DNA methylation as a putative mechanism for reduced dendritic spine density in the superior temporal gyrus of subjects with schizophrenia

Abstract

Reduced dendritic spine density (DSD) in cortical layer 3 of the superior temporal gyrus (STG), and multiple other brain regions, is consistently observed in postmortem studies of schizophrenia (SZ). Elucidating the molecular mechanisms of this intermediate phenotype holds promise for understanding SZ pathophysiology, identifying SZ treatment targets and developing animal models. DNA methylation (DNAm), the addition of a methyl group to a cytosine nucleotide, regulates gene transcription and is a strong candidate for such a mechanism. We tested the hypothesis that DNAm correlates with DSD in the human STG and that this relationship is disrupted in SZ. We used the Illumina Infinium HumanMethylation450 Beadchip Array to quantify DNAm on a genome-wide scale in the postmortem STG from 22 SZ subjects and matched non-psychiatric control (NPC) subjects; DSD measures were available for 17 of the 22 subject pairs. We found DNAm to correlate with DSD at more sites than expected by chance in NPC, but not SZ, subjects. In addition, we show that the slopes of the linear DNAm-DSD correlations differed between SZ and NPC subjects at more sites than expected by chance. From these data, we identified 2 candidate genes for mediating DSD abnormalities in SZ: brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2) and discs large, Drosophila, homolog of, 1 (DLG1). Together, these data suggest that altered DNAm in SZ may be a mechanism for SZ-related DSD reductions.

OPEN

Citation: Transl Psychiatry (2017) 7, e1032; doi:http://dx.doi.org/10.1038/tp.2016.297

Web End =10.1038/tp.2016.297

http://www.nature.com/tp

Web End =www.nature.com/tp

B McKinney1,2, Y Ding3, DA Lewis1,2,4 and RA Sweet1,2,5,6

Reduced dendritic spine density (DSD) in cortical layer 3 of the superior temporal gyrus (STG), and multiple other brain regions, is consistently observed in postmortem studies of schizophrenia (SZ). Elucidating the molecular mechanisms of this intermediate phenotype holds promise for understanding SZ pathophysiology, identifying SZ treatment targets and developing animal models. DNA methylation (DNAm), the addition of a methyl group to a cytosine nucleotide, regulates gene transcription and is a strong candidate for such a mechanism. We tested the hypothesis that DNAm correlates with DSD in the human STG and that this relationship is disrupted in SZ. We used the Illumina Innium HumanMethylation450 Beadchip Array to quantify DNAm on a genome-wide scale in the postmortem STG from 22 SZ subjects and matched non-psychiatric control (NPC) subjects; DSD measures were available for 17 of the 22 subject pairs. We found DNAm to correlate with DSD at more sites than expected by chance in NPC, but not SZ, subjects. In addition, we show that the slopes of the linear DNAm-DSD correlations differed between SZ and NPC subjects at more sites than expected by chance. From these data, we identied 2 candidate genes for mediating DSD abnormalities in SZ: brain-specic angiogenesis inhibitor 1-associated protein 2 (BAIAP2) and discs large, Drosophila, homolog of, 1 (DLG1).

Translational Psychiatry (2017) 7, e1032; doi:http://dx.doi.org/10.1038/tp.2016.297

Web End =10.1038/tp.2016.297 ; published online 14 February 2017

INTRODUCTION

Schizophrenia (SZ) is thought to be a disorder of cerebral cortical circuitry disruption. Particular SZ symptoms are associated with dysfunction of certain cortical circuits.1 For example, cortical circuit abnormalities in the superior temporal gyrus (STG), a brain region critical for auditory processing, are associated with auditory verbal hallucinations and impaired auditory sensory processing. Impaired auditory processing further contributes to phonologic dyslexia and difculty recognizing and expressing spoken emotional tone (prosody) in SZ.2

Reduced dendritic spine density (DSD) in cortical STG layer 3, and other brain regions, is observed in postmortem studies of SZ.36 We have previously demonstrated reduced DSD in STG layer 3 of SZ subjects in multiple cohorts.5,6 We have also shown that

the DSD reduction in SZ is of a similar magnitude in both the

Heschl's Gyrus and planum temporale of the STG.6

Reduced DSD has several features indicating it is an intermediate phenotype for SZ. An intermediate phenotype is a heritable quantitative biological trait that is correlated with a disorder due, in part, to shared genetic architecture.7 A number of genes contribute to regulation of dendritic spine features including DSD8 and several of these are also SZ risk genes.922

The most useful intermediate phenotypes are functionally associated with aspects of the core clinical decits of the disorder. DSD is intimately linked to neuronal function and changes in DSD are essential for normal cognition and sensory processing.8,23,24

Many disorders characterized, in part, by impaired cognition are also characterized by DSD abnormalities,8,25 thus suggesting that reduced DSD likely contributes to cognitive decits in SZ. For example, in the auditory cortex, dendritic spines on layer 2/3 neurons segregate frequency inputs to the neurons.26 Thus

reduced DSD on these neurons would likely lead to impaired frequency discrimination, a decit that has been observed in SZ.2

Elucidating the mechanisms of this intermediate phenotype is important for understanding SZ pathophysiology, identifying SZ treatment targets and developing animal models. DNA methylation (DNAm), the addition of a methyl group to a cytosine nucleotide, regulates gene transcription and is a strong candidate for such a mechanism. DNAm is altered in the brain2734 of SZ

subjects and DNAm alterations are present in other contexts characterized by DSD abnormalities including neurodevelopmental disorders, models of addiction, and activity-dependent plasticity.8 In this study, we evaluated the hypothesis that DNAm correlates with DSD in the human STG and that this relationship is disrupted in SZ.

MATERIALS AND METHODS Postmortem brains

Brains were recovered and processed as described previously.35 Briey, brains were recovered during routine autopsies at the Allegheny County Medical Examiners Ofce, Pittsburgh, PA, USA following informed consent

1Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; 2Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA; 3Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA; 4Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA; 5Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA and 6Mental Illness Research, Education, and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA. Correspondence: Dr RA Sweet, Department of Psychiatry, Neurology and VISN 4 Mental Illness Research, Education and Clinical Center (MIRECC), Biomedical Science Tower, Room W-1645, 3811 O'Hara Street, Pittsburgh, PA 15213, USA.

