{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:53:01Z","timestamp":1780879981709,"version":"3.54.1"},"reference-count":11,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>\n                    Recent advances in multi-omics and spatial proteomics are reshaping our understanding of Alzheimer's disease. Guo et al.\n                    <jats:sup>\n                      <jats:xref ref-type=\"bibr\">1<\/jats:xref>\n                    <\/jats:sup>\n                    applied integrative multi-omics to stratify mild cognitive impairment into biologically distinct subtypes with divergent progression trajectories: one metabolically impaired and slow-progressing, the other immune-activated and rapidly declining. Current techniques such as STC-DESI, LCM-MS, and machine learning enhance regional proteomic resolution, supporting biomarker discovery and spatially targeted interventions. This work exemplifies a broader shift toward precision medicine and a systems-level molecular framework in neurodegenerative disease research.\n                  <\/jats:p>","DOI":"10.1177\/13872877251387169","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T17:24:26Z","timestamp":1760721866000},"page":"1514-1516","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["A molecular renaissance in Alzheimer's disease research: The rise of systems biology and spatial omics"],"prefix":"10.1177","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9281-9202","authenticated-orcid":false,"given":"L Monserrat","family":"Perez-Navarro","sequence":"first","affiliation":[{"name":"Servicio de Nefrolog\u00eda, Hospital General de M\u00e9xico Dr Eduardo Liceaga, Mexico City, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0966-8766","authenticated-orcid":false,"given":"Juan Carlos","family":"Lopez-Alvarenga","sequence":"additional","affiliation":[{"name":"Division of Population Health &amp; Biostatistics, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/13872877251365210"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.3389\/fbinf.2024.1390607"},{"key":"e_1_3_3_4_2","article-title":"AD-GCN: a novel graph convolutional network integrating multi-omics data for enhanced Alzheimer's disease diagnosis","volume":"20","author":"Li Z","year":"2025","unstructured":"Li Z, Li Q, Li X, et al. AD-GCN: a novel graph convolutional network integrating multi-omics data for enhanced Alzheimer's disease diagnosis. 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