Psychiatry Research 339 (2024) 116084

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Psychiatry Research
journal homepage: www.elsevier.com/locate/psychres

Expression of activity-regulated transcripts in pyramidal neurons across thecortical visuospatial working memory network in unaffected comparison
individuals and individuals with schizophrenia
Yufan Bian a , Rika Kawabata a , John F. Enwright b, Makoto Tsubomoto a, Takeshi Okuda a ,Kohei Kamikawa c , Sohei Kimoto c,d, Mitsuru Kikuchi a,e , David A. Lewis b,f,* ,Takanori Hashimoto a,b,g,*
a

Department of Psychiatry and Behavioral Science, Kanazawa University Graduate School of Medical Sciences, Kanazawa, 920-8640, Japan
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USAc
Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, 634-8521, Japand
Department of Neuropsychiatry, Wakayama Medical University School of Medicine, Wakayama, 641-8509, Japane
Research Center for Child Development, Kanazawa University, Kanazawa 920-8640, Japanf
Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15213, USAg
National Hospital Organization Hokuriku Hospital, Nanto, 939-1893, Japanb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Postmortem
Transcript
Gray matter
Parvalbumin
Somatostatin

Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by multiple corticalregions including the primary (V1) and association (V2) visual, posterior parietal (PPC) and dorsolateral prefrontal (DLPFC) cortices. In these regions, parvalbumin (PV) or somatostatin (SST) GABA neurons are altered in
SZ as reflected in lower levels of activity-regulated transcripts. As PV and SST neurons receive excitatory inputs
from neighboring pyramidal neurons, we hypothesized that levels of activity-regulated transcripts are also lower
in pyramidal neurons in these regions. Thus, we quantified levels of four activity-regulated, pyramidal neuronselective transcripts, namely adenylate cyclase-activating polypeptide-1 (ADCYAP1), brain-derived neurotrophic
factor (BDNF), neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs, in V1, V2, PPC and DLPFC from
unaffected comparison and SZ individuals. In SZ, BDNF and NPTX2 mRNA levels were lower across all four
regions, whereas ADCYAP1 and NRN1 mRNA levels were lower in V1 and V2. The regional pattern of deficits in
BDNF and NPTX2 mRNAs was similar to that in transcripts in PV and SST neurons in SZ. These findings suggestthat lower activity of pyramidal neurons expressing BDNF and/or NPTX2 mRNAs might contribute to alterationsin PV and SST neurons across the vsWM network in SZ.

Introduction
In schizophrenia (SZ), deficits in working memory (WM) have beensuggested to be central to impairments in a range of cognitive functions(Silver et al., 2003; Barch and Ceaser, 2012) and thus key to one of themost debilitating symptom domains in the illness (Kahn and Keefe,2013). Visuospatial WM (vsWM), which is impaired in SZ (Park andHolzman, 1992; Forbes et al., 2009; Matthews et al., 2014), depends on
information flow across multiple cortical regions including the primaryvisual cortex (V1), association visual cortex (V2), posterior parietal
cortex (PPC) and dorsolateral prefrontal cortex (DLPFC) (Linden, 2007;

Christophel et al., 2017).
Information flow across these regions of the vsWM network is
mediated by the axonal projections of excitatory pyramidal neurons that
also provide excitatory inputs to local GABA neurons (Melchitzky andLewis, 2003; Jiang et al., 2015), which, in turn, shape the activity ofpyramidal neurons (Rao et al., 2000; Constantinidis et al., 2002). In eachof these regions, levels of transcripts expressed in the parvalbumin (PV)or somatostatin (SST) subtypes of cortical GABA neurons were lower inindividuals with SZ compared with unaffected comparison (UC) individuals (Tsubomoto et al., 2019), suggesting that alterations in both
PV and SST neurons represent a shared feature across cortical regions of* Corresponding authors.
E-mail addresses: lewisda@upmc.edu (D.A. Lewis), takanori@med.kanazawa-u.ac.jp (T. Hashimoto).
https://doi.org/10.1016/j.psychres.2024.116084
Received 29 March 2024; Received in revised form 3 July 2024; Accepted 10 July 2024
Available online 14 July 20240165-1781/© 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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Psychiatry Research 339 (2024) 116084

next of kin, during autopsies conducted at the Allegheny County(Pittsburgh, PA; N = 37) or the Davidson County (Nashville, TN; N = 3)
Medical Examiner’s Office. An independent committee of clinicians
made consensus, lifetime DSM-IV diagnoses for each individual using
the results of an expanded psychological autopsy, including structured
interviews with family members and review of medical records, as wellas toxicology and neuropathology reports (J.R. Glausier et al., 2020).
The same approach was used to confirm the absence of lifetime psychiatric and neurologic disorders in the UC individuals. All procedures
were approved by the University of Pittsburgh Committee for Oversightof Research and Clinical Training Involving Decedents and Institutional
Review Board for Biomedical Research, as well as by the Ethics Committees of Kanazawa University Graduate School of Medical Sciences
and Nara Medical University.
To reduce biological variance between groups, and to employ adesign that controlled for experimental variance, each individual with
SZ was matched to one UC individual for sex, and as closely as possible
for age (Table 1, Supplementary Table 1). Mean age, body mass index(BMI), postmortem interval (PMI), brain pH, RNA integrity number(RIN) and storage time at − 80 ◦ C did not differ significantly between thetwo groups, nor did race distribution (Table 1).

