Browsing by Author "McDade, Eric M."

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    Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease
    (Elsevier, 2020) Dincer, Aylin; Gordon, Brian A.; Hari-Raj, Amrita; Keefe, Sarah J.; Flores, Shaney; McKay, Nicole S.; Paulick, Angela M.; Shady Lewis, Kristine E.; Feldman, Rebecca L.; Hornbeck, Russ C.; Allegri, Ricardo; Ances, Beau M.; Berman, Sarah B.; Brickman, Adam M.; Brooks, William S.; Cash, David M.; Chhatwal, Jasmeer P.; Farlow, Martin R.; la Fougère, Christian; Fox, Nick C.; Fulham, Michael J.; Jack, Clifford R., Jr.; Joseph-Mathurin, Nelly; Karch, Celeste M.; Lee, Athene; Levin, Johannes; Masters, Colin L.; McDade, Eric M.; Oh, Hwamee; Perrin, Richard J.; Raji, Cyrus; Salloway, Stephen P.; Schofield, Peter R.; Su, Yi; Villemagne, Victor L.; Wang, Qing; Weiner, Michael W.; Xiong, Chengjie; Yakushev, Igor; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Neurology, School of Medicine
    Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.
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    Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease
    (Nature Research, 2019-02) Preische, Oliver; Schultz, Stephanie A.; Apel, Anja; Kuhle, Jens; Kaeser, Stephan A.; Barro, Christian; Gräber, Susanne; Kuder-Buletta, Elke; LaFougere, Christian; Laske, Christoph; Vöglein, Jonathan; Levin, Johannes; Masters, Colin L.; Martins, Ralph; Schofield, Peter R.; Rossor, Martin N.; Graff-Radford, Neill R.; Salloway, Stephen; Ghetti, Bernardino; Ringman, John M.; Noble, James M.; Chhatwal, Jasmeer; Goate, Alison M.; Benzinger, Tammie L. S.; Morris, John C.; Bateman, Randall J.; Wang, Guoqiao; Fagan, Anne M.; McDade, Eric M.; Gordon, Brian A.; Jucker, Mathias; Alzheimer Network; Allegri, Ricardo; Amtashar, Fatima; Bateman, Randall; Benzinger, Tammie; Berman, Sarah; Bodge, Courtney; Brandon, Susan; Brooks, William; Buck, Jill; Buckles, Virginia; Chea, Sochenda; Chhatwal, Jasmeer; Chrem, Patricio; Chui, Helena; Cinco, Jake; Clifford, Jack; Cruchaga, Carlos; D’Mello, Mirelle; Donahue, Tamara; Douglas, Jane; Edigo, Noelia; Erekin-Taner, Nilufer; Fagan, Anne; Farlow, Marty; Farrar, Angela; Feldman, Howard; Flynn, Gigi; Fox, Nick; Franklin, Erin; Fujii, Hisako; Gant, Cortaiga; Gardener, Samantha; Ghetti, Bernardino; Goate, Alison; Goldman, Jill; Gordon, Brian; Graff-Radford, Neill; Gray, Julia; Gurney, Jenny; Hassenstab, Jason; Hirohara, Mie; Holtzman, David; Hornbeck, Russ; DiBari, Siri Houeland; Ikeuchi, Takeshi; Ikonomovic, Snezana; Jerome, Gina; Jucker, Mathias; Karch, Celeste; Kasuga, Kensaku; Kawarabayashi, Takeshi; Klunk, William; Koeppe, Robert; Kuder-Buletta, Elke; Laske, Christoph; Lee, Jae-Hong; Levin, Johannes; Marcus, Daniel; Martins, Ralph; Mason, Neal Scott; Masters, Colin; Maue-Dreyfus, Denise; McDade, Eric; Montoya, Lucy; Mori, Hiroshi; Morris, John; Nagamatsu, Akem; Neimeyer, Katie; Noble, James; Norton, Joanne; Perrin, Richard; Raichle, Marc; Ringman, John; Roh, Jee Hoon; Salloway, Stephen; Schofield, Peter; Shimada, Hiroyuki; Shiroto, Tomoyo; Shoji, Mikio; Sigurdson, Wendy; Sohrabi, Hamid; Sparks, Paige; Suzuki, Kazushi; Swisher, Laura; Taddei, Kevin; Wang, Jen; Wang, Peter; Weiner, Mike; Wolfsberger, Mary; Xiong, Chengjie; Xu, Xiong; Pathology and Laboratory Medicine, School of Medicine
    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.