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Chui, Helena C.

https://orcid.org/0000-0003-1348-0931

Mayo Clinic

University of Southern California

Citations 23

Brain Volumetric Trajectories in Down Syndrome and Autosomal Dominant Alzheimer Disease
Kennedy, James Tyler, Boerwinkle, Anna H. , Price, Julie C. , Sathishkumar, Mithra , McMillan, Liv , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Schupf, Nicole , Mapstone, Mark , Christian, Bradley T. , Wisch, Julie K. , Gordon, Brian A. , Benzinger, Tammie L.S. , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Yassa, Michael A. , Brickman, Adam M. , Lao, Patrick , Hartley, Sigan L. , Zaman, Shahid H. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Day, Gregory S. , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter William , Hassenstab, Jason , McDade, Eric , Bateman, Randall J. , Handen, Benjamin L. , Head, Elizabeth , Ances, Beau M.

Alzheimer's & Dementia | January 9, 2025 | Volume: 20 | Issue: S2 | Pages: No page available

10.1002/alz.089313 Get It

AbstractBackgroundAlzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early‐mid 50s) and in those with autosomal dominant mutations (ADAD, 40‐50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD.MethodData for cognitively stable and declining participants was obtained from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS) and the Dominantly Inherited Alzheimer Network (DIAN). Stability/decline was identified based on cognitive testing and interview of individuals and caregivers by trained assessors. Cognitively stable family members without DS/ADAD mutations were recruited as controls from both studies. Participants underwent MRI and amyloid positron emission tomography (PET) scans from which brain volumes and amyloid (centiloids) were derived, respectively. Participants from DIAN had Pittsburgh Compound‐B (PIB) scans, ABC‐DS had PIB or florbetapir. Nonlinear cross‐sectional associations between regional brain volumes and estimated years to onset of cognitive decline (EYO, negative values before onset, positive after) and centiloid were evaluated using generalized additive models while controlling for sex and random effects of family. EYO was set to 52 for all participants with DS and based on parental decline/mutation type for participants with ADAD. EYO for controls was based on the EYO of their family member.ResultData from 239 participants with DS (47 declining), and 340 participants with ADAD (122 declining), and 263 familial controls were included. Higher EYO and centiloid values were associated with lower brain volumes in almost all regions. At earlier EYOs, individuals with DS typically had smaller regional volumes than ADAD or sibling controls, with volume declining linearly across the EYO range. By contrast, ADAD mutation carriers had similar volumes to non‐carriers at early EYOs, with volumes diverging as early as 10 years before decline. Brain volumes and centiloid values were inversely related in ADAD and DSAD. Volume in key cortical regions were similar by the expected year of onset in both groups.ConclusionADAD and DSAD demonstrated different temporal patterns of regional neurodegeneration prior to cognitive change despite being similarly affected by early onset amyloid.
Changes in cortical thickness along the Alzheimer disease continuum in people with Down syndrome
Kennedy, James Tyler, Dincer, Aylin , Thippabhotla, Sharmila, Roman, June, Boerwinkle, Anna H. , Chen, Charles D., Price, Julie C. , Sathishkumar, Mithra , McMillan, Liv , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Mapstone, Mark , Christian, Bradley T. , Network, Dominantly Inherited Alzheimer, Wisch, Julie K. , Gordon, Brian A. , Flores, Shaney , Benzinger, Tammie L.S. , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Yassa, Michael A. , Brickman, Adam M. , Lao, Patrick , Hartley, Sigan L. , Zaman, Shahid H. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Karch, Celeste M. , Hassenstab, Jason , McDade, Eric , Bateman, Randall J. , Handen, Benjamin L. , Head, Elizabeth , Ances, Beau M. , Schofield, Peter R.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S17 | Pages: No page available

