[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-458371-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-458371-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","identifying-populations-with-a-rapid-rate-of-cognitive-decline-using-plasma-biomarkers","Identifying populations with a rapid rate of cognitive decline using plasma biomarkers","","Background: Identifying populations with a rapid rate of cognitive decline is essential for running effective clinical trials to slow decline. Healthy volunteers often show a shallower decline rate, leaving limited room for benefit and risking underpowered trials. Methods: InARIC, frozen plasma (2011-2013) was assayed on Quanterix SiMoA, measuring amyloid-β42/amyloid-β40, p-tau181, NFL, and GFAP. Cognitive trajectories (2011-2022) were modeled with linear mixed effects and multiple imputation; ARIC-derived risk scores predicted decline in ACHIEVE. Results: ARIC participants had annualized change −0.069 (SD 0.087) versus −0.012 (SD 0.231) in ACHIEVE volunteers. Biomarker risk scores validated in ACHIEVE, and predicted progression rates were higher in the top risk quintile. Adding age and MMSE did not improve scores. Trial power rose substantially under higher decline scenarios. Conclusions: Plasma-biomarker risk scores can identify individuals likely to experience rapid cognitive decline and may improve future trial feasibility.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/identifying-populations-with-a-rapid-rate-of-cognitive-decline-using-plasma-biomarkers/458371/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/identifying-populations-with-a-rapid-rate-of-cognitive-decline-using-plasma-biomarkers/458371.png","ImageObject",300,407,{"name":42,"@type":43},"Angel","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-03","2026-09-30",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",8,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"Why is identifying rapid cognitive decline populations important?","Question",{"text":63,"@type":64},"It supports effective clinical trial design to slow cognitive decline. Healthy volunteers often decline more slowly, which can limit detectable benefit and reduce statistical power.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which plasma biomarkers were measured in the study?",{"text":68,"@type":64},"The study measured amyloid-β42/amyloid-β40 ratio, p-tau181, NFL, and GFAP. Biomarker assessments used the Quanterix SiMoA platform in ARIC and an Alamar CNS protein panel in ACHIEVE.",{"name":70,"@type":61,"acceptedAnswer":71},"How were biomarker risk scores used to predict cognitive decline?",{"text":72,"@type":64},"Risk scores developed in ARIC were validated in ACHIEVE as predictors of decline between years 3 and 5. Adding age and Mini Mental State Exam did not improve the risk scores.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},458371,1790812521,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":108,"slug":109},7,40,"healthcare",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":97,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},687207412472,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","DOI: 10. 1002/alz70856_105785  \nBIOMARKERS  \nPOSTER PRESENTATION  \nBIOMARKERS (NON-NEUROIMAGING)  \nIdentifying populations with a rapid rate of cognitive decline using plasma biomarkers  \nJosef Coresh1  James Russell Pike 1  Nicholas S Reed2  Priya Palta3  Jennifer A. Deal4  Keenan A. Walker5  Kevin J. Sullivan6  Bharat Thyagarajan7 Rebecca F. Gottesman8  Thomas H. Mosley Jr.6  Frank R Lin4  \n1 Departments of Population Health and Medicine, New York University Grossman School of Medicine, New York, NY, USA  \n2 New York University, New York, NY, USA  \n3 University of North Carolina at Chapel Hill, Chapel Hill, NC, USA  \n4Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA  \n5 Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA  \n6 University of Mississippi Medical Center, The MIND Center, Jackson, MS, USA  \n7 University of Minnesota, Minneapolis, MN, USA  \n8 National Institute of Neurological Disorders & Stroke, Bethesda, MD, USA  \nCorrespondence  \nJosef Coresh, Departments of Population Health and Medicine, New York University Grossman School of Medicine, New York, NY, USA.  \n[Email:](Email: josef.coresh@nyulangone.org)[ josef.coresh@nyulangone.org](Email: josef.coresh@nyulangone.org)  \nAbstract  \nBackground: Identifying populations with a rapid rate of cognitive decline is important for conducting effective clinical trials to slow down this rate of decline. This is important since healthy volunteers often have a shallower rate of cognitive decline and hence have little room for benefit resulting in underpowered clinical trials.  \nMethods: InARIC, we assayed frozen plasma collected in2011-13using the Quanterix SiMoA platform. Neurodegeneration andAD biomarkers measured included amyloid-β 42 to amyloid-β 40 ratio, p-tau 181, NFL, and GFAP. Global cognition factor score from tenneuropsychological tests were administered toARIC participantsfrom2011-2022. Linear mixed effects models with multiple imputation of pre-death cognitive change estimated the association between biomarkers with annualized change in cognition. In ACHIEVE, assessed the 4 biomarkers using the Alamar CNS protein panel frozen plasma at the 3-year follow-up. Biomarkers were standardized within platforms using inverse-normal transformation. Cognitive decline risk scores developed in ARIC were applied to ACHIEVE and tested as predictors of cognitive decline between years 3 and 5 of ACHIEVE.  \nResults: Table 1 shows baseline characteristics and the annualized change in cognition, mean (SD) of-0.069 (0.087) among 1825 ARIC general population participants and much shallower and more variable-0.012 (0.231) among 502 ACHIEVE clinical trial volunteers. Biomarker risk scores developed in ARIC validated in ACHIEVE (Table 2) with the upper quintile (Table 3) having a mean (95% CI) progression rate of-0. 123 ( - 0.137,-0.108)inARICand-0.111(-0.158,-0.065)inACHIEVE. Adding age and the Mini Mental State Exam did not improve the risk scores. The power of a clinical trial would change from 5% to 64% to 96% as mean annualized cognitive decline increases from-0.012 (volunteers selected like ACHIEVE) to-0.068 (general population like ARIC) to  \nThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.  \n© 2025 The Alzheimer’s Association. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.  \nAlzheimer’s Dement. 2025;21(Suppl. 2):e105785.  \n[https://doi.org/10.1002/alz70856_105785](https://doi.org/10.1002/alz70856_105785)  \nwi[leyonlinelibrary.com/journal/alz](leyonlinelibrary.com/journal/alz)  \n1of5  \nBIOMARKERS  \n-0.111 (selected top risk quintile) assuming 800 participants, a progression SD of 0.25, and a 20% reduction in cognitive decline from an intervention.  \nConclusions: Risk scores based on plasma biomarkers m","cbCaihSM47EkkHtD","https://ap.wps.com/l/cbCaihSM47EkkHtD","pdf",3007036,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions","[{\"question\":\"Why is identifying rapid cognitive decline populations important?\",\"answer\":\"It supports effective clinical trial design to slow cognitive decline. Healthy volunteers often decline more slowly, which can limit detectable benefit and reduce statistical power.\"},{\"question\":\"Which plasma biomarkers were measured in the study?\",\"answer\":\"The study measured amyloid-β42/amyloid-β40 ratio, p-tau181, NFL, and GFAP. Biomarker assessments used the Quanterix SiMoA platform in ARIC and an Alamar CNS protein panel in ACHIEVE.\"},{\"question\":\"How were biomarker risk scores used to predict cognitive decline?\",\"answer\":\"Risk scores developed in ARIC were validated in ACHIEVE as predictors of decline between years 3 and 5. Adding age and Mini Mental State Exam did not improve the risk scores.\"}]","Identifying populations with a rapid rate of cognitive decline using plasma biomarkers | PDF",1790752743,13]