Identification of Sialyltransferase 8B as a Generalized
Susceptibility Gene for Psychotic and Mood Disorders on
Erica Z. McAuley1,2, Anna Scimone1, Yash Tiwari1,2,3, Giti Agahi1, Bryan J. Mowry4,5,
Elizabeth G. Holliday , Jennifer A. Donald , Cynthia Shannon Weickert
Peter R. Schofield1,2,3*, Janice M. Fullerton1,2,3*
46 1,3,7, Phillip B. Mitchell7,8,
1Psychiatric Genetics, Neuroscience Research Australia, Sydney, New South Wales, Australia, 2School of Medical Sciences, University of New South Wales, Sydney, New
South Wales, Australia, 3Developmental Neurobiology, Schizophrenia Research Institute, Sydney, New South Wales, Australia, 4Genetics, Queensland Centre for Mental
Health Research, Brisbane, Queensland, Australia, 5Queensland Brain Institue, University of Queensland, Brisbane, Queensland, Australia, 6Department of Biological
Sciences, Macquarie University, Sydney, New South Wales, Australia, 7School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia, 8Black
Dog Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
We previously identified a significant bipolar spectrum disorder linkage peak on 15q25-26 using 35 extended families with a
broad clinical phenotype, including bipolar disorder (types I and II), recurrent unipolar depression and schizoaffective
disorder. However, the specific gene(s) contributing to this signal had not been identified. By a fine mapping association
study in an Australian case-control cohort (n=385), we find that the sialyltransferase 8B (ST8SIA2) gene, coding for an
enzyme that glycosylates proteins involved in neuronal plasticity which has previously shown association to both
schizophrenia and autism, is associated with increased risk to bipolar spectrum disorder. Nominal single point association
was observed with SNPs in ST8SIA2 (rs4586379, P=0.0043; rs2168351, P=0.0045), and a specific risk haplotype was
identified (frequency: bipolar vs controls=0.41 vs 0.31; x2=6.46, P=0.011, OR=1.47). Over-representation of the specific
risk haplotype was also observed in an Australian schizophrenia case-control cohort (n=256) (x2=8.41, P=0.004, OR=1.82).
Using GWAS data from the NIMH bipolar disorder (n=2055) and NIMH schizophrenia (n=2550) cohorts, the equivalent
haplotype was significantly over-represented in bipolar disorder (x2=5.91, P=0.015, OR=1.29), with the same direction of
effect in schizophrenia, albeit non-significant (x2=2.3, P=0.129, OR=1.09). We demonstrate marked down-regulation of
ST8SIA2 gene expression across human brain development and show a significant haplotype6diagnosis effect on ST8SIA2
mRNA levels in adult cortex (ANOVA: F(1,87)=6.031, P=0.016). These findings suggest that variation the ST8SIA2 gene is
associated with increased risk to mental illness, acting to restrict neuronal plasticity and disrupt early neuronal network
formation, rendering the developing and adult brain more vulnerable to secondary genetic or environmental insults.
Citation: McAuley EZ, Scimone A, Tiwari Y, Agahi G, Mowry BJ, et al. (2012) Identification of Sialyltransferase 8B as a Generalized Susceptibility Gene for Psychotic
and Mood Disorders on Chromosome 15q25-26. PLoS ONE 7(5): e38172. doi:10.1371/journal.pone.0038172
Editor: Chunyu Liu, University of Illinois at Chicago, United States of America
Received March 13, 2012; Accepted May 1, 2012; Published May 31, 2012
Copyright: ? 2012 McAuley et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by the Schizophrenia Research Institute (Australia), and the National Health and Medical Research Council (Australia) via
project grants (510216, 630574), program grant (510135), and personnel support of Dora Lush Scholarship (325641) to EZM, Howard Florey Centenary Fellowship
(325643) to JMF, Senior Principal Research Fellowship (157209) to PRS. The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com (JMF); firstname.lastname@example.org (PRS)
Bipolar disorder and schizophrenia are severe heritable mental
illnesses. Epidemiological and genetic studies [1,2] suggest that
bipolar disorder and schizophrenia share common risk factors.
Candidate schizophrenia susceptibility genes identified first
through linkage, including DISC1 , DAOA , and NRG1
, have subsequently shown association to bipolar disorder
[6,7,8], providing evidence that these related but clinically
distinct illnesses share genetic risk. Recent GWAS studies have
identified genes that contribute to disease risk for both illnesses,
for example ZNF804A  and CACNA1C ; however, as these
genes each contribute around 1% of the phenotypic variance,
much of the shared genetic risk remains unexplained. It may be
that part of the ‘missing heritability’ lies in highly penetrant,
family specific risk factors , and that traditional linkage
approaches in either schizophrenia or bipolar families may
identify specific high-penetrance risk genes, which can then be
interrogated in larger population-based cohorts to determine
their effect at a population level.
We previously reported evidence for a bipolar disorder
susceptibility locus within a 17 cM (6.2 Mb) interval on chromo-
some 15q25-26 through a genome-wide linkage analysis in 35
Australian multi-generational bipolar disorder families with a
broad spectrum of clinical diagnoses, including major depressive
disorder and schizoaffective disorder-manic type . The 6.2 Mb
linkage interval (86.63–92.82 Mb: NCBI Build 36.1) contains over
50 known genes, many of which are expressed in the brain.
