Roh, Jee Hoon

ABSTRACT 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. FUNDING National Institute on Aging, Alzheimer’s Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.

Abstract Background Alzheimer Disease (AD) pathology evolves over decades, and understanding this progression is critical to the understanding of the disease and timing therapeutic interventions. Since individuals with Autosomal Dominant AD (ADAD) develop symptoms around the same age as their parent, it is possible to predict symptom onset and stage individuals by their estimated years to symptom onset (EYO). This approach does not generalize to other forms of AD, thus there is a pressing need for the timecourse of ADAD to be defined in broadly relevant terms. The objective of this project is to validate the Sampled Iterative Local Approximation (SILA) algorithm in a cohort with a known disease timecourse. SILA generates an estimate of time from amyloid positivity (A time ) based on longitudinal PET data. Method We evaluated A time in a longitudinal ADAD sample ( N = 316) with PET PiB data in three ways. First, we compared predicted age at amyloid positive (A+) to observed age at A+ for individuals who became A+ during enrollment. Next, using linear regression, we compared estimated age at A+ to estimated age at symptom onset (EYO=0). Finally, we used generalized additive models to compare the amount of variance in concurrent cognitive performance explained both A time and EYO. Result We observed a mean average error of 1.15 years between actual age at A+ ( N = 26) and the SILA‐predicted A time . Across all participants, SILA‐estimated age at A+ explained 39% of the variance in estimated age at symptom onset ( β = 0.918, p < 0.0001). Finally, we observed a nonlinear association between cognition and both A time and EYO. A time explained 19% of the variance in the general cognitive composite while EYO explained 43% of the variance. Conclusion SILA produces a valid estimate of time‐from‐amyloid positivity in ADAD. This work allows for disease stage in ADAD to be compared to staging for broad forms of AD, which was not previously possible using EYO. However, this work also illustrates that there is a high degree of heterogeneity in preclinical disease duration that is not explained by amyloid alone.

Abstract The cortical asymmetry index evaluates the cortical thickness asymmetry between hemispheres. We investigated cortical asymmetry index in asymptomatic and symptomatic mutation carriers of autosomal dominant Alzheimer’s disease to explore the brain asymmetry within the Alzheimer’s disease continuum. Sixty baseline T1-weighted MRI scans were obtained from the Clinic Barcelona cohort. Baseline and longitudinal MRI data from 564 participants within the dominantly inherited Alzheimer network observational study were used as an independent, confirmatory cohort. Cerebrospinal fluid and plasma neurofilament light chain levels were included when available. Cortical thickness was calculated using Freesurfer and cortical asymmetry index was calculated via an open-source pipeline. Cross-sectional analyses examined cortical asymmetry index differences based on clinical classification and APOE ε4 status, adjusting for age, sex and estimated years from onset, while correlations were assessed with age, estimated years from onset, mini-mental state examination scores, and neurofilament light. Longitudinal cortical asymmetry index evolution was modelled using generalized additive models in the dominantly inherited Alzheimer network observational study cohort, incorporating age, sex, and the interaction between group and estimated years from onset. The cortical asymmetry index successfully distinguished asymptomatic mutation carrier and symptomatic mutation carriers from healthy controls in the Clinic Barcelona cohort and symptomatic mutation carriers from controls in dominantly inherited Alzheimer network observational study. Higher cortical asymmetry index in mutation carriers (asymptomatic mutation carrier and symptomatic mutation carriers combined) and in symptomatic mutation carriers were associated with higher plasma neurofilament light levels, a closer proximity to symptom onset, and lower mini-mental state examination in the Clinic Barcelona cohort. In the dominantly inherited Alzheimer network observational study cohort, mutation carriers exhibited increased cortical asymmetry index compared to controls and correlated with elevated neurofilament light (plasma and Cerebrospinal fluid), lower mini-mental state examination, and a closer proximity to symptom onset. APOE3/3 carriers showed greater asymmetry than other APOE genotypes and significant cortical asymmetry index differences between asymptomatic mutation carrier and symptomatic mutation carriers. Longitudinally, cortical asymmetry index increased over time significantly in symptomatic mutation carriers. These findings underscore brain asymmetry as a potential biomarker for early Alzheimer’s disease progression in autosomal dominant Alzheimer’s disease, with implications for detection and monitoring tracking disease-related neuroanatomical changes.

