Boon, Baayla D.C.

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 Background Monoclonal antibodies targeting amyloid‐β (Aβ), including aducanumab, have been tested to treat Alzheimer's disease (AD). However, limited data exist on neuropathology following treatment and the effects of amyloid‐related imaging abnormalities (ARIA). We report on such data from five aducanumab‐treated study participants with AD of whom two experienced ARIA. Methods Aducanumab‐treated study participants who came to autopsy ( n = 5) were matched to AD controls ( n = 12) based on the presence/type of autosomal dominant AD mutation, APOE genotype, age at cognitive symptom onset, and sex. We assessed cognitive measures, 18 F‐florbetapir PET centiloid, ARIA risk factors, and AD neuropathologic change. Using multiplex immunofluorescence, brain regions affected along Thal Aβ phases were stained for Aβ isoforms and phosphorylated tau, as well as for ARIA‐associated markers, including Perls’ Prussian blue to detect ferric iron, fibrinogen‐α for blood brain barrier integrity, membrane attack complex (C5b‐C9) for complement activation, and activated microglia (IBA1, CD68). Results Study participants included four males and one female, all carrying at least one APOE ε4 allele. Two participants carried a PSEN1 NM_000021.4:c.817G>A , p.Glu273Lys mutation. Cumulative aducanumab dosage ranged between 5–241 mg/kg, with death occurring 5–41 months after the last infusion. Amyloid burden on PET declined in all participants (range 15‐100 centiloids). Two participants experienced ARIA. Compared to AD controls, Aβ aa1‐8 and Aβ 42 were selectively reduced in cortical layer I of aducanumab‐treated study participants ( p <0.05) but not in the total cortex, as shown for the middle frontal cortex in Figure 1. No differences were observed in phosphorylated tau burden. Prussian blue‐stained hemosiderin was present in both treated and untreated AD cases. However, in participants with ARIA, hemosiderin accumulated in superficial cortical layers near CAA‐laden meningeal and penetrating vessels, which also exhibited extensive complement and microglial activation (Figure 2). Conclusions Aβ clearance and ARIA‐related findings were localized predominantly in superficial cortical layers, suggesting that aducanumab biodistribution is more pronounced in these regions rather than deeper cortical layers.

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.

AbstractBackgroundAlzheimer’s disease (AD) is neuropathologically heterogeneous and can be objectively classified along a spectrum of corticolimbic tangle distribution as hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. The olfactory bulb is an early area of tau accumulation with a direct connection to the amygdala. Although tau pathology has been identified in the olfactory bulb, its association with AD subtypes remains unclear. To investigate these differences, tau markers were characterized within the olfactory bulb among AD subtypes.MethodThe cohort included 39 AD cases (HpSp AD: n = 15, typical AD: n = 12, limbic AD: n = 12). Immunofluorescence staining was conducted on 5 µm thick formalin‐fixed paraffin‐embedded olfactory bulb sections using phosphorylated tau (AT8 & PHF‐1) and C‐terminal tau (2E9) antibodies. Slides were digitally scanned on the PhenoImager™ HT slide scanner and analyzed using QuPath Digital Analysis software, quantifying tau burden as a percentage of positive staining.ResultIn whole olfactory bulbs, AT8 was observed as intrasomal tangle‐like immunoreactivity with some extrasomal neuritic staining. AT8 burden did not differ among subtypes (HpSp AD median = 0.28% [interquartile range 0.014‐1.7%], typical AD = 0.28% [0.027‐2.24%], limbic AD = 0.39% [interquartile range 0.39‐0.74%]). PHF‐1 was observed as intrasomal tangle‐like immunoreactivity with abundant extrasomal neuritic pathology. PHF‐1 was observed to be highest in limbic AD (HpSp AD = 3.5% [0.63‐11%)], typical AD = 3.2% [0.38‐13%], and limbic AD = 5.3% [1.97‐10%]) and differed from typical AD (p<0.05). 2E9 was observed as intrasomal tangle‐like immunoreactivity with minimal extrasomal staining and not found to differ among subtypes (HpSp AD = 0.18% [0.036‐2.2%], typical AD = 0.15% [0.021‐2.4%], and limbic AD = 0.29% [0.0030‐8.2%]).ConclusionAbundant tau accumulation was observed among all AD subtypes with some suggestion of higher tau burden in limbic predominant AD. Given the direct connection between olfactory bulb and amygdala, it is interesting to speculate of an environmental contribution to limbic predominant AD through olfactory bulb damage. Future studies will expand the cohort to include AD cases with Lewy body disease co‐pathology and primary tauopathies with a focus on the anterior olfactory nucleus as the primary site of tau pathology.

