Citations

Abstract Background Alzheimer's disease (AD) exhibits significant genetic heterogeneity, with no single model fully explaining its inheritance pattern. Structural variants (SVs) may contribute to the missing heritability of AD, particularly in disease pathology and familial AD, which remain largely unexplored. Method Structural variants (SVs) were analyzed in unrelated 1,162 individuals from the ROSMAP study (687 cognitively normal (CN), 475 AD patients), as well as 197 Non‐Hispanic White (NHW) families (926 individuals, 58.5% with AD) and 214 Caribbean Hispanic (CH) families (1,340 individuals, 59.17% with AD). Large insertions and deletions were identified using Manta, Absinthe, and MELT from whole‐genome sequencing, supplemented by Sniffles2 and external SV call sets. This approach generated a unified VCF file containing 45,251 insertions and 76,566 deletions. After filtering for missingness rate and allele counts, a total of 9,290 insertions and 9,529 deletions were retained for analysis. Genome‐wide SV analyses were performed with AD‐related metrics in ROSMAP, adjusting for age, sex, and principal components, and validated in an independent ADSP replication cohort comprising 29,055 unrelated individuals (17,110 CN and 11,945 AD patients). Result We identified nine SVs (one insertion and eight deletions) segregating in AD families. An insertion near PDCD10 in NHW families reached genome‐wide significance ( p <5×10 ‐8 ) for AD risk in the replication cohort. Two deletions in KIF26B and SPHKAP were found in both CH and NHW families, while five appeared only in NHW and one in CH. All eight deletions showed genome‐wide significance for AD risk. SV GWAS on AD pathologies in ROSMAP revealed an insertion in INPP4B with the strongest association to global brain pathology (β=0.19; p = 2.32×10 ‐5 ), also linked to pathological AD, diffuse plaques, and Braak staging. A deletion near ADGRB1 (β=1.53; p = 5.05×10 ‐6 ) was associated with neuritic plaques, and another near ARMC2 (β=1.66; p = 2.17×10 ‐6 ) was linked to diffuse plaques. All three SVs associated with AD ( p <5×10 ‐6 ) in replication. Conclusion Our findings reveal numerous SVs segregating in familial AD across both CH and NHW families, as well as additional SVs linked to sporadic AD. Prioritizing these SVs based on their potential effects on gene function and expression will provide deeper insight into their contributions to both familial and sporadic AD.

Abstract Background Primary progressive apraxia of speech (PPAOS) is a neurodegenerative disorder affecting speech motor planning/programming. Current interventions for PPAOS are limited and often adapted from treatments for nondegenerative AOS, which rely on intensive practice to maintain speech accuracy for practiced items. Systematic interventions for PPAOS are scarce, and no studies have explored differential effects across AOS subtypes. PPAOS subtypes include those with predominant phonetic (articulatory distortions and substitutions) or prosodic (slow speech rate, segmentation) speech changes. These subtypes likely differ in their neural underpinnings and may respond variably to intervention. Delayed auditory feedback (DAF), which introduces a slight delay in hearing one's speech, has shown promise in altering speech rate and fluency for stuttering and hypokinetic dysarthria, though its effects on stroke‐related AOS have been mixed. Recent studies suggest DAF can increase speech rate in patients with AOS in the context of nonfluent/agrammatic primary progressive aphasia. We hypothesized DAF would improve speech clarity and fluency in PPAOS, with subtype‐specific effects: phonetic PPAOS may see slower, more accurate speech, while prosodic PPAOS may produce faster, less segmented speech. Method Four PPAOS patients (3 prosodic, 1 phonetic) completed a web‐based speech battery with and without DAF. Feedback delay was calibrated individually using the DAF Pro app. Speech metrics were analyzed acoustically, and blinded perceptual ratings of deviant speech features were conducted. Results Key data are summarized in Table 1. Three out of four patients found the DAF helpful and two re‐recorded with DAF to allow for quantitative analysis. Patient 1 produced words faster with DAF but had slower total sentence production times; he did not find it helpful. Patient 2 spoke slower with DAF. Both patients produced AMRs faster with DAF, while SMRs were faster for Patient 1 and slower for Patient 2. Blinded perceptual judgments of speech clarity and prosody revealed mixed effects of DAF across participants. Conclusions Preliminary results suggest DAF may differentially benefit phonetic and prosodic PPAOS, particularly in sentences compared to word production. Further research is needed to assess clinical significance, refine DAF calibration, and explore patient‐perceived improvements with guided practice in a larger, more diverse sample.

