Biomarker development in patients with HNPP

HNPP 患者的生物标志物开发

• 批准号: 10550162
• 负责人: Yongsheng Chen
• 金额: $ 46.04万
• 依托单位: WAYNE STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10550162
• 关键词: Animal Model; Axon; Biological Assay; Biological Markers; Biopsy; Charcot-Marie-Tooth Disease; Clinical; Clinical Trials; Data; Dermal; Disease; Disease Progression; Distal; Enrollment; Excision; Fatty acid glycerol esters; Fiber; Floor; Genes; Goals; Hereditary neuropathy with liability to pressure palsies; Heterozygote; Human; Image; Imaging Techniques; Individual; Intramuscular; Laboratories; Leg; Length; Longitudinal Studies; Magnetic Resonance Imaging; Measurement; Measures; Mechanics; Methods; Monitor; Motor; Muscle; Muscle Weakness; Muscle denervation procedure; Myelin; Myelinated nerve fiber; Nerve; Nerve Fibers; Outcome Measure; Output; PMP22 gene; Pathologic; Pathology; Patients; Peripheral Nerves; Peripheral Nervous System Diseases; Permeability; Phase; Polyneuropathy; Procedures; Process; Protons; Relaxation; Sensory; Severity of illness; Skin; System; Testing; Thigh structure; Time; biomarker development; clinically relevant; cohort; deep learning; deep learning model; density; detection method; disability; functional outcomes; imaging modality; indexing; inter-institutional; minimally invasive; nerve conduction study; nervous system disorder; pathology imaging; pharmacologic; preclinical study; primary outcome; rate of change; seal; secondary outcome; serial imaging; small molecule; success; sural nerve; translational potential; treatment effect

PROJECT SUMMARY/ABSTRACT Heterozygous deletion of human Peripheral Myelin Protein 22 (PMP22) gene results in hereditary neuropathy with liability to pressure palsies (HNPP). HNPP is characterized pathologically by focal myelin thickenings known as “tomacula” in peripheral nerves. Patients with HNPP typically present with transient focal sensory loss and muscle weakness that may be evoked by mild mechanical compressions that do not affect healthy humans. Our preclinical studies testing small molecule compound in HNPP animal model have been shown to arrest disease pathology. However, translation of this potential therapy to clinical use demand specific validated outcome measures to monitor the effects of treatment longitudinally in patients with HNPP. Therefore, the goal of this study is to develop monitoring biomarkers that may serve as either primary or secondary outcome measurements in HNPP clinical trials. The study will investigate two measures: quantitative magnetic resonance imaging (qMRI) and human skin biopsy. The degree of axonal loss is usually correlated with disease severity in neurological disorders. Therefore, measures of axonal loss are often reliable biomarkers for disease progression. Traditionally, pathology in peripheral nerve diseases has been evaluated by sural nerve biopsy, an invasive procedure that requires surgical removal of the nerve, so sequential sural nerve biopsies are not possible for longitudinal studies. Human skin biopsies are minimally invasive and can be repeated many times in the same subject. Preliminary studies have demonstrated that pathologies in dermal axon and myelin can be quantified automatically through deep learning. This study will use the established deep learning-based model to automate dermal nerve morphometrics in skin biopsy. On the other hand, using qMRI to assess muscular fat fraction (FF) in legs, a marker of muscle denervation that indirectly reflects axonal loss, we found that FF is increased in patients with HNPP. This study will determine whether FF quantified in individual muscle can be used to track progression of HNPP with better responsiveness. Furthermore, this study will develop a deep learning-based method to automate the laborious individual muscle FF quantification with qMRI. Although intramuscular fat accumulation is the end pathology resulting from axonal loss in HNPP, direct assessment of the diseased nerve is still needed. This study will use the strategically acquired gradient echo (STAGE) imaging technique to quantify peripheral nerves, including magnetization transfer ratio, proton density, longitudinal and effective transverse relaxation times. Due to the transient, multi-focal features of clinical presentation in patients with HNPP, existing function outcome measures, such as the Charcot-Marie-Tooth neuropathy score or nerve conduction studies, may not capture those episodes in a timely manner. However, axonal loss accumulated over time determines the final disabilities in patients with HNPP. Our overall hypothesis is that quantitative data from skin biopsy together with qMRI can reliably measure axonal loss in patients with HNPP.

项目摘要/摘要 人外周髓磷脂蛋白22（PMP 22）基因杂合性缺失导致遗传性神经病 易患压力性麻痹（HNPP）。HNPP的病理特征是已知的局灶性髓鞘增厚。 就像周围神经中的“tomacula”一样。HNPP患者通常表现为短暂的局灶性感觉丧失， 肌肉无力，可能由不影响健康人的轻度机械压迫引起。我们 在HNPP动物模型中测试小分子化合物的临床前研究已经显示出阻止疾病 病理然而，将这种潜在的疗法转化为临床应用需要特定的经验证的结果 监测HNPP患者纵向治疗效果的措施。因此，这一目标 本研究旨在开发可作为主要或次要结局测量的监测生物标志物 在HNPP临床试验中。该研究将调查两项措施：定量磁共振成像（qMRI） 和人体皮肤活检。轴突丢失的程度通常与神经系统疾病的严重程度相关。 紊乱因此，轴突损失的测量通常是疾病进展的可靠生物标志物。传统上， 周围神经疾病的病理学已经通过腓肠神经活组织检查来评估，这是一种侵入性方法， 需要手术切除神经，因此连续的腓肠神经活检不可能用于纵向研究。 人体皮肤活检是微创的，可以在同一对象中重复多次。初步 研究已经证明， 深度学习本研究将使用已建立的基于深度学习的模型来自动化真皮神经 皮肤活检的形态计量学另一方面，使用qMRI评估腿部肌肉脂肪分数（FF）， 作为肌肉去神经支配的标志物，间接反映了轴突的损失，我们发现FF在患有 HNPP。本研究将确定单个肌肉中定量的FF是否可用于跟踪 HNPP具有更好的响应性。此外，这项研究将开发一种基于深度学习的方法， 使用qMRI自动化费力的个体肌肉FF定量。虽然肌内脂肪堆积 是HNPP中轴突丢失导致的终末病理，仍然需要对患病神经进行直接评估。 本研究将使用战略性采集梯度回波（STAGE）成像技术来量化外周血淋巴细胞的数量。 神经，包括磁化传递率，质子密度，纵向和有效横向弛豫 次由于HNPP患者临床表现的短暂性、多灶性特征， 结果测量，如Charcot-Marie-Tooth神经病变评分或神经传导研究，可能不 及时捕捉这些事件。然而，随着时间的推移，轴突损失的积累决定了最终的 HNPP患者的残疾。我们的总体假设是，皮肤活检的定量数据与 qMRI可以可靠地测量HNPP患者的轴突损失。