The maternal immune activation model uncovers a role for the Arx gene in GABAergic dysfunction in schizophrenia

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

Contents lists available at ScienceDirect

Brain, Behavior, and Immunity journal homepage: www.elsevier.com/locate/ybrbi

The maternal immune activation model uncovers a role for the Arx gene in GABAergic dysfunction in schizophrenia Jay P. Nakamuraa,b,1, Anna Schroedera,1, Matthew Hudsonc,g, Nigel Jonesc,g, Brendan Gillespieb, Xin Dua,b, Michael Notarasd, Vaidy Swaminathanb, William R. Reaye, Joshua R. Atkinse, Melissa J. Greenh,i, Vaughan J. Carrb,h,i, Murray J. Cairnse, Suresh Sundrama,b,c,f, ⁎ Rachel A. Hilla,b, a

Florey Institute for Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria 3010, Australia Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Victoria 3168, Australia University of Melbourne, Parkville, Victoria 3010, Australia d Centre for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medical College, Cornell University, New York 10021, USA e School of Biomedical Sciences and Pharmacy, University of Newcastle, NSW, Australia f Monash Medical Centre, Monash Health, Clayton, Victoria 3168, Australia g Department of Neuroscience, Central Clinical School, Monash University, The Alfred Hospital, Melbourne, Victoria 3004, Australia h School of Psychiatry, University of NSW, Sydney, NSW 2052, Australia i Neuroscience Research Australia (NeuRA), Barker St, Randwick, NSW 2031, Australia b c

ARTICLE INFO

ABSTRACT

Keywords: Schizophrenia Prepulse inhibition Maternal immune activation ARX Parvalbumin Somatostatin GABAergic interneurons Gamma oscillations Theta oscillations Hippocampus

A hallmark feature of schizophrenia is altered high frequency neural oscillations, including reduced auditoryevoked gamma oscillatory power, which is underpinned by parvalbumin (PV) interneuron dysfunction. Maternal immune activation (MIA) in rodents models an environmental risk factor for schizophrenia and recapitulates these PV interneuron changes. This study sought to link reduced PV expression in the MIA model with alterations to auditory-evoked gamma oscillations and transcript expression. We further aligned transcriptional findings from the animal model with human genome sequencing data. We show that MIA, induced by the viral mimetic, poly-I:C in C57Bl/6 mice, caused in adult offspring reduced auditory-evoked gamma and theta oscillatory power paralleled by reduced PV protein levels. We then showed the Arx gene, critical to healthy neurodevelopment of PV interneurons, is reduced in the forebrain of MIA exposed mice. Finally, in a whole-genome sequenced patient cohort, we identified a novel missense mutation of ARX in a patient with schizophrenia and in the Psychiatric Genomics Consortium 2 cohort, a nominal association of proximal ARX SNPs with the disorder. This suggests MIA, as a risk factor for schizophrenia, may be influencing Arx expression to induce the GABAergic dysfunction seen in schizophrenia and that the ARX gene may play a role in the prenatal origins of schizophrenia pathophysiology.

1. Introduction Cognitive dysfunction is a core feature of schizophrenia and is associated with underlying sensory and perceptual processing deficits (Javitt, 2009). Deficits in sensory and sensorimotor gating have been consistently found in patients with schizophrenia (Swerdlow et al., 2014) and are central to many neurodevelopmental (Meyer et al., 2005), genetic (Gomez-Sintes et al., 2014; Notaras et al., 2017), and drug-induced animal models (Bakshi et al., 1994) of relevance to

schizophrenia. These gating functions are reliant on the integration of sensory, attentional and motivational processes through synchronous activity of neuronal networks. High frequency (30–80 Hz) gamma oscillations, in particular, are thought to regulate sensory integration, and attentional processing (Womelsdorf and Fries, 2006). Gamma power is increased at baseline in schizophrenia patients (Spencer 2011), but reduced during cognitive challenge, as evident in early (within 100 ms) auditory-evoked gamma power which is significantly reduced in schizophrenia patients (Leicht et al., 2010). However, an increase in

Corresponding author at: Department of Psychiatry, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Rd, Clayton, VIC 3168, Australia. E-mail address: [email protected] (R.A. Hill). 1 Equal first authorship. ⁎

https://doi.org/10.1016/j.bbi.2019.06.009 Received 19 February 2019; Received in revised form 9 May 2019; Accepted 5 June 2019 0889-1591/ © 2019 Elsevier Inc. All rights reserved.

Please cite this article as: Jay P. Nakamura, et al., Brain, Behavior, and Immunity, https://doi.org/10.1016/j.bbi.2019.06.009

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

baseline low frequency theta power (4–12 Hz) has been linked to memory deficits in patients with schizophrenia (Wichniak et al., 2015). High frequency gamma oscillations are thought to be generated via synchronous inhibition of networks of pyramidal neurons by GABAergic interneurons, particularly those labelled by the calcium binding protein parvalbumin (Uhlhaas et al., 2011). Hippocampal theta oscillations on the other hand are thought to be generated by complex interactions between somatostatin positive and parvalbumin positive GABAergic interneurons (Ferguson et al., 2015). Post-mortem studies of schizophrenia patients have shown reduced expression of the GABAergic synthesizing enzyme GAD in parvalbumin (PV) positive interneurons, as well as reduced number and expression of PV and somatostatin interneurons in the prefrontal cortex and hippocampus (Zhang and Reynolds, 2002; Hashimoto et al., 2003; Morris et al., 2008; Wang et al., 2011). Thus, PV and somatostatin interneuron dysfunction may be a critical component leading to abnormal neuronal synchrony and cognitive dysfunction in schizophrenia. How, and at what time point neurons lose their normal function in schizophrenia is unknown, but it has been suggested that both genetic and environmental insults that occur prenatally can set in motion GABAergic disturbances that persist in adulthood and cause cognitive impairment (Volk and Lewis, 2013). During prenatal development, a range of transcription factors expressed within the medial ganglionic eminence (MGE) and caudal ganglionic eminence (CGE) are responsible for GABAergic subtype specification, migration and maturation; these transcription factors include Nkx2.1, Dlx1/2, Dlx5/6, Arx and Nrp1 (Kelsom and Lu, 2013), and genetic knockdown of these transcripts disrupts forebrain development and behaviour (Cobos et al., 2005; Cho et al., 2015; Simonet et al., 2015). Moreover, hypermethylation of Nrp1 with a corresponding reduction in gene expression has been found in people at risk of developing schizophrenia (Chaumette et al., 2018). Nkx2.1 is a marker of MGE derived GABAergic interneurons, and polymorphisms in the gene encoding for the Nkx2.1 transcript have been associated with schizophrenia (Malt et al., 2016). The ARX gene is located on the X chromosome and a mutation found in exon 5 of the ARX gene caused a range of neuropsychiatric disorders in female heterozygous carriers, including anxiety, depression and schizophrenia but a more severe phenotype in male homozygous carriers, with symptoms including mental retardation, seizures and Ohtahara syndrome (Eksioglu et al., 2011). Furthermore, ARX gene expression can be altered by ultraconserved intronic enhancers, and knockdown of these enhancers disrupts forebrain development resulting in a 21–24% reduction in PV-expressing interneurons that suggests normal Arx expression is critical to forebrain GABAergic development (Dickel et al., 2018). However, as twin and family based studies estimate the heritability of schizophrenia to be between 50 and 80% (Sullivan et al., 2003), environmental factors play a considerable role in the etiology of this disorder. One environmental factor implicated with compelling epidemiological data is maternal infection during pregnancy, which greatly increases the offspring’s risk of developing schizophrenia (Brown and Derkits, 2010), and has been associated with cognitive vulnerabilities in early childhood (Green et al., 2018). Determining whether such an environmental risk factor may alter the above transcription factors involved in GABAergic cell development is critical to understanding its contribution to the disorder. Rodent models of maternal immune activation (MIA) using polyinosinic:polycytidylic acid (poly-I:C) and lipopolysaccharide (LPS) show anatomical, molecular and behavioural features consistent with those found in schizophrenia, some of which could be reversed by antipsychotic treatment (Meyer et al., 2005; Bitanihirwe et al., 2010; Bitanihirwe et al., 2010; Nagai et al., 2011). Moreover, these models were shown inter alia to have altered PV interneurons, an altered GABAergic transcriptome and abnormal baseline synchronized activity of neuronal firing (Basta-Kaim et al., 2011; Dickerson et al., 2014; Richetto et al., 2014) similar to abnormalities seen in schizophrenia.

