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Introduction: We investigated longitudinal associations between self-reported exercise and Alzheimer's disease (AD)-related biomarkers in individuals with autosomal dominant AD (ADAD) mutations., Methods: Participants 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., Results: Greater 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]., Discussion: Exercise 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., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Prior authorization criteria for Federal Drug Administration (FDA) approved immunotherapeutics, among the class of anti-amyloid monoclonal antibodies (mAbs), established by state drug formulary committees, are tailored for adults with late-onset Alzheimer's disease. This overlooks adults with Down syndrome (DS), who often experience dementia at a younger age and with different diagnostic assessment outcomes. This exclusion may deny DS adults access to potential disease-modifying treatments. To address this issue, an international expert panel convened to establish adaptations of prescribing criteria suitable for DS patients and parameters for access to Centers for Medicare & Medicaid Services (CMS) registries. The panel proposed mitigating disparities by modifying CMS and payer criteria to account for younger onset age, using alternative language and assessment instruments validated for cognitive decline in the DS population. The panel also recommended enhancing prescribing clinicians' diagnostic capabilities for DS and initiated awareness-raising activities within healthcare organizations. These efforts facilitated discussions with federal officials, aimed at achieving equity in access to anti-amyloid immunotherapeutics, with implications for national authorities worldwide evaluating these and other new disease-modifying therapeutics for Alzheimer's disease., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab., Methods: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker., Results: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes., Discussion: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials., Highlights: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Reversion, or change in cognitive status from impaired to normal, is common in aging and dementia studies, but it remains unclear what factors predict reversion., Methods: We investigated whether reverters, defined as those who revert from a Clinical Dementia Rating® (CDR®) scale score of 0.5 to CDR 0) differed on cognition and biomarkers from unimpaired participants (always CDR 0) and impaired participants (converted to CDR > 0 and had no reversion events). Models evaluated relationships between biomarker status, apolipoprotein E (APOE) ε4 status, and cognition. Additional models described predictors of reversion and predictors of eventual progression to CDR > 0., Results: CDR reversion was associated with younger age, better cognition, and negative amyloid biomarker status. Reverters that eventually progressed to CDR > 0 had more visits, were older, and were more likely to have an APOE ε4 allele., Discussion: CDR reversion occupies a transitional phase in disease progression between cognitive normality and overt dementia. Reverters may be ideal candidates for secondary prevention Alzheimer's disease (AD) trials., Highlights: Reverters had more longitudinal cognitive decline than those who remained cognitively normal. Predictors of reversion: younger age, better cognition, and negative amyloid biomarker status. Reverting from CDR 0.5 to 0 is a risk factor for future conversion to CDR > 0. CDR reversion may be a transitional phase in Alzheimer's Disease progression. CDR reverters may be ideal for Alzheimer's disease secondary prevention trials., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: The extent to which the Big Five personality traits and subjective well-being (SWB) are discriminatory predictors of clinical manifestation of dementia versus dementia-related neuropathology is unclear., Methods: Using data from eight independent studies (N total = 44,531; N dementia = 1703; baseline M age = 49 to 81 years, 26 to 61% female; M follow-up range = 3.53 to 21.00 years), Bayesian multilevel models tested whether personality traits and SWB differentially predicted neuropsychological and neuropathological characteristics of dementia., Results: Synthesized and individual study results indicate that high neuroticism and negative affect and low conscientiousness, extraversion, and positive affect were associated with increased risk of long-term dementia diagnosis. There were no consistent associations with neuropathology., Discussion: This multistudy project provides robust, conceptually replicated and extended evidence that psychosocial factors are strong predictors of dementia diagnosis but not consistently associated with neuropathology at autopsy., Highlights: N(+), C(-), E(-), PA(-), and NA(+) were associated with incident diagnosis. Results were consistent despite self-report versus clinical diagnosis of dementia. Psychological factors were not associated with neuropathology at autopsy. Individuals with higher conscientiousness and no diagnosis had less neuropathology. High C individuals may withstand neuropathology for longer before death., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: This study aimed to investigate the influence of the overall Alzheimer's disease (AD) genetic architecture on Down syndrome (DS) status, cognitive measures, and cerebrospinal fluid (CSF) biomarkers., Methods: AD polygenic risk scores (PRS) were tested for association with DS-related traits., Results: The AD risk PRS was associated with disease status in several cohorts of sporadic late- and early-onset and familial late-onset AD, but not in familial early-onset AD or DS. On the other hand, lower DS Mental Status Examination memory scores were associated with higher PRS, independent of intellectual disability and APOE (PRS including APOE, PRS APOE , p = 2.84 × 10 -4 ; PRS excluding APOE, PRS nonAPOE , p = 1.60 × 10 -2 ). PRS APOE exhibited significant associations with Aβ42, tTau, pTau, and Aβ42/40 ratio in DS., Discussion: These data indicate that the AD genetic architecture influences cognitive and CSF phenotypes in DS adults, supporting common pathways that influence memory decline in both traits., Highlights: Examination of the polygenic risk of AD in DS presented here is the first of its kind. AD PRS influences memory aspects in DS individuals, independently of APOE genotype. These results point to an overlap between the genes and pathways that leads to AD and those that influence dementia and memory decline in the DS population. APOE ε4 is linked to DS cognitive decline, expanding cognitive insights in adults., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Studies suggest distinct differences in the development, presentation, progression, and response to treatment of Alzheimer's disease (AD) between females and males. We investigated sex differences in cognition, neuroimaging, and fluid biomarkers in dominantly inherited AD (DIAD)., Methods: Three hundred twenty-five mutation carriers (55% female) and one hundred eighty-six non-carriers (58% female) of the Dominantly Inherited Alzheimer Network Observational Study were analyzed. Linear mixed models and Spearman's correlation explored cross-sectional sex differences in cognition, cerebrospinal fluid (CSF) biomarkers, Pittsburgh compound B positron emission tomography ( 11 C-PiB PET) and structural magnetic resonance imaging (MRI)., Results: Female carriers performed better than males on delayed recall and processing speed despite similar hippocampal volumes. As the disease progressed, symptomatic females revealed higher increases in MRI markers of neurodegeneration and memory impairment. PiB PET and established CSF AD markers revealed no sex differences., Discussion: Our findings suggest an initial cognitive reserve in female carriers followed by a pronounced increase in neurodegeneration coupled with worse performance on delayed recall at later stages of DIAD., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Comparisons of late-onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age., Methods: We compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound-B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non-carriers (NON-MCs), and ACS participants with a positive (FH+) and negative (FH-) family history of LOAD., Results: At baseline, MCs had the lowest age-adjusted level of CSF Aβ42 and the highest levels of total and phosphorylated tau-181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline., Discussion: Preclinical ADAD and LOAD share many biomarker signatures, but cross-sectional and longitudinal differences may exist., (© 2023 the Alzheimer's Association.)

