Down syndrome (DS) represents a genetic form of Alzheimer's disease (AD) with an earlier expected symptom onset compared to late onset AD (LOAD). It is thought that the extra copy of the Amyloid Precursor Protein ( APP ) gene, located on chromosome 21 contributes to the earlier onset due to increased amyloid deposition in the brain. Hyperphosphorylation of tau protein is also thought to be elevated in the beginning stages of AD pathology within DS. Although APOE ε4 has been associated with greater AD risk in LOAD, prior cross-sectional investigations into the effects of APOE ε4 in DS have suggested that there is no additional impact of APOE ε4 on the accumulation of amyloid. We aimed to extend this work by examining the associations between longitudinal plasma pTau217 and amyloid PET as a function of APOE ε4 status. Participants with DS were recruited from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. Both p -tau217 ( N  = 564 results from 223 individuals including 122 that had 3 results each, Lilly MSD) and Amyloid PET ([11C]-PiB or [18F]-AV45) ( N  = 366 scans with 253 unique participants including 113 that had 2 scans each) were acquired. We analyzed the influence ɛ4 allele carrier status had on changes in pTau217 and amyloid across age using linear mixed-effects modeling, including the age, APOE ε4 carrier status and their interaction as covariates. Age was also included as a covariate. Individuals that are carriers of the APOE ε4 allele present with similar baseline amyloid and pTau217 values ( p  = .591 & p  = .455 respectively). The rate of amyloid and pTau217 accumulation increased across age similarly for both groups ( p  = .772 & p  = .657 respectively). Although not statistically significant, visual inspection suggests that, with a larger number of participants, individuals between the ages of 45 and 50 who are ɛ4 allele carriers may exhibit elevated pTau217 levels compared to non-carriers. We did not observe increased amyloidosis or tau phosphorylation in APOE ε4 carriers with DS. Future studies targeting individuals aged 45-50 are suggested to investigate the potential APOE ε4 effect on tau phosphorylation observed in this narrow chronological window, which is close to the average expected age of symptom onset of 52.5 years for DS.

Characterizing the timing and progression of Alzheimer’s disease biomarker onset in Down syndrome (DS) and contrasting potential timing differences with neurotypical adults is needed to identify optimal Alzheimer’s disease therapeutic treatment windows in DS. In this study, 198 adults with DS from the Alzheimer Biomarker Consortium – Down Syndrome and 172 neurotypical adults from the Wisconsin Registry for Alzheimer’s Prevention with available longitudinal beta-amyloid PET, tau PET and plasma p-tau217 analyzed on Lilly MSD were included. Individuals with DS had a significantly higher lifetime risk of beta-amyloid plaque onset. Temporal modeling of longitudinal biomarker measures revealed earlier age at positivity of beta-amyloid plaques, p-tau217 and neurofibrillary tau tangles in DS relative to the neurotypical cohort. The onset of p-tau217 and tau PET positivity in DS occurred nearly simultaneously, roughly 4-6 years following beta-amyloid onset, whereas the neurotypical group displayed greater temporal latency between positivity of the two biomarkers. The early and simultaneous onset of these biomarkers in DS highlights the necessity for early therapeutic interventions in this population. This work, combined with the upcoming anti-amyloid safety and efficacy clinical trials for DS will help identify optimal treatment windows for these individuals.

This longitudinal study including four independent cohorts assessed the spatiotemporal dynamics of tau extent and load changes in Alzheimer's disease using tau positron emission tomography data from 2,459 participants, including 898 followed for up to 7 years. Regional standardized uptake value ratios indexed tau load, whereas the spatial extent of tauopathy (SEOT) (proportion of abnormal voxels) measured tau extent. We observed burden-dependent longitudinal dynamics of tau progression: SEOT showed greater sensitivity to increases over time in regions with low baseline tau burden, whereas the standardized uptake value ratio was more informative for tracking accumulation once regional burden was established. This pattern was consistent across Braak regions and cohorts and was reflected in differential associations with other Alzheimer's disease severity markers. These findings refine models of tau propagation by suggesting that tau positron emission tomography changes may be differentially captured by extent-based and load-based metrics at different stages of disease progression, highlighting SEOT as a promising surrogate outcome for trials.

