{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T15:51:51Z","timestamp":1776873111684,"version":"3.51.2"},"reference-count":38,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82272414"],"award-info":[{"award-number":["82272414"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer's Disease Reports"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Alzheimer's disease (AD) is the most common type of dementia, and early screening is crucial for intervention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Currently, early screening for older adults without dementia primarily rely on cognitive scale. This study aims to explore a more feasible approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Plasma biomarkers (A\u03b2\n                      <jats:sub>42\/40<\/jats:sub>\n                      , p-tau181 and p-tau217) and Gaussian mixture models (GMM) were utilized for stratifying risk levels in older adults without dementia from the Alzheimer's Disease Neuroimaging Initiative. Linear mixed effects model was employed to compare subsequent pathological and cognitive changes, alongside a comparison with traditional scale-based screening methods. Cox regression model was used to assess the risk of progression to dementia across different biomarker status groups.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Plasma A\u03b2\n                      <jats:sub>42\/40<\/jats:sub>\n                      and p-tau217 effectively predicted A\u03b2 PET pathological progression, while p-tau217 also predicted tau PET changes. All three biomarkers could forecast the progression of FDG PET and cognitive function. P-tau217 and p-tau181 significantly modulated pathology-related cognitive impairment. All three biomarkers could predict dementia risk. The screening method combining GMM with plasma biomarkers demonstrates superior predictive ability compared to traditional scale-based approaches.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our study indicated that the combination of GMM and plasma biomarkers for community screening shows promising potential in monitoring brain health among older adults without dementia. P-tau217 exhibited the best predictive value among the three plasma biomarkers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/25424823251331110","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T08:04:03Z","timestamp":1750752243000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Predicting brain health in community-dwelling elderly populations by integrating Gaussian mixture model and plasma biomarkers"],"prefix":"10.1177","volume":"9","author":[{"given":"Yue","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianshu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolin","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2828-9067","authenticated-orcid":false,"given":"Pengfei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1228-5739","authenticated-orcid":false,"given":"Zhiming","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Alzheimer's Disease Neuroimaging Initiative (ADNI) *","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,6,24]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijms24010107"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/s43587-023-00410-4"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(21)00066-1"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/alz.12283"},{"key":"e_1_3_5_6_2","first-page":"1797","article-title":"Plasma p-tau231 and p-tau217 as state markers of amyloid-\u03b2 pathology in preclinical Alzheimer's disease","volume":"28","author":"Mil\u00e0-Alom\u00e0 M","year":"2022","unstructured":"Mil\u00e0-Alom\u00e0 M, Ashton NJ, Shekari M, et al. Plasma p-tau231 and p-tau217 as state markers of amyloid-\u03b2 pathology in preclinical Alzheimer's disease. 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Amyloid-beta biomarkers in Braak stages and their predictive relationships with cognitive impairment: Support vector machine and deep learning approaches. bioRxiv 2022. doi: https:\/\/doi.org\/10.1101\/2022.09.25.509432 [Preprint]. 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