Importance:Blood-based biomarkers for Alzheimer disease, particularly plasma phosphorylated tau 217 (p-tau217), accurately reflect early Alzheimer disease brain pathology in cognitively unimpaired individuals, but estimates of absolute risk of progression to cognitive impairment across multiple cohorts are needed. Objective:To estimate absolute risk of progression to cognitive impairment and rates of cognitive decline based on plasma p-tau217 across cognitively unimpaired older adults. Design, Setting, and Participants:Longitudinal cohort study using harmonized data from 2684 cognitively unimpaired older adults (defined within cohort) across 6 observational and clinical trial cohorts based in North America, Japan, and Australia. The earliest enrollment was in 2004, with most recent follow-up in 2025. Exposure:Baseline plasma p-tau217. Main Outcomes and Measures:The primary outcome was time to progression to cognitive impairment (mild cognitive impairment, dementia, or 2 consecutive global Clinical Dementia Rating scores ≥0.5). The secondary outcome was longitudinal change on the latent Preclinical Alzheimer Cognitive Composite (PACC; higher values indicate better performance). Results:Among the 2684 participants (median [IQR] age, 69.6 [66.2-74.2] years; 1697 [63%] female), there were 478 events of progression to cognitive impairment over a median follow-up of 5.4 years (maximum follow-up of 13.5 years). Each 1-SD increase in baseline p-tau217 level was associated with an increased risk of progression to cognitive impairment (hazard ratio, 1.38 [95% CI, 1.30-1.46]), and the association remained significant after adjustment, including β-amyloid positron emission tomography scan Centiloids (hazard ratio, 1.32 [95% CI, 1.24-1.41]). Participants with high (1.1-2.4 SD) and very high (>2.5 SD) baseline p-tau217 had 24% (95% CI, 20%-28%) and 38% (95% CI, 33%-43%) absolute risk of progression over 5 years, respectively, and risk was markedly higher over 10 years, although longer-term estimates were constrained by limited data. Elevated p-tau217 was also associated with faster cognitive decline based on change in latent PACC score. Among the overall sample, baseline latent PACC scores ranged from -0.8 to 2.7. The 5-year annualized decline for the very high p-tau217 group was -0.07 latent PACC units/y (95% CI, -0.10 to -0.05), relative to 0.03 units/y (95% CI, 0.02-0.04) in the low p-tau217 group. Conclusions and Relevance:In a pooled sample of multiple selected cohorts of cognitively unimpaired older adults, higher plasma p-tau217 levels were consistently associated with increased risk of clinical progression and accelerated cognitive decline. By providing time-specific absolute risk estimates, these findings support the potential of p-tau217 for prognostic model development, with direct implications for future trial design. Further validation in unselected populations is needed to inform individual prognosis and clinical decision-making in cognitively unimpaired individuals.

BackgroundNeighborhood disadvantage has been associated with reduced cognitive reserve, increased risk for cognitive impairment, and greater Alzheimer's disease (AD) neuropathology, with particularly pronounced effects among Black and Hispanic/Latino older adults. Blood-based AD biomarkers offer a scalable approach to population-level study of AD risk; however, whether neighborhood-level social determinants influence these biomarkers across diverse populations remains unknown.ObjectiveTo characterize associations between neighborhood disadvantage and AD blood biomarkers in a racially and ethnically diverse community sample of older adults with and without cognitive impairment, and to examine whether these associations differ by race, ethnicity, and cognitive status.MethodsRegression models predicting AD biomarkers (amyloid-β 42/40 ratio, phosphorylated tau-181, total tau, and neurofilament light chain) from demographics and the Area Deprivation Index (ADI) were fit for 1179 Non-Hispanic White, 1264 Hispanic/Latino, and 724 Black adults. Models were stratified by cognitive impairment status and fit separately by race and ethnicity.ResultsAmyloid markers were associated with ADI, but only in cognitively impaired individuals living in highly disadvantaged areas. Total tau was elevated in those from disadvantaged neighborhoods, regardless of cognitive status; however, pTau-181 was not associated with ADI for any group. Significant associations were primarily evident among Black and Hispanic/Latino older adults.ConclusionsThe social exposome is an important factor in AD research, and findings show associations between neighborhood disadvantage and AD blood biomarkers; however, associations are mainly evident among ethnic/racial minority older adults living in moderately to severely disadvantaged neighborhoods. More work is needed to understand these associations.