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 Background Population aging is expected to increase the burden of Alzheimer's disease (AD) and related dementias (ADRD), yet up to 45% of ADRD risk may be modified. Disparities in ADRD burden among Hispanic/Latino and Black/African Americans suggests that socioeconomic deprivation and medical comorbidities may influence AD risk. The relationship between these factors, symptomatic age of onset, and neuropathologic findings in AD remains unclear. This study aims to investigate these associations in an ethnoracially diverse, neuropathologically diagnosed AD case series. Understanding these risk factors may help develop more effective AD risk reduction strategies. Method We queried the Florida Autopsied Multi‐Ethnic (FLAME) cohort database for neuropathologically‐diagnosed AD cases with available age onset of cognitive symptoms, who self‐identified as Hispanic/Latino ( n = 75) or Black/African American ( n = 22). Cases were matched to non‐Hispanic White decedents ( n = 101) by sex and year of birth. Medical records at the time of brain donation were retrospectively reviewed, assessing completeness for demographics, clinical characteristics, and medical comorbidities (Table 1). Result The table shows a comparative analysis stratified by young‐onset AD (YOAD, onset <65 years) and late‐onset AD (LOAD, onset ≥65 years). YOAD cases had a significantly higher level of education compared to LOAD ( p = 0.003). No differences were observed in sex , APOE ε4 carriership, or Area Deprivation Index between YOAD and LOAD. However, YOAD cases had a longer disease duration and were more likely to present with atypical clinical features compared to LOAD (both p <0.001). YOAD cases also showed a faster rate of decline on MMSE compared to LOAD ( p = 0.002), higher frequency of depression ( p = 0.018), and lower frequency of stroke/TIA ( p = 0.025). YOAD cases also had lower brain weight ( p = 0.041), less cerebrovascular disease burden ( p = 0.003) and higher neurofibrillary tangle density in association cortices ( p <0.001) compared to LOAD cases. Conclusion Socioeconomic deprivation and most medical comorbidities were not associated with AD symptomatic onset. Despite having higher education levels and lower cerebrovascular burden, YOAD decedents experienced faster cognitive decline but a longer disease course, with more frequent atypical clinical presentations and depression compared to LOAD. Further discussion will address the topographic distribution of tangle and plaque pathology.

Abstract Background Staging disease severity in dementia research requires input from an informant. The Clinical Dementia Rating Sum of Boxes (CDR) is the most used instrument for staging in Alzheimer's Disease (AD); but has been expanded to stage patients with frontotemporal lobar degeneration (FTLD) with the CDR PLUS NACC‐FTLD. An informant effect on the CDR has been reported in AD. The aim of this study is to evaluate whether informant characteristics influence the CDR PLUS NACC‐FTLD in a large cohort of participants with frontotemporal dementia (FTD). Method We included participants with a FTLD‐related syndrome from the ALLFTD study. We included participants with a CDR PLUS NACC‐FTLD higher than 0, information on the Montreal Cognitive Assessment (MoCA) scores, and the Neuropsychiatric Inventory Questionnaire (NPI‐Q). We performed a conditional growth model using multilevel linear regression analysis. We performed an exploratory stratified analysis by patient sex. Result We included 1411 participants, totalling 2063 visits. The patient's age at the initial visit was 64.7±9.4 years and 44.0% were females. Females were 69.2% of the informants, and the relationship was 79.1% spouse or partner, 10.6% children, 4.1% were siblings and 6.2% other. The CDR PLUS NACC‐FTLD scores were affected by informant characteristics. The CDR PLUS NACC‐FTLD scores were 0.41 (CI 95%:0.08 to 0.75) higher with female informants. The frequency of visits was associated with a CDR PLUS NACC‐FTLD score 0.86 higher (CI 95%:0.17 to 0.56) when visiting at least once a week, 1.46 higher (CI 95%:0.46 to 2.47) when visiting daily, and 0.83 higher (CI 95%:0.06 to 1.60) when living with the patient compared with visiting less than once a week. As expected, CDR‐FLTD scores increased with lower MoCA and higher NPI‐Q scores. In the stratified analysis by sex, we found that female informant was associated with higher CDR PLUS NACC‐FTLD scores only when patients were male. Conclusion We found that the CDR PLUS NACC‐FTLD is influenced by informant sex and frequency of visits in patients with FTLD‐related syndromes. These results are similar to those observed in AD patients and underscore the need to recognize that informant characteristics may impact dementia severity scales.

