The Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs) is a longitudinal, global cohort study investigating brain aging and autosomal dominant Alzheimer’s disease (ADAD), a rare monogenic form of Alzheimer’s disease (AD). Established in 2008 with support from the National Institute on Aging (NIA), DIAN Obs is designed to collect comprehensive and uniform data with the aim to characterize brain biology and clinical trajectory of individuals at risk for ADAD. Mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes cause ADAD with virtually full penetrance and a predictable age at symptomatic onset. Participants, both mutation carriers and non-carriers from affected families, undergo longitudinal clinical and cognitive assessments, neurologic and physical examinations, structural and functional neuro-imaging, and amyloid and tau positron emission tomography (PET). Biospecimens include cerebrospinal fluid, plasma, serum, and whole blood for biochemical, genetic and multi-omic analyses, with brain donation upon death. This dataset enables one of the most detailed longitudinal examinations of the human brain across the continuum from presymptomatic to symptomatic AD. The extensive DIAN Obs data and biospecimen repository provides a globally accessible resource to advance understanding of AD pathophysiology, aging, and the development of preventive and therapeutic interventions.

The minimal amyloid accumulation (MAA) in cognitively unimpaired individuals that predicts the onset of cognitive impairment remains unknown. In a multi-center amyloid positron emission tomography (PET) study of 1834 cognitively unimpaired participants with longitudinal clinical/cognitive assessments for up to 20.3 years, we found that 48.7% of the amyloid-negative participants with MAA starting from an amyloid PET centiloid of 1.03 had a higher risk of cognitive impairment than those with the lowest centiloid values (<1.03; hazards ratio (HR)=1.40, p=0.0046), although their risk was clearly lower than amyloid-positive participants (centiloid>20; HR=0.47, p<0.0001). Amyloid positivity was also associated with the fastest longitudinal amyloid accumulation and cognitive decline, followed by the MAA, and finally by the lowest amyloid. These findings suggest that current thresholds of amyloid positivity used for Alzheimer disease diagnosis may be overly restrictive, potentially excluding a large portion of amyloid-negative participants at elevated risk of developing cognitive impairment from prevention trials.

BACKGROUND:Increasing evidence suggests that accurate prediction of Alzheimer's disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) Aβ42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS:We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS:NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION:Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development.

With the advent of disease-modifying treatment for Alzheimer disease (AD), identifying biomarkers for predicting risk for amyloid-related imaging abnormalities (ARIA), hemorrhagic or edema types, is of increased interest. ARIA are thought to be related to disruption of the blood-brain barrier as fibrillary amyloid is cleared from the brain. Molecular and cellular processes related to these events may inform future trials. We investigated proteomics related to abnormal neurovascular imaging phenotypes such as white matter hyperintensities (WMH) in autosomal dominant AD (ADAD), a relatively young population at risk for ARIA. Participants from the Dominantly Inherited Alzheimer Network observational study (n Carriers =290 and n Non-Carriers =183) were assessed for WMH and microhemorrhages using T2-FLAIR and T2*GRE MRI, and for CSF proteomics using the 7k Somalogic ® platform. A subset (n Carriers =92 and n Non-Carriers =51) was evaluated for microhemorrhage incidence. WMH volumes were segmented with Triplanar U-Net ensemble network. Microhemorrhage count and incidence were classified as none, mild, moderate, or severe, based on current FDA recommendations. We performed differential abundance analyses to investigate proteins associated with WMH as a function of mutation status, accounting for age, APOE-e4 status, and sex, and significant proteins were further evaluated in pathway analyses and for associations with microhemorrhages. Eight proteins were differently expressed in carriers with larger WMH volumes (Figure 1). The genes of seven proteins (e.g., neurofilament light-chain (NEFL), neurofilament heavy-chain (NEFH), matrix metalloproteinase 12 (MMP12), fibronectin-1 (FN1), periostin (POSTN)) were overly represented in vascular-related disorders such as subarachnoid hemorrhages, transient ischemic attack, or cerebrovascular diseases (Figure 2). CSF levels of NEFL, NEFH, MMP12, fibronectin1, and periostin differed as a function of CMH severity. Especially, NEFL and MMP12 were higher in carriers with severe CMH compared to those with none or mild CMH (Figure 3A). MMP12 levels were particularly high in participants having severe increase in microhemorrhages (Figure 3B). Carriers with high levels of MMP12 may more likely develop new microhemorrhages. Our findings confirm the contribution of neurofilament light chain in disease processes and suggest a role for matrix metalloproteinase 12 in the development of microhemorrhages and especially severe case in ADAD. Funding : K01AG080123, RF1-AG044546, UF1AG032438

