Objectives This study examined associations between attention, working memory, inhibition, episodic memory, and adaptive functioning in young adults with Down syndrome (DS).Methods Forty-seven adults with DS (19-30 years) completed measures of attention, working memory, inhibition, and episodic memory within two studies. Study partners completed the Vineland-3, an informant-report of adaptive functioning. Hierarchical regressions were used to examine associations between attention, working memory, inhibition, episodic memory, and Vineland-3 scores.Results Participants with DS with an IQ in the mildly and moderately below average range had comparable levels of daily living and socialization skills but differed in communication. All adaptive functioning scores were lower for those with an IQ in the severely below average range. Working memory and episodic memory were positively associated with all Vineland-3 scores except socialization. Inhibition was positively associated with communication and overall adaptive skills. Attention was positively associated with overall adaptive skills.Conclusions Attention, working memory, inhibition, and episodic memory are associated with the adaptive functioning of adults with DS. Important connections exist between memory and communication and daily living skills, as well as inhibition and communication skills. Future research should explore environmental adaptations for supports in these areas (e.g. assistive technology).

INTRODUCTION:The incidence of Alzheimer's disease (AD) in Down syndrome (DS) exceeds 90%. Approximately 50% of people with DS have congenital heart disease (CHD). Having CHD increases risk for early-onset AD in populations without DS, but it is unclear if CHD influences AD in DS. METHODS:Data from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) were used. Participants with CHD (n = 82, mean age = 39.9 ± 8.5 years, 97.6% White race) were age- and sex-matched to participants without CHD (n = 82, mean age = 40.5 ± 8.1 years, 98.8% White race). Cognitive assessments and Centiloid load (CL) (positron emission tomography) were compared by CHD status. RESULTS:People with CHD scored lower for visuospatial ability (β = -3.515, p = 0.022) but had higher CL (29.8 ± 12.8 vs. 39.8 ± 12.8, β = 8.00, p = 0.036) and were projected to hit Aβ positivity at a younger age (37.6 and 42.1 years). DISCUSSION:Presence of CHD may influence AD progression in DS. Highlights:In adults with Down syndrome (DS), those with congenital heart disease (CHD) had higher amyloid beta and reached the threshold for an amyloid positivity at a younger age than those without CHDNo differences in cognition were seen in the age- and sex-matched sample based on CHD status; however, the average age of the sample may be too young to see cognitive changesCHDs may influence the timing of Alzheimer's disease (AD) in adults with DS.

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 Little is known about circadian rhythm disruption and Alzheimer’s disease (AD) biomarkers in adults with Down syndrome (DS). The study aim was to examine the association of 24-hour rest-activity rhythm (RAR) with plasma Amyloid-Tau-Neurodegeneration (ATN) biomarkers and amyloid PET in adults with DS. Methods Cross-sectional study of adults with DS (25–61 years) enrolled in the Alzheimer Biomarker Consortium-Down syndrome who underwent wrist-worn actigraphy, plasma ATN and amyloid PET assessment. Primary variables were measures of 24-hour RAR: interdaily stability (IS), intradaily variability (IV), relative amplitude (RA), L5 (least active 5-hour period) and M10 (most active 10-hour period). Secondary measures included: coefficient of variation of total sleep time, sleep midpoint, and sleep efficiency; and the sleep regularity index (SRI). ATN biomarkers included amyloid beta 42/40 ratio, phosphorylated-tau 181 (pTau181), and neurofilament light chain. Amyloid PET were harmonized using centiloids. Analyses were performed using linear regressions. Covariates included age, sex, intellectual disability level, site, and obstructive sleep apnea severity. Results Of 91 participants, mean (SD) age was 39.5 (8.6) years and 43% were female. After adjustment, higher IV (indicating fragmentation of RAR in a 24-hour period) was associated with increased levels of pTau181 [standardized beta (β)=0.22, p=0.02]. Higher RA (indicating robust RAR) and higher SRI (indicating consistent and regular sleep patterns) were associated with lower pTau181 (β = -0.21, p=0.03 and β = -0.21, p=0.03, respectively). In the subsample of participants who had amyloid PET data available at the time of analysis (n = 50), higher IV was associated with increased centiloids (β=0.22, p=0.04). Conclusion These findings suggest that circadian rhythm disruption (RAR) is associated with plasma and imaging biomarkers of AD. Further research is needed to understand whether interventions to strengthen circadian rhythms reduce AD biomarker burden. Support (if any) This manuscript was supported by NIH grant #T32HL007909 and #F31AG085730. Data was collected as part of the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) and a related Lifestyle R01 study that are funded by the National Institute on Aging and the National Institute for Child Health and Human Development (U01AG051406, U01AG051412, U19AG068054; R01AG070028) and the Investigation of Co-occurring conditions across the Lifespan to Understand Down syndrome (NIH INCLUDE Project).

