Browsing by Subject "Tau"
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Item 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception(Elsevier, 2016-06-01) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Luthman, Johan; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W.; Trojanowski, John Q.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineThe Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.Item Aging-related tau astrogliopathy (ARTAG): harmonized evaluation strategy(Springer, 2016-01) Kovacs, Gabor G.; Ferrer, Isidro; Alafuzoff, Irina; Attems, Johannes; Budka, Herbert; Cairns, Nigel J.; Crary, John F.; Duyckaerts, Charles; Ghetti, Bernardino; Halliday, Glenda M.; Ironside, James W.; Love, Seth; Mackenzie, Ian R.; Munoz, David G.; Murray, Melissa E.; Nelson, Peter T.; Takahashi, Hitoshi; Trojanowski, John Q.; Ansorge, Olaf; Arzberger, Thomas; Baborie, Atik; Beach, Thomas G.; Bieniek, Kevin F.; Bigio, Eileen H.; Bodi, Istvan; Dugger, Brittany N.; Feany, Mel; Gelpi, Ellen; Gentleman, Stephen M.; Giaccone, Giorgio; Hatanpaa, Kimmo J.; Heale, Richard; Hof, Patrick R.; Hofer, Monika; Hortobágyi, Tibor; Jellinger, Kurt; Jicha, Gregory A.; Ince, Paul; Kofler, Julia; Kövari, Enikö; Kril, Jillian J.; Mann, David M.; Matej, Radoslav; McKee, Ann C.; McLean, Catriona; Milenkovic, Ivan; Montine, Thomas J.; Murayama, Shigeo; Lee, Edward B.; Rahimi, Jasmin; Rodriguez, Roberta D.; Rozemüller, Annemieke; Schneider, Julie A.; Schultz, Christian; Seeley, William; Seilhean, Danielle; Smith, Colin; Tagliavini, Fabrizio; Takao, Masaki; Thal, Dietmar Rudolf; Toledo, Jon B.; Tolnay, Markus; Troncoso, Juan C.; Vinters, Harry V.; Weis, Serge; Wharton, Stephen B.; White III, Charles L.; Wisniewski, Thomas; Woulfe, John M.; Yamada, Masahito; Dicks, Dennis W.; Department of Pathology and Laboratory Medicine, IU School of MedicinePathological accumulation of abnormally phosphorylated tau protein in astrocytes is a frequent, but poorly characterized feature of the aging brain. Its etiology is uncertain, but its presence is sufficiently ubiquitous to merit further characterization and classification, which may stimulate clinicopathological studies and research into its pathobiology. This paper aims to harmonize evaluation and nomenclature of aging-related tau astrogliopathy (ARTAG), a term that refers to a morphological spectrum of astroglial pathology detected by tau immunohistochemistry, especially with phosphorylation-dependent and 4R isoform-specific antibodies. ARTAG occurs mainly, but not exclusively, in individuals over 60 years of age. Tau-immunoreactive astrocytes in ARTAG include thorn-shaped astrocytes at the glia limitans and in white matter, as well as solitary or clustered astrocytes with perinuclear cytoplasmic tau immunoreactivity that extends into the astroglial processes as fine fibrillar or granular immunopositivity, typically in gray matter. Various forms of ARTAG may coexist in the same brain and might reflect different pathogenic processes. Based on morphology and anatomical distribution, ARTAG can be distinguished from primary tauopathies, but may be concurrent with primary tauopathies or other disorders. We recommend four steps for evaluation of ARTAG: (1) identification of five types based on the location of either morphologies of tau astrogliopathy: subpial, subependymal, perivascular, white matter, gray matter; (2) documentation of the regional involvement: medial temporal lobe, lobar (frontal, parietal, occipital, lateral temporal), subcortical, brainstem; (3) documentation of the severity of tau astrogliopathy; and (4) description of subregional involvement. Some types of ARTAG may underlie neurological symptoms; however, the clinical significance of ARTAG is currently uncertain and awaits further studies. The goal of this proposal is to raise awareness of astroglial tau pathology in the aged brain, facilitating communication among neuropathologists and researchers, and informing interpretation of clinical biomarkers and imaging