The current study sought to further explore the transcriptional origins of interneuron dysfunction associated with the gamma oscillatory impairments found in schizophrenia using the maternal immune activation model. 2. Methods and materials 2.1. Animals All live animal experiments were conducted at the Florey Institute of Neuroscience and Mental Health (FINMH) (Parkville, VIC, Australia). All surgical and experimental procedures were conducted according to the guidelines in the Australian Code of Practise for the Care and Use of Animals for Scientific Purposes (National Health and Medical Research Council of Australia, 8th edition 2013) and approved by the Animal Ethics Committee of the FINMH and adhered to the guidelines outlined by the NIH guide for care and use of Laboratory animals (NIH Publications No. 8023). In accordance with the recently reported review of guidelines to improve the rigor, reproducibility and transparency of the maternal immune activation model, we report here a detailed methodology on the breeding, housing, and sex of animals, as well as dosage and administration of poly-I:C (Kentner et al., 2018). All dams (C57BL/6) were ordered from the Animal Resources Centre (Western Australia) to ascertain similar ages. Studs (C57BL/6) were obtained from the breeding colony at the FINMH. Breeding trios of two females and a stud were housed in individually ventilated cages. Pregnancy was ascertained by visual inspection of vaginal plugs in the morning and evening. The day a plug was seen was considered embryonic day 0.5. Offspring were weaned at 3 weeks of age and were group housed with same-sexed mice across different litters and treatment groups to minimize litter effects. In all cohorts, 2–5 mice per cage were housed in individually ventilated cages (391x199x160mm) (Tecniplast, Sealsafe PLUS Mouse IVC Green Line) with ad libitum access to food (Specialty Feeds, Western Australia) and water in a 12/12 h light/dark cycle (lights on 7am7pm) unless stated otherwise. The temperature was maintained at approximately 22 °C. Cages were cleaned once a week. All behavioural experiments were performed during the day between 8am and 5pm. 2.2. Poly-I:C treatment Two cohorts were used for this study. Cohort 1 underwent behavioural experiments, while cohort 2 was used to measure cytokine and microglia levels to ensure the dose and administration of the viral mimetic of polyI:C caused an immune response (Suppl. Fig. 1), as well as to collect samples for mRNA expression analysis. Pregnant dams of both cohorts were injected with either vehicle control (saline) or poly-I:C (20 mg/kg) at gestation day 17.5, a time point shown to induce cognitive deficits related to schizophrenia (Meyer et al., 2006; Connor et al., 2012; Richetto et al., 2013). The dose of 20 mg/kg (i.p) was chosen according to the induction of schizophrenia-like behaviours, which were prevented by an anti-inflammatory antibody (IL-6) (Smith et al., 2007). Pups of cohort 1 were weaned at three weeks and grouphoused (2–5/cage). In cohort 2 blood samples were taken retro-orbitally from pregnant dams one and three hours post injection for cytokine analysis. Six hours after injection, trunk blood was collected from dams and fetal brains were collected. Contributions from each litter into groups are outlined in Table 1. 2.3. Surgical procedures At 10 weeks, mice received an electrode implant into the CA1 region of the dorsal hippocampus as previously described (Schroeder et al., 2017). Mice were single housed following surgery to avoid damage to implant caps. Behavioural testing was performed at 12 weeks. 2

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Table 1 Distribution of litters from dams injected with Poly (I:C) (grey) or Saline (white).

Cohort 1 Poly-I:C

Treatment Dam ID

P1

P2

P3

P4

Saline

P5

P6

P7

P8

P9

S1

S2

S3

S4

Baseline gamma and theta power Males

1

2

1

1

0

2

0

0

0

3

2

3

0

Females

0

2

1

0

2

0

2

1

0

3

3

2

1

Acoustic-evoked gamma and theta power Male

1

1

1

0

0

1

3

0

0

3

1

1

0

Female

0

2

1

0

3

0

0

1

1

2

3

0

0

Males

1

2

1

1

0

0

1

0

0

4

3

3

0

Females

0

2

1

0

2

0

0

2

1

3

3

0

1

PPI

mRNA expression Male

1

2

1

1

0

0

0

0

0

3

1

0

0

Female

0

2

1

1

0

0

1

0

0

3

1

1

0

Protein expression Male

1

2

1

1

0

0

0

0

0

3

1

0

0

Female

0

2

1

0

0

0

1

0

0

3

1

1

0

Cohort 2 Treatment Dam ID Treatment Fetal

P9 Poly-I:C 4

Poly-I:C P10 Poly-I:C 7

P11 Poly-I:C 3

2.4. Behavioural tests and electrophysiological recordings

S5 Saline 5

Saline S6 Saline 6

S7 Saline 4

theta (5–10 Hz), and gamma (30–80 Hz) frequencies were then calculated by taking the integral of the PSD estimate over the appropriate frequency interval and dividing by total power (1–200 Hz). To analyse evoked oscillatory power, single trial epochs (−500 ms to 500 ms relative to onset of prepulse stimuli) were extracted from the continuous LFP data for every pre-pulse-pulse trial. Epochs were visually inspected and any epochs containing notable artefacts were rejected. The remaining clean epochs were subsequently subjected to morlet wavelet decomposition to calculate event-related spectral power (ERSP) at 180 linearly spaced frequencies from 10 to 200 Hz with wavelet cycles increasing from 3 to 10. This analysis was achieved using the newtimef function from the EEGlab MATLAB plugin (Schwartz Centre and Computational Neuroscience). The ERSP was subsequently baseline corrected (baseline: −500 to 0 ms relative to pre-pulse stimulus) and log normalized (dB). Evoked theta power (10–11 Hz) and evoked gamma power (30–80 Hz) was then computed by averaging all values over the appropriate frequency interval occurring 0 to 100 ms relative to the onset of the prepulse stimulus.

2.4.1. Pre-pulse inhibition Prepulse inhibition (PPI) of startle was assessed based on the previously described protocol (van den Buuse et al., 2009; van den Buuse 2010) with slight modifications, using only the pre-pulse intensity of +8 dB (Jones et al., 2014). Pre-pulse inhibition was calculated as the difference between responses to prepulse–pulse trials and pulse-alone trials, expressed as ratio of responses to the pulse-alone trials ([pulse − (prepulse-pulse) * 100]/pulse). 2.4.2. Electrophysiology Cables were attached to caps and local field potentials (LFP) of each mouse were recorded in both their homecage and in a novel environment (holding chamber for 10 min) using LabChart7 (ID Instruments, NSW, Australia) as previously described (Schroeder et al., 2017). All data analysis was conducted using custom-designed scripts written for MATLAB (v7.10.0, Natick, Massachusetts: The MathWorks Inc., 2010). For baseline power, power spectral density (PSD) estimation was performed using the Welch Periodogram and was estimated using a Fast Fourier transform and a Hamming window, to achieve a frequency resolution of 0.5HZ overlying the interval 1–200 Hz. Relative power of

2.5. RNA extraction, reverse transcription and Biomark 96.96 qPCR array One week following behavioural testing, mice were killed by 3