Background: The Apolipoprotein E (APOE) ε4 allele increases the risk of Alzheimer's disease (AD), while the APOEε2 allele reduces risk, particularly in females in the neurotypical population. However, the effect of APOE haplotype and sex on AD in Down syndrome (DS) is unclear. Prior work has been limited by sample size, but here we aggregate the two largest APOE-genotyped cohorts of individuals with DS to date. Methods: We examined the impact of APOE genotype on AD biomarkers and cognitive performance in 1,212 individuals with DS. All participants underwent APOE testing and clinical evaluations. Subsets also completed assessments for amyloid (amyloid PET, CSF Aβ42/40, plasma pTau217), neuroinflammation (plasma glial fibrillary acidic protein [GFAP]), neurodegeneration (plasma neurofilament light [NfL] and structural MRI), and cognition (modified Cued Recall Test [mCRT]). Results: APOEε2 was protective, associated with lower amyloid PET uptake and delayed cognitive impairment. In contrast, APOEε4 was associated with lower CSF Aβ42/Aβ40, worse mCRT performance, and earlier cognitive impairment. These effects were more pronounced in females. Conclusion: APOE allele and biological sex interact to influence AD pathology and symptom onset in DS. Clinical trials, especially anti-amyloid therapies, should consider APOE status for intervention timing. Funding: Data collection and sharing for this project was supported by the ABC-DS (U01AG051406, U01AG051412, and U19 AG068054-04), funded by the National Institute on Aging and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. JKW receives support from the NIH (KL2TR002346). Declaration of Interest: JF reports grants from the Fondo de Investigaciones Sanitario, Carlos III Health Institute (INT21/00073, PI20/01473 and PI23/01786 to JF) and the Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED) Program 1, jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, Una manera de hacer Europa. This work was also supported by the National Institutes of Health grants (1R01AG056850-01A1; R21AG056974, R01AG061566, 1R01AG081394-01 and 1R61AG066543-01 to JF), the Department de Salut de la Generalitat de Catalunya (SLT006/17/00119 to JF), Fundación Tatiana Pérez de Guzmán el Bueno (IIBSP-DOW-2020-151). It was also supported by Horizon 2020 - Research and Innovation Framework Programme from the European Union (H2020-SC1- BHC-2018-2020 to JF). DA acknowledges support from Institute of Health Carlos III (ISCIII), Spain (PI18/00435, PI22/00611, PI25/00422, INT19/00016, INT23/00048) jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, “Una manera de hacer Europa”, and by the Department of Health Generalitat de Catalunya PERIS program (SLT006/17/125, SLT042/25/000034). He also received support for Research Groups funding from the Department of Research and Universities from the Generalitat de Catalunya (2021 SGR 00979). AB acknowledges support from Instituto de Salud Carlos III and co-funded by the European Union through the Miguel Servet grant (CP20/00038) and Fondo de Investigaciones Sanitario (PI22/00307), the Alzheimer's Association (AARG-22-923680), and the Ajuntament de Barcelona, in collaboration with Fundació La Caixa (23S06157-001). LDHS acknowledges support from Instituto de Salud Carlos III through the Miguel Servet grant “CP24/00112” co- funded by the European Union, and the the Jérôme Lejeune Foundation (2326 - GRT-2024A). María Carmona-Iragui acknowledges support from Instituto de Salud Carlos III (ISCIII) (PI18/00335, PI22/00758, ICI23/00032); Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas CIBERNED Program 1, partly jointly funded by Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea, Una Manera de Hacer Europa; Alzheimer's Association (AARG‐22‐973966); the Global Brain Health Institute (GBHI_ALZ‐18‐543740); the Jérôme Lejeune Foundation (#1913 cycle 2019B; #2425 cycle 2024B). MRA was supported by the Alzheimer’s Association Research Fellowship to Promote Diversity (AARF-D) Program (AARFD-21-852492) from 2022 until 2025. LVA is supported by the Sara Borrell postdoctoral fellowship from Institute of Health Carlos III (ISCIII), Spain (CD23/00235). BLH has received research funding from Roche and Autism Speaks; receives royalties from Oxford University Press for book publications; and is the chair of the data safety and monitoring board for the Department of Defense-funded study, “Comparative Effectiveness of EIBI and MABA”. BTC receives research funding from the National Institutes of Health. EH receives research funding from the National Institutes of Health and the BrightFocus Foundation. FL is supported by grants from the National Institute on Aging. HDR has received funding from the National Institutes of Health and is on the scientific advisory committee for the Hereditary Disease Foundation. JHL has received research funding from the National Institutes of Health and the National Institute on Aging. BMA receives research funding from the National Institutes of Health and has a patent (“Markers of Neurotoxicity in CAR T patients”). MSR has received consulting fees from AC Immune and Ionis, Alzheon, Alnylam, Biohaven, Embic, Positrigo and Prescient Imaging. He has received research support from the National Institutes of Health, Eisai and Lilly.. All other authors declare no competing interests. Lucia Maure-Blesa was supported by Instituto de Salud Carlos III through the Río Hortega Fellowship “CM23/00291” and co-funded by the European Union. SG acknowledges support from Institute of Health Carlos III (ISCIII), Spain (PI20/00836) jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, “Una manera de hacer Europa”; the Global Brain Health Institute (GBHI_ALZ-23-971107); the Jérôme Lejeune Foundation (#1801 Cycle 2020), Fundación Tatiana Pérez de Guzmán el Bueno (IIBSP-DOW-2020-151 to JF and SG) ODI reports grants from the Fondo de Investigaciones Sanitario, Carlos III Health Institute (PI21/01395 and PI24/01087 to ODI) jointly funded by Fondo Europeo de Desarrollo Regional, Unión Europea, Una manera de hacer Europa, the Jérôme Lejeune Foundation (#202307 to ODI) and the Alzheimer’s Association (AARF-22–924456)" Ethical Approval: Latest Approval dates for ABC-DS: Advarra sponsor #Pro00044843- 4/3/2025 (exp 4/3/2026), Advarra IBR (#Pro00044843) - 4/3/2025 (exp 4/3/2026 - currently submitted for continuing review), Advarra CUIMC (#Pro00044843) - 3/28/2025 (exp 3/28/2026 - currently submitted for continuing review), NKI IRB #8187 - 6/30/25 - reliance agreement approval (exp is Advarra's date 4/3/2026), CUIMC IRB #AAAU0596 - 4/11/2025 (exp 3/28/2026).

