A genome-wide study of common SNPs and CNVs
in cognitive performance in the CANTAB
Anna C. Need1, Deborah K. Attix3, Jill M. McEvoy1, Elizabeth T. Cirulli1, Kristen L. Linney1,
Priscilla Hunt4, Dongliang Ge1, Erin L. Heinzen1, Jessica M. Maia1, Kevin V. Shianna2,
Michael E. Weale5, Lynn F. Cherkas6, Gail Clement6, Tim D. Spector6, Greg Gibson4
and David B. Goldstein1,?
1Center for Human Genome Variation, Institute for Genome Sciences and Policy and2Genomic Analysis Facility,
Institute for Genome Sciences and Policy, Duke University, 450 Research Drive, Box 91009, Durham, NC 27708,
USA,3Division of Neurology and Division of Medical Psychology, Duke University Medical Center, Durham, NC
27705, USA,4Department of Genetics, Gardner Hall, North Carolina State University, Raleigh, NC 27695, USA,
5Department of Medical and Molecular Genetics, King’s College London, Guy’s Hospital Campus, London SE1 9RT,
UK and6Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital
Campus, London, UK
Received April 10, 2009; Revised July 7, 2009; Accepted August 25, 2009
Psychiatric disorders such as schizophrenia are commonly accompanied by cognitive impairments that are
treatment resistant and crucial to functional outcome. There has been great interest in studying cognitive
measures as endophenotypes for psychiatric disorders, with the hope that their genetic basis will be clearer.
To investigate this, we performed a genome-wide association study involving 11 cognitive phenotypes from
the Cambridge Neuropsychological Test Automated Battery. We showed these measures to be heritable by
comparing the correlation in 100 monozygotic and 100 dizygotic twin pairs. The full battery was tested in
?750 subjects, and for spatial and verbal recognition memory, we investigated a further 500 individuals to
search for smaller genetic effects. We were unable to find any genome-wide significant associations with
either SNPs or common copy number variants. Nor could we formally replicate any polymorphism that has
been previously associated with cognition, although we found a weak signal of lower than expected P-values
for variants in a set of 10 candidate genes. We additionally investigated SNPs in genomic loci that have been
tionof associationwhen consideredas a separate set.OnlyNRXN1showedevidenceofsignificantassociation
with cognition. These results suggest that common genetic variation does not strongly influence cognition in
healthy subjects and that cognitive measures do not represent a more tractable genetic trait than clinical end-
points such as schizophrenia. We discuss a possible role for rare variation in cognitive genomics.
Memory and cognitive problems are characteristic of many
common psychiatric and neurological disorders. Patients with
manifest with cognitive impairments that are unresponsive to
treatment (1,2) and it has been shown that the level of cognitive
function is a strong predictor of the ultimate outcome of the
disease (3,4). Alzheimer’s disease is characterized by severe
memory and cognitive decline with no effective treatment. It
is therefore essential, both for the patients and for society, to
develop treatments that improve cognitive symptoms in these
It was hoped that the development of whole-genome tech-
nologies and their application to common disease would
shed light on the neurobiology underlying psychiatric
disease, leading to better treatment options. Unfortunately,
several genome-wide association studies have now been
?To whom correspondence should be addressed at: Tel: þ1 9196840896; Fax: þ1 9196686787; Email: firstname.lastname@example.org
# The Author 2009. Published by Oxford University Press. All rights reserved.
For Permissions, please email: email@example.com
Human Molecular Genetics, 2009, Vol. 18, No. 23
Advance Access published on September 4, 2009
performed with schizophrenia patients and controls and have
shown it to be unlikely that common single nucleotide poly-
morphisms (SNPs) or copy number variants (CNVs), as rep-
resented in current genome-wide SNP platforms, will
succeed in explaining much of the variation in disease predis-
position (5–10). Findings have been similar for bipolar dis-
order (11–14). Although very large-scale genetic studies
have yet to be reported, it now seems that common variation
does not account in large part for the strong heritability of
these disorders (15,16).
One suggested explanation forthis‘missingheritability’ (17)
is that clinical endpoints do not reflect biologically cohesive
and schizophrenia may in fact have a whole range of overlap-
ping syndromes which could be better classified and more suc-
cessfully investigated if they were defined by more specific
measures would be easier to investigate genetically because
function and its specific biological consequences (20–22).