the vsWM network in SZ. Interestingly, some transcripts with lower
levels in PV and SST neurons (e.g., PV, SST and GAD67 mRNAs) from SZ
individuals are regulated by neuronal activity (Lau and Murthy, 2012;
Cohen et al., 2016; Ampofo et al., 2020). Given that both PV and SST
neurons receive direct excitatory inputs from neighboring pyramidal
neurons (Melchitzky and Lewis, 2003; Jiang et al., 2015; Campagnola
et al., 2022), we hypothesized that levels of activity-regulated transcripts are also lower in pyramidal neurons in SZ across regions of thevsWM network in a manner that is similar to the cross-regional alteration pattern of activity-regulated transcripts in PV and SST neurons.
To test this hypothesis, we used quantitative polymerase chain reaction (qPCR) to evaluate expression levels of activity-regulated, pyramidal neuron-selective transcripts in the total gray matter across four
regions of the cortical vsWM network from 20 matched pairs of UC and
SZ individuals. Specifically, we evaluated adenylate cyclase-activating
polypeptide-1 (ADCYAP1), brain-derived neurotrophic factor (BDNF),
neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs. Thesetranscripts are likely to be particularly informative as they are selectively expressed in pyramidal neurons in the human neocortex (Hodgeet al., 2019; Ma et al., 2022) in a neuronal activity-regulated manner(Ataman et al., 2016; Mardinly et al., 2016; Hrvatin et al., 2018) andtheir protein products regulate the development and maintenance ofsynaptic connections, including those of GABA neurons (Kohara et al.,2007; Chang et al., 2010; Fujino et al., 2011; Picard et al., 2014; Varodayan et al., 2020; Martelle et al., 2021). Furthermore, a recent
single-cell, spatial transcriptome study in the monkey neocortex
demonstrated that these transcripts are expressed in different sets of
excitatory neuron subtypes (Chen et al., 2023).
In addition, to determine if the regional expression patterns observedin total gray matter reflect those present in pyramidal neurons, we also
analyzed previously published RNA sequencing (RNAseq) data of pools oflayer 3 pyramidal neurons captured from V1, PPC and DLPFC of 39 UC
individuals (Enwright et al., 2022). Layer 3 pyramidal neurons appear tohave critical roles in WM because 1) across cortical regions of vsWM
network these neurons exhibit activities that represent specific information during vsWM tasks (Goldman-Rakic, 1995; Chafee andGoldman-Rakic, 1998; van Kerkoerle et al., 2017) and 2) these neurons,
through their corticocortical axonal projections (Jones, 1984; Lewis andGonzalez-Burgos, 2000), directly mediate information flow across corticalregions of the vsWM network (Felleman and Van Essen, 1991; Arion et al.,2023). Furthermore, they are the major source of excitatory inputs toneighboring PV and SST neurons via local axon collaterals (Melchitzky
and Lewis, 2003; Jiang et al., 2015; Campagnola et al., 2022).

2.2. Tissue preparation
The right hemisphere of each brain was blocked coronally, immediately frozen and stored at − 80 ◦ C. The gray matter tissues weredissected from each of the four cortical regions (V1, V2, PPC and DLPFC)
as described previously (Hoftman et al., 2018) (Supplementary
Methods, Supplementary Figure 1) and homogenized in TRIzol reagent(Invitrogen, Carlsbad, CA).
2.3. qPCR procedures
Total RNA was isolated from the homogenate samples and converted
into cDNA as described previously (Tsubomoto et al., 2019) (Supplementary Methods). Real-time amplification of ADCYAP1, BDNF, NPTX2,
and NRN1 mRNAs, as well as three internal control transcripts[beta-actin (ACTB), glyceraldehyde-3-phosphate (GAPDH) and peptidylprolyl isomerase A (PPIA)] were performed as described previously(Vandesompele et al., 2002; Tsubomoto et al., 2019) (Supplementary
Methods), using forward and reverse primers designed to amplify fragments of 87 to 127 bp in the regions common to all variants withamplification efficiency ≥ 96 % (Supplementary Table 2). The primer set
for BDNF mRNA was designed to avoid the region included in the
non-coding antisense RNA (BDNF-AS).
The expression levels of the target transcripts were determined as
expression ratios to the geometric mean of internal control transcripts as
described previously (Tsubomoto et al. 2019) (Supplementary
Methods). The mean expression levels of internal control transcripts did

Methods
2.1. Human individuals
Brain specimens (N = 40) were obtained, following consent from theTable 1
Summary of demographic and postmortem characteristics of human individuals.
MeasureSex
Race
Age (years)
BMI
PMI (hours)
Brain pHRIN
Tissue StorageTime (months)

Male
14
White
15
Mean
45.4
31.3
15.3
6.6
8.4
196.5

Unaffected Comparison

Schizophrenia(n = 20)(n = 20)
Female
6
Black
5
SD
11.6
7.2
5.8
0.2
0.5
39.9

Male
14
White
14
Mean
44.3
28.9
14.2
6.5
8.3
197.7

N/A, not applicable; BMI, body mass index; PMI, postmortem interval; RIN, RNA integrity number.
2

