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Ghetti, Bernardino

https://orcid.org/0000-0002-1842-8019

Mayo Clinic

Indiana University Indianapolis

Citations 75

Pattern and implications of neurological examination findings in autosomal dominant Alzheimer disease
Vöglein, Jonathan , Morris, John C. , Dieterich, Marianne , Preische, Oliver, Hofmann, Anna, Hassenstab, Jason , Fagan, Anne M. , Noble, James M. , Berman, Sarah , Graff‐Radford, Neill R. , Farlow, Martin R. , Chhatwal, Jasmeer P. , Salloway, Stephen , Xiong, Chengjie , Cairns, Nigel J., Perrin, Richard J. , Day, Gregory S. , Mori, Hiroshi , Suzuki, Kazushi , Masters, Colin L. , Goate, Alison , Buckles, Virginia, Fox, Nick C. , Chrem, Patricio, Ringman, John M. , Yakushev, Igor , Laske, Christoph , Bateman, Randall J. , Network, for the Dominantly Inherited Alzheimer, Day, Gregory S , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Berman, Sarah , Noble, James M , Franzmeier, Nicolai , McDade, Eric , Simons, Mikael , Benzinger, Tammie L.S. , Ghetti, Bernardino , Xiong, Chengjie , Karch, Celeste M. , Martins, Ralph N. , Sánchez‐Valle, Raquel , Shimada, Hiroyuki , Ikeuchi, Takeshi , Schofield, Peter R. , Allegri, Ricardo , Jucker, Mathias , Höglinger, Günter U. , Danek, Adrian , Network, for the Dominantly Inherited Alzheimer

Alzheimer's & Dementia | May 24, 2022 | Volume: 19 | Issue: 2 | Pages: 632-645

10.1002/alz.12684 Get It

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.
Autosomal dominant and sporadic late onset Alzheimer's disease share a commonin vivopathophysiology
Schofield, Peter R. , Weiner, Michael W. , Xiong, Chengjie , Coble, Dean W. , Saito, Naomi , Aisen, Paul, Berman, Sarah , Cairns, Nigel J., Carrillo, María C. , Chui, Helena C., Chhatwal, Jasmeer P. , Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Goate, Alison , Gordon, Brian A. , Graff‐Radford, Neill R. , Day, Gregory S. , Hassenstab, Jason , Jack, Clifford R. , Jagust, William J. , Massoumzadeh, Parinaz , Masters, Colin L. , Mori, Hiroshi , Noble, James M. , Petersen, Ronald C. , Ringman, John M. , Salloway, Stephen , Saykin, Andrew J. , Shaw, Leslie M. , Trojanowski, John Q. , Vöglein, Jonathan , Weninger, Stacie, Bateman, Randall J. , Buckles, Virginia, Morris, John C. , Schofield, Peter R , Gordon, Brian A , Ikeuchi, T , Jack, Clifford R , Jagust, William J , Masters, Colin L , Vöglein, Jonathan , Saykin, Andrew J , Day, Gregory S , Bateman, Randall J , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Berman, Sarah , Noble, James M , Xiong, Chengjie , Beckett, Laurel , Allegri, Ricardo , Benzinger, Tammie L.S. , Chui, Helena C. , Cruchaga, Carlos , Ghetti, Bernardino , Ikeuchi, Takeshi , Jucker, Mathias , Martins, Ralph N. , McDade, Eric , Toga, Arthur W.