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.

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.

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.

INTRODUCTION:Individuals with Down syndrome (DS) have a high prevalence of Alzheimer's disease (AD) and reveal an earlier age of amyloid beta (Aβ) onset compared to sporadic AD. Differences in amyloid accumulation rates between DS and sporadic AD populations have not been established. METHODS:Participants with ≥ 3 [C-11]PiB scans (spanning > 6 years) and transitioning to Aβ+ were included, resulting in 20 DS and 23 neurotypical (NT) participants. Amyloid accumulation was compared using global standardized uptake value ratio (SUVR) for Aβ deposition, with individual growth rates (r) estimated using the logistic growth model ( S U V R ( t ) = S U V R B L + K 1 + e - r ( t - t 50 ) $SUVR\ ( t ) = SUV{{R}_{BL}} + \frac{K}{{1 + {{e}^{ - r( {t - {{t}_{50}}} )}}}}$ ). RESULTS:The average growth rate in the DS cohort was 0.28 (0.08)/year versus 0.20 (0.08)/year for NT ( p = . 002 $p = .002$ ), an increase of 40%. DISCUSSION:Using individual longitudinal analyses, accelerated amyloid accumulation in DS is observed, This has important considerations for informing treatment trial design and monitoring beta-amyloid changes in future AD studies involving individuals with DS. HIGHLIGHTS:Aβ accumulation rate was estimated using a logistic growth model. There was no overlap in the age of amyloid positivity between DS and NT cohorts. Participants with DS accumulate amyloid 40% faster than those with sporadic AD.

INTRODUCTION:Individuals with Down syndrome (DS) have elevated risks for Alzheimer's disease (AD) due to amyloid beta (Aβ) precursor protein overexpression, with nearly all developing AD pathology by age 40 at autopsy. This study examined spatial associations between Aβ and tau burden in DS and neurotypical aging. METHODS:Data included 145 DS (25-67 years) and 191 neurotypical aging individuals (63-89 years). Regional Aβ and tau positron emission tomography outcomes were analyzed using multiset canonical correlation analysis to identify joint Aβ/tau spatial patterns, with regression models assessing associations with age and cognition. RESULTS:For a given Aβ burden, cognitively stable DS individuals exhibited relatively higher tau burden than neurotypical aging, while DS mild cognitive impairment/AD individuals exhibited more widespread pathology. Joint Aβ/tau patterns were associated with episodic memory impairment in DS and, as the disease progresses, executive dysfunction. DISCUSSION:DS exhibits overlapping and distinct AD-related neuropathology features, emphasizing the importance of biomarkers for early detection and intervention. HIGHLIGHTS:There are distinct amyloid beta (Aβ) and tau spatial patterns in Down syndrome (DS): For a given level of Aβ burden, individuals with DS exhibited greater and more widespread tau burden compared to neurotypical aging, even before a clinical diagnosis of dementia. Aβ-associated tau burden was linked to episodic memory impairment in DS prior to dementia, with executive dysfunction emerging as the disease progressed, highlighting the sequential impact of pathology on cognition. The unique pattern of early striatal Aβ accumulation in DS supports its use as a potential biomarker for tracking disease progression and guiding clinical trial inclusion criteria for Alzheimer's disease interventions in DS.

