Max Planck Institute of Psychiatry, Molecular Stress Physiology, Kraepelinstrasse 2-10, 80804 Munich, Germany.
Dis Markers. 2013;35(1):23-31. doi: 10.1155/2013/984845. Epub 2013 Jul 21.
Major depression, affecting an estimated 350 million people worldwide, poses a serious social and economic threat to modern societies. There are currently two major problems calling for innovative research approaches, namely, the absence of biomarkers predicting antidepressant response and the lack of conceptually novel antidepressant compounds. Both, biomarker predicting a priori whether an individual patient will respond to the treatment of choice as well as an early distinction of responders and nonresponders during antidepressant therapy can have a significant impact on improving this situation. Biosignatures predicting antidepressant response a priori or early in treatment would enable an evidence-based decision making on available treatment options. However, research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the selection of specific antidepressant compound for an individual patient. In this review, we propose an optimized translational research strategy to overcome some of the major limitations in biomarker discovery. We are confident that early transfer and integration of data between both species, ideally leading to mutual supportive evidence from both preclinical and clinical studies, are most suitable to address some of the obstacles of current depression research.
重度抑郁症，全球估计有 3.5 亿人受其影响，对现代社会构成了严重的社会和经济威胁。目前有两个主要问题需要创新的研究方法，即缺乏预测抗抑郁反应的生物标志物和缺乏概念新颖的抗抑郁化合物。生物标志物可以预测个体患者是否对首选治疗有反应，以及在抗抑郁治疗期间早期区分反应者和无反应者，这两者都可以显著改善这种情况。预测抗抑郁反应的生物标志物或在治疗早期就能预测抗抑郁反应，这将有助于基于证据做出关于可用治疗选择的决策。然而，迄今为止的研究并没有确定任何具有足够临床效用的生物或遗传预测因子，无法为个体患者选择特定的抗抑郁化合物提供信息。在这篇综述中，我们提出了一种优化的转化研究策略，以克服生物标志物发现中的一些主要限制。我们有信心，两种物种之间的数据早期转移和整合，理想情况下从临床前和临床研究中相互支持证据，最适合解决当前抑郁症研究中的一些障碍。