Plasma p-tau217 closely tracks amyloid-β (Aβ) pathology, yet its ability to predict long-term clinical progression in cognitively unimpaired (CU) adults remains uncertain. We analyzed harmonized data from 2,705 CU participants (Agemean=69.8±7years; Female=63%) across six longitudinal cohorts with up to 13.5 years of follow-up. Cox models evaluated associations between p-tau217 and progression to a clinical diagnosis of cognitive impairment, while natural cubic spline models assessed associations with longitudinal decline on a cognitive composite. Higher p-tau217 was associated with increased risk of progression (hazard-ratio[HR]=1.38; 95%CI:1.31-1.44), independent of demographics and APOEε4, and in models with Aβ-PET (HR=1.30; 95%CI:1.23-1.38). Very high p-tau217 levels (>2.5SD) were associated with 61%[95%CI:53-68%] absolute risk of progression over 10 years. Elevated p-tau217 associated with accelerated cognitive decline, both independent of, and synergistic with, greater Aβ-PET. These findings establish plasma p-tau217 as a robust prognostic marker in preclinical AD and support its value in future individualized risk prediction.

Underdiagnosis of cardiometabolic risk factors (CMRFs) may represent an unrecognised biological pathway contributing to dementia risk; yet remains poorly characterised in African and African diaspora populations. We quantified the prevalence and determinants of underdiagnosed hypertension and abnormal glycaemia across four cohorts comprising up to 7,000 adults aged ≥ 40 years from Nigeria, Kenya, and The United States: Indianapolis, and North Texas. Underdiagnosis was defined as absence of self-reported diagnosis despite elevated systolic blood pressure (≥ 130 mmHg) or fasting blood glucose (≥ 100 mg/dL). Cohort-stratified analyses examined demographic, socioeconomic, cognitive, Alzheimer's genetic, and blood-based biomarker correlates. Underdiagnosis was pervasive in African cohorts. Elevated fasting glucose was associated with cognitive impairment in Kenya and North Texas, while severe hypertension and diabetes were linked to Alzheimer's disease-related biomarkers [pTau217/181, NFL and Aβ42/40] in North Texas (all p ≤ 0.05). These findings identify context-specific diagnostic gaps in populations at high dementia risk and highlight cardiometabolic detection as a mechanistic target for prevention.

BackgroundAlzheimer's disease (AD) affects 55 million people worldwide, projected to reach 139 million by 2050; yet, most machine learning (ML)-based AD classifiers have been developed in Non-Hispanic White (NHW) cohorts, limiting generalizability.ObjectiveAssess ethnic differences in AD prediction using classification performance and feature importance derived from multimodal neuroimaging biomarkers across African American (AA), Hispanic, and NHW participants.MethodsSupport vector machine classifiers were applied to multimodal neuroimaging data from a multi-ethnic cohort, incorporating structural magnetic resonance imaging measures, diffusion tensor imaging metrics, and positron emission tomography-based amyloid and tau measures. Models classified cognitively unimpaired (CU) versus cognitively impaired (CI) individuals and mild cognitive impairment (MCI) versus AD dementia, with and without adjustment for age, sex, and education.ResultsClassification performance varied by ethnicity and disease stage. NHW participants showed the strongest overall performance, particularly for CU versus CI, while Hispanic participants demonstrated high sensitivity and balanced performance for MCI versus AD. AA participants exhibited lower AUC and accuracy across tasks but maintained high negative predictive value. Demographic adjustment improved performance primarily for AA and NHW participants. Feature importance analyses revealed shared and population-specific patterns: tau positron emission tomography (PET) measures, especially posterior cingulate and lateral parietal standardized uptake value ratios, consistently ranked highest for CU versus CI across groups, whereas MCI versus AD classification diverged, with amyloid PET predominating in AA participants, tau PET in NHW participants, and mixed medial temporal atrophy and white matter signatures in Hispanics.ConclusionsShared early AD neuroimaging signatures exist across ethnic groups, but biomarker importance diverges at later disease stages, underscoring the need for ethnicity-aware ML models to improve prediction and equitable clinical translation.