The prevalence of Alzheimer’s disease (AD) pathologies in people with Down syndrome (DS) is nearly 100%. In DS, overexpression of APP (on chr21) is associated with increased production of amyloid beta (Aβ) and the formation of phosphorylated tau (ptau) tangles. In the general population, women exhibit higher burdens of ptau compared to age-matched men with AD. We hypothesized that in DS women would have higher ptau levels compared to men, and that age would significantly correlate with the presence of neuropathology. We examined 88 brains (frontal and occipital cortices) of people with DS (age 1-39yr; M/F = 19/12) and DSAD (age 42-61yr, M/F = 20/19) and age-matched controls. Serial sections were immunostained for ptau (AT8) and Aβ (6E10) and quantified using annotated regions of interest from whole slide images in QuPath. Spearman rank correlations of load data were calculated, the Mann-Whitney U test was used to compare men (n = 20) and women (n = 16) with DS. Mean positivity data was modeled using beta binomial regression in our cohort. When comparing neuropathology loads of DS individuals (age 40+), women show consistently higher median levels of Aβ and ptau. Differences were not statistically significant. Aβ and ptau were both significantly correlated with age in the grey matter of the frontal (Aβ: r = 0.76, p≤0.001; ptau: r = 0.72, p≤0.001) and occipital cortices (Aβ: r = 0.72, p≤0.001; ptau: r = 0.70, p≤0.001). Interestingly, the positive correlation with ptau and age within the occipital cortex appears to be stronger in women (R = 0.80, p≤0.0001) than in men (R = 0.71, p≤0.01). We were able to determine that AD pathology presents in the frontal cortex approximately 10 years earlier than the occipital cortex and increases exponentially after age 40. These results suggest age significantly impacts AD pathology in DS, with neuropathologies presenting in the frontal cortex approximately 10 years earlier than the occipital. Trends indicate sex does appear to have an impact on these pathologies, particularly in the occipital cortex where ptau was found to have a stronger association with age in women. Collectively, this warrants further investigation on the impact of sex and age on AD neuropathology in DS and the contributing mechanisms.

Blood-based biomarkers able to detect atypical neuropathology could serve as a cost-effective and noninvasive screening to include participants with Down syndrome (DS) in anti-amyloid clinical trials. Accurately placing these novel biomarkers on the AD pathological cascade as proposed by the AT(N) framework informs relative disease progression of individuals. This work examines associations between plasma pTau217 accumulation, PET amyloid positivity, and cognitive status in adults with Down syndrome. Participants were recruited from the Alzheimer’s Biomarker Consortium – Down Syndrome (ABC-DS) study (Table 1). Amyloid positivity was determined by [ 11 C]PiB or [ 18 F]florbetapir (A+: Centiloids > 18) PET imaging from U01 cycle 1. Participants were classified as cognitively stable, mild cognitive impairment (MCI), or dementia (D). Plasma pTau217 concentration was measured using Lilly’s immunoassay for the Meso Scale Discovery platform. The threshold for ptau217 abnormality was derived using a subsample of amyloid negative participants. Youden’s Index (YI) was optimized to assess ptau217 sensitivity to PET A+ individuals. The time offset between PET amyloid positivity (18 CL) and ptau217 sensitivity was based on amyloid chronicity trajectories (Zammit et al, 2023). A second analysis was performed with respect to varying PET A+ thresholds. Amyloid positive participants showed elevated pTau217 levels compared to amyloid negative participants (A+: 0.82 pg/ml, A-: 0.44 pg/ml, p < 0.05). With a data derived pTau217 threshold of 0.78 pg/ml, optimization of YI identified an optimal cut point of 48.5 CL. In a ROC analysis, AUC increased with increasing PET A+ thresholds (Figure 1). A significant separation of pTau217 with cognitive status was observed (cognitively stable: 0.51 pg/ml, MCI: 0.88 pg/ml, D: 1.50 pg/ml) (Figure 2). Concordance was high between plasma pTau217 using Lilly’s immunoassay and amyloid PET status after reaching elevated amyloid levels of 48.5 CL or ∼6 years PET A+. This work suggests that elevated pTau217 levels follows Aβ neuropathology detected by PET and trends with clinical progression.