AbstractBackgroundRecent studies highlight distinct patterns of cortical atrophy between amnestic (typical) and non‐amnestic (atypical, with subtypes: behavioural, dysexecutive, logopenic and visuospatial) clinical phenotypes of Alzheimer’s disease (AD). The current study aimed to assess regional MRI patterns of cortical atrophy across AD phenotypes, and their association with amyloid‐beta (Aß), phosphorylated tau (pTau), axonal degeneration (NfL) and microvascular deterioration (COLIV).MethodPostmortem In‐situ 3DT1 3T‐MRI data was collected for 33 AD (17 typical, 16 atypical) and 16 control brain donors. Images were segmented and AAL3 atlas regional volumes were obtained using QyScore®. At subsequent autopsy, eight brain regions were selected, immunostained for Aß (4G8), pTau (AT8), Neurofilament‐light (NFL), and Collagen‐IV (COLIV), and quantified using qupath. Group comparisons and volume‐pathology associations were analyzed using linear models and partial correlations with covariates age, sex, postmortem delay, and intracranial volume.ResultsCompared to controls, AD phenotype groups showed overall lower cortical volume, while only minor volume differences were observed between AD phenotype groups, observed primarily in limbic regions (Figure 1). Across pathological markers, AD phenotype groups showed consistently higher immunoreactivity than controls, while atypical AD showed consistently higher immunoreactivity than typical AD (Figure 2). Moreover, different patterns of pathology could be observed between atypical subtypes (e.g. distinctly higher pTau load in the occipital gyrus of the visuospatial subtype). In typical AD, global volume loss was associated with lower Aß and higher pTau, NFL and COLIV immunoreactivity, while in atypical AD, global volume loss was primarily associated with higher NFL immunoreactivity (Figure 3a). Regionally, AD phenotype differences in atrophy‐pathology association were most pronounced in the (para)hippocampal regions. This distinction was mainly characterized by negative associations for NFL and COLIV, which was only observed in typical AD (Figure 3b‐c).ConclusionAtrophy patterns between AD phenotypes showed only minor differences, potentially attributable to the on average later disease stage of the study cohort. The higher immunoreactivity for pathological markers found in atypical AD might suggest a more severe disease burden. (Para)hippocampal volume decline was associated with axonal and microvascular deterioration in typical AD, but not in the higher pathologically burdened atypical AD group, suggesting a differential susceptibility between AD phenotypes.

AbstractBackgroundRecent studies highlight distinct patterns of cortical atrophy between amnestic (typical) and non‐amnestic (atypical, with subtypes: behavioural, dysexecutive, logopenic and visuospatial) clinical phenotypes of Alzheimer’s disease (AD). The current study aimed to assess regional MRI patterns of cortical atrophy across AD phenotypes, and their association with amyloid‐beta (Aβ), phosphorylated tau (pTau), axonal degeneration (NfL) and microvascular deterioration (COLIV).MethodPostmortem In‐situ 3DT1 3T‐MRI data was collected for 33 AD (17 typical, 16 atypical) and 16 control brain donors. Images were segmented and AAL3 atlas regional volumes were obtained using QyScore®. At subsequent autopsy, eight brain regions were selected, immunostained for Aβ (4G8), pTau (AT8), Neurofilament‐light (NFL), and Collagen‐IV (COLIV), and quantified using qupath. Group comparisons and volume‐pathology associations were analyzed using linear models and partial correlations with covariates age, sex, postmortem delay, and intracranial volume.ResultsCompared to controls, AD phenotype groups showed overall lower cortical volume, while only minor volume differences were observed between AD phenotype groups, observed primarily in limbic regions (Fig. 1). Across pathological markers, AD phenotype groups showed consistently higher immunoreactivity than controls, while atypical AD showed consistently higher immunoreactivity than typical AD (Fig. 2). Moreover, different patterns of pathology could be observed between atypical subtypes (e.g. distinctly higher pTau load in the occipital gyrus of the visuospatial subtype). In typical AD, global volume loss was associated with lower Aβ and higher pTau, NFL and COLIV immunoreactivity, while in atypical AD, global volume loss was primarily associated with higher NFL immunoreactivity (Fig. 3a). Regionally, AD phenotype differences in atrophy‐pathology association were most pronounced in the (para) hippocampal regions. This distinction was mainly characterized by negative associations for NFL and COLIV, which was only observed in typical AD (Fig. 3b‐c).ConclusionAtrophy patterns between AD phenotypes showed only minor differences, potentially attributable to the on average later disease stage of the study cohort. The higher immunoreactivity for pathological markers found in atypical AD might suggest a more severe disease burden. (Para) hippocampal volume decline was associated with axonal and microvascular deterioration in typical AD, but not in the higher pathologically burdened atypical AD group, suggesting a differential susceptibility between AD phenotypes.