Abstract Background One of the hallmarks of Alzheimer's disease (AD) is the progressive spread of tau pathology. However, heterogeneity in the spatial patterns of tau deposition at the individual level may contribute to distinct clinical presentations. Here, we investigated the different patterns of tau deposition across disease progression and the different cognitive profiles linked to these patterns. Method We investigated 106 tau PET positive individuals (16% cognitively unimpaired, 84% amnestic cognitively impaired) from the HEAD study using head‐to‐head Flortaucipir and MK6240 tau PET. For each tracer, we extracted the SUVR values from seven major brain networks: Limbic, Visual (Vis), Default Mode (Default), Dorsal Attention (DorsAttn), Frontoparietal, Somatomotor (SomMot) and Salience Ventral Attention (SalVentAttn) as well as the Entorhinal cortex. Pathways were identified by ranking regions from highest to lowest SUVR, with the region displaying the highest SUVR value being defined as the peak region. Individuals in late stages of tau deposition displaying distinct pathways were compared. Image averages and voxel‐wise group comparisons using tau negative individuals as the reference were generated for each pathway and tau PET tracer. Cognitive differences were assessed using ANOVA for MoCA score and domain‐specific composite scores for Memory, Attention and Visuospatial skills. Result In all individuals and tracers, tau in the Entorhinal cortex progressed to the Limbic network, supporting a common starting point for tau propagation. Beyond these initial stages, tau propagation followed three main distinct pathways following either the Vis, Default or DorsAttn networks (Figure 1). Voxel‐wise comparison between individuals across these three pathways captured clear and similar differences in tau PET uptake as measured with Flortaucipir and MK6240. (Figure 2). While MoCA and Memory scores did not differ between groups, individuals following the Vis network exhibited significantly lower Attention scores compared to those in the Default and DorsAttn networks. Additionally, individuals following the Vis network exhibited lower Visuospatial scores compared to the Default network group (Figure 3). Conclusion Our results indicate a model in which, although tau progresses hierarchically, its deposition peaks mainly follow specific networks, which drive tau deposition and, consequently, the clinical manifestations of AD.

Abstract Neuroimaging can assess different pathophysiological features of the brain in Alzheimer's disease (AD), including structure, function and protein deposition, and can be used to help identify patients for clinical treatment trials and monitor and assess potential treatment effects on disease progression. While large scale longitudinal studies are underway to validate potential neuroimaging biomarkers in amnestic AD, less efforts have focused on atypical clinical presentations, such as language, visual, dysexecutive, behavioral and motor presentations of AD. These patients would be ideal candidates for treatment trials given that they are relatively young, and the disease is less influenced by age‐associated co‐pathologies, providing a purer disease model of AD. Rates of brain atrophy provide excellent surrogate disease markers in amnestic AD and they will also likely have utility in atypical AD, although cortical, rather than medial temporal, measurements perform better. Optimum sample size estimates required to detect a 20% treatment effect in both the language and visual variants of AD were obtained with rates of inferior temporal atrophy in our sample (113 and 100 patients required per arm, respectively). However, heterogeneity in rates and patterns of atrophy are observed across phenotypes, and with age and disease stage, and these factors would need to be considered in clinical trials. Utilizing direct markers of tau deposition from PET would be optimal. Tau uptake increases over time in relatively consistent patterns across atypical AD phenotypes, although rates vary across patients and with age and baseline levels, with tau uptake plateauing at high levels potentially limiting utility as an outcome measure in patients with advanced disease. Metrics of connectivity also worsen over time in atypical AD patients, with evidence that declines in default mode network connectivity may be common across phenotypes and have some utility, although once again changes are highly variable and influenced by age and tau burden. In summary, we are gaining a better understanding of factors that influence rates of change in atypical AD that need to be considered in treatment trials, although more work is needed to identify optimum biomarkers to track disease progression across the AD clinical spectrum.

Abstract Background The quantification of Neurofilament Light chain (NfL) in blood and cerebrospinal fluid (CSF) has proven valuable for diagnosing and prognosing various neurological disorders, including Alzheimer's disease, frontotemporal dementia, amyotrophic lateral sclerosis, parkinsonism, multiple sclerosis, and ischemic damage. However, there is considerable variability in clinical and laboratory practices between centers, primarily due to different contexts of use (COU), analytical methods, and the application of cutoffs or scales. Additionally, for the same biochemical profile, the interpretation and reporting of results may vary from one center to another, raising concerns about the commutability of the tests. To date, no consensus has been reached among laboratories to define the most appropriate use of cutoffs or conclusions/comments based on NfL profiles. Method This international project involves 38 laboratories across 18 countries, all specialized in the biochemical diagnosis of neurological disorders. Using a questionnaire, we obtained descriptions from each center regarding their COU, pre‐analytical and analytical protocols (including the biological fluid and methods used to quantify NfL). Through a consensus approach, we developed a harmonized strategy for the use and reporting of NfL results across different centres according to their respective COU. Results Among the centers, 63% quantified NfL in the CSF, 87% in blood and 53% in both fluids. COU were as follow: frontotemporal dementia (71%), Alzheimer disease (71%), multiple sclerosis (61%), amyotrophic lateral sclerosis (61%), psychiatric syndrome (45%), Creutzfeldt‐Jakob disease (32%), Parkinson disease (39%), peripheral neuropathy (29%), traumatic brain injury (21%), Huntington's disease (13%), amyloid transthyretin related (11%) and cardiac arrest (8%). Most of the centers define pathological cutoffs based on publications (50%) and take age into account for this purpose (42%). Reporting is mostly transmitted through numeric results (95%). Conclusion Harmonizing cutoffs, reporting, and interpretation across various clinical contexts will facilitate the incorporation of this biomarker into routine clinical practice.