Adults with Down Syndrome (DS) clearly show a higher risk of developing Alzheimer's disease (AD) when compared with the general population. Thus, it is important to investigate the role AD-related biomarkers in adults with DS. Here we have performed genome-wide association analyses on Tau-PET and plasma Tau levels in the participants of the Alzheimer’s Biomarker Consortium – Down Syndrome (ABC-DS). Genome-wide analyses were performed on 320 individuals of European descent DS (ranging in age from 25 to 81, Male 54.1%) having biomarker data from Tau-PET as well as plasma p-tau 181, p-tau 217, and total tau. The association of these biomarkers with two APOE SNPs, rs429358 (E4) and rs7412 (E2) was also examined. We used a joint model of multiple phenotypes to investigate the genetic factors contributing to all Tau biomarkers simultaneously in those participants having complete phenotypic and genotypic data. In the APOE association analysis, APOE4 was not significantly associated with any biomarker. However, individuals carrying APOE2 had lower plasma p-tau-181 levels (p= 0.0017) than non-carriers. In a genome-wide analysis, we identified three novel genome-wide significant (GWS) associations. The first association was with plasma total Tau on chromosome 11 near JHY (top SNP= rs77264104; MAF=0.017; p=1.75E-08; β=-1.52). The second association was with Tau-PET on trisomy chromosome 21 near a long coding RNA LOC105372747 (top SNP= rs76523946; MAF=0.034; p=2.04E-08; β=0.61). Lastly, the multiple phenotype analysis revealed association with all Tau AD biomarkers on chromosome 7 in the intronic region of SEM1 (Top SNP= rs78223947; MAF= 0.039; p=1.44E-08). We have identified three novel associations with Tau biomarkers in adults with DS associated with either lower tau or higher tau biomarkers. Two of these associations (JHY and SEM1) have also been implicated potentially with Tau pathology and AD risk, respectively, in non-DS participants. This investigation underscores the potential of leveraging the DS population as a valuable resource for discerning genetic elements that contribute to AD or AD-related biomarkers.

BackgroundLifetime incidence of Alzheimer's disease (AD) in Down syndrome (DS) exceeds 90%. In adults with and without DS, low moderate-to-vigorous physical activity (MVPA) and obesity have independently been associated with AD. Research across other disease conditions indicates MVPA may attenuate some negative consequences of obesity.ObjectiveTo evaluate the potential joint association of obesity and MVPA on cognitive function in adults with DS.MethodsSeventy-five adults with DS (age 39.1 years, 46.7% female) enrolled in the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) study and completed a 7-day accelerometer protocol. Cognitive function was assessed using the ABC-DS cognitive battery. Participants were categorized with Obesity (body mass index (BMI) ≥ 30 kg/m2) or No Obesity (BMI < 30 kg/m2). A median split of MVPA was then used to create four groups: No Obesity/High PA (n = 18), No Obesity/Low PA (n = 16), Obesity/High PA (n = 20), and Obesity/Low PA (n = 21). Linear models were used to compare cognitive function across groups.ResultsThe Obesity/High PA group performed better than the No Obesity/Low PA group for episodic memory (β = 4.86, p = 0.009), executive functioning (β = 3.07, p = 0.013), and dementia symptoms (β = -6.57, p = 0.022). The Obesity/High PA group also performed better than the Obesity/Low PA group for memory and orientation (β = 4.43, p = 0.012), social functioning (β = 4.52, p = 0.006), visuo-spatial processing (β = -2.39, p = 0.038), and overall dementia symptoms (β = -7.21, p = 0.016). There were no assessments for which either high PA group performed worse than either Low PA group.ConclusionsPhysical activity may benefit AD-related cognitive function in persons with DS, regardless of obesity status.