Haplotype narrowing in the 35 Australian pedigrees using an
PLoS ONE | www.plosone.org1 May 2012 | Volume 7 | Issue 5 | e38172
autosomal dominant model for a highly penetrant gene of large
effect implicated a 2.5 Mb high priority region (90.32–92.82 Mb)
, which contains 3 hypothetical genes and 5 protein coding
genes, namely: SLCO3A1, ST8SIA2, CHD2, RGMA and MCTP2.
Of these, the alpha-2,8-sialyltransferase 2 gene (ST8SIA2) – an
enzyme responsible for protein glycosylation – has previously been
implicated as a putative susceptibility gene for schizophrenia ,
and autism spectrum disorder (verbal subtype) .
We conducted a fine-mapping association study of the
susceptibility locus on 15q25-26 in an Australian case-control
cohort, providing evidence for association of ST8SIA2 with bipolar
disorder. The specific risk haplotype was then investigated for
association in three independent case-control cohorts with either
bipolar disorder or schizophrenia from Australia and the USA.
Further, we explore the temporal expression profile of ST8SIA2
over postnatal human development in the dorsolateral prefrontal
cortex, and investigate the effect of the associated haplotypes on
global ST8SIA2 gene expression in the adult human dorsolateral
Genotyping and association analysis in the Australian
bipolar disorder cohort
From a pool of 376 genotyped SNPs, 23 failed quality control
measures (93.9% pass) and 4 failed the Hardy-Weinberg
equilibrium test, and were omitted from the results. Eight
individuals (2 BPI; 6 controls) were removed from analyses
(97.9% pass) due to low genotype call rates (10% missingness).
The 349 successfully genotyped SNPs were tested for association
with bipolar disorder (Figure 1). Nominally significant association
(P,0.05) was found with 18 SNPs, in three main clusters across
three adjacent genes SLCO3A1, ST8SIA2, and C15orf32 (Table 1).
Association with 14 of these SNPs held true when empirical P
values were obtained through 10,000 replicate permutations
(Table 1). The strongest single point association signals were
found with SNP rs4586379 (P=0.0043, empirical P=0.006),
which lies 16 kb upstream from ST8SIA2, and rs2168351
(P=0.0045, empirical P=0.007) in the fourth intron of ST8SIA2.
Haplotypes were tested for association with bipolar disorder
using a 3 SNP sliding window analysis, and global significant P
values were found for a haplotype upstream of ST8SIA2
(rs11634097, rs8027941 and rs4586379: omnibus P=0.04,
empirical P=0.050) and for a haplotype with one SNP upstream
of ST8SIA2 and two within the first intron of the gene (rs4586379,
rs2035645 andrs4777973: omnibus
P=0.056). Significant global association was also found for a 3
SNP haplotype across intron 2 of the SLCO3A1 gene (rs1400786,
rs995002 and rs8031518; omnibus P=0.034, empirical P=0.031),
upstream of ST8SIA2.
Implementing regression-based conditional haplotype associa-
tion testing, we investigated various haplotypes with the
individually associated ST8SIA2 SNPs. Global significant associ-
ation across a 6 SNP haplotype spanning 54 kb, starting 16 kb
upstream of ST8SIA2 through to the middle of intron 2, was
found with SNPs rs4586379, rs2035645, rs4777974, rs11637898,
rs11074070 and rs3784735 (P=0.017). Three specific haplotypes
had a minimum haplotype frequency greater than 10 percent,
two of which demonstrated significant association with bipolar
disorder: the most common haplotype AAGGAA (x2=6.90,
P=0.0086, OR 1.47), had a higher frequency in cases (0.41) than
in controls (0.31) constituting a putative bipolar risk haplotype;
and its flip variant GCAACC (x2=4.95, P=0.026, OR 0.61),
representing the third most common haplotype had a higher
frequency in controls (0.19) than in cases (0.13), constituting a
putative protective haplotype (Table 2).
Statistical methods to account for type I (false positive) error
rates after multiple comparisons and are generally conservative,
and may also increase the chance of type II (false negative)
errors, particularly for small effect sizes in large numbers of
SNPs . To correct for multiple comparisons, we determined
the effective number of independent tests using the simpleM
method , and LD based pruning in PLINK , followed
by Sˇida ´k correction. The simpleM method yielded 295
independent tests, and recursive SNP removal in PLINK
yielded 174–210 independent SNPs using the recommended
variance inflation factor values (VIF range=1.5–2.0). No SNPs
or haplotypes passed the Sˇida ´k correction threshold to exclude
type I error after multiple testing correction (at a=0.05,
simpleM: P,0.00017; PLINK: P,0.00028). However, as
replication is the ‘gold standard’ to refute type I error, we
sought to determine whether the observed association in the LD
block containing ST8SIA2 was replicable in other bipolar
disorder cohorts, and to determine whether this same LD risk
haplotype in ST8SIA2 may also increase risk in other cohorts
that included schizophrenia patients.
Testing for association in an Australian schizophrenia
The 6 SNPs comprising the risk haplotype were genotyped in an
Australian schizophrenia cohort, and haplotype phasing and
association analysis conducted in PLINK. We found that the
specific AAGGAA risk haplotype was significantly over-represent-
ed in schizophrenia cases compared to controls when a conditional
analysis was performed (x2=8.04, P=0.004, OR=2.62) (Table 2).
