Citations

AbstractINTRODUCTIONWe used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early‐onset Alzheimer's disease (EOAD).METHODSWe included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non‐Alzheimer's disease (EOnonAD) participants from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel‐wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden.RESULTSEOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non‐carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non‐carriers also had greater gray matter atrophy than female ε4 carriers.DISCUSSIONThe effects of sex and APOE ε4 must be considered when studying these populations.HIGHLIGHTS Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE ε4) carrier status on neuroimaging biomarkers among early‐onset Alzheimer's disease (EOAD), early‐onset non‐AD (EOnonAD), and cognitively normal (CN) participants. Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex. The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts.

Abstract INTRODUCTION We compared white matter hyperintensities (WMHs) in early‐onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups in the Longitudinal Early‐Onset Alzheimer's Disease Study. METHODS We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t ‐tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. Highlights This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups across all brain regions.

AbstractIntroductionOne goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early‐onset Alzheimer's disease (EOAD).MethodsCerebrospinal fluid (CSF) concentrations of Aβ1‐40, Aβ1‐42, total tau (tTau), pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated.ResultsBiomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP‐25, and Ng in EOAD differed significantly from cognitively normal and early‐onset non‐AD dementia; NfL, YKL‐40, and VILIP‐1 did not. Across groups, all biomarkers except SNAP‐25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP‐25 were correlated with at least one cognitive measure.DiscussionThis study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design.

AbstractIntroductionWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use in a large sample of individuals with early‐onset Alzheimer's disease (EOAD; onset 40‐64 years) at the midway point of data collection for the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS).MethodsBaseline NPS (Neuropsychiatric Inventory – Questionnaire; Geriatric Depression Scale) and psychotropic medication use from 282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid negative early‐onset non‐Alzheimer's disease (EOnonAD; n = 70).ResultsAffective behaviors were the most common NPS in EOAD at similar frequencies to EOnonAD. Tension and impulse control behaviors were more common in EOnonAD. A minority of participants were using psychotropic medications, and use was higher in EOnonAD.DiscussionOverall NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants. Future research will investigate moderators and etiological drivers of NPS, and NPS differences in EOAD versus late‐onset AD.

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.

AbstractAlzheimer's disease (AD) is the most common type of dementia in the elderly with no effective treatment currently. Recent studies of noninvasive neuroimaging, resting‐state functional magnetic resonance imaging (rs‐fMRI) with graph theoretical analysis have shown that patients with AD and mild cognitive impairment (MCI) exhibit disrupted topological organization in large‐scale brain networks. In previous work, it is a common practice to threshold such networks. However, it is not only difficult to make a principled choice of threshold values, but also worse is the discard of potential important information. To address this issue, we propose a threshold‐free feature by integrating a prior persistent homology‐based topological feature (the zeroth Betti number) and a newly defined connected component aggregation cost feature to model brain networks over all possible scales. We show that the induced topological feature (Integrated Persistent Feature) follows a monotonically decreasing convergence function and further propose to use its slope as a concise and persistent brain network topological measure. We apply this measure to study rs‐fMRI data from the Alzheimer's Disease Neuroimaging Initiative and compare our approach with five other widely used graph measures across five parcellation schemes ranging from 90 to 1,024 region‐of‐interests. The experimental results demonstrate that the proposed network measure shows more statistical power and stronger robustness in group difference studies in that the absolute values of the proposed measure of AD are lower than MCI and much lower than normal controls, providing empirical evidence for decreased functional integration in AD dementia and MCI.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late‐onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. Methods We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news‐publications/publications/ ). Results (1) Data‐driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β‐Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a “typical AD” subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. Discussion ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.