Statistics
Female
6
Black
6
SD
10.4
7.3
6.4
0.3
0.6
47.3

(N/A)

χ2 = 0.13; p = 0.72
t1,38 = 0.33; p = 0.74
t1,36 = 1.0; p = 0.32
t1,38 = 0.59; p = 0.56
t1,38 = 2.0; p = 0.05
t1,38 = 0.44; p = 0.66
t1,38 = − 0.08; p = 0.94

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Psychiatry Research 339 (2024) 116084

2.5. Analysis of RNAseq data from pools of layer 3 pyramidal neurons

not differ significantly by diagnosis (F1,38 = 1.92, p = 0.174) and the
diagnosis-by-region interaction was not significant (F3,114 = 0.31, p =0.817). We did detect a significant effect of region (F3,114 = 8.00, p <0.001), with post hoc comparisons revealing a significant difference
between V1 and DLPFC. However, this difference appears to have alimited effect on the comparison of target transcript levels between V1
and DLPFC as it is smaller in size (< 2.1 %) relative to the size ofobserved differences in target transcripts (all > 13.4 %). Cases withtranscript levels more than 3 SDs from the mean of all individuals in any
region were considered as outliers for that measure and pairs including
such cases were removed from the comparison between UC and SZ
individuals.

We also examined the transcripts of interest in a previously published RNAseq data set obtained from pools of 100 individuallydissected layer 3 pyramidal neurons collected from V1, PPC andDLPFC of 39 UC individuals (Enwright et al., 2022) (for demographic
information see Enwright et al. 2022). Among these 39 UC individuals,
19 UC individuals were common to the 20 UC individuals analyzed in
the current qPCR analysis. To compare RNAseq data for each transcript
across V1, PPC and DLPFC from UC individuals, the LMM included
transcript level as the dependent variable, region as a fixed effect, individual as a random effect, and sex, age, PMI, brain pH and RIN as
covariates, with only significant covariates included in the final reported
results. If the region effect was significant, post hoc pairwise comparisons between regions were performed by Tukey’s test.

2.4. qPCR data analysis

2.6. Analysis of microarray data of isolated pyramidal neurons fromDLPFC of antipsychotic-exposed monkeys

Analyses were performed with R version 4.1.3 (R: The R Project for
Statistical Computing; http://www.r-project.org) using the “lme4”,“lmerTest”, “tidyverse” and “emmeans” packages. To assess transcriptlevels across the four regions, a linear mixed model (LMM) was performed with observations from the four regions in each individual as
repeated measures to account for within-individual correlation amongfour regions. To compare transcript levels across the four regions in UC
individuals, the LMM included transcript level as the dependent variable, region as a fixed effect, individual as a random effect, and sex, age,
PMI, brain pH, RIN and tissue storage time as covariates. F-tests wereused to assess the overall effect of region. If region effect was significant,post hoc pairwise comparisons between regions were performed by
Tukey’s test. To determine if the expression of these transcripts wasaltered in SZ across regions, the LMM was performed with transcriptlevel as the dependent variable, diagnosis, region and diagnosis-byregion interaction as the fixed effects, individual as a random effect,
and the same set of covariates. F-tests were used to test the diagnosis anddiagnosis-by-region interaction effects. If the diagnosis-by-region
interaction was significant, post hoc pairwise comparisons were performed to assess the diagnosis effect in each region via Tukey’s test. In
each region, the magnitudes of transcript changes in SZ relative to UC
individuals are presented as percentage differences as well as Cohen’sd effect sizes (Cohen, 1988). Negative Cohen’s d values indicate thatmean transcript levels are lower in SZ relative to UC individuals.
To compare alterations in the activity-regulated transcripts withpreviously reported deficits in transcripts from PV and SST neurons (PV,SST and GAD67 mRNAs) (Tsubomoto et al., 2019) across the regions,composite scores were computed for three groups of transcripts(ADCYAP1 and NRN1 mRNAs, BDNF and NPTX2 mRNAs, and PV, SST
and GAD67 mRNAs) as the means of Z-scored expression levels oftranscripts belonging to each group (Supplementary Methods). Transcript levels of PV, SST and GAD67 mRNAs were obtained from thepreviously published analysis of the same cohort used in this study(Tsubomoto et al., 2019). In each region, the magnitudes of diagnosis
effect on composite scores are presented as Cohen’s d with 95 % confidence intervals (CI) (Nakagawa and Cuthill, 2007).
The potential effects of certain cooccurring factors, such as the use ofprescription drugs (benzodiazepines and/or anticonvulsants, antidepressants and antipsychotics) at time of death (ATOD), tobacco use
ATOD, and suicide as the manner of death, on each target transcript
were tested by the LMM with transcript level as the dependent variable,cooccurring factor, region and cooccurring factor-by-region interaction
as the fixed effects, individual as a random effect, and sex, age, PMI, RIN,
tissue storage time and brain pH as covariates. For each transcript, pvalues were corrected for multiple comparisons for 5 cooccurring factors
using the Benjamini-Hochberg Method with the false discovery rate of 5%.
All LMM analyses of individual target transcripts were conducted on
log-transformed data and only significant covariates were included in
the final reported results.