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

cervical dislocation and brains were dissected and snap frozen in dry ice. RNA from fetal whole brain and adult (∼14 weeks) prefrontal cortex and hippocampus was extracted using the RNeasy Mini Kit oncolumn extraction method as per manufacturer protocol (Qiagen, Hilden, Germany). All samples were DNase digested in an on-column step. Reverse transcription of 200 ng RNA/sample was performed using the High-Capacity cDNA Reverse Transcription Kit with RNase Inhibitor (Thermofisher, MA, USA). Samples (1.25uL cDNA) were pre-amplified with TaqMan PreAmp Master Mix and pooled TaqMan assays (Thermofisher, MA, USA) for 14 cycles before diluting 1:5 in Tris EDTA buffer (pH8.0). 5uL of each diluted sample and 10x TaqMan assay was used to load the integrated fluidic circuit (IFC). The IFC was loaded and run as per manufacturer protocol (Fluidigm, San Francisco, USA). Biomark Fluidigm 96.96 IFC were used to assess the expression of 96 genes in 95 pre-amplified samples. These included fetal brain (5/ group), adult PFC (5/group/sex) and adult hippocampus (5/group/sex) in technical duplicates. Our selection of target and reference gene TaqMan assays can be found in Supplementary Table 1. Technical duplicate mean CT values were normalized to two reference genes, PGK-1 and GAPDH (ΔCT). Relative expression was calculated as 2−ΔCT(polyIC)−ΔCT(control).

unnecessary. Protein expression was compared via U test if data are non-parametric and unpaired t-test if parametric, while maternal serum levels of IL-6 were assessed via a two-way ANOVA with time and treatment as the two variables. In all cases, the significance level was set to p ≤ 0.05. 2.9. Analysis of genomic variation in the human ARX gene 2.9.1. Whole genome sequencing (WGS) Peripheral blood mononucleocyte derived DNA from Australian Schizophrenia Research Bank (ASRB) participants (N = 333 DSM IV schizophrenia, 167 healthy controls) underwent whole genome sequencing at the Garvan Institute of Medical Research: Kinghorn Centre for Clinical Genomics using the Illumina HiSeq X Ten system. After library and cluster generation using standard Illumina protocols, 1 μg of high integrity DNA was sequenced with 2 × 150 base pair paired-end reads, such that 75% of bases had a Phred quality score greater than 30 and a minimum mean yield of 30x coverage. Alignment to the reference genome in hg19 assembly was performed using Bowtie2 and conversion to BAM format via SAMtools (Li et al., 2009). After removal of duplicate reads using Picard, indel realignment and quality score recalibration were undertaken with GATK v3.4 (McKenna et al., 2010). Variants were called using the GATK HaplotypeCaller framework followed by GenotypeGVCFs. Variant filtering was applied as adapted from GATK best practices for quality control.

2.6. IL-6 ELISA Interleukin-6 (IL-6) levels in maternal serum samples and fetal brains were analysed using an enzyme-linked immunosorbent assay (ELISA) kit (Abcam, Cambridge, UK).

2.9.2. Scanning for putative deleterious variants within ARX Rare variants with a population frequency < 1% in the WGS database gnomAD (http://gnomad.broadinstitute.org/) were retained. We considered exonic variants annotated by SnpEff (Cingolani et al., 2012) as ‘high’ or ‘moderate’ impact and further assigned these loci a CADD (Combined Annotation Dependent Depletion) score (Kircher et al., 2014) as a measure of pathogenicity. A scaled phred-like CADD threshold > 20 was set to define a deleterious variant as this represents the top 1% of scores in the genome.

2.7. Western blot analysis Protein was extracted and expression assessed by SDS-PAGE Western blotting as previously described (Hill and van den Buuse, 2011). CD68, Iba1, PV, somatostatin and GAD67 were normalized against the internal control, β-actin. Blot density was analysed using CLIQS software (version 1.1) with background subtracted using the rolling ball method. Antibodies used were CD68 (dilution 1:1000; 55 kDa; BD Pharmingen), Iba1 (dilution 1:1000; 17 kDa; FUJIFILM, Osaka, Japan), mouse anti-PV (dilution 1:1000; 12 kDa; Merk-millipore; MAB1572; Billerica, MA, USA), mouse anti-GAD67 (dilution 1:1000; 67 kDa; Sigma-Aldrich; G5419; Castle Hill, NSW, Australia), rat anti-somatostatin (dilution 1:2000; 14 kDa; Merk-millipore; MAB354; Billerica, MA, USA), rabbit anti-TH (1:1000; 60 kDa; Pel Freeze, AR, USA) and mouse anti-β-actin (dilution 1:10,000; 42 kDa; Sigma-Aldrich; A5316; Castle Hill, NSW, Australia) and secondary antibodies; anti-rabbit (dilution 1:2000; Cell signalling; Danvers, MA, USA), antimouse (dilution 1:2000; Cell signalling; Danvers, MA, USA) or anti-rat IgG HRP-linked antibodies (dilution 1:2000; Merk-millipore; Billerica, MA, USA).

2.9.3. Targeted assessment for the enrichment of SNPs in the human ARX gene from the PGC2 data The joint effect of common variants mapped to the ARX gene was investigated with MAGMA (de Leeuw et al., 2015) with default parameters and the genic boundaries of ARX in hg19 assembly set as 5 kilobases (kb) 5′ and 1.5 kb 3′ from its coordinates to capture regulatory variation. We accounted for linkage disequilibrium between ARX markers with the 1000 genomes phase 3 European panel as reference (Genomes Project et al., 2015). P value thresholding for each of the input ARX SNPs was undertaken to reflect distinct biological signals captured at differing levels of polygenicity – therefore, three MAGMA models were constructed: all SNPs in ARX, SNPs with p < 0.5 association with schizophrenia, and SNPs with p < 0.05 association with schizophrenia. Each model used the default SNPwise approach for summary statistics in MAGMA, with the mean of χ2 statistic for ARX SNPs at each threshold.

2.8. Statistical analysis – animal model data Statistical analysis was performed using Prism 7 (GraphPad Software Inc., La Jolla, CA, USA). Our choice for non-parametric vs parametric tests were guided by sample size and normality using Shapiro-Wilk normality test. For all data, sex was originally assessed as a biological variate but no sex differences were found, so sexes were collapsed. Theta/gamma power at baseline and in a novel environment were assessed by two-way ANOVA. Acoustic-evoked theta/gamma power during PPI, percentage PPI and startle amplitude were assessed using a Mann-Whitney U test when data was non-normal and parametric t-tests when normally distributed. For the mRNA data we pre-selected 94 probes with the a priori hypothesis that poly-I:C exposure may alter expression of these transcripts. This was a targeted approach, and data were non-normal therefore individual Mann-Whitney U-tests were planned comparisons between control and MIA samples, and FDR correction was deemed

3. Results 3.1. Maternal and fetal IL-6 and microglia expression levels following polyI:C exposure Levels of IL-6 were measured in maternal serum at 1, 3 and 6hrs following polyI:C exposure. Data are averaged across two IL-6 ELISA plates with duplicates from each sample in each ELISA and were analysed using a two-way ANOVA with poly-I:C and time as the independent variables. All data were within the lower and upper limits of detection. Here we found a main effect of treatment with poly-I:C exposure causing an elevation in IL-6 levels (F (1, 11) = 15.16, P = 0.0025) and a main effect of time (F (2, 11) = 10.73, p = 0.0026) 4

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Fig. 1. Baseline LFP recordings in home cage (circles) and novel environment (squares). A. Baseline gamma power in homecage and novel environment. B. Baseline theta power in homecage and novel environment, n = 15–17/group, * = p < 0.05 effect of novel environment, line with * = p < 0.05, main effect of poly-I:C. Males are blue and females are red and litters are coded by shading.

with post-hoc analysis showing significant differences between the 1 h and 3 h time point (p = 0.001) and the 3 h and 6 h time point (p = 0.0026), suggesting the highest IL-6 levels are at the 3 hr time point. No significant poly-I:C × time interaction was found (Suppl. Fig. 1A). IL-6 (p = 0.04; Suppl. Fig. 1B), Iba1 (p = 0.04; Suppl. Fig. 1C) and CD68 (p = 0.0045; Suppl. Fig. 1D) levels were all significantly higher in the fetal brains 6hr after polyI:C injection.