INTRODUCTION:Down syndrome (DS) exhibits a genetic form of Alzheimer's disease (AD). We used a blood-based proteomic algorithm to predict cognitive status, treatment responders, and change to vitamin E in DS adults from a completed clinical trial, "Vitamin E in Aged Persons with Down Syndrome," which originally showed no significant cognitive benefit using the primary endpoint cognition (Brief Praxis Test [BPT]). METHODS:Plasma and extracellular vesicle (EV; astrocytic and neuronal) biomarkers were assayed at baseline and 36 months (n = 138 each). Cognitive response was measured using combined scores from the BPT, vocabulary, and behavior and function DS tests. Support vector machine (SVM) analyses predicted diagnostic and treatment responders and change accuracy. RESULTS:SVM classified demented versus non-demented with up to 99% accuracy and predicted treatment response and changes with up to 100% accuracy in plasma and EV. DISCUSSION:Our study supports blood-based screening and precision diagnostics for AD therapy in DS.

INTRODUCTION:Dementia prevalence is rising with population aging, disproportionately affecting females and ethnically diverse groups. Physical activity (PA) may mitigate age-related cognitive and brain decline; sex- and ethnicity-specific associations remain poorly understood. METHODS:Data from the Health and Aging Brain Study-Health Disparities were analyzed from 3585 participants (63% female). PA was categorized using the Rapid Assessment of Physical Activity (RAPA) questionnaire as no/little (< 4) or moderate/high (≥ 4). Outcomes included cognitive composites, plasma biomarkers, and magnetic resonance imaging-derived hippocampal subregions and dorsolateral prefrontal cortex volumes. RESULTS:Higher PA was associated with higher global cognition and executive functions in all females and in Hispanic males (ps < 0.05), higher episodic memory and larger hippocampal volumes across participants (ps < 0.05), and lower amyloid beta 40, total tau, and larger hippocampal subregion volumes in females (ps < 0.05). CONCLUSIONS:Findings support PA as a modifiable factor associated with healthy brain aging, emphasizing the importance of incorporating sex and ethnicity into future research.

INTRODUCTION:Alzheimer's disease (AD) dementia in Down syndrome (DS) occurs at predictable ages. It is unclear whether age can differentiate across AD stages (amyloid positivity, tau positivity, mild cognitive impairment [MCI], dementia). METHODS:Using data from the Alzheimer's Biomarker Consortium-Down Syndrome, we analyzed how well age differentiated stage using receiver operating characteristic curves. We compared areas under the curve (AUC) for age to AUCs for imaging, biofluid, cognitive, motor, and behavioral variables. RESULTS:Sample varied by stage and variable. Up to 148 variables and 461 participants were analyzed. Age effectively differentiated amyloid positivity, tau positivity, and MCI (AUCs > 0.85) but poorly discriminated MCI from dementia (0.588). No variable was better than age in distinguishing stages, except for MCI/dementia. DISCUSSION:Our results show that age alone is effective at staging DS AD. Age is the most reliable correlate of amyloid, tau status, and cognitive impairment in DS and could screen for future clinical 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.

Abstract INTRODUCTION Blood‐based biomarkers can improve Alzheimer's disease (AD) characterization in Down syndrome (DS). This study applied hierarchical clustering and machine learning–based feature selection to identify biomarkers associated with disease progression. METHODS Cross‐sectional blood‐based biomarkers were analyzed from 211 DS participants (n = 79 cognitively stable [CS]; n = 72 mild cognitive impairment [MCI]; n = 60 AD dementia [DS‐AD]). These included markers of amyloid, tau, neurodegeneration, and inflammation. Clustering grouped biomarkers. Decision trees classified disease stage, and Shapley values identified the strongest predictors of disease stage. RESULTS The strongest predictors overall were neurofilament light chain (NfL), tau/amyloid beta (Aβ)40, Aβ42/Aβ40, alpha‐2‐macroglobulin (A2M), and interleukin (IL)‐10. Within the CS group, NfL, tau/Aβ40, A2M, and IL‐10 were strong predictors. In MCI, Aβ42/Aβ40, NfL, A2M, and IL‐10 were strong predictors. In DS‐AD, Aβ42/Aβ40, NfL, and tau/Aβ40 were the top predictors. Cluster membership varied based on disease stage. DISCUSSION These findings reveal evolving biomarker signatures and clustering patterns across cognitive stages, underscoring their potential for disease monitoring.

