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A unified metric of human immune health.
Sparks, Rachel; Rachmaninoff, Nicholas; Lau, William W; Hirsch, Dylan C; Bansal, Neha; Martins, Andrew J; Chen, Jinguo; Liu, Candace C; Cheung, Foo; Failla, Laura E; Biancotto, Angelique; Fantoni, Giovanna; Sellers, Brian A; Chawla, Daniel G; Howe, Katherine N; Mostaghimi, Darius; Farmer, Rohit; Kotliarov, Yuri; Calvo, Katherine R; Palmer, Cindy; Daub, Janine; Foruraghi, Ladan; Kreuzburg, Samantha; Treat, Jennifer D; Urban, Amanda K; Jones, Anne; Romeo, Tina; Deuitch, Natalie T; Moura, Natalia Sampaio; Weinstein, Barbara; Moir, Susan; Ferrucci, Luigi; Barron, Karyl S; Aksentijevich, Ivona; Kleinstein, Steven H; Townsley, Danielle M; Young, Neal S; Frischmeyer-Guerrerio, Pamela A; Uzel, Gulbu; Pinto-Patarroyo, Gineth Paola; Cudrici, Cornelia D; Hoffmann, Patrycja; Stone, Deborah L; Ombrello, Amanda K; Freeman, Alexandra F; Zerbe, Christa S; Kastner, Daniel L; Holland, Steven M; Tsang, John S.
Afiliação
  • Sparks R; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Rachmaninoff N; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Lau WW; Graduate Program in Biological Sciences, University of Maryland, College Park, MD, USA.
  • Hirsch DC; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Bansal N; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Martins AJ; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Chen J; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Liu CC; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Cheung F; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Failla LE; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Biancotto A; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Fantoni G; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Sellers BA; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Chawla DG; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Howe KN; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • Mostaghimi D; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Farmer R; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
  • Kotliarov Y; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Calvo KR; NIH Center for Human Immunology, Inflammation, and Autoimmunity, NIAID, NIH, Bethesda, MD, USA.
  • Palmer C; Hematology Section, Department of Laboratory Medicine, Clinical Center, NIH, Bethesda, MD, USA.
  • Daub J; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Foruraghi L; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Kreuzburg S; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Treat JD; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Urban AK; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Jones A; Clinical Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
  • Romeo T; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Deuitch NT; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Moura NS; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Weinstein B; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Moir S; Hematology Branch, NHLBI, NIH, Bethesda, MD, USA.
  • Ferrucci L; Laboratory of Immunoregulation, NIAID, NIH, Bethesda, MD, USA.
  • Barron KS; Translational Gerontology Branch, NIA, Baltimore, MD, USA.
  • Aksentijevich I; Division of Intramural Research, NIAID, NIH, Bethesda, MD, USA.
  • Kleinstein SH; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Townsley DM; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • Young NS; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA.
  • Frischmeyer-Guerrerio PA; Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
  • Uzel G; Hematology Branch, NHLBI, NIH, Bethesda, MD, USA.
  • Pinto-Patarroyo GP; Hematology Branch, NHLBI, NIH, Bethesda, MD, USA.
  • Cudrici CD; Laboratory of Allergic Diseases, NIAID, NIH, Bethesda, MD, USA.
  • Hoffmann P; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Stone DL; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Ombrello AK; Translational Vascular Medicine Branch, NHLBI, NIH, Bethesda, MD, USA.
  • Freeman AF; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Zerbe CS; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Kastner DL; Inflammatory Disease Section, NHGRI, NIH, Bethesda, MD, USA.
  • Holland SM; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
  • Tsang JS; Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA.
Nat Med ; 2024 Jul 03.
Article em En | MEDLINE | ID: mdl-38961223
ABSTRACT
Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article