Citations

AbstractObjectiveThe Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early‐onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data‐collection mid‐point.MethodsData from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid‐positive EOAD [n = 212], and amyloid‐negative early‐onset non‐Alzheimer's disease [EOnonAD; n = 70]).ResultsCognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures.ConclusionsWe present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant.HIGHLIGHTS Findings represent the most comprehensive baseline characterization of sporadic early‐onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups. EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group. Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present.

AbstractOBJECTIVEInvestigation of learning slopes in early‐onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early‐onset dementia with and without β‐amyloid positivityMETHODData from 310 participants in the Longitudinal Early‐Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determinedRESULTSWorse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric—the learning ratio (LR)—outperformed other learning slope calculations across analysesCONCLUSIONSLearning slopes appear to be sensitive to early‐onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses.Highlights Learning is impaired in amyloid‐positive EOAD, beyond cognitive severity scores alone. Amyloid‐positive EOAD participants perform worse on learning slopes than amyloid‐negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.

AbstractIntroductionLumbar puncture (LP) to collect and examine cerebrospinal fluid (CSF) is an important option for the evaluation of Alzheimer's disease (AD) biomarkers but it is not routinely performed due to its invasiveness and link to adverse effects (AE).MethodsWe include all participants who received at least one LP in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Study. For comparison between groups, two‐sample t‐tests for continuous, and Pearson's chi‐square test for categorical variables were performed.ResultsTwo hundred twenty‐seven LP‐related AEs were reported by 172 participants after 1702 LPs (13.3%). The mean age of participants who reported at least one AE was 69.79 (standard deviation (SD) 6.3) versus none 72.44 (7.17) years (p < 0.001) with female predominance (115/172 = 67.4% vs 435/913 = 48%), and had greater entorhinal cortical thickness and hippocampal volume (3.903 (0.782) vs 3.684 (0.775) mm, p = 0.002; 7.38 (1.06) vs 7.05 (1.15) mm3, p < 0.001), respectively.DiscussionWe found that younger age, female sex, and greater thickness of the entorhinal cortex were associated with a higher rate of LP‐related AE reports.

Abstract Alzheimer's disease (AD) clinical trials are designed and powered to detect the impact of a therapeutic intervention, and there has been considerable discussion on what constitutes a clinically meaningful change in those receiving treatment versus placebo. The pathology of AD is complex, beginning many years before clinical symptoms are detectable, with multiple potential opportunities for therapeutic engagement. Introducing treatment strategies early in the disease and assessing meaningful change over the course of an 18‐month clinical trial are critical to understanding the value to an effective intervention. With new clinical trial data expected soon on emerging therapeutics from several AD studies, the Alzheimer's Association convened a work group of experts to discuss key considerations for interpreting data from cognitive and functional measures and what is considered a clinically meaningful benefit or meaningful slowing of this fatal disease. Our expectations of outcomes from therapeutic interventions in AD may need to be modified.

Abstract Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off‐schedule, as including off‐schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical‐time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.

AbstractBackgroundPreviously, we found that female sex is associated with greater pathology burden in early‐onset Alzheimer’s disease (EOAD) in the Longitudinal EOAD Study (LEADS). Here, we have expanded our analyses by adding APOE‐ε4 carrier status as a further predictor of EOAD pathologic burden.MethodWe included 180 EOAD LEADS participants with available APOE genotype, Flortaucipir PET, Florbetaben PET, and MRI data. Demographic and biomarker differences were analyzed using ANOVA. EOAD participants were split by sex and APOE‐ε4 carrier status. Box plots were created in R and a voxel‐wise multiple linear regression in SPM12 yielded statistical brain maps of gray matter density (GMD), amyloid and tau burden.ResultCompared to males, EOAD females showed significantly greater global amyloid uptake (mean SUVR, p=0.002) and greater tau SUVR in the MetaROI, Braak 3&4 and 5&6 regions (p=0.0007, p=0.001, p=0.01, resp., Table 1). Female APOE‐ε4 carriers showed greater tau SUVR in Braak regions 1&2 than female non‐carriers (p<0.01, Figure 2B). Male APOE‐ε4 carriers showed trend‐level thinner entorhinal cortex than male non‐carriers (p=0.06, Figure 1). Interestingly however, femaleAPOE‐ε4 non‐carriers showed greater global amyloid SUVR than female carriers (p<0.01, Figure 2A). Further, APOE‐ε4 non‐carriers showed significantly thinner medial temporal cortices than carriers in both sexes (M, p<0.05; F, p<0.01). Male APOE‐ε4 non‐carriers also showed significantly lower mean cortical thickness than male carriers (p<0.05, Figure 1). Female APOE‐ε4 non‐carriers showed trend‐level lower mean cortical thickness than female carriers (p=0.06, Figure 1). The FWE corrected SPM12 maps showed significantly greater GM atrophy in the right temporal lobe and greater amyloid burden in a right lateralized occipitoparietal pattern in female APOE‐ε4 non‐carriers compared to female carriers. Further, male APOE‐ε4 non‐carriers showed greater tau uptake in the left frontal lobe than male carriers (Figure 3).ConclusionThese results suggest that APOE‐ε4 non‐carrier status is associated with greater atrophy, amyloid and tau deposition in EOAD. This might be due to the presence of other strong genetic drivers of disease pathology in EOAD.