Cognitive function has been shown to be highly heritable
(23–26). Additionally, cognitive impairments associated
with neuropsychiatric disorders are also present in unaffected
relatives at a higher rate than in the general population and are
present in patients even when the illness is not active (27).
These facts suggest that cognitive measures perfectly fit the
description of ‘endophenotypes’ for neuropsychiatric disease
(22). It has therefore been suggested that by studying rela-
tively small sample sizes of healthy subjects, we will be
able to find associations between cognitive phenotypes and
common genetic variation.
To date, a single genome-wide association study has exam-
ined the role of common genetic variation in memory (using a
word recall task) and implicated the genes KIBRA (28) and
CAMTA1 (29). We could not, however, replicate the KIBRA
association in our own studies (30) and the CAMTA1 associ-
ation has yet to be independently replicated. In addition,
over the past 5 years, hundreds of papers have reported associ-
ations between particular genetic polymorphisms and memory
or other cognitive phenotypes in both healthy volunteers and
patients with schizophrenia and other neuropsychiatric dis-
orders (15). Many of these studies have concentrated on a
small number of genes in the dopamine and serotonin
pathways [e.g. COMT (31–34), DRD4 (35,36), HTR2A
(37–39)], or the val66met polymorphism in BDNF (40,41)].
However, despite the huge body of research, findings have
been inconclusive. The interpretation of these studies has
been hampered by small sample sizes, publication bias
(42,43) and lack of correction for population stratification.
Unfortunately, this has not been unusual in the field of candi-
date gene association studies (44). In the wake of genome-
wide association studies, however, clear standards of evidence
for both executing and interpreting human genetic association
studies have emerged (45,46). Here we attempt to apply those
standards in our interpretation of the association evidence in
the same candidate genes that have been widely studied in
cognitive genomics, as well as in analyzing whole-genome
association data for multiple cognitive phenotypes.
We have investigated the role of common genetic variation
in human cognition as assessed using tests from the
Cambridge Neuropsychological Test Automated Battery
(CANTAB). The CANTAB is a set of automated, computer-
ized tests that assess different aspects of cognitive function.
The tests are based on tasks that have been successfully
used to investigate the neural and genetic basis of cognitive
function in animals and have been shown to detect cognitive
impairments in many neuropsychiatric conditions including
Alzheimer’s disease and schizophrenia, as well as being sensi-
tive to differences in cognitive performance in healthy sub-
jects (47–51). A recent study showed that subjects at a high
genetic risk of schizophrenia were impaired in performing
CANTAB spatial working memory (SWM) tests, regardless
of whether they were manifesting any psychotic symptoms
(52). Other studies have shown impairments in CANTAB
test performance at early stages of schizophrenia development
(53) and also independently of current symptoms in both
schizophrenia and bipolar disorder (54). These studies
provide support for the use of CANTAB tests as measure-
ments for schizophrenia endophenotypes.
It is of value to examine the CANTAB test measures indi-
vidually due to the likelihood that the different test measures
reflect different cognitive processes that are underlain by
different molecular pathways. However, it is possible that
there are also genetic determinants of a general cognitive
ability. We therefore examine both individual cognitive
measures (n ¼ 10) and a principal component measure that
reflects performance across all tests.
The full CANTAB battery (see Materials and Methods) was
assessed in 1000 subjects and the short battery comprising just
the spatial and verbal recognition memory (SRM and VRM)
tests was assessed in a further 630 subjects. After genotyping
quality control checks, Eigenstrat analysis and exclusions based
on drugs or illness, 1295 subjects remained, comprising 789
that completed the full battery and 506 that completed the short
battery. Details of the cohort are displayed in Table 1.
To select which CANTAB measures to use for phenotypic
analysis, we used data from 99 monozygotic and 99 dizygotic
twins that performed the full CANTAB test battery to assess
heritability of the different measures (Table 2). The least heri-
table measures were paired associates learning (PAL) first trial
score, SWM within errors (all stages) and SWM between
errors (four box stage). These measures were therefore not
examined as phenotypes for genetic analysis. To reduce redun-
dancy between the measures, we also dropped SWM between
errors (6 boxes) as this had a low heritability and was highly
correlated with SWM between errors (eight boxes). Although
spatial span (SSP) had a low heritability (14%), there was no
more heritable alternative measure from this task so we
retained this as a phenotypic measure.