Abstract INTRODUCTION We examined relationships among subjective memory concerns (SMC), plasma biomarkers, and objective memory within racially/ethnically diverse older adults. METHODS Participants included 1618 cognitively unimpaired older adults (681 Hispanic/Latino [H/L], 164 non‐Hispanic Black [NHB], 773 non‐Hispanic White [NHW]) from the Health and Aging Brain Study–Health Disparities. Associations among SMC, plasma biomarkers (phosphorylated tau 181 [p‐tau181], amyloid beta 42/40 [Aβ42/40], neurofilament light chain [NfL], total tau [t‐tau]), and objective memory were examined. RESULTS Higher SMC was associated with higher plasma p‐tau181 and NfL levels in NHW participants only. Higher depressive symptoms were associated with higher plasma p‐tau181 in NHB participants only. Higher SMC related to lower objective memory for H/L and NHW participants. Plasma biomarkers had unique patterns of association with memory tests by racial/ethnic group. DISCUSSION Different patterns of subjective memory, objective memory, and plasma biomarker associations within racial/ethnic groups suggests variability in the utility of SMC for early detection of Alzheimer's disease–related changes.

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.

INTRODUCTION:This study evaluates plasma-based proteomic profiles for predicting amyloid positivity in adults with Down syndrome (DS) and examines the impact of apolipoprotein E ε4 (APOE ε4) on test performance. METHODS:Cross-sectional data from 290 adults with DS were analyzed using single molecule array (SIMOA) technology to measure plasma amyloid beta (Aβ)42, Aβ40, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), tau phosphorylated at threonine 181, and total tau. Amyloid burden was quantified using Pittsburgh Compound B and (18)F-florbetapir Aβ positron emission tomography. Support vector machine analyses were conducted with biomarkers as predictors and age, sex, and APOE ε4 carrier status as covariates. RESULTS:Age, GFAP, and NfL contributed the most to the model performance. The proteomic profile achieved an area under the curve (AUC) of 96% in models with and without APOE ε4. DISCUSSION:These findings suggest that plasma proteomic biomarkers can effectively identify amyloid positivity in adults with DS and may support clinical triage, monitoring, and selection for clinical trials, independent of APOE ε4 status.

Homozygous APOE- ɛ4 carriers have exhibited heightened white matter hyperintensity (WMH) burden based on severity ratings (Rojas et al., 2018). A higher high-density lipoprotein cholesterol (HDL-c) to low-density lipoprotein cholesterol (LDL-c) ratio is associated with less severe WMHs (Wei et al., 2023). Additionally, higher concentrations of APOE protein are linked to higher cholesterol efflux in Alzheimer's Disease cohorts (Yassine et al., 2016). Despite the understanding of APOE as a lipid carrier (F. Yin, 2021), its mechanistic role in modulating dementia risk is still evolving. Here, we examine whether APOE- ɛ4 positivity modifies the relationship between blood cholesterol levels and WMH volume in a multi-ethnoracial cohort. We examined 1645 cognitively unimpaired (CU) individuals from the Health and Aging Brain Study-Health Disparities cohort (65.96% female, 25.6% APOE- ɛ4+, aged 50-90) (Table 1). Participants underwent a MR scanning (Siemens 3T Skyra or Vida), which included a T2 FLAIR image. We calculated WMH volume using SPM's lesion growth algorithm (LGA) and ran robust linear regressions to test for an interaction between log-transformed blood cholesterol levels and APOE- ɛ4 status on log-transformed WMH volume. Associations between cholesterol markers and WMH volume also were separately examined in APOE- ɛ4 carriers and non-carriers. Covariates included age, sex, years of education, intracranial volume, MRI scanner, body mass index, diabetes, and hypertension. All continuous variables were standardized. We corrected for three comparisons (HDL-c, LDL-c, triglycerides) using the false discovery rate method. There was a significant HDL-c× APOE- ɛ4 interaction on WMH volume (β= -0.10, p -corrected= 0.03) in the fully-corrected model driven mainly by a non-significant association between higher HDL-c and lower WMH volume in APOE- ɛ4 carriers (β= -0.10, p -corrected= 0.17) only. Interactions between APOE 4 carrier status and LDL-c and triglycerides were not significant. APOE- ɛ4 moderated the relationship between HDL-c and WMH volume such that greater HDL-c levels were associated with lower WMH burden in ɛ4 carriers only. APOE- ɛ4 did not interact with LDL-c or triglycerides on WMH volume. This investigation provides support for investigating HDL-c further in the context of brain health in ɛ4 carriers.