Arx (p = 0.04) and Gsx1 (p = 0.0207), and an increase in Nurr1 (p = 0.0164) and Mapk8 (p = 0.0418) in poly-I:C exposed mice compared to controls (Fig. 3C). Due to the location of Arx on the X chromosome and the sexually dimorphic phenotypes of patients presenting with ARX mutations, we also analysed Arx transcript expression by twoway-ANOVA with both sex and poly-I:C exposure as the two independent variables. Here we found a main effect of poly-I:C exposure on Arx expression (F (1, 14) = 6.598, p = 0.02) but no effect of sex and no sex × poly-I:C interaction (Fig. 3D). There was no effect of litter on Arx expression as shown by the shaded coding.

3.2. Baseline gamma and theta power Baseline gamma power was unchanged in MIA offspring within their homecage, but when exposed to a novel environment all mice showed an increase in gamma power (main effect of environment (F [1, 63] = 6.176, p = 0.015; Fig. 1A). For theta power, however, we found a significant main effect of poly-I:C (F [1, 65] = 5.457, p = 0.022) and a significant main effect of environment (F [1, 65] = 5.057, p = 0.028) (Fig. 1B). Here MIA offspring show increased baseline theta power and all mice show an increase in theta power when exposed to a novel environment. For both gamma and theta power there is no significant poly-I:C × environment interaction.

3.6. Adult protein expression Prefrontal cortex: No significant changes in GAD67 (Fig. 4A) or somatostatin (Fig. 4B) expression were found; however, we did find a significant reduction in the protein expression of parvalbumin (p = 0.002; Fig. 4C) in the PFC of poly-I:C exposed mice. In addition, protein levels of tyrosine hydroxylase were significantly increased in the PFC of poly-I:C exposed mice (p = 0.029; Fig. 4D). Hippocampus: GAD67 expression was unchanged in the dorsal hippocampus, but somatostatin (p = 0.024; Fig. 4F) and parvalbumin (p = 0.002, Fig. 4G) expression was significantly reduced following poly-I:C exposure. Similar to the PFC, protein expression levels of tyrosine hydroxylase were significantly increased in the adult dorsal hippocampus of poly-I:C exposed mice (p = 0.04; Fig. 4H). No significant effects of poly-I:C were found for GAD67, somatostatin, parvalbumin and TH in the ventral hippocampus (data not shown). Full western blot images are available in Supplementary Figs. 2 and 3.

3.3. Acoustic-evoked gamma and theta oscillations during pre-pulse inhibition LFP recordings were taken throughout the testing period, and timelocked to the pre-pulse and pulse phases, (Fig. 2A). The pulse is accompanied by a startle from the mouse, which may interfere with the signal, thus only the pre-pulse data was analysed here. Both gamma (Fig. 2B, p = 0.0004) and theta (Fig. 2C, p = 0.0096) power were reduced during the pre-pulse phase (Fig. 2A) in poly-I:C exposed mice. % PPI was significantly reduced in poly-I:C exposed mice (p = 0.0001), indicating disrupted sensorimotor gating (Fig. 2D), while the startle amplitude was unaltered by poly-I:C exposure (Fig. 2E). No effect of litter or sex was found for PPI as shown by colour (sex) and shading (litter) coding.

3.7. Human genetic analysis Given the significant and persistent change in Arx expression in poly-I:C exposed mice, and the relevance of this transcript in mediating GABAergic migration, we investigated whether genetic variation in this gene was associated with schizophrenia. We identified one individual with a missense variant in ARX (chrX:25031321, p.R264Q), which results in the substitution of a proline residue for glutamine; this patient was a female diagnosed with schizoaffective disorder, while no such variants were found in healthy controls. This variant was assigned a Combined Annotation Dependent Depletion (CADD) score of 23.8, suggesting this amino acid substitution has a deleterious effect on ARX and has not been previously described in the general population (not recorded in gnomAD database). Further, a de novo missense variant which substitutes an alanine residue for threonine in ARX was found in a female proband diagnosed with autism spectrum disorder (chrX:25031277, p.A279T) identified from the online database NPdenovo. Similar, to the proband in our cohort, this locus has not been characterized in the general population within gnomAD and has a high (CADD) score = 22.6. We next probed for evidence of severe mental illness in the

3.4. Fetal mRNA expression Poly-I:C exposure caused an increase in mRNA expression of proinflammatory cytokine, IL-6 (p = 0.0159), similar to protein levels (Suppl. Fig. 1B). Poly-I:C exposure significantly decreased expression of Nurr1 (p = 0.0079), Arx (p = 0.0286), Nrp1 (p = 0.0317), Nkx2.1 (p = 0.0357), Grm5 (p = 0.0317), and TrkB (p = 0.0286) (Fig. 3A). 3.5. Adult mRNA expression Hippocampus: There was a significant decrease in expression of Nurr1 (p = 0.0117) and Tnf (p = 0.0274) in poly-I:C exposed mice compared to controls (Fig. 3B). Prefrontal cortex: There was a significant decrease in expression of 5

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Fig. 2. LFP recordings in control and poly I:C treated mice during pre-pulse inhibition testing. A. Event related spectral perturbation (ERSP) represented as a heat map with time (ms) on the x axis and frequency (Hz) on the Y-axis. The time window consists of 300 ms before and after the pulse, with pre-pulses occurring at −100 ms. B. Relative gamma power during the pre-pulse, B. Relative theta power during the pre-pulse stimulus, C. % pre-pulse inhibition, D. startle amplitude, in control (circles) and poly-I:C exposed (squares) adult mice. N = 11–17/group. *P < 0.05, **P < 0.01. Males are blue and females are red. Litters are coded by shading. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

proband’s family tree and identified both parents and her female sibling suffered from depression, while her paternal grandfather was diagnosed with bipolar disorder, and two cousins with Autism Spectrum Disorder; Suppl. Table 2 and Fig. 5). But we were unable to access genetic information about family members in relation to determining the specificity of the ARX gene for schizophrenia. However, summary statistics from the PGC-2 data set (Schizophrenia Working Group of the Psychiatric Genomics 2014),

uncovered nominal enrichment of proximal SNPs in the ARX gene at two of the p value thresholds tested. Specifically, the joint effect of all SNPs with either a GWAS p < 0.5 (Z = 1.9455, p = 0.0259) or a threshold of p < 0.05 (Z = 1.6596, p = 0.0485) was associated with schizophrenia.

6

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Fig. 3. Volcano plots of relative gene expression in the fetal brain (A), adult HPC (B) and adult PFC (C) of poly I:C exposed mice compared to saline exposed controls. Gene names are labelled when differences reached significance, p < 0.05. N = 4–5/group. Arx expression, split by sex as well as poly-I:C exposure in the PFC (D) circles are control and squares are poly-I:C, litters are coded by shading, * over squares signifies significant main effect of poly-I:C.

Fig. 4. Protein expression of selected markers in control (circles) and poly-I:C (squares) adult prefrontal cortex (PFC – top panel) and hippocampus (Hp – bottom panel). Protein expression of A. and E. GAD67, B. and F. somatostatin (SST) expression, C. and G. parvalbumin (PV) expression, and D. and H. Tyrosine hydroxylase (TH) expression. * = P < 0.05, ** = P < 0.01. N = 8–10/group. Males are blue and females are red, litters are coded by shading. 7

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Fig. 5. Family tree of proband with Arx missense mutation and a diagnosis of schizoaffective disorder. Circles are females and squares are males. Patterns reflect diagnosis; proband – dark pattern; diagonal lines – depression; dots – Autism; horizontal stripes – ADHD; squares – bipolar disorder. CHD = chronic heart disease, T2DM = type 2 diabetes mellitus, ADHD = attention deficit hyperactivity disorder, BPAD = bipolar disorder, SAD = schizoaffective disorder.