Similarly, the protective haplotype was over-represented in
controls on conditional haplotype analysis (x2=7.25, P=0.007,
OR 0.768). Single SNP analysis did not yield significant evidence
for association (p values all $0.075).
Figure 1. Association analysis and gene map of 6.5 Mb
candidate locus. 2Log of the P values of genotyped SNPs are
represented on the y-axis with chromosome position in kilobases on
the x-axis. The red diamonds indicate the P values less than 0.05. The
relative positions of protein coding genes in the locus are shown above.
ST8SIA2: Generalised Risk Gene for Mental Illness
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Table 1. SNPs with nominally significant P values (,0.05) and their empirical P values.
location in gene
AGC1 intron 2
SLCO3A1 intron 2
SLCO3A1 intron 4
SLCO3A1 intron 9
16 kb upstream of
ST8SIA2 intron 1
ST8SIA2 intron 1
ST8SIA2 intron 1
ST8SIA2 intron 1
ST8SIA2 intron 1
ST8SIA2 intron 2
ST8SIA2 intron 4
C15orf32 exon 1
C15orf32 intron 1
C15orf32 intron 2
RGMA intron 2
No known gene
No known gene
aSignificant pointwise P values derived empirically through 10,000 permutations (EMP1 P,0.05). Empirical P values for all SNPs are non-significant after multiple testing correction (EMP2 P.0.05).
bminor allele of each SNP is listed first.
ST8SIA2: Generalised Risk Gene for Mental Illness
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Replication in the NIMH bipolar disorder and
Using GWAS data downloaded from GAIN, we determined
whether the over representation of the identified risk haplotype
was replicable. First, we examined population stratification using
whole genome SNP data via PLINK, and only one significant
cluster was identified for both the bipolar and schizophrenia
cohorts (Figure 2). Permutation tests for between group differences
of identity by state (IBS) showed that cases in either cohort did not
show more IBS on average than expected by chance (bipolar:
p=0.208; schizophrenia: p=0.552). Next, we examined whether
the Australian risk haplotype was assessable using SNP genotypes
from the Affymetrix 6.0 chip. Of the six SNPs making up the
Australian risk haplotype, only two were genotyped in the NIMH
data: SNP_A-8471284 (rs4586379 at 90722031 bp, with T
representing the risk allele and C the protective allele), and
SNP_A-2278085 (rs2035645 at 90747330 bp, with T representing
the risk allele and G the protective allele). Accurate representation
of the specific 6 SNP risk haplotype in the NIMH data was not
possible by imputation, as rs11074070 was not genotyped in
HAPMAP3 reference panel (release 28) and rs11637898 per-
formed poorly, with 23.5% of the sample failing to be imputed
To determine whether a different combination of SNPs could
be used to define a surrogate ‘‘risk’’ haplotype in the NIMH
affymetrix data, we investigated the haplotype structure of the
associated LD block in HAPMAP3 data from Caucasian
Europeans (release 28), where both the Australian and NIMH
SNPs had been genotyped (Figure 3). With the addition of three
intermediate Affymetrix SNPs (SNP_A-1920907 (rs8025225) at
90741904 bp, SNP_A-1787148 (rs11074066) at 90745868 bp and
SNP_A-4204154 (rs11074067) at 90747302 bp) we were able to
observe three common haplotypes (MAF.0.1), each of which had
a similar frequency distribution in individuals genotyped with both
sets of markers (Figure 3). Given the similarities in haplotype
frequencies, and the informativity of rs4586379 and rs2035645 in
defining the risk and protective haplotypes, the 5 SNP Affymetrix
haplotype was considered to be a reasonable surrogate for the
Australian 6 SNP haplotype.
Using the five Affymetrix SNPs to phase haplotypes (average
posterior probability of haplotype phases given genotype da-
ta=0.96160.085), we found that the frequencies of the three main
haplotypes were comparable between the NIMH sample and
those observed with 6 SNPs in the Australian population (0.399 vs
0.351, 0.237 vs 0.228 and 0.169 vs 0.149). The most common
haplotype (TTAGT, equivalent to the risk haplotype identified in
the Australian cohort) was significantly over represented in the
NIMH bipolar disorder cases compared to controls (frequen-
cy=0.432 vs 0.398, x2=5.91, df=1, P=0.0151, OR=1.29),
using a conditional haplotype test (Table 2). This haplotype also
showed the same direction of effect in the NIMH cases with
schizophrenia compared to controls (frequency=0.421 vs 0.396),
although it did not reach statistical significance (x2=2.3, df=1,
ST8SIA2 developmental profile
Analysis of microarray data  showed a significant negative
correlation between age and ST8SIA2 gene expression (r=20.93,
P,0.00001), with a steady decrease from birth through to
adulthood. This was confirmed by RT-PCR, with high levels of
expression seen in the neonate and infant groups, and a gradual
decrease in expression from toddler to adult (Figure 4). Impor-
tantly, we found that despite being developmentally regulated,
ST8SIA2 mRNA is detectable in the adult DLPFC.
