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Analysis of neurogranin (NRGN) in schizophrenia.

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Neuropsychiatric Genetics
Analysis of Neurogranin (NRGN) in Schizophrenia
Rhodri Ll. Smith,* Deborah Knight, Hywel Williams, Sarah Dwyer, Alex Richards, George Kirov,
Michael C. O’Donovan, and Michael J. Owen
MRC Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine, Henry Wellcome Building, School of Medicine,
Cardiff University, Cardiff CF14 4XN, United Kingdom
Received 22 December 2010; Accepted 11 March 2011
A recent study reported a genome-wide significant association
between schizophrenia and rs12807809—a SNP located approximately 3 kbp upstream of the neurogranin gene (NRGN). We
sought to determine if (a) NRGN contains common exonic
variants or variants affecting expression (eQTLs) that could
account for the association with rs12807809 and (b) there exist
rare non-synonymous highly penetrant variants that could potentially confer high risk of schizophrenia. We sequenced all four
exons of NRGN in a screening set of 14 individuals but found no
novel common polymorphisms. We additionally sequenced the
coding exons in up to 1,113 individuals (699 cases) but this
revealed only a singleton-coding variant in exon 2 (G246T
leading to Gly-55 ! Val amino acid change) in which prediction
of function analysis suggested is likely to be benign. Finally,
analysis of a brain expression dataset of at least 130 individuals
did not identify any eQTLs that were correlated with associated
SNP rs12807809 following correction for multiple testing.
Ó 2011 Wiley-Liss, Inc.
Key words: neurogranin; sequencing; GWAS; schizophrenia;
Schizophrenia is a psychiatric disorder with a complex etiology
involving both genetic and environmental factors. Affecting approximately 1% of the population, the disorder is characterized by
hallucinations, delusions, and cognitive deficits thought to arise at
least in part from defective neurodevelopment [Weinberger, 1995].
Neurogranin (NRGN), a postsynaptic protein kinase substrate,
functions primarily as a regulator of calmodulin (CaM) activity in
the postsynaptic compartment [Huang, 1993]. NRGN is abundantly expressed in structures that are involved in learning and memory,
such as dendritic spines [Watson, 1992] and CA1 pyramidial
neurones of the hippocampus. During embryonic development,
maternal thyroid hormones, and retinoids regulate NRGN expression which is maximal at the time of cortical synapse formation and
dendritic growth [I~
niguez, 1993]. Such findings suggest a key role
for NRGN in neurodevelopment [I~
niguez, 1993] and cognition
[Pak, 2000; Huang, 2006, 2007] both of which are thought to be
relevant to the etiology of schizophrenia [Goldman-Rakic, 1994].
The possible involvement of NRGN in schizophrenia was originally investigated in a case-control and a family-based candidate
gene association study of Portuguese subjects. Significant associa-
Ó 2011 Wiley-Liss, Inc.
How to Cite this Article:
Smith RLl, Knight D, Williams H, Dwyer S,
Richards A, Kirov G, O’Donovan MC, Owen
MJ. 2011. Analysis of Neurogranin (NRGN)
in Schizophrenia.
Am J Med Genet Part B 156:532–535.
tion was detected between SNP rs7113041 (Fig. 1) and affected
status in males [Ruano, 2008]. More recently, the SGENE-plus
[Stefansson, 2009] consortium reported genome-wide significant
evidence for association (P ¼ 2.3 109; OR ¼ 1.15) between
schizophrenia and a marker (rs12807809; Fig. 1) just upstream of
NRGN in a combined sample of 12,965 cases and 34,598 controls
derived from three large genome-wide association studies (GWAS)
as well as additional replication samples. Thus, currently, the
NRGN locus is one of only four loci (ZNF804A [O’Donovan,
2008], TCF4 [Stefansson, 2009], NRGN [Stefansson, 2009], and
the wider MHC region [Stefansson, 2009]) that are implicated in
schizophrenia at genome-wide levels of significance.