10.1002/alz.079932 Get It

AbstractBackgroundTriplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal‐dominant AD1, but not DS‐related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology.MethodCross‐sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium‐Down Syndrome (106 amyloid‐/cognitively unimpaired, nonclinical, 20% reserved for receiver‐operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV452) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster‐wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired.ResultSignificant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal‐dominant AD (.547/.540)1. Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres.ConclusionCT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment.1. Dincer (2020). NeuroImage: Clinical, 28, 102491.2. Su (2019). Alzheimer’s Dement, 11, 180‐190.
Cross‐sectional comparison of the role of tau burden among Down Syndrome Alzheimer disease and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Thippabhotla, Sharmila, Kennedy, James Tyler, Butt, Omar H. , Chen, Charles D., Christian, Bradley T. , Mapstone, Mark , Tudorascu, Dana , Cohen, Annie , Fagan, Anne M. , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Wisch, Julie K. , Gordon, Brian A. , Flores, Shaney , McKay, Nicole S. , Handen, Benjamin L. , Head, Elizabeth , Zammit, Matthew D. , Johnson, Sterling C. , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Yassa, Michael A. , Keator, David B. , Hartley, Sigan L. , Zaman, Shahid H. , Lao, Patrick , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter William , Xiong, Chengjie , Schindler, Suzanne E. , Morris, John C. , Karch, Celeste M. , Hassenstab, Jason , Benzinger, Tammie L.S. , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S14 | Pages: No page available

10.1002/alz.079102 Get It

AbstractBackgroundAdults with Down Syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS.MethodIn a cross‐sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non‐mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden.ResultCompared to CN, tau PET binding was elevated in participants with (µDS = 2.12 ± 0.22 SUVR, µADAD = 2.52 ± 0.37 SUVR) and without (µDS = 1.24 ± 0.15 SUVR, µADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2).ConclusionWhile tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti‐amyloid but also tau‐reducing agents should be considered for treating cognitive decline in adults with DS.
Refinement of Neurofilament light Dynamics in CSF and Blood for familial Alzheimer’s Disease
Hofmann, Anna, Haesler, Lisa M., Preische, Oliver, Gräber‐Sultan, Susanne, Obermüller, Ulrike , Vöglein, Jonathan , Laske, Christoph , Fitzpatrick, Colleen , Levin, Raina, Chen, Charles D., Chui, Helena C., Fagan, Anne M. , Farlow, Martin R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Graff‐Radford, Neill R. , Chhatwal, Jasmeer P. , Vöglein, Jonathan , Xiong, Chengjie , Joseph‐Mathurin, Nelly , Cruchaga, Carlos , Goate, Alison , Allegri, Ricardo , Benzinger, Tammie L.S. , Berman, Sarah , Chui, Helena C. , Fox, Nick C. , Day, Gregory S. , Hassenstab, Jason , Jack, Clifford R. , Lee, Jae‐Hong , Levey, Allan I. , Martins, Ralph N. , Noble, James M. , Sperling, Reisa Anne , Rosa-Neto, Pedro , Sánchez‐Valle, Raquel , Schofield, Peter R. , Xiong, Chengjie , Karch, Celeste M. , Gordon, Brian A. , Morris, John C. , McDade, Eric , Bateman, Randall J. , Jucker, Mathias , Schultz, Stephanie A.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S14 | Pages: No page available