Brain | May 17, 2022 | Volume: 145 | Issue: 10 | Pages: 3594-3607

10.1093/brain/awac181 Get It

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.
Biomarker clustering in autosomal dominant Alzheimer's disease
Luckett, Patrick H. , Chen, Charlie, Gordon, Brian A. , Wisch, Julie K. , Berman, Sarah , Chhatwal, Jasmeer P. , Cruchaga, Carlos , Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Xiong, Chengjie , Masters, Colin L. , Mori, Hiroshi , Noble, James M. , Salloway, Stephen , Cash, David M. , Fulham, Michael , Jack, Clifford R. , Vöglein, Jonathan , Klunk, William E. , Wang, Qing , Marcus, Daniel C. , Koudelis, Deborah, Cash, Lisa, Hornbeck, Russ C. , Perrin, Richard J. , Hassenstab, Jason , Morris, John C. , Bateman, Randall J. , (DIAN), for the Dominantly Inherited Alzheimer Network, Cruchaga, Carlos , Jack, Clifford R , Gordon, Brian A , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Cash, David M , Wisch, Julie K , Berman, Sarah , Noble, James M , Jucker, Mathias , Schofield, Peter R. , Brickman, Adam M. , Brooks, William S. , Ghetti, Bernardino , Koeppe, Robert A. , Su, Yi , Weiner, Michael W. , Marcus, Daniel, Joseph‐Mathurin, Nelly , Xiong, Chengjie , Karch, Celeste M. , McDade, Eric , Benzinger, Tammie L.S. , Ances, Beau M. , (DIAN), for the Dominantly Inherited Alzheimer Network

Alzheimer's & Dementia | April 1, 2022 | Volume: 19 | Issue: 1 | Pages: 274-284

10.1002/alz.12661 Get It

AbstractINTRODUCTIONAs the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others.METHODSWe used hierarchical clustering to group 19 cross‐sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation.RESULTSThree primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors.DISCUSSIONThese results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.
Association ofBDNFVal66Met With Tau Hyperphosphorylation and Cognition in Dominantly Inherited Alzheimer Disease
Barthélemy, Nicolas R. , Goate, Alison , Hassenstab, Jason , Fagan, Anne M. , Xiong, Chengjie , Cruchaga, Carlos , Farlow, Martin R. , Graff‐Radford, Neill R. , Laske, Christoph , Masters, Colin L. , Salloway, Stephen , Morris, John C. , Bateman, Randall J. , Network, Dominantly Inherited Alzheimer, Chhatwal, Jasmeer P. , Fitzpatrick, Colleen , Bodge, Courtney, Cruz, Chrismary De La, Mejia, Arlene, Neimeyer, Katie, Gardener, Samantha L. , Taddei, Kevin , Ping, Lingyan, Seyfried, Nick , Gräber‐Sultan, Susanne, Häsler, Lisa M., Käser, Stephan, Kuder-Buletta, Elke, Preische, Oliver, Diffenbacher, Anna, Igor, Yakushev, Levin, Johannes, Vöglein, Jonathan , Obermüller, Ulricke, Esposito, Bianca, Goate, Alison, Buck, Jill , Farlow, Marty, Chrem, Patricio, Egido, Noelia , Haass, Christian , Nuscher, Brigitte , Day, Gregory S. , Graham, Morgan, Stephens, Sochenda, Bechara, Jacob , Araki, Aki, Ishii, Kenji , Senda, Michio , Ihara, Ryoko , Nagamatsu, Akemi, Fox, Nick C. , Mummery, Cath, Goldberg, Sarah B. , Ikonomović, Snežana, Mountz, James M. , Nadkarni, Neelesh K. , Patira, Riddhi , Smith, Lori, Snitz, Beth E. , Thompson, Sarah , Weamer, Elise A., Mason, Neal Scott, Chui, Helena, Ringman, John M. , Adams, Sarah , Brandon, Susan E. , Buckles, Virginia, Cash, Lisa, Chen, Charlie, Chua, Jasmin, Cruchaga, Carlos, Denner, Darcy, Dincer, Aylin , Donahue, Tamara, Feldman, Becca , Franklin, Erin , Friedrichsen, Nelly, Gonzalez, Alyssa, Gray, Julia, Gremminger, Emily, Groves, Alex, Hassenstab, Jason, Hellm, Cortaiga, Herries, Elizabeth, Hoechst-Swisher, Laura, Hornbeck, Russ C. , Jerome, Gina, Keefe, Sarah , Koudelis, Deb, Martinez, Rita, Mawuenyega, Kwasi G., McCullough, Austin , McDade, Eric, Norton, Joanne, Perrin, Richard J. , Shady, Kristine, Sigurdson, Wendy, Xu, Jinbin , Cruchaga, Carlos , Day, Gregory S , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Lim, Yen Ying , Maruff, Paul , Sato, Chihiro , Benzinger, Tammie L.S. , Xiong, Chengjie , Schofield, Peter R. , McDade, Eric , Network, Dominantly Inherited Alzheimer, Fitzpatrick, Colleen, Goldman, Jill , Noble, James M. , Martins, Ralph N. , Sohrabi, Hamid R. , Carter, Kathleen, Duong, Duc M , Johnson, Erik C. B. , Levey, Allan I. , Ping, Lingyan, Hofmann, Anna, Jucker, Mathias , Levin, Johannes, Goate, Alison, Renton, Alan , Brosch, Jared R. , Buck, Jill, Ghetti, Bernardino , Allegri, Ricardo , Morenas‐Rodríguez, Estrella , Jack, Clifford R. , Brooks, William S. , Ikeuchi, Takeshi , Kasuga, Kensaku , Fujii, Hisako , Shimada, Hiroyuki , Niimi, Yoshiki , Douglas, Jane, Grilo, Miguel, O’Connor, Antoinette , Koeppe, Robert A. , Berman, Sarah , Klunk, William E. , López, Oscar L. , Brandon, Susan, Cruchaga, Carlos, Feldman, Becca, Flores, Shaney , Gordon, Brian A. , Hassenstab, Jason, Holtzman, David M. , Karch, Celeste M. , Li, Yan , Marsh, Jacob, McDade, Eric, Smith, Jennifer A. , Wang, Peter , Wang, Qing , Xu, Xiong

