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Targeting Pathological Amyloid Aggregates with Conformation-Sensitive Antibodies
Current Alzheimer Research ( IF 1.8 ) Pub Date : 2020-06-30 , DOI: 10.2174/1567205017666201109093848
Alessandra Bigi 1 , Gilda Loffredo 1 , Roberta Cascella 1 , Cristina Cecchi 1
Affiliation  

Background: The pathogenesis of Alzheimer's disease (AD) is not directly caused by the presence of senile plaques but rather by the detrimental effects exerted on neuronal cells by toxic soluble oligomers. Such species are formed early during the aggregation process of the Aβ1-42 peptide or can be released from mature fibrils. Nowadays, efficient tools for an early diagnosis, as well as pharmaceutical treatments targeting the harmful agents in samples of AD patients, are still missing.

Objective: By integrating in vitro immunochemical assay with in vivo neuronal models of toxicity, we aim to understand and target the principles that drive toxicity in AD.

Methods: We evaluated the specificity and sensitivity of A11 and OC conformational antibodies to target a range of pathologically relevant amyloid conformers and rescue their cytotoxic effects in neuronal culture models using a number of cellular readouts.

Results: We demonstrated the peculiar ability of conformational antibodies to label pathologically relevant Aβ1-42 oligomers and fibrils and to prevent their detrimental effects on neuronal cells.

Conclusion: Our results substantially improve our knowledge on the role of toxic assemblies in neurodegenerative diseases, thus suggesting new and more effective diagnostic and therapeutic tools for AD.



中文翻译:

使用构象敏感抗体靶向病理性淀粉样蛋白聚集体

背景:阿尔茨海默病 (AD) 的发病机制不是由老年斑的存在直接引起的,而是由有毒的可溶性寡聚体对神经元细胞的有害影响引起的。这些物种在 Aβ1-42 肽的聚集过程中早期形成,或者可以从成熟的原纤维中释放出来。如今,用于早期诊断的有效工具以及针对 AD 患者样本中有害物质的药物治疗仍然缺失。

目的:通过将体外免疫化学分析与体内毒性神经元模型相结合,我们旨在了解和靶向驱动 AD 毒性的原理。

方法:我们评估了 A11 和 OC 构象抗体针对一系列病理相关淀粉样蛋白构象异构体的特异性和敏感性,并使用许多细胞读数在神经元培养模型中挽救它们的细胞毒性作用。

结果:我们证明了构象抗体具有标记病理相关 Aβ1-42 寡聚体和原纤维并防止它们对神经元细胞产生不利影响的独特能力。

结论:我们的结果大大提高了我们对毒性组装在神经退行性疾病中的作用的认识,从而为 AD 提供了新的、更有效的诊断和治疗工具。

更新日期:2020-06-30
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