Browsing by Author "Mormino, Elizabeth"
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Item Combined neuropathological pathways account for age-related risk of dementia(Wiley, 2018-07) Power, Melinda C.; Mormino, Elizabeth; Soldan, Anja; James, Bryan D.; Yu, Lei; Armstrong, Nicole M.; Bangen, Katherine J.; Delano-Wood, Lisa; Lamar, Melissa; Lim, Yen Ying; Nudelman, Kelly; Zahodne, Laura; Gross, Alden L.; Mungas, Dan; Widaman, Keith F.; Schneider, Julie; Radiology and Imaging Sciences, School of MedicineOBJECTIVE: Our objectives were to characterize the inter-relation of known dementia-related neuropathologies in one comprehensive model and quantify the extent to which accumulation of neuropathologies accounts for the association between age and dementia. METHODS: We used data from 1,362 autopsied participants of three community-based clinicopathological cohorts: the Religious Orders Study, the Rush Memory and Aging Project, and the Minority Aging Research Study. We estimated a series of structural equation models summarizing a priori hypothesized neuropathological pathways between age and dementia risk individually and collectively. RESULTS: At time of death (mean age, 89 years), 44% of our sample had a clinical dementia diagnosis. When considered individually, our vascular, amyloid/tau, neocortical Lewy body, and TAR DNA-binding protein 43 (TDP-43)/hippocampal sclerosis pathology pathways each accounted for a substantial proportion of the association between age and dementia. When considered collectively, the four pathways fully accounted for all variance in dementia risk previously attributable to age. Pathways involving amyloid/tau, neocortical Lewy bodies, and TDP-43/hippocampal sclerosis were interdependent, attributable to the importance of amyloid beta plaques in all three. The importance of the pathways varied, with the vascular pathway accounting for 32% of the association between age and dementia, wheraes the remaining three inter-related degenerative pathways together accounted for 68% (amyloid/tau, 24%; the Lewy body, 1%; and TDP-43/hippocampal sclerosis, 43%). INTERPRETATION: Age-related increases in dementia risk can be attributed to accumulation of multiple pathologies, each of which contributes to dementia risk. Multipronged approaches may be necessary if we are to develop effective therapies.Item CYP1B1-RMDN2 Alzheimer's disease endophenotype locus identified for cerebral tau PET(Springer Nature, 2024-09-20) Nho, Kwangsik; Risacher, Shannon L.; Apostolova, Liana G.; Bice, Paula J.; Brosch, Jared R.; Deardorff, Rachael; Faber, Kelley; Farlow, Martin R.; Foroud, Tatiana; Gao, Sujuan; Rosewood, Thea; Kim, Jun Pyo; Nudelman, Kelly; Yu, Meichen; Aisen, Paul; Sperling, Reisa; Hooli, Basavaraj; Shcherbinin, Sergey; Svaldi, Diana; Jack, Clifford R., Jr.; Jagust, William J.; Landau, Susan; Vasanthakumar, Aparna; Waring, Jeffrey F.; Doré, Vincent; Laws, Simon M.; Masters, Colin L.; Porter, Tenielle; Rowe, Christopher C.; Villemagne, Victor L.; Dumitrescu, Logan; Hohman, Timothy J.; Libby, Julia B.; Mormino, Elizabeth; Buckley, Rachel F.; Johnson, Keith; Yang, Hyun-Sik; Petersen, Ronald C.; Ramanan, Vijay K.; Ertekin-Taner, Nilüfer; Vemuri, Prashanthi; Cohen, Ann D.; Fan, Kang-Hsien; Kamboh, M. Ilyas; Lopez, Oscar L.; Bennett, David A.; Ali, Muhammad; Benzinger, Tammie; Cruchaga, Carlos; Hobbs, Diana; De Jager, Philip L.; Fujita, Masashi; Jadhav, Vaishnavi; Lamb, Bruce T.; Tsai, Andy P.; Castanho, Isabel; Mill, Jonathan; Weiner, Michael W.; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Department of Defense Alzheimer’s Disease Neuroimaging Initiative (DoD-ADNI); Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Study (A4 Study) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN); Australian Imaging, Biomarker & Lifestyle Study (AIBL); Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineDetermining the genetic architecture of Alzheimer's disease pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we perform a genome-wide association study of cortical tau quantified by positron emission tomography in 3046 participants from 12 independent studies. The CYP1B1-RMDN2 locus is associated with tau deposition. The most significant signal is at rs2113389, explaining 4.3% of the variation in cortical tau, while APOE4 rs429358 accounts for 3.6%. rs2113389 is associated with higher tau and faster cognitive decline. Additive effects, but no interactions, are observed between rs2113389 and diagnosis, APOE4, and