E-mail: mailto:[email protected]

Web End [email protected] Received 3 November 2016; accepted 13 November 2016

ORIGINAL ARTICLE

DNA methylation as a putative mechanism for reduced dendritic spine density in the superior temporal gyrus of subjects with schizophrenia

Together, these data suggest that altered DNAm in SZ may be a mechanism for SZ-related DSD reductions.

DNA methylation and spine density in schizophrenia B McKinney et al

2

Table 1. Cohort characteristics

Cohort DNAm DNAm and DSD

Group NPC SZ NPC SZ

Number 22 22 17 17Sex 17 M, 5 F 17 M, 5 F 12M, 5F 12M, 5F Race 16 W, 6 B 16 W, 6 B 11W, 5B, 1O 11W, 6B Age (years) 45.14 2.30 47.14 2.91 44.82 2.76 47.53 3.29 PMI (h) 17.58 1.39 18.23 1.79 16.27 1.67 15.76 1.89

Abbreviations: B, black, DNAm, DNA methylation; DSD, dendritic spine density; F, female; M, male; NPC, non-psychiatric control; O, Other (Asian Indian); PMI, postmortem interval; SZ, schizophrenia; W, white. Data for continuous variables are presented as group average s.e.m.

from next-of-kin. DSM-IV diagnoses were made based on clinical records and structured interviews with surviving relatives. The right hemisphere was blocked coronally and the resultant slabs snap frozen and stored at 80 C. Slabs containing the STG were identied and the STG was removed as a single block. Samples containing all six cortical layers of STG (planum temporale), but excluding the adjacent white matter, were harvested. All procedures were approved by the University of Pittsburgh Committee for the Oversight of Research and Clinical Training Involving the Dead and the Institutional Review Board for Biomedical Research.

Cohort membershipThe cohort was comprised of 22 subjects with either schizophrenia (N = 16)

or schizoaffective disorder.5 Schizophrenia and schizoaffective disorder were considered together because studies of DSD have not found differences between them.5,6 Each SZ subject was matched with a non-psychiatric control (NPC) subject for sex, hemisphere, and as closely as possible for postmortem interval (PMI), age and other characteristics (Table 1 and Supplementary Table 1). DSD measures from STG layer 3 were available for 17 SZ-NPC pairs (NPC = 0.036 0.0019 spines per m3,

SZ = 0.028 0.0021 spines per m3, t = 2.8, P = 0.084; Supplementary Figure 6). The 17 SZ-NPC pairs are a subset of the cohort studied in Shelton et al. (2015)5 and there is no overlap between the 17 SZ-NPC pairs and subjects studied in Sweet et al.6 Each pair was processed together to minimize experimental variability, and experimenter was blinded to subjects diagnosis throughout.

DNA preparation and bisulte conversionDNA (~10 g) was isolated from STG gray matter (~20 mg) using AllPrep

DNA/RNA/Protein Mini Kit (Qiagen, Valencia, CA, USA) and bisulte converted using EZ-96 DNA Methylation Kit (Zymo Research, Irvine, CA, USA), both as per manufacturers protocol.

DNAm arraysDNAm is the addition of a methyl group to a cytosine nucleotide within the context of a cytosine-phosphate-guanine (CpG) dinucleotide, usually, but also within the context of a cytosine-phosphate-H dinucleotide (CpH; H = adenine, cytosine or thymine).36 CpGs and CpHs are referred to as DNAm sites or sites in this manuscript. DNAm was measured at 485 577 sites (482 421 CpG dinucleotides, 3091 CpH dinucleotides and 65 SNPs) using Innium HumanMethylation450 Beadchip Array (HM450; Illumina, San Diego, CA, USA) as per manufacturers protocol. -values, the ratio of signal from a methylated probe relative to the sum of both methylated and unmethylated probes, were calculated. A -value corresponds to the proportion of a particular site that is methylated in a sample.

Data preprocessing and lteringData analyses were performed using the R software environment (http://www.r-project.org

Web End =www.r- http://www.r-project.org

Web End =project.org ). Color adjustment and background correction were performed using the bgAdjust2C method.37 Normalization was performed using the -mixture quantile normalization method.38

Multidimensional scaling (MDS)39 was used to visualize the degree of similarity among subjects using HM450 data. Prior to data ltering,

samples from four subjects were run in replicate and replicate samples from each of the four subjects clustered together (Supplementary Figure 1A). The -values for each replicate pair were averaged for the remaining analyses. Samples also segregated by sex (Supplementary Figure 1A) and this segregation remained after ltering out data from SNP probes (N = 65) and probes with detection P-values40.01 in any sample (N = 3390; Supplementary Figure 1B). After ltering out probe data from sex chromosomes (N = 11 648), samples no longer segregated by sex (Supplementary Figure 1C), but segregation by race became evident (Supplementary Figure 1D). Filtering data from invariable probes (s.d.o5th percentile; N = 23 547), did not alter similarity among samples (Supplementary Figure 1E). Data from 447 392 probes remained for downstream analysis.

Because samples did not segregate by sex on MDS analysis after ltering out probe data from sex chromosomes, sex was not considered a covariate in downstream analyses. Others have shown that DNAm sex differences on autosomal chromosomes are often small in magnitude and inconsistently reproduced.40,41 Given segregation by race on the MDS analysis, race was included as a covariate in downstream analyses. One subject in this study was of Asian Indian ancestry. This subject, consistent with known genetic architecture,42 clustered with the subjects of European ancestry (Supplementary Figure 1D) and was thus combined with this group for analyses. Although the samples did not segregate by age on the MDS analyses (Supplementary Figure 1F), age was considered as a covariate in downstream analyses given the overwhelming evidence that DNAm varies extensively by age.4345 Similarly, the samples did not segregate by PMI (data not shown) on the MDS analysis but because many factors that may have an impact on DSD in postmortem brain have been found to be particularly sensitive to PMI,46,47 PMI was considered as a covariate for downstream analysis. All analyses presented in the body of this paper adjust for race, age and PMI. Results of analyses adjusting only for race and age can be found in Supplementary Tables 36.