studies that focus on tau-related indicators.Item Association between plasma tau and postoperative delirium incidence and severity: a prospective observational study(Elsevier, 2021) Ballweg, Tyler; White, Marissa; Parker, Margaret; Casey, Cameron; Bo, Amber; Farahbakhsh, Zahra; Kayser, Austin; Blair, Alexander; Lindroth, Heidi; Pearce, Robert A.; Blennow, Kaj; Zetterberg, Henrik; Lennertz, Richard; Sanders, Robert D.; Medicine, School of MedicineBackground: Postoperative delirium is associated with increases in the neuronal injury biomarker, neurofilament light (NfL). Here we tested whether two other biomarkers, glial fibrillary acidic protein (GFAP) and tau, are associated with postoperative delirium. Methods: A total of 114 surgical patients were recruited into two prospective biomarker cohort studies with assessment of delirium severity and incidence. Plasma samples were sent for biomarker analysis including tau, NfL, and GFAP, and a panel of 10 cytokines. We determined a priori to adjust for interleukin-8 (IL-8), a marker of inflammation, when assessing associations between biomarkers and delirium incidence and severity. Results: GFAP concentrations showed no relationship to delirium. The change in tau from preoperative concentrations to postoperative Day 1 was greater in patients with postoperative delirium (P<0.001) and correlated with delirium severity (ρ=0.39, P<0.001). The change in tau correlated with increases in IL-8 (P<0.001) and IL-10 (P=0.0029). Linear regression showed that the relevant clinical predictors of tau changes were age (P=0.037), prior stroke/transient ischaemic attack (P=0.001), and surgical blood loss (P<0.001). After adjusting for age, sex, preoperative cognition, and change in IL-8, tau remained significantly associated with delirium severity (P=0.026). Using linear mixed effect models, only tau (not NfL or IL-8) predicted recovery from delirium (P<0.001). Conclusions: The change in plasma tau was associated with delirium incidence and severity, and resolved over time in parallel with delirium features. The impact of this putative perioperative neuronal injury biomarker on long-term cognition merits further investigation.Item Association of Blood Biomarkers With Acute Sport-Related Concussion in Collegiate Athletes: Findings From the NCAA and Department of Defense CARE Consortium(JAMA Network, 2020-01-03) McCrea, Michael; Broglio, Steven P.; McAllister, Thomas W.; Gill, Jessica; Giza, Christopher C.; Huber, Daniel L.; Harezlak, Jaroslaw; Cameron, Kenneth L.; Houston, Megan N.; McGinty, Gerald; Jackson, Jonathan C.; Guskiewicz, Kevin; Mihalik, Jason; Brooks, M. Alison; Duma, Stephan; Rowson, Steven; Nelson, Lindsay D.; Pasquina, Paul; Meier, Timothy B.; CARE Consortium Investigators; Foroud, Tatiana; Katz, Barry P.; Saykin, Andrew J.; Campbell, Darren E.; Svoboda, Steven J.; Goldman, Joshua; DiFiori, Jon; Psychiatry, School of MedicineImportance: There is potential scientific and clinical value in validation of objective biomarkers for sport-related concussion (SRC). Objective: To investigate the association of acute-phase blood biomarker levels with SRC in collegiate athletes. Design, Setting, and Participants: This multicenter, prospective, case-control study was conducted by the National Collegiate Athletic Association (NCAA) and the US Department of Defense Concussion Assessment, Research, and Education (CARE) Consortium from February 20, 2015, to May 31, 2018, at 6 CARE Advanced Research Core sites. A total of 504 collegiate athletes with concussion, contact sport control athletes, and non-contact sport control athletes completed clinical testing and blood collection at preseason baseline, the acute postinjury period, 24 to 48 hours after injury, the point of reporting being asymptomatic, and 7 days after return to play. Data analysis was conducted from March 1 to November 30, 2019. Main Outcomes and Measures: Glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament light chain, and tau were quantified using the