AbstractBackgroundWe developed the Institute on Methods and Protocols for Advancement of Clinical Trials in ADRD (IMPACT‐AD) to address the shortage of qualified investigators with adequate training and expertise to conduct Alzheimer’s Disease (AD) and AD Related Dementias (ADRD) clinical trials.MethodWe describe the experience of the first two years of funding of the IMPACT‐AD course, specifically the rates of applications to the course, descriptive summaries of the accepted trainees, and the measures of participant satisfaction and learning.ResultOver the first two years of the course, we received 195 eligible applications to the course. Most (n = 121, 62%) applicants were female and nearly half self‐reported as being African American/Black, Asian, or Pacific Islander race and/or Hispanic/Latino ethnicity. Forty‐one applicants (21%) indicated that they were the first in their family to attend collegeOf 69 total trainees accepted to the course (36% acceptance rate), a majority (n = 44, 64%) were female. Twenty‐eight (41%) self‐reported as being African American/Black, Asian, or Pacific Islander race and eleven (16%) were of Hispanic ethnicity. Fourteen trainees (20%) identified as being the first person in their family to attend college. Among trainees, 24 (35%) were MDs, 30 (43%) were PhDs, and 9 (13%) held master’s degrees.Course lecture topics were rated, on average, as “essential” or “valuable” by 98% of trainees. Across lecture topics, on average, 48% of trainees rated their prior knowledge of topics as “very strong” or “strong,” and 11% of trainees rated their prior knowledge as “weak.” Overall, 52% of trainees evaluated their change in knowledge based on the lectures as “very much increased,” 46% as “somewhat” or “slightly” increased, and 2% as “no change.” Results were similar for the two tracks. Based on pre‐ and post‐course assessments, trainees improved their knowledge of covered content (from 62% to 79% correct responses on knowledge assessments).ConclusionThe IMPACT‐AD course is achieving its mission of educating and diversifying the next generation of ADRD trialists.We thank Dr. Laurie Ryan and Dr. Kristina McLinden from the National Institute on Aging for their key contributions in leadership and scientific guidance of IMPACT‐AD.

AbstractThe poor generalizability of clinical research data due to the enrollment of highly educated, non‐Latinx White participants hampers the development of therapies for Alzheimer's disease (AD). Black and Latinx older adults have a greater risk for dementia, yet it is unclear how health‐care disparities and sociocultural factors influence potential AD therapies and prognosis. Low enrollment of under‐represented populations may be attributable to several factors including greater exclusion due to higher rates of comorbidities, lower access to AD clinics, and the legacy of unethical treatment in medical research. This perspective outlines solutions tested in the Brain Health Registry (BHR) and the Alzheimer's Disease Neuroimaging Initiative (ADNI), including culturally‐informed digital research methods, community‐engaged research strategies, leadership from under‐represented communities, and the reduction of exclusion criteria based on comorbidities. Our successes demonstrate that it is possible to increase the inclusion and engagement of under‐represented populations into US‐based clinical studies, thereby increasing the generalizability of their results.

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50‐60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022.MethodsADNI4 will recruit URPs using community‐engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50‐60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in‐clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials.Results and DiscussionADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.

AbstractIntroductionEpidemiological studies report an association between traumatic brain injury (TBI) and post‐traumatic stress disorder (PTSD) and clinically diagnosed Alzheimer's disease (AD). We examined the association between TBI/PTSD and biomarker‐defined AD.MethodsWe identified 289 non‐demented veterans with TBI and/or PTSD and controls who underwent clinical evaluation, cerebrospinal fluid (CSF) collection, magnetic resonance imaging (MRI), amyloid beta (Aβ) and tau positron emission tomography, and apolipoprotein E testing. Participants were followed for up to 5.2 years.ResultsExposure groups (TBI, PTSD, and TBI + PTSD) had higher prevalence of mild cognitive impairment (MCI: P < .0001) and worse Mini‐Mental State Examination scores (PTSD: P = .008; TBI & PTSD: P = .009) than controls. There were no significant differences in other cognitive scores, MRI volumes, Aβ or tau accumulation, or in most longitudinal measures.DiscussionTBI and/or PTSD were not associated with elevated AD biomarkers. The poorer cognitive status of exposed veterans may be due to other comorbid pathologies.