Abstract INTRODUCTION Positron emission tomography (PET) without usable or accompanying magnetic resonance imaging (MRI) is typically excluded in quantitative analyses of Alzheimer's disease, potentially limiting study generalizability. We investigated participant features predicting data exclusion in magnetic resonance (MR)‐dependent analyses and evaluated an existing MR‐free PET pipeline to quantify these missing data. METHODS Imaging, clinical, cognitive, and sociodemographic data were analyzed for 2119 individuals in a multi‐site cohort. Agreement between MR‐dependent and MR‐free Centiloids (CL) assessed using intra‐class correlations and features predicting data exclusion were examined using logistic regressions. RESULTS MR‐free and MR‐dependent CLs generally agreed, but MR‐free CLs underestimated MR‐dependent cross‐sectionally and longitudinally. Approximately 19.5% (n = 405) of our cohort would have been excluded in MR‐dependent analyses. Age and cerebrovascular comorbidities were consistent exclusion features across multiple sites. DISCUSSION Data exclusion in imaging studies is not entirely random. Flexible quantification methods like MR‐free PET could supplement traditional methods to improve generalizability in large, multi‐site studies.

Predicting not just if, but also when, cognitively unimpaired individuals are likely to develop onset of Alzheimerʼs disease (AD) symptoms would be useful to clinical trials and, eventually, clinical practice. Although clock models based on amyloid and tau positron emission tomography have shown promise in predicting the onset of AD symptoms, a model based on plasma biomarkers would be more accessible. Using longitudinal plasma %p-tau217 (the ratio of phosphorylated to non-phosphorylated tau at position 217) from two independent cohorts ( n = 258 and n = 345), clock models were used to estimate the age at plasma %p-tau217 positivity. The estimated age at plasma %p-tau217 positivity was associated with the age at onset of AD symptoms (adjusted R 2 of 0.337−0.612) with a median absolute error of 3.0−3.7 years. Notably, the time from %p-tau217 positivity to onset of AD symptoms was markedly shorter in older individuals. Similar models were constructed with data from one p-tau217/Aβ42 immunoassay and four plasma p-tau217 immunoassays. These findings suggest that the time until onset of AD symptoms can be estimated using a single blood test within a margin of error that is acceptable for use in clinical trials.

INTRODUCTION:The Clinical Dementia Rating (CDR) scale typically is administered in person, but use of telephone-based, informant-only assessments increased during the coronavirus disease 2019 (COVID-19) pandemic. The correspondence of informant-only assessments with in-person ratings remains unclear. METHODS:We analyzed 1,140 paired in-person and telephone assessments from the Knight Alzheimer's Disease Research Center Memory and Aging Project conducted within 12 months. Agreement for global CDR and CDR Sum of Boxes (CDR-SB) was examined using kappa statistics, intraclass correlation coefficients (ICCs), and Bland-Altman methods; classification performance of telephone global CDR score ≥ 0.5 was assessed. RESULTS:Agreement for the global CDR was moderate (κ = 0.53, 95% CI: 0.47-0.59). CDR-SB demonstrated moderate reliability (ICC = 0.69, 95% confidence interval [CI]: 0.65-0.73). Telephone CDR-SB scores averaged 0.40 points higher than in-person scores, with wide limits of agreement. Sensitivity was 64.2% and specificity 91.9%. DISCUSSION:Telephone CDR-SB shows moderate concordance with in-person CDR-SB but shows consistent score inflation, which may limit clinical staging utility.