Background: Glial fibrillary acidic protein (GFAP) is a promising candidate blood-based biomarker for Alzheimer's disease (AD) diagnosis and prognostication. The timing of its disease-associated changes, its clinical correlates, and biofluid-type dependency will influence its clinical utility., Methods: We evaluated plasma, serum, and cerebrospinal fluid (CSF) GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease., Results: Plasma GFAP elevations appear a decade before expected symptom onset, after amyloid beta (Aβ) accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished Aβ-positive from Aβ-negative ADAD participants and showed a stronger relationship with Aβ load in asymptomatic than symptomatic ADAD. Higher plasma GFAP was associated with the degree and rate of neurodegeneration and cognitive impairment. Serum GFAP showed similar relationships, but these were less pronounced for CSF GFAP., Conclusion: Our findings support a role for plasma GFAP as a clinical biomarker of Aβ-related astrocyte reactivity that is associated with cognitive decline and neurodegeneration., Highlights: Plasma glial fibrillary acidic protein (GFAP) elevations appear a decade before expected symptom onset in autosomal dominant Alzheimer's disease (ADAD). Plasma GFAP was associated to amyloid positivity in asymptomatic ADAD. Plasma GFAP increased with clinical severity and predicted disease progression. Plasma and serum GFAP carried similar information in ADAD, while cerebrospinal fluid GFAP did not., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia., Methods: We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis., Results: A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC = 0.79), and apolipoprotein E genotype (AUC = 0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC = 0.84), and for plasma amyloid beta (Aβ)42/Aβ40 (AUC = 0.82)., Discussion: An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults., (© 2022 the Alzheimer's Association.)

