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39 citation(s) found for "Lee, Jae‐Hong".

Functional variations in gamma‐secretase processing of APP are critical determinants of the clinical, biomarker, and cognitive progression of autosomal dominant Alzheimer’s disease
Fitzpatrick, Colleen , Levin, Raina, Shirzadi, Zahra , Chen, Charles D., Farlow, Martin R. , Perrin, Richard J. , Johnson, Keith A. , Chhatwal, Jasmeer P. , Investigators, the Dominantly Inherited Alzheimer Network, Schultz, Stephanie A. , Liu, Lei , Schultz, Aaron P. , Bellier, Jean‐Pierre , Joseph‐Mathurin, Nelly , Benzinger, Tammie L.S. , Day, Gregory S. , Hassenstab, Jason , Jack, Clifford R. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Schofield, Peter William , Karch, Celeste M. , Gordon, Brian A. , McDade, Eric , Bateman, Randall J. , Sperling, Reisa Anne , Selkoe, Dennis J. , Investigators, the Dominantly Inherited Alzheimer Network

Mayo Clinic

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S24 | Pages: No page available

10.1002/alz.082318 Get It

AbstractBackgroundThe balance between production, clearance, and toxicity of Ab peptides is central to AD pathobiology. Though highly variable in terms of age of symptom onset (AAO), hundreds of pathogenic variants in Presenilin‐1 (PSEN1) cause autosomal dominant forms of AD (ADAD). PSEN1 forms the catalytic core of the γ‐secretase complex and thereby directly mediates the production of longer, aggregation‐prone Aβ peptides relative to shorter, non‐aggregating peptides. We hypothesized that the broad AAO and biomarker heterogeneity seen across ADAD would be predictable based on mutation‐specific differences in γ‐secretase function, as measured by a ratio of production of shorter vs. longer Aβ species.MethodsAβ‐37, 38, 40, 42, and 43 production was quantified from 162 unique PSEN1 variants expressed in HEK293 cells engineered to lack endogenous wild‐type PSEN1/2 (Figure 1). Prediction of AAO was carried out in 107 PSEN1 variants (characterized by Liu et al, 2022) and then replicated with a set 55 unique PSEN1 variants represented in the Dominantly Inherited Alzheimer Network (DIAN; n = 190 corresponding variant carriers with detailed cognitive and biomarker data; Figure 2).ResultsMutation‐level variations in Aβ production, including a novel composite representing γ‐secretase function (lower score = less g‐processivity), from the cellular model were highly predictive of actual AAO across the 162 mutants examined (Non‐DIAN variants [N = 107]: r = 0.71, p <2.2e‐16; DIAN variants [N = 55]: r = 0.61, p = 6.10e‐07). Our cell‐based γ‐secretase function composite was strongly associated with cerebral PiB‐PET β‐amyloid burden (B[SE] = ‐0.03[0.01], p = 4.06e‐07), MRI gray matter volume (B[SE] = 44.22[6.4], p = 5.15e‐01), cerebrospinal fluid Aβ42/40 (B[SE] = 6.3e‐04[1.5e‐04], p = 4.46e‐05) and phosphorylated tau‐217 (B[SE] = ‐0.01[0.002], p = 1.98e‐05), Clinical Dementia Rating®‐ Sum of Boxes (B[SE] = ‐0.07[0.02], p = 4.86e‐05), and Mini‐Mental State Exam (B[SE] = 0.11[.03], p = 2.17e‐04).ConclusionsBiochemical variations in γ‐secretase function across PSEN1 pathogenic variants broadly predicted the cross‐sectional clinical, cognitive, and biomarker course of ADAD, including AAO. These findings elucidate the critical link between γ‐secretase function, Aβ production, and severity of AD. The novel approach designed here also represents a tool to account for heterogeneity in ADAD clinical trials and to assess the pathogenicity of PSEN1 variants of unknown significance or with limited family history.
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.

Mayo Clinic

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.

Mayo Clinic

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.

Mayo Clinic

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.

