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Recent advances in diagnostic technologies for autoimmune diseases.

机译:自身免疫性疾病诊断技术的最新进展。

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The investigation of autoimmunity provides an interest challenge in "omics" research and, particularly, proteome research, as autoimmune diseases are common disorders of unsolved etiology that occur in a wide range of manifestations, in all of which tissues and organs are attacked by the body's own immune system. Autoantibodies are a hallmark of many autoimmune diseases and the presence of autoantibodies is a distinctive and key characteristic of autoimmune diseases. Conventionally, the study of autoimmune response has always been conducted by analysing the presence and/or concentration of individual antibodies in biological fluids. New proteomic techniques allow the simultaneous identification/measurement of different autoantibodies in sera of patients suffering from autoimmune diseases. The possibility of simultaneously measuring a number of correlated analytes appears to be very interesting for analytical reasons (reduced volumes of biological samples, reagents and low costs), logistical/managerial reasons, and pathophysiological reasons (combination of markers in disease-oriented or organ-oriented profiling). In particular, we describe data collected by using high-throughput techniques such as antigen microarrays and mass spectrometry for antibody profiling. While recently collected data demonstrate satisfactory analytical sensitivity and reproducibility, some issues such as standardization and data interpretation have to be solved before the introduction of these new and promising techniques into clinical practice.
机译:自身免疫的研究为“组学”研究,尤其是蛋白质组学研究提出了有趣的挑战,因为自身免疫性疾病是病因学很普遍的疾病,表现为多种表现形式,所有这些组织和器官都受到人体的攻击。自己的免疫系统。自身抗体是许多自身免疫性疾病的标志,并且自身抗体的存在是自身免疫性疾病的独特特征和关键特征。常规上,总是通过分析生物流体中单个抗体的存在和/或浓度来进行自身免疫应答的研究。新的蛋白质组学技术可以同时鉴定/测量患有自身免疫性疾病的患者血清中的各种自身抗体。由于分析原因(减少生物样品的体积,减少试剂和降低成本),后勤/管理方面的原因以及病理生理原因(针对疾病或器官的标记物组合),同时测量多种相关分析物的可能性似乎非常有趣。定向分析)。特别是,我们描述了通过使用高通量技术(例如抗原微阵列和质谱法)进行抗体分析收集的数据。尽管最近收集的数据显示出令人满意的分析灵敏度和可重复性,但在将这些新的有希望的技术引入临床实践之前,必须解决一些问题,例如标准化和数据解释。

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