amyloid beta positivity. CYP1B1 expression is upregulated in AD. rs2113389 is associated with higher CYP1B1 expression and methylation levels. Mouse model studies provide additional functional evidence for a relationship between CYP1B1 and tau deposition but not amyloid beta. These results provide insight into the genetic basis of cerebral tau deposition and support novel pathways for therapeutic development in AD.Item Genetic and Sex Associations with Earlier Estimated Onset of Amyloid Positivity from over 4000 Harmonized Positron Emission Tomography Images(Wiley, 2025-01-09) Castellano, Tonnar; Wang, Ting Chen; Nolan, Emma; Archer, Derek B.; Cody, Karly; Harrison, Theresa M.; Wu, Yiyang; Durant, Alaina; Janve, Vaibhav A.; Engelman, Corinne D.; Jagust, William J.; Albert, Marilyn S.; Johnson, Sterling C.; Resnick, Susan M.; Sperling, Reisa A.; Bilgel, Murat; Saykin, Andrew J.; Vardarajan, Badri N.; Mayeux, Richard; Betthauser, Tobey J.; Dumitrescu, Logan C.; Mormino, Elizabeth; Hohman, Timothy J.; Koran, Mary Ellen I.; Radiology and Imaging Sciences, School of MedicineBackground: New techniques have been developed to estimate the age when someone converted to amyloid positivity (EAOA) from PET, oftentimes offering information about a participant decades before they joined a research study. EAOA is variable across populations but we do not know the causes for these differences. This study aims to validate APOE associations with EAOA and explore genetic and sex‐based factors with EAOA. Methods: Data from six cohorts were analyzed. Our analysis included 4220 non‐Hispanic white people (57.6% women; 86.7% cognitively unimpaired at baseline scan). Amyloid PET data were harmonized using gaussian mixture models. EAOA was calculated using the sampled iterative local approximation (SILA) algorithm. Sex differences in EAOA were compared using t‐tests amongst amyloid positive individuals. A genome‐wide association study of EAOA was performed. Gene analyses were conducted using MAGMA. Results: Average EAOA was 81.1 years across all individuals regardless of amyloid status. APOE e2 homozygotes had slightly later EAOA than e3/e3 homozygotes. APOE e4 homozygotes converted to amyloid positivity 8.2 years before e3/e4 heterozygotes and over two decades earlier than e3 homozygotes. APOE e2/e4 converted to positivity roughly three years later than e3/e4 and nearly ten years earlier than e3 homozygotes. APOE genotype differences in EAOA described were statistically significant (p < .01). There were significant sex differences between men and women when examining amyloid positivity. Men converted to amyloid positivity over 2 years later than women (65.3 vs 63.2 years, p=3.23x10‐5). The rs12981369 polymorphism in ABCA7 was associated with EAOA (β = 2.14, p=9.27×10−9). Brain eQTL databases indicate associations between rs12981369 and gene expression of ABCA7. Gene‐level analyses revealed significant associations for ABCA7, HMHA1, and KIF13B. Conclusion: This study further describes the role of APOE and reveals roles for ABCA7 and KIF13B on amyloid onset. We identified a novel variant on chromosome 19 correlating with later amyloid onset conversion and highlight important differences between sexes. These findings highlight EAOA as a powerful endophenotype of AD and offer insights into potential drug‐targetable mechanisms for early AD intervention.Item Genetic variants and functional pathways associated with resilience to Alzheimer’s disease(Oxford, 2020-08-25) Dumitrescu, Logan; Mahoney, Emily R; Mukherjee, Shubhabrata; Lee, Michael L; Bush, William S; Engelman, Corinne D; Lu, Qiongshi; Fardo, David W; Trittschuh, Emily H; Mez, Jesse; Kaczorowski, Catherine; Hernandez Saucedo, Hector; Widaman, Keith F; Buckley, Rachel; Properzi, Michael; Mormino, Elizabeth; Yang, Hyun-Sik; Harrison, Tessa; Hedden, Trey; Nho, Kwangsik; Andrews, Shea J; Tommet, Doug; Hadad, Niran; Sanders, R Elizabeth; Ruderfer, Douglas M; Gifford, Katherine A; Moore, Annah M; Cambronero, Francis; Zhong, Xiaoyuan; Raghavan, Neha S.; Vardarajan, Badri; Pericak-Vance, Margaret A.; Farrer, Lindsay A.; Wang, Li-San; Cruchaga, Carlos; Schellenberg, Gerard; Cox, Nancy J.; Haines, Jonathan L,; Keene, C. Dirk; Saykin, Andrew J.; Larson, Eric B.; Sperling, Reisa A.; Mayeux, Richard; Bennett, David A.; Schneider, Julie A.; Crane, Paul K.; Jefferson, Angela L.; Hohman, Timothy J.; Radiology and Imaging Sciences, School of MedicineApproximately 30% of older adults exhibit the neuropathological