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Lao, Patrick

0000-0003-2243-3547

Mayo Clinic

Columbia University

Citations 7

Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease
Soleimani‐Meigooni, David N. , Chiotis, Konstantinos, Allen, Isabel E., Rabinovici, Gil D., Joie, Renaud La , Group, Meta-Centiloid Study, Apostolova, Liana G. , Asken, Breton M., Benzinger, Th., Betthauser, Tobey J., Bluma, Marina, Bombois, Stephanie, Bourgeat, Pierrick, Bouteloup, Vincent , Braskie, Meredith N., Brendel, Matthias, Brickman, Adam M., Bryant, Natalie, Bullich, Santiago , Carrillo, Maria C., Casaletto, Kaitlin, Cash, David M., Chang, Chiung-Chih, CHANG, H L, Chao, Yishu , Collij, Lyduine E., Corrada, Maria M., Craft, Suzanne , Dickerson, Bradford C., Dubois, Bruno, Dufouil, Carole, Fajardo, Alfonso, Farrar, Gill , Fortea, Juan, Frings, Lars , Frisoni, Giovanni B., Gardner, Raquel C., Gnörich, Johannes , Gordon, Brian A., Gu, Yuna , Guan, Yihui, Guo, Tengfei, Hanseeuw, Bernard J., Hansson, Oskar, Harrison, Theresa M., Huang, Qi, Huang, ST , Iaccarino, Leonardo, Ishii, Kazunari, Ishi, Kenji, Jagust, William J., Johnson, Sterling C., Kato, Takashi, Katsumi, Yuta, Kaye, Jeffrey, Kolinger, Guilherme D., Kramer, Joel H. , Landau, Susan M., Landeau, Brigitte, Lao, Patrick J., Lee, Sangwon, Lopresti, Brian J., Lowe, Val J. , Luchsinger, José A., Mao, Xiaoxie, March, Andrew, Masters, Colin L., Meyer, Philipp T., Mezenge, Florence, Mormino, Elizabeth C., Franquesa‐Mullerat, María , Nakamura, Akinori, Nordberg, Agneta, O’Brien, John T., O’Bryant, Sid E., Pappas, Ioannis, Peretti, Debora E., Rowe, Christopher C., Rowe, James B., Schwartz, Daniel L., Seo, Sang Won , Shekari, Mahnaz, Smith, Ruben, Snyder, Heather M. , Sokolowski, Andrzej, Sperling, Reisa A., Sun, Pan, Taggett, Jacinda Z., Touroutoglou, Alexandra , Vaillancourt, David E., Giessen, Elsmarieke van de, Vijverberg, Jort, Villemagne, Victor L. , Villeneuve, Sylvia , Wang, Wei-en, Weiner, Michael, Woodworth, Davis, Xiao, Cally , Xie, F, Yoon, Yeojun, Yun, Mijin, Severanc, A4, ABIDE, ADNI*, ADNI-DoD, AgeWell, AIBL, AMYPAD, BACS, BATON, BIOCARD, BLSA, BioFINDER-2, BrANCH, CPAS, DETECT-AD, GEMS, GHABS, HABS, HABS-HD, IDEAS, IMAP, INSIGHT-preAD, Insight46, K-ROAD, LEADS, MCSA, MULNIAD, MEMENTO, SCAN, PREVENT-AD, SPIN,, Corrada, María M. , La Joie, Renaud , Blazhenets, Ganna , Chiotis, Konstantinos , Allen, Isabel Elaine , Rabinovici, Gil D. , Asken, Breton M. , Bejanin, Alexandre , Benzinger, Tammie L.S. , Betthauser, Tobey J. , Blūma, Marina , Bombois, Stéphanie , Bourgeat, Pierrick , Braskie, Meredith N. , Brendel, Matthias , Brickman, Adam M. , Carrillo, María C. , Casaletto, Kaitlin B. , Cash, David M. , Chang, Chiung‐Chih , Chang, Hsin‐I , Chêne, Geneviève , Chételat, Gaël , Coath, William , Collij, Lyduine , Colmant, Lise , Dickerson, Bradford Clark , Dubois, Bruno , Dufouil, Carole , Fortea, Juan , Garibotto, Valentina , Gordon, Brian A. , Guan, Yihui , Guo, Tengfei , Hanseeuw, Bernard , Hansson, Oskar , Harrison, Theresa M. , Iaccarino, Leonardo , Ishii, Kazunari , Ishii, Kenji, Jagust, William J. , Johnson, Sterling C. , Katsumi, Yuta , Kaye, Jeffrey , Koeppe, Robert A. , Kolinger, Guilherme Domingues , Landau, Susan , Landeau, Brigitte , Lao, Patrick , Lee, Sangwon, Lleó, Alberto , Lopresti, Brian J. , Malpetti, Maura , March, Andrew, Masters, Colin L. , Mézenge, Florence, Mormino, Elizabeth C. , Nakamura, Akinori , Nordberg, Agneta , O'Brien, John Tiernan , O’Bryant, Sid E. , Pappas, Ioannis , Quenon, Lisa , Rowe, Christopher Cleon , Rowe, James B. , Rudolph, Marc D. , Salvadó, Gemma , Schott, Jonathan M. , Schwarz, Christopher G. , Shekari, Mahnaz , Silbert, Lisa C. , Smith, Ruben, Sokolowski, Andrzej, Sperling, Reisa Anne , Sun, Pan , Taggett, Jacinda , Toga, Arthur W. , Vaillancourt, David E. , Giessen, Elsmarieke van de , Vemuri, Prashanthi , Villain, Nicolas , Wang, Wei‐en , Weiner, Michael W. , Xie, Fang , Young, Christina B. , Yun, M R

