Search

Background and purposeSporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive neurodegenerative disease caused by an abnormal isoform of the human prion protein. Structural magnetic resonance imaging in patients with pathologically confirmed sCJD was compared with cognitively normal individuals to identify a cortical thickness signature of sCJD.MethodsThis retrospective cross-sectional study compared patients with autopsy-confirmed sCJD with dementia (n = 11) with age- and sex-matched cognitively normal individuals (n = 22). We identified regions of interest (ROIs) in which cortical thickness was most affected by sCJD. Within patients with sCJD, the relationship between ROI cortical thickness and clinical measures (disease duration, cerebrospinal fluid tau and diffusion-weighted imaging abnormalities) was evaluated.ResultsCompared with cognitively normal individuals, patients with sCJD had significantly reduced cortical thickness in multiple ROIs, including the fusiform gyrus, precentral gyrus, precuneus and superior temporal gyrus bilaterally; the caudal middle frontal gyrus, superior frontal gyrus, postcentral gyrus, inferior temporal gyrus and transverse temporal gyrus in the left hemisphere; and the superior parietal lobule in the right hemisphere. Only one patient with sCJD had co-pathology consistent with Alzheimer's disease. Reduced cortical thickness did not correlate with disease duration, presence of diffusion restriction or elevated cerebrospinal fluid tau.ConclusionCortical signature changes in sCJD may reflect brain changes not captured by standard clinical measures. This information may be used with clinical measures to inform the progression of sCJD and patterns of prion protein spread throughout the brain. These results may have implications for prediction of symptomatic progression and plausibly for development of therapeutic strategies.

Alzheimer's disease (AD) is the most common cause of dementia and the third leading cause of death in the elderly in the United States. Currently, the diagnosis of AD relies upon clinical neurological assessment combined with conventional computed tomography or magnetic resonance imaging (MRI) to exclude other potential etiologies for the patient's dementia. Recently, however, there has been a large volume of research in imaging tests for AD, most notably in the application of diffusion-based MRI. The development of imaging techniques for AD may provide important information for early diagnosis of the disease, for monitoring of disease progression, and for assessing response to therapies. This paper reviews the current imaging tests available for AD, from current clinical protocols to specialized examinations to research protocols, with special emphasis on diffusion tensor MRI. [ABSTRACT FROM AUTHOR]

Introduction: In the research setting, obtaining accurate established biomarker measurements and maximizing use of the precious samples is key. Accurate technologies are available for Alzheimer's disease (AD), but no platform can measure all the established and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA) is a technology that requires 15 µL of sample to measure more than 100 analytes., Methods: We compared AD-relevant biomarkers included in the NULISA against validated assays in cerebrospinal fluid (CSF) and plasma., Results: CSF measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. Other biomarkers show a wide range of correlation values depending on the fluid and the platform., Discussion: The NULISA multiplexed platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume., Highlights: We tested the novel technology NUcleic acid Linked Immuno-Sandwich Assay (NULISA) in the dementia research setting. NULISA multiplexed platform produces reliable results for established and emerging biomarkers using minimal sample volume. Cerebrospinal fluid measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. NULISA measures are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objective: This study investigated how obesity, BMI ≥ 30 kg/m 2 , abdominal adiposity, and systemic inflammation relate to neuroinflammation using diffusion basis spectrum imaging., Methods: We analyzed data from 98 cognitively normal midlife participants (mean age: 49.4 [SD 6.2] years; 34 males [34.7%]; 56 with obesity [57.1%]). Participants underwent brain and abdominal magnetic resonance imaging (MRI), blood tests, and amyloid positron emission tomography (PET) imaging. Abdominal visceral and subcutaneous adipose tissue (VAT and SAT, respectively) was segmented, and Centiloids were calculated. Diffusion basis spectrum imaging parameter maps were created using an in-house script, and tract-based spatial statistics assessed white matter differences in high versus low BMI values, VAT, SAT, insulin resistance, systemic inflammation, and Centiloids, with age and sex as covariates., Results: Obesity, high VAT, and high SAT were linked to lower axial diffusivity, reduced fiber fraction, and increased restricted fraction in white matter. Obesity was additionally associated with higher hindered fraction and lower fractional anisotropy. Also, individuals with high C-reactive protein showed lower axial diffusivity. Higher restricted fraction correlated with continuous BMI and SAT particularly in male individuals, whereas VAT effects were similar in male and female individuals., Conclusions: The findings suggest that, at midlife, obesity and abdominal fat are associated with reduced brain axonal density and increased inflammation, with visceral fat playing a significant role in both sexes., (© 2024 The Author(s). Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society.)

Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarker for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort, including both cognitively unimpaired and cognitively impaired individuals, were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU] and p-tau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, the FDA-approved p-tau181/Aβ42Elecsys, and p-tau181Elecsys. All plasma p-tau217 tests exhibited a high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (Pdiff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (Pdiff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (Pdiff=0.025). Plasma %p-tau217WashU exhibited stronger associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more associated with Aβ-PET load than plasma p-tau217Janssen (Pdiff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all Pdiff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; Pdiff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217NULISA showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test, which needs to be determined by future reviews incorporating results from multiple cohorts., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The grey matter of the brain develops and declines in coordinated patterns during the lifespan. Such covariation patterns of grey matter structure can be quantified as grey matter networks, which can be measured with magnetic resonance imaging. In Alzheimer's disease, the global organization of grey matter networks becomes more random, which is captured by a decline in the small-world coefficient. Such decline in the small-world value has been robustly associated with cognitive decline across clinical stages of Alzheimer's disease. The biological mechanisms causing this decline in small-world values remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and small-world coefficient in mutation carriers ( N = 219) and non-carriers ( N = 136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Amyloid beta, Tau, synaptic (Synaptosome associated protein-25, Neurogranin) and neuronal calcium-sensor protein (Visinin-like protein-1) preceded loss of small-world coefficient by several years, while increased levels in CSF markers for inflammation (Chitinase-3-like protein 1) and axonal injury (Neurofilament light) co-occurred with decreasing small-world values. This suggests that axonal loss and inflammation play a role in structural grey matter network changes., Competing Interests: C.C.: receives research support from: Biogen, EISAI, Alector and Parabon. The funders of the study had no role in the collection, analysis, interpretation of data; or in the writing of the report; or in the decision to submit the paper for publication. C.C. is a member of the advisory board of ADx Healthcare and Vivid Genomics Marty Farlow: Grant/Research Support from AbbVie, ADCS Posiphen, AstraZeneca, Biogen, Eisai, Eli Lilly, Genentech, Novartis, Suven Life Sciences, Ltd., vTv Therapeutics; Consultant/Advisory Boards/DSMB Boards for Allergan, Avanir, AZTherapies, Biogen MA Inc., Cerecin (formerly Accera), Chemigen, Cognition Therapeutics, Cortexyme, Danone, Eisai Inc., Eli Lilly, Longeveron, Green Valley, Medavante, Otsuka Pharmaceutical, Proclara, Neurotrope Bioscience, Samumed, Takeda, vTv Therapeutics, Zhejian Hisun Pharmaceuticals; patent Elan Johannes Levin reports speaker’s fees from Bayer Vital, speaker’s fees from Willi Gross Foundation, consulting fees from Axon Neuroscience, consulting fees from Ionis Pharmaceuticals, non-financial support from Abbvie, MODAG compensation for part time CMO, Thieme medical publishers and W. Kohlhammer GmbH medical publishers author fees, outside the submitted work. E.M.: NIA (research Funding); Eli Lilly-DSMB; ESAI—CMS; Alzamend—scientific advisory board. P.S. is partner at LSP Invester fund and has acquired grant support (for the institution) from GE Healthcare, Danone Research, Piramal and Merck. In the past 2 years, he has received consultancy/speaker fees (paid to the institution) from Lilly, GE Healthcare, Novartis, Sanofi, Nutricia, Probiodrug, Biogen, Roche, Avraham and EIP Pharma. Outside of this manuscript, R.J.B. reports grant/research/clinical trial support: NIH, Alzheimer's Association, BrightFocus Foundation, Rainwater Foundation Tau Consortium, Association for Frontotemporal Degeneration, Cure Alzheimer's Fund, the Tau SILK Consortium (AbbVie, Biogen and Eli Lilly), Janssen, and an anonymous foundation. R.J.B. reports consulting fees/honoraria from Janssen, Pfizer, Roche, Eisai, and Merck. R.J.B. reports equity ownership interest/advisory board income from C2N Diagnostics. All other authors report no disclosures., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations., Competing Interests: Declarations. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Conflicts of interest: The authors declare that there are no conflicts of interest regarding the publication of this paper. This declaration is made to confirm that there has been no financial or personal relationship with other people or organizations that could inappropriately influence or bias the work presented in this manuscript. This includes, but is not limited to, employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding., (© 2024. The Author(s).)

Background and Purpose: Integrated PET/MR allows the simultaneous acquisition of PET biomarkers and structural and functional MRI to study Alzheimer disease (AD). Attenuation correction (AC), crucial for PET quantification, can be performed using a deep learning approach, DL-Dixon, based on standard Dixon images. Longitudinal amyloid PET imaging, which provides important information about disease progression or treatment responses in AD, is usually acquired over several years. Hardware and software upgrades often occur during a multiple-year study period, resulting in data variability. This study aims to harmonize PET/MR DL-Dixon AC amid software and head coil updates and evaluate its accuracy and longitudinal consistency., Materials and Methods: Tri-modality PET/MR and CT images were obtained from 329 participants, with a subset of 38 undergoing tri-modality scans twice within approximately three years. Transfer learning was employed to fine-tune DL-Dixon models on images from two scanner software versions (VB20P and VE11P) and two head coils (16-channel and 32-channel coils). The accuracy and longitudinal consistency of the DL-Dixon AC were evaluated. Power analyses were performed to estimate the sample size needed to detect various levels of longitudinal changes in the PET standardized uptake value ratio (SUVR)., Results: The DL-Dixon method demonstrated high accuracy across all data, irrespective of scanner software versions and head coils. More than 95.6% of brain voxels showed less than 10% PET relative absolute error in all participants. The median [interquartile range] PET mean relative absolute error was 1.10% [0.93%, 1.26%], 1.24% [1.03%, 1.54%], 0.99% [0.86%, 1.13%] in the cortical summary region, and 1.04% [0.83%, 1.36%], 1.08% [0.84%, 1.34%], 1.05% [0.72%, 1.32%] in cerebellum using the DL-Dixon models for the VB20P-16-channel-coil, VE11P-16-channel-coil and VE11P-32-channel-coil data, respectively. The within-subject coefficient of variation and intra-class correlation coefficient of PET SUVR in the cortical regions were comparable between the DL-Dixon and CT AC. Power analysis indicated that similar numbers of participants would be needed to detect the same level of PET changes using DL-Dixon and CT AC., Conclusions: DL-Dixon exhibited excellent accuracy and longitudinal consistency across the two software versions and head coils, demonstrating its robustness for longitudinal PET/MR neuroimaging studies in AD., Abbreviations: AC = attenuation correction; AD = Alzheimer disease; HU = Hounsfield unit; ICC = intraclass correlation coefficient; MAE = mean absolute error; MRAE = mean relative absolute error; pCT = pseudo-CT; PiB = Pittsburgh Compound B; SD = standard deviation; SUVR = standardized uptake value ratio; wCV = within-subject coefficient of variation., (© 2024 by American Journal of Neuroradiology.)

