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Browsing by Subject "Autosomal dominant Alzheimer's disease"
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Item Metabolomic and lipidomic signatures in autosomal dominant and late-onset Alzheimer's disease brains(Wiley, 2023) Novotny, Brenna C.; Fernandez, Maria Victoria; Wang, Ciyang; Budde, John P.; Bergmann, Kristy; Eteleeb, Abdallah M.; Bradley, Joseph; Webster, Carol; Ebl, Curtis; Norton, Joanne; Gentsch, Jen; Dube, Umber; Wang, Fengxian; Morris, John C.; Bateman, Randall J.; Perrin, Richard J.; McDade, Eric; Xiong, Chengjie; Chhatwal, Jasmeer; Dominantly Inherited Alzheimer Network (DIAN) Study Group; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Disease Metabolomics Consortium (ADMC); Goate, Alison; Farlow, Martin; Schofield, Peter; Chui, Helena; Karch, Celeste M.; Cruchaga, Carlos; Benitez, Bruno A.; Harari, Oscar; Neurology, School of MedicineIntroduction: The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain. Methods: We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD). Results: We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration. Discussion: AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation. Highlights: APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. β-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.Item Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease(Wiley, 2021-07-05) Keret, Ophir; Staffaroni, Adam M.; Ringman, John M.; Cobigo, Yann; Goh, Sheng-Yang M.; Wolf, Amy; Allen, Isabel Elaine; Salloway, Stephen; Chhatwal, Jasmeer; Brickman, Adam M.; Reyes-Dumeyer, Dolly; Bateman, Randal J.; Benzinger, Tammie L.S.; Morris, John C.; Ances, Beau M.; Joseph-Mathurin, Nelly; Perrin, Richard J.; Gordon, Brian A.; Levin, Johannes; Vöglein, Jonathan; Jucker, Mathias; la Fougère, Christian; Martins, Ralph N.; Sohrabi, Hamid R.; Taddei, Kevin; Villemagne, Victor L.; Schofield, Peter R.; Brooks, William S.; Fulham, Michael; Masters, Colin L.; Ghetti, Bernardino; Saykin, Andrew J.; Jack, Clifford R.; Graff-Radford, Neill R.; Weiner, Michael; Cash, David M.; Allegri, Ricardo F.; Chrem, Patricio; Yi, Su; Miller, Bruce L.; Rabinovici, Gil D.; Rosen, Howard J.; Pathology and Laboratory Medicine, School of MedicineIntroduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's 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's 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.