Citations

AbstractBackgroundThe overarching goal of the Longitudinal Early‐onset Alzheimer Disease study (LEADS) is to optimally characterize early‐onset AD (EOAD) and establish an EOAD clinical trials network. Here we report the baseline demographic and imaging biomarker comparisons of the LEADS cohort to late‐onset AD (LOAD) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI3).Method123 amyloid‐positive EOAD, 47 amyloid‐negative EOnonAD, 60 cognitively normal young controls were compared to 130 amyloid‐positive LOAD, 110 amyloid‐negative LOnonAD and 286 amyloid‐negative cognitively normal older controls. To account for the effect of cognitive aging between EO and LO populations, each cognitive measure was Z‐transformed. Cortical and hippocampal atrophy were quantified using W‐scores adjusted for age, sex and total intracranial volume. Z‐scores and W‐scores were compared using t‐test or Wilcoxson rank test as appropriate. All p‐values were corrected for multiple comparisons using the false discovery rate correction.ResultEOAD showed greater pathology burden and greater cortical atrophy (AD signature) relative to LOAD. EOAD also showed greater cognitive impairment across all cognitive tests. EOAD showed greater functional impairment, more depression but less neuropsychiatric behaviors overall compared to LOAD (Table 1 and Figure 1, all ps<0.05). Repeating the analyses stratified by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.EOnonAD differed from LOnonAD by also showing greater impairment on all cognitive and functional measures There were no significant differences in amyloid and tau burden, or atrophy W‐scores between these groups. EOnonAD were more depressed and showed more functional impairment compared to LOnonAD (Table 2 and Figure 2, all ps<0.05). Repeating the analyses split by cognitive stage (MCI/dementia) or CDR global rating (0.5/1) did not result in any major differences.ConclusionConsistent with our preexisting hypotheses, EOAD and EOnonAD perform much worse relative to their LO counterparts. EOAD also show greater pathological burden as expected. The reported analyses were done in chronological rather than disease time (time since disease onset). Benchmarking individuals along the disease spectrum might prove to be a better strategy especially when conducting analyses on rate of disease progression.

AbstractPatients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.

AbstractBackgroundApproximately 5% of the 5.6 million (∼280,000) Americans with Alzheimer’s disease (AD) develop symptoms at age 65 or younger and are classified as having early‐onset AD (EOAD). Although EOAD and late‐onset AD (LOAD) share the same pathologic substrate, there are notable differences in their clinical and biological phenotypes. The Longitudinal Early‐onset AD study (LEADS) is a multi‐site, observational clinical and biomarker study of EOAD. In the present study we utilized the currently available LEADS imaging data to explore the spatial extent and magnitude of neurodegeneration EOADMethod95 amyloid positive patients with EOAD, 37 amyloid negative cognitively impaired patients (EOnonAD) , and 55 cognitively unimpaired controls (CNs) were included in the analysis. The magnitude of cortical thinning in the EOAD and EOnonAD groups was estimated using whole‐brain GLMs compared to the CN group. In addition, w‐scores were derived for each EOAD patient for these ROIs: average cortical thickness, hippocampal volume, AD‐signature cortical thickness (typically used in LOAD), and precuneus cortical thickness controlling for age, sex, and acquisition site. The utility of each ROI to differentiate EOAD patients from CNs was assessed by calculating the percentage of patients falling below a W‐threshold of ‐1.5.ResultIn EOAD, a distributed pattern of cortical thinning was observed in lateral temporal, parietal, and frontal cortex (p<.01), and was most prominent in the precuneus (Cohen’s d’ = 1.5). In the EOnonAD group, cortical thinning was observed but was highly variable across individuals. The w‐score analysis in the EOAD group yielded the following results: Mean Cortical thickness: Mean = ‐3.34, SD = 2.97, Classification = 72%.; Hippocampal volume: Mean = ‐2.96, SD = 2.39, Classification = 74%; AD Signature: Mean = ‐4.63, SD = 3.07, Classification = 80%; Precuneus: Mean = ‐5.98, SD = 4.1, Classification = 90%.ConclusionOur results are consistent with previous findings demonstrating cortical thinning in lateral parietal, precuneus, and lateral temporal lobes in EOAD with relatively less involvement of the medial temporal lobes. Our results also suggest that the precuneus may be especially vulnerable to neurodegeneration in patients with EOAD and may serve as a useful biomarker for patient classification.

