Dysbindin-1 mutant mice implicate reduced fast-phasic ... - PNAS

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Dysbindin-1 mutant mice implicate reduced fast-phasic inhibition as a final common disease mechanism in schizophrenia Gregory C. Carlsona,1,2, Konrad Talbota,1, Tobias B. Halenea,b, Michael J. Gandala,b, Hala A. Kazia, Laura Schlossera, Quan H. Phunga, Raquel E. Gura, Steven E. Arnolda, and Steven J. Siegela,b a Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104-3403; and bTranslational Neuroscience Program, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104

DTNBP1 (dystrobrevin binding protein 1) is a leading candidate susceptibility gene in schizophrenia and is associated with working memory capacity in normal subjects. In schizophrenia, the encoded protein dystrobrevin-binding protein 1 (dysbindin-1) is often reduced in excitatory cortical limbic synapses. We found that reduced dysbindin-1 in mice yielded deficits in auditory-evoked response adaptation, prepulse inhibition of startle, and evoked γ-activity, similar to patterns in schizophrenia. In contrast to the role of dysbindin1 in glutamatergic transmission, γ-band abnormalities in schizophrenia are most often attributed to disrupted inhibition and reductions in parvalbumin-positive interneuron (PV cell) activity. To determine the mechanism underlying electrophysiological deficits related to reduced dysbindin-1 and the potential role of PV cells, we examined PV cell immunoreactivity and measured changes in net circuit activity using voltage-sensitive dye imaging. The dominant circuit impact of reduced dysbindin-1 was impaired inhibition, and PV cell immunoreactivity was reduced. Thus, this model provides a link between a validated candidate gene and an auditory endophenotypes. Furthermore, these data implicate reduced fast-phasic inhibition as a common underlying mechanism of schizophrenia-associated intermediate phenotypes.

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atients with schizophrenia have reduced amplitude and gating of auditory event-related potentials (ERPs) (1, 2). Recent clinical studies also show abnormal γ-band oscillations (30–100 Hz) as an endophenotype of the illness that is associated with reduced cognitive function (3–7). Work in animal models shows a prominent role of cortical inhibitory networks in generating γ-oscillations (8, 9), which in turn, supports the role of aberrant GABAergic inhibition as an important potential component of schizophrenia (4, 7, 10, 11). The GABA-producing enzyme glutamic acid decarboxylase is dysregulated in schizophrenia, and postsynaptic GABAA receptors are dysregulated as well (4). Risk alleles for GABAA receptor subunits are also associated with the disease (12, 13), although linkage is weaker than the linkage found with dysbindin-1 and other candidate genes such as DISC1 (14). At the anatomical level, there is a loss of immunoreactivity for parvalbumin (PV) in schizophrenia. PV is a calcium-binding protein marker for a class of fast-spiking GABAergic neurons. It is debated whether reduced PV in postmortem studies is caused by reduction in cell number or merely loss of protein expression. In either case, reduced PV immunoreactivity suggests disruption of an important source of local circuit inhibition (4, 15). Although clinical electrophysiological and postmortem anatomical findings support the role of GABA dysfunction in schizophrenia, a larger set of schizophrenia risk haplotypes are thought to confer reduced NMDA receptor-mediated function and changes in glutamatergic transmission [e.g., DISC1; Neuregulin 1 (NRG1), Damino acid oxidase activator (DAOA), and glutamate receptor, ionotropic, N-methyl D-aspartate 2B (GRIN2B)] (16–22) or dowww.pnas.org/cgi/doi/10.1073/pnas.1109625108

pamine insufficiency [e.g., catechol-O-methyltransferase (COMT); and dopamine receptors D2 and D4 (DRD2 and DRD4)] (23–25). Thus, the recent EEG intermediate phenotypes implicating a common disease mechanism of GABAergic dysfunction are disconnected from established genetic risk factors that lack compelling links to inhibitory dysfunction. DTNBP1 is a well-replicated vulnerability gene for schizophrenia, and it is thought to confer glutamatergic dysfunction when disrupted. DTNBP1 encodes the protein dystrobrevin-binding protein 1 (dysbindin-1) (26–28). More broadly, reduction in dysbindin-1 expression has been found in the schizophrenia population (16, 27, 29), indicating that reduced dysbindin-1 protein levels may be a common disease trait of schizophrenia. Haplotypes of DTNB1 associated with elevated protein expression are associated with enhanced working memory performance in humans (30), whereas risk haplotypes are associated with reduced spatial memory (31). This role for dysbindin-1 has been attributed to changes in excitatory drive, because dysbindin-1 is typically described as highly concentrated in a subset of glutamatergic synaptic vesicles and postsynaptic densities (30, 32, 33). In mice, a loss of function mutation in dysbindin-1 (Dys1−/−) disrupts both glutamatergic and dopaminergic neurotransmission in the hippocampal formation, which are associated with working memory deficits (34– 37). These findings indicate that disruptions of dysbindin-1 may play a direct role in abnormal hippocampal circuit behavior (16, 26, 32, 35, 37–39). What remains unclear is the extent to which reduced dysbindin-1 in mice has a role in other phenotypes characteristic of schizophrenia. Beyond the indicated role of dysbindin-1 in human and mouse hippocampal function, the hippocampus is an ideal system for the current study for several reasons, including that (i) it is a major source of γ-activity, (ii) it is a site of reduced PV interneuron immunoreactivity in schizophrenia (15, 40–42), and (iii) it is particularly well-suited to analyzing the role of disrupted inhibition. The present study tested auditory-evoked endophenotypes of schizophrenia and investigated local circuit GABAergic disruption in the hippocampus of Dys1−/− mice to determine if loss of dysbindin-1 also replicates auditory and EEG phenotypes common to schizophrenia as well as generating inhibitory cell disruptions proposed to underlie these intermediate phenotypes.