10.1002/alz.078802 Get It

AbstractBackgroundDisease‐modifying therapies for Alzheimer’s Disease (AD) are likely most beneficial when initiated in the pre‐symptomatic phase. To track success of such interventions fluid biomarkers became instrumental, with neurofilament light chain (NfL) showing particular promise. We previously reported that serum NfL increases in pre‐symptomatic phases of familial (autosomal‐dominantly inherited) AD (fAD) and that within‐person rate‐of‐change in NfL is an earlier predictor of fAD symptom onset compared to cross‐sectional levels. The aim of the study at hand was to extend these initial findings in a larger cohort.MethodParticipants enrolled in the Dominantly Inherited Alzheimer Network (DIAN) with matched cross‐sectional and longitudinal cerebrospinal fluid (CSF; n = 962) as well as plasma (n = 1294) samples were used. NfL measurements have been performed on the SIMOA platform using commercially available assay‐kits. To investigate the influence of physiological factors independent from AD, we first analyzed whether age and body mass index (BMI) could account for observed variation in inter‐individual CSF and plasma NfL levels considering non‐carrier family‐members (NC) as a healthy control group. Next, utilizing estimated years to symptom onset (EYO) and previously published methods (Preische et al., 2019), we determined the point in disease course when baseline and longitudinal CSF and plasma NfL concentrations started to increase in mutation carriers (MC) relative to NC, after adjusting for age and BMI.ResultOur results reveal a tight correlation of CSF and blood NfL values within MC as well as NC (figure 1A‐B). However, within NC, after correction for age and BMI, some unexplained variability remained (figure 1C). Further, a decrease of the NfL plasma/CSF ratio over age was found after correcting for BMI (figure 1D). The discrimination of MC from NC was equally good for plasma compared to CSF, being possible on the group level as early as around ‐15 to almost ‐20 EYO depending on the modelling (figure 2).ConclusionOur results support plasma equivalently to CSF NfL as a clinically useful biomarker to longitudinally track neurodegeneration in fAD. The systemic factors influencing physiological NfL values in blood should be investigated in future studies to further improve interpretation of this biomarker.
Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease
Shirzadi, Zahra , Schultz, Stephanie A. , Yau, Wai‐Ying Wendy , Fitzpatrick, Colleen , Levin, Raina, Kantarci, Kejal , Preboske, Gregory M., Jack, Clifford R. , Farlow, Martin R. , Hassenstab, Jason , Morris, John C. , Xiong, Chengjie , Levey, Allan I. , Gordon, Brian A. , Salloway, Stephen , Perrin, Richard J. , Xiong, Chengjie , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Chui, Helena C., Berman, Sarah , Mori, Hiroshi , Ruthirakuhan, Myuri , Wu, Che‐Yuan , Sohrabi, Hamid R. , Martins, Ralph N. , Johnson, Keith A. , Greenberg, Steven M. , Chhatwal, Jasmeer P. , Initiative, Dominantly Inherited Alzheimer Network and the Alzheimer’s Disease Neuroimaging, Weiner, Michael W. , Aisen, Paul, Petersen, Ronald , Jack, Clifford R., Jagust, William J. , Trojanowki, John Q., Morris, John C., Shaw, Leslie M. , Khachaturian, Zaven S., Carrillo, Maria, Potter, William Z., Bernard, Marie , Jackson, Jonathan , Masliah, Eliezer , Masterman, Donna, Okonkwo, Ozioma C. , Ryan, Laurie, Silverberg, Nina, Fleisher, Adam , Sacrey, Diana Truran, Fockler, Juliet , Conti, Cat, Jin, Chengshi , Nosheny, Rachel L. , Ashford, Miriam T. , Flenniken, Derek , Kormos, Adrienne, Montine, Tom, Raman, Rema , Jiménez, Gustavo , Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah , Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth , Sloan, Brittany, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Gunter, Jeff, Jahanshad, Neda , DeCarli, Charles, Knaack, Alexander , Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen , Reiman, Eric M. , Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin , Bernhardt, Haley, Taylor‐Reinwald, Lisa, Korecka, Magdalena , Figurski, Michael, Neu, Scott, Apostolova, Liana G. , Foroud, Tatiana M., Faber, Kelley, Wilmes, Kristi, Thal, Leon J., Lind, Betty, Crissey, Rachel, Carter, Raina, Dolen, Sara, Schneider, Lon S. , Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Brewer, James B., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L. , Zbizek-Nulph, Lisa, Mason, Sara S., Albers, Colleen S., Johnson, Kris , Villaneuva-Meyer, Javier, Pavlik, Valory , Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S. , Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir , Rountree, Susan, Dang, Mimi, Mintz, Akiva , Winkfield, David, Carroll, Maria , Stobbs-Cucchi, Georgia , Oliver, Angela , Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David , Love, Marissa Natelson , Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel , Grossman, Hillel, Goldstein, Martin , Mitsis, Effie, Samuels, Patricia, Duara, Ranjan , Greig‐Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie , Smith, Amanda , Raj, Balebail Ashok, Fargher, Kristin, Shulman, Melanie , Faustin, Arline , Rao, Julia, Castro, Karen M. , Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Doraiswamy, P. Murali , Petrella, Jeffrey R. , James, Olga, Borges‐Neto, Salvador , Karlawish, Jason , Vaishnavi, Sanjeev , Clark, Christopher M. , Arnold, Steven E. , Smith, Charles D. , Khouli, Riham El , Raslau, Flavius D., Oakley, MaryAnn, Simpson, Donna M., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. Saleem , Brand, Connie, Thai, Gaby , Pierce, Aimee, Witbracht, Megan , Mathews, Dana, Quiceno, Mary , Hajjar, Ihab , Cellar, Janet S., Swerdlow, Russell H. , Kremen, Sarah , Tingus, Kathleen, Lu, Po H. , Bartzokis, George, Woo, Ellen, Graff‐Radford, Neill R. , Parfitt, Francine, Poki-Walker, Kim, Hake, Ann Marie , Matthews, Brandy R., Herring, Scott, Dyck, Christopher H. van , Mecca, Adam P. , Good, Susan P., MacAvoy, Martha G., Carson, Richard E. , Varma, Pradeep, Chertkow, Howard , Vaitekunis, Susan, Hosein, Chris, Mudge, Benita, Assaly, Michele, Rachinsky, Irina, Kertesz, Andrew, Drost, Dick, Rogers, John, Grant, Ian , Muse, Brittanie, Rogalskı, Emily , Robson, Jordan, Mesulam, M.‐Marsel, Kerwin, Diana , Wu, Chuang‐Kuo, Johnson, Nancy E., Lipowski, Kristine, Weıntraub, Sandra , Bonakdarpour, Borna , Hernando, Raymundo, Sarrael, Antero, Rosen, Howard J., Johnson, Kathleen, Reynolds, Brigid, Poe, Jessica, Sperling, Reisa A., Marshall, Gad A. , Yesavage, Jerome A. , Taylor, Joy L. , Chao, Steven, Coleman, Jaila, White, Jessica D. , Lane, Barton , Rosen, Allyson , Tinklenberg, Jared, Belden, Christine M. , Clark, Kelly, Zamrini, Edward , Sabbagh, Marwan, Kowall, Neil W. , Budson, Andrew E. , Ntekim, Oyonumo, Wolday, Saba, Khan, Javed , Nwulia, Evaristus , Nadarajah, Sheeba , Lerner, Alan J. , Ogrocki, Paula, Tatsuoka, Curtis , Fatica, Parianne, Olichney, John , Bates, Vernice, Capote, Horacio, Rainka, Michelle, Borrie, Michael, Lee, T‐Y, Asthana, Sanjay , Carlsson, Cynthia M., Perrin, Allison, Burke, Anna , Kataki, Maria , Hart, David , Zimmerman, Earl A. , Celmins, Dzintra, Smith, Karen Ekstam, Shim, Hyungsub , Nam, Ki Won , Schtulz, Susan K., Williamson, Jeff D. , Craft, Suzanne , Cleveland, Jo, Ott, Brian R. , Drake, Jonathan, Tremont, Geoffrey , Daiello, Lori A. , Ritter, Aaron, Bernick, Charles , Munic, Donna, O’Connell, Abigail, Mintzer, Jacobo , Wiliams, Arthur, Masdeu, Joseph C. , Shi, Jiong , Garcia, Angelica, Newhouse, Paul , Salloway, Steven, Malloy, Paul, Correia, Stephen , Kittur, Smita, Blank, Karen, Anderson, Karen, Flashman, Laura A. , Seltzer, Marc, Hynes, Mary L. , Santulli, Robert B. , Relkin, Norman , Chiang, Gloria, Lee, Athena, Lin, Michael, Ravdin, Lisa , Sood, Ajay, Blanchard, Kimberly S., Fleischman, Debra , Varon, Daniel, Greig, Maria T., Martin, Kimberly S., Reist, Christopher , Sadowsky, Carl, Villena, Teresa, Rosen, Howard, Peskind, Elaine R. , Li, Gail, Vöglein, Jonathan , Méndez, Patricio Chrem, Ikonomović, Snežana, Nadkarni, Neelesh K. , Ramírez, Laura, Leon, Yudy Milena, Ramos, Cláudia , Alzate, Diana, Baena, Ana , Londono, Natalia, Laske, Christoph , Kuder-Buletta, Elke, Gräber‐Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ishii, Kenji , Senda, Michio , Riddle, Meghan C., Menard, William, Bodge, Courtney, Surti, Mustafa, Sanchez-Gonzalez, VJ, Orozco-Barajas, Maribel, Esposito, Bianca, Fernanadez, Victoria, Jerome, Gina, Herries, Elizabeth, Seyfried, Nicholas T. , Bechara, Jacob , Chen, Allison , Hantler, Nancy, Hornbeck, Russ C. , Jarman, Steve, Keefe, Sarah , Koudelis, Deborah, Massoumzadeh, Parinaz , Nicklaus, Joyce , Pulizos, Christine, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily , Candela, Madison, Smith, Hunter , Scott, Jalen , Gremminger, Emily, Ma, Yinjiao , Bui, Ryan , Lu, Ruijin , Daniels, Alisha , Courtney, Laura, Supnet, Charlene , Xu, Jinbin , Ringman, John M. , Barthélemy, Nicolas R. , Jack, Clifford R , Gordon, Brian A , Kantarci, Kejal , Day, Gregory S , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Supnet-Bell, Charlene , Berman, Sarah , Levey, Allan I , Kremen, Sarah , Joseph‐Mathurin, Nelly , Jucker, Mathias , Xiong, Chengjie , Karch, Celeste M. , Schofield, Peter R. , McDade, Eric , Cruchaga, Carlos , Allegri, Ricardo , Koeppe, Robert A. , Chui, Helena C. , Sánchez‐Valle, Raquel , Lee, Jae‐Hong , Rosa-Neto, Pedro , Swardfager, Walter , Benzinger, Tammie L.S. , Bateman, Randall J. , Sperling, Reisa Anne , Schultz, Aaron P. , Initiative, Dominantly Inherited Alzheimer Network and the Alzheimer’s Disease Neuroimaging, Jack, Clifford R., Toga, Arthur W. , Beckett, Laurel , Green, Robert C. , Saykin, Andrew J. , Morris, John C., Barnes, Lisa L. , González, Hector, Ho, Carole , Hsiao, John , Veitch, Dallas P. , Neuhaus, John M , Rafii, Michael S. , Donohue, Michael , Smith, Stephanie R. , Harvey, Danielle , Arani, Arvin , Schwarz, Christopher G. , Jones, David T. , Senjem, Matthew L. , Vemuri, Prashanthi , Reid, Robert I. , Malone, Ian B. , Thompson, Paul M. , Thomopoulos, Sophia I. , Nir, Talia M. , Fletcher, Evan M. , Tosun, Duygu , Yushkevich, Paul A. , Das, Sandhitsu R. , Chen, Kewei , Mathis, Chet, Nho, Kwangsik T. , Risacher, Shannon L. , Shen, Li , Nudelman, Kelly , Silbert, Lisa C. , Kaye, Jeffrey , Carter, Raina, Quinn, Joseph F. , Lord, Joanne L. , Knopman, David S. , Stern, Yaakov , Honig, Lawrence S. , Ances, Beau M. , Goldstein, Martin A., Greenberg, Jonathan, Shah, Raj C. , Lamar, Melissa , Duara, Ranjan , Sadowski, Martin , Wısnıewskı, Thomas , Wong, Terence Z. , Wolk, David A. , Jicha, Gregory A. , López, Oscar L. , Porsteinsson, Anton P. , Yanez, Beatriz, Sosa, Elizabeth M. , Kelley, Brendan , Nguyen, Trung Dung , Womack, Kyle , Lah, James J. , Burns, Jeffrey M. , Brooks, William Miles , Silverman, Daniel H.S. , Teng, Edmond , Brosch, Jared R. , Black, Sandra E. , Stefanovic, Bojana , Heyn, Chris , Hsiung, Ging‐Yuek Robin , Kim, Ellen , Sossi, Vesna , Feldman, Howard , Finger, Elizabeth C. , Pasternak, Stephen , Miller, Bruce L. , Perry, David C. , Turner, Raymond Scott , MCCann, Kelly, Sperling, Reisa A., Atri, Alireza , Killiany, Ronald , Stern, Robert A. , Mez, Jesse , Obisesan, Thomas O. , Maillard, Pauline , Carmichael, Owen , Bartha, Robert , Johnson, Sterling C. , Carlsson, Cynthia M. , Scharre, Douglas W. , Tarawneh, Rawan M. , Miller, Del D. , Ponto, Laura L. Boles , Koleva, Hristina , Yang, Mia , Sink, Kaycee M. , Masdeu, Joseph C , Potkin, Steven G. , Salloway, Steve , Pearlson, Godfrey D. , Sood, Ajay, Arfanakis, Konstantinos , Varón, Daniel , Martínez, Walter Fabián , Petrie, Eric C. , Noble, James M. , Surace, Ezequiel , Lopera, Francisco Javier , Aguillon, David , Londono, Natalia, Moreno, Sonia, Ikeuchi, Takeshi , Kasuga, Kensaku , Niimi, Yoshiki , Cash, David M. , Roh, Jee Hoon , Takada, Leonel Tadao , Renton, Alan , Marsh, Jacob A. , Llibre‐Guerra, Jorge J. , Johnson, Erik C. B. , Brooks, William S. , Chen, Charles , Flores, Shaney , McCullough, Austin , McKay, Nicole S. , Wáng, Qīng , Candela, Madison, Hobbs, Diana A. , Wang, Peter , Xu, Xiong, Li, Yan , Sosa, Ana Luisa , Smith, Jennifer A.