Quanterix Simoa multiplex assay. Clinical outcome measures included the Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, and Brief Symptom Inventory 18. Results: A total of 264 athletes with concussion (mean [SD] age, 19.08 [1.24] years; 211 [79.9%] male), 138 contact sport controls (mean [SD] age, 19.03 [1.27] years; 107 [77.5%] male), and 102 non-contact sport controls (mean [SD] age, 19.39 [1.25] years; 82 [80.4%] male) were included in the study. Athletes with concussion had significant elevation in GFAP (mean difference, 0.430 pg/mL; 95% CI, 0.339-0.521 pg/mL; P < .001), UCH-L1 (mean difference, 0.449 pg/mL; 95% CI, 0.167-0.732 pg/mL; P < .001), and tau levels (mean difference, 0.221 pg/mL; 95% CI, 0.046-0.396 pg/mL; P = .004) at the acute postinjury time point compared with preseason baseline. Longitudinally, a significant interaction (group × visit) was found for GFAP (F7,1507.36 = 16.18, P < .001), UCH-L1 (F7,1153.09 = 5.71, P < .001), and tau (F7,1480.55 = 6.81, P < .001); the interaction for neurofilament light chain was not significant (F7,1506.90 = 1.33, P = .23). The area under the curve for the combination of GFAP and UCH-L1 in differentiating athletes with concussion from contact sport controls at the acute postinjury period was 0.71 (95% CI, 0.64-0.78; P < .001); the acute postinjury area under the curve for all 4 biomarkers combined was 0.72 (95% CI, 0.65-0.79; P < .001). Beyond SCAT-3 symptom score, GFAP at the acute postinjury time point was associated with the classification of athletes with concussion from contact controls (β = 12.298; 95% CI, 2.776-54.481; P = .001) and non-contact sport controls (β = 5.438; 95% CI, 1.676-17.645; P = .005). Athletes with concussion with loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with neither loss of consciousness nor posttraumatic amnesia at the acute postinjury time point (mean difference, 0.583 pg/mL; 95% CI, 0.369-0.797 pg/mL; P < .001). Conclusions and Relevance: The results suggest that blood biomarkers can be used as research tools to inform the underlying pathophysiological mechanism of concussion and provide additional support for future studies to optimize and validate biomarkers for potential clinical use in SRC.Item Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease–related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group(Wiley, 2022) Verberk, Inge M. W.; Misdorp, Els O.; Koelewijn, Jannet; Ball, Andrew J.; Blennow, Kaj; Dage, Jeffrey L.; Fandos, Noelia; Hansson, Oskar; Hirtz, Christophe; Janelidze, Shorena; Kang, Sungmin; Kirmess, Kristopher; Kindermans, Jana; Lee, Ryan; Meyer, Matthew R.; Shan, Dandan; Shaw, Leslie M.; Waligorska, Teresa; West, Tim; Zetterberg, Henrik; Edelmayer, Rebecca M.; Teunissen, Charlotte E.; Neurology, School of MedicineIntroduction: Pre-analytical sample handling might affect the results of Alzheimer's disease blood-based biomarkers. We empirically tested variations of common blood collection and handling procedures. Methods: We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze–thawing. We measured amyloid beta (Aβ)42 and 40 peptides with six assays, and Aβ oligomerization-tendency (OAβ), amyloid precursor protein (APP)699-711, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t-tau), and phosphorylated tau181. Results: Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aβ and t-tau; t-tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations. Discussion: We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood-based biomarkers into the research and clinical settings.Item Classification of Diseases with Accumulation of Tau(Wiley, 2022) Kovacs, Gabor G.; Ghetti, Bernardino; Goedert, Michel; Pathology and Laboratory Medicine, School of MedicineItem Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum(Wiley, 2022) Tosun, Duygu; Demir, Zeynep; Veitch, Dallas P.; Weintraub, Daniel; Aisen, Paul; Jack, Clifford R., Jr.; Jagust, William J.