Browsing by Author "Buckles, Virginia D."

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    Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology
    (Oxford University Press, 2022) Morris, John C.; Weiner, Michael; Xiong, Chengjie; Beckett, Laurel; Coble, Dean; Saito, Naomi; Aisen, Paul S.; Allegri, Ricardo; Benzinger, Tammie L. S.; Berman, Sarah B.; Cairns, Nigel J.; Carrillo, Maria C.; Chui, Helena C.; Chhatwal, Jasmeer P.; Cruchaga, Carlos; Fagan, Anne M.; Farlow, Martin; Fox, Nick C.; Ghetti, Bernardino; Goate, Alison M.; Gordon, Brian A.; Graff-Radford, Neill; Day, Gregory S.; Hassenstab, Jason; Ikeuchi, Takeshi; Jack, Clifford R.; Jagust, William J.; Jucker, Mathias; Levin, Johannes; Massoumzadeh, Parinaz; Masters, Colin L.; Martins, Ralph; McDade, Eric; Mori, Hiroshi; Noble, James M.; Petersen, Ronald C.; Ringman, John M.; Salloway, Stephen; Saykin, Andrew J.; Schofield, Peter R.; Shaw, Leslie M.; Toga, Arthur W.; Trojanowski, John Q.; Vöglein, Jonathan; Weninger, Stacie; Bateman, Randall J.; Buckles, Virginia D.; Dominantly Inherited Alzheimer Network; Alzheimer’s Disease Neuroimaging and Initiative; Neurology, School of Medicine
    The 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.
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    Different rates of cognitive decline in autosomal dominant and late-onset Alzheimer disease
    (Wiley, 2022-10) Buckles, Virginia D.; Xiong , Chengjie; Bateman, Randall J.; Hassenstab, Jason; Allegri, Ricardo; Berman, Sarah B.; Chhatwal, Jasmeer P.; Danek, Adrian; Fagan, Anne M.; Ghetti, Bernardino; Goate, Alison; Graff-Radford, Neill; Jucker, Mathias; Levin, Johannes; Marcus, Daniel S.; Masters, Colin L.; McCue, Lena; McDade, Eric; Mori, Hiroshi; Moulder, Krista L.; Noble, James M.; Paumier , Katrina; Preische, Oliver; Ringman, John M.; Fox, Nick C.; Salloway, Stephen; Schofield, Peter R.; Martins, Ralph; Vöglein, Jonathan; Morris, John C.; Dominantly Inherited Alzheimer Network; Pathology and Laboratory Medicine, School of Medicine
    As 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.
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    Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing
    (Oxford University Press, 2018-05-01) Chhatwal, Jasmeer P.; Schultz, Aaron P.; Johnson, Keith A.; Hedden, Trey; Jaimes, Sehily; Benzinger, Tammie L S.; Jack, Clifford; Ances, Beau M.; Ringman, John M.; Marcus, Daniel S.; Ghetti, Bernardino; Farlow, Martin R.; Danek, Adrian; Levin, Johannes; Yakushev, Igor; Laske, Christoph; Koeppe, Robert A.; Galasko, Douglas R.; Xiong, Chengjie; Masters, Colin L.; Schofield, Peter R.; Kinnunen, Kirsi M.; Salloway, Stephen; Martins, Ralph N.; McDade, Eric; Cairns, Nigel J.; Buckles, Virginia D.; Morris, John C.; Bateman, Randall; Sperling, Reisa A.; Pathology and Laboratory Medicine, School of Medicine
    Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.