Article

Gamma frequency entrainment attenuates amyloid load and modifies microglia

Received:
Accepted:
Published online:

Abstract

Changes in gamma oscillations (20–50 Hz) have been observed in several neurological disorders. However, the relationship between gamma oscillations and cellular pathologies is unclear. Here we show reduced, behaviourally driven gamma oscillations before the onset of plaque formation or cognitive decline in a mouse model of Alzheimer’s disease. Optogenetically driving fast-spiking parvalbumin-positive (FS-PV)-interneurons at gamma (40 Hz), but not other frequencies, reduces levels of amyloid-β (Aβ)1–40 and Aβ 1–42 isoforms. Gene expression profiling revealed induction of genes associated with morphological transformation of microglia, and histological analysis confirmed increased microglia co-localization with Aβ. Subsequently, we designed a non-invasive 40 Hz light-flickering regime that reduced Aβ1–40 and Aβ1–42 levels in the visual cortex of pre-depositing mice and mitigated plaque load in aged, depositing mice. Our findings uncover a previously unappreciated function of gamma rhythms in recruiting both neuronal and glial responses to attenuate Alzheimer’s-disease-associated pathology.

  • Subscribe to Nature for full access:

    $199

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Accessions

Primary accessions

Gene Expression Omnibus

Data deposits

RNA-seq data available at Gene Expression Omnibus under accession number GSE77471. Other data are publicly available upon request.

References

  1. 1.

    , & Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nature Rev. Neurosci. 8, 45–56 (2007)

  2. 2.

    , & The gamma cycle. Trends Neurosci. 30, 309–316 (2007)

  3. 3.

    et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–667 (2009)

  4. 4.

    et al. Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer’s disease. Neuron 55, 697–711 (2007)

  5. 5.

    et al. Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell 149, 708–721 (2012)

  6. 6.

    et al. Neuronal activity regulates the regional vulnerability to amyloid-β deposition. Nature Neurosci. 14, 750–756 (2011)

  7. 7.

    et al. The role of APP processing and trafficking pathways in the formation of amyloid beta-protein. Ann. NY Acad. Sci. 777, 57–64 (1996)

  8. 8.

    et al. Generalized synchronization of MEG recordings in Alzheimer’s disease: evidence for involvement of the gamma band. J. Clin. Neurophysiol. 19, 562–574 (2002)

  9. 9.

    et al. Apolipoprotein E4 causes age-dependent disruption of slow gamma oscillations during hippocampal sharp-wave ripples. Neuron 90, 740–751 (2016)

  10. 10.

    et al. Intraneuronal β-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J. Neurosci. 26, 10129–10140 (2006)

  11. 11.

    et al. Frequency of gamma oscillations routes flow of information in the hippocampus. Nature 462, 353–357 (2009)

  12. 12.

    Rhythms of the Brain (Oxford Univ. Press, 2006)

  13. 13.

    et al. Hippocampal network patterns of activity in the mouse. Neuroscience 116, 201–211 (2003)

  14. 14.

    , & Transient slow gamma synchrony underlies hippocampal memory replay. Neuron 75, 700–713 (2012)

  15. 15.

    & Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature 440, 680–683 (2006)

  16. 16.

    , & Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval. Nature Neurosci. 14, 147–153 (2011)

  17. 17.

    et al. The neuroendocrine protein 7B2 suppresses the aggregation of neurodegenerative disease-related proteins. J. Biol. Chem. 288, 1114–1124 (2013)

  18. 18.

    et al. Activity-induced convergence of APP and BACE-1 in acidic microdomains via an endocytosis-dependent pathway. Neuron 79, 447–460 (2013)

  19. 19.

    et al. Endocytic pathway abnormalities precede amyloid beta deposition in sporadic Alzheimer’s disease and Down syndrome: differential effects of APOE genotype and presenilin mutations. Am. J. Pathol. 157, 277–286 (2000)

  20. 20.

    et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature 518, 365–369 (2015)

  21. 21.

    & Colony-stimulating factor-1 in immunity and inflammation. Curr. Opin. Immunol. 18, 39–48 (2006)

  22. 22.

    et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer’s disease model. Cell 160, 1061–1071 (2015)

  23. 23.

    , , & Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989)

  24. 24.

    et al. Coherent oscillations: a mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biol. Cybern. 60, 121–130 (1988)

  25. 25.

