{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T17:17:41Z","timestamp":1777396661199,"version":"3.51.4"},"reference-count":62,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T00:00:00Z","timestamp":1727913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["U54GM115677"],"award-info":[{"award-number":["U54GM115677"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["U54GM115677"],"award-info":[{"award-number":["U54GM115677"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-\u03b2 (A\u03b2) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein ( APOE) \u025b4 status) risk factors in detecting preclinical AD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      125 cognitively unimpaired older adults (mean age\u2009=\u200966 years) who completed A\u03b2 PET and plasma draw were analyzed using multiple regression with A\u03b2 PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors APOE \u025b4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (A\u03b2\n                      <jats:sub>42\/40<\/jats:sub>\n                      ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted A\u03b2 PET status, and these markers were added in Model 4.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The best model for predicting A\u03b2 PET status included age, years of education, APOE \u025b4 status, A\u03b2\n                      <jats:sub>42\/40<\/jats:sub>\n                      ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13872877241283692","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T01:50:42Z","timestamp":1732499442000},"page":"89-98","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Added value of inflammatory plasma biomarkers to pathologic biomarkers in predicting preclinical Alzheimer's disease"],"prefix":"10.1177","volume":"102","author":[{"given":"Haley","family":"Leclerc","sequence":"first","affiliation":[{"name":"Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Athene KW","family":"Lee","sequence":"additional","affiliation":[{"name":"Butler Hospital Memory & Aging Program, Providence, RI, USA"},{"name":"Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zachary J","family":"Kunicki","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5090-4206","authenticated-orcid":false,"given":"Jessica","family":"Alber","sequence":"additional","affiliation":[{"name":"Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, USA"},{"name":"Butler Hospital Memory & Aging Program, Providence, RI, USA"},{"name":"Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI, 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