features of Alzheimer’s disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer’s disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10−20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10−4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer’s disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10−8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10−13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer’s disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.Item Novel rare variant associations with late‐life cognitive performance(Wiley, 2025-01-09) Regelson, Alexandra N.; Archer, Derek B.; Durant, Alaina; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse; Bush, William S.; Kuzma, Amanda B.; Cuccaro, Michael L.; Cruchaga, Carlos; Farrer, Lindsay A.; Wang, Li-San; Schellenberg, Gerard D.; Mayeux, Richard; Kukull, Walter A.; Keene, C. Dirk; Saykin, Andrew J.; Johnson, Sterling C.; Engelman, Corinne D.; Bennett, David A.; Barnes, Lisa L.; Larson, Eric B.; Nho, Kwangsik; Goate, Alison M.; Renton, Alan E.; Marcora, Edoardo; Fulton-Howard, Brian; Patel, Tulsi; Risacher, Shannon L.; DeStefano, Anita L.; Schneider, Julie A.; Habes, Mohamad; Seshadri, Sudha; Satizabal, Claudia L.; Maillard, Pauline; Toga, Arthur W.; Crawford, Karen; Tosun, Duygu; Vance, Jeffery M.; Mormino, Elizabeth; DeCarli, Charles S.; Montine, Thomas J.; Beecham, Gary; Biber, Sarah A.; De Jager, Philip L.; Vardarajan, Badri N.; Lee, Annie J.; Brickman, Adam M.; Reitz, Christiane; Manly, Jennifer J.; Lu, Qiongshi; Rentería, Miguel Arce; Deming, Yuetiva; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Crane, Paul K.; Hohman, Timothy J.; Dumitrescu, Logan C.; Medical and Molecular Genetics, School of MedicineBackground: Despite evidence that Alzheimer’s disease (AD) is highly heritable, there remains substantial “missing” heritability, likely due in part to the effect of rare variants and to the past reliance on case‐control analysis. Here, we leverage powerful endophenotypes of AD (cognitive performance across multiple cognitive domains) in a rare variant analysis to identify novel genetic drivers of cognition in aging and disease. Method: We leveraged 8 cohorts of cognitive aging with whole genome sequencing data from the AD Sequencing Project to conduct rare variant analyses of multiple domains of cognition (N = 9,317; mean age = 73; 56% female; 52% cognitively unimpaired). Harmonized scores for memory, executive function, and language were derived using confirmatory factor analysis models. Participants genetically similar to the 1000Genomes EUR reference panel were included in analysis. Variants included in the analysis had a minor allele frequency < 0.01, a minor allele count of ≥ 10, and were annotated as a high or moderate impact SNP using VEP. Associations of baseline scores in each cognitive domain were performed using SKAT‐O, including 92,905 rare variants among 16,243 genes. All tests were adjusted for sex, baseline age, sequencing center and platform, and genetic principal components. Correction for multiple comparisons was completed using the Benjamini‐Hochberg false discovery rate (FDR) procedure. Result: APOE was associated with baseline memory, language, and executive function, though only memory survived multiple‐test correction (p.FDR = 0.001). Outside of APOE, ITPKB was associated with baseline executive function (p.FDR = 0.048). AKTIP, SHCBP1L, and CCNF showed nominal associations with multiple domains of cognition that did not survive correction for multiple comparisons (p.FDRs<0.07). Conclusion: These results highlight novel rare variants associated with cognition. IPTKB is an AGORA nominated gene target for potential AD treatment. It is important in the regulation of immune cells and displays higher expression in the cortex of AD patients compared to controls. CCNF and AKTIP are brain eQTLs and have differential RNA expression in AD brains. Previously, variants in AKTIP have been associated with educational attainment, intelligence, and memory, while variants in CCNF have been associated with neuritic plaques and neurofibrillary tangles. Future analyses will incorporate longitudinal cognition and expand into additional populations.Item Patterns of Tau Deposition by Cognitive Subtype in the Alzheimer's Disease Neuroimaging Initiative(Wiley, 2025-01-09) Scollard, Phoebe; Gibbons, Laura E.; Choi, Seo-Eun; Lee, Michael L.; Klinedinst, Brandon S.; Trittschuh, Emily H.; Mez, Jesse; Saykin, Andrew