Mayo Clinic

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

10.1001/jamaneurol.2023.3618 | PMID 37843849 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.
Unique genetic architecture of CSF and brain metabolites pinpoints the novel targets for the traits of human wellness
Wang, Ciyang , Western, Daniel , Yang, Chengran , Wang, Lihua , Gorijala, Priyanka , Ruiz, Agustı́n , Pástor, Pau , Fernández, María Victoria , Deming, Yuetiva, Mori, Hiroshi , Perrin, Richard J. , Sung, Yun Ju , Network, Dominantly Inherited Alzheimer, Initiative, Alzheimer’s Disease Neuroimaging, Western, Dan , Ruiz, Agustín , Pastor, Pau , Fernandez, Maria , Panyard, Daniel , Deming, Yuetiva , Boada, Merce , García-González, Pablo , Perrin, Richard , Cruchaga, Carlos , Ali, Muhammad , Timsina, Jigyasha , Engelman, Corinne D. , Boada, Merçé , Cano, Amanda C. , García‐González, Pablo , Graff, Caroline , Lee, Jae‐Hong

Mayo Clinic

No container title available | June 9, 2023 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-2923409/v1 | PMID 37333177 Get It

Abstract Brain metabolism perturbation can contribute to traits and diseases. We conducted the first large-scale CSF and brain genome-wide association studies, which identified 219 independent associations (59.8% novel) for 144 CSF metabolites and 36 independent associations (55.6% novel) for 34 brain metabolites. Most of the novel signals (97.7% and 70.0% in CSF and brain) were tissue specific. We also integrated MWAS-FUSION approaches with Mendelian Randomization and colocalization to identify causal metabolites for 27 brain and human wellness phenotypes and identified eight metabolites to be causal for eight traits (11 relationships). Low mannose level was causal to bipolar disorder and as dietary supplement it may provide therapeutic benefits. Low galactosylglycerol level was found causal to Parkinson’s Disease (PD). Our study expanded the knowledge of MQTL in central nervous system, provided insights into human wellness, and successfully demonstrates the utility of combined statistical approaches to inform interventions.
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

Mayo Clinic

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

10.1111/acel.13871 | PMID 37291760 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.
Change in Cerebrospinal Fluid Tau Microtubule Binding Region Detects Symptom Onset, Cognitive Decline, Tangles, and Atrophy in Dominantly Inherited Alzheimer's Disease
Li, Yan , Barthélemy, Nicolas R. , Gordon, Brian A. , Hassenstab, Jason , Fagan, Anne M. , Morris, John C. , Xiong, Chengjie , Méndez, Patricio Chrem, Noble, James M. , Farlow, Martin R. , Chhatwal, Jasmeer P. , Day, Gregory S. , Masters, Colin L. , Roh, Jee Hoon , Sachdev, Pallavi, Koyama, Akihiko , Reyderman, Larisa, Bateman, Randall J. , Network, and the Dominantly Inherited Alzheimer, Sachdev, Perminder S. , Vöglein, Jonathan , Gordon, Brian A , Kasuga, Kensaku , Day, Gregory S , Jucker, Mathias , Roh, Jee Hoon , Sato, Chihiro , McDade, Eric M , Sachdev, Perminder S , Bateman, Randall J , Masters, Colin L , Vöglein, Jonathan , Xiong, Chengjie , Hassenstab, Jason , Morris, John C , Noble, James M , Horie, Kanta , Li, Yan, Benzinger, Tammie L.S. , Karch, Celeste M. , Xiong, Chengjie , Allegri, Ricardo , Ikeuchi, Takeshi , Schofield, Peter R. , Lee, Jae‐Hong , Sachdev, Pallavi, McDade, Eric , Network, and the Dominantly Inherited Alzheimer

Mayo Clinic

Annals of Neurology | February 27, 2023 | Volume: 93 | Issue: 6 | Pages: 1158-1172