The life expectancy of people with multiple sclerosis (MS) has increased, yet we have noted that development of a typical Alzheimer disease dementia syndrome is uncommon. We hypothesized that Alzheimer disease pathology is uncommon in MS patients. In 100 MS patients, the rate of amyloid-β plasma biomarker positivity was approximately half the rate in 300 non-MS controls matched on age, sex, apolipoprotein E proteotype, and cognitive status. Interestingly, most MS patients who did have amyloid-β pathology had features atypical for MS at diagnosis. These results support that MS is associated with reduced Alzheimer disease risk, and suggest new avenues of research. ANN NEUROL 2024;96:453-459., (© 2024 American Neurological Association.)

Introduction: Cerebrospinal fluid (CSF) tau phosphorylation at multiple sites is associated with cortical amyloid and other pathologic changes in Alzheimer's disease. These relationships can be non-linear. We used an artificial neural network to assess the ability of 10 different CSF tau phosphorylation sites to predict continuous amyloid positron emission tomography (PET) values., Methods: CSF tau phosphorylation occupancies at 10 sites (including pT181/T181, pT217/T217, pT231/T231 and pT205/T205) were measured by mass spectrometry in 346 individuals (57 cognitively impaired, 289 cognitively unimpaired). We generated synthetic amyloid PET scans using biomarkers and evaluated their performance., Results: Concentration of CSF pT217/T217 had low predictive error (average error: 13%), but also a low predictive range (ceiling 63 Centiloids). CSF pT231/T231 has slightly higher error (average error: 19%) but predicted through a greater range (87 Centiloids)., Discussion: Tradeoffs exist in biomarker selection. Some phosphorylation sites offer greater concordance with amyloid PET at lower levels, while others perform better over a greater range., Highlights: Novel pTau isoforms can predict cortical amyloid burden. pT217/T217 accurately predicts cortical amyloid burden in low-amyloid individuals. Traditional CSF biomarkers correspond with higher levels of amyloid., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics., Methods: Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance., Results: Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress., Discussion: Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology., Highlights: In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Genetic variants that cause autosomal dominant Alzheimer's disease are highly penetrant but vary substantially regarding age at symptom onset (AAO), rates of cognitive decline, and biomarker changes. Most pathogenic variants that cause autosomal dominant Alzheimer's disease are in presenilin 1 (PSEN1), which encodes the catalytic core of γ-secretase, an enzyme complex that is crucial in production of amyloid β. We aimed to investigate whether the heterogeneity in AAO and biomarker trajectories in carriers of PSEN1 pathogenic variants could be predicted on the basis of the effects of individual PSEN1 variants on γ-secretase activity and amyloid β production., Methods: For this cross-sectional and longitudinal analysis, we used data from participants enrolled in the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS) via the DIAN-OBS data freeze version 15 (data collected between Feb 29, 2008, and June 30, 2020). The data freeze included data from 20 study sites in research institutions, universities, hospitals, and clinics across Europe, North and South America, Asia, and Oceania. We included individuals with PSEN1 pathogenic variants for whom relevant genetic, clinical, imaging, and CSF data were available. PSEN1 pathogenic variants were characterised via genetically modified PSEN1 and PSEN2 double-knockout human embryonic kidney 293T cells and immunoassays for Aβ37, Aβ38, Aβ40, Aβ42, and Aβ43. A summary measure of γ-secretase activity (γ-secretase composite [GSC]) was calculated for each variant and compared with clinical history-derived AAO using correlation analyses. We used linear mixed-effect models to assess associations between GSC scores and multimodal-biomarker and clinical data from DIAN-OBS. We used separate models to assess associations with Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini-Mental State Examination (MMSE), and Wechsler Memory Scale-Revised (WMS-R) Logical Memory Delayed Recall, [ 11 C]Pittsburgh compound B (PiB)-PET and brain glucose metabolism using [ 18 F] fluorodeoxyglucose (FDG)-PET, CSF Aβ42-to-Aβ40 ratio (Aβ42/40), CSF log 10 (phosphorylated tau 181), CSF log 10 (phosphorylated tau 217), and MRI-based hippocampal volume., Findings: Data were included from 190 people carrying PSEN1 pathogenic variants, among whom median age was 39·0 years (IQR 32·0 to 48·0) and AAO was 44·5 years (40·6 to 51·4). 