Down syndrome is characterized by triplication of chromosome 21, leading to early-onset Alzheimer disease pathology, with nearly all individuals with Down syndrome developing amyloid and tau pathology. In the new era of amyloid modifying therapies, it is vital to identify early biomarkers for Alzheimer disease (AD) pathology in Down syndrome. Striatal amyloid may begin to accumulate sooner than cortical amyloid in Down syndrome. Tau phosphorylation at specific sites, including 217, can be quantified in plasma and may represent an important mechanistic step in the development of tau pathology. This study had two aims: 1. To compare the relative age at increase of multiple biomarkers (cortical amyloid, striatal amyloid, plasma pTau217 and summary tau pathology) 2. To test whether plasma pTau217 can identify both the current presence and likely future accumulation of amyloid and tau pathology. To identify optimal biomarkers for early intervention, we examined longitudinal cortical and striatal amyloid PET, plasma pTau217, and tau PET in 328 individuals with Down syndrome enrolled in the Alzheimer Biomarker Consortium – Down Syndrome study. To compare the timing of biomarker changes, we modeled longitudinal biomarkers using generalized additive mixed models relative to age. We used receiver operating characteristic curve analysis to identify thresholds for both current and likely future accumulation of amyloid and tau pathology. For all comparisons, we used age as the null model, performing Delong tests to evaluate the performance of age relative to biomarker-based prediction. Imaging biomarkers increased around 40 years old, with plasma pTau217 increasing somewhat later than the three PET biomarkers. Striatal amyloid increased before cortical amyloid in some participants; however, this was not uniform across individuals. If an individual was classified as a reliable accumulator with one biomarker, he or she was likely to be a reliable accumulator in other biomarkers. Age was as sensitive as plasma pTau217 in its ability to both detect preclinical Alzheimer disease pathology and predict near future accumulation of both amyloid and tau. These results suggest that all adults with Down syndrome should be screened for Alzheimer disease pathology starting shortly before age 40 and considered for clinical trials. Age alone was as effective at detecting both current pathology and likely future accumulation as plasma pTau217. Because this disease is so closely concurrent with age in individuals with Down Syndrome, plasma pTau217 may not provide more diagnostic benefits than age.

