phage display biopanning and next generation sequencing to identify peptides that bind antibodies specifically enriched in patients with sporadic ALS and develop a peptide array capable of reproducibly detecting this immunosignature from serum. In Phase 2, we will refine the immunosignature for the early detection of ALS at baseline and additional timepoints, assess utility of the array to determine progression of the disease, and scale up array production. This simple peptide-based test will provide clear and actionable results for primary care physicians and neurologists, allowing the definitive and rapid diagnosis of ALS, thereby increasing the rate of early detection, diagnosis, and proper management. This test also has potential to enable the serum-based prediction of disease progression.