导读：英国诺丁汉大学的研究人员最近发现了7种可作为检测阿尔茨海默病的标记的蛋白，通过这些蛋白的异常程度来判定被测者是否患上阿尔茨海默病，其准确率最高可达95%，该研究为提高早期诊断阿尔茨海默氏症提供了可能。
英国诺丁汉大学研究人员最近发现了7种可作为检测阿尔茨海默病的标记的蛋白，通过这些蛋白的异常程度来判定被测者是否患上阿尔茨海默病，其准确率最高可达95%，该研究为提高早期诊断阿尔茨海默氏症提供了可能。相关研究论文发表于《阿尔茨海默病期刊》(Journal of Alzheimer's Disease)。
阿尔茨海默氏症被早期诊断出来后有助于及时进行干预治疗，从而在最大程度上治愈患者。然而由于导致记忆以及认知能力的退化原因多种多样，阿尔茨海默病的早期诊断一直是个难题，开发出有效的诊断方法，成为科学家们急需攻克的重要目标。
为查找阿尔茨海默病的潜在标记物，诺丁汉大学的研究人员将目标瞄向了脑脊髓液。他们对30名阿尔茨海默病患者、20名健康老人以及10名轻度认知障碍人士的脑脊髓液样本进行了比较，以寻找健康人群与患病人群间的差异。通过对比，他们发现，患有阿尔茨海默病的人群的脑脊髓液中有4种蛋白水平明显较常人高，3种蛋白的水平则较常人低。特别是一种名为SPARCL1的蛋白，其作为阿尔茨海默病标记的效果十分明显。当仅就脑脊髓液样本中该蛋白水平进行检测时，研究人员诊断被测者是否患有阿尔茨海默病的准确率为65%，而如果将7种蛋白的异常水平都纳入检测范围，诊断准确率高达95%。
研究人员随后对另外32名健康人士和30名阿尔茨海默病人的脑脊髓液样本进行了检测，结果显示对这一新人群所进行的7种蛋白标记检测，诊断准确率为85%。这表明这7种蛋白完全可作为阿尔茨海默病的诊断标记。
研究人员指出，新发现为达成阿尔茨海默病的早期诊断提供了一条新途径，有助于科学家开发出新的疾病诊断甚至是治疗方法。下一步他们计划利用新发现开发出可在阿尔茨海默病早期阶段即能对其进行诊断的血液检测方法。
Identification of SPARC-like 1 Protein as Part of a Biomarker Panel for Alzheimer's Disease in Cerebrospinal Fluid
Baharak Vafadar-Isfahani, Graham Ball, Clare Coveney, Christophe Lemetre, David Boocock, Lennart Minthon, Oskar Hansson, Amanda Kathleen Miles, Sabina M Janciauskiene, Donald Warden, A. David Smith, Gordon Wilcock, Noor Kalsheker, Robert Rees, Balwir Matharoo-Ball, Kevin Morgan
We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-β, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17).
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https://iospress.metapress.com/content/k05121028n61j902/?p=336c2bd408d447f0b106c81892a06828
