{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T17:52:34Z","timestamp":1791913954573,"version":"4.3.4"},"reference-count":48,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Host restriction factors can block HIV at multiple stages, but they are often studied as individual genes or within a single molecular layer. I performed an evidence-structured computational reanalysis of three independent public datasets to determine how the human HIV restrictome varies across clinical states, immune-cell compartments, and protein responses. The analysis used bulk monocyte RNA sequencing (GSE157198), PBMC single-cell\/CITE-seq data (GSE256089), and primary CD4 T-cell proteomics (PXD012263) within a prespecified restrictome-immunometabolism framework. In GSE157198, ART-naive monocytes had higher core-restrictome activity than healthy controls (difference\u2009=\u20091.154, p\u2009=\u20090.000746), and core scores were strongly correlated with interferon\/innate-sensing scores (Spearman r\u2009=\u20090.800, p\u2009=\u20097.47\u2009\u00d7\u200910^-11). Core-lipid\/cholesterol correlation was weaker and was not independent of interferon after conditional analysis. In GSE256089, participant-paired core-restrictome scores were enriched in NK cells relative to B cells, monocytes, and T cells, and matched random-gene-set analyses supported enrichment beyond background expression structure. FCGR3A monocytes also had higher participant-paired core scores than CD14 monocytes. Exploratory sensing\/death-gene analysis identified cell-type-specific expression patterns but did not establish pathway activation, pyroptosis, or apoptosis. In PXD012263, the historical q\u2009&lt;\u20090.05 proteomic selection contained 19 curated genes and retained mixed response polarity; sensitivity thresholds q\u2009&lt;\u20090.01 and q\u2009&lt;\u20090.10 selected 10 and 25 genes, respectively. Together, the results show that HIV restrictome activity varies across clinical and immune-cell contexts and is embedded within broader interferon-linked and immunometabolic states. Because the datasets are independent and not subject matched, the findings are observational and hypothesis-generating rather than causal.<\/jats:p>","DOI":"10.1371\/journal.pone.0356591","type":"journal-article","created":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T17:26:47Z","timestamp":1791912407000},"page":"e0356591","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cross-omics mapping of the human HIV restrictome across clinical states, immune-cell compartments, and protein responses"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2453-5993","authenticated-orcid":true,"given":"Reuben S.","family":"Maghembe","sequence":"first","affiliation":[{"name":"St. Francis University College of Health and Allied Sciences","place":["Ifakara, Tanzania"],"department":["Department of Microbiology and Parasitology, Faculty of Medicine"]},{"name":"AfroBiomics Co. 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