Browsing by Author "Apostolova, Liana G."
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Item A harmonized memory composite score for cross‐cohort Alzheimer’s disease and related dementia research: development and validation(Wiley, 2025-01-03) Sanderson-Cimino, Mark E.; Gross, Alden L.; Gaynor, Leslie S.; Paolillo, Emily W.; Casaletto, Kaitlin B.; Chatterjee, Ankita; Albert, Marilyn S.; Apostolova, Liana G.; Boersema, Brooke; Boxer, Adam L.; Boeve, Brad F.; Clark, Lindsay R.; La Joie, Renaud; Eloyan, Ani; Tomaszewski Farias, Sarah; Gonzales, Mitzi M.; Hammers, Dustin B.; Wise, Amy B.; Cobigo, Yann; Yballa, Claire; Schonhaut, Daniel R.; Hampstead, Benjamin M.; Mechanic-Hamilton, Dawn; Miller, Bruce L.; Rabinovici, Gil D.; Rascovsky, Katya; Ringman, John M.; Rosen, Howard J.; Ryman, Sephira; Salmon, David P.; Smith, Glenn E.; Decarli, Charles; Kramer, Joel H.; Staffaroni, Adam M.; Neurology, School of MedicineBackground: The Uniform Data Set (UDS) neuropsychological battery, administered across Alzheimer’s Disease Centers (ADC), includes memory tests but lacks a list‐learning paradigm. ADCs often supplement the UDS with their own preferred list‐learning task. Given the importance of list‐learning for characterizing memory, we aimed to develop a harmonized memory score that incorporates UDS memory tests while allowing centers to contribute differing list‐learning tasks. Method: We applied item‐banking confirmatory factor analysis to develop a composite memory score in 5,287 participants (mean age 67.1; SD = 12.2) recruited through 18 ADCs and four consortia (DiverseVCID, MarkVCID, ALLFTD, LEADS) who completed UDS memory tasks (used as linking‐items) and one of five list‐learning tasks. All analyses used linear regression. We tested whether memory scores were affected by which list‐learning task was administered. To assess construct validity, we tested associations of memory scores with demographics, disease severity (CDR Box Score), an independent memory task (TabCAT Favorites, n = 675), and hippocampal volume (n = 811). We compared performances between cognitively unimpaired (n = 279), AD‐biomarker+ MCI (n = 26), and AD‐biomarker+ dementia (n = 98). In a subsample with amyloid‐ and tau‐PET (n = 49), we compared memory scores from participants with positive vs negative scans determined using established quantitative cutoffs. Result: Model fit indices were excellent (e.g., CFI = 0.998) and factor loadings were strong (0.43‐0.93). Differences in list‐learning task had a negligible effect on scores (average Cohen’s d = 0.11). Higher memory scores were significantly (p’s<.001) correlated with younger age (β = ‐0.18), lower CDR Box Scores (β = ‐0.63), female sex (β = 0.12), higher education (β = 0.19), larger hippocampal volume (β = 0.42), and an independent memory task (β = 0.71, p<0.001). The memory composite declined in a stepwise fashion by diagnosis (cognitively unimpaired>MCI>AD dementia, p<0.001). On average, amyloid‐PET positivity was associated with lower composite scores, but was not statistically significant (β = ‐0.34; p = 0.25; d = 0.40). Tau‐PET positivity was associated with worse performance, demonstrating a large effect size (β = ‐0.75; p<0.002; d = 0.91). Conclusion: The harmonized memory score developed in a large national sample was stable regardless of contributing list‐learning task and its validity for cross‐cohort ADRD research is supported by expected associations with demographics, clinical measures, and Alzheimer’s biomarkers. A processing script will be made available to enhance cross‐cohort ADRD research.Item A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer’s disease risk and rates of disease progression(Wiley, 2023) Bae, Jinhyeong; Logan, Paige E.; Acri, Dominic J.; Bharthur, Apoorva; Nho, Kwangsik; Saykin, Andrew J.; Risacher, Shannon L.; Nudelman, Kelly; Polsinelli, Angelina J.; Pentchev, Valentin; Kim, Jungsu; Hammers, Dustin B.