In the present study, we sought to determine whether NRGN
contains common exonic variants, or variants that influence expression of NRGN or neighboring genes, that might account for
the association between rs12807809 and schizophrenia. Second, we
attempted to determine if rare non-synonymous variants exist at
the locus that might confer high risk of the disorder. The hypothesis
that rare variants contribute to schizophrenia is supported by the
high incidence of schizophrenia in individuals carrying rare deletions of 22q11.2 [Murphy, 1999] as well as a number of other rare
copy number variants (CNVs) [The International Schizophrenia
Consortium, 2008; Kirov, 2009a,b; Stefansson, 2008; Walsh, 2008;
Xu, 2008], although it should be noted that with respect to the
Grant sponsor: Medical Research Council.
Rhodri Ll Smith, Deborah Knight are joint first authors
*Correspondence to:
Dr. Rhodri Ll. Smith, BSc(Hons), MSc, PhD, Henry Wellcome Building,
Heath Hospital, Cardiff University, Cardiff, Glamorgan, UK.
Published online 2 May 2011 in Wiley Online Library
DOI 10.1002/ajmg.b.31191
schizophrenia phenotype, these CNVs are not highly penetrant
[Vassos, 2010]. With the exception of CNVs and major structural re
-arrangements, there have been no systematic scans of the genomes
of people with schizophrenia for rare single base (or small insertion
deletion) variants. The reason for this is that rare variant detection
relies mainly on sequencing. This has only very recently become
technically feasible at a genome-wide level, but remains very
expensive. In the absence of few clear targets for sequencing from
unambiguous linkage findings, sequencing approaches to rare
mutation detection have therefore largely focussed on candidate
genes, an approach that has met with some notable successes in nonpsychiatric phenotypes [Cohen, 2004; Fearnhead, 2004; Ahituv, 2007;
Ji, 2008]. Clearly, as one of only four loci that are implicated
in schizophrenia at genome-wide levels of significance, NRGN is
a pre-eminent candidate gene for schizophrenia, although it should
be noted that GWAS studies implicate genomic locations, not
genes, and it is always possible that the association at this locus
points to an as yet unknown functional element.
NRGN is approximately 7.4 kbp in length and is located on
chromosome 11q24.2. It has four exons with exons 1 and 2
encoding the protein whilst exons 3 and 4 remain untranslated
(Fig. 1). The gene has two known reference transcripts which differ
by three bases; however, both encode the same 78 amino acid
We initially sequenced all four exons of NRGN in 14 unrelated
Caucasian subjects from the UK diagnosed with schizophrenia,
each of whom had at least one affected sib. Details of case recruitment and diagnosis are given elsewhere [O’Donovan, 2008]. Briefly, all cases were white, born in the British Isles, and had a consensus
diagnosis of schizophrenia according to DSM-IV criteria made by
two independent raters following semi-structured interviews using
the Present State Examination [Wing, 1974] or the Schedules for
Clinical Assessment in Neuropsychiatry (SCAN) [Wing, 1990] and
a review of case records. Cases with substance-induced psychotic
disorder or psychosis due to a general medical condition were
excluded. Multicenter and Local Research Ethics Committee approval were obtained, and all subjects gave written informed
consent to participate.
To further investigate the gene for rare variants, we sequenced
the coding exons of the gene in a minimum of 652 Bulgarians cases
diagnosed with schizophrenia according to DSM-IV and 386
healthy Bulgarian controls. Cases were recruited from psychiatric
inpatient and outpatient services. All had a history of hospitalization for schizophrenia. Each proband was interviewed with an
abbreviated Bulgarian version of SCAN (Schedules for Clinical
Assessment in Neuropsychiatry) that contains the sections on
psychosis and affective disorders. Consensus best-estimate diagnoses were made according to DSM-IV criteria based on interview and
hospital notes. Ethics committee approval was obtained from all
regions where patients were recruited. All subjects provided written
informed consent for participation in genetic association studies.