BACKGROUND AND OBJECTIVES:There is a paucity of research on the role of circadian rhythm disruption in Alzheimer disease (AD)-related cognitive impairments in adults with Down syndrome (DS). The aim of this study was to examine the association of the 24-hour rest-activity rhythm with cognition, dementia symptoms, and clinical AD status in adults with DS. METHODS:In this cross-sectional study, adults with DS aged 25-61 years in the Alzheimer's Biomarkers Consortium-Down Syndrome underwent wrist-worn actigraphy (≥4 days) and cognitive assessment. Primary variables included interdaily stability, intradaily variability, relative amplitude, most active 10-hour period (M10), and least active 5-hour period (L5). Secondary measures included coefficient of variation of total sleep time, sleep midpoint, sleep efficiency, and the sleep regularity index. Cognitive outcomes included modified Cued Recall Test (mCRT), Wechsler Block Design with Haxby Extension (Block Design), Purdue Pegboard, Cat and Dog Modified Stroop Task, DS Mental Status Examination (DSMSE), National Task Group-Early Detection Screen for Dementia (NTG-EDSD), Dementia Questionnaire for People with Learning Disabilities (DLD), and clinical AD status based on a case consensus process (stable vs mild cognitive impairment [MCI]/dementia). Linear and logistic regression models were adjusted for age, sex, intellectual disability level, site, and obstructive sleep apnea severity, with false discovery rate (FDR) correction. RESULTS:Of 115 participants (mean age 40.0 ± 9.2 years; 43.5% female), higher interdaily stability was associated with higher DSMSE scores B = 20.6 (95% CI 5.0-36.2). Higher intradaily variability was associated with worse cognitive performance and increased dementia symptoms: mCRT B = -9.2 (95% CI -15.2 to -3.1), Block Design B = -11.0 (95% CI -19.0 to -3.0), DSMSE B = -12.0 (95% CI -20.1 to -3.9), and DLD-cognitive B = 6.3 (95% CI 3.0-10.5). Lower M10 was associated with increased dementia symptoms: NTG-EDSD B = -0.004 (95% CI -0.008 to -0.001); DLD-cognitive B = -0.004 (95% CI -0.006 to -0.001), and DLD-social B = -0.003 (95% CI -0.005 to -0.0008). All associations remained significant after FDR correction (p < 0.05). Fifteen participants had MCI/dementia. Higher intradaily variability was associated with increased odds of MCI/dementia (OR: 1.45; 95% CI 1.04-2.29) although this was not significant after FDR correction. DISCUSSION:Fragmentation and low amplitude of the 24-hour rest-activity rhythm are associated with AD-related cognitive impairment, dementia symptoms, and increased odds of MCI/dementia in adults with DS. Circadian rhythm disruption may contribute to AD-related outcomes in adults with DS and potentially serve as a modifiable risk factor.

OBJECTIVE:Adults with Down syndrome (DS) often show elevated systemic inflammation, but the association with obesity, aging, and Alzheimer's disease (AD) pathology is not well understood. METHODS:Data were drawn from 188 nondemented adults with DS participating in the Alzheimer Biomarkers Consortium-DS (ABC-DS). Participants completed clinical assessments, blood draws, and neuroimaging. Plasma biomarkers included indicators of general, pro-, and anti-inflammation. Mixed linear models tested associations between BMI, age, PET-measured amyloid burden, and inflammatory biomarkers, adjusting for sex, trisomy type, and collection site. False discovery rate correction was applied. RESULTS:The majority of the participants met criteria for obesity. Higher BMI was significantly associated with elevated levels of CRP, IL-6, TNF-α, B2M, IL-18, and slCAM-1 (p < 0.05). Older age was significantly associated with higher B2M (β = 1.22e + 05, p < 0.001). Amyloid burden was positively associated with IL-6 (β = 0.005, p = 0.037). CONCLUSIONS:Obesity, aging, and amyloid burden relate to systemic inflammation in adults with DS. Obesity showed the strongest and most consistent associations, emphasizing the value of regular monitoring and weight management strategies to help reduce inflammation. Aging and early amyloid accumulation showed more limited links with systemic inflammation; future work should examine whether these processes are more closely related to biomarkers of neuroinflammation as AD progresses.

Understanding the rate of tau accumulation is critical for staging Alzheimer disease (AD), monitoring its progression, and informing clinical trial design. Although PET imaging with 18F-MK-6240, also known as florquinitau, can track tau pathology, longitudinal data remain limited. We evaluated longitudinal tau changes using 18F-MK-6240 PET across cognitive stages and analyzed regional rates of change with the goal of informing future clinical trial outcome measures. Methods: In this observational study, 27 participants with varying cognitive statuses (cognitively unimpaired [CU], mild cognitive impairment [MCI], and AD) underwent 18F-MK-6240 PET at baseline and at 6, 12, and 24 mo (or at 18 and 30 mo during the COVID-19 pandemic). Amyloid positivity at baseline was determined with 11C-labeled Pittsburgh compound B PET. Tau PET data were analyzed as SUV ratios (SUVRs) in regions of interest (ROIs) corresponding to Braak staging as well as the inferior temporal gyrus and 2 composite ROIs (metatemporal composite [MTC]) and an early tau composite. Annualized SUVR changes were compared across groups and correlated with cognitive scores (Mini-Mental State Examination, Clinical Dementia Rating Scale, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale) using the Kruskal-Wallis test. Correlations between the change in SUVR and cognitive outcomes were estimated using Spearman ρ. Results: Baseline 18F-MK-6240 PET showed a minimal signal in CU participants, localized signal to the medial temporal lobe in participants with MCI, and a signal spanning the inferolateral temporal lobe and extending posteriorly along the ventral cortex in participants with AD. Longitudinal analysis showed that the annualized percent change in tau deposition in the MTC was 0.17% ± 4.16, 5.77% ± 2.97, and 4.31% ± 5.84 in the CU, MCI, and AD groups, respectively (P = 0.075). The change in tau deposition was 0.00 ± 0.05, 0.10 ± 0.07, and 0.12 ± 0.16 in the CU, MCI, and AD groups, respectively (P = 0.039). Tau accumulation correlated with a decline on the Alzheimer Disease Assessment Scale-Cognitive Subscale (ρ = 0.43, P < 0.05). Conclusion: 18F-MK-6240 PET tracked tau accumulation over time and provided preliminary evidence that these changes correlate with cognitive decline, supporting its utility for longitudinal AD studies and trial design, with MTC emerging as a promising ROI for clinical trials.