Cell population estimationDNAm differs markedly between neurons and glia.48 The proportion of neurons to glia in samples was estimated using a model based on -values from cell-type-specic sites.49 Neuronal proportion did not differ between SZ and NPC subjects (Supplementary Figure 2A).

Site-specic DNAm-DSD correlationsPearson correlations between DNAm (normalized -values) at each site and DSD (spines per m3) were calculated for all subjects. Examination of the linear DNAm-DSD correlations was performed for each of 3 groups (NPC and SZ subjects, NPC subjects and SZ subjects) using linear regression models with race, age and PMI adjusted.

Diagnosis-dependent differences in the DNAm-DSD correlations Differences in the slopes DNAm-DSD correlations were assessed using linear regression models. For each site, two models were tted: (1) DSD ~ 0+1 DNAm+2 diagnosis and (2) DSD ~ 0+1 DNAm +2 diagnosis+3 (DNAm diagnosis). The likelihood-ratio test (LRT) was then used to test whether the DNAm-DSD correlation differed between SZ and NPC subjects.

Candidate genes for mediating reduced DSD in SZFor each candidate gene, a permutation-based test was performed to assess whether the difference in slope of the DNAm-DSD correlation (SZNPC; across all sites in that gene) is signicant. The diagnosis label (SZ or NPC) was permuted 1000 times for all 34 samples. Within each permutation, the differences in slopes of the DNAm-DSD correlation (SZNPC) for all the sites in that gene were computed, and then a one-sample t-test statistic was computed for these difference values. Finally, the permutation-based P-value was generated by comparing this one-sample t-test statistic under the true diagnosis to those under the permutation.

RESULTSThere are more DNAm-DSD correlations than would be expected by chance in NPC, but not SZ, subjects

When all subjects are combined for analysis, there are more DNAm-DSD correlations than would be expected by chance

Translational Psychiatry (2017), 1 8

DNA methylation and spine density in schizophrenia B McKinney et al

3

Figure 1. Q-Q plots showing that DNAm-DSD correlation analysis is enriched in small P-values for (a) the group comprised of NPC and SZ subjects and (c) the group comprised of NPC subjects only, but not (e) the group comprised of SZ subjects only. Manhattan plots showing that DNAm at many sites correlate with DSD at a suggestive level of signicance (Po1 104) in (d) NPC subjects and that the number of such sites is fewer in (f) SZ subjects and (b) when NPC and SZ subjects are considered together. DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; SZ, schizophrenia.

(Figures 1a and b). This is true when NPC subjects only (Figures 1c and d) are considered. The number of DNAm-DSD correlations in SZ subjects is no more than would be expected by chance (Figures 1e and f). In the combined group, no DNAm-DSD correlations reached signicance (Po1 107) and 84 reached a suggestive level of signicance (Po1 10-4; Figure 1b). In NPC subjects, one DNAm-DSD correlation reached signicance and 150 reached a suggestive level of signicance (Figure 1d). In SZ subjects, no DNAm-DSD correlations reached signicance and 51 reached a suggestive level of signicance (Figure 1f and Table 3). After adjusting for potential confounders, DNAm-DSD correlations were, in general, less statistically signicant (Table 2).

DNAm-DSD correlations at multiple sites differ between NPC and SZ subjects

Not only were there many fewer strong DNAm-DSD correlations in SZ subjects, the slopes of the linear DNAm-DSD correlations

differed between NPC and SZ subjects at more sites than would be expected by chance (Figure 2a). The slopes of the DNAm-DSD correlations at two sites differed signicantly (Po1x10-7), and at

269 sites suggestively (Po1 10-4), between SZ and NPC subjects (Table 3, Supplementary Table 4 and Figure 2b).

Candidate genes for mediating reduced DSD in SZWe selected for more detailed follow-up genes meeting three criteria: (1) it was a gene for which there is evidence that one of its variants, either rare or common, genetically associates with SZ; (2) it was a gene in which a role in regulation of dendritic spines is established; and (3) it was one of the genes (or closest genes) to a site with a DNAm-DSD correlation reaching at least the suggestive level of signicance, Po1 104. For this latter criterion the more liberal suggestive level of signicance was chosen so as not to preclude detection of potentially causally related genes due to the limited power inherent in a study of the current sample size. Two

Translational Psychiatry (2017), 1 8

DNA methylation and spine density in schizophrenia B McKinney et al

4

Table 2. DNAm sites of DNAm-DSD correlations

Probe Marginal correlation Linear regression

Pearson's R P-value Slope P-value Gene Closest gene(s)

(DNAm-DSD) (DNAmDSD)

cg06741996 0.77 1.09E 07 0.17 8.30E 07 PDXK PDXK cg11828470 0.72 1.53E 06 0.23 2.04E 06 NLRP1 NLRP1 cg07596086 0.70 3.74E 06 1.04 1.84E 05 ZNF276 ZNF276, CHMP1A cg26805882 0.69 5.85E 06 0.38 1.12E 05 HAND2-AS1 HAND2-AS1 cg15393304 0.68 9.93E 06 0.76 7.96E 05 SMOC2 SMOC2

Abbreviations: DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; PMI, postmortem interval; SZ, schizophrenia. The ve DNAm sites at which DNAm correlates with DSD at a level of Po1x105 in the combined group (both SZ and NPC subjects) are listed in the table. See Supplementary

Table 3 for a list of all 84 DNAm sites signicant at Po1x104. The Pearson R and P-value for the marginal correlation between DNAm and DSD at each DNAm site as well as the slope and P-value for the regression equation between DNAm and adjusting for race, age and PMI are included in the table.