ST8SIA2 expression in adult bipolar disorder and
Consistent with the Australian and US based case-control
cohorts, there was a higher frequency of risk haplotypes in SMRI
cases with bipolar and schizophrenia compared to controls
Table 2. Summary of haplotype frequencies and associations for Australian and NIMH case-control cohorts and SMRI postmortem
cohorthaplotype Freq (all)Freq (cases) Freq (controls)
P valueOdds ratio (95%CI)
0.3510.405 0.3136.46 0.0111.473 (1.09–1.99)
0.348 0.415 0.297 8.410.0041.82 (1.2–2.74)
0.3990.432 0.3985.91 0.015 1.29 (1.03–1.33)
NIMH SZ riskb
0.3950.4210.3962.30 0.129 1.09 (0.97–1.23)
SMRI (BP+SZ) riska
0.3190.3770.2374.78 0.029 2.185 (1.05–4.56)
0.3190.357 0.2372.24 0.134 1.865 (0.81–4.30)
0.319 0.3950.2375.080.024 2.456 (1.08–5.58)
Aus BP protectivec
0.1490.1290.1925.97 0.015 0.5857 (0.38–0.90)
0.1380.1050.1775.300.021 0.515 (0.29–0.92)
0.169 0.1660.185 2.83 0.0900.87 (0.73–1.02)
NIMH SZ protectived
0.1670.1690.176 0.68 0.4080.938 (0.81–1.09)
0.106 0.0900.135 0.880.3500.614 (0.22–1.67)
SMRI (SZonly) protectivec
0.106 0.112 0.1350.16 0.6850.794 (0.26–2.44)
ahaplotype defined by AAGGAA at rs4586379, rs2035645, rs4777974, rs11637898, rs11074070, and rs3784735.
bhaplotype defined by TTAGT at rs4586379, rs8025225, rs11074066, rs11074067, and rs2035645.
chaplotype defined by GCAACC at rs4586379, rs2035645, rs4777974, rs11637898, rs11074070, and rs3784735.
dhaplotype defined by CCCCG at rs4586379, rs8025225, rs11074066, rs11074067, and rs2035645.
ST8SIA2: Generalised Risk Gene for Mental Illness
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(36.7%, 38.9% and 22.8% respectively) and lower frequency of
protective haplotypes (8.8%, 11.1% and 14.2% respectively)
As expected, there was a significant negative correlation of
ST8SIA2 expression with patient age (r=20.392, P=5.561025)
and duration of illness (r=20.516, P=9.361026), which are
highly correlated measures (r=0.664, P=4.861026). As a result,
age was included in a linear regression against ST8SIA2
expression, and the residuals used in further analysis. There was
no significant correlation of ST8SIA2 mRNA with other demo-
graphic variables tested (including post-mortem interval, brain pH,
refrigerator interval, duration of illness, age of onset or lifetime
Figure 2. Multidimensional scaling of GAIN data showing no evidence of population stratification. A) bipolar disorder case control
cohort; B) schizophrenia case control cohort. Cases and controls are represented by the red and blue crosses respectively.
Figure 3. Linkage disequilibrium structure of the ST8SIA2 and C15ORF32 region, spanning 132 kb, in Caucasian Europeans from
the CEPH collection. LD blocks are indicated in black triangles, with red shading indicating high LD (D9) for CEU genotypes downloaded from
HAPMAP3 (release #28; 90720–90845 kb, NCBI build 36.1). Locations of SNPs which make up the risk haplotype in the Australian bipolar disorder
cohort are indicated by the black asterisks. Affymetrix SNPs used to replicate the haplotype association in the NIMH bipolar and schizophrenia case-
control samples are indicated by the red asterisks. Insets A–C show the relationships between common haplotypes (frequency greater than 2%) in the
CEPH genotype data using different SNP combinations. Haplotypes indicated by the superscript letters in inset A (when both NIMH and Australian
SNPs are considered simultaneously) indicate those haplotypes which are indistinguishable when using only the Australian SNPs (inset B), or the
surrogate NIMH SNPs (inset C). The strongly associated SNPs from genome wide association studies of bipolar disorder in the Han Chinese
(rs8040009) , and of autism in Caucasians (rs3784730)  are indicated by the blue and green asterisks respectively.
ST8SIA2: Generalised Risk Gene for Mental Illness
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antipsychotic use), nor were there any significant effects (by t-test)
of sex, brain hemisphere, smoking, or psychotic features.
There was no main effect of diagnosis on ST8SIA2 expression
(three-way ANOVA: F(2, 94)=0.486, p=0.617), but a trend
towards lower ST8SIA2 expression in schizophrenia cases
(ANOVA: F(1, 61)=2.737, p=0.103) (Figure 5A). There was no
significant diagnosis6haplotype effect for the risk haplotype (P
values all.0.744). However a significant diagnosis6haplotype
effect was observed with the protective haplotype (ANOVA:
bipolar versus control: F(1,55)=6.462, P=0.014; combined
diagnostic group: F(1,87)=6.031, P=0.016) (Figure 5), with
suggestive effects in the control versus schizophrenia comparison
(F(1,57)=3.825, P=0.055). Post-hoc comparisons showed signif-
icant reductions in ST8SIA2 expression in case non-carriers of the
protective haplotype compared to control non-carriers (Fisher
LSD: combined diagnoses p=0.007 (Figure 5); bipolar disorder or
schizophrenia only p=0.023 or 0.006 respectively), as well as
p=0.034). Most of these effects remained significant or suggestive
after Bonferroni correction for multiple comparisons (corrected
post-hoc LSD p values=0.041, 0.14, 0.036, 0.21 respectively).
