Solving Immunology?

Affiliations

¹ Departments of Surgery, Immunology, Computational and Systems Biology, Clinical and Translational Science, and Communication Science and Disorders, and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
² Division of Allergy, Immunology and Transplantation, National Institute of Allergy and Infectious Diseases National Institutes of Health, 5601 Fishers Lane, Room 7A78, MSC 9828, Rockville, MD 20852, USA; Current address: Molecular Transducers of Physical Activities (MoTrPAC) Division of Diabetes, Endocrinology, & Metabolic Diseases (DEM), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), 6707 Democracy Blvd, RM 6074, Bethesda, MD 20817, USA.
³ Department of Chemical Engineering & Materials Science, Department of Molecular Biology & Biochemistry, University of California, Irvine, CA 92697, USA.
⁴ Biocomplexity Institute of Virginia Tech, 1015 Life Sciences Circle, Blacksburg, VA 24060, USA.
⁵ Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA.
⁶ Department of Mathematics, Institute for Quantitative Biology, and Cancer Institute of NJ, Rutgers University, New Brunswick, NJ 08903, USA.
⁷ State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry of Chinese Academy of Sciences, Changchun 130022, China; Department of Chemistry and Physics, Stony Brook University, Stony Brook, NY 11794-3400, USA.
⁸ Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, Trans-NIH Center for Human Immunology, National Institutes of Health, Bethesda, MD 20892, USA.
⁹ Departments of Mathematics and Electrical Engineering & Computer Science, National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN 37996, USA.
¹⁰ Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
¹¹ Institute for Computational Health Sciences, University of California, San Francisco, Mission Hall 550 16th Street, 4th Floor, Box 0110, San Francisco, CA 94158-2549, USA.
¹² Department of Allergy and Infectious Diseases, University of Washington, Seattle, WA 98109, USA.
¹³ Center on Social Dynamics & Policy, Economic Studies Program, The Brookings Institution, Washington DC 20036, USA.
¹⁴ Center for Advanced Research on Diagnostic Assays, Immunology Institute, Friedman Brain Institute, and Departments of Neurology, Neuroscience, Pharmacology, and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: stuart.sealfon@mssm.edu.

PMID: 27986392
PMCID: PMC5695553
DOI: 10.1016/j.it.2016.11.006

Review

Solving Immunology?

Yoram Vodovotz et al. Trends Immunol. 2017 Feb.

. 2017 Feb;38(2):116-127.

doi: 10.1016/j.it.2016.11.006. Epub 2016 Dec 13.

Authors

Affiliations

¹ Departments of Surgery, Immunology, Computational and Systems Biology, Clinical and Translational Science, and Communication Science and Disorders, and McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
² Division of Allergy, Immunology and Transplantation, National Institute of Allergy and Infectious Diseases National Institutes of Health, 5601 Fishers Lane, Room 7A78, MSC 9828, Rockville, MD 20852, USA; Current address: Molecular Transducers of Physical Activities (MoTrPAC) Division of Diabetes, Endocrinology, & Metabolic Diseases (DEM), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), 6707 Democracy Blvd, RM 6074, Bethesda, MD 20817, USA.
³ Department of Chemical Engineering & Materials Science, Department of Molecular Biology & Biochemistry, University of California, Irvine, CA 92697, USA.
⁴ Biocomplexity Institute of Virginia Tech, 1015 Life Sciences Circle, Blacksburg, VA 24060, USA.
⁵ Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA.
⁶ Department of Mathematics, Institute for Quantitative Biology, and Cancer Institute of NJ, Rutgers University, New Brunswick, NJ 08903, USA.
⁷ State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry of Chinese Academy of Sciences, Changchun 130022, China; Department of Chemistry and Physics, Stony Brook University, Stony Brook, NY 11794-3400, USA.
⁸ Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, Trans-NIH Center for Human Immunology, National Institutes of Health, Bethesda, MD 20892, USA.
⁹ Departments of Mathematics and Electrical Engineering & Computer Science, National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN 37996, USA.
¹⁰ Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
¹¹ Institute for Computational Health Sciences, University of California, San Francisco, Mission Hall 550 16th Street, 4th Floor, Box 0110, San Francisco, CA 94158-2549, USA.
¹² Department of Allergy and Infectious Diseases, University of Washington, Seattle, WA 98109, USA.
¹³ Center on Social Dynamics & Policy, Economic Studies Program, The Brookings Institution, Washington DC 20036, USA.
¹⁴ Center for Advanced Research on Diagnostic Assays, Immunology Institute, Friedman Brain Institute, and Departments of Neurology, Neuroscience, Pharmacology, and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: stuart.sealfon@mssm.edu.

PMID: 27986392
PMCID: PMC5695553
DOI: 10.1016/j.it.2016.11.006

Abstract

Emergent responses of the immune system result from the integration of molecular and cellular networks over time and across multiple organs. High-content and high-throughput analysis technologies, concomitantly with data-driven and mechanistic modeling, hold promise for the systematic interrogation of these complex pathways. However, connecting genetic variation and molecular mechanisms to individual phenotypes and health outcomes has proven elusive. Gaps remain in data, and disagreements persist about the value of mechanistic modeling for immunology. Here, we present the perspectives that emerged from the National Institute of Allergy and Infectious Disease (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regarding the potential synergy of high-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disease and to accelerate the translation of these insights into therapies.

Keywords: autoimmune disease; conference; mathematical modeling; personalized medicine; translation.

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Figures

**Figure 1. Different Perspectives of Immunology Researchers**
Generally, immunologists seek to understand the role of immune system in health and disease, focusing on how genetic, epigenetic, and environmental variations affect immune function and influence individual disease expression and response to treatment. Data-driven modelers seek to map predictive relationships between multiple data variables and disease in individuals, reconstructing and examining how molecular and celluar networks change in health and disease. Mechanistic modelers seek to define how a defined set of molecular and cellular interactions can lead to complex outcomes in health and immunological disease. This latter group utilizes abstractions of biological mechanisms encoded into computational models, and seek to define how diverse, complex health and disease phenotypes emerge from a defined set of immune interactions, set in motion by defined initial biological conditions.

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References

1. Genomes Project C, et al. A global reference for human genetic variation. Nature. 2015;526(7571):68–74. - PMC - PubMed
1. Lek M, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–291. - PMC - PubMed
1. Farh KK, et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature. 2015;518(7539):337–343. - PMC - PubMed
1. Germain RN, et al. Systems biology in immunology: a computational modeling perspective. Annu Rev Immunol. 2011;29:527–585. - PMC - PubMed
1. Mayya V, Dustin ML, et al. What Scales the T Cell Response? Trends Immunol. 2016;37(8):513–522. - PubMed

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Solving Immunology?

Affiliations

Solving Immunology?

Authors

Affiliations

Abstract

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical