{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T15:00:10Z","timestamp":1787065210006,"version":"build-2736575974"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T00:00:00Z","timestamp":1656547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Biomarkers used for predicting longitudinal cognitive change in Alzheimer\u2019s disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Patients and Methods<\/jats:title>\n                    <jats:p>A total of 430 subjects including, 96 cognitive normal (CN) with amyloid \u03b2 (A\u03b2)-negative, 54 CN with A\u03b2-positive, 195 mild cognitive impairment (MCI) with A\u03b2-positive, and 85 AD with amyloid-positive (A\u03b2-positive are identified by CSF A\u03b242\/A\u03b240 &amp;lt; 0.138). A\u03b2 burden was evaluated by CSF and plasma A\u03b242\/A\u03b240 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer\u2019s Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Baseline CSF A\u03b242\/A\u03b240 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 \u00d7 time, plasma p-tau181 \u00d7 time, CSF sTREM2 \u00d7 time, and brain volumes \u00d7 time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2022.848180","type":"journal-article","created":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T07:43:01Z","timestamp":1656574981000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer\u2019s Disease Continuum"],"prefix":"10.3389","volume":"14","author":[{"given":"Yi-He","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong-Rong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui-Feng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan-Yan","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing-Qing","family":"Tao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,6,30]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.jalz.2010.03.006","article-title":"Clinical core of the alzheimer\u2019s disease neuroimaging initiative: progress and plans.","volume":"6","author":"Aisen","year":"2010","journal-title":"Alzheimers Dement."},{"key":"B2","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.aaf2362","article-title":"Tau and A\u03b2 imaging, CSF measures, and cognition in Alzheimer\u2019s disease.","volume":"8","author":"Brier","year":"2016","journal-title":"Sci. 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