Neuroimaging correlates of pathologically defined subtypes of Alzheimer's disease: a case-control study

Abstract

Background Atypical variants of Alzheimer’s disease (AD) have been pathologically defined based on the distribution of neurofibrillary tangles; hippocampal sparing (HpSp) AD shows minimal involvement of the hippocampus and limbic predominant (LP) AD shows neurofibrillary tangles restricted to the medial temporal lobe. We aimed to determine whether MRI patterns of atrophy differ across HpSp AD, LP AD and typical AD, and whether imaging could be a useful predictor of pathological subtype during life. Methods In this case-control study, we identified 177 patients who had been prospectively followed in the Mayo Clinic Alzheimer’s Disease Research Center, were demented during life, had AD pathology at autopsy (Braak stage ≥ IV, intermediate-high probability AD) and an antemortem MRI. Cases were assigned to one of three pathological subtypes (HpSp n=19, typical n=125, or LP AD n=33) based on neurofibrillary tangle counts and their ratio in association cortices to hippocampus, without reference to neuronal loss. Voxel-based morphometry and atlas-based parcellation were used to compare patterns of grey matter loss across groups, and to controls. Findings The severity of medial temporal and cortical grey matter atrophy differed across subtypes. The most severe medial temporal atrophy was observed in LP AD, followed by typical AD, and then HpSp AD. Conversely, the most severe cortical atrophy was observed in HpSp AD, followed by typical AD, and then LP AD. A ratio of hippocampal-to-cortical volume provided the best discrimination across all three AD subtypes. The majority of typical AD (98/125;78%) and LP AD (31/33;94%) subjects, but only 8/19 (42%) of the HpSp AD subjects, presented with a dominant amnestic syndrome. Interpretation Patterns of atrophy on MRI differ across the pathological subtypes of AD, suggesting that MR regional volumetrics reliably track the distribution of neurofibrillary tangle pathology and can predict pathological subtype during life. Funding US National Institutes of Health (National Institute on Aging)

Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease

“…In the remainder of this paper, we highlighted the results of three-factor model (Fig. 2B), because the emergence of the temporal and cortical factors were consistent with the "limbicpredominant" and "hippocampal-sparing" pathologically defined AD subtypes previously reported (3,7). We additionally repeated analyses for two-and four-factor models, which yielded behavioral insights consistent with the three-factor model.…”

“…Specifically, heterogeneity has been observed in the clinical presentation of AD (2) and the spatial distribution of neurofibrillary tangles (NFTs) (3,4) as well as the presence of comorbid pathologies, such as vascular disease, Lewy bodies, and transactive response DNA binding protein 43 kDa (TDP-43) (5,6). Interestingly, the spatial distribution of atrophy varies across AD subtypes defined on the basis of NFT distribution (7), suggesting that analyses of gray matter (GM) patterns are useful to characterize heterogeneity in AD. Furthermore, although distinct atrophy patterns have been observed in patients who clearly show atypical clinical presentations (8), heterogeneity in GM atrophy has also been reported among late-onset AD cases (9).…”

“…Most studies investigating the heterogeneity of AD have examined patients soon after AD onset or at advanced AD stages (3,7,(15)(16)(17). However, the pathophysiological processes of AD begin at least a decade before clinical diagnosis (18), suggesting that the emergence of this heterogeneity may occur before the onset of clinical dementia.…”

P2‐143: Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns

“…In our present study, the P subtype cases were also younger at symptom onset than those of the MT or D subtypes, which finding is consistent with hippocampussparing AD. Given the fact that the global cognitive assessments did not differ among these three subgroups (Table 1), the younger age in the P subtype subjects may suggest a faster disease course [7]. There were some discrepancies between our findings and those of the autopsy study.…”

Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease

“…Quantification of the volume loss and/or structural changes in brain areas has shown an improvement of the differential diagnosis between the AD and some atypical pathological subtypes (Whitwell et al., 2012). Interestingly, this type of quantification does, indeed, resembles the anatomo‐functional correlations that neuroradiologists perform for the early stages of the disease, for example, if there is some evidence of functional impairment, clinicians will search for structural abnormalities and changes in particular brain regions such as the hypothalamus.…”