The sample for which sequence data were obtained for the coding
exons has power of 80% to detect a neutral allele with a population
frequency of >0.0007. Assuming an allele with an effect size (OR) of
10 or of 2, the respective population frequencies for which we have
80% power are >1.3 103 and >0.03. Power to detect alleles in
the non-coding exons with a MAF > 0.05 and MAF > 0.1 was 80%
and 95%, respectively.
All exons were amplified by PCR using specified forward and
reverse primers. PCR products were subsequently cleaned using
Ampure (Agencourt Bioscience Corporation, Beverly, MA). Sequencing by PCR was achieved using BigDye Chemistry (Applied
Biosystems, Foster City, CA) in both the forward and reverse
directions for the common variants, and in the forward direction
for rare variant detection. Products were then cleaned using
CleanSEQ (Agencourt Bioscience Corporation) and finally sequenced on a 3100 capillary sequencer (Applied Biosystems).
Exonic regions were screened for sequence variation using
NovoSNP (Version 2.1.6) software [Weckx, 2005]. Sequencing
reactions that failed or were of poor quality were removed from
the analysis. Traces with a NovoSNP score >5 were manually
FIG. 1. A schematic of the neurogranin gene highlighting the location of both SNPs previously showing evidence of association with schizophrenia.
eQTL Analysis
eQTL Analysis
NRGN expression was analyzed within two eQTL datasets derived
from brain tissue. The first, published by Myers and Gibbs [2007]
consists of gene expression profiles generated using RNA extracted
from the frontal or temporal cortex of 184 neuropathologically
normal human brains. Genotyping and expression analysis was
performed using the Affymetrix GeneChip Human Mapping 500 K
Array Set and Illumina HumanRefseq-8 Expression BeadChip
platforms. The second eQTL dataset [Gibbs and van der Brug,
2011] analyzed 143 neurologically normal subjects of European
ancestry. Frozen tissue samples were obtained from four brain
regions (cerebellum, pons, frontal, and temporal cortices) for each
subject. Genotyping was performed using Infinium HumanHap550 BeadChips (Illumina, San Diego, CA). Expression analysis
was performed using Illumina HumanRef-8 Expression BeadChips.
Genotype data were used as presented in the original publications
[Myers and Gibbs, 2007; Gibbs and van der Brug, 2011]. The
expression data were normalized and log transformed as described
in the original articles [Myers and Gibbs, 2007; Gibbs and van der
Brug, 2011]. Samples with over 10% missing data were removed
from the Myers et al. dataset, leaving 161 samples. In the Gibbs et al.
dataset, samples where over 50% of the probes had a present/absent
call P-value of >0.05 were removed. This left 143 samples in the
temporal cortex dataset, 133 samples in the frontal cortex dataset,
130 samples in the cerebellum dataset, and 134 samples in the pons
Expression levels were then corrected for clinical and
biological factors that might influence expression, using linear
regression in the statistical package R [Ihaka and Gentleman,
1996]. In the Myers et al. dataset, these factors were sex, age
at death, cortex region, postmortem interval, institute source,
hybridization batch, and ENO2 expression. For the Gibbs et al.
dataset, these factors were sex, age at death, postmortem
interval, institute source, hybridization batch and ENO2 expression. ENO2 expression was included as a factor because it is a
reliable neuronal marker [Marangos and Schmechel, 1987], and so
including it will correct for differing proportions of neurons
between samples.
eQTLs were tested by linear regression of normalized NRGN
expression level on SNP genotypes (coded as the number of minor
alleles at each SNP: 0, 1, or 2). This analysis was performed using
the—assoc option in the software package PLINK [Purcell and
Neale, 2007].