109 (57%) of 190 carriers were female and 81 (43%) were male. Lower GSC values (ie, lower γ-secretase activity than wild-type PSEN1) were associated with earlier AAO (r=0·58; p<0·0001). GSC was associated with MMSE (β=0·08, SE 0·03; p=0·0043), CDR-SB (-0·05, 0·02; p=0·0027), and WMS-R Logical Memory Delayed Recall scores (0·09, 0·02; p=0·0006). Lower GSC values were associated with faster increase in PiB-PET signal (p=0·0054), more rapid decreases in hippocampal volume (4·19, 0·77; p<0·0001), MMSE (0·02, 0·01; p=0·0020), and WMS-R Logical Memory Delayed Recall (0·004, 0·001; p=0·0003)., Interpretation: Our findings suggest that clinical heterogeneity in people with autosomal dominant Alzheimer's disease can be at least partly explained by different effects of PSEN1 variants on γ-secretase activity and amyloid β production. They support targeting γ-secretase as a therapeutic approach and suggest that cell-based models could be used to improve prediction of symptom onset., Funding: US National Institute on Aging, Alzheimer's Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Korea Health Industry Development Institute, South Korean Ministry of Health and Welfare, South Korean Ministry of Science and ICT, and Spanish Institute of Health Carlos III., Competing Interests: Declaration of interests SAS receives research funding from the Alzheimer's Association and the US National Institutes of Health (NIH). LL receives research funding from the US NIH; consulting fees from Korro Bio; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Biogen and Cell Signaling Technology. NJ-M receives research funding from the Alzheimer's Association and the US NIH. RJB receives research funding from the US NIH, Biogen, AbbVie, Bristol Myers Squibb, Novartis, the US National Intelligence Authority, US National Institute of Neurological Disorders and Stroke, Centene, the Rainwater Foundation, the BrightFocus Foundation, the Association for Frontotemporal Degeneration Biomarkers Initiative, Coins for Alzheimer's Research Trust Fund, the Good Ventures Foundation, Hoffman–La Roche, CogState, Signant, the Cure Alzheimer's Research Trust Fund, Eisai, and C2N Diagnostics; receives royalties or licences from C2N Diagnosticsf payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Korean Dementia Association, the American Neurological Association, Fondazione Prada, Weill Cornell Medical College, Harvard University, Beeson, and Adler Symposium. ZS receives research funding from the BrightFocus Foundation, the Foundation for Barnes-Jewish Hospital, Eli Lilly, the Health Equity Scholars Program, and the Alzheimer's Society of Canada. RAS receives research funding from the US NIH, the Gerald and Henrietta Rauenhorst Foundation, Eli Lilly, the Alzheimer's Assocation, and Eisai and receives consulting fees from AbbVie, Bristol Myers Squibb, Eisai, Eli Lilly, Roche, Prothena, AC Immune, Acumen, Alector, Alnylam, Biohaven, Genentech, Janssen, the Japanese Organization for Medical Device Development, Nervgen, Neuraly, Neurocentria, Oligomerix, Renew, Shionogi, Vigil Neuroscience, Ionis, and Vaxxinity. GSD receives research funcing from the US NIH, the Alzheimer's Association, and the Chan–Zuckerberg Initiative; consulting fees from Parabon Nanolabs and Arialysis Therapeutics; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from PeerView Media, Continuing Education, Eli Lilly, DynaMed, and SixSense Concierge. EM receives research funding from the US National Intelligence Authority, Eisai, Eli Lilly, Roche, and the Gerald and Henrietta Rauenhorst Foundation; consulting fees from AstraZeneca, Sanofi, and Merck; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Alzheimer Association, Projects in Knowledge, and Neurology Live. JPC receives research funding from the US NIH. RJP receives grants from the US NIH. JL is a consultant for and receives grants, contracts, and royalties from Eisai, Eli Lilly, the German Center of Neurodegenerative Diseases, the German Ministry for Research and Education, the Anton and Petra Ehrmann Foundation, the Luneburg Foundation, Innovationsfonds, the Michael J Fox Foundation, CurePSP, the Jerome LeJeune Foundation, the Alzheimer Forschungs Initiative, Deutsche Stiftung Down Syndrom, Else Kroner Fresenius Stiftung, and MODAG. DJS receives consulting fees from Prothena Biosciences and Eisai. CX receives research funding from the US NIH and consulting fees from Diadem. PRS receives research funding from the the US NIH, the Roth Charitable Foundation, the Australian National Health and Medical Research Council, and the Australian Medical Research Future Fund and receives consulting fees from Outside Opinion and Moira Clay Consulting. JJL receives research funding from the German Center for Neurodegenerative Diseases, the German Ministry for Research and Education, the Anton and Petra Ehrmann Foundation, the Lüneburg Foundation, Innovationsfonds, the Michael J Fox Foundation for Parkinson's Research, CurePSP, the Jerome LeJeune Foundation, the Alzheimer Forschungs Initiative, Deutsche Stiftung Down Syndrom, and Else Kröner Fresenius Stiftung; consulting fees from Eisai and Biogen; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Bayer Vital, Biogen, Eisai, Teva, Roche, and Zambon. MJ receives payment or honoraria for lectures, presentations, speakers, bureaus, manuscript writing, or educational events from Eisai. TLSB receives research funding from the US NIH and Siemens; consulting fees from Biogen, Eli Lilly, Eisai, Bristol Myers Squibb, and Johnson & Johnson; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Medscape and PeerView. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor ( APP ), presenilin 1 ( PSEN1 ), or presenilin 2 ( PSEN2 ) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.

Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRI-determined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman's partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology.

