Buckles, Virginia

AbstractBackgroundComparisons of late‐onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age.MethodsWe 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.ResultsAt 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.DiscussionPreclinical ADAD and LOAD share many biomarker signatures, but cross‐sectional and longitudinal differences may exist.

Abstract Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer’s disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer’s disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer’s disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer’s disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer’s disease.

AbstractIntroductionAs 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.MethodsFrequencies 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.ResultsAD 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.DiscussionADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.

AbstractThe extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of ‘sporadic’ late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease.We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer’s Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset.Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants.These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

AbstractAs 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.

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.

AbstractIntroductionAlthough 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.MethodsMutation 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.ResultsMutation 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.DiscussionKnowledge 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.

Aβ deposition in the basal ganglia is common in autosomal dominant Alzheimer’s disease. Vöglein et al. report an increased severity of motor symptoms in autosomal dominant versus sporadic disease in advanced disease stages. Motor symptoms are more severe in post-codon 200 presenilin 1 mutation carriers and correlate with basal ganglia Aβ.

AbstractIntroduction18F‐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.MethodsFDG, 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.ResultsMetabolism 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.DiscussionHypometabolism estimated by PiB‐R1 may provide a measure of brain perfusion without increasing radiation exposure.