10.1002/ana.26620 | PMID 36843330 Get It

ObjectiveIdentifying cerebrospinal fluid measures of the microtubule binding region of tau (MTBR‐tau) species that reflect tau aggregation could provide fluid biomarkers that track Alzheimer's disease related neurofibrillary tau pathological changes. We examined the cerebrospinal fluid (CSF) MTBR‐tau species in dominantly inherited Alzheimer's disease (DIAD) mutation carriers to assess the association with Alzheimer's disease (AD) biomarkers and clinical symptoms.MethodsCross‐sectional and longitudinal CSF from 229 DIAD mutation carriers and 130 mutation non‐carriers had sequential characterization of N‐terminal/mid‐domain phosphorylated tau (p‐tau) followed by MTBR‐tau species and tau positron emission tomography (tau PET), other soluble tau and amyloid biomarkers, comprehensive clinical and cognitive assessments, and brain magnetic resonance imaging of atrophy.ResultsCSF MTBR‐tau species located within the putative “border” region and one species corresponding to the “core” region of aggregates in neurofibrillary tangles (NFTs) increased during the presymptomatic stage and decreased during the symptomatic stage. The “border” MTBR‐tau species were associated with amyloid pathology and CSF p‐tau; whereas the “core” MTBR‐tau species were associated stronger with tau PET and CSF measures of neurodegeneration. The ratio of the border to the core species provided a continuous measure of increasing amounts that tracked clinical progression and NFTs.InterpretationChanges in CSF soluble MTBR‐tau species preceded the onset of dementia, tau tangle increase, and atrophy in DIAD. The ratio of 4R‐specific MTBR‐tau (border) to the NFT (core) MTBR‐tau species corresponds to the pathology of NFTs in DIAD and change with disease progression. The dynamics between different MTBR‐tau species in the CSF may serve as a marker of tau‐related disease progression and target engagement of anti‐tau therapeutics. ANN NEUROL 2023;93:1158–1172
Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer’s disease
Wheelock, Muriah D. , Strain, Jeremy F. , Mansfield, Patricia K. , Tu, Jiaxin Cindy , Tanenbaum, Aaron , Preische, Oliver, Chhatwal, Jasmeer P. , Cash, David M. , Fagan, Anne M. , Fox, Nick C. , Graff‐Radford, Neill R. , Hassenstab, Jason , Jack, Clifford R. , Xiong, Chengjie , Perrin, Richard J. , Xiong, Chengjie , Morris, John C. , Ances, Beau M. , Eggebrecht, Adam T. , Gordon, Brian A. , Network, the Dominantly Inherited Alzheimer, Adams, Sarah , Araki, Aki, Barthélemy, Nicolas R. , Bechara, Jacob , Berman, Sarah , Bodge, Courtney, Brandon, Susan E. , Brooks, W. K. , Brosch, Jared R. , Buck, Jill , Buckles, Virginia, Cash, Lisa, Chen, Charlie, Chrem, Patricio, Chua, Jasmin, Chui, Helena, Cruchaga, Carlos , Day, Gregory S. , Cruz, Chrismary De La, Denner, Darcy, Diffenbacher, Anna, Dincer, Aylin , Donahue, Tamara, Egido, Noelia , Esposito, Bianca, Farlow, Marty, Feldman, Becca , Fitzpatrick, Colleen , Franklin, Erin , Friedrichsen, Nelly, Gardener, Samantha L. , Goate, Alison , Goldberg, Sarah B. , Gonzalez, Alyssa, Gräber‐Sultan, Susanne, Graham, Morgan, Gray, Julia, Gremminger, Emily, Groves, Alex, Haass, Christian , Häsler, Lisa M., Hellm, Cortaiga, Herries, Elizabeth, Hoechst-Swisher, Laura, Hornbeck, Russ C. , Igor, Yakushev, Ihara, Ryoko , Ikonomović, Snežana, Ishii, Kenji , Jerome, Gina, Käser, Stephan, Keefe, Sarah , Klunk, William E. , Koudelis, Deb, Kuder-Buletta, Elke, Laske, Christoph , Martinez, Rita, Mason, Neal Scott, Mawuenyega, Kwasi G., Mejia, Arlene, Morenas‐Rodríguez, Estrella , Mori, Hiroshi , Mountz, James M. , Mummery, Cath, Nadkami, Neelesh, Nagamatsu, Akemi, Neimeyer, Katie, Norton, Joanne, Nuscher, Brigitte , Obermüller, Ulricke, Patira, Riddhi , Ping, Lingyan, Ringman, John M. , Salloway, Stephen , Senda, Michio , Seyfried, Nick , Shady, Kristine, Sigurdson, Wendy, Smith, Lori, Snitz, Beth E. , Sohrabi, Hamid R. , Stephens, Sochenda, Taddei, Kevin , Thompson, Sarah , Vöglein, Jonathan , Wang, Peter, Weamer, Elise A., Xu, Jinbin , Cruchaga, Carlos , Fagan, Anne M , Fox, Nick C , Graff-Radford, Neill R , Hassenstab, Jason , Jack, Clifford R , Karch, Celeste M , Xiong, Chengjie , McDade, Eric M , Schofield, Peter R , Xiong, Chengjie , Morris, John C , Bateman, Randall J , Jucker, Mathias , Benzinger, Tammie L S , Ances, Beau M , Eggebrecht, Adam T , Gordon, Brian A , Cruchaga, Carlos , Day, Gregory S , Vöglein, Jonathan , Cash, David M , Goate, Alison M , Berman, Sarah , Karch, Celeste M. , McDade, Eric , Schofield, Peter R. , Bateman, Randall J. , Benzinger, Tammie L.S. , Network, the Dominantly Inherited Alzheimer, Allegri, Ricardo , Brandon, Susan, Brooks, William (Bill), Buck, Jill, Carter, Kathleen, Douglas, Jane, Duong, Duc M , Feldman, Becca, Fitzpatrick, Colleen, Flores, Shaney , Fujii, Hisako , Ghetti, Bernardino , Goldman, Jill , Grilo, Miguel, Hofmann, Anna, Holtzman, David M. , Ikeuchi, Takeshi , Johnson, Erik C. B. , Kasuga, Kensaku , Koeppe, Robert A. , Lee, Jae‐Hong , Levey, Allan I. , Li, Yan , López, Oscar L. , Marsh, Jacob, Martins, Ralph N. , Masters, Colin L. , McCullough, Austin , Niimi, Yoshiki , Noble, James M. , O’Connor, Antoinette , Ping, Lingyan, Renton, Alan , Sánchez‐Valle, Raquel , Shimada, Hiroyuki , Smith, Jennifer A. , Thompson, Sarah, Wang, Qing , Xu, Xiong

