Citations 2
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
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.
Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes
Guen, Yann Le , Luo, Guo , Damotte, Vincent , Jansen, Iris E. , Nicolas, Aude , Rojas, Itziar de, Bellenguez, Céline , Lian, Michelle Mulan , Parveen, Kayenat, Morizono, Takashi, Park, Hyeonseul, Grenier‐Boley, Benjamin , Naito, Tatsuhiko , Talyansky, Seth D., Yogeshwar, Selina , Sempere, Vicente Peris, Satake, Wataru , Álvarez, Victoria , Arosio, Beatrice , Boland, Anne , Daniele, Antonio , Darling, D.H., Dichgans, Martin , Dufouil, Carole , Düzel, Emrah , García‐Ribas, Guillermo, García‐Alberca, José María , García-González, Pablo, Giedraitis, Vilmantas , Graff, Caroline , Grünblatt, Edna , Hausner, Lucrezia , Jung, Yoo Jin , Deckert, Jürgen, Kern, Silke , Kuulasmaa, Teemu , Lee, Kun Ho , Lin, Ling , Masullo, Carlo , Mehrabian, Shima , Mendonça, Alexandre de , Boada, Merçé , Mir, Pablo , Moreno, Fermín , Nicolas, Gaël , Niida, Shumpei , Nordestgaard, Børge G. , Papenberg, Goran, Papma, Janne M., Pástor, Pau , Peters, Oliver , Popp, Julius , Molina‐Porcel, Laura , Puerta, Raquel , 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Proceedings of the National Academy of Sciences | August 29, 2023 | Volume: 120 | Issue: 36 | Pages: No page available
Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.