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of MedicineBackground: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies. Methods: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed. Results: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression. Discussion: The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.Item Adverse Social Exposome by Area Deprivation Index (ADI) and Alzheimer’s Disease and Related Dementias (ADRD) Neuropathology for a National Cohort of Brain Donors within the Neighborhoods Study(Wiley, 2025-01-09) Kind, Amy J. H.; Bendlin, Barbara B.; Keller, Sarah A.; Powell, W. Ryan; DeWitt, Amanda; Cheng, Yixuan; Chamberlain, Luke; Lyons Boone, Brittney; Miller, Megan J.; Vik, Stacie M.; Abner, Erin L.; Alosco, Michael L.; Apostolova, Liana G.; Bakulski, Kelly M.; Barnes, Lisa L.; Bateman, James R.; Beach, Thomas G.; Bennett, David A.; Brewer, James B.; Carrion, Carmen; Chodosh, Joshua; Craft, Suzanne; Croff, Raina; Fabio, Anthony; Tomaszewski Farias, Sarah; Goldstein, Felicia; Henderson, Victor W.; Karikari, Thomas; Kofler, Julia; Kucharska-Newton, Anna M.; Lamar, Melissa; Lanata, Serggio; Lepping, Rebecca J.; Lingler, Jennifer H.; Lockhart, Samuel N.; Mahnken, Jonathan D.; Marsh, Karyn; Meyer, Oanh L.; Miller, Bruce L.; Morris, Jill K.; Neugroschl, Judith A.; O'Connor, Maureen K.; Paulson, Henry L.; Perrin, Richard J.; Pierce, Aimee; Raji, Cyrus A.; Reiman, Eric M.; Risacher, Shannon L.; Rissman, Robert A.; Rodriguez Espinoza, Patricia; Sano, Mary; Saykin, Andrew J.; Serrano, Geidy E.; Sultzer, David L.; Whitmer, Rachel A.; Wisniewski, Thomas; Woltjer, Randall; Zhu, Carolyn W.; Neurology, School of MedicineBackground: Adverse social exposome (indexed by high national Area Deprivation Index [ADI]) is linked to structural inequities and increased risk of clinical dementia diagnosis, yet linkage to ADRD neuropathology remains largely unknown. Early work from single site brain banks suggests a relationship, but assessment in large national cohorts is needed to increase generalizability and depth, particularly for rarer neuropathology findings. Objective: Determine the association between adverse social exposome by ADI and ADRD neuropathology for brain donors from 21 Alzheimer’s Disease Research Center (ADRC) brain banks as part of the on‐going Neighborhoods Study. Methods: All brain donors in participating sites with neuropathology data deposited at the National Alzheimer’s Coordinating Center (NACC) and identifiers for ADI linkage (N = 8,637; Figure 1) were included. Geocoded donor addresses were linked to time‐concordant national ADI percentiles for year of death, categorized into standard groupings of low (ADI 1‐19), medium (20‐49) and high (50‐100) ADI. Neuropathological findings were drawn from NACC and reflected standard assessment practices at time of donation. Logistic regression models, adjusted for sex and age at death, assessed relationships between high ADI and neuropathology findings. Results: Of the N = 8,637 brain donors (Table 1), 2,071 of 2,366 assessed (88%) had AD pathology by NIA‐AA criteria; 4,197 of 6,929 assessed (61%) had cerebral amyloid angiopathy; 2582 of 8092 assessed (32%) had Lewy body pathology; 391 of 2351 assessed (17%) had non‐AD tauopathy; and 586 of 1680 assessed (35%) had TDP‐43 pathology. 2,126(25%) were high ADI; 3,171(37%) medium ADI and 3,340(38%) low ADI with 51% female and average age at death of 81.9 years. As compared to low ADI donors, high ADI brain donors had adjusted odds = 1.35 (95% CI = 0.98‐1.86, p‐value = 0.06) for AD pathology; 1.10 (0.98–1.25, p = 0.11) for cerebral amyloid angiopathy; 1.37 (1.21–1.55, p<0.01) for Lewy body; 1.09 (0.83–1.44, p = 0.53) for non‐AD tauopathy; and 1.40 (1.08‐1.81, p = 0.01) for TDP‐43 pathology (Table 2). Conclusions: This first‐in‐field study provides evidence that the adverse social exposome (high ADI) is strongly associated with an increased risk of Lewy body, an increased risk of TDP‐43, and a trend towards increased AD pathology in a national cohort of brain donors.Item Altered Cerebral Blood Flow in Older Adults with Alzheimer’s Disease: A Systematic Review(Springer, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Wu, Yu-Chien; Apostolova, Liana G.; Gao, Sujuan; Bice, Paula J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineThe prevalence of Alzheimer’s disease is projected to reach 13 million in the U.S. by 2050. Although major efforts have been made to avoid this outcome, so far there are no treatments that can stop or reverse the progressive cognitive decline that defines Alzheimer’s disease. The utilization of preventative treatment before significant cognitive decline has occurred