JAMA Neurology | January 31, 2022 | Volume: 79 | Issue: 3 | Pages: 261

10.1001/jamaneurol.2021.5181 Get It

Different rates of cognitive decline in autosomal dominant and late‐onset Alzheimer disease
Buckles, Virginia, Xiong, Chengjie , Bateman, Randall J. , Hassenstab, Jason , Berman, Sarah , Chhatwal, Jasmeer P. , Fagan, Anne M. , Goate, Alison , Graff‐Radford, Neill R. , Marcus, Daniel S., Masters, Colin L. , McCue, Lena , Mori, Hiroshi , Moulder, Krista L., Noble, James M. , Paumier, Katrina L. , Preische, Oliver, Ringman, John M. , Fox, Nick C. , Salloway, Stephen , Vöglein, Jonathan , Morris, John C. , Network, for the Dominantly Inherited Alzheimer's, Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Berman, Sarah , Xiong, Chengjie , Allegri, Ricardo , Danek, Adrian , Ghetti, Bernardino , Jucker, Mathias , McDade, Eric , Schofield, Peter R. , Martins, Ralph N. , Network, for the Dominantly Inherited Alzheimer's, Noble, James M

Alzheimer's & Dementia | December 2, 2021 | Volume: 18 | Issue: 10 | Pages: 1754-1764

10.1002/alz.12505 Get It

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.
Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease
Keret, Ophir , Staffaroni, Adam M. , Ringman, John M. , Goh, Sheng‐Yang M., Wolf, Amy , Allen, Isabel Elaine , Salloway, Stephen , Chhatwal, Jasmeer P. , Reyes‐Dumeyer, Dolly , Bateman, Randall J. , Morris, John C. , Joseph‐Mathurin, Nelly , Perrin, Richard J. , Gordon, Brian A. , Xiong, Chengjie , Vöglein, Jonathan , Fougère, Christian la , Martins, Ralph N. , Sohrabi, Hamid R. , Taddei, Kevin , Villemagne, Victor L. , Fulham, Michael , Masters, Colin L. , Saykin, Andrew J. , Graff‐Radford, Neill R. , Weiner, Michael W. , Cash, David M. , Chrem, Patricio, Rabinovici, Gil D. , Rosen, Howard J. , Network, Dominantly Inherited Alzheimer, Gordon, Brian A , Saykin, Andrew J , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Joseph-Mathurin, Nelly , Xiong, Chengjie , Morris, John C , Cash, David M , Rabinovici, Gil D , Cobigo, Yann , Brickman, Adam M. , Benzinger, Tammie L.S. , Ances, Beau M. , Jucker, Mathias , Schofield, Peter R. , Brooks, William S. , Ghetti, Bernardino , Jack, Clifford R. , Allegri, Ricardo , Su, Yi , Miller, Bruce L. , Network, Dominantly Inherited Alzheimer

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring | July 5, 2021 | Volume: 13 | Issue: 1 | Pages: No page available

10.1002/dad2.12197 Get It

Abstract Introduction 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.
Modeling autosomal dominant Alzheimer's disease with machine learning
Luckett, Patrick H. , McCullough, Austin , Gordon, Brian A. , Strain, Jeremy F. , Flores, Shaney , Dincer, Aylin , Kuffner, Todd A. , Stern, Ari, Meeker, Karin L. , Berman, Sarah , Chhatwal, Jasmeer P. , Cruchaga, Carlos , Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Xiong, Chengjie , Masters, Colin L. , Mori, Hiroshi , Noble, James M. , Salloway, Stephen , Cash, David M. , Fulham, Michael , Jack, Clifford R. , Vöglein, Jonathan , Klunk, William E. , Oh, Hwamee , Swisher, Laura, Marcus, Daniel S. , Koudelis, Deborah, Joseph‐Mathurin, Nelly , Cash, Lisa, Hornbeck, Russ C. , Perrin, Richard J. , Hassenstab, Jason , Morris, John C. , Bateman, Randall J. , (DIAN), for the Dominantly Inherited Alzheimer Network, Wang, Qing , Cruchaga, Carlos , Jack, Clifford R , Gordon, Brian A , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Joseph-Mathurin, Nelly , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Cash, David M , Berman, Sarah , McCarthy, John Edward , Jucker, Mathias , Schofield, Peter R. , Brickman, Adam M. , Brooks, William S. , Ghetti, Bernardino , Koeppe, Robert A. , Su, Yi , Weiner, Michael W. , Wáng, Qīng , Xiong, Chengjie , Karch, Celeste M. , McDade, Eric , Benzinger, Tammie L.S. , Ances, Beau M. , (DIAN), for the Dominantly Inherited Alzheimer Network, Noble, James M

Alzheimer's & Dementia | January 21, 2021 | Volume: 17 | Issue: 6 | Pages: 1005-1016

10.1002/alz.12259 Get It

AbstractIntroductionMachine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.MethodsLongitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non‐carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status.ResultsThe Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non‐carriers.DiscussionResults suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.
Lewy Body Disease is a Contributor to Logopenic Progressive Aphasia Phenotype
Buciuc, Marina , Whitwell, Jennifer L. , Kasanuki, Koji , Graff‐Radford, Jonathan , Lowe, Val J. , Graff‐Radford, Neill R. , Rush, Beth , Franczak, Malgorzata, Flanagan, Margaret E. , Rademakers, Rosa , Ross, Owen A. , Parisi, Joseph E., Reichard, R. Ross , Bigio, Eileen H. , Josephs, Keith A. , Strand, Edythe A. , Baker, Matthew C, Ross, Owen A , Dickson, Dennis W , Josephs, Keith A , Buciuc, Marina , Machulda, Mary M. , Duffy, Joseph R. , Baker, Matthew , Ghetti, Bernardino , Raghunathan, Aditya , Dickson, Dennis W.