BACKGROUND AND OBJECTIVES:Clinical trials in REM sleep behavior disorder (RBD) to delay or prevent the development of Parkinson disease (PD), dementia with Lewy bodies (DLBs), and multiple system atrophy (MSA) will soon begin. The Prodromal Synucleinopathy Rating Scale (PSRS) was developed to capture the breadth and severity of clinical burden of prodromal disease. We analyzed the clinicometric properties and reliability of the PSRS in the North American Prodromal Synucleinopathy (NAPS) cohort. METHODS:PSRS ratings were examined for visits conducted from August 2022-June 2025 on participants who did not have overt PD, DLB, or MSA (n = 348). Clinician raters used clinical judgement to evaluate signs and symptoms within each domain. Scores range from 0 (none) to a maximum of 2-4 points per domain, with a total maximum score of 25. The domains include cognitive (COG), behavioral/psychiatric (PSY), motor-axial (MAX), motor-appendicular (MAP), autonomic (AUT), sleep (SLP), and sensory (SEN). Spearman correlations were generated between ratings for each domain, the total sum score (SUM), and with independent measures of similar constructs. Test-retest reliability for 20 case examples protocols among 20 different raters was quantified using Bayesian generalized linear mixed-effects model. RESULTS:Participants were 79% male with a mean age of 65.4 ± 10.4 years. The following correlations were statistically significant at p < 0.0001: COG with Montreal Cognitive Assessment (r = -0.42) and Clinical Dementia Rating-Sum of Boxes (r = 0.77); PSY with Neuropsychiatric Inventory-Questionnaire (r = 0.38); MAX and MAP with the Movement Disorders Society-Unified Parkinson Disease Rating Scale Motor (r = 0.65 and 0.75, respectively); AUT with Scales for Outcomes in Parkinson's Disease-Autonomic Dysfunction (r = 0.39); SLP with Epworth Sleepiness Scale (r = 0.23); and SEN with Brief Smell Identification Test (r = -0.66). The PSRS SUM was correlated with the Functional Assessment Scale (r = 0.47), Schwab and England Activities of Daily Living (r = -0.58), and Clinician Global Impression of Severity (r = 0.29, p < 0.0001 for each). The inter-rater and intrarater reliability means ranged from 0.76 to 0.98. DISCUSSION:In this large multicenter RBD cohort, moderate to strong correlations were observed between PSRS domains and multiple independent measures of clinical burden. Reliability data were good to excellent. These findings demonstrate preliminary validity for the PSRS for measuring synucleinopathy clinical burden in those with RBD. TRIAL REGISTRATION INFORMATION:NCT05826457 NAPS Consortium Website: naps-rbd.org/.

INTRODUCTION:Usage of biomarker tests for Alzheimer's disease pathology and rates of positivity were assessed at the Washington University Memory Diagnostic Center. METHODS:Patients who underwent at least one biomarker test for clinical purposes between June 2021 and March 2025 were included (n = 1136). Data were retrospectively extracted from electronic health records. RESULTS:The median age was 73.2 years (52% female; 93% White). In total, 455 amyloid positron emission tomography (PET) scans, 505 cerebrospinal fluid tests, and 242 blood tests were performed. The number of biomarker tests increased seven-fold over the past 4 years. The rate of positivity was ≈70% across modalities. Higher rates of biomarker positivity were associated with older age, female sex, and White race; lower rates were associated with hypertension and diabetes. DISCUSSION:Biomarker testing greatly increased following the approval of amyloid-targeting treatments. The overall rate of biomarker positivity was high and varied by demographic factors and medical comorbidities.

There is increasing evidence for an association between white matter hyperintensities (WMH) and brain beta-amyloid deposition. WMH are not exclusive correlates of a single etiology, and the spatial topography can associate with different pathologic markers of vascular or neurodegenerative disease. How WMH are longitudinally associated with brain beta-amyloid burden requires further investigation, particularly with respect to co-existent vascular risk factors and differences across brain regions. We retrospectively measured WMH on MRI and vascular risk factors in a combined neuroimaging data set comprised of the ADNI, AIBL and OASIS3 studies, which included harmonized centiloid estimates of beta-amyloid burden from PET imaging. WMH were measured using the TrUE-Net algorithm. Vascular risk factors were extracted from provided clinical data and used to calculate individual revised Framingham Stroke Risk Profile (FSRP) scores. Five established data-driven WM regions (juxtacortical, deep frontal, periventricular, parietal, posterior) were used for regional relationships with WMH volume and growth. Linear mixed effects modelling was used to determine the relationship between the growth rate of normalized regional WMH volumes and baseline beta-amyloid burden, controlling for age, sex, APOE4 status, and vascular risk factors. 1245 participants [48.7% female, mean age 71.7 y (SD 7.6 y)] had at least 3 brain MRIs suitable for WMH volume measurement. Linear mixed models demonstrate robust independent cross-sectional relationships between WMH and baseline beta-amyloid burden ( p  <0.001), age ( p  <0.001) and FSRP ( p  <0.001). Growth rates of WMH increased with baseline beta-amyloid burden ( p  <0.05) and decreased with vascular risk ( p  <0.001), above and beyond age, sex, and APOE4 status. Regional analyses revealed both baseline beta-amyloid burden and FSRP associated with the juxtacortical deep frontal and periventricular regions, but the parietal region was unique to beta-amyloid ( p  <0.05). Longitudinally, the association for beta-amyloid burden ( p  <0.005) persisted in only the parietal WMH and no normalized regional values associated longitudinally with FSRP. Our study suggests that in Alzheimer disease research cohorts, WMH progression is associated with beta-amyloid burden, particularly in parietal white matter. Vascular risk associated WMH were influential for WMH volume but did not associate with WMH progression in a regionally specific manner.