In linear regression models [implemented in PLINK (55)]
including sex and 18 EIGENSTRAT axes as covariates (as
well as additional covariates shown in Table 3), we found
that no single polymorphism showed a genome-wide signifi-
cant association in the discovery cohort: the lowest P-value
for any phenotype was 1.1 ? 1027. The most strongly associ-
ated SNPs are shown in Table 3 and the top 100 associated
Human Molecular Genetics, 2009, Vol. 18, No. 234651
of BDNF and human memory and hippocampal function. Cell, 112,
42. Barnett, J.H., Scoriels, L. and Munafo, M.R. (2008) Meta-analysis of the
cognitive effects of the catechol-O-methyltransferase gene Val158/
108Met polymorphism. Biol. Psychiatry, 64, 137–144.
43. Munafo, M.R., Stothart, G. and Flint, J. (2009) Bias in genetic
association studies and impact factor. Mol. Psychiatry, 14, 119–120.
44. Hirschhorn, J.N., Lohmueller, K., Byrne, E. and Hirschhorn, K. (2002)
A comprehensive review of genetic association studies. Genet. Med., 4,
45. McCarthy, M.I., Abecasis, G.R., Cardon, L.R., Goldstein, D.B., Little, J.,
Ioannidis, J.P. and Hirschhorn, J.N. (2008) Genome-wide association
studies for complex traits: consensus, uncertainty and challenges. Nat.
Rev. Genet., 9, 356–369.
46. Chanock, S.J., Manolio, T., Boehnke, M., Boerwinkle, E., Hunter, D.J.,
Thomas, G., Hirschhorn, J.N., Abecasis, G., Altshuler, D.,
Bailey-Wilson, J.E. et al. (2007) Replicating genotype-phenotype
associations. Nature, 447, 655–660.
47. Fray, P.J. and Robbins, T.W. (1996) CANTAB battery: proposed utility
in neurotoxicology. Neurotoxicol. Teratol., 18, 499–504.
48. Sahakian, B.J. and Owen, A.M. (1992) Computerized assessment in
neuropsychiatry using CANTAB: discussion paper. J. R. Soc. Med., 85,
49. Levaux, M.N., Potvin, S., Sepehry, A.A., Sablier, J., Mendrek, A. and
Stip, E. (2007) Computerized assessment of cognition in schizophrenia:
promises and pitfalls of CANTAB. Eur. Psychiatry, 22, 104–115.
50. Robbins, T.W., James, M., Owen, A.M., Sahakian, B.J., Lawrence, A.D.,
McInnes, L. and Rabbitt, P.M. (1998) A study of performance on tests
from the CANTAB battery sensitive to frontal lobe dysfunction in a large
sample of normal volunteers: implications for theories of executive
functioning and cognitive aging. Cambridge Neuropsychological Test
Automated Battery. J. Int. Neuropsychol. Soc., 4, 474–490.
51. Robbins, T.W., James, M., Owen, A.M., Sahakian, B.J., McInnes, L. and
Rabbitt, P. (1994) Cambridge Neuropsychological Test Automated
Battery (CANTAB): a factor analytic study of a large sample of normal
elderly volunteers. Dementia, 5, 266–281.
52. O’Connor, M., Harris, J.M., McIntosh, A.M., Owens, D.G., Lawrie, S.M.
and Johnstone, E.C. (2009) Specific cognitive deficits in a group at
genetic high risk of schizophrenia. Psychol. Med., 1–7. Epub ahead of
53. Bartok, E., Berecz, R., Glaub, T. and Degrell, I. (2005) Cognitive
functions in prepsychotic patients. Prog. Neuropsychopharmacol. Biol.
Psychiatry, 29, 621–625.
54. McKirdy, J., Sussmann, J.E., Hall, J., Lawrie, S.M., Johnstone, E.C. and
McIntosh, A.M. (2008) Set shifting and reversal learning in patients with
bipolar disorder or schizophrenia. Psychol. Med., 39, 1289–1293.
55. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.,
Bender, D., Maller, J., Sklar, P., de Bakker, P.I., Daly, M.J. et al. (2007)
PLINK: a tool set for whole-genome association and population-based
linkage analyses. Am. J. Hum. Genet., 81, 559–575.
56. McCarroll, S.A., Kuruvilla, F.G., Korn, J.M., Cawley, S., Nemesh, J.,
Wysoker, A., Shapero, M.H., de Bakker, P.I., Maller, J.B., Kirby, A.
et al. (2008) Integrated detection and population-genetic analysis of
SNPs and copy number variation. Nat. Genet., 40, 1166–1174.
57. Stranger, B.E., Forrest, M.S., Dunning, M., Ingle, C.E., Beazley, C.,
Thorne, N., Redon, R., Bird, C.P., de Grassi, A., Lee, C. et al. (2007)
Relative impact of nucleotide and copy number variation on gene
expression phenotypes. Science, 315, 848–853.
58. Ge, D., Zhang, K., Need, A.C., Martin, O., Fellay, J., Urban, T.J.,
Telenti, A. and Goldstein, D.B. (2008) WGAViewer: software for
genomic annotation of whole genome association studies. Genome Res.,
59. Heinzen, E.L., Ge, D., Cronin, K.D., Maia, J.M., Shianna, K.V., Gabriel,
W.N., Welsh-Bohmer, K.A., Hulette, C.M., Denny, T.N. and Goldstein,
D.B. (2008) Tissue-specific genetic control of splicing: implications for
the study of complex traits. PLoS Biol., 6, e1.
60. Barrett, J.C. and Cardon, L.R. (2006) Evaluating coverage of
genome-wide association studies. Nat. Genet., 38, 659–662.
61. Glessner, J.T., Wang, K., Cai, G., Korvatska, O., Kim, C.E., Wood, S.,
Zhang, H., Estes, A., Brune, C.W., Bradfield, J.P. et al. (2009) Autism
genome-wide copy number variation reveals ubiquitin and neuronal
genes. Nature, 459, 569–573.
62. Kirov, G., Gumus, D., Chen, W., Norton, N., Georgieva, L., Sari, M.,
O’Donovan, M.C., Erdogan, F., Owen, M.J., Ropers, H.H. et al. (2008)
Comparative genome hybridization suggests a role for NRXN1 and
APBA2 in schizophrenia. Hum. Mol. Genet., 17, 458–465.
63. Vrijenhoek, T., Buizer-Voskamp, J.E., van der Stelt, I., Strengman, E.,
Sabatti, C., Geurts van Kessel, A., Brunner, H.G., Ophoff, R.A. and
Veltman, J.A. (2008) Recurrent CNVs disrupt three candidate genes in
schizophrenia patients. Am. J. Hum. Genet., 83, 504–510.
64. Rujescu, D., Ingason, A., Cichon, S., Pietilainen, O.P., Barnes, M.R.,
Toulopoulou, T., Picchioni, M., Vassos, E., Ettinger, U., Bramon, E.
et al. (2008) Disruption of the neurexin 1 gene is associated with
schizophrenia. Hum. Mol. Genet., 18, 988–996.
65. Kim, H.G., Kishikawa, S., Higgins, A.W., Seong, I.S., Donovan, D.J.,
Shen, Y., Lally, E., Weiss, L.A., Najm, J., Kutsche, K. et al. (2008)
Disruption of neurexin 1 associated with autism spectrum disorder.
Am. J. Hum. Genet., 82, 199–207.
66. Alarcon, M., Plomin, R., Fulker, D.W., Corley, R. and DeFries, J.C.
(1998) Multivariate path analysis of specific cognitive abilities data at 12
years of age in the Colorado Adoption Project. Behav. Genet., 28,
67. Crow, T.J. (2007) How and why genetic linkage has not solved the
problem of psychosis: review and hypothesis. Am. J. Psychiatry, 164,
68. Abel, T. and Zukin, R.S. (2008) Epigenetic targets of HDAC inhibition
in neurodegenerative and psychiatric disorders. Curr. Opin. Pharmacol.,
69. Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O.P., Ingason, A.,
Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T.,
Buizer-Voskamp, J.E. et al. (2008) Large recurrent microdeletions
associated with schizophrenia. Nature, 455, 232–236.