Author contributions: G.C.C., K.T., M.J.G., R.E.G., S.E.A., and S.J.S. designed research; G.C.C., K.T., T.B.H., M.J.G., H.A.K., L.S., and Q.H.P. performed research; M.J.G. and S.E.A. contributed new reagents/analytic tools; G.C.C., K.T., T.B.H., and M.J.G. analyzed data; and G.C.C. and S.J.S. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. 1

G.C.C. and K.T. contributed equally to this work.

2

To whom correspondence should be addressed. E-mail: [email protected].

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. 1073/pnas.1109625108/-/DCSupplemental.

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Edited by Leslie Lars Iversen, University of Oxford, Oxford, United Kingdom, and approved September 9, 2011 (received for review July 12, 2011)

Results Auditory Responses in the Dysbindin-1−/− Mouse. Auditory ERPs

were recorded after paired click stimuli (two white noise clicks given 500 ms apart), similar to the method performed for humans. Grand average waveforms (Fig. 1A) show mouse maximal positive deflection (P1) and maximal negative deflection (N1) peak amplitudes and gating in Dys1−/− mice and controls. Although there was no significant difference in P1 or N1 amplitudes between genotypes, there was a trend to a reduction in P1 amplitude in Dys1−/− mice (F1,21 = 3.86, P = 0.063). In contrast, sensory gating, which measures the ratio of peak amplitudes after second stimulus (S2) divided by the first stimulus (S1) response, was significantly reduced in Dys1−/− mice (F1, 21 = 4.8915, P = 0.038) (Fig. 1B). This trend to a reduction in the S1 P1 amplitude that likely drives the significant reduction in the S2/S1 ratio is consistent with the clinical observations, including a reduction in visually evoked P1 found in nonsymptomatic carriers of DTNBP1 risk alleles (43). To rule out the potential confound that such findings could be caused by differences in hearing threshold between WT and transgenic mice, an additional cohort of animals was tested for acoustic brainstem responses (ABRs; Fig. S1A). Results show no difference in hearing or subcortical auditory processing between groups (n = 4/group; P = 0.6) (Fig. S1B) (44). Thus, ERPs in these mice were consistent with reductions in the S2/S1 ratio reported in schizophrenia (45). Reduction of prepulse inhibition (PPI) of the acoustic startle response is a well-replicated endophenotype of schizophrenia. Dys1−/− mice showed a significant reduction in PPI (dysbindin-1−/−: 18.4 ± 10.36%; WT: 48.9 ± 7.64%; F1,30 = 5.05, P = 0.032) (Fig. 1D). There was no significant difference in startle amplitude, which further indicates that Dys1−/− mice in the current study lack gross auditory or motor deficits (Fig. 1C). These measures of auditory adaptation, combined with previous neurobehavioral studies in the

Fig. 2. γ-Power profile in Dys1−/− mice. (A and B) Time frequency plots constructed by averaging responses from dysbindin−/− (Dys−/−) and WT mice are shown in the 5- to 100-Hz frequency range for total power (dB) relative to prestimulus baseline. (C) Total power difference plot of γ-band activity (dysbindin−/− − WT) is masked to reveal significant differences (P < 0.05, corrected for multiple comparisons) that seem almost exclusively in the high γ-range of 60–100 Hz (dark gray). Dys1−/− mice show reduced early γ-power (∼60–100 Hz; blue) followed by later elevated late γ-power (∼60–100 Hz and 200–500 ms; orange). (D) Power in the high γ-range (60–100 Hz) was also calculated by fast-Fourier transform for each group. These results reflected the time frequency plotted data with reduced early high γ-power (bar; 30–70 ms, P = 0.05) and increased late high γ-power (bar over trace indicates periods with P = 0.03) in the Dys1−/− mice. There is a subbaseline reduction in power in the WT mice. The difference in late γ-power in the Dys1−/− mice, therefore, seemed to be because of a failure to suppress high γ-activity. (E) The early and late γ-alterations in Dys1−/− mice were not correlated (red dots, Dys1−/− animals; blue dots, WT animals), suggesting separate mechanisms for these two γ–band alterations.

Dys1−/− mice, indicate broad face validity for auditory endophenotypes common to schizophrenia (33).

Fig. 1. Auditory ERPs and PPI of startle in the Dys1−/− mouse model. (A) Grand average of paired ERPs showed similar component structure for WT (black trace) and Dys1−/− mice (red trace); these similarities included prominent P1, N1, and P2 components. There was no significant interaction between genotype and component amplitude. Calculating P1 − N1 also did not generate a significant interaction. (B) P1 − N1 is plotted for each animal (thin lines) and as group data (markers). There is a trend for a reduction in S1 between groups (P = 0.07). P1 − N1 responses from S1 were compared with the response of the S2 by taking the ratio of S2 over S1 (S2/S1). This S2/S1 ratio was reduced in the Dys1−/− mice relative to WT littermates (P = 0.03). (C) Startle responses were the same in both groups, indicating no confounding auditory or motor abnormalities. (D) PPI was reduced in Dys1−/− mice (P = 0.03).