Abstract Background Extracellular vesicles (EVs) are key mediators in transferring pathological proteins associated with Alzheimer's disease (AD). The apolipoprotein E (APOE) gene, particularly the ε4 allele, is a major genetic risk factor for late‐onset AD. However, the influence of APOE genotype on the biological characteristics and cargo composition of brain‐derived extracellular vesicles (BDEVs) in AD remains poorly understood. Method In this study, BDEVs were isolated from human AD temporal cortex with APOE3/3 and APOE4/4 genotypes ( N = 20 / group). Nanoflow cytometry and super‐resolution microscopy were used to evaluate the tau load within these BDEVs. EV‐mediated tau transmission was assessed in aged human Tau KI and APP NL‐G‐F : Tau KI mice in vivo . BDEV uptake and tau seeding were evaluated in iPSC‐derived neurons through live imaging. Additionally, shotgun lipidomics and data independent acquisition proteomics were analyzed lipidome and proteome of BDEVs, respectively. Key molecules linked to APOE genotype were identified through integrated weighted gene co‐expression network and trait correlation analysis. Result APOE4/4 BDEVs exhibited a higher proportion of phosphorylated tau (pS396) at single EV levels. Upon injection of 300pg tau of BDEVs into aged Tau KI and APP NL‐G‐F : Tau KI mice, APOE4/4 BDEVs significantly increased AT8 + phosphorylated tau levels, and induced neuroinflammation in vivo . Moreover, APOE4/4 BDEVs demonstrated stronger neuronal uptake and tau transfer compared to APOE3/3 BDEVs, impairing the neuronal activity of iPSC‐derived neurons. Lipidomic revealed that APOE4/4 BDEVs were significantly more enriched in pro‐inflammatory long‐chain polyunsaturated fatty acids (PUFA) compared to APOE3/3 with Braak stage association. Furthermore, gene ontology pathway analysis using differentially expressed proteins in APOE4/4 BDEVs showed increased activity in oxidative phosphorylation and sterol‐binding. Multi‐omics integrated data revealed that upregulation of PUFA was significantly associated with elevated cell adhesion molecules and ATPase transporter activity with neural cell adhesion molecule as one of key molecule. Notably, neutralizing antibody against the molecule effectively reduced APOE4/4 BDEV internalization and mitigated EV‐mediated tau pathology in recipient cells. Conclusion Our comprehensive analysis suggested that AD APOE4/4 BDEV may enhance transmissibility of tau pathology and neuroinflammation via enriched pro‐inflammatory PUFA and cell adhesion molecules. Targeting these pathways presents a promising therapeutic strategy to mitigate disease progression, particularly in APOE4 individuals.

Abstract Background Dynamically predicting patients at risk of Alzheimer's disease (AD) is crucial for timely treatment and care in precision medicine. Method We present a novel architecture, a Kolmogorov‐Arnold networks (KANs)‐based joint prediction model of longitudinal and survival data (JM‐KAN). Real‐life data of patients with Mild Cognitive Impairment (MCI) with no prior AD diagnosis from National Alzheimer's Coordinating Center (NACC) dataset was utilized for individualized predictions. We built joint models with landmark times every 1 year up to 4 years after the MCI diagnosis, and predicted survival outcomes one year after each landmark (i.e. 1, 2, 3, and 4 years). Integrated AUC (iAUC), and integrated Brier score (iBS) were measured for existing prediction models and our novel architecture. Result Out of 2711 unique patients with MCI, 821 patients progressed to develop AD. Mean time‐to‐event in years was 3.19 (standard deviation (SD): 2.29). The number of visits prior to AD diagnosis was 4.03 (SD: 2.41). With iAUC of 0.789, iBS of 0.118, JM‐KAN has both the highest iAUC and lowest iBS among joint models, which indicates superiority in discrimination and overall performance. For individualized predictions, the model successfully predicted both longitudinal risk factors and survival probability, as new information came in every year. Conclusion Using neural network‐based Artificial Intelligence (AI) model, we demonstrated that this architecture improves upon prior methods in dynamically updating predictions of AD as new longitudinal data becomes available.