<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Peterson LS</submitter><funding>Doris Duke Charitable Foundation</funding><funding>NIGMS NIH HHS</funding><pagination>714090</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8420969</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12</volume><pubmed_abstract>Although most causes of death and morbidity in premature infants are related to immune maladaptation, the premature immune system remains poorly understood. We provide a comprehensive single-cell depiction of the neonatal immune system at birth across the spectrum of viable gestational age (GA), ranging from 25 weeks to term. A mass cytometry immunoassay interrogated all major immune cell subsets, including signaling activity and responsiveness to stimulation. An elastic net model described the relationship between GA and immunome (R=0.85, p=8.75e-14), and unsupervised clustering highlighted previously unrecognized GA-dependent immune dynamics, including decreasing basal MAP-kinase/NFκB signaling in antigen presenting cells; increasing responsiveness of cytotoxic lymphocytes to interferon-α; and decreasing frequency of regulatory and invariant T cells, including NKT-like cells and CD8&lt;sup>+&lt;/sup>CD161&lt;sup>+&lt;/sup> T cells. Knowledge gained from the analysis of the neonatal immune landscape across GA provides a mechanistic framework to understand the unique susceptibility of preterm infants to both hyper-inflammatory diseases and infections.</pubmed_abstract><journal>Frontiers in immunology</journal><pubmed_title>Single-Cell Analysis of the Neonatal Immune System Across the Gestational Age Continuum.</pubmed_title><pmcid>PMC8420969</pmcid><funding_grant_id>2018100</funding_grant_id><funding_grant_id>R35 GM137936</funding_grant_id><funding_grant_id>R35 GM138353</funding_grant_id><pubmed_authors>Feyaerts D</pubmed_authors><pubmed_authors>Houghteling P</pubmed_authors><pubmed_authors>Tsai AS</pubmed_authors><pubmed_authors>Stelzer IA</pubmed_authors><pubmed_authors>Tsai ES</pubmed_authors><pubmed_authors>Han X</pubmed_authors><pubmed_authors>Aghaeepour N</pubmed_authors><pubmed_authors>Ando K</pubmed_authors><pubmed_authors>Lewis DB</pubmed_authors><pubmed_authors>Angst MS</pubmed_authors><pubmed_authors>Gaudilliere B</pubmed_authors><pubmed_authors>Reiss JD</pubmed_authors><pubmed_authors>Harbert E</pubmed_authors><pubmed_authors>Ringle M</pubmed_authors><pubmed_authors>Winn VD</pubmed_authors><pubmed_authors>Hedou J</pubmed_authors><pubmed_authors>Adusumelli Y</pubmed_authors><pubmed_authors>Peterson LS</pubmed_authors><pubmed_authors>Ganio EA</pubmed_authors><pubmed_authors>Stevenson DK</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-Cell Analysis of the Neonatal Immune System Across the Gestational Age Continuum.</name><description>Although most causes of death and morbidity in premature infants are related to immune maladaptation, the premature immune system remains poorly understood. We provide a comprehensive single-cell depiction of the neonatal immune system at birth across the spectrum of viable gestational age (GA), ranging from 25 weeks to term. A mass cytometry immunoassay interrogated all major immune cell subsets, including signaling activity and responsiveness to stimulation. An elastic net model described the relationship between GA and immunome (R=0.85, p=8.75e-14), and unsupervised clustering highlighted previously unrecognized GA-dependent immune dynamics, including decreasing basal MAP-kinase/NFκB signaling in antigen presenting cells; increasing responsiveness of cytotoxic lymphocytes to interferon-α; and decreasing frequency of regulatory and invariant T cells, including NKT-like cells and CD8&lt;sup>+&lt;/sup>CD161&lt;sup>+&lt;/sup> T cells. Knowledge gained from the analysis of the neonatal immune landscape across GA provides a mechanistic framework to understand the unique susceptibility of preterm infants to both hyper-inflammatory diseases and infections.</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021</publication><modification>2026-03-12T23:30:04.178Z</modification><creation>2025-08-12T03:04:48.97Z</creation></dates><accession>S-EPMC8420969</accession><cross_references><pubmed>34497610</pubmed><doi>10.3389/fimmu.2021.714090</doi></cross_references></HashMap>