4. Discussion

recordings were only taken from the hippocampus. Further studies with electrodes implanted in both prefrontal cortex and hippocampus would be beneficial here. Another limitation is that mice were single housed following surgical implantation of the electrodes. This may have caused additional stress, which may influence their behaviour. However, it is important to note that both control and poly-I:C exposed mice were housed in this manner. That being said, the familiar ‘two-hit’ hypothesis suggests that psychiatric disturbances may be caused by a combination of two significant genetic or environmental hits across two critical time points of brain development (Maynard et al., 2001). Here the single housing from young adulthood may represent a second-hit in the form of stress for the poly-I:C exposed mice, resulting in more severe phenotypes. This should be considered when comparing this model to other poly-I:C models. PPI deficits following poly-I:C exposure on GD17 were found in both male and female mice. This varies from previous reports by Meyer et al. where PPI deficits were only apparent in GD9 exposed mice but not GD17 (Meyer et al., 2008). Variations in the dose and route of administration of poly-I:C (20 mg/kg i.p. here, while Meyer et al. use 5 mg/kg, i.v) as well as the housing and electrode implantation surgery may account for these differences. Interestingly, in a genetic plateletderived growth factor receptor-β knockout model with relevance to schizophrenia, disrupted auditory phase-locked gamma power was correlated with reduced density of PV-positive neurons and impaired PPI (Nakamura et al., 2015), similar to what we found in our model. Thus the above study as well as our data suggest that prefrontal cortical PV interneurons play a role in regulating acoustic-evoked gamma power and PPI performance. We have exposed our mice to poly-I:C at GD17 – a time point when GABA-positive cells are in the process of migrating (Le Magueresse and Monyer, 2013), and we see significant changes to transcripts involved in interneuron migration. For example, TrkB was significantly reduced in poly-I:C exposed fetal brain and this neurotrophin receptor is known

We found a robust increase in baseline theta power in poly-I:C exposed mice. As far as we are aware, this has not been previously reported in the poly-I:C model. However, models of NMDA receptor hypofunction with relevance to schizophrenia have also shown increased baseline theta power (Sampaio et al., 2018; Wang et al., 2018). In addition, increased theta power has been associated with memory deficits in people with schizophrenia (Wichniak et al., 2015). Hippocampal theta oscillations are thought to be regulated (at least in part) by somatostatin positive cells, (Katona et al., 2014) as well as bistratified parvalbumin positive cells (Ferguson et al., 2015). This aligns with our protein expression data in which we found reduced somatostatin and parvalbumin in the hippocampus. Both gamma and theta power were reduced following pre-pulse sensory stimuli in poly-I:C exposed mice compared to controls, similar to what is found in drug-induced animal models with relevance to schizophrenia (Jones et al., 2014; Hudson et al., 2016) and in people with schizophrenia (Kwon et al., 1999; Leicht et al., 2010). However, we are not aware of any previous studies that have shown gamma and theta power deficits during PPI testing in poly-I:C exposed mice. Encoding of new sensory information is posited to occur during the peak of the theta cycle, a time point where by the entorhinal cortical input to the CA1 is strong, but CA3 input is weak (Hasselmo et al., 2002). Thus, the disturbances in interneuron protein expression that we found in both hippocampal (reduced parvalbumin and somatostatin) and prefrontal cortical (reduced parvalbumin) regions may suggest that disruptions to both local and input circuits contribute to hippocampal theta power during PPI. Indeed, a previous study showed disrupted EEG coherence between the mPFC and dorsal hippocampus in poly-I:C exposed rats, although recordings were not taken during PPI testing, but rather during foraging in an open field environment (Dickerson et al., 2014). A limitation of the current study is that electrophysiological 8

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

to play a critical role in GABAergic interneuron migration and development (Xenos et al., 2017). Nrp1 was also significantly reduced in the poly-I:C fetal brain. Nrp1 is expressed on migrating MGE-derived neurons, and migrating interneurons expressing Nrp1 are directed to the cortex (Marin et al., 2001). Arx is downstream of Dlx1/2 and modulates Dlx-dependent GABAergic migration (Marsh et al., 2016). Reduced expression of Dlx genes has been shown in a rat model of MIA via LPS (Oskvig et al., 2012). We found reductions in both Dlx 1 and 2 following poly-I:C exposure, although these did not reach significance here, however, Arx expression was significantly reduced and this persisted into adulthood. Recent studies of mutant Arx mice show abnormal tangential migration of GABAergic neurons into the cortex (Kitamura et al., 2002; Marsh et al., 2016). Our data suggest disruption to GABAergic migration in poly-I:C exposed mice, with the functional consequences being altered acoustic-evoked gamma power and disrupted PPI. Reduced Arx expression persisted into adulthood. It is unclear from this study what the relevance of this may be, but previous studies have shown expression of Arx within adult GABAergic cortical interneurons, whereby it is posited to play a role in adult neurogenesis (Colombo et al., 2004). Thus, the ARX gene appears to be critical throughout life in regulating GABAergic cell fate – and we show that a single exposure to poly-I:C at gestational day 17 can durably alter its expression. In a post-mortem human study ARX expression was found to be unaltered in the prefrontal cortex of 62 control-matched patients with schizophrenia (Volk et al., 2016). Here we suggest that altered ARX expression may be present in sub-groups of people with a psychiatric disorders (for example who have been exposed prenatally to immune activation or have a mutation), and that this may be difficult to capture in a post-mortem study which naturally tends to have low numbers. Altered expression of transcripts involved in GABAergic cell development in the fetal brain aligns with the protein expression data in adulthood, which shows reduced expression of MGE-derived GABAergic subtypes, parvalbumin and somatostatin in the hippocampus, and reduced parvalbumin expression in the prefrontal cortex. This corresponds with human post-mortem studies, which consistently show reduced parvalbumin and somatostatin expression and cell density in the prefrontal cortex and hippocampus of schizophrenia patients (Zhang and Reynolds, 2002; Hashimoto et al., 2003; Morris et al., 2008; Wang et al., 2011). However, while protein expression was altered, we did not find any significant changes to mRNA expression of parvalbumin or somatostatin. This aligns with a recent study by Luoni et al., 2017, who also found that parvalbumin mRNA expression was unchanged by polyI:C exposure at gestational day 17, but protein levels of parvalbumin were reduced in the dorsal hippocampus (Luoni et al., 2017). Interestingly, Luoni et al. showed that treatment with the antipsychotic lurasidone recovered parvalbumin protein expression, thus it would be of interest to investigate in future studies whether lurasidone modifies auditory-evoked gamma oscillations. Interestingly, and in contrast to previous reports (Richetto et al., 2014) we did not find significant changes in GAD67 mRNA or protein expression levels in the prefrontal cortex or hippocampus. These differences across studies may be due to the nature of the dissections. While our study includes the whole prefrontal cortex dissected from the optic chiasm and with the caudate removed, the study from Richetto microdissected just the medial prefrontal cortex from coronal sections. Thus, our section of tissue contains other regions of prefrontal cortex that may have diluted the signal. This suggests that altered GAD67 expression is mPFC specific. Our animal model data aligned with the human genetic data, in which we report a patient with schizoaffective disorder from the ASRB cohort having a functional missense mutation in the ARX gene, and an association found between ARX SNPs and schizophrenia in the PGC2 data set (Schizophrenia Working Group of the Psychiatric Genomics 2014). The novel missense mutation identified is predicted to cause a deleterious amino acid substitution, and may therefore have clinically relevant functional consequences such as reduced Arx protein