Background Alzheimer's disease (AD) clinical trials often involve uneven follow-up durations and long-term open-label extensions (OLE), yet conventional statistical models are typically designed for fixed schedules, limiting their efficiency in such settings. Objective To describe and illustrate alternative statistical modeling approaches developed and implemented in the Dominantly Inherited Alzheimer Network Trials Unit platform trial to optimally leverage data with irregular and extended follow-up. Methods We present three complementary models: (1) a Cox proportional hazards model for recurrent disease progression events that uses all observed worsening events rather than only the first event; (2) a parametric disease progression model based on estimated years from expected symptom onset that estimates proportional slowing or time delay in disease progression; and (3) piecewise linear mixed-effects models tailored to the "gap" period between the double-blind phase and OLE, accommodating variable off-treatment intervals and missing interim data. All methods are illustrated with hypothetical examples, and ready-to-use SAS code is provided in the Supplemental Material. Results The proposed models successfully handle complex longitudinal data structures typical trials with OLE phases, offering greater statistical efficiency and more comprehensive capture of treatment effects over extended periods compared with traditional approaches. Conclusions These flexible, efficient statistical models are well-suited for rare disease and long-duration AD trials. Wider adoption and further validation of these approaches may enhance the power and interpretability of future neurodegenerative disease trials.

Abstract Introduction Patients with Parkinson’s disease commonly underreport sleep symptoms, but the extent to which such mismatch may be present in people with isolated RBD (iRBD) is unknown. We evaluated how the patient–bedpartner (PT–BP) mismatch in night-time and daytime sleep complaints relates to cognition, apathy, dopaminergic degeneration, and cortical structure in iRBD. Methods We retrospectively analyzed 425 iRBD participants (2018–2025) from the North American Prodromal Synucleinopathy (NAPS) Consortium with clinicodemographic data, dopamine transporter (DAT) imaging, and magnetic resonance imaging. Using Scales for Outcomes in Parkinson’s Disease (SCOPA)-Sleep, PT–BP mismatch was classified into overestimator (PT>BP), concordant (PT=BP), and underestimator (PT< BP) groups, separately for complaints during night and day. Outcomes included cognition (CDR-Sum of Boxes [CDR-SB], CDR-global, and individual subdomain tests), pareidolia, apathy, subregional DAT uptake, and cortical thickness. Group differences were tested with analysis of covariance adjusting for age, sex, disease duration, education, clinician-rated OSA treatment inadequacy, and the corresponding patient-reported SCOPA-Sleep domain (night or day), and estimated total intracranial volume for cortical thickness; pairwise tests used Bonferroni correction. Results The PT–BP mismatch was common (night – overestimator 127/425, 29.9% and underestimator 116/425, 27.3%; day – overestimator 77/425, 18.1% and underestimator 134/425, 31.5%). For night-time mismatch, underestimators showed lower CDR-SB and lower CDR-global than overestimators. In addition, underestimators exhibited more illusory responses, fewer correct noise rejections, and fewer total correct responses than overestimator and concordant groups. For daytime mismatch, CDR-SB was lower in underestimators versus overestimators; CDR-global was lower in underestimators and concordant participants versus overestimators. No significant associations were found for apathy. Subregional DAT uptake did not differ by mismatch group. Cortical thickness analyses revealed thinner right transverse gyrus in underestimator and concordant groups compared to the overestimator group and thinner left superior temporal gyrus in underestimator group compared to overestimator group, for night-time mismatch only. Conclusion The PT–BP subjective sleep mismatch can be used as a clinical marker associated with overall cognitive decline and cortical thinning in auditory and language processing areas, which may underlie impairment in perceptual interpretation and hallucination proneness. Further research is warranted to seek longitudinal change and phenoconversion in mismatch groups. Support (if any) #U19-AG071754 (NAPS Consortium)