A crucial aspect of any clinical trial is using the right outcome measure to assess treatment efficacy. Compared to the rapidly evolved understanding and measurement of pathophysiology in preclinical and early symptomatic stages of Alzheimer's disease (AD), relatively less progress has been made in the evolution of clinical outcome assessments (COAs) for those stages. The current paper aims to provide a benchmark for the design and evaluation of COAs for use in early AD trials. We discuss lessons learned on capturing cognitive changes in predementia stages of AD, including challenges when validating novel COAs for those early stages and necessary evidence for their implementation in clinical trials. Moving forward, we propose a multi-step framework to advance the use of more effective COAs to assess clinically meaningful changes in early AD, which will hopefully contribute to the much-needed consensus around more appropriate outcome measures to assess clinical efficacy of putative treatments. HIGHLIGHTS: We discuss lessons learned on capturing cognitive changes in predementia stages of AD. We propose a framework for the design and evaluation of performance based cognitive tests for use in early AD trials. We provide recommendations to facilitate the implementation of more effective cognitive outcome measures in AD trials., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD., Methods: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers., Results: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1%. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time., Discussion: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others., Methods: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation., Results: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors., Discussion: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression., (© 2022 the Alzheimer's Association.)

Introduction: Longitudinal changes in Alzheimer's disease (AD) biomarkers, including cerebrospinal fluid (CSF) analytes, amyloid uptakes from positron emission tomography (PET), structural outcomes from magnetic resonance imaging (MRI), and cognition, have not been compared between Blacks and Whites., Methods: A total of 179 Blacks and 1180 Whites who were cognitively normal at baseline and had longitudinal data from at least one biomarker modality were analyzed for the annual rates of change., Results: CSF amyloid beta (Aβ)42/Aβ40 declined more slowly (P = .0390), and amyloid (PET) accumulated more slowly (P = .0157), in Blacks than Whites. CSF Aβ42 changed in opposite directions over time between Blacks and Whites (P = .0039). The annual increase in CSF total tau and phosphorylated tau181 for Blacks was about half of that for Whites., Discussion: Longitudinal racial differences in amyloid biomarkers are observed. It will be important to comprehensively and prospectively examine the effects of apolipoprotein E genotype and sociocultural factors on these differences., (© 2022 the Alzheimer's Association.)

As prevention trials advance with autosomal dominant Alzheimer disease (ADAD) participants, understanding the similarities and differences between ADAD and "sporadic" late-onset AD (LOAD) is critical to determine generalizability of findings between these cohorts. Cognitive trajectories of ADAD mutation carriers (MCs) and autopsy-confirmed LOAD individuals were compared to address this question. Longitudinal rates of change on cognitive measures were compared in ADAD MCs (n = 310) and autopsy-confirmed LOAD participants (n = 163) before and after symptom onset (estimated/observed). LOAD participants declined more rapidly in the presymptomatic (preclinical) period and performed more poorly at symptom onset than ADAD participants on a cognitive composite. After symptom onset, however, the younger ADAD MCs declined more rapidly. The similar but not identical cognitive trajectories (declining but at different rates) for ADAD and LOAD suggest common AD pathologies but with some differences., (© 2021 the Alzheimer's Association.)

Introduction: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease., Methods: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status., Results: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R 2  = 0.95), fluorodeoxyglucose (R 2  = 0.93), and atrophy (R 2  = 0.95) in mutation carriers compared to non-carriers., Discussion: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions., (© 2021 the Alzheimer's Association.)

Introduction: The Clinical Dementia Rating (CDR) is widely used in Alzheimer's disease research studies and has well established reliability and validity. To facilitate the development of an online, electronic CDR (eCDR) for more efficient clinical applications, this study aims to produce a shortened version of the CDR, and to develop the statistical model for automatic scoring., Methods: Item response theory (IRT) was used for item evaluation and model development. An automatic scoring algorithm was validated using existing CDR global and domain box scores as the reference standard., Results: Most CDR items discriminate well at mild and very mild levels of cognitive impairment. The bi-factor IRT model fits best and the shortened CDR still demonstrates very high classification accuracy (81%∼92%)., Discussion: The shortened version of the CDR and the automatic scoring algorithm has established a good foundation for developing an eCDR and will ultimately improve the efficiency of cognitive assessment., (© 2020 the Alzheimer's Association.)