Alzheimer disease (AD) and obesity are related to disruptions in the white matter (WM) connectome. We examined the link between the WM connectome and obesity and AD through edge-density imaging/index (EDI), a tractography-based method that characterizes the anatomical embedding of tractography connections. A total of 60 participants, 30 known to convert from normal cognition or mild-cognitive impairment to AD within a minimum of 24 months of follow up, were selected from the Alzheimer disease Neuroimaging Initiative (ADNI). Diffusion-weighted MR images from the baseline scans were used to extract fractional anisotropy (FA) and EDI maps that were subsequently averaged using deterministic WM tractography based on the Desikan-Killiany atlas. Multiple linear and logistic regression analysis were used to identify the weighted sum of tract-specific FA or EDI indices that maximized correlation to body-mass-index (BMI) or conversion to AD. Participants from the Open Access Series of Imaging Studies (OASIS) were used as an independent validation for the BMI findings. The edge-density rich, periventricular, commissural and projection fibers were among the most important WM tracts linking BMI to FA as well as to EDI. WM fibers that contributed significantly to the regression model related to BMI overlapped with those that predicted conversion; specifically in the frontopontine, corticostriatal, and optic radiation pathways. These results were replicated by testing the tract-specific coefficients found using ADNI in the OASIS-4 dataset. WM mapping with EDI enables identification of an abnormal connectome implicated in both obesity and conversion to AD.

The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease., (© 2024. The Author(s).)

Here we report our design and synthesis of 28 new fluorine-containing compounds as potential F-18 radiotracers for CNS imaging of sphingosine-1-phosphate receptor 1 (S1PR1), and determination of their in vitro binding potency and selectivity toward S1PR1 over other S1PR subtypes. Nine potent and selective compounds, 7c&d, 9a&c, 12b, 15b, and 18a-c with IC 50 values ranging from 0.6-12.3 nM for S1PR1 and weak binding toward S1PR2, 3, 4, and 5, were further 18 F-radiolabeled to produce [ 18 F]7c&d, [ 18 F]9a&c, [ 18 F]12b, [ 18 F]15b, and [ 18 F]18a-c. Multi-step F-18 radiochemistry procedures were investigated for radiosynthesis of [ 18 F]7c&d and [ 18 F]9a&c, and the presumed intermediates were synthesized and authenticated by analytic HPLC. We then performed nonhuman primate (NHP) PET brain imaging studies for eight radiotracers: [ 18 F]7c&d, [ 18 F]9a, [ 18 F]12b, [ 18 F]15b, and [ 18 F]18a-c. Three radiotracers, [ 18 F]7c, [ 18 F]7d, and [ 18 F]15b, had high NHP brain uptake with standardized uptake values (SUVs) at 2 h post-injection of 2.42, 2.84, and 2.00, respectively, and good brain retention. Our ex vivo biodistribution study in rats confirmed [ 18 F]7d had a high brain uptake with no in vivo defluorination. Radiometabolic analysis of [ 18 F]7c and [ 18 F]7d in rat plasma and brain samples found that [ 18 F]7c has a more favorable metabolic profile than [ 18 F]7d. However, the trend of increased brain uptake precludes [ 18 F]7c as a suitable PET radiotracer for imaging S1PR1 in the brain. Further structural optmization is warranted to identify a highly S1PR1-specific radiotracer with rapid brain uptake kinetics.

Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C 2 N Diagnostics' PrecivityAD test for Aβ42 and Aβ40. Compared to white individuals, Black individuals had higher average plasma Aβ42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aβ40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aβ42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups., (© 2024. The Author(s).)

Introduction: Alzheimer disease (AD) has a long preclinical phase in which AD pathology is accumulating without detectable clinical symptoms. It is critical to identify participants in this preclinical phase as early as possible since treatment plans may be more effective in this stage. Monitoring for changes in driving behavior, as measured with GPS sensors, has been explored as a low-burden, easy-to-administer method for detecting AD risk. However, driving is a complex, multifaceted process that is likely influenced by other factors, including personality traits, that may change in preclinical AD., Methods: We examine the moderating influence of neuroticism and conscientiousness on longitudinal changes in driving behavior in a sample of 203 clinically normal older adults who are at varying risk of developing AD., Results: Neuroticism moderated rates of change in the frequency of speeding as well as the number of trips taken at night. Conscientiousness moderated rates of change in typical driving space., Conclusions: Personality traits change in early AD and also influence driving behaviors. Studies that seek to utilize naturalistic driving behavior to establish AD risk need to accommodate interpersonal differences, of which personality traits are one of many possible factors. Future studies should explicitly establish how much benefit is provided by including personality traits in predictive models of AD progression., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer Disease (AD) heterogeneity. We employed a deep learning-based multimodal normative framework to analyze individual-level variation across ATN (amyloid-tau-neurodegeneration) imaging biomarkers., Methods: We selected cross-sectional discovery (n = 665) and replication cohorts (n = 430) with available T1-weighted MRI, amyloid and tau PET. Normative modeling estimated individual-level abnormal deviations in amyloid-positive individuals compared to amyloid-negative controls. Regional abnormality patterns were mapped at different clinical group levels to assess intra-group heterogeneity. An individual-level disease severity index (DSI) was calculated using both the spatial extent and magnitude of abnormal deviations across ATN., Results: Greater intra-group heterogeneity in ATN abnormality patterns was observed in more severe clinical stages of AD. Higher DSI was associated with worse cognitive function and increased risk of disease progression., Discussion: Subject-specific abnormality maps across ATN reveal the heterogeneous impact of AD on the brain., Competing Interests: Competing Interests Author AS has received personal compensation for serving as a grant reviewer for BrightFocus Foundation. The remaining authors have no conflicting interests to report.