Whereas longitudinal data are needed to pinpoint the exact age when individuals become positive for biomarkers of Alzheimer disease (AD), cross-sectional data can be used to examine the typical age of biomarker positivity across groups. Using cross-sectional data, we estimated the age when groups of self-identified Black and White individuals reached a threshold for plasma Aβ42/40 positivity. We assembled plasma samples and data from a large cohort of 324 Black or African American and 1,547 White individuals from three AD Research Centers (Washington University, University of Pennsylvania, and University of Alabama at Birmingham). Plasma Aβ42/40 was measured with C2N Diagnostics mass spectrometry-based assays. Locally estimated scatterplot smoothing (LOESS) was used to estimate the mean levels of plasma Aβ42/40 as a nonparametric function of age. Statistical calibration was then used to estimate the age when plasma Aβ42/40 reached the threshold for positivity (0.100). Analyses were performed with and without matching the Black and White groups by major AD covariates, and also in groups with and without comorbidities. Unmatched analyses revealed an estimated age at plasma Aβ42/40 positivity of 69.6 years for the group of White participants and 86.9 years for the group of Black participants. Black participants ( n  = 317) were then matched 1:2 with White participants ( n  = 634) by age, sex, APOE ε4 carrier status, global Clinical Dementia Rating (CDR) (CDR=0, 0.5, >=1), and years of education (>12 years vs. <=12 years). The matched analyses estimated an age at plasma Aβ42/40 positivity of 68.4 years for the group of White participants and 86.9 years for the group of Black participants. Interestingly, participants with hypertension, stroke, or diabetes had a later age at plasma Aβ42/40 positivity. The typical age at plasma Ab42/40 positivity may depend on racialized group and also medical comorbidities. These results are consistent with recent reports that groups of Black individuals have a lower incidence of AD biomarker positivity compared to groups of White individuals. These findings may aid design and analyses of future clinical trials of AD.

Biomarkers are routinely measured from human biospecimens and imaging scans in Alzheimer disease (AD) research. Age is a well-known risk factor for AD. Detecting the baseline age at which the longitudinal change in biomarkers starts to accelerate is important to design preventive interventions. We analyzed longitudinal biomarker data by a random intercept and random slope model where the slope (longitudinal rate of change) was modeled as a piecewise linear and continuous function of baseline age. We proposed to estimate the baseline age at the intersection of the two linear functions by multiple methods: maximum (profile) likelihood, minimum squared pseudo bias, minimum variance, minimum mean square error (MSE), and a two-stage method. We simulated large numbers of data sets to evaluate the performance of these estimators. Finally, we implemented them to analyze the longitudinal white matter hypointensity from brain magnetic resonance imaging scans in an AD cohort study of 616 participants conducted by the Washington University (WU) Knight Alzheimer Disease Research Center (ADRC) to estimate the baseline age when the longitudinal rate of change starts to accelerate. Our simulations indicated that performance was universally poor for all point estimators and confidence interval (CI) estimates when the true baseline age corresponding to the accelerated longitudinal change was near the boundary or when the sample size was small (N = 100). Yet, the proposed estimators became approximately unbiased and showed relatively small mean squared error when the sample size increased (N > 200) and the true baseline age was away from the boundary. The 95

Isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) is a usually prodromal manifestation of neurodegenerative disorders with α-synuclein pathology: Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Clinical trials in the iRBD population face substantial barriers: limited access to well-characterized cohorts, inconsistent assessment protocols across centers, and the absence of validated biomarkers of disease burden. The North American Prodromal Synucleinopathy (NAPS) Consortium was established to address these challenges and facilitate clinical trials for neuroprotective therapies targeting synucleinopathy at the earliest known stages. In this multi-site, longitudinal, observational study, nine academic centers across North America will enroll and follow over 500 individuals with iRBD from existing sleep centers. Sixty control participants, matched for age, sex, and race will also be recruited. A harmonized protocol—including a standardized clinical battery assessing motor, cognitive, autonomic, psychiatric, sensory, and sleep function; structured diagnostic adjudication; biospecimen collection; and centralized analysis of both polysomnography and neuroimaging data—is outlined herein and reflects NAPS Stage 2. Each participants completes these assessments annually, and are replaced in the event of phenoconversion. By unifying assessments and expanding geographic reach, NAPS lays the groundwork for efficient, well-powered clinical trials designed to delay or prevent progression of iRBD to overt PD, DLB, or MSA—ultimately enabling earlier, more effective therapeutic intervention for neurodegenerative disease. Registered at clinicaltrials.gov (NCT05826457).