Figure 2. (a) Q-Q plot showing that the differential DNAm-DSD correlation analysis is enriched in small P-values. (b) Manhattan Plot showing that the slopes of DNAm-DSD correlation at two sites signicantly differ (Po1 107) between NPC and SZ subjects and that the slopes of

DNAm-DSD correlation differ at an additional 269 DNAm sites at a level of suggestive genome-wide signicance (Po1 10-4). DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; SZ, schizophrenia.

genes met all three criteria: Brain-specic angiogenesis inhibitor 1-associated protein 2 (BAIAP2) and Discs Large, Drosophila, Homolog of, 1 (DLG1).

BAIAP2DNAm-DSD correlations at two BAIAP2 sites (cg01276536 and cg23261327) reached a suggestive level of signicance (Supplementary Table 3; criterion 1). Multiple rare BAIAP2 mutations have been associated with SZ16,18 (criterion 2). BAIAP2 encodes a scaffolding and adaptor protein that regulates membrane and actin dynamics in dendritic spines and Baiap2 null mice exhibit reduced DSD17 (criterion 3).

DNAm (normalized -values) at 120 of 176, or 68.2%, of the BAIAP2 sites were relatively hypomethylated in SZ subjects (Figure 3a), signicantly more than the proportion of such sites observed among all sites analyzed (43.2%, Pearson 2-test, P = 0.00013).

DNAm was correlated with DSD at many sites across BAIAP2 in both SZ and NPC subjects but the direction and magnitude of correlation often differed by diagnosis (Figure 3b). The slopes of the linear DNAm-DSD correlations differed between NPC and SZ subjects using the LRT (Figure 3c). Further, the difference in slope of the DNAm-DSD correlation (SZ-NPC; across all 176 BAIAP2 sites) is signicant (permutation-based P = 0.011).

The BAIAP2-AS1 gene is an antisense-oriented long non-coding RNA with a head-to-head orientation with respect to the 5 region of BAIAP2. Like BAIAP2, BAIAP2-AS1 is characterized by DNAm-DSD

correlations at multiple sites, which differ between NPC and SZ subjects (Figure 3b). The LRT performed to assess whether the correlations differ by diagnosis showed an excess of small P-values compared to what would be expected by chance (data not shown). The difference in slopes of the DNAm-DSD correlation (SZ-NPC; across 13 BAIAP2-AS1 sites) is signicant (permutation-based Po0.001). Notably, the slope of the correlation was negative at all sites in NPC subjects and positive in 11 of 13 of the sites in SZ subjects (Supplementary Table 5 and Figure 3b).

DLG1One site for which the DNAm-DSD correlation differed signicantly between SZ and NPC subjects (cg07756562) is located in the region 5 to DLG1 (Table 3; criterion 1). Studies have found common DLG1 variants to be associated with SZ.20,21 Further,

studies of copy-number variation have found a signicant excess of deletions at the chromosomal position 3q29, which includes the DLG1 gene, in SZ50,51 (criterion 2). DLG1 encodes a scaffolding protein that participates in the localization of glutamate receptors to the post-synaptic membrane and overexpression of DLG1 in organotypic slice cultures alters dendritic spine morphology 19,52

(criterion 3).

DNAm sites in DLG1 and the genomic region immediately 5 to DLG1 were characterized by a wide range of DNAm levels (Supplementary Figure 3B). DNAm levels did not exhibit any discernible pattern with respect to DLG1 gene features, though such an assessment is limited by the fact that no data for DNAm

Translational Psychiatry (2017), 1 8

5

Table 3. DNAm sites at which slope of DNAm-DSD correlations differed most between NPC and SZ subjects

Probe P-value Gene Closest gene(s)

cg07756562 6.22E 08 DLG1, BDH1 cg02546690 6.99E 08 SERGEF SERGEF cg21278787 1.49E 07 TPGS2 cg04616529 5.14E 07 CLEC16A CLEC16A cg04021706 7.66E 07 AHRR AHRR cg03699749 1.26E 06 OSBPL2 OSBPL2 cg10758286 1.32E 06 TMEM51 TMEM51 cg26106316 1.39E 06 CCDC85A cg02260885 1.48E 06 IGF2BP2 IGF2BP2 cg01755336 2.20E 06 WDR20 WDR20 cg11495377 2.30E 06 TMEM18 cg23462402 2.35E 06 VPS16 cg00946491 3.00E 06 STARD13 STARD13 cg07139162 3.83E 06 ST3GAL2 ST3GAL2 cg09191732 4.10E 06 RABGEF1 cg02584610 4.39E 06 TPCN2 TPCN2 cg25269432 4.78E 06 NDUFA4 NDUFA4 cg12177942 5.05E 06 SRM SRM cg07110043 5.33E 06 FABP3 FABP3 cg09229797 5.82E 06 DHRS1 cg09020384 5.98E 06 ERICH1-AS1 cg14304674 6.39E 06 C9orf47 cg01646639 6.56E 06 SLC8A3 SLC8A3 cg23264776 6.59E 06 IGSF21 IGSF21 cg26306636 6.59E 06 RPL17-C18orf32 cg01674361 6.59E 06 MRGPRX4 cg10503635 6.72E 06 MOG MOG cg17277729 7.15E 06 TMEM51 cg25574849 7.22E 06 UBE4A UBE4A cg02293354 7.52E 06 HLA-DQA2 HLA-DQA2 cg16706631 7.53E 06 HIST1H4E HIST1H4E cg12645247 7.59E 06 ADM cg19433697 7.69E 06 FOXB1 cg02447304 8.69E 06 NA cg12960782 9.13E 06 DEPDC1B DEPDC1B cg16248435 9.23E 06 JARID2 JARID2 cg17134302 9.38E 06 FBXO36 FBXO36 cg00509921 9.48E 06 MAF MAF cg04018738 9.54E 06 VARS VARS cg14628708 9.77E 06 COG5 COG5

Abbreviations: DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; PMI, postmortem interval; SZ, schizophrenia. The 40 DNAm sites at which the DNAm-DSD correlation differed between NPC and SZ subjects at a level of Po1 105 (adjusted for age, race and

PMI) are listed in the table, see Supplementary Table 4 for list of sites at which the association differed at Po1 104 level.

DNA methylation and spine density in schizophrenia B McKinney et al

sites at the 3 end of DLG1 were available in the data set. No overall hypo- or hypermethylation in SZ is evident in DLG1 (Pearson 2-test, P = 1).