Multiple studies have shown linkage of psychiatric illness to
chromosome 15q25-26, including bipolar disorder , bipolar
disorder with psychosis , bipolar disorder and schizophrenia
, and recurrent early onset depression [21,22], indicating that
this locus may harbour a generalized susceptibility gene for both
psychotic and mood disorders. Through a fine mapping study of a
bipolar disorder linkage peak , we identified a specific risk
haplotype within ST8SIA2 which was over-represented in cases in
three independent cohorts: 1) the Australian bipolar disorder case-
control cohort; 2) the Australian schizophrenia case-control
cohort; and 3) the American NIMH bipolar disorder case-control
cohort. While the results from a fourth cohort – the American
NIMH schizophrenia cohort – were not significant, the same
direction of effect was observed. Taken together, these findings
indicate that ST8SIA2, a facilitator of neural plasticity which is
highly expressed early in human brain development, may play a
role in the genetic susceptibility for both bipolar disorder and
Variants in the promoter of ST8SIA2 have previously shown
association with schizophrenia in Japanese and Chinese cohorts
[13,23], after the gene was selected as a functional candidate due
to its interaction with NCAM, which has also previously shown
association with bipolar disorder . Indeed our study has also
identified genetic variants in the promoter region that are
associated with bipolar disorder, albeit with different alleles. The
low frequency of the associated alleles from the Asian studies in the
Caucasian population may explain the failure to replicate
association with those specific promoter variants in an Italian
cohort  and our Australian cohort (data not shown).
Moreover, a GWAS of bipolar disorder in Han Chinese found
strong association (P,661026) with two SNPs which lie 30 kb
downstream of ST8SIA2 in the C15orf32 gene . Long range
linkage disequilibrium between the two C15orf32 SNPs with
markers towards the 39 end of ST8SIA2 (D9$0.916) (Figure 2)
suggests these independent signals may converge functionally on a
single genetic effect.
An association study of 15q25-26 for recurrent early onset
depression showed nominal association with NTRK3 and the genes
flanking ST8SIA2: SLCO3A1 and C15orf32; but not ST8SIA2 itself
Figure 4. The mean normalized quantity for each develop-
mental group. The age range in years and number of subjects per
group (n) were: neonate 0.11–0.24 (n=10); infant 0.32–0.91 (n=13);
toddler 1.58–4.86 (n=9); school age 6.88–12.97 (n=8); teenage 15–
17.82 (n=8); young adult 20.14–25.38 (n=8); adult 35.99–48.69 (n=7).
Error bars indicate one standard deviation from the mean. Significant
group differences from post-hoc Fisher LSD tests comparing neonates
to the six other developmental age groups are indicated, where one
asterisk represents P,0.001, two asterisks represent P,0.0001 and
three asterisks represent P,0.00001.
Figure 5. The effect of protective haplotype on ST8SIA2 gene
expression in adult post-mortem DLPFC. Normalised and trans-
formed ST8SIA2 expression was regressed against age, and standardized
residuals were used to compare the effect of haplotype in Caucasian
brains from the Stanley Medical Research Institute Array cohort. The
mean values for each group are represented by horizontal black bars,
and boxes represent the 95% confidence intervals of each group (6
standard errors), with the numbers of individuals in each group
indicated within the boxes. One individual homozygous for the
protective haplotype was identified, and was included in the $1 copy
group. There was no significant overall effect of diagnosis on expression
(three-way ANOVA: F(2, 94)=0.486, p=0.617), but a trend towards
lower ST8SIA2 expression in schizophrenia cases compared to controls
(ANOVA: F(1, 61)=2.737, p=0.103; combined diagnostic group ANOVA:
F(1, 91)=1.948, p=0.166). Significant diagnosis6haplotype effects were
observed for the protective haplotype in control versus the combined
diagnostic group (ANOVA: F(1, 87)=6.031, p=0.016). Post-hoc com-
parisons showed significant reductions in ST8SIA2 expression in non-
haplotype carriers in cases compared to non-haplotype carrier controls
(Fisher LSD: combined diagnoses p=0.007, indicated by double
asterisk), as well as control carriers versus control non-carriers (Fisher
LSD: p=0.034, indicated by single asterisk).
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[21,22]. Interestingly, a recent GWAS for autism spectrum
disorder using 1314 families with the verbal subtype identified a
significant signal (P=5.3761028) for rs3784730 in intron 4 of
ST8SIA2 , which lies 3.4 kb from our associated single SNP
marker rs2168351. As autism is thought to be part of a broader
spectrum of neurodevelopmental disorders, and shares genetic and
clinical overlaps with both schizophrenia and bipolar disorder
, it is possible that ST8SIA2 may be a generalised susceptibility
gene for all three illnesses.
