Mohanty, Rosaleena

Abstract Patients with atypical variants of Alzheimer's disease (AD) often present at a younger age with predominantly non‐amnestic impairments and a more aggressive disease course. Historically, individuals with atypical presentations have not been included in large‐scale clinical trials, which typically focus on late‐onset, sporadic amnestic‐predominant AD. Consequently, treatment options and research efforts specific to atypical AD remain limited. The emergence of amyloid‐targeting therapies that slow disease progression underscores these challenges, as evidence supporting their efficacy in early‐onset amnestic and non‐amnestic AD variants is scarce. This perspective article argues that atypical AD represents an excellent disease model for clinical trials and proposes strategies to address critical gaps in clinical trial design for this population. Key considerations include optimizing participant selection approaches, establishing syndrome‐specific or surrogate biological and clinical endpoints, and fostering advocacy to enhance early and accurate diagnosis, equitable representation, and outcomes for these populations.

Abstract Background The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution. In typical (memory‐predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicenters. However, atypical (non‐amnestic‐predominant) AD variants with heterogeneous tau patterns provide a key opportunity to assess the universality of connectivity as a scaffold for tau progression. Method We included tau‐PET data from 320 subjects with atypical AD, characterized by highly heterogeneous tau patterns ( n = 139 posterior cortical atrophy/PCA‐AD; n = 103 logopenic variant primary progressive aphasia/lvPPA‐AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS‐AD) from 14 sites, with a subset of patients ( n = 78) having longitudinal tau‐PET data. As an independent sample, we further included regional post‐mortem tau stainings from 93 atypical AD patients from two sites ( n = 19 PCA‐AD, n = 32 lvPPA‐AD, n = 23 bvAD, n = 19 CBS‐AD). Gaussian mixture modeling was used to harmonize different tau‐PET tracers by transforming tau‐PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether 1) brain regions with stronger functional connectivity showed greater covariance in cross‐sectional and longitudinal tau‐PET and post‐mortem tau pathology, and 2) functional connectivity of tau‐PET epicenters and tau‐PET accumulation epicenters was associated with cross‐sectional and longitudinal tau patterns. Result Tau‐PET epicenters—defined as the 5% brain regions with the highest tau load—aligned with clinical variants, e.g. a posterior pattern in PCA‐AD (“visual AD”) and left‐hemispheric temporal predominance in lvPPA‐AD (“language AD”) (Figure 1). More strongly functionally connected regions showed correlated concurrent tau‐PET levels, which was confirmed with post‐mortem data (Figure 2). Moreover, the connectivity profile of tau‐PET epicenters and accumulation epicenters corresponded to tau‐PET progression patterns (Figure 3). Conclusion Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicenters, across all AD clinical variants. Since tau proteinopathy is a key driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant‐specific endpoints in clinical trials.

Abstract The link between regional tau load and clinical manifestation of Alzheimer’s disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD (‘visual AD’) and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD (‘language AD’). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.

AbstractBackgroundPure Alzheimer’s disease (AD), characterized by combined amyloid and tau pathology, is not the most prevalent form of the disease as non‐AD pathologies (e.g., alpha‐synuclein and TDP‐43) are commonly observed postmortem. The role of AD and non‐AD pathologies is unclear in relation to disease heterogeneity. Therefore, we investigated whether antemortem MRI‐based atrophy subtypes of AD differ in postmortem neuropathological features and comorbid non‐AD pathologies.MethodsWe selected individuals from the ADNI with antemortem MRI evaluating brain atrophy within 2 years before death; antemortem diagnosis of AD dementia/mild cognitive impairment; and a postmortem‐confirmed AD neuropathologic change. Antemortem atrophy subtypes were modeled as continuous phenomena using a recent conceptual framework: typicality (spanning limbic predominant AD to hippocampal sparing AD) and severity (spanning typical AD to minimal atrophy AD). Postmortem neuropathological evaluation included AD hallmarks (amyloid‐beta, tau), non‐AD pathologies (alpha‐synuclein, TDP‐43) and concomitant pathological burden. Partial correlations assessed the associations between antemortem atrophy subtype dimensions and postmortem neuropathological outcomes.ResultsIn 31 individuals (mean age = 80y, 26% females), antemortem typicality was significantly associated with neuropathological features: amyloid‐beta (rho = ‐0.39 overall), tau (rho = ‐0.38 regionally), neuritic plaque density (rho = ‐0.4 overall), alpha‐synuclein (rho = ‐0.39 regionally), TDP‐43 (rho = ‐0.49 overall), and concomitance pathological burden (rho = ‐0.59 regionally). This suggests that limbic predominant AD was associated with higher burden of these pathologies compared to hippocampal sparing AD. Antemortem severity was significantly associated with concomitant pathological burden (rho = ‐0.43 regionally), such that typical AD showed higher burden than minimal atrophy AD.ConclusionsBased on our direct antemortem‐to‐postmortem validation, we hypothesize that: (a) typicality and severity in atrophy reflect differential aspects of susceptibility of the brain to AD and non‐AD pathologies; (b) limbic predominant AD and typical AD subtypes may share similar biological pathways, making them more vulnerable to the investigated AD and non‐AD pathologies compared to hippocampal sparing AD, which may follow a different biological pathway. Our findings provide a deeper understanding of associations of atrophy subtypes in AD with different pathologies, enhancing prevailing knowledge of biological heterogeneity in AD.