INTRODUCTION:Individuals with Down syndrome (DS) face high risk for Alzheimer's disease (AD), yet presymptomatic detection of cognitive decline is hindered by lifelong intellectual disability. METHODS:Using data from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS), blood samples from 246 participants were analyzed, yielding 404 longitudinal observations (45 Converters, 359 Stable) collected at 0, 16, and 32 months were analyzed. A Support Vector Machine was trained on 25 plasma biomarkers spanning neurodegeneration, inflammation, and vascular health, along with demographic factors (age, sex, ethnicity, karyotype, apolipoprotein E [APOE ε4]). Batch-effect correction and feature selection were applied, resulting in 13 key markers. RESULTS:The refined model achieved 92.4% sensitivity, 59.9% specificity, and an area under the curve (AUC) of 77.9%, accurately identifying individuals at risk of cognitive decline up to 16 months before clinical progression. DISCUSSION:This multi-domain, blood-based machine learning approach demonstrates that plasma biomarkers are valuable non-invasive tools for early detection and risk stratification of cognitive decline in DS.

Adults with Down syndrome (DS) develop Alzheimer's disease (AD) pathology by age 40, despite few vascular risk factors. MRI shows cerebrovascular disease (CVD) that precedes or begins contemporaneously with markers of AD pathology. We have found that vascular lesions observed on MRI interact with a marker of astrocytosis to promote tau pathology and neurodegeneration. However, it's unclear how CVD and astrocytosis interact with elevated Aβ to influence AD progression. We investigated whether markers of CVD and astrocytosis are linked to longitudinal changes in tau biomarkers and their interaction with Aβ levels. We included 114 participants (mean age[SD]=45.1[6]) from the Alzheimer's Biomarkers Consortium–Down Syndrome with baseline Aβ PET imaging ([11C]PiB or [18F]florbetapir) and three follow-up visits with MRI and plasma biomarker data. White matter hyperintensity (WMH) volumes were derived from T2-weighted FLAIR MRI, and plasma biomarkers (GFAP, p -tau181) were measured at baseline and follow-ups. Centiloid values were derived from Aβ standard uptake value ratio values and standardized across a scale from 0 to 100. Linear mixed effects models first estimated whether baseline WMH volume was associated change in GFAP concentration and whether baseline GFAP was associated with change in p -tau181 concentration. Separate models then tested if each baseline measure interacted with amyloid centiloid values. Models included site, age, sex/gender, and years from baseline as fixed effects and a random effect for participant intercept. Baseline WMH volume predicted an increase in GFAP over time (β=0.22[0.12, 0.31], AIC=-102.84), and baseline GFAP predicted an increase in p -tau181 (β=0.36[0.24, 0.4], AIC=-122.66). However, baseline GFAP did not predict WMH change (β=0.07[-0.1, 0.14], AIC = -25.7) nor did p -tau181 predict GFAP change (β=0.009[-0.18, 0.09], AIC=-33.41). Higher WMH volume predicted increased GFAP, especially in those with higher amyloid levels (β=0.38[0.26, 0.45], AIC=-146.3), and higher GFAP predicted increased p -tau181, particularly in those with higher amyloid levels (β=0.49[0.32, 0.55], AIC=-154.86). Cerebrovascular lesions promote astrocyte-related inflammation, particularly in the context of elevated amyloid pathology, which has a downstream effect on tau pathophysiology in adults with DS. The results support the hypothesis that the interface between CVD and astrocytosis is critical in AD progression in people with DS.