70. Weiss, L.A., Shen, Y., Korn, J.M., Arking, D.E., Miller, D.T., Fossdal,
R., Saemundsen, E., Stefansson, H., Ferreira, M.A., Green, T. et al.
(2008) Association between microdeletion and microduplication at
16p11.2 and autism. N. Engl. J. Med., 358, 667–675.
71. Friedman, J.I., Vrijenhoek, T., Markx, S., Janssen, I.M., van der Vliet,
W.A., Faas, B.H., Knoers, N.V., Cahn, W., Kahn, R.S., Edelmann, L.
et al. (2008) CNTNAP2 gene dosage variation is associated with
schizophrenia and epilepsy. Mol. Psychiatry, 13, 261–266.
72. Helbig, I., Mefford, H.C., Sharp, A.J., Guipponi, M., Fichera, M.,
Franke, A., Muhle, H., de Kovel, C., Baker, C., von Spiczak, S. et al.
(2009) 15q13.3 microdeletions increase risk of idiopathic generalized
epilepsy. Nat. Genet., 41, 160–162.
73. Kaiser, J. (2008) DNA sequencing. A plan to capture human diversity in
1000 genomes. Science, 319, 395.
74. Qu, L., Akbergenova, Y., Hu, Y. and Schikorski, T. (2009)
Synapse-to-synapse variation in mean synaptic vesicle size and its
relationship with synaptic morphology and function. J. Comp. Neurol.,
75. Bellgrove, M.A., Chambers, C.D., Johnson, K.A., Daibhis, A., Daly, M.,
Hawi, Z., Lambert, D., Gill, M. and Robertson, I.H. (2007)
Dopaminergic genotype biases spatial attention in healthy children. Mol.
Psychiatry, 12, 786–792.
76. Parker, E.S., Cahill, L. and McGaugh, J.L. (2006) A case of unusual
autobiographical remembering. Neurocase, 12, 35–49.
77. Mefford, H.C., Sharp, A.J., Baker, C., Itsara, A., Jiang, Z., Buysse, K.,
Huang, S., Maloney, V.K., Crolla, J.A., Baralle, D. et al. (2008)
Recurrent rearrangements of chromosome 1q21.1 and variable pediatric
phenotypes. N. Engl. J. Med., 359, 1685–1699.
78. Brunetti-Pierri, N., Berg, J.S., Scaglia, F., Belmont, J., Bacino, C.A.,
Sahoo, T., Lalani, S.R., Graham, B., Lee, B., Shinawi, M. et al. (2008)
Recurrent reciprocal 1q21.1 deletions and duplications associated with
microcephaly or macrocephaly and developmental and behavioral
abnormalities. Nat. Genet., 40, 1466–1471.
79. Hannes, F.D., Sharp, A.J., Mefford, H.C., de Ravel, T., Ruivenkamp,
C.A., Breuning, M.H., Fryns, J.P., Devriendt, K., Van Buggenhout, G.,
Vogels, A. et al. (2008) Recurrent reciprocal deletions and duplications
of 16p13.11: The deletion is a risk factor for MR/MCA while the
duplication may be a rare benign variant. J. Med. Genet., 46, 223–232.
80. Fellay, J., Shianna, K.V., Ge, D., Colombo, S., Ledergerber, B., Weale,
M., Zhang, K., Gumbs, C., Castagna, A., Cossarizza, A. et al. (2007)
A whole-genome association study of major determinants for host
control of HIV-1. Science, 317, 944–947.
4660 Human Molecular Genetics, 2009, Vol. 18, No. 23
81. Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick,
N.A. and Reich, D. (2006) Principal components analysis corrects for
stratification in genome-wide association studies. Nat. Genet., 38,
82. Ge, D., Zhang, K., Need, A.C., Martin, O., Fellay, J., Urban, T.J.,
Telenti, A. and Goldstein, D.B. (2008) WGAViewer: software for
genomic annotation of whole genome association studies. Genome Res.,
83. Takamiya, K., Mao, L., Huganir, R.L. and Linden, D.J. (2008) The
glutamate receptor-interacting protein family of GluR2-binding proteins
is required for long-term synaptic depression expression in cerebellar
Purkinje cells. J. Neurosci., 28, 5752–5755.