J.; Nakano, Connie; Sanders, Elizabeth; Lila, Eardi; Risacher, Shannon L.; Mormino, Elizabeth; Smith, Viktorija; Carlson, Mackenzie L.; Young, Christina B.; Crane, Paul K.; Mukherjee, Shubhabrata; Radiology and Imaging Sciences, School of MedicineBackground: Cognitive subtypes of Alzheimer’s Dementia (AD), defined by a relative impairment in a particular domain of cognition, have previously been shown to be associated with patterns of gray matter atrophy. Here we assessed the association of these subtypes with patterns of tau deposition measured in vivo using tau PET imaging in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Method: We included amyloid positive individuals with AD and Mild Cognitive Impairment (MCI). We selected the first diagnosis visit for AD and the most recent visit for MCI. Previously, AD individuals were categorized into AD‐Memory, AD‐Language, AD‐Executive, AD‐Visuospatial, AD‐Multiple domains, or AD‐No domain subtypes based on a relative cognitive impairment. These methods were extended to categorize MCI individuals. The AD/MCI‐Memory, AD/MCI‐Visuospatial, and AD/MCI‐No domain groups were large enough for our analyses. The tau PET scan closest to the subtyping visit was selected (median 49 days between scan and visit). Tau deposition for 35 brain regions (left and right sides averaged) were included as predictors. Separate five‐fold cross validated LASSO regressions were run for each of the three pairwise comparisons. Each model was repeated 100 times with different random fold selections to assess the stability of results. Result: We included 240 individuals (118 AD; 122 MCI) in our analyses (Table 1). There was some variation in the chosen models across repetitions with the AD/MCI‐Visuospatial versus AD/MCI‐No domain comparison varying the most (Table 2). We limit interpretation to those regions that appeared in ≥70% of repetitions. The amygdala was consistently selected in all pair‐wise comparisons. Higher tau deposition in this region was associated with a higher likelihood of being in AD/MCI‐Memory. Higher tau deposition in the postcentral region was associated with a lower likelihood of being in AD/MCI‐Memory compared to AD/MCI‐Visuospatial. Coefficients on consistently selected regions in the AD/MCI‐visuospatial versus AD/MCI‐No domain comparison were small. Figure 1 summarizes the top results from our analyses. Conclusion: We found heterogeneity in regional tau deposition among three cognitive subtypes. Future work will make use of additional cohorts with harmonized cognitive and imaging data. We plan to incorporate all cognitive subtypes and evaluate lateral asymmetry.Item Relationship between baseline brain metabolism measured using [18F]FDG PET and memory and executive function in prodromal and early Alzheimer's disease(Springer, 2012) Habeck, Christian; Risacher, Shannon; Lee, Grace J.; Glymour, M. Maria; Mormino, Elizabeth; Mukherjee, Shubhabrata; Kim, Sungeun; Nho, Kwangsik; DeCarli, Charles; Saykin, Andrew J.; Crane, Paul K.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineDifferences in brain metabolism as measured by FDG-PET in prodromal and early Alzheimer's disease (AD) have been consistently observed, with a characteristic parietotemporal hypometabolic pattern. However, exploration of brain metabolic correlates of more nuanced measures of cognitive function has been rare, particularly in larger samples. We analyzed the relationship between resting brain metabolism and memory and executive functioning within diagnostic group on a voxel-wise basis in 86 people with AD, 185 people with mild cognitive impairment (MCI), and 86 healthy controls (HC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found positive associations within AD and MCI but not in HC. For MCI and AD, impaired executive functioning was associated with reduced parietotemporal metabolism, suggesting a pattern consistent with known AD-related hypometabolism. These associations suggest that decreased metabolic activity in the parietal and temporal lobes may underlie the executive function deficits in AD and MCI. For memory, hypometabolism in similar regions of the parietal and temporal lobes were significantly associated with reduced performance in the MCI group. However, for the AD group, memory performance was significantly associated with metabolism in frontal and orbitofrontal areas, suggesting the possibility of compensatory metabolic activity in these areas. Overall, the associations between brain metabolism