{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Olinger B"],"funding":["NIA NIH HHS"],"pubmed_abstract":["Cellular senescence increases with age and contributes to age-related declines and pathologies. We identified circulating biomarkers of senescence associated with diverse clinical traits in humans to facilitate future non-invasive assessment of individual senescence burden and efficacy testing of novel senotherapeutics. Using a novel nanoparticle-based proteomic workflow, we profiled the senescence-associated secretory phenotype (SASP) in monocytes and examined these proteins in plasma samples (N = 1060) from the Baltimore Longitudinal Study of Aging (BLSA). Machine learning models trained on monocyte SASP associated with several age-related phenotypes in a test cohort, including body fat composition, blood lipids, inflammation, and mobility-related traits, among others. Notably, a subset "],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2024.08.01.24311368"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11451660"],"repository":["biostudies-literature"],"pubmed_title":["A plasma proteomic signature links secretome of senescent monocytes to aging- and obesity-related clinical outcomes in humans."],"pmcid":["PMC11451660"],"funding_grant_id":["U54 AG079779"],"pubmed_authors":["Nyunt T","Simonsick EM","Candia J","Cui L","Gorospe M","Basisty N","Ram A","Peng Z","Walker KA","Olinger B","Banarjee R","Dey A","Daya G","Ferrucci L","Tanaka T","Tsitsipatis D"],"additional_accession":[]},"is_claimable":false,"name":"A plasma proteomic signature links secretome of senescent monocytes to aging- and obesity-related clinical outcomes in humans.","description":"Cellular senescence increases with age and contributes to age-related declines and pathologies. We identified circulating biomarkers of senescence associated with diverse clinical traits in humans to facilitate future non-invasive assessment of individual senescence burden and efficacy testing of novel senotherapeutics. Using a novel nanoparticle-based proteomic workflow, we profiled the senescence-associated secretory phenotype (SASP) in monocytes and examined these proteins in plasma samples (N = 1060) from the Baltimore Longitudinal Study of Aging (BLSA). Machine learning models trained on monocyte SASP associated with several age-related phenotypes in a test cohort, including body fat composition, blood lipids, inflammation, and mobility-related traits, among others. Notably, a subset ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Aug","modification":"2025-08-27T03:10:56.676Z","creation":"2025-04-04T20:54:47.289Z"},"accession":"S-EPMC11451660","cross_references":{"pubmed":["39371126"],"doi":["10.1101/2024.08.01.24311368"]}}