Levels of ADCYAP1, BDNF, NPTX2 and NRN1 mRNAs were obtained
from microarray data of pools of individually captured pyramidal neurons from DLPFC layers 3 and 5 of monkeys chronically exposed to
haloperidol, olanzapine or placebo (n = 6 per group) (Dorph-Petersen
et al., 2004). Levels of the transcripts of interest were computed as
described previously (Datta et al., 2015) and used as the dependent
variable in an analysis of variance model that assessed the effect ofantipsychotic-exposure on each transcript.
3. Results
3.1. Levels of activity-regulated, pyramidal neuron-selective transcripts
across regions of vsWM network in UC individuals
In UC individuals, the levels in total gray matter of pyramidal
neuron-selective, activity-regulated transcripts showed two patterns ofregional differences across the vsWM network (Fig. 1). In the firstpattern, transcript levels for ADCYAP1 (F3,57 = 17.38, p < 0.001), BDNF
(F3,57 = 33.98, p < 0.001) and NPTX2 (F3,57 = 54.73, p < 0.001)
increased from posterior to anterior regions. Specifically, levels of thesethree transcripts were lowest in V1, intermediate in V2 and highest in
PPC and DLPFC (Fig. 1A-C). In contrast, NRN1 mRNA (F3,57 = 8.68, p <0.001) showed the opposite pattern with levels highest in V1 anddecreasing across the vsWM network (Fig. 1D), although the magnitudeof the between-region differences appears smaller than for transcripts inthe first pattern. Among 20 UC individuals, the numbers of individuals
with higher ADCYAP1, BDNF and NPTX2 mRNA levels in DLPFC than in
V1 were 20, 20 and 19, respectively, whereas the number of individuals
with higher NRN1 mRNA levels in V1 than in DLPFC was 16.
We also evaluated the levels of these transcripts in isolated layer 3
pyramidal neurons from V1, PPC and DLPFC of UC individuals using ourpreviously published RNAseq data (Enwright et al., 2022). The effect ofregion was significant or nearly significant for ADCYAP1 (F2,76 = 41.18,
p < 0.001), BDNF (F2,76 = 2.80, p = 0.067), and NPTX2 (F2,76 = 104.62,
p < 0.001) mRNAs (Fig. 1E-G). Similar to the qPCR data of gray matter,
ADCYAP1 and NPTX2 showed posterior-to-anterior increases with levelsof these mRNAs significantly higher in DLPFC than in V1 (Fig. 1E, G).
BDNF mRNA showed a similar trend with mean levels lowest in V1,
intermediate in PPC and highest in DLPFC (Fig. 1F). In contrast to theqPCR data, NRN1 mRNA levels in layer 3 pyramidal neurons did not
differ across vsWM regions (F2,76 = 0.39, p = 0.678) (Fig. 1H).
3.2. Effect of SZ on activity-regulated, pyramidal neuron-selective
transcripts in regions of vsWM network
For ADCYAP1 mRNA, our mixed model detected a significant effectof diagnosis (F1,38 = 6.87, p = 0.013), significant effects of region (F3,114
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Fig. 1. Expression levels of activity-regulated, pyramidal neuron-selective transcripts across the four regions of the cortical visuospatial working memory network in
unaffected comparison (UC) individuals measured in total gray matter by quantitative polymerase chain reaction (qPCR) (A-D) and in layer 3 pyramidal neurons by
RNA sequencing (RNAseq) (E-H). The linear mixed model results are shown at the top left of each panel for each transcript. Within each panel, symbols indicate
individuals and horizontal bars represent group means. For each transcript, regions that do not share the same lower-case letter are significantly different by post hoc
Tukey’s tests with alpha level of 0.05. For qPCR results (A-D), transcript levels of each UC individual are shown by the same symbol across all regions and graphs. For
RNAseq results (E-H), box plots depict the mean, and 25th and 75th percentiles, with whiskers extending to the 95th percentiles of each distribution. V1, primaryvisual cortex; V2, association visual cortex; PPC, posterior parietal cortex; DLPFC, dorsolateral prefrontal cortex.

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Psychiatry Research 339 (2024) 116084

Fig. 2. Effect of schizophrenia (SZ) on activity-regulated, pyramidal neuron-selective transcripts across the four cortical regions of visuospatial working memory
network. For each panel (A-D), transcript name is at the top left and the linear mixed model results at the top center. In each panel, symbols indicate the percentage
difference between the unaffected comparison (UC) and SZ individual in each pair; symbols correspond to the UC individual plotted in Fig. 1 for a given pair. The
percentage differences in mean levels between SZ and UC individuals are indicated by horizontal bars and shown in parentheses. Asterisks (*) indicate significant
differences between UC and SZ individuals in each region by post hoc Tukey’s tests that were performed when the linear mixed model detected a significant
diagnosis-by-region interaction. V1, primary visual cortex; V2, association visual cortex; PPC, posterior parietal cortex; DLPFC, dorsolateral prefrontal cortex.