The linear DNAm-DSD correlation at site cg07756562 differed between SZ and NPC subjects (P = 6.22x10-8). At this site, DNAm

correlates positively with DSD in SZ subjects and negatively with DSD in NPC subjects (Supplementary Table 6, Figure 4b).

DISCUSSIONTo our knowledge, this is the rst postmortem brain study of the relationship of DNAm to DSD in SZ subjects. We evaluated the hypothesis that DNAm correlates with DSD in the human STG and that this relationship is disrupted in SZ subjects. Consistent with our hypothesis, we found DNAm to correlate with DSD at more sites than expected by chance in NPC, but not SZ, subjects. We also found that the slopes of DNAm-DSD correlations often differed between NPC and SZ subjects. We identied BAIAP2 and DLG1 as candidate genes for mediating DSD abnormalities in SZ.

DNAm-DSD correlationsOur ndings suggest that DNAm is an important upstream mechanism for generating normal DSD and that this mechanism is disrupted in SZ subjects. Although, to our knowledge, this is the rst time a DNAm-DSD relationship has been demonstrated in SZ, DNAm is altered in a number of contexts characterized by abnormal DSD.53 Perhaps the most convincing evidence for a causal effect of DNAm on DSD comes from the study of addiction models where overexpression of a DNA methyltransferase, and downstream DNAm, alone, is sufcient to alter DSD.54

The DNAm alterations observed in SZ, and thus the disrupted DNAm-DSD relationships, are likely to result from a combination of both genetic and environmental factors.36 Notably, common risk variants for SZ have been shown to regulate local DNAm,31,32 but

none of the sites in Tables 2 and 3 have been identied as targets of methylation quantitative trait loci (mQTLs) that overlap with SZ risk loci32 or neurodevelopmental mQTLs (http://epigenetics.essex.ac.uk/mQTL/

Web End =http://epigenetics.essex. http://epigenetics.essex.ac.uk/mQTL/

Web End =ac.uk/mQTL/ ).31 A number of environmental factors have been implicated in the pathogenesis of SZ,55 and many of them have been shown to alter DNAm.56 It is also important to consider that alterations in DNAm and DNAm-DSD correlations observed in SZ subjects may be the result of treatment-induced changes in the brain. We have previously found that antipsychotic treatment does not alter STG DSD in an animal model6 but accumulating evidence suggests that antipsychotics do alter DNAm.57 However, DNAm alterations are observed in peripheral blood from early SZ subjects with only brief (o16 weeks) antipsychotic treatment58

thus suggesting that not all DNAm alterations in SZ are explained by antipsychotic treatment. In some cases, SZ-associated DNAm alterations are normalized by antipsychotic drugs,59 perhaps suggesting that the therapeutic effect of antipsychotics are mediated, in part, by affecting DNAm.

Putative mechanisms underlying DNAm-DSD correlationThe study of DNAm function has historically focused on its role in promoter regions. In this context, DNAm usually blocks transcription. It is now recognized that DNAm function is context dependent60 and that intragenic and intergenic DNAm affects transcription. Notably, DNAm affects alternative promoter usage, regulation of short and long non-coding RNAs, alternative splicing and enhancer activity.61,62

DNAm-DSD correlations in BAIAP2 and DLG1 were distributed throughout intragenic, associated non-coding RNAs, and promoter regions, suggesting that DNAm may alter DSD in SZ by affecting transcription via both canonical and non-canonical mechanisms. DNAm at two BAIAP2 sites within intron 78 are strongly and positively correlated with DSD. These two sites are in a CCCTC-binding factor (CTCF) binding site. CTCF binds unmethylated DNA and, in intragenic contexts, promotes exon inclusion into the mature transcript.62 We predict that DNAm at these sites leads to an increase in BAIAP2 transcript variants with exclusion of exons local to intron 78 and that these transcript variants positively regulate DSD. Consistent with this prediction, multiple BAIAP2 transcript variants have been identied which differ with respect to the composition of their 3 end (Miyahara et al., 2003)

and primary data including mRNA and EST alignments suggest that there are transcripts that do not contain exon 7 and/or 8.63

Most of the BAIAP2 DNAm-DSD correlations in NPC subjects, however, were negative ones in which lower DNAm was correlated with higher DSD. DNAm at a site 5 to DLG1 (cg07756562) is similarly correlated with DSD in NPC subjects. Decreased DNAm in 5 regions is usually associated with increased total transcription.64 We suggest that lower DNAm at these sites allows for increased BAIAP2 and DLG1 transcription, promoting dendritic spine formation. Supporting this interpretation is evidence that BAIAP2 overexpression promotes DSD17 and DLG1

overexpression promotes dendrite growth and complexity.65,66

Translational Psychiatry (2017), 1 8

DNA methylation and spine density in schizophrenia B McKinney et al

6

Figure 3. (a) BAIAP2 is hypomethylated in SZ subjects relative to NPC subjects and (b) the slopes of the DNAm-DSD correlations at most BAIAP2 sites analyzed differ between SZ and NPC subjects but DNAm at the sites associated with both cg01276536 and cg23261327 positively correlates with DSD independent of diagnosis. (c) Q-Q plot showing that the differential DNAm-DSD correlation analysis is enriched in small P-values compared to what would be expected by chance for the DNAm sites analyzed in BAIAP2. DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; SZ, schizophrenia.

Figure 4. (a) DLG1 DNAm does not differ between subjects with SZ and NPC subjects. (b) The DNAm site cg0775662 is 5 of DLG1 and is one of two DNAm sites in which the differential correlation between DNAm and DSD reached signicance. DNAm, DNA methylation; DSD, dendritic spine density; NPC, non-psychiatric control; SZ, schizophrenia.

Other DNAm-DSD correlations are annotated to BAIAP2-AS1 and are also relatively hypomethylated in SZ subjects. We anticipate increased BAIAP2-AS1 transcription in SZ as a result of this hypomethylation. It is difcult to know how higher levels of BAIAP2-AS1 might affect expression of BAIAP2. Antisense long non-coding RNAs, like BAIAP2-AS1, often regulate local gene transcription at multiple levels 67 but BAIAP2-AS1 has not been studied.