JAMA | July 13, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jama.2026.13116 Get It

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.
Sex, education and race/ethnicity have distinct effects on amyloid and tau‐PET status
Groot, Colin , Rowe, Christopher C., Giessen, Elsmarieke van de, Flier, Wiesje M. van der, Pijnenburg, Yolande A.L., Visser, Pieter Jelle, Braber, Anouk den, Pontecorvo, Michael J. , Burnham, Samantha C., Lu, Ming , Jagust, William J., Baker, Suzanne L. , Harrison, Theresa, Gispert, Juan Domingo, Shekari, Mahnaz , Minguillón, Carolina, Smith, Ruben, Mattsson‐Carlgren, Niklas, Palmqvist, Sebastian, Strandberg, Olof, Stomrud, Erik, Brickman, Adam, Manly, Jennifer J., Lao, Patrick J., Kreisl, William Charles, Malpetti, Maura, O'Brien, John T, Jäger, Elena, Bischof, Gérard, Drzezga, Alexander, Xie, Fang, Mao, Xiaoxie, Guan, Yihui, Frisoni, Giovanni B, Peretti, Débora Elisa , Skoog, I., Kern, Silke, Sperling, Reisa A., Johnson, Keith A., Risacher, Shannon, Saykin, Andrew J., Carrillo, Maria C., Dickerson, Brad C., Apostolova, Liana G., Rabinovici, Gil D., Barthel, H, Messerschmidt, Konstantin, Vandenberghe, Rik, Laere, Koen J. Van, Spruyt, Laure , Petersen, Ronald, Jack, Clifford R., Franzmeier, Nicolai, Brendel, Matthias, Gnörich, Johannes, Benzinger, Tammie L.S., Lagarde, Julien, Sarazin, Marie , Villeneuve, Sylvia , Poirier, Judes, Seo, Sang Won, Gu, Yuna , Kim, Jun Pyo, Mormino, Beth C., Vossler, Hillary , Rosa‐Neto, Pedro, Therriault, Joseph, Rahmouni, Nesrine, Cash, David M, Schott, Jonathan M, Hanseeuw, Bernard J, Jansen, Willemijn J. , Joie, Renaud La, Rosen, Howard J., Johnson, Sterling C., Christian, Bradley T, Betthauser, Tobey J., Landau, Susan M., O'Bryant, Sid E., Hansson, Oskar H., Ossenkoppele, Rik, Prevent‐AD, ADNI, ADNI‐DOD, A‐Study, MCSA,, O’Brien, John T. , O'Brien, John Tiernan , Groot, Colin , Coomans, Emma M. , Rowe, Christopher C., Doré, Vincent , Feizpour, Azadeh , Giessen, Elsmarieke van de , Flier, Wiesje M. van der , Pijnenburg, Yolande A.L. , Visser, Pieter Jelle , Braber, Anouk den , Burnham, Samantha C. , Kennedy, Ian Andrew , Jagust, William J. , Harrison, Theresa M. , Gispert, Juan Domingo , Shekari, Mahnaz , Minguillón, Carolina , Smith, Ruben, Mattsson, Niklas , Palmqvist, Sebastian , Strandberg, Olof, Stomrud, Erik , Brickman, Adam M. , Luchsinger, Jose Alejandro , Manly, Jennifer J. , Lao, Patrick , Malpetti, Maura , Rowe, James B. , Bischof, Gérard N. , Drzezga, Alexander E. , Xie, Fang , Guan, Yihui , Garibotto, Valentina , Frisoni, Giovanni B. , Schöll, Michael , Kern, Silke , Sperling, Reisa Anne , Johnson, Keith A. , Risacher, Shannon L. , Saykin, Andrew J. , Carrillo, María C. , Dickerson, Bradford Clark , Apostolova, Liana G. , Rabinovici, Gil D. , Rullmann, Michael , Messerschmidt, Konstantin, Vandenberghe, Rik , Petersen, Ronald, Jack, Clifford R. , Franzmeier, Nicolai , Brendel, Matthias , Gnörich, Johannes , Benzinger, Tammie L.S. , Lagarde, Julien , Bottlaender, Michel , Poirier, Judes , Seo, Sang Won , Kim, Jun Pyo, Young, Christina B. , Rosa-Neto, Pedro , Therriault, Joseph , Rahmouni, Nesrine , Coath, William , Cash, David M. , Schott, Jonathan M. , Hanseeuw, Bernard , Salman, Yasmine , Malotaux, Vincent , Joie, Renaud La , Rosen, Howard J. , Johnson, Sterling C. , Christian, Bradley T. , Betthauser, Tobey J. , Landau, Susan , O’Bryant, Sid E. , Hansson, Oskar , Ossenkoppele, Rik