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γ-Oscillations. Abnormalities in auditory-evoked γ-oscillatory activity have been observed in schizophrenia as well as other neuropsychiatric disorders such as autism (3, 7, 10, 46–48). To test for disruptions in oscillatory activity during the evoked response in the Dys1−/− mice, EEG trials were wavelet-transformed to extract instantaneous power and phase over all frequencies from θ to γ (4– 100 Hz) (Fig. 2 A and B). During the peak activation in both groups of mice (30–70 ms after stimulation), there is an increase in all frequencies measured (Fig. 2 A and B, orange and red) relative to the prestimulus baseline period. Between groups, there was a significant effect of genotype within the γ-band that was largely restricted to a frequency band of 60–100 Hz (high γ) (Fig. 2C, regions with P < 0.05 shown). Dys1−/− mice showed a reduction in high γ-power during the early time range (average = 30–70 ms, t22 = 1.89, P = 0.05) (Fig. 2C, dark blue cluster) and a relative increase in high γ-power at later time points (average = 250–350 ms, t22 = −2.39, P < 0.03) (Fig. 2C, orange). This difference in late γ-activity seemed to be because of a failure of Dys1−/− mice to generate suppression of γ-activity, which was characteristic of WT controls (Fig. 2D). Although the early and late oscillatory abnormalities occurred in the same frequency band, there was no correlation between changes in early and late high γ-activity across subjects (Fig. 2E), suggesting that different mechanisms underlie the distinct temporal changes in Dys1−/− mice. Carlson et al.

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γ-Phase Locking. The auditory stimuli used to generate the ERPs

can reset or phase lock oscillatory activity, producing increased phase coherence across trials. Reduced oscillatory phase coherence has been described as an endophenotype of schizophrenia (49, 50). To directly determine the phase relationship of γ-oscillations across trials, we calculated the phase-locking factor (PLF; i.e., intertrial coherence) of the time series data from each mouse. The resulting phase coherence was examined over time (Fig. 3A). These results showed several connected clusters of time frequency bins that were significantly different between groups (Fig. 3A, red areas show regions with P < 0.05), again located in the high γ-range. Dys1−/− mice showed significantly reduced PLF in these clusters. To confirm these results, average high (60–100 Hz) and low (30–60 Hz) γ-PLF values were also calculated from 30 to 70 ms for each mouse and compared between groups. Dys1−/− mice showed significantly reduced high γ-PLF compared with WT littermates (t22 = 2.14, P = 0.044), with no difference in the low γ-range (t22 = 0.91, P = 0.37) (Fig. 3). Correlation Analyses. To determine which, if any, of these measures was associated, we calculated Pearson correlation coefficients between time and frequency domain measures. There was a significant relationship between the early high γ-power and the high γ-PLF (R2 = 0.44, F1,22 = 17.15, P = 0.0004) (Fig. 4). This shared variance of 44% indicates that there is a strong relationship between PLF and power in the early high γ-activity. The initial reduction of high γ-PLF and power occurred in the same time window as the N1 (Fig. 1A), suggesting a potential interaction with N1 amplitude and S2/S1 ratio. Analyses confirmed that PLF and

power differences were correlated with the P1 − N1 amplitude (PLF: R2 = 0.50, F1,19 = 18.93, P = 0.0003; power: R2 = 0.31, F1,19 = 8.64, P = 0.008). Additionally, there was correlation between early high γ-power and PLF with P1 − N1 S2/S1 ratio (PLF: R2 = 0.48, F1,19 = 17.21, P = 0.0005; power: R2 = 0.54, F1,19 = 21.82, P = 0.0002) (Fig. 4). To identify if these relationships extended to other deficits in Dys1−/− mice, we tested for associations between PPI and the high γ-measures and found significant correlations between PPI and both PLF and high γ-activity (PLF: R2 = 0.32, F1,21 = 9.92, P = 0.0048; high γ-power: R2 = 0.30, F1,21 = 8.94, P = 0.007). Taken together, these data show a constellation of behavioral and sensory response measurements associated with changes in γ-power and PLF. The later-sustained γ-power differences did not correlate with P1 − N1, S2/S1 ratio, or PPI, providing additional evidence that the early high γ-activity represents a specific sensory response component, discreet from later high γ-activity. These findings provide support that across trial synchronization of early high γ-band activity has a unique role in schizophrenia-associated intermediate phenotypes. PV Cell Population Is Compromised in the Dys1−/− Mice. PV cells mediate γ-band activity (8, 9), and reduced PV immunoreactivity in inhibitory neurons is observed in schizophrenia (51–53). PV cells of the hippocampus are sparsely distributed, occurring primarily in stratum pyramidal, where they comprise up to 70% of the GABAergic neurons and a smaller portion of the interneurons in the adjoining areas of stratum oriens and stratum radiatum (Fig. 5 A–D) (54, 55). In the Dys1−/− mice, there was a significant decrease

Fig. 4. Early high γ-components correlate broadly with other auditory phenotypes. Linear correlation between early high γ-power and PLF were tested. Power and PLF were correlated (Upper, box 1). PLF and power also showed a significant association (P < 0.001 for all) with P1 − N1 S1 amplitude, P1 − N1 S2/S1 ratio, and PPI. In all cases, the Pearson’s R2 was between 0.30 and 0.50. These data associate the early high γ-band phenotype to other schizophrenia-associated auditory phenotypes in the Dys1−/− mice.