    & Sex differences in the response to GABA antagonists depend on the route of drug administration. Exp. Brain Res. 115, 187–190 (1997)

  26. 26.

    et al. Mutant presenilins specifically elevate the levels of the 42 residue β-amyloid peptide in vivo: evidence for augmentation of a 42-specific γ secretase. Hum. Mol. Genet. 13, 159–170 (2004)

  27. 27.

    et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013)

  28. 28.

    et al. Synapse loss and microglial activation precede tangles in a P301S tauopathy mouse model. Neuron 53, 337–351 (2007)

  29. 29.

    , & The road to restoring neural circuits for the treatment of Alzheimer’s disease. Nature 539, 187–196 (2016)

  30. 30.

    , , & Intracellular dynamics of hippocampal place cells during virtual navigation. Nature 461, 941–946 (2009)

  31. 31.

    & Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system. Neuron 84, 442–456 (2014)

  32. 32.

    , et al. Spike sorting for large, dense electrode arrays. Nature Neurosci. 19, 634–642 (2016)

  33. 33.

    Theta oscillations in the hippocampus. Neuron 33, 325–340 (2002)

  34. 34.

    et al. Multisensory control of hippocampal spatiotemporal selectivity. Science 340, 1342–1346 (2013)

  35. 35.

    et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014)

  36. 36.

    et al. Mutant Huntingtin promotes autonomous microglia activation via myeloid lineage-determining factors. Nature Neurosci. 17, 513–521 (2014)

  37. 37.

    et al. Host microbiota constantly control maturation and function of microglia in the CNS. Nature Neurosci. 18, 965–977 (2015)

  38. 38.

    et al. A neurodegeneration-specific gene-expression signature of acutely isolated microglia from an amyotrophic lateral sclerosis mouse model. Cell Reports 4, 385–401 (2013)

  39. 39.

    et al. Environment drives selection and function of enhancers controlling tissue-specific macrophage identities. Cell 159, 1327–1340 (2014)

  40. 40.

    et al. Cell-intrinsic lysosomal lipolysis is essential for alternative activation of macrophages. Nature Immunol. 15, 846–855 (2014)

  41. 41.

    et al. Tet3 regulates synaptic transmission and homeostatic plasticity via DNA oxidation and repair. Nature Neurosci. 18, 836–843 (2015)

Download references

Acknowledgements

We are grateful to S. Tonegawa and D. Roy for APP/PS1 mice, and E. Demmons, W. Raja, E. Wu, and B. Arkhurst and the Boyden laboratory for technical assistance. We thank members of the Tsai and Boyden laboratories, C. Moore, C. Deister, D. Rei, J. Penney, R. Madabhushi, A. Mungenast, A. Bero, and J. Young for discussions and comments on the paper. H.F.I. acknowledges the Cameron Hayden Lord Foundation and Barbara J. Weedon Fellowship; E.S.B. acknowledges the New York Stem Cell Foundation-Robertson Award, National Institutes of Health (NIH) 1R01EY023173, and NIH 1DP1NS087724; L.H.T. acknowledges the JPB Foundation, Belfer Neurodegeneration Consortium, Halis Family Foundation, and NIH RF1 AG047661. E.S.B. and E.N.B. acknowledge NIH ROI GM104948.

Author information

Author notes

    • Hannah F. Iaccarino
    •  & Annabelle C. Singer

    These authors contributed equally to this work.

Affiliations

  1. Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

    • Hannah F. Iaccarino
    • , Anthony J. Martorell
    • , Andrii Rudenko
    • , Fan Gao
    • , Tyler Z. Gillingham
    • , Hansruedi Mathys
    • , Jinsoo Seo
    • , Oleg Kritskiy
    • , Fatema Abdurrob
    • , Chinnakkaruppan Adaikkan
    • , Rebecca G. Canter
    • , Richard Rueda
    • , Emery N. Brown
    •  & Li-Huei Tsai
  2. McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Annabelle C. Singer
    •  & Edward S. Boyden
  3. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Hannah F. Iaccarino
    • , Annabelle C. Singer
    • , Anthony J. Martorell
    • , Andrii Rudenko
    • , Fan Gao
    • , Tyler Z. Gillingham
    • , Hansruedi Mathys
    • , Jinsoo Seo
    • , Oleg Kritskiy
    • , Fatema Abdurrob
    • , Chinnakkaruppan Adaikkan
    • , Rebecca G. Canter
    • , Richard Rueda
    • , Emery N. Brown
    • , Edward S. Boyden
    •  & Li-Huei Tsai
  4. MIT Media Lab, Departments of Biological Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Annabelle C. Singer
    •  & Edward S. Boyden
  5. Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Emery N. Brown
  6. Massachusetts General Hospital, Boston, Massachusetts, Massachusetts 02114, USA

