Subjects

Abstract

Immune dysfunction is commonly associated with several neurological and mental disorders. Although the mechanisms by which peripheral immunity may influence neuronal function are largely unknown, recent findings implicate meningeal immunity influencing behaviour, such as spatial learning and memory1. Here we show that meningeal immunity is also critical for social behaviour; mice deficient in adaptive immunity exhibit social deficits and hyper-connectivity of fronto-cortical brain regions. Associations between rodent transcriptomes from brain and cellular transcriptomes in response to T-cell-derived cytokines suggest a strong interaction between social behaviour and interferon-γ (IFN-γ)-driven responses. Concordantly, we demonstrate that inhibitory neurons respond to IFN-γ and increase GABAergic (γ-aminobutyric-acid) currents in projection neurons, suggesting that IFN-γ is a molecular link between meningeal immunity and neural circuits recruited for social behaviour. Meta-analysis of the transcriptomes of a range of organisms reveals that rodents, fish, and flies elevate IFN-γ/JAK-STAT-dependent gene signatures in a social context, suggesting that the IFN-γ signalling pathway could mediate a co-evolutionary link between social/aggregation behaviour and an efficient anti-pathogen response. This study implicates adaptive immune dysfunction, in particular IFN-γ, in disorders characterized by social dysfunction and suggests a co-evolutionary link between social behaviour and an anti-pathogen immune response driven by IFN-γ signalling.

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Accessions

Primary accessions

Gene Expression Omnibus

Data deposits

RNA-seq data have been deposited in the Gene Expression Omnibus under accession number GSE81783.

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Acknowledgements

This work was supported by grants from the National Institutes of Health (AG034113 and NS081026 to J.K.), (T32-AI007496 to A.J.F.), and the Hartwell Foundation (to A.J.F.). We thank all the members of the Center for Brain Immunology and Glia (BIG) for their comments during numerous discussions of this manuscript. We also thank J. Roy for his expertise in MRI, B. Tomlin and N. Al Hamadani for animal care, as well as S. Rich, S. Onengut-Gumuscu, and E. Farber for sequencing the cDNA library.

Author information

Author notes

    • Vladimir Litvak
    •  & Jonathan Kipnis

    These authors jointly supervised this work.

Affiliations

  1. Center for Brain Immunology and Glia, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Anthony J. Filiano
    • , Rachel L. Marsh
    • , Wendy Baker
    • , Igor Smirnov
    • , Christopher C. Overall
    • , Sachin P. Gadani
    • , Kevin S. Lee
    •  & Jonathan Kipnis
  2. Department of Neuroscience, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Anthony J. Filiano
    • , Rachel L. Marsh
    • , Wendy Baker
    • , Igor Smirnov
    • , Christopher C. Overall
    • , Sachin P. Gadani
    • , Kevin S. Lee
    •  & Jonathan Kipnis
  3. Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA

    • Yang Xu
    • , Sayeda Najamussahar Peerzade
    •  & Vladimir Litvak
  4. Department of Radiology and Medical Imaging, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Nicholas J. Tustison
  5. Neuroscience Graduate Program, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Sachin P. Gadani
    • , Kevin S. Lee
    • , Michael M. Scott
    • , Mark P. Beenhakker
    •  & Jonathan Kipnis
  6. Medical Scientist Training Program, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Sachin P. Gadani
    •  & Jonathan Kipnis
  7. Department of Public Health Sciences, School of Medicine University of Virginia, Charlottesville, Virginia 22908, USA

    • Stephen D. Turner
  8. Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA

    • Zhiping Weng
    •  & Hao Chen
  9. Department of Neurosurgery, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Kevin S. Lee
  10. Department of Pharmacology, School of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA

    • Michael M. Scott
    •  & Mark P. Beenhakker

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Contributions

A.J.F. and J.K. designed and performed experiments and wrote the manuscript. Y.X. and V.L. provided intellectual contributions and analysed all transcriptome data. S.D.T., Z.W., S.N.P., and H.C. analysed transcriptome data. N.T. and C.C.O. analysed BOLD data. R.L.M., W.B., I.S., S.P.G., M.M.S. and M.P.B. provided intellectual contributions and assisted with experimental procedures. M.P.B. performed all electrophysiological experiments. K.S.L. critically reviewed the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Anthony J. Filiano or Vladimir Litvak or Jonathan Kipnis.

Reviewer Information Nature thanks M. Kano, L. Steinman and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    R values for ROIs analyzed by rsfMRI. This table contains the raw data of all R-values analyzed from BOLD sequences.

  2. 2.

    Supplementary Table 2

    Custom gene sets. This table shows the list of custom gene sets signatures used to generate the circus plot. These signatures were derived from indicated publicly available datasets.

  3. 3.

    Supplementary Table 3

    This table shows metatranscriptome analysis output for Circos plot generation. Pairwise connectivity between transcriptomes was determined by GSEA analysis. Connectivity is determined by GSEA statistical scores of NES > 1.5 and Nominal P-value < 0.05.

  4. 4.

    Supplementary Table 4

    IFN-ᵞ and JAK/STAT custom gene set signatures. Shown is the list of custom gene sets of IFN-ᵞ and JAK/STAT signatures derived from indicated publicly available database.

  5. 5.

    Supplementary Table 5

    IFN-ᵞ and JAK/STAT signature genes up-regulated in brain transcriptomes. Shown are IFNg and JAK/STAT signature genes that are up-regulated in brain transcriptomes of mice, rats, drosophila flies and zebrafish derived from indicated public available datasets.

  6. 6.

    Supplementary Table 6

    GSEA output of transcriptional signatures enriched in the prefrontal cortex transcriptomes of group-housed mice. Shown are the statistical scores of the enrichment of Molecular Signature Database C2 version 4.0 gene sets in the prefrontal cortex transcriptome of group-housed mice. A line showing the over-representation of IFN-ᵞ transcriptional signature in the prefrontal cortex transcriptome of group-housed mice is highlighted in grey.

  7. 7.

    Supplementary Table 7

    Over-representation of IFN-ᵞ and JAK/STAT transcriptional signatures in the head transcriptomes of D. rerio and D. melanogaster. Shown is the summary of GSEA output that indicates the statistical scores of the enrichment of IFN-ᵞ and JAK/STAT transcriptional signature genes in the head transcriptome of D. rerio and D. melanogaster derived from indicated publicly available datasets.

  8. 8.

    Supplementary Table 8

    Values for statistical analysis. Detailed statistical information is provided including >Ns, F-values, degrees of freedom, and P values.

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https://doi.org/10.1038/nature18626

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