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods: Within 248 Aβ-positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ-positron emission tomography [PET] uptake, regional tau-PET uptake, and regional magnetic resonance imaging-based atrophy) and risk-factors (age, sex, education, apolipoprotein E [APOE], and white-matter lesions) on cross-sectional cognitive impairment and longitudinal cognitive decline. Results: Sixteen percent of variance in cross-sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ-tau-atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion: These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.Item Creating the Pick's disease International Consortium: Association study of MAPT H2 haplotype with risk of Pick's disease(medRxiv, 2023-04-24) Valentino, Rebecca R.; Scotton, William J.; Roemer, Shanu F.; Lashley, Tammaryn; Heckman, Michael G.; Shoai, Maryam; Martinez-Carrasco, Alejandro; Tamvaka, Nicole; Walton, Ronald L.; Baker, Matthew C.; Macpherson, Hannah L.; Real, Raquel; Soto-Beasley, Alexandra I.; Mok, Kin; Revesz, Tamas; Warner, Thomas T.; Jaunmuktane, Zane; Boeve, Bradley F.; Christopher, Elizabeth A.; DeTure, Michael; Duara, Ranjan; Graff-Radford, Neill R.; Josephs, Keith A.; Knopman, David S.; Koga, Shunsuke; Murray, Melissa E.; Lyons, Kelly E.; Pahwa, Rajesh; Parisi, Joseph E.; Petersen, Ronald C.; Whitwell, Jennifer; Grinberg, Lea T.; Miller, Bruce; Schlereth, Athena; Seeley, William W.; Spina, Salvatore; Grossman, Murray; Irwin, David J.; Lee, Edward B.; Suh, EunRan; Trojanowski, John Q.; Van Deerlin, Vivianna M.; Wolk, David A.; Connors, Theresa R.; Dooley, Patrick M.; Frosch, Matthew P.; Oakley, Derek H.; Aldecoa, Iban; Balasa, Mircea; Gelpi, Ellen; Borrego-Écija, Sergi; de Eugenio Huélamo, Rosa Maria; Gascon-Bayarri, Jordi; Sánchez-Valle, Raquel; Sanz-Cartagena, Pilar; Piñol-Ripoll, Gerard; Molina-Porcel, Laura; Bigio, Eileen H.; Flanagan, Margaret E.; Gefen, Tamar; Rogalski, Emily J.; Weintraub, Sandra; Redding-Ochoa, Javier; Chang, Koping; Troncoso, Juan C.; Prokop, Stefan; Newell, Kathy L.; Ghetti, Bernardino; Jones, Matthew; Richardson, Anna; Robinson, Andrew C.; Roncaroli, Federico; Snowden, Julie; Allinson, Kieren; Green, Oliver; Rowe, James B.; Singh, Poonam; Beach, Thomas G.; Serrano, Geidy E.; Flowers, Xena E.; Goldman, James E.; Heaps, Allison C.; Leskinen, Sandra P.; Teich, Andrew F.; Black, Sandra E.; Keith, Julia L.; Masellis, Mario; Bodi, Istvan; King, Andrew; Sarraj, Safa-Al; Troakes, Claire; Halliday, Glenda M.; Hodges, John R.; Kril, Jillian J.; Kwok, John B.; Piguet, Olivier; Gearing, Marla; Arzberger, Thomas; Roeber, Sigrun; Attems, Johannes; Morris, Christopher M.; Thomas, Alan J.; Evers, Bret M.; White, Charles L.; Mechawar, Naguib; Sieben, Anne A.; Cras, Patrick P.; De Vil, Bart B.; De Deyn, Peter Paul P. P.; Duyckaerts, Charles; Le Ber, Isabelle; Seihean, Danielle; Turbant-Leclere, Sabrina; MacKenzie, Ian R.; McLean, Catriona; Cykowski, Matthew D.; Ervin, John F.; Wang, Shih-Hsiu J.; Graff, Caroline; Nennesmo, Inger; Nagra, Rashed M.; Riehl, James; Kovacs, Gabor G.; Giaccone, Giorgio; Nacmias, Benedetta; Neumann, Manuela; Ang, Lee-Cyn; Finger, Elizabeth C.; Blauwendraat, Cornelis; Nalls, Mike A.; Singleton, Andrew B.; Vitale, Dan; Cunha, Cristina; Carvalho, Agostinho; Wszolek, Zbigniew K.; Morris, Huw R.; Rademakers, Rosa; Hardy, John A.; Dickson, Dennis W.; Rohrer, Jonathan D.; Ross, Owen A.; Pathology and Laboratory Medicine, School of MedicineBackground: Pick's disease (PiD) is a rare and predominantly sporadic form of frontotemporal dementia that is classified as a primary tauopathy. PiD is pathologically defined by argyrophilic inclusion Pick bodies and ballooned neurons in the frontal and temporal brain lobes. PiD is characterised by the presence of Pick bodies which are formed from aggregated, hyperphosphorylated, 3-repeat tau proteins, encoded by the MAPT gene. The MAPT H2 haplotype has consistently been associated with a decreased disease risk of the 4-repeat tauopathies of progressive supranuclear palsy and corticobasal degeneration, however its role in susceptibility to PiD is unclear. The primary aim of this study was to evaluate the association between MAPT H2 and risk of PiD. Methods: We established the Pick's disease International Consortium (PIC) and collected 338 (60.7% male) pathologically confirmed PiD brains from 39 sites worldwide. 