Literature DB >> 29352003

Gene Expression Signatures Characterized by Longitudinal Stability and Interindividual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation.

Adam D Scheid1, Virginia P Van Keulen2, Sara J Felts2, Steven C Neier1, Sumit Middha3, Asha A Nair3, Robert W Techentin4, Barry K Gilbert4, Jin Jen5, Claudia Neuhauser6, Yuji Zhang3, Larry R Pease7,2.   

Abstract

Human immunity exhibits remarkable heterogeneity among individuals, which engenders variable responses to immune perturbations in human populations. Population studies reveal that, in addition to interindividual heterogeneity, systemic immune signatures display longitudinal stability within individuals, and these signatures may reliably dictate how given individuals respond to immune perturbations. We hypothesize that analyzing relationships among these signatures at the population level may uncover baseline immune phenotypes that correspond with response outcomes to immune stimuli. To test this, we quantified global gene expression in peripheral blood CD4+ cells from healthy individuals at baseline and following CD3/CD28 stimulation at two time points 1 mo apart. Systemic CD4+ cell baseline and poststimulation molecular immune response signatures (MIRS) were defined by identifying genes expressed at levels that were stable between time points within individuals and differential among individuals in each state. Iterative differential gene expression analyses between all possible phenotypic groupings of at least three individuals using the baseline and stimulated MIRS gene sets revealed shared baseline and response phenotypic groupings, indicating the baseline MIRS contained determinants of immune responsiveness. Furthermore, significant numbers of shared phenotype-defining sets of determinants were identified in baseline data across independent healthy cohorts. Combining the cohorts and repeating the analyses resulted in identification of over 6000 baseline immune phenotypic groups, implying that the MIRS concept may be useful in many immune perturbation contexts. These findings demonstrate that patterns in complex gene expression variability can be used to define immune phenotypes and discover determinants of immune responsiveness.
Copyright © 2018 by The American Association of Immunologists, Inc.

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Year:  2018        PMID: 29352003      PMCID: PMC5821558          DOI: 10.4049/jimmunol.1701099

Source DB:  PubMed          Journal:  J Immunol        ISSN: 0022-1767            Impact factor:   5.422


  49 in total

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Authors:  Kathleen Jentsch-Ullrich; Michael Koenigsmann; Martin Mohren; Astrid Franke
Journal:  Clin Immunol       Date:  2005-08       Impact factor: 3.969

2.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

3.  Variation in the human immune system is largely driven by non-heritable influences.

Authors:  Petter Brodin; Vladimir Jojic; Tianxiang Gao; Sanchita Bhattacharya; Cesar J Lopez Angel; David Furman; Shai Shen-Orr; Cornelia L Dekker; Gary E Swan; Atul J Butte; Holden T Maecker; Mark M Davis
Journal:  Cell       Date:  2015-01-15       Impact factor: 41.582

Review 4.  Human immune system variation.

Authors:  Petter Brodin; Mark M Davis
Journal:  Nat Rev Immunol       Date:  2016-12-05       Impact factor: 53.106

5.  Global analyses of human immune variation reveal baseline predictors of postvaccination responses.

Authors:  John S Tsang; Pamela L Schwartzberg; Yuri Kotliarov; Angelique Biancotto; Zhi Xie; Ronald N Germain; Ena Wang; Matthew J Olnes; Manikandan Narayanan; Hana Golding; Susan Moir; Howard B Dickler; Shira Perl; Foo Cheung
Journal:  Cell       Date:  2014-04-10       Impact factor: 41.582

6.  High serum IFN-alpha activity is a heritable risk factor for systemic lupus erythematosus.

Authors:  T B Niewold; J Hua; T J A Lehman; J B Harley; M K Crow
Journal:  Genes Immun       Date:  2007-06-21       Impact factor: 2.676

7.  Distribution and compartmentalization of human circulating and tissue-resident memory T cell subsets.

Authors:  Taheri Sathaliyawala; Masaru Kubota; Naomi Yudanin; Damian Turner; Philip Camp; Joseph J C Thome; Kara L Bickham; Harvey Lerner; Michael Goldstein; Megan Sykes; Tomoaki Kato; Donna L Farber
Journal:  Immunity       Date:  2012-12-20       Impact factor: 31.745

8.  The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression.

Authors:  Thomas Derrien; Rory Johnson; Giovanni Bussotti; Andrea Tanzer; Sarah Djebali; Hagen Tilgner; Gregory Guernec; David Martin; Angelika Merkel; David G Knowles; Julien Lagarde; Lavanya Veeravalli; Xiaoan Ruan; Yijun Ruan; Timo Lassmann; Piero Carninci; James B Brown; Leonard Lipovich; Jose M Gonzalez; Mark Thomas; Carrie A Davis; Ramin Shiekhattar; Thomas R Gingeras; Tim J Hubbard; Cedric Notredame; Jennifer Harrow; Roderic Guigó
Journal:  Genome Res       Date:  2012-09       Impact factor: 9.043

9.  Widespread seasonal gene expression reveals annual differences in human immunity and physiology.

Authors:  Xaquin Castro Dopico; Marina Evangelou; Ricardo C Ferreira; Hui Guo; Marcin L Pekalski; Deborah J Smyth; Nicholas Cooper; Oliver S Burren; Anthony J Fulford; Branwen J Hennig; Andrew M Prentice; Anette-G Ziegler; Ezio Bonifacio; Chris Wallace; John A Todd
Journal:  Nat Commun       Date:  2015-05-12       Impact factor: 14.919

10.  The cellular composition of the human immune system is shaped by age and cohabitation.

Authors:  Edward J Carr; James Dooley; Michelle A Linterman; Adrian Liston; Josselyn E Garcia-Perez; Vasiliki Lagou; James C Lee; Carine Wouters; Isabelle Meyts; An Goris; Guy Boeckxstaens
Journal:  Nat Immunol       Date:  2016-02-15       Impact factor: 25.606

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  4 in total

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Journal:  Genes Immun       Date:  2020-10-09       Impact factor: 2.676

2.  Meta-Analysis of Immune Induced Gene Expression Changes in Diverse Drosophila melanogaster Innate Immune Responses.

Authors:  Ashley L Waring; Joshua Hill; Brooke M Allen; Nicholas M Bretz; Nguyen Le; Pooja Kr; Dakota Fuss; Nathan T Mortimer
Journal:  Insects       Date:  2022-05-23       Impact factor: 3.139

3.  Stochastic changes in gene expression promote chaotic dysregulation of homeostasis in clonal breast tumors.

Authors:  Sara J Felts; Xiaojia Tang; Benjamin Willett; Virginia P Van Keulen; Michael J Hansen; Krishna R Kalari; Larry R Pease
Journal:  Commun Biol       Date:  2019-06-14

Review 4.  Patient-Derived Xenografts as an Innovative Surrogate Tumor Model for the Investigation of Health Disparities in Triple Negative Breast Cancer.

Authors:  Margarite D Matossian; Alexandra A Giardina; Maryl K Wright; Steven Elliott; Michelle M Loch; Khoa Nguyen; Arnold H Zea; Frank H Lau; Krzysztof Moroz; Adam I Riker; Steven D Jones; Elizabeth C Martin; Bruce A Bunnell; Lucio Miele; Bridgette M Collins-Burow; Matthew E Burow
Journal:  Womens Health Rep (New Rochelle)       Date:  2020-09-24
  4 in total

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