AbstractBackgroundAlzheimer’s disease (AD) is heterogeneous in both its clinical and neuropathologic course. Age at onset and distribution of corticolimbic tangles can vary widely among individuals. Genetic risk factors APOE ε4 and MAPT H1 increase AD risk. However, the association with the spatial distribution of pathology remains a key gap in knowledge. We investigated the effects of age at onset, APOE ε4, MAPT H1, and family history of cognitive symptoms on corticolimbic tangle density variability to better distinguish how each factor contributes.MethodThe FLorida Autopsied Multi‐Ethnic (FLAME) cohort was queried for neuropathologically confirmed AD cases (n = 1233). Tangle density (count per 0.125mm2) was quantified using thioflavin‐S staining in nucleus basalis of Meynert (nbM), hippocampal CA1 and subiculum, association cortices, and primary cortices. Cortical thickness was measured using digital pathology on hematoxylin‐eosin‐stained sections. We employed univariate and multivariate negative binomial regression models to evaluate the association of each factor on tangle density across the corticolimbic axis. Multivariate analysis was adjusted for significant variables from univariate analyses.ResultDonors with young‐onset (<65) AD (YOAD; n = 314) had more tangles than those with late‐onset AD (LOAD; n = 919) across most corticolimbic regions (Fig. 1). Except for CA1, younger age at onset was associated with a higher expected tangle density with an increase ranging from 8% in subiculum up to 99% in motor cortex (Table 1). Male sex was associated with lower expected tangle density throughout all corticolimbic regions. Being male associated the strongest in visual cortex with a 41% tangle density decrease. The APOE ε4 allele associated with an increase of tangle density in the nbM, CA1, subiculum, and visual cortex, whereas the MAPT H1 haplotype associated with a decrease in association and motor cortices. A positive family history for cognitive problems was associated with a 16% decrease of tangle density in visual cortex. Tangle density correlated closely with (sub)cortical thickness in the CA1+subiculum, superior temporal, inferior parietal, and middle frontal cortex (Spearman Rho = ‐0.39 ‐ ‐0.58, p<0.001).ConclusionThese data contribute to the concept that brain regions may experience aging and genetics differentially, underlining the need to distinguish these aspects when investigating AD disease mechanisms.

Abstract Aims Although the neuroanatomical distribution of tau and amyloid‐β is well studied in Alzheimer's disease (AD) (non)‐amnestic clinical variants, that of neuroinflammation remains unexplored. We investigate the neuroanatomical distribution of activated myeloid cells, astrocytes, and complement alongside amyloid‐β and phosphorylated tau in a clinically well‐defined prospectively collected AD cohort. Methods Clinical variants were diagnosed antemortem, and brain tissue was collected post‐mortem. Typical AD ( n = 10), behavioural/dysexecutive AD ( n = 6), posterior cortical atrophy (PCA) AD ( n = 3), and controls ( n = 10) were neuropathologically assessed for AD neuropathology, concurrent pathology including Lewy body disease, limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), and vascular pathology. For quantitative assessment, we analysed the corticolimbic distribution of phosphorylated tau, amyloid‐β, CD68, MHC‐II, C4b, and glial fibrillary acidic protein (GFAP) using digital pathology. Results Phosphorylated tau was distinctly distributed in each variant. In all variants, amyloid‐β was neocortical‐dominant, with a notable increase in the middle frontal cortex of behavioural/dysexecutive AD. Typical AD and PCA AD had no concurrent Lewy body disease, whereas three out of six cases with behavioural/dysexecutive AD did. LATE‐NC stage >0 was observed in three AD cases, two typical AD (stage 1/3), and one behavioural/dysexecutive AD (stage 2/3). Vascular pathology was present in each variant. In typical AD, CD68 and MHC‐II were hippocampal‐dominant. In behavioural/dysexecutive AD, C4b was elevated in the middle frontal and inferior parietal cortex. In PCA AD, MHC‐II was increased in the fusiform gyrus, and GFAP in parietal cortices. Correlations between AD neuropathology and neuroinflammation were distinct within variants. Conclusions Our data suggests that different involvement of neuroinflammation may add to clinical heterogeneity in AD, which has implications for neuroinflammation‐based biomarkers and future therapeutics.