Biomarkers for Alzheimer's disease: ready for the next step.
Biomarkers for Alzheimer's disease: ready for the next step.
复制标题
阿尔茨海默病的生物标志物：为下一步做好准备。
DOI：
10.1093/brain/awp184
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Hillis,ArgyeE
中科院分区：
文献类型：
--
作者：
Rosenberg,PaulB;Hillis,ArgyeE
As potential disease-modifying treatments for Alzheimer’s disease advance into phase II and III human trials, it is apparent that biomarker development will be needed for several reasons. The most relevant of these include the ability to detect treatment response sensitively, to improve understanding of the effect of drugs that target disease mechanisms, and to identify Alzheimer’s disease in its pre-clinical stage. We have reviewed several recent papers published in Brain, which address biomarker development in Alzheimer’s disease, and use their findings to suggest further research.Some of these studies are early results from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a large multi-centre trial of biomarker modalities in patients with Alzheimer’s disease, mild cognitive impairment (MCI) and cognitively healthy older controls with an emphasis on standardized imaging techniques across centres. Nestor et al.(2008) measured ventricular volume changes over time and found that MCI subjects had a faster rate of ventricular enlargement than controls, and that Alzheimer’s disease subjects had an even faster rate. Most importantly, among participants with MCI, the rate of ventricular enlargement was higher in those who progressed to Alzheimer’s disease than in those who did not. The authors estimate that using ventricular enlargement as a surrogate marker of treatment outcome could improve the power of a treatment trial significantly versus standard cognitive outcomes. Desikan et al.(2009) developed methods of automated MRI analysis of regional brain volumes with the goal of identifying differences between patients with MCI and healthy controls. Entorhinal and supramarginal gyrus cortical thickness and hippocampal volumes afforded the best discrimination between these two groups. The automated analysis tools were impressively reliable and yielded replicable results in two different cohorts and with many different MRI scanners. Querbes et al.(2009) developed a rapid automated method for measuring cortical thickness and found that these changes were good predictors of an alteration in diagnosis from normal to MCI, or from MCI to overt Alzheimer’s disease up to 24 months prior to that change. Their method is particularly attractive as it is relatively simple and builds on a reasonably robust literature on cortical thickness assessed by manual methods. Interestingly enough,