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Fig. 3. Reduced auditory-evoked γ-PLF in dysbindin−/− mice. (A) Average time frequency plots of PLF values (intertrial coherence) for Dys1−/− mice (n = 11) and WT littermates (n = 13). Corresponding plot of P values shows significant differences between groups (P < 0.05, corrected), with Dys1−/− mice showing several clusters of significantly decreased PLF in the γ-band. The greatest differences (red) were in the frequency band of high γ-band (dark gray; 60–100 Hz), and to a lesser extent (blue and green), these differences extended into the low γ-band (light gray; 30–60 Hz). (B) Average PLF values are shown in the (Upper) high (60–100 Hz) and (Lower) low (30–60 Hz) γ-band ranges for each group (average ± SE). In this analysis, Dys1−/− mice showed significantly reduced average phase locking from 30 to 70 ms in the high γ-range (bar over trace indicates periods with P < 0.05) but not in the low γ-band (bar over trace indicates periods with P = 0.37).

in the number of PV immunoreactive cells per millimeter squared in hippocampus CA1-3 without any consistent alteration in cell body size or the axon terminal fields of PV neurons in stratum pyramidal (Fig. 5 E–G). These abnormalities were evident in all CA fields, including CA1, where the number of PV-positive cells was also significantly reduced in the Dys1−/− mice (P = 0.028). In schizophrenia, such reductions in PV cell immunoreactivity are extensive throughout the forebrain. To test if differences in PV immunoreactivity were similarly expansive in the dysbindin-1 mouse model, immunoreactivity was also measured in auditory cortex. Indeed, both cell densities and optical densities of cellular immunoreactivity were decreased in the auditory cortex (P = 0.012 and P = 0.018, respectively) (Fig. S2). These findings indicate that PV cell-dependent changes in clinical neurophysiology may also be because of abnormalities in local circuitry encompassed by other forebrain areas, including the auditory cortex. Hippocampal Excitability in the Dys1−/− Mouse. Results from ana-

tomic and ERP studies in Dys1−/− mice mirror abnormalities commonly found in schizophrenia and indicate a role for disrupted inhibition. To test whether the dominant impact of reduced dysbindin-1 is on excitation or inhibition, we used voltagesensitive dye imaging (VSDI) in area CA1 of the hippocampus.

We focused on area CA1, because pyramidal cells in that region make up ∼90% of the neurons and provide a relatively pure readout of net circuit activity modulating the membrane voltage of the primary hippocampal output neurons. These pyramidal cells provide an especially clear view of inhibition. Because these cells do not generate recurrent excitation, afferent induced excitatory post-synaptic potentials (EPSPs) are followed nearly exclusively by locally generated feed-forward and feedback inhibitory post-synaptic potentials (IPSPs). Thus, CA1 IPSPs in the pyramidal cells form a temporally distinct and easily measurable VSDI inhibitory component of circuit function (56, 57). To assess differences in the circuit responses to afferent activity, compound population EPSPs and IPSPs were induced with a single 200-μs pulse to the Schaffer collaterals as they entered CA1, and images of the resultant responses were recorded at 1 kHz. VSDI of area CA1 showed an evoked fast depolarization that was followed by a rapid repolarization (Fig. 6 A–C), reflecting the response at the single-cell level (56, 58). As previously validated, these components were an AMPA/NMDA EPSP followed by a GABAergic IPSP (56). The EPSP/IPSP can be visualized spatially in snapshots of the averaged peak response of component (Fig. 6B) and temporally as traces of fluorescent changes (Δf/f0) over time (Fig. 6C). In WT mice, there is a clear activation of

Fig. 5. Reductions in PV cell immunoreactivity in the hippocampal formation in Dys1−/− mice. WT mice (A and B) show characteristic sparse distribution of PVimmunoreactive neurons within and proximal to the cell body layer of the hippocampus (CA1–3). In dysbindin mice, the density of PV cells is reduced (C and D). The borders of the three components of the hippocampal formation (hippocampus, dentate gyrus, and dorsal subiculum) have been outlined. Higher magnification views of the boxed areas in A and C are shown in B and D, respectively. The arrowed cells in D indicate reduced immunoreactivity of PV cells in Dys1−/− mice. Image analysis on all of the WT (n = 20) and Dys1−/− (n = 23) mice confirmed the reduction in cell density (E) and immunoreactivity (F) of PV cells in CA1–3 of dysbinidin-1−/− mice. (G) Cell body size was not significantly different. P values for comparisons on the left (L) and right (R) hippocampus are shown above each graph.


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a large portion of the stratum radiatum, which contains the Schaffer synapses, and to a lesser extent, strata oriens and lacunosum moleculare (Fig. 6) followed by a hyperpolarization (IPSP). No difference was seen in peak EPSP amplitude when WT (0.13 ± 0.013% Δf/f0; n = 6) mice were compared with Dys1−/− mice (0.11 ± 0.038% Δf/f0; n = 8) (Fig. 6D), showing no gross difference in excitatory response to a single stimulus. In contrast, Dys1−/− mice rarely produced a hyperpolarization (seven of eight animals) after the evoked EPSP. This lack of frank hyperpolarization produced a difference in peak inhibitory amplitude between groups within a time window of 30–40 ms after stimulation (Fig. 6 C Inset and D) (peak IPSP). On average, WT mice generated a peak hyperpolarization of −0.02 ± 0.002% Δf/f0 (n = 6). However, peak analysis produced a positive average value of 0.03 ± 0.01% Δf/f0 in Dys1−/− mice (n = 8, P = 0.048) (Fig. 6D), showing that inhibition was greatly reduced. In some cases, Dys1−/− mice showed an exponential decay to baseline (four of eight mice) that could be fitted to generate a decay time constant (τ) (Fig. 5C Inset). The remaining Dys1−/− mice did not show an exponential decay characteristic of normal CA1-evoked activity, indicating more severe dysregulation. To capture this prolongation of the EPSP and allow comparison with the exponential fitted decays, the decay τ in these mice was calculated as the time point equivalent to 63% of peak amplitude. The average Dys1−/− EPSP took more than 20 times as long to Carlson et al.