Fig. 3. Effect of schizophrenia (SZ) on composite scores obtained for activity-regulated, pyramidal neuron-selective transcripts and for transcripts in PV and SST
neurons in each region of the cortical visuospatial working memory network. In each panel (A-C), bargraphs show the Cohen’s d effect sizes of SZ on transcript
composite scores across the regions for three groups of transcripts, ADCYAP1 and NRN1 mRNAs (A), BDNF and NPTX2 mRNAs (B) and PV, SST and GAD67 mRNAs(C). Error bars indicate 95 % confidence intervals (CI). V1, primary visual cortex; V2, association visual cortex; PPC, posterior parietal cortex; DLPFC, dorsolateralprefrontal cortex.
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Psychiatry Research 339 (2024) 116084= 62.45, p < 0.001) and diagnosis-by-region interaction (F3,114 = 9.52, p< 0.001) (Fig. 2A). Compared with UC individuals, ADCYAP1 mRNAlevels were significantly lower in V1 (Cohen’s d = − 1.21, p < 0.001) andV2 (Cohen’s d = − 0.99, p = 0.002) but unaltered in PPC and DLPFC ofindividuals with SZ. Levels of BDNF mRNA significantly differed bydiagnosis (F1,36 = 15.10, p < 0.001) and by region (F3,114 = 41.43, p <0.001), but the interaction term was not significant (F3,114 = 0.56, p =0.645) (Fig. 2B). Compared with UC individuals, BDNF mRNA levels
were lower in V1, V2, PPC and DLPFC (Cohen’s d = − 0.80, − 1.03,− 0.87 and − 0.60, respectively) in SZ individuals. For NPTX2 mRNAlevels, we detected a significant effect of diagnosis (F1,35 = 6.27, p =0.017) and a significant effect of region (F3,108 = 93.85, p < 0.001),
without a diagnosis-by-region interaction (F3,108 = 0.30, p = 0.825)(Fig. 2C). NPTX2 mRNA levels were lower in V1, V2, PPC and DLPFC(Cohen’s d = − 0.37, − 0.51, − 0.59, and − 0.33, respectively) in individuals with SZ. Finally, NRN1 mRNA levels showed significant effects
of region (F3,108 = 11.42, p < 0.001) and diagnosis-by-region interaction(F3,108 = 3.06, p = 0.031), but the effect of diagnosis was not significant(F1,34 = 2.40, p = 0.131) (Fig. 2D). NRN1 mRNA levels were significantly lower in V1 (Cohen’s d = − 0.91, p = 0.005), but unaltered in theother regions.

transcripts in pyramidal neurons from layer 3 (all F2,15 < 0.59, all p >0.567) or layer 5 (all F2,15 < 1.14, all p > 0.345).

3.3. Comparison with transcript alterations in PV and SST neurons

4.1. Transcript levels in UC individuals

The findings above reveal two distinct cross-regional patterns ofactivity-regulated transcript alterations in SZ: ADCYAP1 and NRN1
mRNAs levels were lower only in the two occipital regions (Fig. 2A andD), whereas the deficits in BDNF and NPTX2 mRNA levels were comparable across all four regions (Fig. 2B and C). Therefore, to assess therelationship of activity-regulated transcripts with the previously reported transcript alterations in PV and SST neurons in SZ, we computed
composite scores in each region of each individual for ADCYAP1 and
NRN1 mRNAs, for BDNF and NPTX2 mRNAs and for PV, SST and GAD67
mRNAs using previously published data from the same cohort(Tsubomoto et al., 2019). The magnitude (Cohen’s d effect size) of the
deficit in the ADCYAP1/NRN1 composite scores in SZ was largest in V1
and decreased from posterior to anterior regions (Fig. 3A). In contrast,
although regional differences in the magnitudes of the disease effectwere much smaller for the BDNF/NPTX2 scores, the magnitudes of
deficits were in the order of PPC>V2>V1>DLPFC (Fig. 3B), the same
regional order observed for the larger deficits in the PV/SST/GAD67
scores (Fig. 3C). Although the data points were limited to the four regions, the effects of SZ on BDNF/NPTX2 scores and PV/SST/GAD67
scores were positively correlated (r = 0.96, p = 0.042) across these regions, whereas the ADCYAP1/NRN1 and PV/SST/GAD67 scores werenot (r = − 0.19, p = 0.890).