may ultimately be the solution, necessitating a reliable biomarker of preclinical/prodromal disease stages to determine which older adults are most at risk. Quantitative cerebral blood flow is a promising potential early biomarker for Alzheimer’s disease, but the spatiotemporal patterns of altered cerebral blood flow in Alzheimer’s disease are not fully understood. The current systematic review compiles the findings of 81 original studies that compared resting gray matter cerebral blood flow in older adults with mild cognitive impairment or Alzheimer’s disease and that of cognitively normal older adults and/or assessed the relationship between cerebral blood flow and objective cognitive function. Individuals with Alzheimer’s disease had relatively decreased cerebral blood flow in all brain regions investigated, especially the temporoparietal and posterior cingulate, while individuals with mild cognitive impairment had consistent results of decreased cerebral blood flow in the posterior cingulate but more mixed results in other regions, especially the frontal lobe. Most papers reported a positive correlation between regional cerebral blood flow and cognitive function. This review highlights the need for more studies assessing cerebral blood flow changes both spatially and temporally over the course of Alzheimer’s disease, as well as the importance of including potential confounding factors in these analyses.Item Alzheimer Disease(Wolters Kluwer, 2016-04) Apostolova, Liana G.; Neurology, School of MedicinePURPOSE OF REVIEW: This article discusses the recent advances in the diagnosis and treatment of Alzheimer disease (AD). RECENT FINDINGS: In recent years, significant advances have been made in the fields of genetics, neuroimaging, clinical diagnosis, and staging of AD. One of the most important recent advances in AD is our ability to visualize amyloid pathology in the living human brain. The newly revised criteria for diagnosis of AD dementia embrace the use for biomarkers as supportive evidence for the underlying pathology. Guidelines for the responsible use of amyloid positron emission tomography (PET) have been developed, and the clinical and economic implications of amyloid PET imaging are actively being explored. SUMMARY: Our improved understanding of the clinical onset, progression, neuroimaging, pathologic features, genetics, and other risk factors for AD impacts the approaches to clinical diagnosis and future therapeutic interventions.Item Alzheimer’s Disease Polygenic Risk in the LEADS Cohort(Wiley, 2025-01-03) Nudelman, Kelly N.; Pentchev, Julian V.; Jackson, Trever; Eloyan, Ani; Dage, Jeffrey L.; Foroud, Tatiana M.; Hammers, Dustin B.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium; Medical and Molecular Genetics, School of MedicineBackground: Currently, it is unclear to what extent late‐onset Alzheimer’s disease (AD) risk variants contribute to early‐onset AD (EOAD). One method to clarify the contribution of late‐onset AD genetic risk to EOAD is to investigate the association of AD polygenic risk scores (PRS) with EOAD. We hypothesize that in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), EOAD participants will have greater PRS than early‐onset amyloid‐negative cognitively‐impaired participants (EOnonAD) and controls, and investigate the association of AD PRS with age of disease onset (AoO) and cognitive performance. Methods: GWAS data was generated for LEADS participants, including those with EOAD, EOnonAD, and controls, with the Illumina Global Screening Array. A PRS was calculated using the 31 SNPs and weights published previously by Desikan et al. (2017) for LEADS participants with imputed GWAS data (N = 369). Logistic regression models including age, sex, PRS, and genetic ancestry principal components were tested to identify predictors of EOAD (N = 210) vs. EOnonAD (N = 69) and controls (N = 89). ANCOVA models were used to assess group differences in PRS scores. Kaplan‐Meier regression was used to assess differences in EOAD AoO for tertile‐binned PRS groups. Within EOAD, pre‐calculated cognitive domain scores for speed and attention, working memory, episodic memory, language, and visuospatial performance were assessed for correlation with PRS. Results: The AD PRS was a predictor of EOAD (p = 0.014), with the model