一组16个血清分子对阿尔茨海默病鉴别诊断的多重评估

American journal of neurodegenerative disease Pub Date : 2013-01-01 Epub Date: 2013-03-08
Gloria Biella, Massimo Franceschi, Francesca De Rino, Annalisa Davin, Giacomo Giacalone, Paola Brambilla, Panagiotis Bountris, Maria Haritou, Giuseppe Magnani, Filippo Martinelli Boneschi, Gianluigi Forloni, Diego Albani
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摘要

阿尔茨海默病(AD)目前面临的挑战之一是确定可靠的生物标志物,这些标志物可能提高诊断的准确性,可能与疾病进展和患者对治疗的反应有关。由于临床验证的AD生物标志物评估脑脊液(CSF)参数,因此对侵入性较小的诊断标志物的需求是很明显的。在这方面,血液循环细胞因子或生长因子提供了一些令人鼓舞的结果,尽管迄今尚未得到临床验证。2007年Ray等人提出了一个由18个循环分子组成的小组,可以提高AD诊断的准确性。为了复制他们的数据,我们设计了一种多重荧光测定法,包括16种独立的分析物,覆盖了18种描述蛋白质中的15种。我们收集了三个诊断组的血清样本:疑似AD (n=33),匹配的健康对照(CNT, n=23)和非AD痴呆(NAD, n=14)。校正年龄后,我们发现与CNT和NAD相比,AD中EGF-1水平升高,而NAD中TRAIL-R4水平升高。然而,通过ROC曲线分析的特异性/敏感性评价给出了诊断准确性的微弱证据(EGF和TRAIL-R4的曲线下面积分别为0.63和0.66)。最后,我们尝试用多变量算法找到一个诊断分类器。我们只发现了AD的诊断证据,而NAD样本没有显示出诊断模式。
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Multiplex assessment of a panel of 16 serum molecules for the differential diagnosis of Alzheimer's disease.

One of the current challenge in Alzheimer's disease (AD) is the identification of reliable biomarkers that might improve diagnostic accuracy, possibly correlating with the disease progression and patient's response to therapy. As the clinically validated AD biomarkers evaluate cerebrospinal fluid (CSF) parameters, the need for less invasive diagnostic markers is well evident. To this respect, blood circulating cytokines or growth factors have provided some encouraging results, even though no clinically validated to date. In 2007 Ray et al suggested a panel of 18 circulating molecules that might increase AD diagnostic accuracy. In an attempt of replicating their data, we designed a multiplex fluorimetric assay comprising 16 independent analytes and covering 15 out of the 18 described proteins. We collected serum samples from three diagnostic groups: probable AD (n=33), matched healthy controls (CNT, n=23) and non AD demented (NAD, n=14). After correction for age, we found an increased level of EGF-1 in AD in comparison to CNT and NAD, while an increase of TRAIL-R4 was found in NAD. However, evaluation of specificity/sensitivity by ROC curve analysis gave weak evidence of diagnostic accuracy (area under the curve = 0.63 and 0.66 for EGF and TRAIL-R4, respectively). Finally, we tried to find a diagnostic classifier by a multivariate algorithm. We found indication of diagnostic evidence for AD only, while NAD samples did not show a diagnostic pattern.

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