{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T18:16:28Z","timestamp":1789668988170,"version":"4.0.1"},"reference-count":140,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000957","name":"Alzheimer\u2019s Association","doi-asserted-by":"publisher","award":["AARG-NTF-1244080"],"award-info":[{"award-number":["AARG-NTF-1244080"]}],"id":[{"id":"10.13039\/100000957","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Alzheimer\u2019s Disease (AD) management is challenging due to limitations in detection methods. Currently, cerebrospinal fluid (CSF) biomarkers involve assessing \u03b2-amyloid (A\u03b2) and phosphorylated tau proteins. The lumbar puncture procedure to obtain CSF is invasive and sometimes causes significant anxiety in patients. In contrast, plasma biomarkers would allow rapid, accurate, and cost-effective diagnosis, while minimizing invasiveness and discomfort. Using a dataset involving 120 plasma proteins from clinically diagnosed AD patients versus cognitively normal subjects, we developed classification models by applying various machine learning algorithms (EBlasso, EBEN, XGBoost, LightGBM, TabNet, and TabPFN) to plasma proteomic measurements. Gene ontology and pathway enrichment, and a literature review were used to evaluate the potential relevance of the biomarkers identified in AD-related mechanisms. Biomarkers identified were also evaluated for the enrichment of aging-related biomarkers. The models developed yielded high AUROC and accuracy, mostly &gt;0.9. Proteins selected as predictors by all the models included Angiopoietin-2 (ANG-2), epidermal growth factor (EGF), Interleukin 1\u03b1 (IL-1\u03b1), and platelet growth factor subunit B (PDGF-BB). Ample previous literature supported their relevance in AD. The pool of all the biomarkers identified was significantly enriched with known aging-related biomarkers (p = 0.040). Applying cutting-edge algorithms is expected to be advantageous for developing AD prediction models with plasma proteomic data, and future large studies to externally validate the constructed models in other populations to assess their generalizability is important. The proteins uncovered may represent novel preventative or therapeutic targets.<\/jats:p>","DOI":"10.3390\/ijms262311673","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T12:39:43Z","timestamp":1764679183000},"page":"11673","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Development of Plasma Protein Classification Models for Alzheimer\u2019s Disease Using Multiple Machine Learning Approaches"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7678-169X","authenticated-orcid":false,"given":"Amy","family":"Tsurumi","sequence":"first","affiliation":[{"name":"Department of Surgery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit St., Boston, MA 02114, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine M.","family":"Cahill","sequence":"additional","affiliation":[{"name":"Neurochemistry Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, 149 13th St., Charlestown, MA 02129, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3096-1788","authenticated-orcid":false,"given":"Andy J.","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Duke University School of Medicine, 3116 N. Duke St., Durham, NC 27704, USA"},{"name":"Duke-UNC Alzheimer\u2019s Disease Research Center, 2424 Erwin Rd, Durham, NC 27705, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pranam","family":"Chatterjee","sequence":"additional","affiliation":[{"name":"Department of Bioengineering, University of Pennsylvania, 210 South 33rd Street, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudeshna","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 65 Lansdowne St., Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7347-7537","authenticated-orcid":false,"given":"Ami","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Department of Neurology, Brigham and Women\u2019s Hospital and Harvard Medical School, 60 Fenwood Rd., Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"ref_1","unstructured":"Skaria, A. 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