JAMA Neurology | October 16, 2023 | Volume: 80 | Issue: 12 | Pages: 1353

10.1001/jamaneurol.2023.3618 Get It

ImportanceIncreased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.ObjectiveTo estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.Design, Setting, and ParticipantsThis cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).Main Outcome and MeasuresThe main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.ResultsData from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [P = .002]; ADNI: t = −5.6 [P &amp;lt; .001]; HABS: t = −2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P &amp;lt; .001]; ADNI: t = 9.1 [P &amp;lt; .001]; HABS: t = 5.4 [P &amp;lt; .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P &amp;lt; .001).Conclusions and RelevanceThe findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.
Location of pathogenic variants in PSEN1 impacts progression of cognitive, clinical, and neurodegenerative measures in autosomal‐dominant Alzheimer's disease
Schultz, Stephanie A. , Shirzadi, Zahra , Liu, Lei , Fitzpatrick, Colleen , Barthélemy, Nicolas R. , Esposito, Bianca, Chen, Charles D., Goate, Alison , Berman, Sarah , Chui, Helena C., Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Gordon, Brian A. , Day, Gregory S. , Graff‐Radford, Neill R. , Hassenstab, Jason , Hanseeuw, Bernard , Hofmann, Anna, Levey, Allan I. , Xiong, Chengjie , Mori, Hiroshi , Morris, John C. , Perrin, Richard J. , Salloway, Stephen , Johnson, Keith A. , Chhatwal, Jasmeer P. , Investigators, the Dominantly Inherited Alzheimer Network, Vöglein, Jonathan , Liu, Lei , Gordon, Brian A , Day, Gregory S , Vöglein, Jonathan , Xiong, Chengjie , Chen, Charles D , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Berman, Sarah , Levey, Allan I , Schultz, Aaron P. , McDade, Eric , Renton, Alan , Joseph‐Mathurin, Nelly , Cruchaga, Carlos , Allegri, Ricardo , Benzinger, Tammie L.S. , Chui, Helena C. , Jack, Clifford R. , Jucker, Mathias , Karch, Celeste M. , Koeppe, Robert A. , Lee, Jae‐Hong , Martins, Ralph N. , Noble, James M. , Rosa-Neto, Pedro , Sánchez‐Valle, Raquel , Schofield, Peter R. , Xiong, Chengjie , Bateman, Randall J. , Sperling, Reisa Anne , Investigators, the Dominantly Inherited Alzheimer Network