1,312 neurologically healthy clinical controls were recruited from Mayo Clinic Jacksonville, FL (N=881) or Rochester, MN (N=431). For the primary analysis, subjects were directly genotyped for MAPT H1-H2 haplotype-defining variant rs8070723. In secondary analysis, we genotyped and constructed the six-variant MAPT H1 subhaplotypes (rs1467967, rs242557, rs3785883, rs2471738, rs8070723, and rs7521). Findings: Our primary analysis found that the MAPT H2 haplotype was associated with increased risk of PiD (OR: 1.35, 95% CI: 1.12-1.64 P=0.002). In secondary analysis involving H1 subhaplotypes, a protective association with PiD was observed for the H1f haplotype (0.0% vs. 1.2%, P=0.049), with a similar trend noted for H1b (OR: 0.76, 95% CI: 0.58-1.00, P=0.051). The 4-repeat tauopathy risk haplotype MAPT H1c was not associated with PiD susceptibility (OR: 0.93, 95% CI: 0.70-1.25, P=0.65). Interpretation: The PIC represents the first opportunity to perform relatively large-scale studies to enhance our understanding of the pathobiology of PiD. This study demonstrates that in contrast to its protective role in 4R tauopathies, the MAPT H2 haplotype is associated with an increased risk of PiD. This finding is critical in directing isoform-related therapeutics for tauopathies.Item Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes(IOS Press, 2023) Hammers, Dustin B.; Lin, Joshua H.; Polsinelli, Angelina J.; Logan, Paige E.; Risacher, Shannon L.; Schwarz, Adam J.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of MedicineBackground: Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. Objective: The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. Methods: Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. Results: Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. Conclusions: Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.Item Cryo-EM structures of amyloid-β filaments with the Arctic mutation (E22G) from human and mouse brains(Springer, 2023) Yang, Yang; Zhang, Wenjuan; Murzin, Alexey G.; Schweighauser, Manuel; Huang, Melissa; Lövestam, Sofia; Peak‑Chew, Sew Y.; Saito, Takashi; Saido, Takaomi C.; Macdonald, Jennifer; Lavenir, Isabelle; Ghetti, Bernardino; Graff, Caroline; Kumar, Amit; Nordberg, Agneta; Goedert, Michel; Scheres, Sjors H. W.; Pathology and Laboratory Medicine, School of MedicineThe Arctic mutation, encoding E693G in the amyloid precursor protein (APP) gene [E22G in amyloid-β (Aβ)], causes dominantly inherited Alzheimer’s disease. Here, we report the high-resolution cryo-EM structures of Aβ filaments from the frontal cortex of a previously described case (AβPParc1) with the Arctic mutation. Most filaments consist of two pairs of non-identical protofilaments that comprise residues V12–V40 (human Arctic fold A) and E11–G37 (human Arctic fold B). They have a substructure (residues F20–G37) in common with the folds of type I and type II Aβ42. When compared to the structures of wild-type Aβ42 filaments, there are subtle conformational changes in the human Arctic folds, because of the lack of a side chain at G22, which may strengthen hydrogen bonding between mutant Aβ molecules and promote filament formation. A minority of Aβ42 filaments of type II was also present, as were tau paired helical filaments. In addition, we report the cryo-EM structures of Aβ filaments with the Arctic mutation from mouse knock-in line AppNL−G−F. Most filaments are made of two identical mutant protofilaments that extend from D1 to G37 (AppNL−G−F murine Arctic fold). In a minority of filaments, two dimeric folds pack against each other in an anti-parallel fashion. The AppNL−G−F murine Arctic fold differs from the human Arctic folds, but shares some substructure.