Isolated REM sleep behavior disorder (iRBD) is a parasomnia that reflects an evolving α-synucleinopathy disorder, providing an opportunity to study early pathological changes. While diffusion tensor imaging (DTI) studies have shown white matter changes in iRBD, Neurite Orientation Dispersion and Density Imaging (NODDI) may offer better biological specificity in characterizing microstructural alterations through measures of Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and Free Water Fraction (FWF). We included 77 participants with polysomnography-confirmed iRBD from the North American Prodromal Synucleinopathy (NAPS) Consortium and 154 age- and sex-matched cognitively unimpaired controls from the Mayo Clinic Study of Aging. White matter microstructure was evaluated using standardized multi-shell diffusion on 3T MRI, quantifying DTI metrics (fractional anisotropy, FA; and mean diffusivity, MD) and NODDI parameters across bilateral white matter tracts defined by the JHU “Eve” WM atlas. Group differences were assessed using conditional logistic regression, with correlations to motor performance evaluated using the Purdue Pegboard and Alternating Finger Tapping tests. Compared to controls, iRBD participants demonstrated widespread and bidirectional white matter changes across major white matter pathways (see Figure 1 for glass brain visualizations). While predominantly showing decreases, FA exhibited some increases, particularly in the corticospinal tract. MD showed a largely opposite pattern with predominantly increased values across tracts. NODDI metrics revealed complex bidirectional patterns: ODI was broadly increased across multiple tracts with focal decreases, while NDI showed a pattern of predominantly decreased values alongside localized increases. FWF demonstrated a mixed pattern with predominant decreases across most tracts. In addition, both DTI and NODDI metrics showed extensive, moderate correlations with the Purdue Pegboard Test and Alternating Finger Tapping performance ( T  = 2.0, p  < 0.05, Figure 2). Our study highlighted widespread and complex bidirectional white matter microstructural alterations in individuals with iRBD, demonstrating significant correlations with dexterity and motor performance even during the prodromal stage. These results suggest that extensive white matter abnormalities occur early in prodromal α-synucleinopathies and highlight the value of advanced diffusion imaging techniques in characterizing iRBD and its potential prediction of phenoconversion to overt neurodegenerative disorders.

BACKGROUND AND OBJECTIVES:Cognitive reserve has been shown to modulate the onset and progression of Alzheimer disease (AD) symptoms. Although its role in sporadic AD is well-studied, how cognitive reserve influences the timing and progression of symptoms in dominantly inherited AD (DIAD) remains unclear. This study aimed to quantify cognitive reserve in DIAD carriers and test whether higher cognitive reserve is associated with later symptom onset and slower functional decline. METHODS:We analyzed data from the Dominantly Inherited Alzheimer's Network study. Cognitive reserve was modeled using a residual-based latent variable approach, decomposing cognitive performance into demographic (CogD), biomarker (CogB), and reserve or residual (CogR) components. Primary outcomes were age at clinical symptom onset (CDR >0) and longitudinal change in the Clinical Dementia Rating-Sum of Boxes (CDR-SBs). Data were analyzed using Cox proportional hazards models and linear mixed-effects models, adjusting for estimated years from onset (EYO). RESULT:A total of 710 Dominantly Inherited Alzheimer Network (DIAN) participants were included in the analysis, comprising 271 non-DIAD carriers (nMC), 284 asymptomatic DIAD carriers (aMC), and 155 symptomatic DIAD carriers. In asymptomatic carriers, using a zero-inflation model adjusted for EYO showed that a 1 SD increase in the reserve component (CogR) was associated with a 4.06-fold increase in the odds of being clinically unimpaired (CDR-SB = 0; 95% CI 1.84-8.95). Similarly, a 1 SD increase in the demographic (CogD) and biomarker (CogB) components increased the odds of being CDR-SB = 0 by 2.60 (95% CI 1.10-6.16) and 5.16 (95% CI 2.00-13.33), respectively. Among symptomatic carriers, only the reserve and the biomarker components were significant. A 1 SD increase in CogR was associated with a 0.81-fold reduction in baseline CDR-SB score (95% CI 0.72-0.92), and a 1 SD increase in CogB was associated with a 0.60-fold reduction in CDR-SB (95% CI 0.50-0.71). DISCUSSION:Our findings indicate that higher cognitive reserve values are associated with delayed conversion to mild cognitive impairment and slower progression on clinical dementia rating scales. These findings suggest that cognitive reserve plays a protective role in modifying the clinical trajectory of genetically determined AD.

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.