Our qPCR findings revealed that levels of ADCYAP1, BDNF andNPTX2 mRNAs increased, whereas those of NRN1 mRNAs declined fromposterior visual to anterior association regions of the vsWM network in
UC individuals. As recent single-cell transcriptome analyses of the primate neocortex revealed that these transcripts are selectively expressedin different sets of excitatory neuron subtypes including those in layer 3(Hodge et al., 2019; Ma et al., 2022; Chen et al., 2023), thecross-regional differences in their levels in total gray matter could reflect
regional differences in the activity and/or abundance of pyramidal
neuron subtypes that selectively express each of these transcripts. The
qPCR result of ADCYAP1, BDNF and NPTX2 mRNAs were replicated in
our RNAseq analysis of isolated layer 3 pyramidal neurons (Enwrightet al., 2022), suggesting that regional differences in the mRNA levels in
total gray matter reflect, at least in part, their expression in layer 3
pyramidal neurons. Interestingly, layer 3 pyramidal neurons exhibit
progressive increases in the size and complexity of dendritic arbors(Elston and Rosa, 1997; Elston, 2000) and in the number and density ofdendritic spines, the principal sites of excitatory synapses on pyramidal
neurons (Spruston, 2008), from V1 to DLPFC (Elston, 2000; Elston et al.,2011). Furthermore, in monkeys, the magnitude, frequency and duration of excitatory synaptic inputs to layer 3 pyramidal neurons were all
greater in DLPFC than in V1 (Amatrudo et al., 2012), indicating greater
amounts and more effective summation of excitatory inputs to theseneurons in DLPFC than in V1. Therefore, the posterior-to-anterior increase in ADCYAP1, BDNF and NPTX2 mRNAs might reflect the regional
gradient in the activity of layer 3 pyramidal neurons. Consistent withthis idea, in our RNAseq data of isolated layer 3 pyramidal neurons,
levels of transcripts for oxidative phosphorylation, which reflect
neuronal activity (Wong-Riley, 2012), exhibited higher expression
levels in DLPFC and PPC than in V1 (Enwright et al., 2022).
In contrast, NRN1 mRNA levels were higher in V1 and V2 than in
DLPFC with the levels in PPC intermediate by qPCR. However, theRNAseq analysis of isolated layer 3 pyramidal neurons did not detect asignificant difference across the regions. The RNAseq data for 19 UC
individuals, which are common to the current qPCR analysis, showed atrend of difference in NRN1 mRNA among the four regions (F2,36 = 2.78,
p = 0.075) with the levels in V1 higher by 2.3 % than in DLPFC, whereas
in the qPCR data for the total gray matter of the same 19 UC individuals
NRN1 mRNA levels differ significantly across regions (F3,54 = 8.21, p <0.001) with the levels in V1 significantly higher by 12.9 % than those in
DLPFC. It is also possible that the observed difference between V1 and
DLPFC in qPCR data is overrated by the lower mean levels of internal

4. Discussion
In this study, we quantified levels of four neuronal activity-regulatedtranscripts that are selectively expressed in pyramidal neurons acrossfour cortical regions of vsWM network from 20 matched pairs of UC and
SZ individuals. In UC individuals, levels of ADCYAP1, BDNF and NPTX2
mRNAs were lowest in V1 and increased from posterior to anterior regions with the highest levels in the PPC and DLPFC, whereas NRN1mRNA levels were higher in V1 and V2 than in PPC or DLPFC. Relative
to UC individuals, levels of BDNF and NPTX2 mRNAs were lower in SZ
across all four regions, whereas ADCYAP1 and NRN1 mRNA levels werelower in V1 and V2, but not in PPC or DLPFC. Across the four regions,the deficits in BDNF and NPTX2 mRNA levels were similar to the previously reported deficits in PV, SST and GAD67 mRNA levels in the samecohort. These findings are consistent with the idea that the activity ofpyramidal neurons that selectively express BDNF and/or NPTX2 mRNAs
is lower in SZ and contribute to alterations in PV and SST neurons acrossmultiple regions of the cortical vsWM network in SZ.

3.4. Effects of cooccurring factors on activity-regulated transcripts in SZ
individuals
In the LMM model, none of cooccurring factors, including the use ofprescription drugs (benzodiazepines and/or anticonvulsants, antidepressants and antipsychotics) ATOD, tobacco use ATOD or suicide (all p> 0.073), nor the interaction between each of these factors and regions(all p > 0.069) exhibited a significant effect on levels of all transcripts inindividuals with SZ (Supplementary Table 3), except for a significant
effect of benzodiazepines/anticonvulsants ATOD on NRN1 mRNA levels(Supplementary Figure 2). Individuals with SZ who used benzodiazepines/anticonvulsants ATOD had NRN1 mRNA levels that were 16–29 %higher across regions compared with those who did not use these drugs(Supplementary Figure 2).
To further assess the effect of antipsychotics on the four transcripts,
we analyzed microarray data of pooled pyramidal neurons individually
captured from layers 3 and 5 of DLPFC of monkeys chronically exposed
to haloperidol, olanzapine or placebo (Datta et al., 2015). The exposure
to antipsychotics did not have a significant effect on any of the four6

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Psychiatry Research 339 (2024) 116084

pyramidal neuron subtypes that are defined by their layer localizationand projection targets showed different chromatin accessibility patterns,
especially in the gene regulatory regions, across different neocorticalregions (Lei et al., 2022). Therefore, the lower levels of ADCYAP1 and
NRN1 mRNAs in posterior visual, but not anterior association, regions
might reflect regional differences in epigenetic regulation that could
contribute to region-selective influence of pyramidal neuron activity onthese transcripts.
The cross-regional patterns of deficits in SZ were different between
BDNF and NPTX2 mRNAs and ADCYAP1 and NRN1 mRNAs and thepattern of transcript alterations in PV and SST neurons was similar tothat of BDNF and NPTX2 mRNAs. In a recent single-cell, spatial transcriptome analysis of the monkey cortex (Chen et al., 2023), 59 out of
122 cortical excitatory neuron subtypes were found to express at least
one of the four activity-regulated transcripts as their selective markers.
Among them, 25 subtypes selectively express ADCYAP1 and/or NRN1
mRNAs without selective expression of BDNF or NPTX2 mRNAs and 19
subtypes selectively express BDNF and/or NPTX2 mRNAs without selective expression of ADCYAP1 or NRN1 mRNAs. These findings suggestthat pyramidal neuron subtypes that selectively express BDNF and/or
NPTX2 mRNAs contribute to alterations of PV and SST neurons throughtheir lower activity and reduced synthesis of BDNF and NPTX2 in eachregion of vs WM network.