explaining 10.5% of variance (X2 = 40.971, p<0.001). EOAD participants had higher PRS scores (mean = 0.0012, standard deviation (SD) = 0.015) compared to EOnonAD and controls (mean = ‐0.0018, SD = 0.015) (F = 6.602, p = 0.011). Survival analysis indicated no significant differences in EOAD AoO between PRS groups (X2 = 3.396, p = 0.183). In the EOAD group, PRS was associated with cognitive scores for speed and attention (r = 0.204, p = 0.007), language (r = 0.230, p = 0.002), and visuospatial performance (r = 0.166, p = 0.037). Conclusions: In the LEADS cohort, AD PRS is a predictor for EOAD, and is associated with cognitive performance, but does not predict EOAD AoO. This suggests that while late onset AD‐associated genetic variants contribute to disease risk and processes, they do not account for a large portion of disease risk, and do not explain differences in disease AoO in the LEADS cohort.Item Amyloid and Tau Pathology are Associated with Cerebral Blood Flow in a Mixed Sample of Nondemented Older Adults with and without Vascular Risk Factors for Alzheimer’s Disease(Elsevier, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Vosmeier, Aaron; Deardorff, Rachael; Chumin, Evgeny J.; Dzemidzic, Mario; Wu, Yu-Chien; Gao, Sujuan; McDonald, Brenna C.; Yoder, Karmen K.; Unverzagt, Frederick W.; Wang, Sophia; Farlow, Martin R.; Brosch, Jared R.; Clark, David G.; Apostolova, Liana G.; Sims, Justin; Wang, Danny J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineIdentification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.Item Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS)(Wiley, 2023) Cho, Hanna; Mundada, Nidhi S.; Apostolova, Liana G.; Carrillo, Maria C.; Shankar, Ranjani; Amuiri, Alinda N.; Zeltzer, Ehud; Windon, Charles C.; Soleimani-Meigooni, David N.; Tanner, Jeremy A.; Heath, Courtney Lawhn; Lesman-Segev, Orit H.; Aisen, Paul; Eloyan, Ani; Lee, Hye Sun; Hammers, Dustin B.; Kirby, Kala; Dage, Jeffrey L.; Fagan, Anne; Foroud, Tatiana; Grinberg, Lea T.; Jack, Clifford R.; Kramer, Joel; Kukull, Walter A.; Murray, Melissa E.; Nudelman, Kelly; Toga, Arthur; Vemuri, Prashanthi; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph; Mendez, Mario; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily J.; Salloway, Stephen; Sha, Sharon; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Koeppe, Robert; Iaccarino, Leonardo; Dickerson, Bradford C.; La Joie, Renaud; Rabinovici, Gil D.; LEADS Consortium; Neurology, School of MedicineIntroduction: We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). Methods: We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. Results: 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. Discussion: LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. Highlights: 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.Item Amyloid-related imaging abnormalities (ARIA): radiological, biological and clinical characteristics(Oxford University Press, 2023) Hampel, Harald; Elhage, Aya; Cho, Min; Apostolova, Liana G.; Nicoll, James A. R.; Atri, Alireza; Neurology, School of MedicineExcess accumulation and aggregation of toxic soluble and insoluble amyloid-β species in the brain are a major hallmark of Alzheimer's disease. Randomized clinical trials show reduced brain amyloid-β deposits using monoclonal antibodies that target amyloid-β and have identified MRI signal abnormalities called amyloid-related imaging abnormalities (ARIA) as possible spontaneous or treatment-related adverse events. This review provides a comprehensive state-of-the-art conceptual review of radiological features, clinical detection and classification challenges, pathophysiology, underlying biological mechanism(s) and risk factors/predictors associated with ARIA. We summarize the existing literature and current lines of evidence with ARIA-oedema/effusion (ARIA-E) and ARIA-haemosiderosis/microhaemorrhages (ARIA-H) seen across anti-amyloid clinical trials and therapeutic development. Both forms of ARIA may occur, often early, during anti-amyloid-β monoclonal antibody treatment. Across randomized controlled trials, most ARIA cases were asymptomatic. Symptomatic ARIA-E cases often occurred at higher doses and resolved within 3-4 months or upon treatment cessation. Apolipoprotein E haplotype and treatment dosage are major