Objective: We aimed to illustrate how complex cognitive data can be used to create domain-specific and general cognitive composites relevant to Alzheimer disease research., Method: Using equipercentile equating, we combined data from the Charles F. and Joanne Knight Alzheimer Disease Research Center that spanned multiple iterations of the Uniform Data Set. Exploratory factor analyses revealed four domain-specific composites representing episodic memory, semantic memory, working memory, and attention/processing speed. The previously defined preclinical Alzheimer disease cognitive composite (PACC) and a novel alternative, the Knight-PACC, were also computed alongside a global composite comprising all available tests. These three composites allowed us to compare the usefulness of domain and general composites in the context of predicting common Alzheimer disease biomarkers., Results: General composites slightly outperformed domain-specific metrics in predicting imaging-derived amyloid, tau, and neurodegeneration burden. Power analyses revealed that the global, Knight-PACC, and attention and processing speed composites would require the smallest sample sizes to detect cognitive change in a clinical trial, while the Alzheimer Disease Cooperative Study-PACC required two to three times as many participants., Conclusions: Analyses of cognition with the Knight-PACC and our domain-specific composites offer researchers flexibility by providing validated outcome assessments that can equate across test versions to answer a wide range of questions regarding cognitive decline in normal aging and neurodegenerative disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R 2 PET =0.32 vs R 2 PLASMA =0.32, p difference =0.812) and with progression to mild cognitive impairment (Hazard ratio[HR] PET =1.56[1.43-1.70] vs HR PLASMA =1.63[1.50-1.77], p difference =0.627). Combined plasma and PET models were superior to the single biomarker models (R 2 =0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD., Competing Interests: DECLARATION OF INTERESTS R.O. has received research support from Avid Radiopharmaceuticals, Janssen Research & Development, Roche, Quanterix and Optina Diagnostics. He has given lectures in symposia sponsored by GE Healthcare and serves on advisory boards for Asceneuron and Bristol Myers Squibb. SP has acquired research support (for the institution) from ki elements / ADDF and Avid. In the past 2 years, he has received consultancy/speaker fees from Bioartic, Biogen, Esai, Lilly, and Roche. Research programs of WF have been funded by ZonMW, NWO, EU-JPND, EU-IHI, Alzheimer Nederland, Hersenstichting CardioVascular Onderzoek Nederland, Health~Holland, Topsector Life Sciences & Health, stichting Dioraphte, Gieskes-Strijbis fonds, stichting Equilibrio, Edwin Bouw fonds, Pasman stichting, stichting Alzheimer & Neuropsychiatrie Foundation, Philips, Biogen MA Inc, Novartis-NL, Life-MI, AVID, Roche BV, Fujifilm, Eisai, Combinostics. WF holds the Pasman chair. WF is recipient of ABOARD, which is a public-private partnership receiving funding from ZonMW (#73305095007) and Health~Holland, Topsector Life Sciences & Health (PPP-allowance; #LSHM20106). WF is recipient of TAP-dementia (www.tap-dementia.nl), receiving funding from ZonMw (#10510032120003) in the context of Onderzoeksprogramma Dementie, part of the Dutch National Dementia Strategy. TAP-dementia receives co-financing from Avid Radiopharmaceuticals and Amprion. Gieskes-Strijbis fonds also contributes to TAP-dementia. WF has been an invited speaker at Biogen MA Inc, Danone, Eisai, WebMD Neurology (Medscape), NovoNordisk, Springer Healthcare, European Brain Council. WF is consultant to Oxford Health Policy Forum CIC, Roche, Biogen MA Inc, and Eisai. WF participated in advisory boards of Biogen MA Inc, Roche, and Eli Lilly. WF is member of the steering committee of EVOKE/EVOKE+ (NovoNordisk). All funding is paid to her institution. WF is member of the steering committee of PAVE, and Think Brain Health. WF was associate editor of Alzheimer, Research & Therapy in 2020/2021. WF is associate editor at Brain. EvdG has performed contract research for Heuron Inc. and Roche. EvdG has a consultancy agreement with IXICO and Life Molecular Imaging for reading PET scans. CET has research contracts with Acumen, ADx Neurosciences, AC-Immune, Alamar, Aribio, Axon Neurosciences, Beckman-Coulter, BioConnect, Bioorchestra, Brainstorm Therapeutics, Celgene, Cognition Therapeutics, EIP Pharma, Eisai, Eli Lilly, Fujirebio, Instant Nano Biosensors, Novo Nordisk, Olink, PeopleBio, Quanterix, Roche, Toyama, Vivoryon. She is editor in chief of Alzheimer Research and Therapy, and serves on editorial boards of Medidact Neurologie/Springer, and Neurology: Neuroimmunology & Neuroinflammation. She had consultancy/speaker contracts for Eli Lilly, Merck, Novo Nordisk, Olink and Roche. SES has served as a consultant to Eisai and Novo Nordisk and has received speaker fees from Eli Lilly and Medscape. She has analyzed biomarker data provided by C2N Diagnostics. JT has served as a consultant for the Neurotorium educational platform and for Alzheon. PR-N has served at scientific advisory boards and/or as a consultant for Roche, Novo Nordisk, Eisai, and Cerveau radiopharmaceuticals. CCR has received research grants from NHMRC, Enigma Australia, Biogen, Eisai and Abbvie. He is on the scientific advisory board for Enigma/Mellieur Technologies and has consulted for Prothena, Eisai, Roche, and Biogen Australia. RJB laboratory research funding from the National Institutes of Health, Alzheimer’s Association, BrightFocus Foundation, Rainwater Foundation, Association for Frontotemporal Degeneration FTD Biomarkers Initiative, Avid Radiopharmaceuticals, Janssen, Tau Consortium, Novartis, Centene Corporation, Association for Frontotemporal Degeneration, the Cure Alzheimer’s Fund, Coins for Alzheimer’s Research Trust Fund, The Foundation for Barnes-Jewish Hospital, Good Ventures Foundation, DIAN-TU Pharma Consortium, Tau SILK Consortium (AbbVie, Biogen, Eli Lilly, and an anonymous organization), the NfL Consortium (AbbVie, Biogen, Bristol Meyers Squibb, Hoffman La Roche), and the Tracy Family SILQ Center; having equity ownership interest in C2N Diagnostics and receiving income based on technology licensed by Washington University to C2N Diagnostics; and receiving income from C2N Diagnostics for serving on the scientific advisory board. OH has acquired research support (for the institution) from AVID Radiopharmaceuticals, Biogen, C2N Diagnostics, Eli Lilly, Eisai, Fujirebio, GE Healthcare, and Roche. In the past 2 years, he has received consultancy/speaker fees from AC Immune, Alzpath, BioArctic, Biogen, Bristol Meyer Squibb, Cerveau, Eisai, Eli Lilly, Fujirebio, Merck, Novartis, Novo Nordisk, Roche, Sanofi and Siemens. SCJ has served in the past two years on advisory boards for Enigma Biomedical and ALZPath. The other authors report no competing interests.