Abstract INTRODUCTION Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time. METHODS We estimated time from amyloid positivity (A+) using sampled iterative local approximation (SILA) in a longitudinal autosomal dominant AD (ADAD) sample ( N = 379) with amyloid positron emission tomography. We compared (1) predicted age at A+ to imputed age, (2) estimated age at A+ to estimated age at symptom onset, and (3) variance in cognitive performance explained. RESULTS Mean error between imputed and SILA‐estimated age at A+ ( N = 26) was 1.15 years. Age at A+ explained 39% of estimated years to symptom onset (EYO) variance. Time from A+ explained 19% of cognitive composite variance and 14% of Clinical Dementia Rating Sum of Boxes CDR‐SB variance; EYO explained 43% and 57%, respectively. DISCUSSION SILA estimates A+ age in ADAD with reasonably good accuracy. SILA‐estimated time from A+ describes the start of pathology, but the time from A+ onset to symptoms is variable in ADAD and better described by EYO. Highlights Amyloid chronicity predicts a 14‐year preclinical AD phase in ADAD. SILA accurately estimates age at A+ (MAE < 2 years). EYO outperforms chronicity in predicting symptom onset. APP mutation carriers show atypical amyloid accumulation. Chronicity models help reveal AD heterogeneity in preclinical stages.

Abstract BACKGROUND Tau‐derived cerebrospinal fluid (CSF) biomarkers correlate with amyloid‐beta (Aβ) plaques or tau tangles in Alzheimer's disease (AD). This study assessed the effects of long‐term anti‐Aβ antibodies on amyloid plaques, tau tangles, and CSF tau species to determine the relationships between them. METHODS A post‐hoc analysis of the DIAN‐TU‐001 trial (NCT01760005) examined 142 participants at risk for dominantly inherited AD randomized to solanezumab ( n = 50), gantenerumab ( n = 52), or placebo ( n = 40). High‐resolution mass spectrometry quantified CSF tau species over four years. RESULTS Phosphorylated tau (p‐tau) species (153, 181, 217, 231) increased early in preclinical AD but were reduced with gantenerumab‐mediated Aβ plaque reduction. Nearly a decade later, MTBR‐tau243 and p‐tau205 increased, showing no association with Aβ reduction, aligning with tau tangle pathology progression. DISCUSSION Initially changing soluble p‐tau species track Aβ plaque reduction, while ptau205 and MTBR‐243 reflect tau tangle pathology, informing different pathways of therapeutic strategies. Highlights p‐tau217 and p‐tau231 correlate with Aβ‐PET and respond to Aβ‐plaque lowering therapies. Aβ immunotherapy trials support a direct link between p‐tau changes and Aβ plaques Gantenerumab reduces Aβ plaques but does not affect tau NFT‐related biomarkers. Blood‐based p‐tau217 assays may provide a non‐invasive tool to monitor Aβ therapies. MTBR‐tau243 strongly correlates with tau PET and tracks NFT pathology progression. Further studies are needed to validate tau biomarkers for tracking NFT‐targeting therapies.

Objectives Directly compare the brain glucose patterns seen with [F‐18] fluorodeoxyglucose (FDG) positron emission tomography (PET) between 2 genetically determined forms of Alzheimer's disease: Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD). Methods Cross‐sectional analyses of FDG were performed in individuals with DS (n = 76) from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS), ADAD (n = 297), and neurotypical familial controls (n = 188) from the Dominantly Inherited Alzheimer Network (DIAN). Within‐group linear regression models and generalized additive models were performed for select regional FDG uptake measures (isthmus cingulate and inferior parietal, precuneus, middle temporal gyrus, and precentral gyrus). Age, sex, apolipoprotein (APOE) ε4 carrier status, and cortical amyloid burden were included within these analyses. Results Even 20 years before expected onset of clinical symptoms, FDG uptake was lower for DS compared to neurotypical familial controls ( p < 0.01). ADAD baseline FDG was similar to neurotypical familial controls until 7 years before expected symptom onset. Both symptomatic individuals with DS and ADAD had lower FDG compared to neurotypical familial controls ( p < 0.01). A higher amyloid burden was associated with lower FDG for both genetic forms, with similar rates of decline in FDG uptake for DS and ADAD who were amyloid positive. Interpretation Brain glucose metabolism is substantially lower for people with DS, even in individuals who are cognitively stable. The patterns of FDG decline are distinct in these 2 genetically determined forms of AD. The diagnostic utility of FDG‐PET is specific to the genetic form of AD. ANN NEUROL 2025;98:1237–1248