84. Moessner, R., Marshall, C.R., Sutcliffe, J.S., Skaug, J., Pinto, D.,
Vincent, J., Zwaigenbaum, L., Fernandez, B., Roberts, W., Szatmari, P.
et al. (2007) Contribution of SHANK3 mutations to autism spectrum
disorder. Am. J. Hum. Genet., 81, 1289–1297.
85. Durand, C.M., Betancur, C., Boeckers, T.M., Bockmann, J., Chaste, P.,
Fauchereau, F., Nygren, G., Rastam, M., Gillberg, I.C., Anckarsater, H.
et al. (2007) Mutations in the gene encoding the synaptic scaffolding
protein SHANK3 are associated with autism spectrum disorders. Nat.
Genet., 39, 25–27.
86. Wong, A.H., Lipska, B.K., Likhodi, O., Boffa, E., Weinberger, D.R.,
Kennedy, J.L. and Van Tol, H.H. (2005) Cortical gene expression in the
neonatal ventral-hippocampal lesion rat model. Schizophr. Res., 77,
87. Tang, Y.P., Shimizu, E., Dube, G.R., Rampon, C., Kerchner, G.A., Zhuo,
M., Liu, G. and Tsien, J.Z. (1999) Genetic enhancement of learning and
memory in mice. Nature, 401, 63–69.
88. McOmish, C.E., Burrows, E.L., Howard, M. and Hannan, A.J. (2008)
PLC-beta1 knockout mice as a model of disrupted cortical development
and plasticity: behavioral endophenotypes and dysregulation of RGS4
gene expression. Hippocampus, 18, 824–834.
89. DeLorey, T.M., Handforth, A., Anagnostaras, S.G., Homanics, G.E.,
Minassian, B.A., Asatourian, A., Fanselow, M.S., Delgado-Escueta, A.,
Ellison, G.D. and Olsen, R.W. (1998) Mice lacking the beta3 subunit of
the GABAA receptor have the epilepsy phenotype and many of the
behavioral characteristics of Angelman syndrome. J. Neurosci., 18,
90. Zhang, C.S., Bertaso, F., Eulenburg, V., Lerner-Natoli, M., Herin, G.A.,
Bauer, L., Bockaert, J., Fagni, L., Betz, H. and Scheschonka, A. (2008)
Knock-in mice lacking the PDZ-ligand motif of mGluR7a show impaired
PKC-dependent autoinhibition of glutamate release, spatial working
memory deficits, and increased susceptibility to pentylenetetrazol.
J. Neurosci., 28, 8604–8614.
91. Siegl, S., Flor, P.J. and Fendt, M. (2008) Amygdaloid metabotropic
glutamate receptor subtype 7 is involved in the acquisition of
conditioned fear. Neuroreport, 19, 1147–1150.
92. Goddyn, H., Callaerts-Vegh, Z., Stroobants, S., Dirikx, T.,
Vansteenwegen, D., Hermans, D., van der Putten, H. and D’Hooge, R.
(2008) Deficits in acquisition and extinction of conditioned responses in
mGluR7 knockout mice. Neurobiol. Learn. Mem., 90, 103–111.
93. Fendt, M., Schmid, S., Thakker, D.R., Jacobson, L.H., Yamamoto, R.,
Mitsukawa, K., Maier, R., Natt, F., Husken, D., Kelly, P.H. et al. (2008)
mGluR7 facilitates extinction of aversive memories and controls
amygdala plasticity. Mol. Psychiatry, 13, 970–979.
94. Callaerts-Vegh, Z., Beckers, T., Ball, S.M., Baeyens, F., Callaerts, P.F.,
Cryan, J.F., Molnar, E. and D’Hooge, R. (2006) Concomitant deficits in
working memory and fear extinction are functionally dissociated from
reduced anxiety in metabotropic glutamate receptor 7-deficient mice.
J. Neurosci., 26, 6573–6582.
95. Holscher, C., Schmid, S., Pilz, P.K., Sansig, G., van der Putten, H. and
Plappert, C.F. (2005) Lack of the metabotropic glutamate receptor
subtype 7 selectively modulates Theta rhythm and working memory.
Learn. Mem., 12, 450–455.