AbstractBackgroundWhite matter (WM) hypointensity volume in T1 MRI correlates strongly with T2 hyperintensities and both are typically associated with advancing age and vascular brain injury (VBI). Recent research has suggested that Alzheimer’s Disease (AD) neuropathologic changes (ADNC) also increases WM hypointensity volume. Sporadic early onset AD (EOAD) patients provide a unique model to examine the relationship between ADNC biomarkers and WM hypointensity volume in the absence of advanced age, cardiovascular injury, or autosomal dominant genetic mutations.MethodIncluded in the analysis were sporadic EOAD patients (n = 75) and cognitively normal controls (n = 39) from the Longitudinal Alzheimer’s Disease Study (LEADS) for whom full demographic and health information were available. WM hypointensity volume in T1 MRI was segmented by Freesurfer and corrected for total white matter volume. Multiple‐factor ANOVA models with logarithmic transformations were used to determine the effects of age, cohort, and presence of cardiovascular conditions on WM hypointensity volume. Further multiple‐factor ANOVA models assessed whether the addition of covariates improved the model fit.ResultIn a reproduction of prior research, WM hypointensity volume was correlated with age for controls (p < 0.05), but not for EOAD patients. We additionally found an effect of cohort, such that EOAD patients had a higher mean WM hypointensity volume than controls when accounting for age (p < 0.05). No difference in the presence or number of cardiovascular conditions was found between groups. Additionally, no correlation was found between WM hypointensity volume and the presence or number of cardiovascular conditions. Including cardiovascular condition as a covariate failed to improve the model fit, even when accounting for interaction effects.ConclusionThese results support the hypothesis that patients with ADNC have higher WM hypointensity volume beyond what would be expected based on aging or cardiovascular risk factors. Further research is needed to assess the co‐localization of WM hypointensities with cortical degradation, amyloid pathology, and tau pathology.

AbstractBackgroundPrevious studies have reported that age modifies the distribution and burden of tau (and, to a lesser extent, amyloid) pathology in sporadic Alzheimer’s disease (AD). Here we present preliminary baseline amyloid and tau PET results from the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), a multi‐site longitudinal study of sporadic early‐onset AD.Method135 patients meeting clinical criteria for MCI or probable AD and 50 cognitively normal controls (all age<65 at enrollment) were enrolled at 12 US centers between August 2018 and December 2019 (Table 1). 18F‐Florbetaben amyloid‐PET (FBB) was used to assign patients to EOAD (amyloid‐positive) or EOnonAD (amyloid‐negative) subgroups based on visual rating and semi‐quantification. 130 patients and all controls had 18F‐Flortaucipir tau‐PET (FTP). Regional Standardized Uptake Value Ratios (SUVR) for FBB (whole cerebellum reference) and FTP (inferior cerebellar gray reference) were extracted using co‐registered 3T‐MRI.Result98 patients (72.6%) were amyloid PET‐positive (EOAD) and 37 (27.4%) were amyloid PET‐negative (EOnonAD). Compared to EOAD, EOnonAD patients had higher MMSE, MOCA and CDR sum‐of‐boxes (CDR‐SB) and were more frequently male (Table 1). Patients with EOAD showed elevated FBB and FTP SUVR in temporoparietal and frontal cortex compared to CN and EOnonAD (Figures 1‐2). In EOAD, MMSE, MOCA and CDR‐SB were significantly correlated with FTP SUVR (Figure 3), while no significant correlations were found with FBB SUVR. EOnonAD patients showed variable FTP binding ranging from negative to mildly elevated binding in anterior temporal and frontal cortex and underlying white matter. Two EOnonAD cases showed intense FTP binding comparable to typical EOAD cases, despite visually and quantitatively negative FBB scans.ConclusionPatients with clinically mild, sporadic EOAD typically show an extensive distribution and burden of tau pathology in the setting of positive amyloid PET. Global clinical measures correlate with tau but not amyloid PET. Over 25% of patients meeting clinical criteria for early‐onset MCI/probable AD have negative amyloid PET, suggesting alternative etiologies for cognitive decline. These findings will inform future design of drug trials in this important and under‐studied population.

AbstractBackgroundOur understanding of the biological changes in the brain associated with Alzheimer’s disease (AD) pathology and cognitive impairment remains incomplete. Unbiased discovery proteomic analysis of AD brain can help to increase our understanding of these changes.MethodWe analyzed dorsolateral prefrontal cortex, precuneus, and temporal cortex of control, asymptomatic AD, and AD brains from multiple different centers by label‐free quantitative mass spectrometry and weighted protein co‐expression analysis to obtain a consensus protein co‐expression network of AD brain. We also analyzed cerebrospinal fluid to investigate potential biomarkers related to this network.ResultThe network consisted of 13 protein co‐expression modules. Six of these modules correlated with amyloid‐β plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community‐based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti‐inflammatory state, suggesting that the biological functions it represents may serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network.ConclusionIn this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.