Alzheimer's disease progresses heterogeneously across diverse cohorts, yet current predictive models fail to capture this complexity while remaining clinically interpretable. Here we present a multi-dimensional attention framework that simultaneously captures both temporal dynamics and biomarker importance to predict disease progression across three fundamentally different populations: the general late-onset population using the Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) dataset (N=1669), cases with Down Syndrome-associated Alzheimer's disease using the Alzheimer's Biomarker Consortium - Down Syndrome (ABC-DS) dataset (N=396), and cases with autosomal dominant Alzheimer's disease using the Dominantly Inherited Alzheimer Network (DIAN) dataset (N=425). Trained on each dataset independently, our framework achieved multi-class Area Under the Receiver Operating Characteristic Curve (mAUC) values of 0.793 (TADPOLE), 0.680 (ABC-DS), and 0.902 (DIAN) when predicting individuals' future diagnostic status (cognitively normal/stable, mild cognitive impairment, or Alzheimer's disease) from their longitudinal biomarker history, outperforming conventional approaches. The model generates individual-specific attention maps revealing distinct biomarker importance over time. Transfer learning from TADPOLE-which included neuroimaging data-improved prediction performance on the imaging-free ABC-DS dataset from 0.680 to 0.771, demonstrating that disease mechanisms transcend both etiological boundaries and data modalities. Ultimately, this framework could enable precision medicine approaches for data-limited cohorts across the Alzheimer's disease spectrum.

Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self-reported sex, educational attainment and race/ethnicity on amyloid-positivity, and tau-PET-positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Logistic generalized estimating equations were used to estimate frequency of amyloid-positivity (using cohort-specific thresholds for amyloid-PET [84%] or CSF) and tau-PET-positivity (cohort-specific thresholds of 2SD above mean temporal uptake in amyloid-negative controls). We assessed: i) sex and APOEε4 ( N  = 10,098) associations, to complement earlier findings of a higher frequency of tau-positivity in females, ii) effects of lower/higher education ( N  = 10,970; cohort-specific median-split), and iii) effects of race/ethnicity (non-Hispanic White [hereafter: White], N  = 4880; Asian, N  = 116; Black or African-American [hereafter: Black], N  = 353; Hispanic, N  = 356, only from Northern-American cohorts). Outcomes were frequency of amyloid-positivity in CU individuals only, and tau-PET-positivity in both amyloid-positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau-positivity were assessed and only retained in the models when significant. Female sex was associated with an APOEε4 -independent increased frequency of amyloid-positivity (β=0.51[0.22], p  = 0.02) in CU and increase of tau-positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p  <0.01). Remarkably, tau-positivity frequencies of female APOEε4 non-carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid-positivity frequency (β=-0.12[0.05], p  = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau-positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p  <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non-White groups compared to White (Hispanic:β interaction =-0.05[0.01], p  <0.01; Black:-0.04[0.01], p  <0.01; Asian:-0.02[0.01], p  = 0.04). This suggests that the impact of age on amyloid-positivity was less pronounced in non-White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau-positivity frequency than White (β=0.51[0.22], p  = 0.02; Figure 3). In this multi-center initiative comprised of clinical and community-based cohorts, we observed that self-reported sex, educational attainment and race/ethnicity were related to positivity-frequencies of Alzheimer's disease pathology.

