Barsoum Stephanie, Latimer Caitlin S, Nolan Amber L, Barrett Alexander, Chang Koping, Troncoso Juan, Keene C Dirk, Benjamini Dan
bioRxiv. 2024 May 8:2024.05.06.592719. doi: 10.1101/2024.05.06.592719.
Despite the presence of significant Alzheimer's disease (AD) pathology, characterized by amyloid β (Aβ) plaques and phosphorylated tau (pTau) tangles, some cognitively normal elderly individuals do not inevitably develop dementia. These findings give rise to the notion of cognitive 'resilience', suggesting maintained cognitive function despite the presence of AD neuropathology, highlighting the influence of factors beyond classical pathology. Cortical astroglial inflammation, a ubiquitous feature of symptomatic AD, shows a strong correlation with cognitive impairment severity, potentially contributing to the diversity of clinical presentations. However, noninvasively imaging neuroinflammation, particularly astrogliosis, using MRI remains a significant challenge. Here we sought to address this challenge and to leverage multidimensional (MD) MRI, a powerful approach that combines relaxation with diffusion MR contrasts, to map cortical astrogliosis in the human brain by accessing sub-voxel information. Our goal was to test whether MD-MRI can map astroglial pathology in the cerebral cortex, and if so, whether it can distinguish cognitive resiliency from dementia in the presence of hallmark AD neuropathological changes. We adopted a multimodal approach by integrating histological and MRI analyses using human postmortem brain samples. cerebral cortical tissue specimens derived from three groups comprised of non-demented individuals with significant AD pathology postmortem, individuals with both AD pathology and dementia, and non-demented individuals with minimal AD pathology postmortem as controls, underwent MRI at 7 T. We acquired and processed MD-MRI, diffusion tensor, and quantitative T and T MRI data, followed by histopathological processing on slices from the same tissue. By carefully co-registering MRI and microscopy data, we performed quantitative multimodal analyses, leveraging targeted immunostaining to assess MD-MRI sensitivity and specificity towards Aβ, pTau, and glial fibrillary acidic protein (GFAP), a marker for astrogliosis. Our findings reveal a distinct MD-MRI signature of cortical astrogliosis, enabling the creation of predictive maps for cognitive resilience amid AD neuropathological changes. Multiple linear regression linked histological values to MRI changes, revealing that the MD-MRI cortical astrogliosis biomarker was significantly associated with GFAP burden (standardized β=0.658, pFDR<0.0001), but not with Aβ (standardized β=0.009, =0.913) or pTau (standardized β=-0.196, =0.051). Conversely, none of the conventional MRI parameters showed significant associations with GFAP burden in the cortex. While the extent to which pathological glial activation contributes to neuronal damage and cognitive impairment in AD is uncertain, developing a noninvasive imaging method to see its affects holds promise from a mechanistic perspective and as a potential predictor of cognitive outcomes.
尽管存在以淀粉样β(Aβ)斑块和磷酸化tau(pTau)缠结为特征的显著阿尔茨海默病(AD)病理改变,但一些认知正常的老年人并不一定会发展为痴呆症。这些发现引发了认知“弹性”的概念,即尽管存在AD神经病理学改变,但认知功能仍得以维持,这突出了经典病理学之外的因素的影响。皮质星形胶质细胞炎症是有症状AD的一个普遍特征,与认知障碍严重程度密切相关,可能导致临床表现的多样性。然而,使用MRI对神经炎症,特别是星形胶质细胞增生进行无创成像仍然是一项重大挑战。在这里,我们试图应对这一挑战,并利用多维度(MD)MRI,一种将弛豫与扩散磁共振对比相结合的强大方法,通过获取亚体素信息来绘制人脑皮质星形胶质细胞增生图谱。我们的目标是测试MD-MRI是否能够绘制大脑皮质中的星形胶质细胞病理图谱,如果可以,在存在典型AD神经病理变化的情况下,它是否能够区分认知弹性和痴呆症。我们采用了一种多模态方法,通过对人类死后大脑样本进行组织学和MRI分析。来自三组的大脑皮质组织标本,包括死后有显著AD病理改变的非痴呆个体、既有AD病理改变又有痴呆症的个体,以及死后AD病理改变最小的非痴呆个体作为对照,在7T下进行MRI检查。我们获取并处理了MD-MRI、扩散张量以及定量T1和T2 MRI数据,随后对来自同一组织的切片进行组织病理学处理。通过仔细地将MRI和显微镜数据进行配准,我们进行了定量多模态分析,利用靶向免疫染色来评估MD-MRI对Aβ、pTau和胶质纤维酸性蛋白(GFAP,一种星形胶质细胞增生的标志物)的敏感性和特异性。我们的研究结果揭示了皮质星形胶质细胞增生独特的MD-MRI特征,能够在AD神经病理变化中创建认知弹性的预测图谱。多元线性回归将组织学值与MRI变化联系起来,表明MD-MRI皮质星形胶质细胞增生生物标志物与GFAP负荷显著相关(标准化β = 0.658,pFDR < 0.0001),但与Aβ(标准化β = 0.009,p = 0.913)或pTau(标准化β = -0.196,p = 0.051)无关。相反,没有一个传统的MRI参数显示与皮质中的GFAP负荷有显著关联。虽然病理性胶质细胞激活在AD中导致神经元损伤和认知障碍的程度尚不确定,但开发一种无创成像方法来观察其影响,从机制角度以及作为认知结果的潜在预测指标来看都具有前景。