expression, and interneuronopathy (Price et al., 2009; Katsarou et al., 2017). This locus plausibly has a very low population frequency as it is yet to be characterized in publicly available databases. While this mutation is predicted to cause deleterious effects, the penetrance of this mutation in terms of causality is likely to be low. Here the authors propose, rather, that the mutation may have increased risk in the identified patient and a second ‘hit’ (either genetic or environmental) may have triggered the emergence of schizophrenia. The timing and nature of this ‘second hit’ would then dictate which disorder the person will present with (e.g. Autism or schizophrenia) and may explain why mutations in this gene have been associated with earlier developmental disorders such as Autism as well as other psychiatric disorders, such as depression and anxiety (Eksioglu et al., 2011). ARX mutations, including duplication, expansion, missense and deletions, have previously been associated with severe mental retardation, various forms of epilepsy (Jackson et al., 2017), and autism spectrum disorder, with varying phenotypes depending on the type of mutation and the sex (Stromme et al., 2002). Indeed, findings of a de novo ARX variant in an ASD patient, which was also predicted to have deleterious effects on gene function, suggests this gene may contribute to the aetiology of other neuropsychiatric disorders (Li et al., 2016). Further support for this stems from the identification of a mutation in exon 5, which caused a frameshift in the aristaless domain of the ARX gene, and was found to result in Ohtahara syndrome, (ambiguous genitalia, and mental retardation) in male homozygous carriers, whereas female heterozygous carriers presented with neuropsychiatric disorders, including anxiety, major depression and schizophrenia (Eksioglu et al., 2011). As far as we are aware this is the only other study that has reported a mutation in a female, and we suggest that perhaps the sexually dimorphic nature of ARX gene mutations may be the reason it has not been identified as a risk loci in large genetic association studies for schizophrenia. This highlights the need for stratification by sex. We similarly found a history of mental illness in several of the biological family members of the patient identified here, with their diagnoses spanning depression, bipolar disorders and ASD. This suggests that the ARX gene may be associated with neuropsychiatric disorders more generally. Polymorphisms or mutations in genes involved in dopaminergic cell development such as Nurr1 (Buervenich et al., 2000) have also been associated with severe psychiatric disorders and reduced mRNA expression of Nurr1 has been reported in the prefrontal cortex in schizophrenia and bipolar disorders (Xing et al., 2006). We found reduced expression of Nurr1 in the fetal brain and the adult hippocampus, but increased expression in the adult prefrontal cortex of poly-I:C exposed mice. This aligns with previous studies that have shown reduced Nurr1 at 2 days post treatment in the fetal brain of mice exposed to poly-I:C at GD9 (Meyer et al., 2008), but a post-pubertal increase in Nurr1 expression in midbrain substantia nigra and ventral tegmental area (VTA) regions (Vuillermot et al., 2010). Our study extends upon this earlier study, showing that the post-pubertal increase in Nurr1 following polyI:C exposure is also evident in the prefrontal cortex, but within the hippocampus, Nurr1 expression is reduced. In addition, we found that tyrosine hydroxylase expression was increased in both the prefrontal cortex and hippocampus. Given that the hippocampus receives dopamine projections from the substantia nigra and VTA, where Nurr1 and TH expression was previously reported to be increased post-puberty in poly-I:C exposed mice (Vuillermot et al., 2010), it is not surprising then that TH levels are elevated in the hippocampus, but we suggest that perhaps hippocampal Nurr1 expression may be reduced here as a compensatory mechanism. Interestingly, previous studies report that Nurr1 was not essential for poly-I:C-induced disruptions to PPI (Vuillermot et al., 2011). Here, GABAergic disturbances, or the combination of disinhibition followed by increased dopamine, may be required to elicit behavioural disruption.

9

J.P. Nakamura, et al.

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

4.1. Conclusions

et al., 2005. Mice lacking Dlx1 show subtype-specific loss of interneurons, reduced inhibition and epilepsy. Nat. Neurosci. 8, 1059–1068. Colombo, E., Galli, R., Cossu, G., Gecz, J., Broccoli, V., 2004. Mouse orthologue of ARX, a gene mutated in several X-linked forms of mental retardation and epilepsy, is a marker of adult neural stem cells and forebrain GABAergic neurons. Dev. Dyn. 231, 631–639. Connor, C.M., Dincer, A., Straubhaar, J., Galler, J.R., Houston, I.B., Akbarian, S., 2012. Maternal immune activation alters behavior in adult offspring, with subtle changes in the cortical transcriptome and epigenome. Schizophr. Res. 140, 175–184. de Leeuw, C.A., Mooij, J.M., Heskes, T., Posthuma, D., 2015. MAGMA: generalized geneset analysis of GWAS data. PLoS Comput. Biol. 11, e1004219. Dickel, D.E., Ypsilanti, A.R., Pla, R., Zhu, Y., Barozzi, I., Mannion, B.J., et al., 2018. Ultraconserved enhancers are required for normal development. Cell 172, 491–499 e415. Dickerson, D.D., Overeem, K.A., Wolff, A.R., Williams, J.M., Abraham, W.C., Bilkey, D.K., 2014a. Association of aberrant neural synchrony and altered GAD67 expression following exposure to maternal immune activation, a risk factor for schizophrenia. Transl. Psychiatry 4. Dickerson, D.D., Overeem, K.A., Wolff, A.R., Williams, J.M., Abraham, W.C., Bilkey, D.K., 2014b. Association of aberrant neural synchrony and altered GAD67 expression following exposure to maternal immune activation, a risk factor for schizophrenia. Transl. Psychiatry 4, e418. Eksioglu, Y.Z., Pong, A.W., Takeoka, M., 2011. A novel mutation in the aristaless domain of the ARX gene leads to Ohtahara syndrome, global developmental delay, and ambiguous genitalia in males and neuropsychiatric disorders in females. Epilepsia 52, 984–992. Ferguson, K.A., Huh, C.Y., Amilhon, B., Manseau, F., Williams, S., Skinner, F.K., 2015. Network models provide insights into how oriens-lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations. Front. Syst. Neurosci. 9, 110. Genomes Project, C., Auton, A., Brooks, L.D., Durbin, R.M., Garrison, E.P., Kang, H.M., et al., 2015. A global reference for human genetic variation. Nature 526, 68–74. Gomez-Sintes, R., Kvajo, M., Gogos, J.A., Lucas, J.J., 2014. Mice with a naturally occurring DISC1 mutation display a broad spectrum of behaviors associated to psychiatric disorders. Front. Behav. Neurosci. 8, 253. Green, M.J., Kariuki, M., Dean, K., Laurens, K.R., Tzoumakis, S., Harris, F., et al., 2018. Childhood developmental vulnerabilities associated with early life exposure to infectious and noninfectious diseases and maternal mental illness. J. Child Psychol. Psychiatry 59, 801–810. Hashimoto, T., Volk, D.W., Eggan, S.M., Mirnics, K., Pierri, J.N., Sun, Z., et al., 2003. Gene expression deficits in a subclass of GABA neurons in the prefrontal cortex of subjects with schizophrenia. J. Neurosci. 23, 6315–6326. Hasselmo, M.E., Bodelon, C., Wyble, B.P., 2002. A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Comput. 14, 793–817. Hill, R.A., van den Buuse, M., 2011. Sex-dependent and region-specific changes in TrkB signaling in BDNF heterozygous mice. Brain Res. 1384, 51–60. Hudson, M.R., Rind, G., O'Brien, T.J., Jones, N.C., 2016. Reversal of evoked gamma oscillation deficits is predictive of antipsychotic activity with a unique profile for clozapine. Transl. Psychiatry 6, e784. Jackson, M.R., Lee, K., Mattiske, T., Jaehne, E.J., Ozturk, E., Baune, B.T., et al., 2017. Extensive phenotyping of two ARX polyalanine expansion mutation mouse models that span clinical spectrum of intellectual disability and epilepsy. Neurobiol. Dis. 105, 245–256. Javitt, D.C., 2009. When doors of perception close: bottom-up models of disrupted cognition in schizophrenia. Annu. Rev. Clin. Psychol. 5, 249–275. Jones, N.C., Anderson, P., Rind, G., Sullivan, C., van den Buuse, M., O'Brien, T.J., 2014. Effects of aberrant gamma frequency oscillations on prepulse inhibition. Int. J. Neuropsychopharmacol. 17, 1671–1681. Katona, L., Lapray, D., Viney, T.J., Oulhaj, A., Borhegyi, Z., Micklem, B.R., et al., 2014. Sleep and movement differentiates actions of two types of somatostatin-expressing GABAergic interneuron in rat hippocampus. Neuron 82, 872–886. Katsarou, A.M., Moshe, S.L., Galanopoulou, A.S., 2017. Interneuronopathies and their role in early life epilepsies and neurodevelopmental disorders. Epilepsia Open 2, 284–306. Kelsom, C., Lu, W., 2013. Development and specification of GABAergic cortical interneurons. Cell Biosci. 3, 19. Kentner, A.C., Bilbo, S.D., Brown, A.S., Hsiao, E.Y., McAllister, A.K., Meyer, U., et al., 2018. Maternal immune activation: reporting guidelines to improve the rigor, reproducibility, and transparency of the model. Neuropsychopharmacology. Kircher, M., Witten, D.M., Jain, P., O'Roak, B.J., Cooper, G.M., Shendure, J., 2014. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315. Kitamura, K., Yanazawa, M., Sugiyama, N., Miura, H., Iizuka-Kogo, A., Kusaka, M., et al., 2002. Mutation of ARX causes abnormal development of forebrain and testes in mice and X-linked lissencephaly with abnormal genitalia in humans. Nat. Genet. 32, 359–369. Kwon, J.S., O'Donnell, B.F., Wallenstein, G.V., Greene, R.W., Hirayasu, Y., Nestor, P.G., et al., 1999. Gamma frequency-range abnormalities to auditory stimulation in schizophrenia. Arch. Gen. Psychiatry 56, 1001–1005. Le Magueresse, C., Monyer, H., 2013. GABAergic interneurons shape the functional maturation of the cortex. Neuron 77, 388–405. Leicht, G., Kirsch, V., Giegling, I., Karch, S., Hantschk, I., Moller, H.J., et al., 2010. Reduced early auditory evoked gamma-band response in patients with schizophrenia. Biol. Psychiatry 67, 224–231. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., et al., 2009. The