risk factors for ARIA-E and ARIA-H. Presence of any microhaemorrhage on baseline MRI increases the risk of ARIA. ARIA shares many clinical, biological and pathophysiological features with Alzheimer's disease and cerebral amyloid angiopathy. There is a great need to conceptually link the evident synergistic interplay associated with such underlying conditions to allow clinicians and researchers to further understand, deliberate and investigate on the combined effects of these multiple pathophysiological processes. Moreover, this review article aims to better assist clinicians in detection (either observed via symptoms or visually on MRI), management based on appropriate use recommendations, and general preparedness and awareness when ARIA are observed as well as researchers in the fundamental understanding of the various antibodies in development and their associated risks of ARIA. To facilitate ARIA detection in clinical trials and clinical practice, we recommend the implementation of standardized MRI protocols and rigorous reporting standards. With the availability of approved amyloid-β therapies in the clinic, standardized and rigorous clinical and radiological monitoring and management protocols are required to effectively detect, monitor, and manage ARIA in real-world clinical settings.Item Amyloid‐PET in patients with a clinical diagnosis of sporadic early‐ versus late‐onset AD: comparison of the LEADS and ADNI cohorts(Wiley, 2025-01-09) Lagarde, Julien; Maiti, Piyush; Schonhaut, Daniel R.; Zhang, Jiaxiuxiu; Soleimani-meigooni, David N.; Zeltzer, Ehud; Windon, Charles; Raya, Maison Abu; Vrillon, Agathe; Hammers, Dustin B.; Dage, Jeffrey L.; Nudelman, Kelly N.; Eloyan, Ani; Koeppe, Robert A.; Landau, Susan M.; Carrillo, Maria C.; Touroutoglou, Alexandra; Vemuri, Prashanthi; Dickerson, Bradford C.; Apostolova, Liana G.; Rabinovici, Gil D.; La Joie, Renaud; LEADS Consortium, Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of MedicineBackground: Large‐scale studies comparing sporadic early‐onset AD (EOAD, age<65) and late‐onset AD (LOAD, age≥65) are lacking. We compared amyloid‐PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early‐Onset AD Study (LEADS) and the Alzheimer’s Disease Neuroimaging Initiative 3 (ADNI3). Method: 731 patients meeting the 2011 NIA‐AA criteria for AD dementia or MCI were included (505 early‐onset from LEADS, 226 late‐onset from ADNI3, Table 1). All participants underwent amyloid‐PET with [18F]Florbetaben or [18F]Florbetapir. Amyloid positivity was centrally determined by a process involving a visual read by a trained expert and PET‐only quantification; in case of a discrepancy, a read from an independent physician acted as a tiebreaker. Logistic regressions in each cohort examined relations between amyloid positivity and age, sex, MMSE and APOE4 genotype. Amyloid burden was independently quantified in Centiloids using an MRI‐based pipeline. Mean Centiloids in LEADS and ADNI were compared with two‐way ANOVA, for visually positive and visually negative scans. Result: Amyloid positivity rate was higher in LEADS (76%) than ADNI (64%, p<0.001, Figure 1A). Lower MMSE and APOE4 genotype increased odds of amyloid positivity in both cohorts, although the APOE4 effect was stronger in ADNI than LEADS (OR=10.1 versus 2.4, p=0.007, Table 2). Amyloid positivity was more common in females across cohorts, but this effect was only statistically significant in LEADS (Table 2). Centiloids were bimodally distributed in both cohorts, although the separation between positive and negative scans was more prominent in LEADS (Figure 1B). Visually positive scans had significantly higher Centiloids in LEADS than in ADNI, whereas no cohort difference was observed for visually negative scans (Figure 1C). Sensitivity analyses showed that this effect was driven by patients with MCI (CDR≤0.5; Figure 1D‐E). Conclusion: The lower amyloid positivity rate in ADNI might be due to AD‐mimicking pathologies being more common at an older age. The higher amyloid burden in early‐onset, amyloid‐positive patients could reflect younger patients being diagnosed later in the disease course compared to typical, late‐onset patients. Alternatively, younger patients might tolerate higher neuropathology burden due to higher brain reserve or fewer co‐pathologies.