bioRxivNeurosciencePreprint
Mouse mutants in schizophrenia risk genes GRIN2A and AKAP11 show EEG abnormalities in common with schizophrenia patients
Linnea E. HerzogiD, Lei A. WangiD, Eunah YuiD, Soonwook ChoiiD, Zohreh FarsiiD, Bryan J. SongiD, Jen Q. PaniD, Morgan ShengiD
Abstract
BACKGROUNDSchizophrenia is a heterogeneous psychiatric disorder with a strong genetic basis, whose etiology and pathophysiology remain poorly understood. Exome sequencing studies have uncovered rare, loss-of-function variants that greatly increase risk of schizophrenia [1], including loss-of-function mutations in GRIN2A (aka GluN2A or NR2A, encoding the NMDA receptor subunit 2A) and AKAP11 (A-Kinase Anchoring Protein 11). AKAP11 and GRIN2A mutations are also associated with bipolar disorder [2], and epilepsy and developmental delay/intellectual disorder [1, 3, 4], respectively. Accessible in both humans and rodents, electroencephalogram (EEG) recordings offer a window into brain activity and display abnormal features in schizophrenia patients. Does loss of Grin2a or Akap11 in mice also result in EEG abnormalities? METHODSWe monitored EEG in heterozygous and homozygous knockout Grin2a and Akap11 mutant mice compared with their wild-type littermates, at 3- and 6-months of age, across the sleep/wake cycle and during auditory stimulation protocols. RESULTSGrin2a and Akap11 mutants exhibited increased resting gamma power, attenuated 40-50 Hz auditory steady-state responses (ASSR), and reduced responses to unexpected auditory stimuli during mismatch negativity (MMN) tests. Sleep spindle density was reduced in a gene dose-dependent manner in Akap11 mutants, whereas Grin2a mutants showed increased sleep spindle density. CONCLUSIONSThe EEG phenotypes of Grin2a and Akap11 mutant mice show a variety of abnormal features that overlap considerably with human schizophrenia patients, reflecting systems-level changes caused by Grin2a and Akap11 deficiency. These neurophysiologic findings further substantiate Grin2a and Akap11 mutants as genetic models of schizophrenia and identify potential biomarkers for stratification of schizophrenia patients.
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