DNAm differences between SZ and NPC subjects at particular sites is one mechanism by which the DNAm-DSD correlations may be disrupted in SZ. Indeed, our data suggest that there are many sites where DNAm differs between SZ and NPC subjects (Supplementary Table 2 and Supplementary Figure 4). Global DNAm, however, does not appear to differ between SZ and NPC subjects (Supplementary Figure 5). Disruptions of DNAm-DSD correlations in SZ that do not result from a change in DNAm may reect an abnormality downstream of DNAm (e.g., disrupted binding of a DNAm-dependent transcription factor and so on).

LimitationsDespite plausible relationships between DNAm in multiple genes (including BAIAP2 and DLG1) and DSD, the ndings, like those of any postmortem brain study, are only correlative and cannot establish a mechanistic relationship. Our use of SZ risk gene and

DSD regulator criteria to dene candidate genes limits the ability to identify novel genes important in SZ pathophysiology or dendritic spine regulation. However, because of the large number of sites tested, there is a likelihood that some DNAm-DSD correlations are spurious and not relevant to the DSD phenotype in SZ. We chose to use these criteria to increase the probability of identifying DNAm alterations that may contribute causally to the DSD phenotype in SZ. Another potential technical limitation is that the sites studied were constrained by the use of the HM450 array. It only measures a fraction of the 428 million DNAm sites in the human genome and coverage is biased toward CpG islands, promoters and genic regions.

Conclusions and future directionsThe study of reduced DSD as an intermediate phenotype in SZ across different levels of analysis including genetics,68

transcriptomics69 and proteomics35 has provided valuable insights into SZ. This study suggests that epigenetic alterations, specically disrupted DNAm-DSD correlations, in SZ may be a mechanism for SZ-related reductions in DSD and justify future studies probing this relationship.

Studies to conrm the DNAm-DSD relationship and the effect of DNAm on candidate gene transcription in additional, larger

Translational Psychiatry (2017), 1 8

DNA methylation and spine density in schizophrenia B McKinney et al

7

cohorts will be a critical next step. Also, DNAm varies widely between cell types in the human cerebral cortex, with studies indicating that DNAm in GABA neurons is more extensive by several fold than in glutamatergic neurons.70 Thus, future cell-type-specic studies, using laser capture microdissection,71 uorescent-activated nuclei sorting72 or similar methods, may increase the likelihood of detecting diagnosis-specic DNAm alterations by decreasing variability and revealing ndings that were masked by opposing DNAm changes in different cell types. Studies in model systems to evaluate the correlative versus causal nature of the DNAm-DSD relationship will be also important. Understanding the DNAm-DSD relationship may facilitate the development of new, and/or the repurposing of existing, DNAm modifying drugs for SZ treatment.

CONFLICT OF INTEREST

The authors declare no conict of interest.

ACKNOWLEDGMENTS

This work was supported by NIH Grants RO1 MH071533 (RAS), RO3 MH108849 (YD), T32 MH016804 (BCM), and KL2 TR001856 (BCM). The content is solely the responsibility of the authors and does not necessarily represent the ofcial views of the National Institutes of Health, the Department of Veterans Affairs, or the United States Government.

AUTHOR CONTRIBUTIONSDAL currently receives investigator-initiated research support from Pzer and in 20122014 served as a consultant in the areas of target identication and validation and new compound development to Autifony, Bristol-Myers Squibb, Concert Pharmaceuticals and Sunovion. The remaining authors declare no conict of interest.

REFERENCES

1 Lewis DA, Sweet RA. Schizophrenia from a neural circuitry perspective: advancing toward rational pharmacological therapies. J Clin Invest 2009; 119: 706716.

2 Javitt DC, Sweet RA. Auditory dysfunction in schizophrenia: integrating clinical and basic features. Nat Rev Neurosci 2015; 16: 535550.

3 Glausier JR, Lewis DA. Dendritic spine pathology in schizophrenia. Neuroscience 2013; 251: 90107.

4 Moyer CE, Shelton MA, Sweet RA. Dendritic spine alterations in schizophrenia. Neurosci Lett 2015; 601: 4653.

5 Shelton MA, Newman JT, Gu H, Sampson AR, Fish KN, MacDonald ML et al. Loss of microtubule-associated protein 2 immunoreactivity linked to dendritic spine loss in schizophrenia. Biol Psychiatry 2015; 78: 374385.

6 Sweet RA, Henteleff RA, Zhang W, Sampson AR, Lewis DA. Reduced dendritic spine density in auditory cortex of subjects with schizophrenia. Neuropsycho-pharmacology 2009; 34: 374389.

7 Preston GA, Weinberger DR. Intermediate phenotypes in schizophrenia: a selective review. Dialogues Clin Neurosci 2005; 7: 165179.

8 Bhatt DH, Zhang S, Gan WB. Dendritic spine dynamics. Annu Rev Physiol 2009; 71: 261282.

9 Balu DT, Coyle JT. Neuronal D-serine regulates dendritic architecture in the somatosensory cortex. Neurosci Lett 2012; 517: 7781.

10 Balu DT, Li Y, Puhl MD, Benneyworth MA, Basu AC, Takagi S et al. Multiple risk pathways for schizophrenia converge in serine racemase knockout mice, a mouse model of NMDA receptor hypofunction. Proc Natl Acad Sci U S A 2013; 110: E2400E2409.

11 Schizophrenia Working Group of the Psychiatric Genomics C. schizophrenia-associated genetic loci. Nature 2014; 511: 421427.

12 Cahill ME, Remmers C, Jones KA, Xie Z, Sweet RA, Penzes P. Neuregulin1 signaling promotes dendritic spine growth through kalirin. J Neurochem 2013; 126: 625635.

13 Remmers C, Sweet RA, Penzes P. Abnormal kalirin signaling in neuropsychiatric disorders. Brain Res Bull 2014; 103: 2938.

