Carlson Jesper O E, Gatz Margaret, Pedersen Nancy L, Graff Caroline, Nennesmo Inger, Lindström Anna-Karin, Gerritsen Lotte
From the Karolinska Institutet, Stockholm, Sweden (JOEC, MG, NLP, CG, IN, A-KL, LG); University of Southern California, Los Angeles, California (MG, NLP); and VU University Medical Centre, Amsterdam, The Netherlands (LG).
J Neuropathol Exp Neurol. 2015 Nov;74(11):1061-70. doi: 10.1097/NEN.0000000000000251.
We examined the extent to which tauopathy distribution, as determined by Braak staging, might be predicted by various risk factors in older individuals. The Swedish Twin Registry provided extensive information on neuropsychological function, lifestyle, and cardiovascular risk factors of 128 patients for whom autopsy data including Braak staging were available. Logistic regression was used to develop a prognostic model that targeted discrimination between Braak stages 0 to II and III to VI. The analysis showed that Braak stages III to VI were significantly predicted by having 1 or more APOE ε4 alleles, older age, high total cholesterol, absence of diabetes and cardiovascular disease, and poorer scores on the Wechsler Adult Intelligence Score Information test, verbal fluency, and recognition memory but better verbal recall. The algorithm predicted Braak stages III to VI well (receiver-operating characteristic area under curve, 0.897; 95% confidence interval, 0.842-0.951). Using a cutoff of 50% risk or more, the sensitivity was 85%, the specificity was 70%, and the negative predictive value was 69%. This study demonstrates that tauopathy distribution can be accurately predicted using a combination of antemortem patient data. These results provide further insight into tauopathy development and AD-related disease mechanisms and suggest a prognostic model that predicts the spread of neurofibrillary tangles above the transentorhinal stage.
我们研究了在老年人中,由Braak分期确定的tau蛋白病分布在多大程度上可由各种风险因素预测。瑞典双胞胎登记处提供了128例患者的神经心理功能、生活方式和心血管风险因素的广泛信息,这些患者可获得包括Braak分期在内的尸检数据。采用逻辑回归建立了一个预后模型,目标是区分Braak分期0至II期和III至VI期。分析表明,具有1个或更多APOE ε4等位基因、年龄较大、总胆固醇水平高、无糖尿病和心血管疾病、韦氏成人智力量表信息测试得分较低、语言流畅性较差以及识别记忆较差但语言回忆较好,可显著预测Braak分期III至VI期。该算法对Braak分期III至VI期预测良好(曲线下受试者工作特征面积为0.897;95%置信区间为0.842 - 0.951)。使用50%或更高风险的临界值,敏感性为85%,特异性为70%,阴性预测值为69%。本研究表明,结合生前患者数据可准确预测tau蛋白病分布。这些结果为tau蛋白病的发展和阿尔茨海默病相关疾病机制提供了进一步的见解,并提出了一种预测神经原纤维缠结在跨内嗅皮质阶段以上扩散的预后模型。