Importance: Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD)., Objective: To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment., Design, Setting, and Participants: From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed., Interventions: In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks., Main Outcomes and Measures: Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL., Results: Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo., Conclusions and Relevance: This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification., Trial Registration: ClinicalTrials.gov Identifier: NCT04623242.

Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To develop a deep learning model to classify minimally processed brain PET scans as amyloid positive or negative, evaluate its performance on independent data sets and different tracers, and compare it with human visual reads. Materials and Methods This retrospective study used 8476 PET scans (6722 patients) obtained from late 2004 to early 2023 that were analyzed across five different data sets. A deep learning model, AmyloidPETNet, was trained on 1538 scans from 766 patients, validated on 205 scans from 95 patients, and internally tested on 184 scans from 95 patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) fluorine 18 ( 18 F) florbetapir (FBP) data set. It was tested on ADNI scans using different tracers and scans from independent data sets. Scan amyloid positivity was based on mean cortical standardized uptake value ratio cutoffs. To compare with model performance, each scan from both the Centiloid Project and a subset of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study were visually interpreted with a confidence level (low, intermediate, high) of amyloid positivity/negativity. The area under the receiver operating characteristic curve (AUC) and other performance metrics were calculated, and Cohen κ was used to measure physician-model agreement. Results The model achieved an AUC of 0.97 (95% CI: 0.95, 0.99) on test ADNI 18 F-FBP scans, which generalized well to 18 F-FBP scans from the Open Access Series of Imaging Studies (AUC, 0.95; 95% CI: 0.93, 0.97) and the A4 study (AUC, 0.98; 95% CI: 0.98, 0.98). Model performance was high when applied to data sets with different tracers (AUC ≥ 0.97). Other performance metrics provided converging evidence. Physician-model agreement ranged from fair (Cohen κ = 0.39; 95% CI: 0.16, 0.60) on a sample of mostly equivocal cases from the A4 study to almost perfect (Cohen κ = 0.93; 95% CI: 0.86, 1.0) on the Centiloid Project. Conclusion The developed model was capable of automatically and accurately classifying brain PET scans as amyloid positive or negative without relying on experienced readers or requiring structural MRI. Clinical trial registration no. NCT00106899 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Bryan and Forghani in this issue.

Objective: Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD., Method: Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials., Results: Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites., Conclusions: Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

