Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns

Atrophy patterns in cerebral amyloid angiopathy with and without cortical superficial siderosis

OBJECTIVE

To investigate differential atrophy patterns based on the presence of cortical superficial siderosis (cSS) and the role of cSS in predicting amyloid positivity in memory clinic patients fulfilling the diagnostic criteria for probable cerebral amyloid angiopathy (CAA).

METHODS

We retrospectively collected data from 44 cognitively impaired patients with probable CAA who underwent 3-dimensional, T1-weighted MRIs (cSS+, n = 27; cSS-, n = 17). Amyloid-positive patients with Alzheimer disease (AD) (n = 56) and amyloid-negative cognitively normal participants (n = 34) were recruited as controls. Among the patients with CAA who underwent amyloid-PET scans (75.0%), we investigated whether amyloid-negative cases were unevenly distributed based on cSS presentation. APOE genotypes, Mini-Mental State Examination scores, and cortical atrophy pattern along with hippocampal volume were compared across groups.

RESULTS

Ten patients with probable CAA presented amyloid negativity and all of them belonged to the cSS- group (58.8%). Compared to the cSS- group, the cSS+ group presented higher APOE ε4 frequency, worse memory dysfunction, and lower hippocampal volume. Compared with cognitively normal participants, the cSS+ group exhibited atrophy in the precuneus, posterior cingulate, parietotemporal, superior frontal, and medial temporal areas, a pattern similar to AD-specific atrophy. The cSS- group exhibited atrophy in the parietotemporal, superior frontal, and precentral regions.

CONCLUSION

Our findings imply that the current version of the Boston criteria may not be sufficient enough to remove non-CAA cases from a cognitively impaired population, especially in the absence of cSS. Patients with probable CAA presenting cSS appear to reflect a CAA phenotype that shares pathologic hallmarks with AD, providing insight into the CAA-to-AD continuum.

The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment

Introduction

An Alzheimer's disease (AD) biomarker adjusted for age-related brain changes should improve specificity for AD-related pathological burden.

Methods

We calculated a brain-age-adjusted “personalized AD cortical thickness index” (pADi) in mild cognitive impairment patients from the Alzheimer's Disease Neuroimaging Initiative. We performed receiver operating characteristic analysis for discrimination between patients with and without cerebrospinal fluid evidence of AD and logistic regression in an independent sample to determine if a dichotomized pADi predicted conversion to AD dementia.

Results

Receiver operating characteristic area under the curve was 0.69 and 0.72 in the two samples. Three empirical methods identified the same cut-point for pADi in the discovery sample. In the validation sample, 83% of pADi+ mild cognitive impairment patients were cerebrospinal fluid AD biomarker positive. pADi+ mild cognitive impairment patients (n = 63, 38%) were more likely to progress to AD dementia after 1 (odds ratio = 2.9) and 3 (odds ratio = 2.6) years.

Discussion

The pADi is a personalized, magnetic resonance imaging–derived AD biomarker that predicts progression to dementia.

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The personalized AD cortical thickness index (pADi) is a personalized magnetic resonance imaging–derived, brain-age-adjusted Alzheimer's disease (AD) biomarker.

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The pADi accurately identifies mild cognitive impairment patients with cerebrospinal fluid markers of AD.

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The pADi was consistent across two independent samples with 1.5T and 3T magnetic resonance imaging data.

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An optimal cut-point predicted progression to AD dementia over 1 or 3 years.

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The pADi can identify mild cognitive impairment likely due to AD in individual patients.

Posterior atrophy predicts time to dementia in patients with amyloid-positive mild cognitive impairment

BACKGROUND

In patients with amyloid-positive mild cognitive impairment (MCI), neurodegenerative biomarkers such as medial temporal lobe atrophy (MTA) are useful to predict disease progression to dementia. Although posterior atrophy (PA) is a well-known neurodegenerative biomarker of Alzheimer's disease, little is known about PA as a predictor in patients with amyloid-positive MCI.

METHODS

We included 258 patients with amyloid-positive MCI with at least one follow-up visit, and who had low cerebrospinal fluid (CSF) β-amyloid_1-42 concentration. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative study. We assessed PA and MTA on magnetic resonance imaging (MRI) using visual rating scales and retrospectively determined progression to dementia during the follow-up period of up to 3 years (median 24 months). The Cox proportional hazards model was used to analyze hazard ratios (HRs) of PA and MTA for disease progression. Additionally, subjects were divided into four groups according to brain atrophy pattern (no atrophy, MTA only, PA only, both MTA and PA), and HRs for disease progression were compared with the no atrophy reference group. Analyses were conducted with and without adjustment for CSF phosphorylated tau_181p (p-tau) and baseline demographics.