In the expression dataset, we identified two SNPs which were at least
weakly correlated (r2 > 0.2) with rs12807809, the variant associated
with schizophrenia in the earlier study [Stefansson, 2009]. Neither
of these nor rs12807809 was associated with NRGN expression
(P > 0.05). Moreover, given that association formally points to a
region rather than a gene, we investigated whether expression of any
transcripts within 1 Mb of this SNP were associated with schizophrenia. However, rs12807809 was not associated at a nominal level
of significance with any of the transcripts following bonferroni
correction (data not shown) in the region although data was
available from one of the Gibbs et al. dataset only.
In the screen set in which all exons were sequenced (n ¼ 14), analysis
of exons 1–4 revealed no variants, which effectively precludes the
existence of common exonic variation in this gene (95% power
to detect variants with MAF 1%). In the larger sample in which
the coding region was screened, we observed only a single variant,
G > T at position 246, in exon 2. The variant is nonsynonymous,
and is predicted to change amino acid residue 55 of NRGN from
a glycine to a valine. No other polymorphisms were detected in
our sequence data, including rs61910621 which is listed in dbSNP
build 131.
The NRGN locus is one of a small number of loci that have been
associated with schizophrenia at a genome-wide significant level of
support [Ruano, 2008], and given its function, the NRGN gene itself
is a likely source of the association signal. Our study aimed to
identify if common exonic variants exist within the gene, or
common eQTLs in the vicinity of the gene, might account for the
association. We also sought to establish if there are rare nonsynonymous variants that contribute to the disease. Observing the
latter would firmly establish NRGN as the relevant functional unit
responsible for the association at this locus. However, we found
only a single non-synonymous variant and no synonymous variants
within this gene. Given high power (>0.99) to detect variants at a
frequency >0.01, our data effectively exclude a role in NRGN for
even fairly rare coding susceptibility variants in schizophrenia.
However, it should be noted that risk alleles or haplotypes influencing expression could in principal be exclusive to a particular
developmental stage or anatomical region and thus would not have
been detected by our study.
We did identify a single occurrence non-synonymous variant
in a case which results in a glycine to valine change. The nsSNP
identified in the current study alters the amino acid sequence at
position 55, which lies just outside the IQ domain of NRGN
(encoded by amino acids 22–47) that is important for CaM binding
[Prichard, 1999]. PolyPhen (
pph/), a prediction of function program, suggests that this
variant is likely to be benign. Given the singleton nature of the
observation, we can therefore not implicate this variant as of
likely relevance to schizophrenia either statistically or on the basis
of likely functionality, although predictive algorithms do not
preclude an effect.
Clearly, our analysis cannot discount a role for ultra rare or
unique high penetrance variants in this gene in schizophrenia;
doing so would require sequence analysis of every person in the
world with the disorder. However, our data do show if such variants
exist, they must have very low population frequencies, and will be
extremely difficult to implicate in the disorder. Based upon the
power analysis for a dominant allele with a relative risk of 10, our
study puts an upper boundary of the cumulative population
frequency of all such rare variants within NRGN exonic sequence
at 0.0001. If such a set of variants exist at just below this level,
it will be necessary to sequence approximately 8,000 cases and
8,000 controls to demonstrate an association at a very modest
P ¼ 0.05.
In summary, our study provides strong evidence that common
exonic variation does not account for the genome-wide significant
association between schizophrenia and variation at NRGN, and,
with the caveats above, suggests that eQTLs at this locus cannot
explain it either. The source of the association signal therefore
remains to be explained. We also find no evidence that rare but fairly
highly penetrant coding variants at this locus are involved in
schizophrenia. No study can exclude the existence of private or
ultra rare variants, but if these exist, in the absence of multiple
families showing unequivocal linkage to variants at this locus,
documenting them will require sequencing studies at least as large
as those deployed in GWAS studies.
The authors are grateful to all individuals who have participated in,
or helped with this research. The research was supported by the
Medical Research Council (UK).
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