14 Kushima I, Nakamura Y, Aleksic B, Ikeda M, Ito Y, Shiino T et al. Resequencing and association analysis of the KALRN and EPHB1 genes and their contribution to schizophrenia susceptibility. Schizophr Bull 2012; 38: 552560.

15 Russell TA, Blizinsky KD, Cobia DJ, Cahill ME, Xie Z, Sweet RA et al. A sequence variant in human KALRN impairs protein function and coincides with reduced cortical thickness. Nat Commun 2014; 5: 4858.

16 Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 2014; 506: 179184.

17 Kang J, Park H, Kim E. IRSp53/BAIAP2 in dendritic spine development, NMDA receptor regulation, and psychiatric disorders. Neuropharmacology 2016; 100: 2739.

18 Purcell SM, Moran JL, Fromer M, Ruderfer D, Solovieff N, Roussos P et al. A polygenic burden of rare disruptive mutations in schizophrenia. Nature 2014; 506: 185190.

19 Poglia L, Muller D, Nikonenko I. Ultrastructural modications of spine and synapse morphology by SAP97. Hippocampus 2011; 21: 990998.

20 Sato J, Shimazu D, Yamamoto N, Nishikawa T. An association analysis of synapse-associated protein 97 (SAP97) gene in schizophrenia. J Neural Transm (Vienna) 2008; 115: 13551365.

21 Uezato A, Kimura-Sato J, Yamamoto N, Iijima Y, Kunugi H, Nishikawa T. Further evidence for a male-selective genetic association of synapse-associated protein 97 (SAP97) gene with schizophrenia. Behav Brain Funct 2012; 8: 2.

22 Hall J, Trent S, Thomas KL, O'Donovan MC, Owen MJ. Genetic risk for schizophrenia: convergence on synaptic pathways involved in plasticity. Biol Psychiatry 2015; 77: 5258.

23 Holtmaat A, Svoboda K. Experience-dependent structural synaptic plasticity in the mammalian brain. Nat Rev Neurosci 2009; 10: 647658.

24 Chen CC, Lu J, Zuo Y. Spatiotemporal dynamics of dendritic spines in the living brain. Front Neuroanat 2014; 8: 28.

25 Penzes P, Buonanno A, Passafaro M, Sala C, Sweet RA. Developmental vulnerability of synapses and circuits associated with neuropsychiatric disorders. J Neurochem 2013; 126: 165182.

26 Chen X, Leischner U, Rochefort NL, Nelken I, Konnerth A. Functional mapping of single spines in cortical neurons in vivo. Nature 2011; 475: 501505.

27 Jaffe AE, Shin J, Collado-Torres L, Leek JT, Tao R, Li C et al. Developmental regulation of human cortex transcription and its clinical relevance at single base resolution. Nat Neurosci 2015; 18: 154161.

28 Mill J, Tang T, Kaminsky Z, Khare T, Yazdanpanah S, Bouchard L et al. Epigenomic proling reveals DNA-methylation changes associated with major psychosis. Am J Hum Genet 2008; 82: 696711.

29 Xiao Y, Camarillo C, Ping Y, Arana TB, Zhao H, Thompson PM et al. The DNA methylome and transcriptome of different brain regions in schizophrenia and bipolar disorder. PLoS ONE 2014; 9: e95875.

30 Connor CM, Akbarian S. DNA methylation changes in schizophrenia and bipolar disorder. Epigenetics 2008; 3: 5558.

31 Hannon E, Spiers H, Viana J, Pidsley R, Burrage J, Murphy TM et al. Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci. Nat Neurosci 2016; 19: 4854.

32 Jaffe AE, Gao Y, Deep-Soboslay A, Tao R, Hyde TM, Weinberger DR et al. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat Neurosci 2016; 19: 4047.

33 Numata S, Ye T, Herman M, Lipska BK. DNA methylation changes in the postmortem dorsolateral prefrontal cortex of patients with schizophrenia. Front Genet 2014; 5: 280.

34 Ruzicka WB, Subburaju S, Benes FM. Circuit- and diagnosis-specic DNA methylation changes at gamma-aminobutyric acid-related genes in postmortem human hippocampus in schizophrenia and bipolar disorder. JAMA Psychiatry 2015; 72: 541551.

35 MacDonald ML, Ding Y, Newman J, Hemby S, Penzes P, Lewis DA et al. Altered glutamate protein co-expression network topology linked to spine loss in the auditory cortex of schizophrenia. Biol Psychiatry 2015; 77: 959968.

36 Nestler EJ, Pena CJ, Kundakovic M, Mitchell A, Akbarian S. Epigenetic basis of mental illness. Neuroscientist 2015; 22: 447463.

37 Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics 2008; 24: 15471548.

38 Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Innium 450 k DNA methylation data. Bioinformatics 2013; 29: 189196.

39 Cox TF, Cox MAA. Multidemensional Scaling. 2nd Chapman and Hall/CRC: Boca Raton, FL, 2001.

40 McCarthy NS, Melton PE, Cadby G, Yazar S, Franchina M, Moses EK et al. Meta-analysis of human methylation data for evidence of sex-specic autosomal patterns. BMC Genomics 2014; 15: 981.

41 Youse P, Huen K, Dave V, Barcellos L, Eskenazi B, Holland N. Sex differences in DNA methylation assessed by 450 K BeadChip in newborns. BMC Genomics 2015; 16: 911.

Translational Psychiatry (2017), 1 8

DNA methylation and spine density in schizophrenia B McKinney et al

8

42 Xing J, Watkins WS, Shlien A, Walker E, Huff CD, Witherspoon DJ et al. Toward a more uniform sampling of human genetic diversity: a survey of worldwide populations by high-density genotyping. Genomics 2010; 96: 199210.

43 Horvath S. DNA methylation age of human tissues and cell types. Genome Biol 2013; 14: R115.

44 Akbarian S, Beeri MS, Haroutunian V. Epigenetic determinants of healthy and diseased brain aging and cognition. JAMA Neurol 2013; 70: 711718.