Alzheimer's & Dementia | January 8, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_105387 Get It

Abstract Background Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self‐reported sex, educational attainment and race/ethnicity on amyloid‐positivity, and tau‐PET‐positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Method Logistic generalized estimating equations were used to estimate frequency of amyloid‐positivity (using cohort‐specific thresholds for amyloid‐PET [84%] or CSF) and tau‐PET‐positivity (cohort‐specific thresholds of 2SD above mean temporal uptake in amyloid‐negative controls). We assessed: i) sex and APOEε4 ( N = 10,098) associations, to complement earlier findings of a higher frequency of tau‐positivity in females, ii) effects of lower/higher education ( N = 10,970; cohort‐specific median‐split), and iii) effects of race/ethnicity (non‐Hispanic White [hereafter: White], N = 4880; Asian, N = 116; Black or African‐American [hereafter: Black], N = 353; Hispanic, N = 356, only from Northern‐American cohorts). Outcomes were frequency of amyloid‐positivity in CU individuals only, and tau‐PET‐positivity in both amyloid‐positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau‐positivity were assessed and only retained in the models when significant. Result Female sex was associated with an APOEε4 ‐independent increased frequency of amyloid‐positivity (β=0.51[0.22], p = 0.02) in CU and increase of tau‐positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p <0.01). Remarkably, tau‐positivity frequencies of female APOEε4 non‐carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid‐positivity frequency (β=‐0.12[0.05], p = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau‐positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non‐White groups compared to White (Hispanic:β interaction =‐0.05[0.01], p <0.01; Black:‐0.04[0.01], p <0.01; Asian:‐0.02[0.01], p = 0.04). This suggests that the impact of age on amyloid‐positivity was less pronounced in non‐White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau‐positivity frequency than White (β=0.51[0.22], p = 0.02; Figure 3). Conclusion In this multi‐center initiative comprised of clinical and community‐based cohorts, we observed that self‐reported sex, educational attainment and race/ethnicity were related to positivity‐frequencies of Alzheimer's disease pathology.
The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI): Overview of consortium sites and anticipated enrollment
Oomens, Julie Elisabeth , Biber, Sarah , Albert, Marilyn, Alosco, Michael L. , Arfanakis, Konstantinos , Brewer, James B., Chin, Erin, Clark, Lindsay R. , Cohen, Ann D. , Dage, Jeffrey L. , Detre, John A. , DiFilippo, Frank P. , Dyck, Christopher H. van , Grabowski, Thomas J. , Habes, Mohamad, Hedden, Trey , Jagust, William, Jefferson, Angela L. , Kecskemeti, Steven , Kantarci, Kejal, Keene, Dirk, Knoefel, Janice E. , Lin, Weili, Masurkar, Arjun V. , Morhardt, Darby, Okonkwo, Ozioma C. , Rabinovici, Gil D. , Rahman‐Filipiak, Annalise , Reiman, Eric M., Risacher, Shannon L. , Rosen, Howie, Schneider, Lon S. , Song, Allen W. , Swerdlow, Russell H. , Vaillancourt, David E. , Villemagne, Victor L. , Qiu, Deqiang , Foroud, Tatiana, Mormino, Elizabeth C. , Kantarci, Kejal , Oomens, Julie E , Kantarci, Kejal , Rabinovici, Gil D , Dage, Jeffrey L , Cohen, Annie , Benzinger, Tammie L.S. , Burns, Jeffrey M. , Chin, Nathaniel A. , Dickerson, Bradford Clark , Donohue, Michael , Fan, Audrey Peiwen , Habes, Mohamad , Harrison, Theresa M. , Hohman, Timothy J. , Jicha, Gregory A. , Kukull, Walter A. , Lin, Weili , Lao, Patrick , Lepping, Rebecca J. , Levendovszky, Swati Rane , McConathy, Jonathan , Mindt, Mónica Rivera , Noll, Douglas C. , Parrish, Todd B. , Reiman, Eric M. , Rudolph, Marc D. , Silbert, Lisa C. , Stark, Craig E.L. , Thompson, Paul M. , Wolk, S. J. , Johnson, Sterling C.

