From the Division of Psychology and Mental Health (R.U.I., G.P.), University of Manchester; Dementia Research Centre (D.O., D.M.C., S.C., K.X.Y.), UCL Institute of Neurology, London; and MRC Cognition and Brain Sciences Unit (A.H., M.A.L.R.), University of Cambridge, United Kingdom.
Neurology. 2024 Aug 27;103(4):e209679. doi: 10.1212/WNL.0000000000209679. Epub 2024 Jul 23.
Alzheimer disease (AD) spans heterogeneous typical and atypical phenotypes. Posterior cortical atrophy (PCA) is a striking example, characterized by prominent impairment in visual and other posterior functions in contrast to typical, amnestic AD. The primary study objective was to establish how the similarities and differences of cognition and brain volumes within AD and PCA (and by extension other AD variants) can be conceptualized as systematic variations across a transdiagnostic, graded multidimensional space.
This was a cross-sectional, single-center, observational, cohort study performed at the National Hospital for Neurology & Neurosurgery, London, United Kingdom. Data were collected from a cohort of patients with PCA and AD, matched for age, disease duration, and Mini-Mental State Examination (MMSE) scores. There were 2 sets of outcome measures: (1) scores on a neuropsychological battery containing 22 tests spanning visuoperceptual and visuospatial processing, episodic memory, language, executive functions, calculation, and visuospatial processing and (2) measures extracted from high-resolution T1-weighted volumetric MRI scans. Principal component analysis was used to extract the transdiagnostic dimensions of phenotypical variation from the detailed neuropsychological data. Voxel-based morphometry was used to examine associations between the PCA-derived clinical phenotypes and the structural measures.
We enrolled 93 participants with PCA (mean: age = 59.9 years, MMSE = 21.2; 59/93 female) and 58 AD participants (mean: age = 57.1 years, MMSE = 19.7; 22/58 female). The principal component analysis for PCA (sample adequacy confirmed: Kaiser-Meyer-Olkin = 0.865) extracted 3 dimensions accounting for 61.0% of variance in patients' performance, reflecting general cognitive impairment, visuoperceptual deficits, and visuospatial impairments. Plotting AD cases into the PCA-derived multidimensional space, and vice versa, revealed graded, overlapping variations between cases along these dimensions, with no evidence for categorical-like patient clustering. Similarly, the relationship between brain volumes and scores on the extracted dimensions was overlapping for PCA and AD cases.
These results provide evidence supporting a reconceptualization of clinical and radiologic variation in these heterogenous AD phenotypes as being along shared phenotypic continua spanning PCA and AD, arising from systematic graded variations within a transdiagnostic, multidimensional neurocognitive geometry.
阿尔茨海默病（AD）表现为多种典型和非典型表型。后部皮质萎缩（PCA）就是一个显著的例子，其特征是在视觉和其他后部功能方面存在明显障碍，而典型的遗忘型 AD 则没有这种障碍。主要研究目的是确定 AD 和 PCA（以及其他 AD 变异型）内认知和脑容量的相似和差异如何在跨诊断、分级多维空间中被视为系统变化。
这是一项在英国伦敦国家神经学与神经外科学院进行的横断面、单中心、观察性队列研究。该研究从 PCA 和 AD 患者队列中收集数据，这些患者按年龄、疾病持续时间和 Mini-Mental State Examination（MMSE）评分进行匹配。有 2 组结果测量指标：（1）包含 22 项测试的神经心理学测试套件的分数，这些测试涵盖了视知觉和视空间处理、情景记忆、语言、执行功能、计算和视空间处理；（2）从高分辨率 T1 加权容积 MRI 扫描中提取的测量指标。主成分分析用于从详细的神经心理学数据中提取表型变异的跨诊断维度。体素形态计量学用于检查 PCA 衍生的临床表型与结构测量之间的关联。
我们共纳入 93 名 PCA 患者（平均年龄=59.9 岁，MMSE=21.2；59/93 为女性）和 58 名 AD 患者（平均年龄=57.1 岁，MMSE=19.7；22/58 为女性）。PCA 的主成分分析（样本充足性得到确认：Kaiser-Meyer-Olkin=0.865）提取了 3 个维度，解释了患者表现中 61.0%的方差，反映了总体认知障碍、视知觉缺陷和视空间障碍。将 AD 病例绘制到 PCA 衍生的多维空间中，并反之亦然，显示出这些维度上病例之间存在渐变、重叠的变化，没有证据表明病例存在分类聚类。同样，PCA 和 AD 病例的脑容量与提取维度上的分数之间的关系也是重叠的。
这些结果提供了证据，支持将这些异质 AD 表型的临床和影像学变异重新概念化为沿 PCA 和 AD 共享的表型连续体，这是由跨诊断、多维神经认知几何中的系统分级变化引起的。
