Neuropathologic assessment of participants in two multi-center longitudinal observational studies: the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN)

It has been hypothesized that the relatively rare autosomal dominant Alzheimer disease (ADAD) may be a useful model of the more frequent, sporadic, late-onset AD (LOAD). Individuals with ADAD have a predictable age at onset and the biomarker profile of ADAD participants in the preclinical stage may be used to predict disease progression and clinical onset. However, the extent to which the pathogenesis and neuropathology of ADAD overlaps with that of LOAD is equivocal. To address this uncertainty, two multicenter longitudinal observational studies, the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN), leveraged the expertise and resources of the existing Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine, St. Louis, Missouri, USA, to establish a Neuropathology Core (NPC). The ADNI/DIAN-NPC is systematically examining the brains of all participants who come to autopsy at the 59 ADNI sites in the USA and Canada and the 14 DIAN sites in the USA (8), Australia (3), UK (1), and Germany (2). By 2014, 41 ADNI and 24 DIAN autopsies (involving 9 participants and 15 family members) had been performed. The autopsy rate in the ADNI cohort in the most recent year was 93% (total since NPC inception: 70%). In summary, the ADNI/DIAN NPC has implemented a standard protocol for all sites to solicit permission for brain autopsy and to send brain tissue to the NPC for a standardized, uniform, and state-of-the-art neuropathologic assessment. The benefit to ADNI and DIAN of the implementation of the NPC is very clear. The NPC provides final ‘gold standard’ neuropathological diagnoses and data against which the antecedent observations and measurements of ADNI and DIAN can be compared

An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations.

Parietal cortex RNA-sequencing (RNA-seq) data were generated from individuals with and without Alzheimer disease (AD; ncontrol = 13; nAD = 83) from the Knight Alzheimer Disease Research Center (Knight ADRC). Using this and an independent (Mount Sinai Brain Bank (MSBB)) AD RNA-seq dataset, cortical circular RNA (circRNA) expression was quantified in the context of AD. Significant associations were identified between circRNA expression and AD diagnosis, clinical dementia severity and neuropathological severity. It was demonstrated that most circRNA-AD associations are independent of changes in cognate linear messenger RNA expression or estimated brain cell-type proportions. Evidence was provided for circRNA expression changes occurring early in presymptomatic AD and in autosomal dominant AD. It was also observed that AD-associated circRNAs co-expressed with known AD genes. Finally, potential microRNA-binding sites were identified in AD-associated circRNAs for miRNAs predicted to target AD genes. Together, these results highlight the importance of analyzing non-linear RNAs and support future studies exploring the potential roles of circRNAs in AD pathogenesis

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease

Introduction: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is commonly used to estimate neuronal injury in Alzheimer's disease (AD). Here, we evaluate the utility of dynamic PET measures of perfusion using 11C-Pittsburgh compound B (PiB) to estimate neuronal injury in comparison to FDG PET. Methods: FDG, early frames of PiB images, and relative PiB delivery rate constants (PiB-R1) were obtained from 110 participants from the Dominantly Inherited Alzheimer Network. Voxelwise, regional cross-sectional, and longitudinal analyses were done to evaluate the correlation between images and estimate the relationship of the imaging biomarkers with estimated time to disease progression based on family history. Results: Metabolism and perfusion images were spatially correlated. Regional PiB-R1 values and FDG, but not early frames of PiB images, significantly decreased in the mutation carriers with estimated year to onset and with increasing dementia severity. Discussion: Hypometabolism estimated by PiB-R1 may provide a measure of brain perfusion without increasing radiation exposure

Ante- and postmortem tau in autosomal dominant and late-onset Alzheimer\u27s disease

Antemortem tau positron emission tomography imaging suggests elevated tau pathology in autosomal dominant versus late-onset Alzheimer\u27s disease at equivalent clinical stages, but does not implicate the specific tau pathologies responsible. Here we made stereological measurements of tau neurofibrillary tangles, neuritic plaques, and neuropil threads and found compared to late-onset Alzheimer\u27s disease, autosomal dominant Alzheimer\u27s disease showed even greater tangle and thread burdens. Regional tau burden resembled that observed in tau imaging of a separate cohort at earlier clinical stages. Finally, our results suggest tau imaging measures total tau burden in Alzheimer\u27s disease, composed predominantly of tangle and thread pathology

Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer\u27s disease

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer\u27s disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score\u27s predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials

Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer\u27s disease

Amyloid-beta deposition is one of the hallmark pathologies in both sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease, the latter of which is caused by mutations in genes involved in amyloid-beta processing. Despite amyloid-beta deposition being a centrepiece to both sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease, some differences between these Alzheimer\u27s disease subtypes have been observed with respect to the spatial pattern of amyloid-beta. Previous work has shown that the spatial pattern of amyloid-beta in individuals spanning the sporadic Alzheimer\u27s disease spectrum can be reproduced with high accuracy using an epidemic spreading model which simulates the diffusion of amyloid-beta across neuronal connections and is constrained by individual rates of amyloid-beta production and clearance. However, it has not been investigated whether amyloid-beta deposition in the rarer autosomal-dominant Alzheimer\u27s disease can be modelled in the same way, and if so, how congruent the spreading patterns of amyloid-beta across sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease are. We leverage the epidemic spreading model as a data-driven approach to probe individual-level variation in the spreading patterns of amyloid-beta across three different large-scale imaging datasets (2 sporadic Alzheimer\u27s disease, 1 autosomal-dominant Alzheimer\u27s disease). We applied the epidemic spreading model separately to the Alzheimer\u27s Disease Neuroimaging initiative (n = 737), the Open Access Series of Imaging Studies (n = 510) and the Dominantly Inherited Alzheimer\u27s Network (n = 249), the latter two of which were processed using an identical pipeline. We assessed inter-and intra-individual model performance in each dataset separately and further identified the most likely subject-specific epicentre of amyloid-beta spread. Using epicentres defined in previous work in sporadic Alzheimer\u27s disease, the epidemic spreading model provided moderate prediction of the regional pattern of amyloid-beta deposition across all three datasets. We further find that, whilst the most likely epicentre for most amyloid-beta-positive subjects overlaps with the default mode network, 13% of autosomal-dominant Alzheimer\u27s disease individuals were best characterized by a striatal origin of amyloid-beta spread. These subjects were also distinguished by being younger than autosomal-dominant Alzheimer\u27s disease subjects with a default mode network amyloid-beta origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most autosomal-dominant Alzheimer\u27s disease patients express amyloid-beta spreading patterns similar to those of sporadic Alzheimer\u27s disease, but that there may be a subset of autosomal-dominant Alzheimer\u27s disease patients with a separate, striatal phenotype