Functionally, ST8SIA2 is an attractive candidate for mental
illnesses with neurodevelopmental pathology. The sialyltrans-
ferases, ST8SIA2 and ST8SIA4, are principally responsible for
the post-translational glycosylation of the neuronal cell adhesion
molecule (NCAM), which in its polysialylated form (PSA-NCAM),
plays an important role in processes such as neuronal migration
and axon pathfinding, synaptogenesis and plasticity [28,29]. This
occurs via masking the adhesive properties of NCAM through
steric repulsion after the addition of large hydrophilic glycopoly-
mers, which facilitates movement through intracellular space for
both neurons and neuronal processes . In addition, PSA-
NCAM has been implicated in hormone response via the
dopamine D2 receptor [31,32], in regulation of circadian cues
via photic entrainment of the suprachiasmatic nucleus , and in
stress response and learning and memory . The high
expression of ST8SIA2 early in brain development, when neuronal
networks are first being established, and the persistence of PSA-
NCAM in regions of neurogenesis in the adult brain [34,35],
suggests that aberrant temporal or spatial expression of ST8SIA2
may disrupt the highly coordinated early development of brain
connectivity and affect plasticity of established neuronal networks
. Some adults with schizophrenia have a 20–95% reduction of
PSA-NCAM immunoreactive cells in the hippocampus that is not
accounted for by changes in NCAM expression , suggesting a
polysialylation defect which may continue into adulthood. Mouse
knockouts of sialytransferase have abnormal fear responses 
and misguidance of axonal fibre tracts in the anterior commissure,
corpus callosum and internal capsule . While we did not find
an effect of the risk haplotype on global ST8SIA2 mRNA in the
adult DLPFC, the absence of the protective haplotype in cases
appears to reduce global ST8SIA2 expression compared to
controls, which is conceptually consistent with reduced neuroplas-
ticity. This result should be considered preliminary, and the
opposing effects of the protective haplotype in controls may
indicate that additional interacting factors with disease specific
expression may be required to fully understand the mechanism
through which the protective haplotype exerts its effects. It may be
that alterations specific to the risk haplotype occur earlier in
development, or affect particular splicing isoforms of ST8SIA2,
neither of which were assessed in the current study. Further
investigations of the effects of the risk and protective haplotypes on
gene function are required, and are currently underway.
Finally, we acknowledge that there are limitations to our study.
Firstly, while our discovery sample is enriched for individuals from
families which may share a susceptibility gene on 15q25-26 due to
inclusion of individual pedigree members from families showing
linkage to this genomic region, our discovery sample is small in the
current context of large scale genome-wide association studies.
This is problematic for two reasons: 1) the power of our cohort to
detect significant association which exceeds multiple testing
correction penalties is limited; and 2) the results from our fine-
mapping study may not be generalizable to other cohorts which
are not enriched for the 15q25-26 susceptibility gene/s. We have
attempted to reconcile these problems by replicating our findings
in additional independent cohorts, with which we have had some
success. While the results from the NIMH bipolar disorder cohort
are significant, the effect size is smaller than in our discovery
cohort. This is not surprising given the ascertainment of the
samples, the difference in genotyped SNPs across the studies, and
the difference in sample size. Our cohort is largely derived from
extended families with a high density of illness, hence may contain
rarer and more highly penetrant risk genes than the NIMH
cohort, which is largely derived from singleton cases whose illness
may be more sporadic in nature. In spite of this, we did observe an
over-representation of a surrogate ST8SIA2 risk haplotype in the
NIMH data, suggesting that ST8SIA2 may contribute to disease
risk. However this result should be considered preliminary and
requires further replication. Imputation or direct genotyping of the
SNPs pertaining to the specific risk haplotype in the NIMH cohort
would circumvent problems with using surrogate haplotypes,
which are less than ideal. Secondly, we acknowledge that our
primary fine-mapping findings do not withstand correction for
multiple comparisons, and hence should be interpreted with
caution. Thirdly, as we do not have genome-wide SNP data for the
Australian samples, we are unable to directly test for population
stratification, nor determine how this may affect our findings.
While we have ensured our sample is racially homogeneous
through demographic information, it is possible that the associ-
ation in our discovery sample is affected by population sub-
structure. Nonetheless, we were able to confirm that population
stratification did not affect the association signal in the NIMH
We propose that ST8SIA2 is a generalised susceptibility gene for
mental illnesses with neurodevelopmental origins. The role of
sialyltransferase as a facilitator of neuronal migration and
synaptogenesis makes this gene an appealing functional candidate
for bipolar disorder, schizophrenia and autism, each being
complex genetic syndromes with overlapping constellations of
clinical symptoms. The involvement of ST8SIA2 fits with a
polyfactorial model of susceptibility for mental illness, where
defects in the development of brain connectivity early in life,
caused by inheritance of risk variants in ST8SIA2 which reduce
glycosylation of NCAM resulting in axonal misguidance and
reduced neuronal plasticity, may render the brain more susceptible
to secondary genetic and environmental insults later in life.
Materials and Methods
This study was carried out in accordance with the latest version
of the Declaration of Helsinki after specific approval by the
University of New South Wales Human Research Ethics
Committee (Australian bipolar disorder cohort: HREC # 04144
and 10078), and the Wolston Park Hospital Institutional Ethics
Committee (Australian Schizophrenia cohort). Developing human
post-mortem DLPFC tissue was obtained from the University of
Maryland Brain Tissue Bank for Developmental Disorders
(NICHHD contract # NO1-HD8-3283). Samples from the
Stanley Medical Research Institute were collected and distributed
under approval for the Department of Psychiatry, Uniformed
Services University of the Health Sciences, Bethesda USA.
