首页> 美国卫生研究院文献>Diagnostics >Parkinson’s Disease: Available Clinical and Promising Omics Tests for Diagnostics Disease Risk Assessment and Pharmacotherapy Personalization
【2h】

Parkinson’s Disease: Available Clinical and Promising Omics Tests for Diagnostics Disease Risk Assessment and Pharmacotherapy Personalization

机译:帕金森氏病:可用于诊断疾病风险评估和药物治疗个性化的临床和有希望的组学测试

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Parkinson’s disease is the second most frequent neurodegenerative disease, representing a significant medical and socio-economic problem. Modern medicine still has no answer to the question of why Parkinson’s disease develops and whether it is possible to develop an effective system of prevention. Therefore, active work is currently underway to find ways to assess the risks of the disease, as well as a means to extend the life of patients and improve its quality. Modern studies aim to create a method of assessing the risk of occurrence of Parkinson’s disease (PD), to search for the specific ways of correction of biochemical disorders occurring in the prodromal stage of Parkinson’s disease, and to personalize approaches to antiparkinsonian pharmacotherapy. In this review, we summarized all available clinically approved tests and techniques for PD diagnostics. Then, we reviewed major improvements and recent advancements in genomics, transcriptomics, and proteomics studies and application of metabolomics in PD research, and discussed the major metabolomics findings for diagnostics and therapy of the disease.
机译:帕金森氏病是第二常见的神经退行性疾病,代表着重大的医学和社会经济问题。对于为什么帕金森氏病会发展以及是否有可能建立有效的预防系统的问题,现代医学仍然没有答案。因此,目前正在进行积极的工作,以寻找评估疾病风险的方法,以及延长患者寿命和改善其质量的手段。现代研究旨在创建一种评估帕金森氏病(PD)发生风险的方法,寻找纠正在帕金森氏病前驱期发生的生化疾病的具体方法,并使抗帕金森氏症药物疗法的方法个性化。在这篇综述中,我们总结了用于PD诊断的所有可用的临床批准的测试和技术。然后,我们回顾了基因组学,转录组学和蛋白质组学研究的重大进展和最新进展,以及代谢组学在PD研究中的应用,并讨论了用于疾病诊断和治疗的主要代谢组学发现。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号