Abstract Background Donepezil is an approved therapy for the treatment of Alzheimer’s disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to Donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes. Methods From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical-AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We compared two subtyping approaches: the conventional categorical approach and an approach based on continuous dimensions. Results Donepezil treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response. Conclusions Our data suggest that individuals with MCI, with hippocampal sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment. Trial registration: Clinical Trial.gov Number: NCT00403520, Submission Date: November 21, 2006.

AbstractBackgroundBiological heterogeneity in Alzheimer’s disease (AD) has been observed and described as subtypes in measures of neurodegeneration (e.g., hypometabolism and atrophy). However, the relationship between these AD subtypes have not been studied. Thus, we aimed to compare and identify pathways associated with hypometabolism‐based and atrophy‐based subtypes.MethodCross‐sectional FDG‐PET and MRI scans from 173 amyloid‐positive AD individuals and 120 amyloid‐negative cognitively normal control individuals from the ADNI were included. Subtypes were identified in each neuroimaging modality by random forest hierarchical clustering using FDG‐PET uptake (measuring hypometabolism) and MRI volumes (measuring atrophy) in cortical and subcortical regions. We performed cross‐modal comparisons of atrophy patterns in hypometabolism‐based subtypes and hypometabolism patterns in atrophy‐based subtypes. To identify neurodegenerative pathways corresponding to each subtype, we used event‐based modelling to predict sequential progression of abnormality in hypometabolism and atrophy across brain regions (hippocampus, AD signature, frontal, posterior areas).ResultClustering revealed four hypometabolism‐based (two relatively limbic‐predominant: 25.7%, 19.8% and two relatively cortical‐predominant: 25.7%, 28.6%) and three atrophy‐based (diffuse: 18.7%, relatively limbic‐predominant: 28.6%, minimal: 52.6%) subtypes of AD with distinct spatial patterns and demographic and clinical characteristics. Cross‐modally, we found comparable AD‐typical atrophy patterns (involving the hippocampus and temporal regions) across the four hypometabolism‐based subtypes and comparable AD‐typical hypometabolism patterns (involving the retrosplenial cortex) across the three atrophy‐based subtypes. Event‐based modelling showed that each hypometabolism‐based subtype was associated with a unique sequential progression of regional hypometabolism, but not regional atrophy (sequence always initiated with frontal atrophy across all subtypes). Similarly, each atrophy‐based subtype was associated with a unique sequential progression of regional atrophy, but not regional hypometabolism (sequence always initiated with hypometabolism in AD signature areas across all subtypes).ConclusionOur findings suggest that hypometabolism‐based and atrophy‐based AD subtypes are not interchangeable. We identified unique metabolic and atrophy pathways specific to each subtype, which supports the notion that neurodegeneration manifests and progresses differentially across subtypes of AD. Despite being measures of neurodegeneration, hypometabolism and atrophy may not share the same extent of heterogeneity, bearing a complex multimodal relationship. Disentangling such relationships and combining complementary biomarkers to investigate heterogeneity could aid personalized treatment of AD.