AbstractINTRODUCTIONThis study investigated the role of the ubiquitin–proteasome system (UPS) in dominantly inherited Alzheimer's disease (DIAD) by examining cerebrospinal fluid (CSF) levels of UPS proteins.METHODThe SOMAscan assay was used to detect changes in UPS proteins in mutation carriers (MCs) relative to disease progression; imaging and CSF biomarkers of amyloid, tau, and neurodegeneration measures; and Clinical Dementia Rating scale.RESULTSSubtle increases in specific ubiquitin enzymes were detected in MCs up to two decades before symptom onset, with more pronounced elevations in UPS‐activating enzymes near symptom onset. Significant correlations were found between UPS proteins and Alzheimer's disease (AD) biomarkers, especially between autophagy markers and late‐stage tau biomarkers, microglia, and axonal degeneration.DISCUSSIONThe rise in UPS proteins alongside tau‐related markers suggests UPS involvement in tau neurofibrillary tangles. Elevated CSF UPS proteins in DIAD MCs may serve as indicators of disease progression, and may support the UPS as a therapeutic target in AD.Highlights This study investigates the ubiquitin‐proteasome system (UPS) in Dominantly Inherited Alzheimer's Disease (DIAD), highlighting early molecular changes linked to disease progression. Using SOMAscan proteomics, we identified significant UPS protein alterations in cerebrospinal fluid of mutation carriers, notably up to 20 years before clinical symptom onset. Correlations between UPS protein levels and Alzheimer's biomarkers, particularly tau and neurodegeneration markers, suggest a strong association between UPS dysregulation and tau pathology in DIAD. Dynamic UPS changes align with A/T biological staging: UPS proteins were shown to increase across Aβ/tau (A/T) groups, with largest increases in the A+/T+ group, reinforcing their role in late‐stage tau pathology and disease progression. These findings underscore the potential of UPS proteins as early biomarkers for Alzheimer's disease progression and as novel therapeutic targets, especially in tau‐pathology‐driven neurodegeneration. This work contributes to understanding AD pathogenesis, by emphasizing the importance of protein quality control systems and by offering avenues for future biomarker discovery and therapeutic development in Alzheimer's disease.

Abstract INTRODUCTION β‐synuclein is a promising blood marker to track synaptic degeneration in Alzheimer's disease (AD) but changes in preclinical AD are unclear. METHODS We investigated serum β‐synuclein in 69 cognitively unimpaired mutation non‐carriers, 78 cognitively unimpaired AD mutation carriers (asymptomatic AD), and 31 symptomatic mutation carriers from the Dominantly Inherited Alzheimer Network. RESULTS β‐synuclein levels were already higher in asymptomatic AD mutation carriers compared to non‐carriers and highest in symptomatic carriers. Longitudinal trajectories and correlation analyses indicated that β‐synuclein levels start to rise after amyloid deposition preceding axonal degeneration, brain atrophy and hypometabolism, and cognitive decline. β‐synuclein levels were associated with cognitive impairment and gradually increased with declining cognition. DISCUSSION Our study supports the use of blood β‐synuclein to track synaptic changes in preclinical AD and as a surrogate marker for cognitive impairment which might be used in early diagnosis and to support patient selection and monitoring of treatment effects in clinical trials. Highlights Blood β‐synuclein levels were already higher in asymptomatic Alzheimer's disease (AD) mutation carriers. Blood β‐synuclein levels were highest in symptomatic AD mutation carriers. Blood β‐synuclein levels start to rise 11 years before symptom onset. Rise of β‐synuclein precedes axonal degeneration, brain atrophy, and cognitive decline. β‐synuclein levels gradually increased with declining cognition.

Abstract We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer’s disease (ADAD). A total of 550 variants in the APP, PSEN1 and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature and public databases. Symptomatic age at onset (AAO) data were estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity and AAO. Importantly, 226 variants met eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrated the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study. This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria.

AbstractINTRODUCTIONWe investigated longitudinal associations between self‐reported exercise and Alzheimer's disease (AD)‐related biomarkers in individuals with autosomal dominant AD (ADAD) mutations.METHODSParticipants were 308 ADAD mutation carriers aged 39.7 ± 10.8 years from the Dominantly Inherited Alzheimer's Network. Weekly exercise volume was measured via questionnaire and associations with brain volume (magnetic resonance imaging), cerebrospinal fluid biomarkers, and brain amyloid beta (Aβ) measured by positron emission tomography were investigated.RESULTSGreater volume of weekly exercise at baseline was associated with slower accumulation of brain Aβ at preclinical disease stages β = –0.16 [–0.23 to –0.08], and a slower decline in multiple brain regions including hippocampal volume β = 0.06 [0.03 to 0.08].DISCUSSIONExercise is associated with more favorable profiles of AD‐related biomarkers in individuals with ADAD mutations. Exercise may have therapeutic potential for delaying the onset of AD; however, randomized controlled trials are vital to determine a causal relationship before a clinical recommendation of exercise is implemented.Highlights Greater self‐reported weekly exercise predicts slower declines in brain volume in autosomal dominant Alzheimer's disease (ADAD). Greater self‐reported weekly exercise predicts slower accumulation of brain amyloid beta in ADAD. Associations varied depending on closeness to estimated symptom onset.