    • Emery N. Brown
  7. Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02139, USA

    • Li-Huei Tsai

Authors

  1. Search for Hannah F. Iaccarino in:

  2. Search for Annabelle C. Singer in:

  3. Search for Anthony J. Martorell in:

  4. Search for Andrii Rudenko in:

  5. Search for Fan Gao in:

  6. Search for Tyler Z. Gillingham in:

  7. Search for Hansruedi Mathys in:

  8. Search for Jinsoo Seo in:

  9. Search for Oleg Kritskiy in:

  10. Search for Fatema Abdurrob in:

  11. Search for Chinnakkaruppan Adaikkan in:

  12. Search for Rebecca G. Canter in:

  13. Search for Richard Rueda in:

  14. Search for Emery N. Brown in:

  15. Search for Edward S. Boyden in:

  16. Search for Li-Huei Tsai in:

Contributions

H.F.I, A.C.S., E.N.B, E.S.B., and L.-H.T. designed experiments. H.F.I. and F.G. performed RNA sequencing experiments. H.F.I. and A.C.S. performed electrophysiology. A.C.S. analysed electrophysiology data. H.F.I. performed and analysed optogenetics and ELISA experiments. T.Z.G., J.S., and O.K. performed western blots. H.F.I., A.R., F.A., R.R., and R.G.C. performed and analysed imaging experiments. F.G. analysed RNA sequencing data. H.F.I., A.J.M., and C.A. performed visual stimulation experiments. H.M. performed FACS experiments. H.F.I, A.C.S., A.R., F.G., E.S.B., and L.-H.T. wrote the manuscript.

Competing interests

L.-H.T. and E.S.B. are scientific founders and serve on the scientific advisory board of Cognito Therapeutics, and H.F.I. and A.C.S. own shares of Cognito Therapeutics Inc.

Corresponding author

Correspondence to Li-Huei Tsai.

Extended data

Supplementary information

Videos

  1. 1.

    40 Hz optogenetic stimulation causes microglia morphological transformation

    3D rendering of Iba1-positive microglia and Aβ in hippocampal CA1 region of 5XFAD/PV-Cre mice expressing only EYFP. Immunohistochemistry was performed with anti-Iba1 (019-19741, green) and anti-Aβ (12F4, red) antibodies. Images were taken with 40x objective.

  2. 2.

    40 Hz optogenetic stimulation causes microglia morphological transformation

    3D rendering of Iba1-positive microglia and Aβ in hippocampal CA1 region of 5XFAD/PV-Cre mice after 40 Hz stimulation. Immunohistochemistry was performed with anti-Iba1 (019-19741, green) and anti-Aβ (12F4, red) antibodies. Images were taken with 40x objective.

  3. 3.

    40 Hz optogenetic stimulation causes microglia morphological transformation

    3D rendering of Iba1-positive microglia and Aβ in hippocampal CA1 region of 5XFAD/PV-Cre mice after random stimulation. Immunohistochemistry was performed with anti-Iba1 (019-19741, green) and anti-Aβ (12F4, red) antibodies. Images were taken with 40x objective.

  4. 4.

    Mouse undergoes light flicker behavioral paradigm

    Video of a mouse exposed to light flicker. Video shows 20 Hz because the frame rate obscures the on/off dynamics of 40 Hz light flicker.

  5. 5.

    40 Hz light flicker causes microglia morphological transformation

    3D rendering of Iba1-positive microglia after dark condition from CLARITY treated 100 μm tissue sections. Immunohistochemistry was performed with anti-Iba1 (019-19741, green) in 5XFAD visual cortex. Images were taken with 63x objective.

  6. 6.

    Hz light flicker causes microglia morphological transformation

    3D rendering of Iba1-positive microglia after 40 Hz flicker from CLARITY treated 100 μm tissue sections. Immunohistochemistry was performed with anti-Iba1 (019-19741, green) in 5XFAD visual cortex. Images were taken with 63x objective.