Annals of Neurology | December 4, 2020 | Volume: 89 | Issue: 3 | Pages: 520-533

10.1002/ana.25979 Get It

ObjectiveThe objective of this study was to describe clinical features, [18F]‐fluorodeoxyglucose (FDG)‐positron emission tomography (PET) metabolism and digital pathology in patients with logopenic progressive aphasia (LPA) and pathologic diagnosis of diffuse Lewy body disease (DLBD) and compare to patients with LPA with other pathologies, as well as patients with classical features of probable dementia with Lewy bodies (pDLB).MethodsThis is a clinicopathologic case‐control study of 45 patients, including 20 prospectively recruited patients with LPA among whom 6 were diagnosed with LPA‐DLBD. We analyzed clinical features and compared FDG‐PET metabolism in LPA‐DLBD to an independent group of patients with clinical pDLB and regional α‐synuclein burden on digital pathology to a second independent group of autopsied patients with DLBD pathology and antemortem pDLB (DLB‐DLBD).ResultsAll patients with LPA‐DLBD were men. Neurological, speech, and neuropsychological characteristics were similar across LPA‐DLBD, LPA‐Alzheimer's disease (LPA‐AD), and LPA‐frontotemporal lobar degeneration (LPA‐FTLD). Genetic screening of AD, DLBD, and FTLD linked genes were negative with the exception of APOE ε4 allele present in 83% of LPA‐DLBD patients. Seventy‐five percent of the patients with LPA‐DLBD showed a parietal‐dominant pattern of hy pometabolism; LPA‐FTLD – temporal‐dominant pattern, whereas LPA‐AD showed heterogeneous patterns of hypometabolism. LPA‐DLBD had more asymmetrical hypometabolism affecting frontal lobes, with relatively spared occipital lobe in the nondominantly affected hemisphere, compared to pDLB. LPA‐DLBD had minimal atrophy on gross brain examination, higher cortical Lewy body counts, and higher α‐synuclein burden in the middle frontal and inferior parietal cortices compared to DLB‐DLBD.InterpretationWhereas AD is the most frequent underlying pathology of LPA, DLBD can also be present and may contribute to the LPA phenotype possibly due to α‐synuclein‐associated functional impairment of the dominant parietal lobe. ANN NEUROL 2021;89:520–533
Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel
Kunkle, Brian W. , Schmidt, Michael A. , Klein, Hans‐Ulrich , Hamilton‐Nelson, Kara L., Larson, Eric B., Evans, Denis A., Jager, Phil L. De, Crane, Paul K. , Buxbaum, Joseph D. , Ertekin‐Taner, Nilüfer , Barnes, Lisa L. , Fallin, M. Daniele , Go, Rodney C.P., Obisesan, Thomas O. , Bennett, David A. , Hall, Kathleen, Goate, Alison , Foroud, Tatiana M., Martin, Eden R. , Wang, Li‐San , Byrd, Goldie S. , Haines, Jonathan L. , Schellenberg, Gerard D., Mayeux, Richard , Pericak‐Vance, Margaret A. , Reitz, Christiane, Perrie, M. Adams, Roger, L. Albin, Liana, G Apostolova, Steven, Eschrich, Craig, S , Clinton, T. Baldwin, Robert, C. Barber, Barral, Sandra, Thomas, Gunther, James, T., Gary, W. Beecham, Eileen, H. Bigio, Thomas, D., Blacker, Deborah, Bradley, F. Boeve, James, D. Bowen, Boxer, Adam, James, R. Burke, Jeffrey, Morris, Nigel, J Cairns, Cynthia, M. Carlsson, Regina, M. Carney, Minerva, M. Carrasquillo, David, Hugh-Jones, Dick, Malcom, Dickson, Dennis, W., Doody, Rachelle S., Duara, Ranjan , Kelley, M. Faber, Thomas, Jaya , Kenneth, B., David, W. Fardo, Martin, Roger, Matthew, P. Frosch, Douglas, R. Galasko, Gearing, Marla , Daniel, Hervé, Gilbert, John, R., Robert, C. Green, John, Harding, Ronald, L. Hamilton, Hardy, John , Lindy, E. Harrell, Lawrence, Steve, Ryan, Mary, Matthew, J. Huentelman, Christine, M Hulette, Gail, P. Jarvik, Jin, Lee‐Way, Karydas, Anna, Mindy, J. Katz, John, S., Joel, H. Kramer, James, J. Lah, Andrew, Peter, Richard, B., Constantine, G. Lyketsos, Malamon, John , Daniel, Chammiran , Martiniuk, Frank , Masliah, Eliezer , Wayne, C. McCormick, Susan, M, Andrew, Nesbit M, McDonough, Stefan, Ann., Canfield, Mesulam, Marsel, Bruce, L. Miller, Carol, A. Miller, Thomas, J. Montine, Amanda, J. Myers, John, M. Olichney, Joseph, E. Parisi, Peskind, Elaine R. , Pierce, Aimee, Wayne, W. Poon, Joseph, F. Quinn, Raj, Ashok , Raskind, Murray A. , Reisch, Joan, S., John, M. Ringman, Erik, D. Roberson, Howard, J. Rosen, Donald, R. Royall, Mark, A. Sager, Julie, A. Schneider, Lon, Su, William, W. Seeley, Small, Scott A. , Sonnen, Joshua, A., Robert, Aiko, Rudolph, E. Tanzi, Juan, Caballero, Debby, W. Tsuang, Vivianna, M. Van Deerlin, Badri, Nabeel, Harry, Vanessa, Vonsattel, Jean Paul, Weıntraub, Sandra , Kathleen, A Welsh-Bohmer, Kirk, C W, Thomas, SubinVarghese, Randall, Linnell B., Wu, Chuang‐Kuo, Steven, G. Younkin, Yu, Lei , Yu, Chang‐En , Graff‐Radford, Neill R. , Martinez, Izri, Ayodele, Temitope , Cantwell, Laura B., Jean‐Francois, Melissa, Kuzma, Amanda , Adams, Lonnie D., Chung, Jaeyoon , Jun, Gyungah , Hendrie, Hugh C. , Reiman, Eric M. , Kowall, Neil W. , Golde, Todd E. , Saykin, Andrew J. , Starks, Takiyah D. , Albert, Marilyn S. , Petersen, Ronald , Sano, Mary , Wısnıewskı, Thomas , Vassar, Robert , Kaye, Jeffrey A., Henderson, Victor W. , DeCarli, Charles , LaFerla, Frank M. , Brewer, James B., Miller, Bruce L. , Swerdlow, Russell H. , Paulson, Henry L. , Trojanowski, John Q. , Chui, Helena C., Rosenberg, Roger N., Craft, Suzanne , Grabowski, Thomas J. , Asthana, Sanjay , Morris, John C. , Strittmatter, Stephen M. , Kukull, Walter A. , Asthana, Sanjay , Jarvik, Gail P. , Cribbs, David H. , Sonnen, Joshua A. , Bennett, David A. , Saykin, Andrew J , Miller, Bruce L , Jarvik, Gail P , Paulson, Henry L , Hardy, John , Morris, John C , Goate, Alison M , Sonnen, Joshua , Barnes, Lisa L , Naj, Adam Christian , Hamilton‐Nelson, Kara L. , Manly, Jennifer J. , Kamboh, M. Ilyas , Farrer, Lindsay A. , Abner, Erin L. , Atwood, Craig, S., Becker, James, T., Eileen, H Bigio, Blacker, Deborah , Cao, Chuanhai , Cruchaga, Carlos , Dickson, Dennis, W., Duara, Ranjan , David, W. Fardo, Farlow, Martin, R., Ferris, Steven H. , Geschwind, Daniel, H., Ghetti, Bernardino , Gilbert, John, R., Håkonarson, Håkon , Honig, Lawrence, S., Huebinger, Ryan, M., Matthew, J Huentelman, Kauwe, John, S.K., Keene, C. Dirk , Kim, Ronald, Leung, Yuk Yee , Li, Ge , Lipton, Richard, B., Marson, Daniel, C., McDavid, Andrew, N., Mesulam, Marsel M. , Bruce, L Miller, Mukherjee, Shubhabrata , O’Bryant, Sid, E., Potter, Huntington , Qu, Liming , Raj, Ashok, Reisberg, ‌Barry , Reisch, Joan, S., Rogaeva, Ekaterina A. , Julie, A Schneider, Schneider, Lon, S., William, W Seeley, Spina, Salvatore , George‐Hyslop, Peter St , Valladares, Otto , Vardarajan, Badri, N., Wilhelmsen, Kirk, C., Williamson, Jennifer , Wingo, Thomas, S., Woltjer, Randall, L., Steven, G Younkin, Zhao, Yi Chen , Logue, Mark W. , Adams, L.D., Vance, Jeffery M. , Cuccaro, Michael L. , Mez, Jesse , Lunetta, Kathryn L. , López, Oscar L. , Leverenz, James B. , Levey, Allan I. , Hyman, Bradley T. , Kaye, Jeffrey A., Eldik, Linda J. Van , Chui, Helena C.

JAMA Neurology | October 19, 2020 | Volume: 78 | Issue: 1 | Pages: 102

10.1001/jamaneurol.2020.3536 Get It