Aging Cell | June 9, 2023 | Volume: 22 | Issue: 8 | Pages: No page available

10.1111/acel.13871 Get It

AbstractAlthough pathogenic variants in PSEN1 leading to autosomal‐dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non‐carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre‐symptomatic and symptomatic phases of disease as compared to CY, using both cross‐sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ‐secretase and the generation of toxic β‐amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.
Progressive white matter injury in autosomal dominant Alzheimer’s disease is strongly associated with cerebral microbleeds and neurodegeneration
Shirzadi, Zahra , Yau, Wai‐Ying Wendy , Preboske, Gregory M., Farlow, Martin R. , Fagan, Anne M. , Fitzpatrick, Colleen , Salloway, Stephen , Perrin, Richard J. , Graff‐Radford, Neill R. , Koeppe, Robert, Chui, Helena C., Mori, Hiroshi , Johnson, Keith A., Greenberg, Steven M. , Chhatwal, Jasmeer P. , Investigators, DIAN, Schultz, Stephanie A. , Joseph‐Mathurin, Nelly , Kantarci, Kejal , Jack, Clifford R. , Hassenstab, Jason , Jucker, Mathias , Morris, John C. , Xiong, Chengjie , Karch, Celeste M. , Levey, Allan I. , Gordon, Brian A. , Schofield, Peter William , McDade, Eric , Xiong, Chengjie , Cruchaga, Carlos , Allegri, Ricardo , Fox, Nick C. , Goate, Alison , Noble, James M. , Chui, Helena C. , Berman, Sarah , Sánchez‐Valle, Raquel , Lee, Jae‐Hong , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Sohrabi, Hamid R. , Martins, Ralph N. , Schultz, Aaron P. , Bateman, Randall J. , Johnson, Keith A. , Sperling, Reisa Anne , Investigators, DIAN

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S6 | Pages: No page available

10.1002/alz.066715 Get It

AbstractBackgroundWhite matter (WM) injury visible on MRI is a common finding in Alzheimer’s disease (AD) and is often attributed to small vessel ischemic changes secondary to increased systemic vascular risk. Increased WM injury has been associated with the progression of Autosomal Dominant AD (ADAD), though ADAD pathogenic variant carriers are relatively young and may not have elevated vascular risk factors. We hypothesized that WM injury in ADAD may reflect worsening of cerebral amyloid angiopathy (CAA) and neurodegeneration. Here we examine this hypothesis using cross‐sectional and longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN).MethodMRI data from ADAD pathogenic variant carriers (n=223) and non‐carriers (n=136) were used in the present study (Table 1). We extracted FreeSurfer‐based WM lesion (WML) volume from T1‐weighted images (hypointensities). Cortical microbleed (CMB) burden was assessed visually on susceptibility weighted/T2*‐weighted gradient echo images by experienced radiologists (blineded to the mutation status) at the Mayo Clinic in Rochester. Linear regression models compared WML volume at baseline in people with and without CMB. Linear mixed effect models assessed the relationships between longitudinal WML and both CMBs and FreeSurfer‐based total gray matter (GM) volume. Models were corrected for age and estimated years to symptom onset (EYO).ResultGreater baseline WML volume was seen in ADAD carriers vs. non‐carriers, particularly close to the age of estimated symptom onset. Baseline WML volume was greater in carriers with CMBs compared to those without (t=2.9, p=0.003, Figure 1). Longitudinal increase in WML amongst ADAD pathogenic variant carriers with CMBs was estimated to be 214 mm3/year greater than that amongst carriers without CMBs (t=4.1, p<0.001, Figure 2). Independent of this CMB effect, decreasing GM volume was strongly associated with increasing longitudinal WML volume (t=‐6.2, p<0.001, Figure 3). Similar analyses in the non‐carrier group yielded no significant findings.ConclusionConsistent with prior reports, WML volume was increased in ADAD pathogenic variant carriers. However, the results here suggest WML in ADAD may not solely be due to small vessel ischemic changes, but rather may be a result of worsening CAA and more rapid neurodegeneration.
Comparison of amyloid accumulation between Down syndrome and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Butt, Omar H. , Chen, Charles D., Fagan, Anne M. , Christian, Bradley T. , Mapstone, Mark , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Gordon, Brian A. , Wisch, Julie K. , Flores, Shaney , Benzinger, Tammie L.S. , Handen, Benjamin L. , Head, Elizabeth , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Hartley, Sigan L. , Zaman, Shahid H. , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter R. , Karch, Celeste M. , Hassenstab, Jason , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S6 | Pages: No page available