45 McKinney BC, Lin CW, Oh H, Tseng GC, Lewis DA, Sibille E. Hypermethylation of BDNF and SST genes in the orbital frontal cortex of older individuals: a putative mechanism for declining gene expression with age. Neuropsychopharmacology 2015; 40: 26042613.

46 Lewis DA. The human brain revisited: opportunities and challenges in postmortem studies of psychiatric disorders. Neuropsychopharmacology 2002; 26: 143154.47 McCullumsmith RE, Hammond JH, Shan D, Meador-Woodruff JH. Postmortem brain: an underutilized substrate for studying severe mental illness. Neuropsychopharmacology 2015; 40: 1307.

48 Kozlenkov A, Roussos P, Timashpolsky A, Barbu M, Rudchenko S, Bibikova M et al. Differences in DNA methylation between human neuronal and glial cells are concentrated in enhancers and non-CpG sites. Nucleic Acids Res 2014; 42: 109127.

49 Guintivano J, Aryee MJ, Kaminsky ZA. A cell epigenotype specic model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression. Epigenetics 2013; 8: 290302.

50 Mulle JG, Dodd AF, McGrath JA, Wolyniec PS, Mitchell AA, Shetty AC et al. Microdeletions of 3q29 confer high risk for schizophrenia. Am J Hum Genet 2010; 87: 229236.

51 Quintero-Rivera F, Shari-Hannauer P, Martinez-Agosto JA. Autistic and psychiatric ndings associated with the 3q29 microdeletion syndrome: case report and review. Am J Med Genet A 2010; 152A: 24592467.

52 Fourie C, Li D, Montgomery JM. The anchoring protein SAP97 inuences the trafcking and localisation of multiple membrane channels. Biochim Biophys Acta 2014; 1838: 589594.

53 Smrt RD, Zhao X. Epigenetic regulation of neuronal dendrite and dendritic spine development. Front Biol (Beijing) 2010; 5: 304323.

54 LaPlant Q, Vialou V, Covington HE 3rd, Dumitriu D, Feng J, Warren BL et al. Dnmt3a regulates emotional behavior and spine plasticity in the nucleus accumbens. Nat Neurosci 2010; 13: 11371143.

55 Janoutova J, Janackova P, Sery O, Zeman T, Ambroz P, Kovalova M et al. Epidemiology and risk factors of schizophrenia. Neuro Endocrinol Lett 2016; 37: 18.

56 Aberg KA, McClay JL, Nerella S, Clark S, Kumar G, Chen W et al. Methylome-wide association study of schizophrenia: identifying blood biomarker signatures of environmental insults. JAMA Psychiatry 2014; 71: 255264.

57 Castellani CA, Melka MG, Diehl EJ, Laufer BI, O'Reilly RL, Singh SM. DNA methylation in psychosis: insights into etiology and treatment. Epigenomics 2015; 7: 6774.58 Nishioka M, Bundo M, Koike S, Takizawa R, Kakiuchi C, Araki T et al. Comprehensive DNA methylation analysis of peripheral blood cells derived from patients with rst-episode schizophrenia. J Hum Genet 2013; 58: 9197.

59 Abdolmaleky HM, Pajouhanfar S, Faghankhani M, Joghataei MT, Mostafavi A, Thiagalingam S. Antipsychotic drugs attenuate aberrant DNA methylation of

DTNBP1 (dysbindin) promoter in saliva and post-mortem brain of patients with schizophrenia and Psychotic bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2015; 168: 687696.60 Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet 2012; 13: 484492.61 Kulis M, Queiros AC, Beekman R, Martin-Subero JI. Intragenic DNA methylation in transcriptional regulation, normal differentiation and cancer. Biochim Biophys Acta 2013; 1829: 11611174.62 Lev Maor G, Yearim A, Ast G. The alternative role of DNA methylation in splicing regulation. Trends Genet 2015; 31: 274280.63 Kersey PJ, Allen JE, Armean I, Boddu S, Bolt BJ, Carvalho-Silva D et al. Ensembl Genomes 2016: more genomes, more complexity. Nucleic Acids Res 2016; 44: D574D580.64 Baubec T, Schubeler D. Genomic patterns and context specic interpretation of DNA methylation. Curr Opin Genet Dev 2014; 25: 8592.65 Zhang L, Hsu FC, Mojsilovic-Petrovic J, Jablonski AM, Zhai J, Coulter DA et al.Structure-function analysis of SAP97, a modular scaffolding protein that drives dendrite growth. Mol Cell Neurosci 2015; 65: 3144.66 Zhou W, Zhang L, Guoxiang X, Mojsilovic-Petrovic J, Takamaya K, Sattler R et al.GluR1 controls dendrite growth through its binding partner, SAP97. J Neurosci 2008; 28: 1022010233.67 Villegas VE, Zaphiropoulos PG. Neighboring gene regulation by antisense long non-coding RNAs. Int J Mol Sci 2015; 16: 32513266.68 Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N et al. Schizophrenia risk from complex variation of complement component 4. Nature 2016; 530: 177183.69 Datta D, Arion D, Corradi JP, Lewis DA. Altered expression of CDC42 signaling pathway components in cortical layer 3 pyramidal cells in schizophrenia. Biol Psychiatry 2015; 78: 775785.70 Kozlenkov A, Wang M, Roussos P, Rudchenko S, Barbu M, Bibikova M et al.Substantial DNA methylation differences between two major neuronal subtypes in human brain. Nucleic Acids Res 2016; 44: 25932612.71 Bernard R, Burke S, Kerman IA. Region-specic in situ hybridization-guided laser-capture microdissection on postmortem human brain tissue coupled with gene expression quantication. Methods Mol Biol 2011; 755: 345361.72 Jiang Y, Matevossian A, Huang HS, Straubhaar J, Akbarian S. Isolation of neuronal chromatin from brain tissue. BMC Neurosci 2008; 9: 42.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the articles Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

Web End =http:// http://creativecommons.org/licenses/by-nc-nd/4.0/

Web End =creativecommons.org/licenses/by-nc-nd/4.0/

The Author(s) 2017

Supplementary Information accompanies the paper on the Translational Psychiatry website (http://www.nature.com/tp)

Translational Psychiatry (2017), 1 8