We link an epidemiologically identified risk factor for schizophrenia, maternal immune activation, with disruptions to transcripts critical to GABAergic cell migration, long term changes to protein levels of GABAergic subtypes, and reduced gamma and theta power during sensorimotor gating testing. We identified that the Arx gene, critical to interneuron development, is disrupted both in our animal model as well as in some patients with schizophrenia disorders, suggesting the ARX gene may play a critical role in the prenatal origins of GABAergic dysfunction in schizophrenia. Future studies should be directed towards the recovery of altered Arx expression at various developmental stages to prevent disturbed interneuron function and behaviour. Funding This study was supported by a NARSAD Young Investigator Award to R.A.H. and a Monash University internal grant. R.A.H. is supported by a National Health and Medical Research Council Career Development (R.D. Wright) Fellowship. J.P.N. is supported by an Australian Rotary Health scholarship. M.N. is supported by an NHMRC CJ Martin fellowship. X.D. is supported by an NHMRC/ARC dementia fellowship. N.J. is supported by an Australian Research Council Future fellowship. The behavioural neuroscience laboratory are supported by ‘One in Five’, philanthropic organization. Data obtained from the Australia Schizophrenia Research Bank are supported by a NSW Health Sydney Genomics Collaborative Grants Program (2015). Translational genomics for schizophrenia: Using whole genome sequencing to define the network architecture for personalized interventions. CIs: Cairns MJ, Green MJ, Carr VC. $800,000, as well as NHMRC project grant (grant number APP1051673). The Authors have declared that there are no conflicts of interest in relation to the subject of this study. Acknowledgements We would like to acknowledge the support from the Monash Health Translation Precinct genomics facility. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.bbi.2019.06.009. References Bakshi, V.P., Swerdlow, N.R., Geyer, M.A., 1994. Clozapine antagonizes phencyclidineinduced deficits in sensorimotor gating of the startle response. J. Pharmacol. Exp. Ther. 271, 787–794. Basta-Kaim, A., Budziszewska, B., Leskiewicz, M., Fijal, K., Regulska, M., Kubera, M., et al., 2011. Hyperactivity of the hypothalamus-pituitary-adrenal axis in lipopolysaccharide-induced neurodevelopmental model of schizophrenia in rats: effects of antipsychotic drugs. Eur. J. Pharmacol. 650, 586–595. Bitanihirwe, B.K., Peleg-Raibstein, D., Mouttet, F., Feldon, J., Meyer, U., 2010. Late prenatal immune activation in mice leads to behavioral and neurochemical abnormalities relevant to the negative symptoms of schizophrenia. Neuropsychopharmacology 35, 2462–2478. Brown, A.S., Derkits, E.J., 2010. Prenatal infection and schizophrenia: a review of epidemiologic and translational studies. Am. J. Psychiatry 167, 261–280. Buervenich, S., Carmine, A., Arvidsson, M., Xiang, F., Zhang, Z., Sydow, O., et al., 2000. NURR1 mutations in cases of schizophrenia and manic-depressive disorder. Am. J. Med. Genet. 96, 808–813. Chaumette, B., Kebir, O., Pouch, J., Ducos, B., Selimi, F., I. s. group, et al., 2018. Longitudinal analyses of blood transcriptome during conversion to psychosis. Schizophr. Bull. Cho, Kathleen K.A., Hoch, R., Lee, Anthony T., Patel, T., Rubenstein, John L.R., Sohal, Vikaas S., 2015. Gamma rhythms link prefrontal interneuron dysfunction with cognitive inflexibility in Dlx5/6+/− mice. Neuron 85, 1332–1343. Cingolani, P., Platts, A., Wang le, L., Coon, M., Nguyen, T., Wang, L., et al., 2012. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80–92. Cobos, I., Calcagnotto, M.E., Vilaythong, A.J., Thwin, M.T., Noebels, J.L., Baraban, S.C.,

10

Brain, Behavior, and Immunity xxx (xxxx) xxx–xxx

J.P. Nakamura, et al.