approach the baseline of τ = 142.8 ± 76.07 ms compared with the rapid decay of τ = 6.7 ms in the WT mice (P = 0.0011) (Fig. 5D, decay τ). In the subset of Dys1−/− mice with EPSP kinetics that enabled exponential fitting, the decay τ was nevertheless double the value in WT mice (τ = 14.3 ± 2.33 ms vs. WT τ = 6.7 ± 0.77 ms, P = 0.013) (Fig. 6D, expanded). This prolonged initial repolarization is attributable to a reduction or change in kinetics of the evoked fast inhibitory circuit activity (56, 59). Thus, VSDI shows that disinhibition is the primary net circuit alteration in CA1of Dys1−/− mice, and specifically, it implicates a disruption in fast feed-forward inhibition. Discussion Dys1−/− mice show face validity for auditory-evoked response endophenotypes characteristic of schizophrenia, including reduced amplitude and reduced S2/S1 ratio of P1 − N1 responses. These mice also show a reduction in PPI, supporting a broad auditory processing phenotype also associated with schizophrenia. Analysis of EEG responses in the spectral domain shows a reduction in early phase-locked high γ-activity in the Dys1−/− mice followed by reduced suppression of late γ-activity. Although the reduction in early γ-power and lack of late γ-suppression are both associated with reduced dysbindin-1, correlation analysis provided an indication that they are independent phenomena. PNAS Early Edition | 5 of 9

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Fig. 6. Inhibition but not excitation is reduced in the Dys1−/− mice. (A) Evoked responses were recorded using VSDI from hippocampal slices. The green box in A shows the area displayed in the snapshot in WT (B). Stimulation at ∼90% of maximum produced spatially broad activation as shown in the snapshot averaging 5 ms over the peak of the response (B, red and yellow). In WT animals, depolarization was often replaced by a frank hyperpolarization 30 ms after stimulation (WT, blue). However, the depolarization persisted in Dys1−/− mice (Dys−/−, red and yellow). (C) This difference in the kinetics of the evoked compound potential between Dys1−/− and WT mice was also reflected in traces describing change in fluorescence over stratum radiatum. Here, two different stimulation intensities (∼90% of max in Upper and ∼20% of max in Lower) generated a pronounced EPSP/IPSP in slices from the WT mouse (black trace) and a prolonged depolarization in the Dys1−/− mouse (red trace). Not all slices from Dys1−/− mice showed such prolonged depolarization. Inset shows data from another animal that generated an EPSP whose decay can be fit with an exponential decay curve (red trace showing fitted curve). Nevertheless, the decay was much slower than in the EPSP recorded from a WT mouse (blue trace). (D) The findings illustrated in the representative traces are reflected in the group data. The initial excitation forming the peak of the EPSP was not different between groups, but the peak hyperpolarizing response between 30 and 40 ms after stimulation (magenta band in C Inset) showed an average change in sign from hyperpolarizing in WT to depolarizing in Dys1−/− mice (peak IPSP; P = 0.048). The greatest difference between groups was the length of the EPSP, which was reflected in the group differences of decay time constants (decay τ). EPSP decays in one-half of the Dys1−/− mice (four of eight) could be fit with an exponential. Thus, group τ was analyzed in two ways. WT τ was compared with a 63% reduction to baseline from peak amplitude for all Dys1−/− mice (Dys−/− ; P = 0.0011) or with the subset of slices from Dys1−/− mice (four of eight) that returned to baseline with an exponential decay (Dys−/−′; P = 0.013). An expansion of the bar graph highlights the differences between WT and Dys−/−′. DG, dentate gyrus; oriens, strata oriens; sl.m., lacunosum molecular; sp., pyramidal, sr., radiatum; Sub, subiculum.

Measures of high γ-PLF and power in the early time window were correlated with P1 − N1 amplitude, S2/S1 ratio, and PPI. Thus, a common mechanism may underlie this constellation of auditory endophenotypes. Notably, in both ERP and in vitro VSDI data, measures with known or proposed reliance on inhibition were predominantly impacted by genotype. In contrast, there was no significant effect on excitatory measures such as ERP or VSDI EPSP amplitudes. Thus, despite the proposed involvement of dysbindin-1 with glutamatergic transmission (16, 27, 35), the reduced effectiveness of hippocampal inhibitory circuitry to rapidly repolarize the principal neurons was the dominant effect. The immunological results indicate that this loss of fast feed-forward inhibitory input likely involves the disruption of PV basket cell activity in the Dys1−/− mice, but there are a number of non-PV inhibitory cells that can also contribute fast feed-forward inhibition. Additional work is needed to dissect PV-specific effects from more general disruption of inhibitory activity to which PV cells likely contribute. Also, these findings exclude a role for disrupted glutamate release in the development of such circuit abnormalities. Indeed, several models suggest disruption of excitatory input into inhibitory neurons as a cause of reduced PV immunoreactivity (60–62). The shared association between PV cell disruption and the described auditory phenotypes in schizophrenia as well as the Dys1−/− mice indicates that understanding the mechanisms leading to PV dysregulation may be critical to understanding the development of schizophrenia-associated endophenotypes. Role of Disrupted Fast-Phasic Inhibition in Reduced γ-Power and PLF in the Dys1−/− Mouse. γ-Band oscillations in the hippocampus are