Genotype data were obtained with approval from the National
Institutes of Health Data Access Committee, after approval by the
Johns Hopkins University School of Medicine institutional review
Australian Bipolar disorder cohort
The Australian bipolar disorder case-control cohort was mostly
selected from families previously used for linkage analysis and was
ST8SIA2: Generalised Risk Gene for Mental Illness
PLoS ONE | www.plosone.org7 May 2012 | Volume 7 | Issue 5 | e38172
recruited through the Mood Disorders Unit and Black Dog
Institute, Prince of Wales Hospital/School of Psychiatry, Univer-
sity of New South Wales, Australia. Families were ascertained
through a bipolar I disorder proband using the Family Interview
for Genetic Studies (FIGS), where a relative with schizophrenia in
the absence of mood disturbance resulted in family exclusion. One
affected individual, plus a spouse or completely unrelated pedigree
member, was selected from each family for cases and controls
respectively. Gender was matched across the groups, although the
control group was older to reduce the likelihood of a later
diagnosis. The rest of the cases were recruited from a specialized
bipolar disorder clinic . In total, 50.5% of the sample had
psychotic features, 70% had a family history of bipolar disorder,
and 87% had a family history of bipolar disorder or depression. All
individuals gave written informed consent, and were assessed using
the Diagnostic Interview for Genetic Studies (DIGS) by experi-
enced medical practitioners, psychologists and psychiatric nurses
trained in this instrument . Information obtained from FIGS,
DIGS and medical records was used to generate best-estimate
Research Diagnostic Criteria (RDC) diagnoses for Bipolar I
disorder (BPI:n=158), Bipolar II disorder (BPII:n=41), Schizo-
affective Disorder-Manic type (SZ/MA:n=10), Major Depressive
Disorder (MDD:n=10) or unaffected controls (n=166). All
genotyped individuals were Caucasian and almost entirely of
Anglo-Celtic descent and 50% were female. Demographic
information for the cohort is presented in Table 3. The study
was approved by the Human Research Ethics Committee of the
University of New South Wales.
Australian Schizophrenia cohort
Samples were selected from a larger cohort (n=310), initially
recruited for the Australian national prevalence study of psychosis
, for which diagnoses were assigned using the Diagnostic
Interview for Psychosis . Individuals were included in the
current study if they were Caucasian, had a confirmed diagnosis of
schizophrenia and a DNA sample available. In total, 128 cases (85
men and 43 women) with a DSM-III-R  diagnosis of
schizophrenia and 128 age-, gender- and ethnically-matched
controls were included.
NIMH bipolar disorder and schizophrenia cohorts
Genome wide association study data was downloaded from the
Genetic Association Information Network (GAIN) through the US
based National Institutes of Health. Filtered genotypes generated
on the Affymetrix 6.0 SNP from European ancestry samples were
used from: 1) the GWAS of Bipolar Disorder version 3 study,
which contained 1034 controls and 1021 patients with bipolar
disorder and related disorders, including any psychiatric disorder
as defined in DSM-IV or ICD-10; and 2) the GWAS of
Schizophrenia version 2 data, which contained 1378 controls
and 1172 cases with schizophrenia and related conditions,
including schizoaffective disorder, acute psychoses, bipolar disor-
der, major depressive disorder, or ‘‘Cluster A’’ personality
disorders (schizotypal, schizoid, paranoid).
SNP selection and genotyping of the linkage interval
The 6.2 Mb linkage interval defined by microsatellite markers
D15S979 and D15S816 included only the 59 end of the NTRK3
gene, so the screened region was expanded to 6.5 Mb (86.32–
92.82 Mb) to cover the NTRK3 gene. The 6.5 Mb region
contained ,22,000 known SNPs, (7,315 in HAPMAP release
28, Caucasian Europeans), from which 376 were selected using the
Illumina GoldenGate Genotyping Assay on the BeadArray
platform (Illumina Inc., San Diego USA). Selected SNPs had a
score of ,0.6 in the score file supplied by Illumina, and a minor
allele frequency $0.1. They either tagged common (.5%
frequency in Caucasians) major haplotype blocks around known
genes, as determined through HAPLOVIEW; covered other
putative functional regions with high sequence conservation (28-
way cross-species alignment; UCSC Genome Bioinformatics); or
covered major gaps between other selected SNPs, such that the
average inter-SNP distance was 15 kb across the 2.5 Mb high
priority region, or 20 kb across the rest of the 6.5 Mb region. Six
extra putative functional SNPs within ST8SIA2 were selected,
which were predicted bioinformatically  to alter splice donor/
acceptor sites. While the SNPs selected for genotyping represent
only 5% of the known SNP variation in the region (HAPMAP
release 28, Caucasian Europeans), through the underlying linkage
disequilibrium structure they tag 53.6% of all common variation in
the interval (MAF.0.1 at r2.0.80), and tag 66.2% of common
variation within genes (mean max r2=0.94).
Table 3. Demographic information for bipolar disorder case control cohort.
male femaletotal % male
total controls 89 77 1660.54
average age of controls (years6SD) 61.2613.058.9614.060.3613.5
Bipolar I 6890 158 0.43
Bipolar II2813 41 0.68
Schizoaffective disorder-manic type73 100.70
Recurrent Unipolar depression28 10 0.20
total cases 105114219 0.48
average age of cases (years6SD)47.3615.1 46.7615.346.7615.3
age of onset for depression (years6SD) 23.9610.9
age of onset for mania (years6SD) 28.1611.3
number of cases with psychotic features92
number of cases with family history (bipolar, depression, either)119, 94, 151
ST8SIA2: Generalised Risk Gene for Mental Illness
PLoS ONE | www.plosone.org8 May 2012 | Volume 7 | Issue 5 | e38172
Scan data from the BeadArray was interpreted using the
BeadStudio-GT module (Illumina Inc, San Diego USA), where
SNP allele calls were clustered and assessed for genotype quality,
and genotype reports generated. SNPs and samples that did not
pass standard quality control measures, including clustering
distribution and missingness (per marker or per sample) were
removed from further analyses.