Alzheimer's & Dementia | November 10, 2025 | Volume: 21 | Issue: 11 | Pages: No page available

10.1002/alz.70880 Get It

Abstract INTRODUCTION The Consortium for Clarity in Alzheimer's disease related dementias (ADRD) Research Through Imaging (CLARiTI) is a study that aims to collect standardized imaging and plasma biomarkers on 2000 Clinical Core participants enrolled across all Alzheimer's Disease Research Centers (ADRC) sites. We sought to summarize the known heterogeneity across centers regarding scientific focus and initial enrollment plans for CLARiTI. METHODS We developed and distributed a survey capturing information on the 36 CLARiTI site's theme/expertise, recruitment plans, and the intersection of CLARiTI with other ADRC imaging efforts. RESULTS Anticipated CLARiTI enrollees spanned 11 different categories of suspected etiologies underlying impairment. A wide range of risk factors were endorsed across sites regarding the enrollment of unimpaired individuals. Variability also existed regarding site‐level strategies in enrollment into CLARiTI versus other imaging efforts. DISCUSSION We anticipate that the 2000 individuals that will enroll into CLARiTI will reflect the clinical heterogeneity already in place across the ADRC network. Highlights The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will leverage and contribute to the existing Alzheimer's Disease Research Centers (ADRC) program by supporting standardized imaging and plasma collection across all centers. We summarize the variation in scientific focus and enrollment plans across ADRC sites participating in CLARiTI. The anticipated CLARiTI cohort will reflect the clinical heterogeneity that already exists across the ADRC network. CLARiTI will contribute to scientific goals related to the detection of multi‐etiological signatures relevant for Alzheimer's disease and related disorders (ADRDs).
Cross‐Sectional FDG in Down Syndrome and Autosomal Dominant Alzheimer's Disease
Abdelmoity, Omar , Wisch, Julie K. , Kennedy, James T. , Vlassenko, Andrei G. , Handen, Benjamin L. , Head, Elizabeth , Lai, Florence , Rosas, H. Diana , Hartley, Sigan L. , Tudorascu, Dana , Keefe, Sarah , Ikeuchi, Takeshi, Morris, John C., Roh, Jee Hoon , Day, Gregory S. , Xiong, Chengjie , Head, Elizabeth , Lao, Patrick , Keefe, Sarah , Roh, Jee Hoon , Day, Gregory S , Gordon, Brian A , Xiong, Chengjie , Wisch, Julie K , Goyal, Manu S. , Flores, Shaney , Keator, David B. , Rafii, Michael S. , Zaman, Shahid H. , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Fougère, Christian la , Llibre‐Guerra, Jorge J. , Ikeuchi, Takeshi , Morris, John C. , Schofield, Peter R. , Gordon, Brian A. , Benzinger, Tammie L.S. , Ances, Beau M.

Annals of Neurology | September 22, 2025 | Volume: 98 | Issue: 6 | Pages: 1237-1248

10.1002/ana.78002 Get It

Objectives Directly compare the brain glucose patterns seen with [F‐18] fluorodeoxyglucose (FDG) positron emission tomography (PET) between 2 genetically determined forms of Alzheimer's disease: Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD). Methods Cross‐sectional analyses of FDG were performed in individuals with DS (n = 76) from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS), ADAD (n = 297), and neurotypical familial controls (n = 188) from the Dominantly Inherited Alzheimer Network (DIAN). Within‐group linear regression models and generalized additive models were performed for select regional FDG uptake measures (isthmus cingulate and inferior parietal, precuneus, middle temporal gyrus, and precentral gyrus). Age, sex, apolipoprotein (APOE) ε4 carrier status, and cortical amyloid burden were included within these analyses. Results Even 20 years before expected onset of clinical symptoms, FDG uptake was lower for DS compared to neurotypical familial controls ( p < 0.01). ADAD baseline FDG was similar to neurotypical familial controls until 7 years before expected symptom onset. Both symptomatic individuals with DS and ADAD had lower FDG compared to neurotypical familial controls ( p < 0.01). A higher amyloid burden was associated with lower FDG for both genetic forms, with similar rates of decline in FDG uptake for DS and ADAD who were amyloid positive. Interpretation Brain glucose metabolism is substantially lower for people with DS, even in individuals who are cognitively stable. The patterns of FDG decline are distinct in these 2 genetically determined forms of AD. The diagnostic utility of FDG‐PET is specific to the genetic form of AD. ANN NEUROL 2025;98:1237–1248
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.