control transcripts in V1 relative to DLPFC in UC individuals. However,this influence appears to be limited as the mean levels of the threecontrol transcripts were lower by 2.1 % in V1 than in DLPFC, whereas
NRN1 mRNA levels were higher by 13.5 % in V1 than in DLPFC.
Together, these findings suggest that the posterior-to-anterior decline in
NRN1 mRNA levels in total gray matter is not merely an artifact associated with the difference in cohorts or the regional difference in thelevels of internal control transcripts. It is possible that the qPCR results
reflect, at least in part, NRN1 mRNA expression in non-layer 3 pyramidal
neurons. Interestingly, in a recent single-cell, spatial transcriptome
analysis of the monkey cortex (Chen et al., 2023), NRN1 mRNA wasselectively detected in seven excitatory neuron subtypes that exhibited
gradual decreases in the density from posterior visual to anterior association regions along the hierarchy of visual cortices. Among thesesubtypes, six subtypes, which represent the majority in the total densities of the seven subtypes across these regions, were located outside oflayer 3. Therefore, the posterior-to-anterior decline of NRN1 mRNAlevels might reflect the regional gradients of the density of the pyramidal
neuron subtypes located outside of layer 3.
4.2. Alterations in SZ individuals
We have previously demonstrated that levels of BDNF and NPTX2
mRNAs were lower in the DLPFC of SZ individuals (Hashimoto et al.,2005; Kimoto et al., 2015). In the current study, we detected significant
effects of diagnosis on BDNF and NPTX2 mRNAs, respectively, without asignificant diagnosis-by-region interaction, indicating that these transcripts are similarly lower across the four regions in SZ individuals. As
both BDNF and NPTX2 are synthesized in pyramidal neurons in an
activity-dependent manner (Tsui et al., 1996; Hrvatin et al., 2018;
Esvald et al., 2022), their lower levels in SZ could reflect reduced activity of pyramidal neurons, which could contribute to lower levels ofactivity-regulated transcripts in PV and SST neurons via excitatory inputs from pyramidal neurons. Furthermore, BDNF has been reported tobe necessary for the formation and maintenance of inhibitory synapses
by cortical GABA neurons (Kohara et al., 2007) and was shown toregulate expression of PV (Huang et al., 1999; Sakata et al., 2009), SST(Glorioso et al., 2006; Mellios et al., 2009) and GAD67 (Matsumoto
et al., 2006; Hanno-Iijima et al., 2015). NPTX2 is released from pyramidal neurons, accumulates at excitatory synapses on PV neurons andenhances excitatory inputs to these neurons by recruiting AMPA receptors to synaptic surface (Chang et al., 2010). Therefore, lower levelsof BDNF and NPTX2 mRNAs could represent, in addition to reduced
excitatory inputs to PV and SST neurons, a direct molecular mechanismthat could contribute to the lower transcript levels in PV and SST neurons across cortical regions.
In contrast to BDNF and NPTX2 mRNAs, levels of ADCYAP1 and
NRN1 mRNAs were lower only in posterior visual regions. ADCYAP1and NRN1 mRNAs are selectively expressed in pyramidal neurons ofhuman cortex (Hodge et al., 2019; Ma et al., 2022) and upregulated withenhanced activity in pyramidal neurons in rodent cortex (Hrvatin et al.,2018). As recent single-nucleus transcriptome analyses revealed multiple pyramidal neuron subtypes in the primate neocortex (Hodge et al.,2019; Ma et al., 2022; Chen et al., 2023), the region-specific deficits in
ADCYAP1 and NRN1 mRNAs could reflect that pyramidal neuron subtypes that selectively express these transcripts are hypoactive primarily
in posterior regions in SZ individuals. Alternative, though not mutually
exclusive, is the possibility that activity-dependent regulation of thesetranscripts in pyramidal neurons differs across cortical regions so thatthe effect of activity has greater impacts on these transcripts in posterior
than in anterior regions. Activity-regulated transcription was shown tooccur through the interaction with epigenetic mechanisms, such as DNA
methylation and chromatin modifications (Yap and Greenberg, 2018;
Pumo et al., 2022). Among different cell types in human neocortex,
pyramidal neurons exhibited the greatest cross-regional variability inchromatin accessibility (Hauberg et al., 2020), and in monkeys, most