Association and haplotype analysis
Statistical analyses were performed with PLINK v1.02 software
. SNPs failing the Hardy-Weinberg exact test at a 0.001
significance threshold were removed. Individuals with high SNP
genotype failure rates (.10%) were excluded. Association analysis
for bipolar disorder was performed using a broad disease model
where individuals diagnosed with BPI, SZMA, BPII or MDD were
all classified as affected (n=218). To devise empirical P values for
SNP and haplotype association, ten thousand permutations for
each SNP were performed using the –mperm option.
Multimarker haplotype analysis was conducted using probabi-
listically inferred haplotypes for each individual, generated using a
standard E-M algorithm in PLINK . For each imputed
haplotype, the average posterior probability of haplotype phases
given genotype data was generated, with average values of
0.9560.10 for the Australian bipolar disorder case-control cohort,
0.9360.11 for the Australian schizophrenia case-control cohort,
0.9460.12 for the Stanley Medical Research Institute post-
mortem brain cohort, 0.9660.09 for the NIMH bipolar disorder
cohort and 0.9660.09 for the NIMH schizophrenia cohort.
Haplotype association analysis was performed using the –hap-assoc
option with a sliding windows (–hap-window 3) or specified
haplotype (–hap-snps) approach with standard association testing.
Conditional regression-based association using the –chap option
was performed on specific haplotypes of interest.
ST8SIA2 expression profiling over normal brain
Because ST8SIA2 is expressed early in development , we
determined the temporal expression profile of ST8SIA2 using a
cohort of 63 normal human brains at different stages of
development, consisting of 10 neonates (aged between 0.11–0.24
years); 13 infants (0.32–0.91 years); 9 toddlers (1.58–4.86 years); 8
school age children (6.88–12.97 years); 8 teenagers (15–17.82
years); 8 young adults (20.14–25.38); and 7 adults (35.99–48.69
years). A previous genome-wide transcription profiling microarray
experiment of the dorsolateral prefrontal cortex (DLPFC) from
this cohort  included a probe specific for ST8SIA2 exon 6
(239537_at), which showed a marked reduction in expression over
brain development. We validated the microarray findings by
quantitative real-time PCR after reverse transcribing RNA using
the SuperScript III First-Strand Synthesis kit with random
hexamers (Invitrogen). Relative ST8SIA2 transcript levels were
determined using a TaqMan probe spanning exons 5–6
(Hs00544029_m1) on the ABI 7900HT PCR by the relative
standard curve method using standard quantitative techniques
. ST8SIA2 expression was then normalized to the geometric
mean of two housekeeping genes, HMBS (Hs00609297_m1) and
GUSB (Hs99999908_m1), neither of which changes over develop-
ment. Statistical analysis was done by two-way ANOVA with age
as an independent factor, and post hoc Fisher LSD.
ST8SIA2 expression in bipolar disorder and schizophrenia
patients with the associated genetic risk variants
To determine whether the ST8SIA2 risk or protective haplo-
types have an effect on gene expression in brains of adult patients
with bipolar disorder or schizophrenia, we used DNA and RNA
extracted from 102 brains of Caucasian patients with bipolar
disorder (n=33), schizophrenia (n=34) and controls (n=35) from
the Stanley Medical Research Institute (SMRI) Array cohort. The
6 SNPs comprising the risk haplotype were genotyped manually
via restrictiondigest (rs4586379,
rs3784735 with XbaI, BstEII, HpyCH4IV and AlwNI respectively)
or direct sequencing (rs4777974, rs11637898), and haplotypes
inferred using PLINK . ST8SIA2 gene expression was
determined from DLFPC cDNA, using the methods described
above and normalizing to the geometric mean of three house-
keeper RNAs. Individual outliers were identified if they were
greater than two standard deviations above or below their
diagnostic group means, resulting in the exclusion of 5 samples
from further analysis (3 controls, 2 schizophrenia cases). The effect
of demographic variables, diagnosis and genotype on ST8SIA2
gene expression was determined by correlation, linear regression
and factorial ANOVA. The distribution of ST8SIA2 expression
was positively skewed, and was square root transformed to
normalize the distribution to allow application of parametric
The sample genotypes provided through the Genetic Association
Information Network (GAIN) datasets used for the analyses described in
this manuscript were obtained from the database of Genotype and
Phenotype (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap through
dbGaP (accession numbers phs000017.v3.p1 and phs000021.v2.p1).
Samples and associated phenotype data for the Whole Genome Association
Study of Bipolar Disorder version 3 project were provided by John R.
Kelsoe University of California, San Diego, CA, USA. Samples and
associated phenotype data for Genome-Wide Association Study of
Schizophrenia project were provided by Pablo V. Gejman MD, North
Shore University Health System (NUH), Evanston, IL, USA. Post-mortem
brain samples used in this study were kindly provided by Dr Maree
Webster of the Stanley Medical Research Institute, and the University of
Maryland Brain Tissue Bank.
Conceived and designed the experiments: EZM CSW PRS JMF.
Performed the experiments: EZM AS YT GA JMF. Analyzed the data:
EZM JMF EGH BJM. Contributed reagents/materials/analysis tools: BJM
PBM PRS CSW. Wrote the paper: EZM JMF CSW PRS PBM JAD.
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