INTRODUCTION:It is unknown if neurodegeneration trajectories differ between Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD), both of which are genetic forms of Alzheimer's disease (AD). METHODS:We compared brain volumes in DS, ADAD, and unaffected family members serving as controls. Participants underwent magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET), deriving volumetric and amyloid burden, respectively. Nonlinear associations between regional volumes and estimated years to clinical symptom onset (EYO) were evaluated using generalized additive mixed-models. RESULTS:Longitudinal data from 267 controls, 341 participants with DS, and 358 participants with ADAD were included, totaling 1908 scans. DS volumes were lower than ADAD and controls initially and dropped linearly. ADAD had similar volumes to controls until diverging, beginning at EYO -7. Amyloid was negatively associated with volume, with similar slopes in DS and ADAD. DISCUSSION:ADAD and DS demonstrate distinct patterns of brain volume decline prior to symptom onset despite being similarly affected by amyloid.

Previous work in the Down syndrome (DS) population has revealed early and accelerated accumulation of Alzheimer's disease (AD) pathology when compared with neurotypical adults. Temporal models of [ 11 C]PiB PET beta-amyloid (Aβ) trajectories aligned with the progression of [ 18 F]flortaucipir neurofibrillary tau (NFT) burden through Braak-associated regions (Zammit 2023). These analyses were extended to a larger DS cohort that includes individuals who underwent Aβ imaging with [ 18 F]florbetapir. This work investigated the temporal relationship between regional NFT burden and a standardized model of Aβ onset in the DS population. 282 participants with DS underwent longitudinal NFT and Aβ PET imaging (Table 1). PiB and florbetapir scans underwent Centiloid (CL) processing using a previously calibrated pipeline. Flortaucipir scans were realigned, summed 80-100 min, and warped into standard space. SUVR was calculated (inferior cerebellar grey reference) for Braak-associated NFT regions (described in Figure 1). Using the sampled iterative local approximation (SILA) method, the average rate of change was discretely sampled across the CL range, yielding a generalized model for amyloid progression. The estimated time-to-Aβ onset (or Aβ chronicity) was calculated for each participant by aligning their trajectories to the model. Flortaucipir SUVR and % Change were binned within discrete Aβ chronicity stages and fit to a linear mixed effects model for each region, using: SUVR or % Change ∼ Age+Sex+Scanner+APOE4+Chronicity Stage+Cognitive Status+(1|Participant) The model was used to estimate the influence of biological parameters and the relative time of significant NFT onset. Across all NFT regions, participants with dementia had the highest flortaucipir SUVR and latest chronicity, followed by MCI (Figure 1). SUVR was significantly increased by the 0-5 years chronicity window in NFT I and II, while NFT III-VI were not significantly increased until 5-10 years (Figure 2). % Change was significantly increased in the 0-5 years chronicity window for NFT I and in the >10 years window for NFT III-VI. Scanner, cognitive status, and age effects were significant in each region. This work supports previous findings that NFT regions I-II demonstrate earlier increases to flortaucipir SUVR than other NFT regions when using a standardized temporal model for Aβ onset.

Because of the high incidence of Alzheimer's disease (AD) amyloid-b pathology in individuals with Down syndrome (DS), they are considered an ideal target population for anti-amyloid therapy trials. However, not all individuals with DS develop dementia. Intra-individual cognitive variability (IICV) is proposed to be a sensitive marker for pre-clinical changes in AD, but has not yet been tested in individuals with DS. Using the ABC-DS (Alzheimer's Biomarker Consortium-DS) data, we characterize the relationships between baseline IICV with dementia status, cognitive decline and brain amyloid-b (using positron emission tomography (PET)) in adults with DS. Data from the ABC-DS study, includes 460 adults with DS ranging from 25 to 81 years of age (mean age 43.27, 45.7% female) at baseline and mean follow up of 40 months (standard deviation of 7.8 months). All participants had complete neuropsychological evaluations at baseline and follow up, and consensus dementia diagnosis and brain PET amyloid-b measures in centiloids. IICV measures for memory, executive function and combined memory and executive functions were calculated. Regression models were used to examine the associations between baseline IICV scores with dementia at follow up, clinical presentation worsening from baseline to follow up, more than one standard deviation below the mean change in general cognition considering the level of intellectual disability, as well as PET amyloid-b at baseline and follow up, adjusting for age, sex, intellectual disability, site, presence of APOEe4 and time latency between baseline and follow up. We adjusted for multiple comparisons using Bonferroni correction. IICV for memory and executive functions was associated with all outcomes tested (odds ratio ranged from 4.4 to 17.2, p  <0.05), except for PET amyloid-b at follow up. The associations of baseline IICV and dementia at follow up persisted with the additional adjustment of cognitive performance on the tests included in the IICV measure. IICV appears be an early indicator of dementia in individuals with DS. Future studies are needed to understand whether IICV can contribute to clinical trials assessing potential candidates for secondary prevention and what are the underlying mechanisms related to within-person cognitive variability and the development of AD neuropathology in this population.