Individuals with Down syndrome (DS) typically develop Alzheimer’s disease (AD) at an early age. Estimates of the age of decline vary, but typically place it in the early-mid 50s. As AD onset can be difficult to identify in intellectually impaired cohorts, understanding the expected timing of decline may help individuals and caregivers prepare. It is unclear how timing in changes in different domains relates to the onset of AD dementia. Data was obtained for individuals with DS (188 total, 53% male), ages 25 to 61, from the Alzheimer’s Biomarker Consortium–Down Syndrome and used in cross-sectional analyses based on the baseline session. Decline was determined by performance on direct measures of cognition with participants and interviews of caregivers. Diagnosis of AD related decline was arrived at by group consensus. Domain-specific decline was dichotomized as a stable vs decline binary for Adaptive, Behavioral/Emotional, Cognitive, Interpersonal, Memory, and Psychomotor changes. Consensus and domain-specific data (Consensus n = 175, 18 declining, Domain n = 186-187, 21-60 declining) was available. The association between age and decline was analyzed in logistic generalized additive models (GAM), controlling for sex. Ages where individuals were equally likely to be stable or declining were extracted from GAM models. The relationship between domains/consensus was also examined using tetrachoric correlations. Results were considered significant at a p < .05 following multiple comparison correction. Age was significantly associated with decline for all measures except the Behavioral/Emotional domain. AD related decline began at age 54, domain-specific estimates varied: earliest in Memory (49.7) and Cognitive (49.8) and latest in Behavioral/Emotional (64.7). The relationship between age and decline probability was linear except for AD consensus where slope slows at age 44 and the Cognitive measure where slope increases at age 37. Age at decline did not differ between sexes. Correlations ranged from 0.96 (Memory with Consensus) to 0.47 (Consensus with Behavioral/Emotional). AD decline occurs at the age of 54 and is preceded by a change in cognition and memory ∼4 years earlier. Sex does not affect decline onset. Change in memory and cognition are closely related while behavioral/emotional changes are not strongly associated with AD-related decline or other domains.

INTRODUCTION:Adults with Down syndrome (DS) accumulate amyloid beta (Aβ) plaques faster and earlier on average than neurotypical adults with sporadic Alzheimer's disease (AD). White matter (WM) microstructure characterized with diffusion tensor imaging (DTI) can indicate underlying architectural changes in longitudinal studies, suggestive of neurodegeneration. This study investigated relationships between DTI and Aβ in DS along the AD continuum. METHODS:Using longitudinal amyloid Pittsburgh compound B positron emission tomography, Centiloid (CL) and DTI parameters were examined in 35 adults with DS ages 25 to 57. DTI measures of anisotropy and diffusivity were analyzed using tract-based spatial statistics and permutation analysis of linear models, testing for significant correlation between the rates of change for CL and DTI. RESULTS:All rates of DTI and Aβ changes were significantly related. Significant regions included the corpus callosum, corona radiata, and long-association fibers. DISCUSSION:Aβ burden is associated with widespread longitudinal WM changes in DS. This suggests WM microstructure alterations accompany amyloid accumulation. HIGHLIGHTS:A Down syndrome-specific template was created. Longitudinal diffusion tensor imaging (DTI) and amyloid burden rates of change correlate. Longitudinal results show more significant regions than cross-sectional results. DTI and amyloid changes were found over two timepoints, 3.7 years apart on average. DTI and amyloid-PET offer greater sensitivity when tracking microstructural changes.

INTRODUCTION:Despite having few vascular risk factors, people with Down syndrome (DS) have MRI evidence of cerebrovascular disease (CVD) and neuroinflammation that worsens with Alzheimer's disease (AD) severity. We investigated whether markers of CVD and inflammation are associated with AD-related diagnostic progression in people with DS. METHODS:We included 149 participants (mean age [SD] = 44.6 [9]) from the Alzheimer's Biomarkers Consortium-Down Syndrome who had two (n = 24) or three follow-up visits (n = 125). We derived white matter hyperintensity (WMH) volume and plasma biomarker (glial fibrillary acidic protein [GFAP], amyloid beta [Aβ]42/Aβ40, hyperphosphorylated tau-217 [p-tau217], and neurofilament light [NfL]) concentrations at baseline and examined their association with progression in clinical diagnosis. RESULTS:Higher baseline WMH volume and higher GFAP were associated with a greater likelihood of diagnostic progression. Combining WMH and GFAP with p-tau217 improved clinical conversion classification accuracy over AD biomarkers alone. Among individuals with evidence of amyloidosis, both WMH and GFAP were associated with clinical progression. DISCUSSION:In DS, markers of CVD and inflammation are independently and synergistically associated with clinical AD progression. HIGHLIGHTS:Higher baseline white matter hyperintensity (WMH) volume and plasma glial fibrillary acidic protein (GFAP) concentration were associated with a higher likelihood of progressing from cognitively stable to either mild cognitive impairment or clinical Alzheimer's disease in Down syndrome. WMH volume and GFAP concentration discriminated between those who progressed and those who did not. Models including the independent and interactive effects of WMH and GFAP more accurately discriminated between participants who progressed diagnostically from those who did not. Individuals with evidence of amyloid pathology were more likely to progress if they also had elevated WMH or GFAP.

