TY - JOUR
T1 - Gene expression signatures characterized by longitudinal stability and interindividual variability delineate baseline phenotypic groups with distinct responses to immune stimulation
AU - Scheid, Adam D.
AU - Van Keulen, Virginia P.
AU - Felts, Sara J.
AU - Neier, Steven C.
AU - Middha, Sumit
AU - Nair, Asha A.
AU - Techentin, Robert W.
AU - Gilbert, Barry K.
AU - Jen, Jin
AU - Neuhauser, Claudia
AU - Zhang, Yuji
AU - Pease, Larry R.
N1 - Funding Information:
This work was supported by the Mayo Clinic Center for Individualized Medicine, the Mayo Clinic Cancer Center Cancer Immunology and Immunotherapy Program, Merck & Co., Inc., Kenilworth, NJ, and National Institutes of Health Training Grant T32 AI07425.
Publisher Copyright:
© 2018 by The American Association of Immunologists, Inc. All rights reserved.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - 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 phenotypedefining 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.
AB - 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 phenotypedefining 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.
UR - http://www.scopus.com/inward/record.url?scp=85044739540&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044739540&partnerID=8YFLogxK
U2 - 10.4049/jimmunol.1701099
DO - 10.4049/jimmunol.1701099
M3 - Article
C2 - 29352003
AN - SCOPUS:85044739540
SN - 0022-1767
VL - 200
SP - 1917
EP - 1928
JO - Journal of Immunology
JF - Journal of Immunology
IS - 5
ER -