{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T06:29:44Z","timestamp":1773210584655,"version":"3.50.1"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T00:00:00Z","timestamp":1773100800000},"content-version":"vor","delay-in-days":9,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Alzheimer\u2019s disease involves complex cellular alterations, yet current methods analyze cell states, signaling, and genetic risk in isolation, preventing systems-level understanding.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed an integrative framework combining quasi-binomial compositional analysis, scDemon [1], LIANA [2], scFates [3], and scDRS [4], applied to 12 integrated snRNA-seq datasets from human entorhinal and prefrontal cortex.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Analysis revealed coordinated cellular alterations with inhibitory neuron depletion and microglia expansion. scDemon identified novel microglial states including a filopedia dynamics module (MYO10\/PARVG). Trajectory analysis showed progression from homeostatic (P2RY12-high) to proliferative (APOE, AXL-high) and senescent (CDKN1A-high) states. LIANA implicated RTN4-LINGO1 signaling in impaired neuronal repair, while scDRS mapped disease genetic risk to microglial cells.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our framework links cellular pathophysiology to genetic etiology, providing a blueprint for identifying therapeutic targets in neurodegenerative disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>References<\/jats:title>\n                    <jats:p>1. Mathys H, Boix CA, Akay LA et al. \u2018Single-cell multiregion dissection of Alzheimer\u2019s disease.\u2019 Nature 2024;632:858\u2013868.<\/jats:p>\n                    <jats:p>2. Dimitrov D, Sch\u00e4fer PSL, Farr E et al. \u2018LIANA+ provides an all-in-one framework for cell\u2013cell communication inference.\u2019 Nature Cell Biology 2024;26:1613\u20131622.<\/jats:p>\n                    <jats:p>3. Faure L, Soldatov R, Kharchenko PV et al. \u2018scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data.\u2019 Bioinformatics 2022;39.<\/jats:p>\n                    <jats:p>4. Zhang MJ, Hou K, Dey KK et al. \u2018Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data.\u2019 Nature Genetics 2022;54:1572\u20131580.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bib\/bbag057","type":"journal-article","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T12:47:07Z","timestamp":1772023627000},"page":"i3-i3","source":"Crossref","is-referenced-by-count":0,"title":["An integrative multi-omics framework for decoding microglial ecosystems in Alzheimer's disease"],"prefix":"10.1093","volume":"27","author":[{"given":"Chuyun","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of BMS, City University of HK , HK SAR ,","place":["China"]}]},{"given":"Kei Hang Katie","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of BMS, City University of HK , HK SAR ,","place":["China"]},{"name":"Department of EE, City University of HK , HK SAR ,","place":["China"]},{"name":"Dept of Epi & Biostat, Ctr for Global Cardiometabolic Hlth & Nutr , UCI ,","place":["United States"]}]}],"member":"286","published-online":{"date-parts":[[2026,3,10]]},"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/27\/2\/i3\/67283579\/bbag057.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/27\/2\/i3\/67283579\/bbag057.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T08:42:36Z","timestamp":1773132156000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/27\/2\/i3\/8512614"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,1]]},"references-count":0,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbag057","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,3]]},"published":{"date-parts":[[2026,3,1]]}}}