The cerebellum is frequently used as the reference region for amyloid PET analysis. However, this reference region has been shown to demonstrate longitudinal variability, particularly with [ 18 F]florbetapir (FBP) PET (Landau, JNM 2015). For investigations in individuals with Down syndrome (DS), cerebellar atrophy and rapid disease progression may increase these longitudinal variabilities. Although white matter possesses different non-displaceable uptake properties, the relative lack of specific binding makes white matter a suitable reference region for longitudinal studies. This work compares the observed longitudinal change when using whole cerebellum and white matter reference regions in [ 18 F]FBP and [ 11 C]PiB scans of adults with DS. Participants with DS, recruited through the ABC-DS study, underwent longitudinal PiB or FBP PET imaging and T1w MRIs (Table 1 lists cohort differences). PET images were smoothed to 8mm resolution, summed 50-70 min, co-registered with the MRI, and normalized to a common DS MRI template (LeMerise, 2022). GAINN whole cerebellum (WC) VOI was applied to create SUVR WC . Whole brain white matter was segmented in native space using SPM, smoothed to PET resolution, and eroded to 90% tissue probability. The resulting eroded white matter (EWM) mask was used as reference to create SUVR EWM . Average SUVR was calculated for GAINN global cortex (CTX). Longitudinal scans were assessed for correlations between reference region strategies and average rate of SUVR change: % Change/year = (SUVR 2 -SUVR 1 )/(SUVR 1 *Δt). Figure 1 displays the averaged EWM reference template. Figure 2 displays longitudinal PET data and regressions between SUVRs. Across participants, SUVR WC shows 78/90 (PiB) and 50/83 (FBP) between-scan increases. SUVR EWM shows 66/90 (PiB) and 71/83 (FBP) between-scan increases. For A+ individuals (18CL cutoff), the average difference (% Change EWM - % Change WC )/year is -0.5%/year [-1.2,0.3] (PiB) and 1.9%/yr [0.5,3.3]** (FBP). FBP group SD in % Change/year decreases from 5.6% (WC) to 2.9% (EWM). As observed in LOAD, SUVR EWM demonstrates lower group variability and greater longitudinal change in FBP. SUVR EWM shows strong agreement with SUVR WC in PiB. These data suggest that an EWM reference region can reduce variability in longitudinal FBP studies in DS.

INTRODUCTION:The Down syndrome-associated Alzheimer's disease (DSAD) autosomal dominant Alzheimer's disease (ADAD) 2024 Conference in Barcelona, convened under an Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) grant through the Down syndrome and Alzheimer's disease (AD) Professional Interest Area (PIA), brought together global researchers to foster collaboration and knowledge exchange between the fields of DSAD and ADAD. METHODS:This article provides a synthesis review of the conference proceedings, summarizing key discussions on biomarkers, natural history models, clinical trials, and ethical considerations in anti-amyloid therapies. RESULTS:A total of 211 attendees from 16 countries joined the meeting. Global researchers presented on disease mechanisms, therapeutic developments, and patient care strategies. Discussions focused on challenges and opportunities unique to DSAD and ADAD. Experts emphasized the urgent need for tailored clinical trials for ADAD and DSAD and debated the safety and efficacy of anti-amyloid treatments. Ethical considerations highlighted equitable access to therapies and the crucial role of patient and caregiver involvement. DISCUSSION:The conference highlighted the importance of inclusive research and collaboration across the genetic forms of AD. HIGHLIGHTS:Biomarker research and natural history models developed in Down syndrome-associated Alzheimer's disease (DSAD) and autosomal dominant Alzheimer's disease (ADAD) enable the prediction of disease progression not only for DSAD and ADAD, but also for sporadic Alzheimer's disease (AD). -Collaboration and knowledge exchange among researchers across these genetic forms of AD will accelerate our understanding of the pathophysiology and advance preventive trials in DSAD and ADAD. -Tailored clinical trials for DSAD are urgently needed to address specific safety and efficacy concerns. -Inclusive research practices are crucial for advancing treatments and understanding of DSAD and ADAD.