Background:Plasma phosphorylated tau217 (P-tau217), a plasma biomarker of Alzheimer's disease (AD), can increase before overt symptoms. P-tau217 positivity is linked to the age at symptom onset in model-based predictions, not time to clinical event. Individuals with different genetic backgrounds, yet similar P-tau217 levels may differ in whether cognitive decline will occur or when it will emerge. Whether APOE-ε4 carrier status provides additional prognostic information beyond P-tau217 remains unclear. Methods:Using data from 8,582 individuals in several multi-ethnic cohorts, we evaluated how APOE-ε4 carrier status modifies the risk and time to cognitive impairment associated with plasma P-tau217. Plasma P-tau217 was analyzed as a continuous measure, with positivity analyses performed secondarily. Associations of baseline P-tau217 with prevalent and incident cognitive impairment were assessed using logistic regression and Cox models, stratified by APOE-ε4 and in interaction models. Adjusted survival curves, restricted mean survival time, and accelerated failure time model were used to predict time to event and risk. Prognostic performance was evaluated using discrimination measures, including the AUC, incremental R2, and Harrell's C-index, and nonparametric random survival forest models. Findings:Elevated P-tau217 levels were associated with subsequent cognitive impairment in both APOE-ε4 carriers and non-carriers, but the effects on risk and timing of cognitive impairment were significantly stronger among APOE-ε4 carriers. In stratified meta-analyses, increase in P-tau217 levels was associated with cognitive impairment at baseline and with incident cognitive impairment in APOE-ε4 carriers compared to noncarriers (OR = 2.25 vs 1.52; HR = 1.76 vs 1.26 for 1-SD increase of P-tau217 levels). Each 1-SD increase in P-tau217 levels was accompanied by a 23% shorter period to cognitive impairment among APOE-ε4 carriers, compared to 13% among non-carriers. Clinically relevant differences in cognitive-impairment-free survival emerged three to four years before symptom onset. Across parametric and nonparametric models, the prognostic value of P-tau217 was consistently greater among APOE-ε4 carriers. Interpretation:Plasma P-tau217 levels and APOE genotypes are commercially available and can be used to estimate the years before the onset of overt cognitive impairment. These findings may also determine optimal timing for therapeutic intervention, particularly during the preclinical phase of the disease. Funding:NIH.

Background: Individuals with intellectual disability (ID) may have a five-fold increased risk for developing Alzheimer's disease (AD). However, studies investigating brain aging among individuals with ID without Down syndrome (DS) are lacking. To begin addressing this gap, our study utilized word reading, a widely recognized indicator of an individual's premorbid intellectual ability (pIQ), to examine the effects of ID without DS on plasma AD biomarker outcomes. Objective: To investigate the relationship between premorbid intellectual ability (pIQ) and plasma AD biomarkers in individuals with ID without DS, while considering ethnic differences in these associations. Methods: Participants from the Health & Aging Brain Study – Health Disparities (HABS-HD) were categorized into low (z ≤ −2.00) or average (z = 0.00 ± 1.00) pIQ groups based on word reading scores. Plasma biomarkers including Aβ 40 , Aβ 42 , Aβ 42/40 , phosphorylated tau 181 (p-Tau181), neurofilament light chain (NfL), and total tau (t-tau) were assayed using Simoa technology. Results: Individuals with low pIQ exhibited significantly higher levels of p-Tau181 ( p < 0.05), NfL ( p < 0.05), and t-tau ( p < 0.05) compared to those with average pIQ. Stratified analysis by ethnicity revealed differential associations, with Hispanic and non-Hispanic White (NHW) participants showing distinct biomarker profiles relative to non-Hispanic Black (NHB) individuals. Conclusions: The findings demonstrate that low pIQ is a reliable factor associated with plasma AD biomarker outcomes. Ethnicity appears to modulate these associations, suggesting complex interactions between factors driving AD susceptibility across diverse populations. This study highlights the importance of considering both pIQ and ethnicity in neurodegenerative processes, particularly in individuals with non-DS intellectual developmental disability.