Mayo Clinic

Brain | January 10, 2023 | Volume: 146 | Issue: 7 | Pages: 2928-2943

10.1093/brain/awac498 | PMID 36625756 Get It

Abstract Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer’s disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer’s disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer’s disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer’s disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer’s disease.
Plasma glial fibrillary acidic protein in autosomal dominant Alzheimer's disease: Associations with Aβ‐PET, neurodegeneration, and cognition
Chatterjee, Pratishtha , Vermunt, Lisa , Gordon, Brian A. , Boonkamp, Lynn , Armstrong, Nicola J. , Xiong, Chengjie , Singh, Abhay Kumar , Li, Yan , Sohrabi, Hamid R. , Taddei, Kevin , Molloy, Mark P. , Morris, John C. , Berman, Sarah , Chhatwal, Jasmeer P. , Graff‐Radford, Neill R. , Day, Gregory S. , Farlow, Martin R. , Fox, Nick C. , Goate, Alison , Hassenstab, Jason , Mori, Hiroshi , Perrin, Richard J. , Levey, Allan I. , Masters, Colin L. , Fagan, Anne M. , Bateman, Randall J. , Martins, Ralph N. , Network, and the Dominantly Inherited Alzheimer, Vöglein, Jonathan , Gordon, Brian A , 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 , Levey, Allan I , Pedrini, Steve , Xiong, Chengjie , Benzinger, Tammie L.S. , Karch, Celeste M. , Cruchaga, Carlos , Lee, Jae‐Hong , McDade, Eric , Sánchez‐Valle, Raquel , Schofield, Peter R. , Jucker, Mathias , Teunissen, Charlotte E. , Network, and the Dominantly Inherited Alzheimer

Mayo Clinic

Alzheimer's & Dementia | December 28, 2022 | Volume: 19 | Issue: 7 | Pages: 2790-2804

10.1002/alz.12879 | PMID 36576155 Get It

Abstract Background Glial fibrillary acidic protein (GFAP) is a promising candidate blood‐based biomarker for Alzheimer's disease (AD) diagnosis and prognostication. The timing of its disease‐associated changes, its clinical correlates, and biofluid‐type dependency will influence its clinical utility. Methods We evaluated plasma, serum, and cerebrospinal fluid (CSF) GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease. Results Plasma GFAP elevations appear a decade before expected symptom onset, after amyloid beta (Aβ) accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished Aβ‐positive from Aβ‐negative ADAD participants and showed a stronger relationship with Aβ load in asymptomatic than symptomatic ADAD. Higher plasma GFAP was associated with the degree and rate of neurodegeneration and cognitive impairment. Serum GFAP showed similar relationships, but these were less pronounced for CSF GFAP. Conclusion Our findings support a role for plasma GFAP as a clinical biomarker of Aβ‐related astrocyte reactivity that is associated with cognitive decline and neurodegeneration. Highlights Plasma glial fibrillary acidic protein (GFAP) elevations appear a decade before expected symptom onset in autosomal dominant Alzheimer's disease (ADAD). Plasma GFAP was associated to amyloid positivity in asymptomatic ADAD. Plasma GFAP increased with clinical severity and predicted disease progression. Plasma and serum GFAP carried similar information in ADAD, while cerebrospinal fluid GFAP did not.