Introduction: Previous approaches pursuing in vivo staging of tau pathology in Alzheimer's disease (AD) have typically relied on neuropathologically defined criteria. In using predefined systems, these studies may miss spatial deposition patterns which are informative of disease progression., Methods: We selected discovery (n = 418) and replication (n = 132) cohorts with flortaucipir imaging. Non-negative matrix factorization (NMF) was applied to learn tau covariance patterns and develop a tau staging system. Flortaucipir components were also validated by comparison with amyloid burden, gray matter loss, and the expression of AD-related genes., Results: We found eight flortaucipir covariance patterns which were reproducible and overlapped with relevant gene expression maps. Tau stages were associated with AD severity as indexed by dementia status and neuropsychological performance. Comparisons of flortaucipir uptake with amyloid and atrophy also supported our model of tau progression., Discussion: Data-driven decomposition of flortaucipir uptake provides a novel framework for tau staging which complements existing systems., Highlights: NMF reveals patterns of tau deposition in AD. Data-driven staging of flortaucipir tracks AD severity. Learned flortaucipir patterns overlap with AD-related gene expression., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD., Methods: 445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants., Findings: We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β = 0.59), but then tau burden elevated relative to spread (β = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83)., Interpretation: Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design., Funding: This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund., Competing Interests: Declaration of interests Data collection and sharing for this project was supported by the Dominantly Inherited Alzheimer Network (DIAN, U19-AG032438) funded by the National Institute on Aging (NIA), the Alzheimer's Association (SG-20-690363-DIAN), the German Center for Neurodegenerative Diseases (DZNE), the Queen Square Dementia Biomedical Research Centre and the Medical Research Council Dementias Platform UK (MR/L023784/1 and MR/009076/1). Partial support has also been provided by research and development grants for dementia from the Japan Agency for Medical Research and Development (JP22dk0207049), AMED, the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), Korea Dementia Research Center (KDRC) funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (HI21C0066), the Spanish Institute of Health Carlos III (ISCIII), the Canadian Institutes of Health Research (TAD-125697), the Canadian Consortium of Neurodegeneration and Aging, the Brain Canada Foundation, Fonds de Recherche du Québec, and the Raul Carrea Institute for Neurological Research (FLENI). In addition to the acknowledged funding sources for this research, the authors of this manuscript have received financial support from the National Institutes of Health (BMA, TLSB, JH, JCM, CX), National Institute on Aging (AJA, RJB, CC), National Institute of Neurological Disorders and Stroke (RJB), Alzheimer's Association (RJB, CC), DIAN-TU-001 Tau NextGen and OLE (RJB), Biogen (RJB), AbbVie (RJB), Bristol Myers Squibb (RJB), Novartis (RJB), Centene Corporation (RJB), Rainwater Foundation (RJB), Association for Frontotemporal Degeneration FTD Biomarkers Initiative (RJB), BrightFocus Foundation (RJB), Cure Alzheimer's Fund (RJB), Coins for Alzheimer's Research Trust Fund (RJB), Eisai (RJB), The Foundation for Barnes-Jewish Hospital (RJB), TargetALS (RJB), Good Ventures Foundation (RJB), DIAN-TU Pharma Consortium (RJB), Eli Lilly (RJB, TLSB), Avid Radiopharmaceuticals (TLSB), Hoffman-La Roche (RJB), CogState (RJB), Signant (RJB), Siemens (TLSB), and Michael J. Fox Foundation (CC). Travel support was received from Hoffman-La Roche (RJB), Alzheimer's Association Roundtable (RJB), Duke Margolis Alzheimer's Roundtable (RJB), BrightFocus Foundation (RJB), Tau Consortium Investigator's Meeting (RJB), Fondazione Prada (RJB), NAPA Advisory Council on Alzheimer's Research (RJB), and Somalogics (CC). Consultations have been declared for Biogen (TLSB), Eli Lilly (TLSB), Eisai (TLSB), Siemens (TLSB), Bristol Myers Squibb (TLSB), Alector (CC), Circular Genomics (CC), Parabon Nanolabs (JH), Hoffman-La Roche (JH), AlzPath (JH), Prothena (JH), Barcelona Brain Research Center (JCM), Native Alzheimer Disease-Related Resource Center in Minority Aging Research (JCM), and Diadem (CX). Honoraria was received from Korean Dementia Association (RJB), American Neurological Association (RJB), Fondazione Prada (RJB), Weill Cornell Medical College (RJB), Harvard University (RJB), Biogen (TLSB), Eisai (TLSB), Montefiore Grand Rounds NY (JCM), and Tetra-Inst ADRC seminar series Grand Rounds NY (JCM). Patents have been declared for NfL as a marker for ICANs due to CAR-T (BMA), methods for measuring the metabolism of CNS derived biomolecules in vivo (RJB), methods for measuring the metabolism of neutrally derived biomolecules in vivo (RJB), plasma based methods for detecting CNS amyloid disposition (RJB), plasma based methods for determining A-Beta amyloidosis (RJB), methods of treating based on site-specific tau phosphorylation (RJB), and tau kinetic measurements (RJB). Authors participated on advisory boards for VID (BMA), NNTC (BMA), Hoffman-La Roche/Genentech (RJB), Biogen (RJB), UK Dementia Research Institute at University College London (RJB), Stanford University (RJB), Next Generation Translational Proteomics for Alzheimer's and Related Dementias (RJB), C2N Diagnostics (RJB), Eisai (TLSB), Siemens (TLSB), Eli Lilly (TLSB), Bristol Myers Squibb (TLSB), NIH-sponsored external advisor grants (TLSB), NIA-sponsored Caring Bridge and Wall-E (JH), Cure Alzheimer's Fund Research Strategy Council (JCM), Indiana University LEADS Advisory Board (JCM), and FDA Advisory Committee on Imaging Medical Products (CX). Other declared interests include royalties with equity ownership from C2N Diagnostics (RJB), partnering and receiving stock from Circular Genomics (CC), and being the executive director of DIAN (AD). Participation in the ASNR Alzheimer's and ARIA Study Group, QIBA Amyloid PET Working Group, Alzheimer's Association Clinical Tau PET Work Group, and American College of Radiology/AlzNet Work Group (TLSB). Precursors for radiopharmaceuticals and technology transfer were received from Avid Radiopharmaceuticals/Eli Lilly, LMI, and Cerveau/Lantheus (TLSB). Drugs and services were received from Eisai, Janssen, and Hoffman- La Roche for the DIAN-TU Next Generation Trial and DIAN-TU Gantenerumab Open Label Extension (RJB). All other authors have nothing to disclose., (Copyright © 2024. Published by Elsevier B.V.)