Abstract Background. Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. Objectives. We used data-driven analysis of MRI data to investigate DLB subtypes. Methods. We included 165 probable DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid and cerebrovascular biomarkers at baseline, and cognitive decline over three years. Results. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n=49, 30%); a subtype with low GM volumes in fronto-occipital regions (n=76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n=40, 24%). Conclusions. This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.

AbstractBackgroundThe field of biological subtypes of Alzheimer’s disease (AD) has recently gained attention as a strong driver of precision medicine and future clinical trials. Neuropathology and neuroimaging studies have consistently identified four subtypes: hippocampal sparing AD, typical AD, limbic predominant AD, and minimal atrophy or minimal tau NFT AD. An important and still unresolved question is whether a truly hippocampal sparing subtype of AD can really exist, since it would challenge the widely accepted model of NFT spread. To address this question, we conducted a systematic review of the literature and performed original analyses on tau PET data.MethodOur systematic review included a search on EMBASE, PubMed, and Web of Science databases up to October 2020. Original analyses included implementation of several methods for AD subtyping on tau PET, and utilization of five complementary cut points to identify hippocampal sparing AD cases both in published studies and in data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).ResultIn the three reviewed neuropathologic studies, we did not find any individual case with tau NFT in the association cortex while completely sparing the hippocampus (i.e., truly hippocampal sparing cases). In the in vivo tau PET studies, more lenient cut points consistently identified AD patients with tau NFT in the association cortex while completely sparing the hippocampus.ConclusionOur current data suggests that the hippocampal sparing subtype of AD does exist ante‐mortem, at earlier stages of the disease, but more research is needed to understand its pathogenesis and progression during life. Based on the findings from both in vivo tau PET and neuropathologic studies, we suggest that there are two possible independent pathways of tau spread: (1) a canonical pathway with early involvement of entorhinal cortex with subsequent involvement of limbic regions before eventually affecting multimodal association cortices, and (2) a less common pathway that affects multimodal association cortices with limbic involvement observed at end stages of the disease. As emphasized in the Murray 2011 study, hippocampal sparing relative to greater cortical involvement defines the phenotype.

AbstractBackgroundDementia with Lewy bodies (DLB) is a neurodegenerative disorder that presents with a variety of clinical symptoms. Part of the clinical heterogeneity within DLB has been related to the atrophy/sparing of the hippocampus. We extended that previous research by investigating whether different atrophy patterns exist in DLB, beyond and above the atrophy/sparing of the hippocampus, and whether those patterns contribute to the clinical heterogeneity in DLB. We aimed to identify DLB atrophy subtypes using a hypothesis‐free data‐driven clustering approach based on regional gray matter (GM) volumes and characterize the resulting subtypes across key measures.MethodWe included data from three centers of the European DLB consortium. A high‐resolution 3D T1‐weigthed magnetization prepared rapid gradient echo (MPRAGE) sequence was acquired for 97 DLB patients. Eighty‐four cortical regions and 12 subcortical regions from Mayo Clinic Adult Lifespan Template (https://www.nitrc.org/projects/mcalt/) atlases were obtained. Clusters of DLB patients were then determined using the random forest method. Between‐group differences in key demographic, clinical, MRI volumes and cerebrospinal fluid biomarkers (CSF) (amyloid‐beta, phosphorylated‐tau) were performed for clusters characterization.ResultWe identified three subtypes of DLB patients, with distinct patterns of GM volumes and differences in several clinical and demographic measures. Cluster 1 (C1) included 32 DLB patients (33%), cluster 2 (C2) included 29 DLB patients (30%), and cluster 3 (C3) included 36 DLB patients (37%). The clusters differed in age, with C1 being significantly older (72±8.6) than C3 (66±9.5) (F=3.93, p=0.02). C1 was characterized by lower volumes in fronto‐temporal regions and had a higher frequency of visual hallucinations (68%, vs. C2 35%). C2 showed lower volumes in occipital regions. C3 had higher GM volumes overall compared with the other two clusters and presented with a higher frequency of cognitive fluctuations (91%, vs. C1 67%). There were no differences between groups in CSF biomarkers. These results were independent of cluster differences in age and global GM volume.ConclusionThere are distinct patterns of brain atrophy in patients with DLB. These patterns seem to differentially contribute to the frequencies of visual hallucinations and cognitive fluctuations, independently of differences in age and global GM volume across subtypes.