and cognition in this study suggest the importance of parietal and temporal lobar regions in memory and executive function in the early stages of disease and an increased importance of frontal regions for memory with increasing impairment.Item The prevalence of tau‐PET positivity in aging and dementia(Wiley, 2025-01-09) Coomans, Emma M.; Groot, Colin; Rowe, Christopher C.; Dore, Vincent; Villemagne, Victor L.; van de Giessen, Elsmarieke; van der Flier, Wiesje M.; Pijnenburg, Yolande A. L.; Visser, Pieter Jelle; den Braber, Anouk; Pontecorvo, Michael; Shcherbinin, Sergey; Kennedy, Ian A.; Jagust, William J.; Baker, Suzanne L.; Harrison, Theresa M.; Gispert, Juan Domingo; Shekari, Mahnaz; Minguillon, Carolina; Smith, Ruben; Mattsson-Carlgren, Niklas; Palmqvist, Sebastian; Strandberg, Olof; Stomrud, Erik; Malpetti, Maura; O'Brien, John T.; Rowe, James B.; Jäger, Elena; Bischof, Gérard N.; Drzezga, Alexander; Garibotto, Valentina; Frisoni, Giovanni; Peretti, Débora Elisa; Schöll, Michael; Skoog, Ingmar; Kern, Silke; Sperling, Reisa A.; Johnson, Keith A.; Risacher, Shannon L.; Saykin, Andrew J.; Carrillo, Maria C.; Dickerson, Brad C.; Apostolova, Liana G.; Barthel, Henryk; Rullmann, Michael; Messerschmidt, Konstantin; Vandenberghe, Rik; Van Laere, Koen; Spruyt, Laure; Franzmeier, Nicolai; Brendel, Matthias; Gnörich, Johannes; Benzinger, Tammie L. S.; Lagarde, Julien; Sarazin, Marie; Bottlaender, Michel; Villeneuve, Sylvia; Poirier, Judes; Seo, Sang Won; Gu, Yuna; Kim, Jun Pyo; Mormino, Elizabeth; Young, Christina B.; Vossler, Hillary; Rosa-Neto, Pedro; Therriault, Joseph; Rahmouni, Nesrine; Coath, William; Cash, David M.; Schott, Jonathan M.; Rabinovici, Gil D.; La Joie, Renaud; Rosen, Howard J.; Johnson, Sterling C.; Christian, Bradley T.; Betthauser, Tobey J.; Hansson, Oskar; Ossenkoppele, Rik; Radiology and Imaging Sciences, School of MedicineBackground Tau‐PET imaging allows in‐vivo detection of neurofibrillary tangles. One tau‐PET tracer (i.e., [18F]flortaucipir) has received FDA‐approval for clinical use, and multiple other tau‐PET tracers have been implemented into clinical trials for participant selection and/or as a primary or secondary outcome measure. To optimize future use of tau‐PET, it is essential to understand how demographic, clinical and genetic factors affect tau‐PET‐positivity rates. Method This large‐scale multi‐center study includes 9713 participants from 35 cohorts worldwide who underwent tau‐PET with [18F]flortaucipir (n = 6420), [18F]RO948 (n = 1999), [18F]MK6240 (n = 878) or [18F]PI2620 (n = 416) (Table‐1). We analyzed individual‐level tau‐PET SUVR data using a cerebellar reference region that were processed either centrally (n = 3855) or by each cohort (n = 5858). We computed cohort‐specific SUVR thresholds based on the mean + 2 standard deviations in a temporal meta‐region of amyloid‐negative cognitively normal (CN) individuals aged >50. Logistic generalized estimating equations were used to estimate tau‐PET‐positivity probabilities, using an exchangeable correlation structure to account for within‐cohort correlations. Analyses were performed with (interactions between) age, amyloid‐status, and APOE‐e4 carriership as independent variables, stratified for syndrome diagnosis. Result The study included 5962 CN participants (7.5% tau‐PET‐positive), 1683 participants with mild cognitive impairment (MCI, 33.8% tau‐PET‐positive) and 2068 participants with a clinical diagnosis of dementia (62.1% tau‐PET‐positive) (Figure‐1). From age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 1.2% [95% CI: 0.9%‐1.5%] to 3.7% [2.3%‐5.1%] among CN amyloid‐negative participants; and from 16.4% [10.8%‐22.1%] to 20.5% [18.8%‐22.2%] among CN amyloid‐positive participants. Among amyloid‐negative participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 3.5% [1.6%‐5.3%] to 11.8% [7.1%‐16.5%] and from 12.6% [4.5%‐20.7%] to 15.9% [6.7%‐25.1%] respectively. In contrast, among amyloid‐positive participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity decreased from 66.5% [57.0%‐76.0%] to 48.3% [42.9%‐53.8%] and from 92.3% [88.7%‐95.9%] to 73.4% [67.5%‐79.3%] respectively. APOE‐e4 status primarily modulated the association of age with tau‐PET‐positivity estimates among CN and MCI amyloid‐positive participants (Figure‐2). Conclusion This large‐scale multi‐cohort study provides robust prevalence estimates of tau‐PET‐positivity, which can aid the interpretation of tau‐PET in the clinic and inform clinical trial designs.