4.3. Evidence supporting lower pyramidal neuron activity in SZ
In SZ, the density of dendritic spines was found to be lower acrossmultiple cortical regions (Glausier and Lewis, 2013). Given that spines
are the site of most excitatory inputs to pyramidal neuron, these findings
have been interpreted as evidence of lower excitatory drive to, andhence lower activity of, pyramidal neurons. This interpretation is supported by findings that markers of energy production are also lower inpyramidal neurons in cortical regions of the vsWM network in SZ (Arionet al., 2015; Glausier et al., 2020; Kimoto et al., 2022). Furthermore,
many SZ risk loci identified by large-scale genetic studies implicate
genes involved in synaptic glutamate signaling or spine formation andmaintenance (Singh et al., 2022; Trubetskoy et al., 2022). Together,
these findings converge on the idea that fewer excitatory inputs tocortical pyramidal neurons contribute to lower activity of these neurons
in SZ. Previous functional imaging studies have shown lower activity of
DLPFC and PPC during WM tasks (Minzenberg et al., 2009; Barch andCeaser, 2012). As pyramidal neurons are excitatory and represent the
majority of neurons across cortical regions (Hendry et al., 1987; Jorstad
et al., 2023), these findings are also consistent with lower activity ofpyramidal neurons in the vsWM network in SZ.
4.4. Effects of cooccurring factors
Several lines of evidence suggest that altered levels of activityregulated transcripts in pyramidal neurons across the regions of vsWM
network are unlikely to be the consequences of other factors frequently
associated with SZ. First, our LMM model did not reveal a significant
effect of cooccurring factors, such as prescription drug use ATOD
(including benzodiazepines/anticonvulsants, antidepressants and antipsychotics), tobacco use ATOD or death by suicide, or a significant
coocurring factor-by-region interaction for ADCYAP1, BDNF and NPTX2
mRNAs in SZ individuals (Supplementary Table 3). For NRN1, only useof benzodiazepines/anticonvulsants ATOD had a significant effectwithout a significant interaction with region. However, NRN1 mRNAlevels were higher in SZ individuals treated with benzodiazepines/anticonvulsants ATOD than in those who were not treated with these drugs
across the regions (Supplementary Figure 2). Therefore, benzodiazepines/anticonvulsants use ATOD did not explain the lower NRN1 mRNAlevels in SZ compared to UC individuals. Second, our previous studies inthe DLPFC of individuals with SZ demonstrated that BDNF mRNA levels
did not differ as a function of antidepressant or antipsychotic use or of7

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Psychiatry Research 339 (2024) 116084

death by suicide (Hashimoto et al., 2005), and NPTX2 mRNA levels were
not affected by use of benzodiazepines/anticonvulsants, antidepressantsor antipsychotics ATOD, tobacco use ATOD, or death by suicide (Kimoto
et al., 2015). Third, neither BDNF nor NPTX2 mRNA levels were alteredin the total gray matter of DLPFC of monkeys chronically exposed to
antipsychotics (Hashimoto et al., 2005; Kimoto et al., 2015). Fourth, inthe same antipsychotic-exposed monkeys, none of the four transcripts
exhibited a significantly altered levels in pooled pyramidal neurons
individually captured from layers 3 or 5 of the DLPFC. Finally, thecomparable magnitudes of alterations of BDNF and NPTX2 mRNAs as
well as posterior region-dominant alterations of ADCYAP1 and NRN1
mRNAs argue against the potential influence of antipsychotics because
any effects of antipsychotics would likely to show a posterior-to-anterior
increase that reflect greater densities of dopamine terminals (Lewis
et al., 1987; Gaspar et al., 1989) and receptors (Lidow et al., 1989) inanterior than in posterior regions.

Tissue Donation Program or the NIH NeuroBioBank at the University ofPittsburgh.
Supplementary materials
Supplementary material associated with this article can be found, inthe online version, at doi:10.1016/j.psychres.2024.116084.
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4.5. Conclusions
Our analyses of four activity-regulated transcripts that are selectively
expressed in pyramidal neurons across the four cortical regions of vsWM
network revealed two opposite cross-regional expression patterns in UC
individuals, which appear to reflect regional differences in activity and/or relative abundance of pyramidal neuron subtypes selectively
expressing each transcript. In SZ individuals, levels of these transcripts
were lower across the four regions, indicating lower activity of pyramidal neurons. The similar alterations of BDNF and NPTX2 mRNAs
across the four regions could reflect reduced activity of pyramidal
neurons selectively expressing these transcripts as well as dysregulationof GABA neuron phenotypes, both of which could contribute to theregionally conserved alterations of PV and SST neurons in the vsWM
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the activity of pyramidal neurons selectively expressing these transcripts
and/or the transcriptional regulation of these transcripts by neuronal
activity.
Funding
This work was supported by the Japan Society for the Promotion of
Science Grants-in-Aid 19H03580 to TH and 20K07949 to SK.
CRediT authorship contribution statement
Yufan Bian: Writing – review & editing, Writing – original draft,
Investigation, Formal analysis, Data curation. Rika Kawabata: Writing– review & editing, Investigation, Formal analysis. John F. Enwright:
Writing – review & editing, Formal analysis, Data curation, Conceptualization. Makoto Tsubomoto: Writing – review & editing, Investigation, Formal analysis. Takeshi Okuda: Writing – review & editing,
Investigation, Formal analysis. Kohei Kamikawa: Writing – review &editing, Investigation. Sohei Kimoto: Writing – review & editing,Writing – original draft, Funding acquisition, Conceptualization. Mitsuru Kikuchi: Writing – review & editing, Project administration,
Formal analysis. David A. Lewis: Writing – review & editing, Writing –original draft, Supervision, Conceptualization. Takanori Hashimoto:
Writing – review & editing, Writing – original draft, Supervision,
Funding acquisition, Data curation, Conceptualization.
Declaration of competing interest
The authors have no competing interests to declare.
Acknowledgement
Tissue samples were obtained from the University of Pittsburgh Brain
8

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