Introduction: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge., Methods: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated., Results: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R 2 = 24%) and memory (R 2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%-75%., Discussion: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD., (© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

Introduction: Although some members of families with autosomal dominant Alzheimer's disease mutations learn their mutation status, most do not. How knowledge of mutation status affects clinical disease progression is unknown. This study quantifies the influence of mutation awareness on clinical symptoms, cognition, and biomarkers., Methods: Mutation carriers and non-carriers from the Dominantly Inherited Alzheimer Network (DIAN) were stratified based on knowledge of mutation status. Rates of change on standard clinical, cognitive, and neuroimaging outcomes were examined., Results: Mutation knowledge had no associations with cognitive decline, clinical progression, amyloid deposition, hippocampal volume, or depression in either carriers or non-carriers. Carriers who learned their status mid-study had slightly higher levels of depression and lower cognitive scores., Discussion: Knowledge of mutation status does not affect rates of change on any measured outcome. Learning of status mid-study may confer short-term changes in cognitive functioning, or changes in cognition may influence the determination of mutation status., (© 2020 the Alzheimer's Association.)

Introduction: Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention., Methods: Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β-amyloid with positron emission tomography, magnetic resonance imaging-based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated., Results: The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudinal data), and 1498 participated in the positron emission tomography amyloid studies (849 had longitudinal data). The database provides adequate power for detecting early biomarker changes, and demonstrates the feasibility of AD prevention trials on middle-aged individuals., Discussion: The harmonized database is an optimum resource to design AD prevention trials decades before symptomatic onset., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: Vascular factors increase the risk of Alzheimer's disease (AD). We investigated the associations between such factors, longitudinal AD cerebrospinal fluid biomarkers, and cognition., Methods: 433 cognitively normal participants were classified into four biomarker groups using their baseline amyloid (A+/-) and tau status (T+/-). 184 participants had undergone serial cerebrospinal fluid collection. Frequencies of risk factors and the Framingham Risk Score (FRS) were compared, and we tested the influence of risk factors on change in biomarker concentrations and cognition., Results: The absence of obesity, presence of hypertension, and a high FRS were associated with an increase in tau levels, particularly in A+T+ individuals. Risk factors were not associated with amyloid. Depression was associated with higher cognitive scores, whereas high FRS was associated with lower scores and a faster decline., Discussion: Our results demonstrate that vascular risk factors may enhance neurodegeneration but not amyloid accumulation in preclinical AD., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: Four less well-studied but promising "emerging" cerebrospinal fluid (CSF) biomarkers are elevated in late-onset Alzheimer disease (AD): neurogranin, synaptosomal-associated protein-25 (SNAP-25), visinin-like protein 1 (VILIP-1), and chitinase-3-like protein 1 (YKL-40)., Methods: CSF neurogranin, SNAP-25, VILIP-1, and YKL-40 were measured in families carrying autosomal-dominant AD mutations., Results: The four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP-25, VILIP-1, and YKL-40 were altered very early in the AD time course, approximately 15-19 years before estimated symptom onset. All CSF biomarkers predicted important AD-related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset., Discussion: Early abnormalities in CSF tTau, pTau, SNAP-25, VILIP-1, and YKL-40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation., (Copyright © 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: Staging preclinical Alzheimer disease (AD) by the expected years to symptom onset (EYO) in autosomal dominant AD (ADAD) through biomarker correlations is important., Methods: We estimated the correlation matrix between EYO/cognition and imaging/CSF biomarkers, and searched for the EYO cutoff where a change in the correlations occurred before and after the cutoff among the asymptomatic mutation carriers of ADAD. We then estimated the longitudinal rate of change for biomarkers/cognition within each preclinical stage defined by the EYO., Results: Based on the change in the correlations, the preclinical ADAD was divided by EYOs -7 and -13 years. Mutation carriers demonstrated a temporal ordering of biomarker/cognition changes across the three preclinical stages., Discussion: Duration of each preclinical stage can be estimated in ADAD, facilitating better planning of prevention trials with the EYO cutoffs under the recently released FDA guidance. The generalization of these results to sporadic AD warrants further investigation., (Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Introduction: The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer's disease in autosomal dominant Alzheimer's disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation (NexGen) prevention trial., Methods: In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the National Institutes of Health, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen prevention trial., Results: Our expanded trial toolbox consists of a disease progression model for ADAD, primary end point DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion., Conclusion: These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD., (Copyright © 2016 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)