generated in CA3 and entorhinal cortex, and they are propagated into CA1 by inhibitory networks (42). This propagation generates broad γ-coherence throughout the hippocampal formation (41). Changes in fast CA1 inhibition are likely to be measured at EEG electrodes as changes in high-frequency components. A subset of inhibitory interneurons in CA1 produces fast-phasic inhibition. These interneurons include the majority of PV cells but also a number of non–PV-positive cell types. In response to afferent sensory input, these interneurons can produce a brief but intense shunting of conductance to principle cells in the hippocampus and other cortical structures. In the midst of excitation, this inhibition produces a strong circuit-dependent repolarization of postsynaptic targets. In vivo, this strong perisomatic GABAergic input can induce fast changes in polarity along the long axis of the neurons and gate cell firing at the high γ-frequencies (50), which we found disrupted in the Dys1−/− mouse. Potential Role for PV Cells. There are a number of characteristics that suit PV cells to mediating the inhibitory component of evoked and phase-locked γ-activity. First, PV cells respond with high reliability to initial but not to repeated afferent input (63, 64). Second, PV cells generate a high-amplitude synchronous compound input that is well-positioned to limit action potentials because of their profuse synaptic innervations of cell bodies (creating the basket-like appearance around the soma when visualized) or axon initial segments (65). Third, GABAA receptors opposite PV cell terminals produce very rapid rising and decaying IPSCs. Loss of PV immunoreactivity because of a reduction in PV expression and actual loss of PV-positive cells has been implicated in a number of neuropsychiatric diseases and models associated with schizophrenia (65–68). Although both are considered markers for loss of appropriate inhibition, it remains a matter of contention whether loss of PV protein or loss of the PV cells themselves generates the decreased immunoreactivity observed in the disease state. It also remains possible that reduced PV immunoreactivity is a marker of broad inhibitory and circuit deficits involved in the loss of fastphasic inhibition and that other non–PV-positive interneurons are involved. 6 of 9 | www.pnas.org/cgi/doi/10.1073/pnas.1109625108

Linking γ-Band Abnormalities to Features of Schizophrenia. There has been strong interest in γ-band changes predicting other abnormalities associated with schizophrenia (7, 50). Such a link between γ-associated inhibitory mechanisms and schizophrenia-associated behavioral phenotypes is also reflected in our data. In particular, auditory-evoked high γ-activity correlated with both PPI and auditory S2/S1 ratio. Recent intracerebral recordings in humans have also associated hippocampal γ-activity with working memory capacity, and working memory is a behavior disrupted in the Dys1−/− mouse (33, 47, 48, 69). Thus, by extension, our findings suggest that γ-abnormalities may be associated with the working memory deficits found in the Dys1−/− mouse. Because working memory deficits are a treatment-refractory symptom of schizophrenia, such relationship between the intermediate γ-phenotype and working memory should be directly tested in the Dys1−/− mouse. We found that PV immunoreactivity was reduced in other areas of hippocampus and cortex, which was found in the human schizophrenia population. This finding signals that the reduction in evoked γ-activity and phase locking in Dys1−/− mice and its potential role in schizophrenia-associated symptoms are likely compounded by a global disruption of inhibition in those areas. Potential Mechanisms of Reduced Dysbindin-1 in Hippocampal Disinhibition. There are multiple lines of evidence linking dysbin-

din-1 and other genetic risk haplotypes to reduced glutamatergic transmission as well as reduced excitatory drive to inhibitory dysfunction (16, 18, 27, 32, 33, 38, 39, 62, 70). Specifically, pharmacological reduction of NMDA activity through ketamine is a model of induced forms of psychosis, and chronic ketamine causes reductions in PV cells in the hippocampus and neocortex (60, 61, 70, 71). Thus, the role of reduced glutamatergic transmission through NMDA hypofunction is a converging hypothesis in the development of schizophrenia that may be modeled by the present work. Alternatively, dysbindin-1 is also found in PVpositive neurons, and recent work has indicated a direct role for dysbindin in NMDA receptor trafficking (16, 34, 72). Therefore, dysbindin-1 may impact NMDA activity in interneurons both preand postsynaptically. Such a combined impact on NMDA function may be important for overcoming compensatory mechanisms seeking to maintain appropriate inhibitory activity in the brain. Current data strongly support the hypothesis that common risk factors such as reduced dysbindin-1 as well as its genetic risk alleles (DTNBP1) converge through developmental cascades to disrupt fast-phasic inhibition, including PV cells. Such loss of evoked fastphasic inhibition in turn likely leads to disrupted evoked γ-band activity (Fig. 7). Previous clinical studies show abnormal EEG γ-band activity and postmortem evidence of disrupted PV cell immunoreactivity in schizophrenia. The present data now uniquely link dysbindin-1 to a large set of schizophrenia-associated auditory endophenotypes and replicate the reductions in PV in the dysbindin-1 mouse model. These findings establish disrupted fastphasic inhibitory circuit activity involving PV cells as a strong candidate for a common final disease mechanism involved in schizophrenia-associated auditory phenotypes. Methods Animals. All mouse experiments where performed in male and female Dys1−/− and WT littermate mice. The original Dys1−/− mouse occurred as a spontaneous mutation on the DBA/2J background, which was identified by coat color, and thus, these mice are commonly named Sandy (73). Mice were produced on site by breeding the original Dys1−/− mice on DBA/2J background with pure C57/B6 mice for eight generations. Their breeding and behavioral phenotypes have been described in ref. 33. All experiments were performed during their light cycle when they were 3–6 mo of age. All protocols for their care and testing were performed in accordance with University Laboratory Animal Resources guidelines and approved by the Institutional Animal Care and Use Committee.