10.1002/alz.064684 Get It

AbstractBackgroundGiven the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development.MethodWe assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium‐Down Syndrome (ABC‐DS) and 265 mutation‐carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) (Table 1). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated‐years‐to‐symptom‐onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC‐DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40.ResultThe relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants (Figure 1). We did not observe significant differences between MC and DS grouped by cognitive status (Figure 2). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ ‐23 but was not elevated in DS until EYO ≥ ‐15 (Figure 3). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region (Figure 4 and 5).ConclusionThese results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5‐10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.
AD‐causing variants that affect PSEN1 transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains
Fagan, Anne M. , Chen, Charles D., Fitzpatrick, Colleen , Chui, Helena C., Mori, Hiroshi , Johnson, Keith A., Farlow, Martin R. , Farrell, Michelle E. , Graff‐Radford, Neill R. , Perrin, Richard J. , Salloway, Stephen , Shirzadi, Zahra , Chhatwal, Jasmeer P. , Schultz, Stephanie A. , Allegri, Ricardo , Schultz, Aaron P. , Goate, Alison , Levey, Allan I. , Hanseeuw, Bernard , Koeppe, Robert A. , Gordon, Brian A. , Cruchaga, Carlos , Karch, Celeste M. , Xiong, Chengjie , Jack, Clifford R. , McDade, Eric , Chui, Helena C. , Lee, Jae‐Hong , Noble, James M. , Hassenstab, Jason , Xiong, Chengjie , Morris, John C. , Johnson, Keith A. , Liu, Lei , Jucker, Mathias , Joseph‐Mathurin, Nelly , Fox, Nick C. , Schofield, Peter R. , Martins, Ralph N. , Sánchez‐Valle, Raquel , Berman, Sarah , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Bateman, Randall J. , Sperling, Reisa Anne

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S4 | Pages: No page available

10.1002/alz.067186 Get It

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).ResultsPSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.
AD‐causing variants that affect PSEN1 transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains.
Schultz, Stephanie A. , Fagan, Anne M. , Hanseeuw, Bernard , Gordon, Brian A. , Chen, Charles D., Xiong, Chengjie , Fitzpatrick, Colleen , Chui, Helena C., Mori, Hiroshi , Morris, John C. , Johnson, Keith A., Liu, Lei , Farlow, Martin R. , Farrell, Michelle E. , Graff‐Radford, Neill R. , Perrin, Richard J. , Berman, Sarah , Salloway, Stephen , Shirzadi, Zahra , Bateman, Randall J. , Chhatwal, Jasmeer P. , Gordon, Brian A , Bateman, Randall J , Xiong, Chengjie , Morris, John C , Berman, Sarah , Allegri, Ricardo , Schultz, Aaron P. , Goate, Alison , Levey, Allan I. , Koeppe, Robert A. , Cruchaga, Carlos , Karch, Celeste M. , Xiong, Chengjie , Jack, Clifford R. , McDade, Eric , Chui, Helena C. , Lee, Jae‐Hong , Noble, James M. , Hassenstab, Jason , Johnson, Keith A. , Jucker, Mathias , Joseph‐Mathurin, Nelly , Fox, Nick C. , Schofield, Peter R. , Martins, Ralph N. , Sánchez‐Valle, Raquel , Rosa-Neto, Pedro , Benzinger, Tammie L.S. , Sperling, Reisa Anne

Alzheimer's & Dementia | December 20, 2022 | Volume: 18 | Issue: S1 | Pages: No page available

10.1002/alz.068221 Get It

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).Results PSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.