INTRODUCTION:Adults with Down syndrome (DS) are at risk for Alzheimer's disease (AD), yet identifying the preclinical phase remains challenging. Intraindividual cognitive variability (IICV) may be a sensitive marker of early AD-related changes but remains understudied in DS. METHODS:Adults from the Alzheimer's Biomarker Consortium-DS (ABC-DS) study (N = 460, mean age 43.3 years; 45.7% female) were included. Generalized linear models examined whether baseline IICV predicted incident mild cognitive impairment (MCI)/dementia, cognitive decline, and amyloid and tau positron emission tomography outcomes, adjusting for demographics, intellectual disability, apolipoprotein E ε4, site, assessment interval, and mean cognitive performance, with Bonferroni correction. RESULTS:Greater IICV predicted incident MCI/dementia (odds ratio = 4.63 to 5.13, p < 0.05), greater amyloid burden, early tau accumulation, and higher tau across Braak stages, independent of mean cognition. Exploratory analyses suggested sex-specific interactions with tau outcomes. DISCUSSION:IICV is a sensitive marker of dementia risk and cognitive resilience in DS, with potential utility for secondary prevention and trial enrichment.

The β-amyloid radiotracer [18F]NAV4694 is a desirable alternative to [11C]PiB, possessing similar imaging characteristics and favorable radiopharmaceutical distribution. This work examined the consistency of amyloid measures between [11C]PiB and [18F]NAV4694 as participants transition between radiotracers in longitudinal studies. Thirty-five participants with ≥1 [11C]PiB scans, followed by a [18F]NAV4694 scan, were recruited from ongoing AD studies at the University of Wisconsin. Amyloid stability was evaluated in Aβ- individuals and amyloid accumulation was evaluated in Aβ+ individuals. In Aβ- participants, [18F]NAV4694 measures were consistent with the preceding [11C]PiB measures, showing no significant differences in CL values. Aβ+ participants exhibited an average annualized Aβ accumulation of 6.0 ± 1.8 CL/yr, consistent with modeled [11C]PiB Aβ projected outcomes. [18F]NAV4694 demonstrated both consistency in trending amyloid accumulation and constancy in sustained Aβ- participants compared with [11C]PiB. This study highlights how both radiotracers can be integrated within a single analytical framework under a uniform processing pipeline.

Given the prevalence of alcohol use and stress during pregnancy, we examined the effects in offspring of prenatal alcohol and stress on the dopamine system and drinking behavior in a primate model. In a 20-year prospective longitudinal experiment, we studied alcohol-naive adult rhesus monkeys of both sexes bred from mothers randomly assigned during pregnancy to consume moderate alcohol, be exposed to mild stress, both, or neither. Positron emission tomography (PET) was used to measure dopamine D2-type receptor (D2) and transporter (DAT) availability in substantia nigra/ventral tegmental area (SN/VTA), striatum, and prefrontal cortex (PFC), at baseline and after chronic fixed-dose drinking in offspring. After the follow-up PET scans, monkeys were given ad libitum access to alcohol. Findings were: (1) prenatal stress increased DAT in SN/VTA and striatum, while an interaction of prenatal stress and alcohol altered D2 in PFC; (2) prenatal alcohol alone increased the fixed-dose drinking rate; (3) in the three brain regions, low baseline D2 predicted faster fixed-dose drinking rate, and changes in DAT from baseline to follow-up predicted consumption in subsequent ad libitum drinking; and (4) no significant alteration of D2 or DAT due to drinking was observed. This experiment highlights the sensitivity of the primate dopamine system to prenatal perturbations, dopamine's role in drinking, and an individual neuroadaptive response to chronic alcohol consumption. The results suggest that alcohol abuse may originate, in part, from prenatal alcohol exposure. Moreover, reports in AUD of lower D2 might reflect preexisting dopamine receptor status rather than resulting entirely from alcohol consumption.