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Fig. 7. Proposed impact of dysbindin-1–related reduction of PV cell inhibition on γ-oscillations. A illustrates a subset of feed-forward and feedback somatically targeted inhibitory neurons in area CA1. PV cells make up more than half the basket cells in area CA1, and are less then 5% of all CA1 neurons. B illustrates the loss of PV cell activity in the Dys1−/− mouse as shown in Fig 5. (C) PV cells generate a rapid hyperpolarization that is consistent over trials in WT mice. (D) Loss or reduced PV cell function can impact the kinetics of these summed measures by reducing inhibition in all cells and increasing the variance across trials. Note that, as in our data, EPSP amplitude is not affected, but the slope of the average decay time constant (τ) is affected, which is shown in Fig. 6. (E) Activity of pyramidal neurons in the hippocampus needs to be gated either by fast repolarization or PV cell-dependent shunting to support γ-oscillations. The ability of the circuit to generate such rapid activity is reflected by the decay time constant of the net EPSP. To compare EPSP kinetics to the frequency of γ-band activity, we overlaid exponential traces described by the decay time constants of EPSPs in WT and Dys1−/− mice onto waves representing high (90 Hz) and low (30 Hz) γ-oscillations. E illustrates that pyramidal cell activity would be less able to contribute to the high γ-oscillations in the dysbindin-1−/− mice. Thus, loss of PV interneurons likely contributes to the specific reduction in sensoryevoked high γ-band power and across trial coherence in the hippocampus (shown in Figs. 2 and 3).

Genotyping. Tail snips from all animals were genotyped using a duplex PCR procedure yielding PCR products across the deleted DTNBP1 segment in Dys1−/− mice (73). They were weaned at postnatal day 21, and testing began during their light cycle when they were 3–6 mo of age. Electrode Implantation. Sandy homozygous mice (dysbindin-1−/−; n = 12) and WT littermates matched for age and sex (n = 11) underwent stereotaxic implantation of electrodes. Animals were anesthetized with isoflurane for surgeries. Positive electrodes were placed in the right hippocampal region 1.8 mm posterior, 2.65 mm right lateral, and 2.75 mm deep relative to bregma (junction of the sagittal and coronal sutures used as surgical point of reference for positive, negative, and ground electrode). Negative electrodes were placed adjacent to positive and ground electrodes on the ipsilateral cortex at 0.2 mm anterior, 2.75 mm lateral, and 0.75 mm deep. Ground electrodes were located between positive and negative electrodes on the ipsilateral cortex at 0.8 mm posterior, 2.75 mm lateral, and 0.75 mm deep. The electrode pedestal was secured to the skull with ethyl cyanoacrylate (Loctite; Henkel) and dental cement (Ortho Jet; Lang Dental). This recording paradigm can replicate clinical auditory ERP findings in humans that are primarily sourced to the cortex (11, 21, 41, 70, 74–76). Amplitude and Habituation Studies. The recording of brain activity for auditory ERPs was performed 2 wk after the electrode implantation. Each animal was placed in its home cage in a sound-attenuated Faraday recording chamber. Background white noise was at 65 dB. Electrode pedestals were

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Time Frequency Analyses. Time frequency decomposition of auditory-evoked potentials was performed with the EEGLAB toolbox in Matlab (70, 79). Dys1−/− (n = 11) and WT littermate (n = 12) mice were included in time frequency decomposition studies. Single trial epochs between −0.2 and 0.6 s relative to the first auditory white noise stimulus (S1) were extracted from data sampled at 1,667 Hz. For each epoch, total power (event-related spectral perturbation) and PLF values (intertrial coherence) were calculated using Morlet wavelets in 50 linearly spaced frequency bins between 5 and 100 Hz, with wavelet cycles linearly increasing from three to six cycles. Total power was calculated in decibels relative to baseline power (−200 to 0 ms) in each frequency band. PLF is expressed as a unitless ratio between zero and one, where one represents complete phase synchrony at a given frequency and time across trials. Significance for total power and PLF differences between the group-derived time frequency graphs was assessed by unpaired t tests at each time frequency bin. Correction for multiple comparisons was achieved using a nonparametric permutation bootstrap method as implemented in EEGLAB using 500 permuted samples. The permutation bootstrap method involves pooling all of the single-subject 2D time frequency images from both groups, randomly shuffling, and partitioning the pooled samples into two random groups of the same size as the initial comparison. Unpaired t tests are then conducted between these two randomly chosen groups at each time frequency bin, and the maximum t statistic is retained. Repeating this procedure 500 times generates a distribution of t statistics. One can then compare t statistics from the original group comparisons with this permuted bootstrap distribution, retaining any points that have P values less than 0.05. Such correction for multiple comparisons has been commonly used in the neuroimaging community (80). Additionally, PLF values were calculated from 30 to 70 ms poststimulus in the high (60–100 Hz) and low (30–60 Hz) γ-frequency ranges, and group significance was assessed with unpaired t tests. To examine shared variance between measures, Pearson’s correlation coefficients were calculated over all subjects. Significance for these two sets of measures was assessed by ANOVA. ABRs. ABRs were recorded to determine hearing thresholds in adult Dys−/− and WT mice (n = 4/group). Electrode implantation and recordings were performed as previously published (44). Stimuli consisted of 4,000 white noise clicks (0.1-ms duration, 125 ms interstimulus interval, alternating polarity) sampled at 10 kHz that were repeated at decreasing intensities from 85 to 50 dB (background SPL). Recordings were filtered 100–500 Hz offline (Digital IIR filter, butterworth bandpass order 4). Grand averages were then created from −50 to 50 ms poststimulus and baseline corrected from −40 to −10 ms. Thresholds were compared between groups by computing the maximal rms amplitude from 0 to 10 ms poststimulus and plotting them as a function of stimulus intensity (Fig. S1). Statistical significance was assessed by repeated measures ANOVA, which indicated that groups did not differ in hearing threshold (group: F1,66 = 0.31, P = 0.6; group × intensity: F11,66 = 0.4, P = 0.95). Startle Response and PPI. After being tested for auditory ERPs and auditoryevoked γ-band oscillations, the 12 Dys1−/− mice and 11 WT littermates were tested for startle and PPI to acoustic white noise stimuli as previously described (81). For startle quantified with an accelerometer, each mouse was first placed in a test chamber, allowed a 5-min acclimation period with background white noise at 60 dB, and then exposed to a pretest block of five 120-dB startle pulses. During the next 10 min, startle was measured in response to 40 ms white noise at 0, 90, 95, 100, 110, 115, and 120 dB, each presented five times in random order with interstimulus intervals randomized from 10 to 20 s. These startle tests were followed by PPI trials. These trials consisted of a 20-ms prepulse stimulus 4, 8, or 16 dB above background noise (60 dB) followed 100 ms later by a 40-ms pulse of a 120-dB startle