RESULTS

A total of 123 patients (47.7%) showed MTA and 174 patients (67.4%) showed PA. Of the total cohort, 139 cases (53.9%) progressed to dementia. PA and MTA were associated with an increased risk for progression to dementia (HR 2.244, 95% confidence interval (CI) 1.497-3.364, and HR 1.682, 95% CI 1.203-2.352, respectively). In the analysis according to atrophy pattern, HR (95% CI) for progression was 2.998 (1.443-6.227) in the MTA only group, 3.126 (1.666-5.864) in the PA only group, and 3.814 (2.045-7.110) in both MTA and PA group. These results remained significant after adjustment.

CONCLUSIONS

In patients with amyloid-positive MCI, PA could predict progression to dementia independently of MTA.

Alzheimer disease brain atrophy subtypes are associated with cognition and rate of decline

OBJECTIVE

To test the hypothesis that cortical and hippocampal volumes, measured in vivo from volumetric MRI (vMRI) scans, could be used to identify variant subtypes of Alzheimer disease (AD) and to prospectively predict the rate of clinical decline.

METHODS

Amyloid-positive participants with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 and ADNI2 with baseline MRI scans (n = 229) and 2-year clinical follow-up (n = 100) were included. AD subtypes (hippocampal sparing [HpSp_MRI], limbic predominant [LP_MRI], typical AD [tAD_MRI]) were defined according to an algorithm analogous to one recently proposed for tau neuropathology. Relationships between baseline hippocampal volume to cortical volume ratio (HV:CTV) and clinical variables were examined by both continuous regression and categorical models.

RESULTS

When participants were divided categorically, the HpSp_MRI group showed significantly more AD-like hypometabolism on ¹⁸F-fluorodeoxyglucose-PET (p < 0.05) and poorer baseline executive function (p < 0.001). Other baseline clinical measures did not differ across the 3 groups. Participants with HpSp_MRI also showed faster subsequent clinical decline than participants with LP_MRI on the Alzheimer's Disease Assessment Scale, 13-Item Subscale (ADAS-Cog₁₃), Mini-Mental State Examination (MMSE), and Functional Assessment Questionnaire (all p < 0.05) and tAD_MRI on the MMSE and Clinical Dementia Rating Sum of Boxes (CDR-SB) (both p < 0.05). Finally, a larger HV:CTV was associated with poorer baseline executive function and a faster slope of decline in CDR-SB, MMSE, and ADAS-Cog₁₃ score (p < 0.05). These associations were driven mostly by the amount of cortical rather than hippocampal atrophy.

CONCLUSIONS

AD subtypes with phenotypes consistent with those observed with tau neuropathology can be identified in vivo with vMRI. An increased HV:CTV ratio was predictive of faster clinical decline in participants with AD who were clinically indistinguishable at baseline except for a greater dysexecutive presentation.

Neuroimaging as a tool to study the sources of phenotypic heterogeneity in Huntington's disease

PURPOSE OF REVIEW

Huntington's disease is a neurodegenerative disorder characterized by a triad of motor, cognitive and psychiatric disturbances. There is great variability regarding the prominence and evolution of each type of clinical sign. One possible source of phenotypic heterogeneity could be the more prominent degeneration of specific brain circuits. The scope of this review is to highlight the most recent neuroimaging studies that have analysed the relationship between brain changes and motor, cognitive and psychiatric alterations in Huntington's disease.

RECENT FINDINGS

The results from recent neuroimaging studies are heterogeneous. Although there is a great overlap between the different regions associated with each symptomatic domain, there is some degree of differentiation. For example, the motor network is associated with motor impairment, whereas the ventral striatum is especially involved in emotional deficits related with psychiatric problems.

SUMMARY

Motor, cognitive and psychiatric impairments are associated with structural and functional brain biomarkers. However, the specificity of the regions involved remains unknown, because these studies focused on specific regions and symptoms. In order to tease apart the neural substrates that underlie the phenotypic heterogeneity in Huntington's disease, multivariate approaches combining brain and behavioural measures related to all symptomatic domains should be considered in the future.