Schizophrenia Working Group of the Psychiatric Genomics, C., 2014. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427. Schroeder, A., Hudson, M., Du, X., Wu, Y.W., Nakamura, J., van den Buuse, M., et al., 2017. Estradiol and raloxifene modulate hippocampal gamma oscillations during a spatial memory task. Psychoneuroendocrinology 78, 85–92. Simonet, J.C., Sunnen, C.N., Wu, J., Golden, J.A., Marsh, E.D., 2015. Conditional loss of Arx from the developing dorsal telencephalon results in behavioral phenotypes resembling mild human ARX mutations. Cereb. Cortex 25, 2939–2950. Smith, S.E.P., Li, J., Garbett, K., Mirnics, K., Patterson, P.H., 2007. Maternal immune activation alters fetal brain development through interleukin-6. J. Neurosci. 27, 10695–10702. Spencer, K.M., 2011. Baseline gamma power during auditory steady-state stimulation in schizophrenia. Front. Hum. Neurosci. 5, 190. Stromme, P., Mangelsdorf, M.E., Scheffer, I.E., Gecz, J., 2002. Infantile spasms, dystonia, and other X-linked phenotypes caused by mutations in Aristaless related homeobox gene, ARX. Brain Dev. 24, 266–268. Sullivan, P.F., Kendler, K.S., Neale, M.C., 2003. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch. Gen. Psychiatry 60, 1187–1192. Swerdlow, N.R., Light, G.A., Sprock, J., Calkins, M.E., Green, M.F., Greenwood, T.A., et al., 2014. Deficient prepulse inhibition in schizophrenia detected by the multi-site COGS. Schizophr. Res. 152, 503–512. Uhlhaas, P.J., Pipa, G., Neuenschwander, S., Wibral, M., Singer, W., 2011. A new look at gamma? High- (> 60 Hz) gamma-band activity in cortical networks: function, mechanisms and impairment. Prog. Biophys. Mol. Biol. 105, 14–28. van den Buuse, M., 2010. Modeling the positive symptoms of schizophrenia in genetically modified mice: pharmacology and methodology aspects. Schizophr. Bull. 36, 246–270. van den Buuse, M., Wischhof, L., Lee, R.X., Martin, S., Karl, T., 2009. Neuregulin 1 hypomorphic mutant mice: enhanced baseline locomotor activity but normal psychotropic drug-induced hyperlocomotion and prepulse inhibition regulation. Int. J. Neuropsychopharmacol. 12, 1383–1393. Volk, D.W., Edelson, J.R., Lewis, D.A., 2016. Altered expression of developmental regulators of parvalbumin and somatostatin neurons in the prefrontal cortex in schizophrenia. Schizophr. Res. 177, 3–9. Volk, D.W., Lewis, D.A., 2013. Prenatal ontogeny as a susceptibility period for cortical GABA neuron disturbances in schizophrenia. Neuroscience 248, 154–164. Vuillermot, S., Feldon, J., Meyer, U., 2011. Nurr1 is not essential for the development of prepulse inhibition deficits induced by prenatal immune activation. Brain Behav. Immun. 25, 1316–1321. Vuillermot, S., Weber, L., Feldon, J., Meyer, U., 2010. A longitudinal examination of the neurodevelopmental impact of prenatal immune activation in mice reveals primary defects in dopaminergic development relevant to schizophrenia. J. Neurosci. 30, 1270–1287. Wang, A.Y., Lohmann, K.M., Yang, C.K., Zimmerman, E.I., Pantazopoulos, H., Herring, N., et al., 2011. Bipolar disorder type 1 and schizophrenia are accompanied by decreased density of parvalbumin- and somatostatin-positive interneurons in the parahippocampal region. Acta Neuropathol. 122, 615–626. Wang, X., Pinto-Duarte, A., Behrens, M.M., Zhou, X., Sejnowski, T.J., 2018. Ketamine independently modulated power and phase-coupling of theta oscillations in Sp4 hypomorphic mice. PLoS ONE 13, e0193446. Wichniak, A., Okruszek, L., Linke, M., Jarkiewicz, M., Jedrasik-Styla, M., Ciolkiewicz, A., et al., 2015. Electroencephalographic theta activity and cognition in schizophrenia: preliminary results. World J. Biol. Psychiatry 16, 206–210. Womelsdorf, T., Fries, P., 2006. Neuronal coherence during selective attentional processing and sensory-motor integration. J. Physiol. Paris 100, 182–193. Xenos, D., Kamceva, M., Tomasi, S., Cardin, J.A., Schwartz, M.L., Vaccarino, F.M., 2017. Loss of TrkB signaling in parvalbumin-expressing basket cells results in network activity disruption and abnormal behavior. Cereb. Cortex 1–15. Xing, G., Zhang, L., Russell, S., Post, R., 2006. Reduction of dopamine-related transcription factors Nurr1 and NGFI-B in the prefrontal cortex in schizophrenia and bipolar disorders. Schizophr. Res. 84, 36–56. Zhang, Z.J., Reynolds, G.P., 2002. A selective decrease in the relative density of parvalbumin-immunoreactive neurons in the hippocampus in schizophrenia. Schizophr. Res. 55, 1–10.

sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079. Li, J., Cai, T., Jiang, Y., Chen, H., He, X., Chen, C., et al., 2016. Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database. Mol. Psychiatry 21, 298. Luoni, A., Richetto, J., Longo, L., Riva, M.A., 2017. Chronic lurasidone treatment normalizes GABAergic marker alterations in the dorsal hippocampus of mice exposed to prenatal immune activation. Eur. Neuropsychopharmacol. 27, 170–179. Malt, E.A., Juhasz, K., Malt, U.F., Naumann, T., 2016. A role for the transcription factor Nk2 homeobox 1 in schizophrenia: convergent evidence from animal and human studies. Front. Behav. Neurosci. 10, 59. Marin, O., Yaron, A., Bagri, A., Tessier-Lavigne, M., Rubenstein, J.L., 2001. Sorting of striatal and cortical interneurons regulated by semaphorin-neuropilin interactions. Science 293, 872–875. Marsh, E.D., Nasrallah, M.P., Walsh, C., Murray, K.A., Nicole Sunnen, C., McCoy, A., et al., 2016. Developmental interneuron subtype deficits after targeted loss of Arx. BMC Neurosci. 17, 35. Maynard, T.M., Sikich, L., Lieberman, J.A., LaMantia, A.S., 2001. Neural development, cell-cell signaling, and the “two-hit” hypothesis of schizophrenia. Schizophr. Bull. 27, 457–476. McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., et al., 2010. The genome analysis toolkit: a MapReduce framework for analyzing nextgeneration DNA sequencing data. Genome Res. 20, 1297–1303. Meyer, U., Engler, A., Weber, L., Schedlowski, M., Feldon, J., 2008a. Preliminary evidence for a modulation of fetal dopaminergic development by maternal immune activation during pregnancy. Neuroscience 154, 701–709. Meyer, U., Feldon, J., Schedlowski, M., Yee, B.K., 2005. Towards an immuno-precipitated neurodevelopmental animal model of schizophrenia. Neurosci. Biobehav. Rev. 29, 913–947. Meyer, U., Nyffeler, M., Engler, A., Urwyler, A., Schedlowski, M., Knuesel, I., et al., 2006. The time of prenatal immune challenge determines the specificity of inflammationmediated brain and behavioral pathology. J. Neurosci. 26, 4752–4762. Meyer, U., Nyffeler, M., Yee, B.K., Knuesel, I., Feldon, J., 2008b. Adult brain and behavioral pathological markers of prenatal immune challenge during early/middle and late fetal development in mice. Brain Behav. Immun. 22, 469–486. Morris, H.M., Hashimoto, T., Lewis, D.A., 2008. Alterations in somatostatin mRNA expression in the dorsolateral prefrontal cortex of subjects with schizophrenia or schizoaffective disorder. Cereb. Cortex 18, 1575–1587. Nagai, T., Kitahara, Y., Ibi, D., Nabeshima, T., Sawa, A., Yamada, K., 2011. Effects of antipsychotics on the behavioral deficits in human dominant-negative DISC1 transgenic mice with neonatal polyI: C treatment. Behav. Brain Res. 225, 305–310. Nakamura, T., Matsumoto, J., Takamura, Y., Ishii, Y., Sasahara, M., Ono, T., et al., 2015. Relationships among parvalbumin-immunoreactive neuron density, phase-locked gamma oscillations, and autistic/schizophrenic symptoms in PDGFR-beta knock-out and control mice. PLoS ONE 10, e0119258. Notaras, M.J., Hill, R.A., Gogos, J.A., van den Buuse, M., 2017. BDNF Val66Met genotype interacts with a history of simulated stress exposure to regulate sensorimotor gating and startle reactivity. Schizophr. Bull. 43, 665–672. Oskvig, D.B., Elkahloun, A.G., Johnson, K.R., Phillips, T.M., Herkenham, M., 2012. Maternal immune activation by LPS selectively alters specific gene expression profiles of interneuron migration and oxidative stress in the fetus without triggering a fetal immune response. Brain Behav. Immun. 26, 623–634. Price, M.G., Yoo, J.W., Burgess, D.L., Deng, F., Hrachovy, R.A., Frost Jr, J.D., et al., 2009. A triplet repeat expansion genetic mouse model of infantile spasms syndrome, Arx (GCG)10+7, with interneuronopathy, spasms in infancy, persistent seizures, and adult cognitive and behavioral impairment. J. Neurosci. 29, 8752–8763. Richetto, J., Calabrese, F., Meyer, U., Riva, M.A., 2013. Prenatal versus postnatal maternal factors in the development of infection-induced working memory impairments in mice. Brain Behav. Immun. 33, 190–200. Richetto, J., Calabrese, F., Riva, M.A., Meyer, U., 2014. Prenatal immune activation induces maturation-dependent alterations in the prefrontal GABAergic transcriptome. Schizophr. Bull. 40, 351–361. Sampaio, L.R.L., Borges, L.T.N., Silva, J.M.F., de Andrade, F.R.O., Barbosa, T.M., Oliveira, T.Q., et al., 2018. Average spectral power changes at the hippocampal electroencephalogram in schizophrenia model induced by ketamine. Fundam. Clin. Pharmacol. 32, 60–68.

11