MEF2C regulates cortical inhibitory and excitatory synapses and behaviors relevant to neurodevelopmental disorders

  1. Adam J Harrington
  2. Aram Raissi
  3. Kacey Rajkovich
  4. Stefano Berto
  5. Jaswinder Kumar
  6. Gemma Molinaro
  7. Jonathan Raduazzo
  8. Yuhong Guo
  9. Kris Loerwald
  10. Genevieve Konopka
  11. Kimberly M Huber
  12. Christopher W Cowan  Is a corresponding author
  1. Medical University of South Carolina, United States
  2. Harvard Medical School, United States
  3. The University of Texas Southwestern Medical Center, United States

Abstract

Numerous genetic variants associated with MEF2C are linked to autism, intellectual disability (ID) and schizophrenia (SCZ) - a heterogeneous collection of neurodevelopmental disorders with unclear pathophysiology. MEF2C is highly expressed in developing cortical excitatory neurons, but its role in their development remains unclear. We show here that conditional embryonic deletion of Mef2c in cortical and hippocampal excitatory neurons (Emx1-lineage) produces a dramatic reduction in cortical network activity in vivo, due in part to a dramatic increase in inhibitory and a decrease in excitatory synaptic transmission. In addition, we find that MEF2C regulates E/I synapse density predominantly as a cell-autonomous, transcriptional repressor. Analysis of differential gene expression in Mef2c mutant cortex identified a significant overlap with numerous synapse- and autism-linked genes, and the Mef2c mutant mice displayed numerous behaviors reminiscent of autism, ID and SCZ, suggesting that perturbing MEF2C function in neocortex can produce autistic- and ID-like behaviors in mice.

Data availability

The following data sets were generated

Article and author information

Author details

  1. Adam J Harrington

    Department of Neuroscience, Medical University of South Carolina, Charleston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Aram Raissi

    Department of Psychiatry, Harvard Medical School, Belmont, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Kacey Rajkovich

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Stefano Berto

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jaswinder Kumar

    Department of Psychiatry, Harvard Medical School, Belmont, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Gemma Molinaro

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Jonathan Raduazzo

    Department of Psychiatry, Harvard Medical School, Belmont, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Yuhong Guo

    Department of Psychiatry, Harvard Medical School, Belmont, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Kris Loerwald

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Genevieve Konopka

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Kimberly M Huber

    Department of Neuroscience, The University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Christopher W Cowan

    Department of Neuroscience, Medical University of South Carolina, Charleston, United States
    For correspondence
    cowanc@musc.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5472-3296

Funding

Eunice Kennedy Shriver National Institute of Child Health and Human Development

  • Adam J Harrington

Simons Foundation (SFARI #206919)

  • Kimberly M Huber
  • Christopher W Cowan

National Institute on Drug Abuse

  • Christopher W Cowan

NIH Office of the Director

  • Kimberly M Huber

National Institutes of Health (F32 HD078050)

  • Adam J Harrington

National Institutes of Health (DA027664)

  • Christopher W Cowan

National Institutes of Health (HD052731)

  • Kimberly M Huber

National Institutes of Health (OD010737)

  • Christopher W Cowan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the NIH. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#2015N000178 and #2015N000160) of McLean Hospital.

Copyright

© 2016, Harrington et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Download links

Share this article

https://doi.org/10.7554/eLife.20059

Further reading

    1. Neuroscience
    Barbora Rehak Buckova, Charlotte Fraza ... Jaroslav Hlinka
    Tools and Resources

    Longitudinal neuroimaging studies offer valuable insight into brain development, ageing, and disease progression over time. However, prevailing analytical approaches rooted in our understanding of population variation are primarily tailored for cross-sectional studies. To fully leverage the potential of longitudinal neuroimaging, we need methodologies that account for the complex interplay between population variation and individual dynamics. We extend the normative modelling framework, which evaluates an individual’s position relative to population standards, to assess an individual’s longitudinal change compared to the population’s standard dynamics. Using normative models pre-trained on over 58,000 individuals, we introduce a quantitative metric termed ‘z-diff’ score, which quantifies a temporal change in individuals compared to a population standard. This approach offers advantages in flexibility in dataset size and ease of implementation. We applied this framework to a longitudinal dataset of 98 patients with early-stage schizophrenia who underwent MRI examinations shortly after diagnosis and 1 year later. Compared to cross-sectional analyses, showing global thinning of grey matter at the first visit, our method revealed a significant normalisation of grey matter thickness in the frontal lobe over time—an effect undetected by traditional longitudinal methods. Overall, our framework presents a flexible and effective methodology for analysing longitudinal neuroimaging data, providing insights into the progression of a disease that would otherwise be missed when using more traditional approaches.

    1. Neuroscience
    Lenia Amaral, Xiaosha Wang ... Ella Striem-Amit
    Research Article

    Research on brain plasticity, particularly in the context of deafness, consistently emphasizes the reorganization of the auditory cortex. But to what extent do all individuals with deafness show the same level of reorganization? To address this question, we examined the individual differences in functional connectivity (FC) from the deprived auditory cortex. Our findings demonstrate remarkable differentiation between individuals deriving from the absence of shared auditory experiences, resulting in heightened FC variability among deaf individuals, compared to more consistent FC in the hearing group. Notably, connectivity to language regions becomes more diverse across individuals with deafness. This does not stem from delayed language acquisition; it is found in deaf native signers, who are exposed to natural language since birth. However, comparing FC diversity between deaf native signers and deaf delayed signers, who were deprived of language in early development, we show that language experience also impacts individual differences, although to a more moderate extent. Overall, our research points out the intricate interplay between brain plasticity and individual differences, shedding light on the diverse ways reorganization manifests among individuals. It joins findings of increased connectivity diversity in blindness and highlights the importance of considering individual differences in personalized rehabilitation for sensory loss.