Besson Florent L, La Joie Renaud, Doeuvre Loïc, Gaubert Malo, Mézenge Florence, Egret Stéphanie, Landeau Brigitte, Barré Louisa, Abbas Ahmed, Ibazizene Meziane, de La Sayette Vincent, Desgranges Béatrice, Eustache Francis, Chételat Gaël
Institut National de la Santé et de la Recherche Médicale, Unité U1077, 14000 Caen, France, Université de Caen Basse-Normandie, Unité Mixte de Recherche (UMR)-S1077, 14000 Caen, France, Centre Hospitalier Universitaire de Caen, U1077, 14000 Caen, France, Department of Nuclear Medicine, Centre Hospitalier Universitaire de Caen, 14000 Caen, France.
Institut National de la Santé et de la Recherche Médicale, Unité U1077, 14000 Caen, France, Université de Caen Basse-Normandie, Unité Mixte de Recherche (UMR)-S1077, 14000 Caen, France, Centre Hospitalier Universitaire de Caen, U1077, 14000 Caen, France, Ecole Pratique des Hautes Etudes, UMR-S1077, 14000 Caen, France.
J Neurosci. 2015 Jul 22;35(29):10402-11. doi: 10.1523/JNEUROSCI.0150-15.2015.
Neuroimaging biomarkers, namely hippocampal volume loss, temporoparietal hypometabolism, and neocortical β-amyloid (Aβ) deposition, are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our aim was to characterize the cognitive and brain profiles of elders classified as positive or negative for each biomarker to further our understanding of their use in the preclinical diagnosis of AD. Fifty-four cognitively normal individuals (age = 65.8 ± 8.3 years) underwent neuropsychological tests (structural MRI, FDG-PET, and Florbetapir-PET) and were dichotomized into positive or negative independently for each neuroimaging biomarker. Demographic, neuropsychological, and neuroimaging data were compared between positive and negative subgroups. The MRI-positive subgroup had lower executive performances and mixed patterns of lower volume and metabolism in AD-characteristic regions and in the prefrontal cortex. The FDG-positive subgroup showed only hypometabolism, predominantly in AD-sensitive areas extending to the whole neocortex, compared with the FDG-negative subgroup. The amyloid-positive subgroup was older and included more APOE ε4 carriers compared with the amyloid-negative subgroup. When considering MRI and/or FDG biomarkers together (i.e., the neurodegeneration-positive), there was a trend for an inverse relationship with Aβ deposition such that those with neurodegeneration tended to show less Aβ deposition and the reverse was true as well. Our findings suggest that: (1) MRI and FDG biomarkers provide complementary rather than redundant information and (2) relatively young cognitively normal elders tend to have either neurodegeneration or Aβ deposition, but not both, suggesting additive rather than sequential/causative links between AD neuroimaging biomarkers at this age. Significance statement: Neuroimaging biomarkers are included in the recent research criteria for preclinical Alzheimer's disease (AD). However, how to use these biomarkers is still being debated, especially regarding their sequence. Our findings suggest that MRI and FDG-PET biomarkers should be used in combination, offering an additive contribution instead of reflecting the same process of neurodegeneration. Moreover, the present study also challenges the hierarchical use of the neuroimaging biomarkers in preclinical AD because it suggests that the neurodegeneration observed in this population is not due to β-amyloid deposition. Rather, our results suggest that β-amyloid- and tau-related pathological processes may interact but not necessarily appear in a systematic sequence.
神经影像学生物标志物，即海马体体积缩小、颞顶叶代谢减退和新皮质β-淀粉样蛋白（Aβ）沉积，被纳入了近期临床前阿尔茨海默病（AD）的研究标准。然而，如何使用这些生物标志物仍存在争议，尤其是关于它们的先后顺序。我们的目的是对根据每种生物标志物分类为阳性或阴性的老年人的认知和脑部特征进行描述，以加深我们对其在AD临床前诊断中应用的理解。54名认知正常的个体（年龄 = 65.8 ± 8.3岁）接受了神经心理学测试（结构MRI、氟代脱氧葡萄糖正电子发射断层显像[FDG-PET]和氟比他哌正电子发射断层显像[Florbetapir-PET]），并针对每种神经影像学生物标志物独立分为阳性或阴性。对阳性和阴性亚组之间的人口统计学、神经心理学和神经影像学数据进行了比较。MRI阳性亚组在执行功能方面表现较差，在AD特征区域和前额叶皮质存在体积减小和代谢降低的混合模式。与FDG阴性亚组相比，FDG阳性亚组仅表现出代谢减退，主要在延伸至整个新皮质的AD敏感区域。与淀粉样蛋白阴性亚组相比，淀粉样蛋白阳性亚组年龄更大，且载脂蛋白E ε4携带者更多。当同时考虑MRI和/或FDG生物标志物（即神经退行性变阳性）时，与Aβ沉积呈负相关趋势，即神经退行性变者往往Aβ沉积较少，反之亦然。我们的研究结果表明：（1）MRI和FDG生物标志物提供的是互补而非冗余信息；（2）相对年轻的认知正常老年人往往要么有神经退行性变，要么有Aβ沉积，但不会两者兼有，这表明在这个年龄段，AD神经影像学生物标志物之间是相加关系而非先后顺序/因果关系。意义声明：神经影像学生物标志物被纳入了近期临床前阿尔茨海默病（AD）的研究标准。然而，如何使用这些生物标志物仍存在争议，尤其是关于它们的先后顺序。我们的研究结果表明，MRI和FDG-PET生物标志物应联合使用，它们起到相加作用，而非反映神经退行性变的相同过程。此外，本研究还对临床前AD中神经影像学生物标志物的分层使用提出了挑战，因为它表明在该人群中观察到的神经退行性变并非由β-淀粉样蛋白沉积所致。相反，我们的结果表明，β-淀粉样蛋白和tau相关的病理过程可能相互作用，但不一定按系统顺序出现。