Individuals with Down syndrome (DS) have an increased risk of developing Alzheimer disease (AD), with nearly all individuals exhibiting AD neuropathology, including amyloid beta (Aβ) plaques and neurofibrillary tangles (NFT), by age 40 years. Fluid AD biomarker studies highlight an increase in several phosphorylated tau (p-tau) epitopes in DS. However, neuropathological measures of p-tau epitopes in DS have not been examined. Therefore, our main objective was to characterize p-tau epitope burdens across the DS lifespan at autopsy. We analyzed postmortem brain samples of 98 individuals with late-onset AD (LOAD), DS with AD neuropathology (DSAD), young DS (below 40 years of age), and age-matched neurotypical controls, ranging from 1 to 96 years of age. Immunohistochemical and digital pathology measures of p-tau epitopes at threonine 181 (pThr181), threonine 217 (pThr217), and threonine 231 (pThr231) burdens in the frontal cortex were compared across groups. We observed similar pThr181, pThr217, and pThr231 burdens between DSAD and LOAD, despite DSAD cases being younger on average. Observed pThr181, pThr217, and pThr231 burdens were higher in DSAD compared to young DS and neurotypical controls. Generalized additive models (GAMs) were used to model the cross-sectional trajectory of p-tau epitope burdens across the DS lifespan. Estimated age breakpoints revealed a significant rise in frontal cortex pThr231 at age 40, followed by pThr181 and pThr217 at age 42. In summary, our findings revealed an age-associated increase in p-tau epitopes across the DS lifespan. Our results have the potential to inform future associations between neuropathological and biofluid and neuroimaging biomarker measures of p-tau epitopes.

BACKGROUND:Plasma biomarkers associated with Alzheimer's disease could improve prognostic assessment for people with Down syndrome in both clinical practice and research settings. We aimed to identify the plasma biomarkers that most accurately predict longitudinal changes in Alzheimer's disease-related pathology and cognitive functioning in individuals with Down syndrome. METHODS:This longitudinal cohort study included data from 258 adults (aged ≥25 years) with Down syndrome who were followed up prospectively every 16 months as part of the longitudinal Alzheimer's Biomarker Consortium-Down Syndrome study (recruited from seven university sites in the USA and UK between July 13, 2016, and Jan 15, 2019). Participants had baseline and longitudinal assessments of plasma tau phosphorylated at threonine 217 (p-tau217), glial fibrillary acidic protein (GFAP), amyloid β (Aβ)42/40, neurofilament light (NfL), or total tau (t-tau). Associations of baseline plasma biomarkers and longitudinal changes in plasma biomarkers with changes in global cognitive functioning (Down Syndrome Mental Status Examination [DS-MSE] scores), Aβ-PET, and tau-PET were examined using linear regression models. Plasma biomarker-associated risk of progression to dementia was assessed using Cox regression analysis. FINDINGS:Baseline p-tau217, as well as GFAP, NfL, or t-tau, were individually associated with longitudinal changes in DS-MSE, Aβ-PET, and tau-PET, and with progression to dementia. However, in combined models, only baseline p-tau217 remained associated with changes in DS-MSE (β -0·30 [95% CI -0·45 to -0·15], p=0·0001, n=220), tau-PET (0·42 [0·14 to 0·70], p=0·0039, n=88), and progression to dementia (hazard ratio 3·51 [95% CI 1·76-7·00], p=0·0004, n=194), whereas baseline p-tau217 (0·29 [0·14-0·45], p=0·0003) and GFAP (0·37 [0·18-0·56], p=0·0003) were associated with changes in Aβ-PET (n=106 for both). Similar associations were shown between longitudinal p-tau217 or GFAP and changes in DS-MSE (p-tau217: β -0·33 [95% CI-0·52 to -0·13], p=0·0015, n=133), tau-PET (p-tau217: 0·61 [0·40 to 0·83], p<0·0001, n=87), and Aβ-PET (p-tau217: 0·35 [0·19 to 0·50], p<0·0001; GFAP: 0·49 [0·27 to 0·70], p<0·0001, n=88). INTERPRETATION:Baseline and longitudinal plasma p-tau217 were associated with subsequent decline in global cognition, progression to dementia, and increased tau burden, whereas baseline p-tau217 and GFAP were associated with Aβ accumulation. These findings suggest that plasma p-tau217 and GFAP might be valuable for prognostic assessment of Alzheimer's disease in people with Down syndrome in both clinical and research contexts. The results further support evaluation of these biomarkers for monitoring disease progression in clinical trials of Down syndrome-related Alzheimer's disease. FUNDING:The European Research Council and National Institute on Aging (National Institute of Health).

BACKGROUND:Centiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate. METHODS:PMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non-DS populations. RESULTS:Five accepted PMs improved the Centiloid-processing success rate in the DS cohort from 61.3% to 95.6%. DISCUSSION:The identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS. HIGHLIGHTS:Image preprocessing pipeline is proposed for Centiloid analysis of DS. Preprocessing pipelines are evaluated for adherence to Centiloid standards. Pipelines are evaluated for improvement in yield of usable imaging data. Preprocessing of amyloid imaging data resulted in a large yield improvement.