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connected to a 30-cm tripolar electrode cable that exited the chamber to connect to a high-impedance differential AC amplifier (A-M Systems). Recording sessions were preceded by a 15-min acclimation phase. Auditory ERPs were recorded as described earlier (77, 78). Stimuli were generated by Micro 1401 hardware with Spike 5 software (Cambridge Electronic Design) and delivered through speakers attached to the cage top. A series of 150 paired stimuli was presented to drug naïve animals first (1,500 Hz, 85 dB sound pressure, 10-ms duration presented 500 ms apart with a 9-s interstimulus interval). P1 (10–30 ms) and N1 (25–60 ms) amplitudes were determined for S1 and S2 response using repeated measures ANOVA. Significant main effects were followed by Fisher least significant difference posthoc comparisons. An overall measure of sensory adaptation was calculated using a ratio of response for the P1 − N1 for S2 divided by the response to S1 (S2/S1 ratio) and evaluated using a one-way ANOVA.

stimulus. There were five trials with each prepulse intensity. Ten trials with startle pulses only were presented in random order. Immunohistochemistry and in Situ and Image Analyses. Dys1−/− mice (11 female and 11 male) and WT littermates (12 female and 11 male) were used for immunohistochemical analysis. These animals were anesthetized with sodium pentobarbital (1.0 mg/kg) and then perfused transcardially with saline followed by 4% formaldehyde. Their brains were postfixed in the same fixative overnight, embedded in paraffin, and sectioned coronally at 6 μm. After mounting on slides, dried sections were reacted immunohistochemically for PV with mouse monoclonal antibody P3088 (1:1,000 dilution; Sigma-Aldrich) with a standard avidin-biotin-peroxidase method using nickel sulfate intensification of the DAB reaction product. Within hippocampal field CA1 of the dorsal hippocampus at the level of plates 44–48 in the mouse brain atlas of Franklin and Paxinos (82), PV cell immunoreactivity, number, density, and cell body size were determined at 100× using Image ProPlus software (Media Cybernetics). The same approach was repeated for the auditory cortex. Unpaired t tests were used to evaluate differences between the Dys1−/− mice and WT littermates, with P < 0.05 significance.

ficial cerebral spinal fluid (ACSF) sucrose (130 mM sucrose, 3 mM KCl, 1.25 mM NaHPO4, 1 mM MgCl2, 2 mM CaCl2, 26 mM NaHCO3, 10 mM dextrose), where NaCl is replaced with sucrose. Hippocampal slices (350 μm) were cut at 12° off horizontal with a vibrating tissue slicer (VT1000S; Leica), transferred to a static interface chamber (34 °C) for 30 min, and then stored at room temperature for up to 6 h. In Vitro VSDI. Slices were stained with 0.125 mg/mL JPW 3031 (gift from Leslie Loew and Joe Wuskell, Farmington, CT) in artificial CSF for 10 min and imaged in an oxygenated interface chamber (34 °C) using an 80 × 80 CCD camera (NeuroCCD; RedShirtImaging). Epilumination was provided by a custom LED illuminator. Compared with the more commonly used photodiode array, the CCD chip well size (215,000 e−) requires use of relatively low light intensities, which minimized photodynamic damage. A 4× objective lens (0.28 N.A.; Olympus) imaged a 2.5 × 2.5-mm region in the hippocampal area CA1 (32 × 32-μm region imaged per pixel). These techniques have been described (57).

Hippocampal Slice Preparation. Six age- and sex-matched pairs of Dys1−/− and littermate controls were used. Mice were anesthetized and decapitated, and their brains were removed. Then, the brains were blocked in ice-cold arti-

ACKNOWLEDGMENTS. We thank Leslie Loew and Joe Weskell for the kind gift of the voltage-sensitive dye. This study was supported by National Institutes of Health Grants P50 MH64045, MH072880, 5R01DA023210-02, and P50-CA-084718, and Deutsche Forschungsgemeinschaft Grant IRTG 1328.

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