96. Holscher, C., Schmid, S., Pilz, P.K., Sansig, G., van der Putten, H. and
Plappert, C.F. (2004) Lack of the metabotropic glutamate receptor
subtype 7 selectively impairs short-term working memory but not
long-term memory. Behav. Brain Res., 154, 473–481.
97. Pietilainen, O.P., Paunio, T., Loukola, A., Tuulio-Henriksson, A.,
Kieseppa, T., Thompson, P., Toga, A.W., van Erp, T.G., Silventoinen,
K., Soronen, P. et al. (2008) Association of AKT1 with verbal learning,
verbal memory, and regional cortical gray matter density in twins.
Am. J. Med. Genet. B Neuropsychiatr. Genet.
98. Barnett, J.H., Jones, P.B., Robbins, T.W. and Muller, U. (2007) Effects
of the catechol-O-methyltransferase Val158Met polymorphism on
executive function: a meta-analysis of the Wisconsin Card Sort Test in
schizophrenia and healthy controls. Mol. Psychiatry, 12, 502–509.
99. Aerni, A., Traber, R., Hock, C., Roozendaal, B., Schelling, G.,
Papassotiropoulos, A., Nitsch, R.M., Schnyder, U. and de Quervain, D.J.
(2004) Low-dose cortisol for symptoms of posttraumatic stress disorder.
Am. J. Psychiatry, 161, 1488–1490.
100. Jansen, A., Krach, S., Krug, A., Markov, V., Eggermann, T., Zerres, K.,
Stocker, T., Shah, N.J., Nothen, M.M., Treutlein, J. et al. (2009) A
putative high risk diplotype of the G72 gene is in healthy individuals
associated with better performance in working memory functions and
altered brain activity in the medial temporal lobe. Neuroimage, 45,
101. Stefanis, N.C., Trikalinos, T.A., Avramopoulos, D., Smyrnis, N.,
Evdokimidis, I., Ntzani, E.E., Ioannidis, J.P. and Stefanis, C.N. (2007)
Impact of schizophrenia candidate genes on schizotypy and cognitive
endophenotypes at the population level. Biol. Psychiatry, 62, 784–792.
102. Stone, J.L., O’Donovan, M.C., Gurling, H., Kirov, G.K., Blackwood,
D.H., Corvin, A., Craddock, N.J., Gill, M., Hultman, C.M., Lichtenstein,
P. et al. (2008) Rare chromosomal deletions and duplications increase
risk of schizophrenia. Nature, 455, 237–241.
103. Roohi, J., Montagna, C., Tegay, D.H., Palmer, L.E., DeVincent, C.,
Pomeroy, J.C., Christian, S.L., Nowak, N. and Hatchwell, E. (2009)
Disruption of contactin 4 in three subjects with autism spectrum disorder.
J. Med. Genet., 46, 176–182.
104. Kirov, G., Grozeva, D., Norton, N., Ivanov, D., Mantripragada, K.K.,
Holmans, P., Craddock, N., Owen, M.J. and O’Donovan, M.C. (2009)
Support for the involvement of large cnvs in the pathogenesis of
schizophrenia. Hum. Mol. Genet., 18, 1497–1503.
105. Ben-Shachar, S., Lanpher, B., German, J.R., Qasaymeh, M., Potocki, L.,
Nagamani, S., Franco, L.M., Malphrus, A., Bottenfield, G.W., Spence,
J.E. et al. (2009) Microdeletion 15q13.3: a locus with incomplete
penetrance for autism, mental retardation, and psychiatric disorders.
J. Med. Genet.
106. Pagnamenta, A.T., Wing, K., Akha, E.S., Knight, S.J., Bolte, S.,
Schmotzer, G., Duketis, E., Poustka, F., Klauck, S.M., Poustka, A. et al.
(2009) A 15q13.3 microdeletion segregating with autism. Eur. J. Hum.
Genet., 17, 687–692.
107. Bijlsma, E.K., Gijsbers, A.C., Schuurs-Hoeijmakers, J.H., van
Haeringen, A., Fransen van de Putte, D.E., Anderlid, B.M., Lundin, J.,
Lapunzina, P., Perez Jurado, L.A., Delle Chiaie, B. et al. (2009)
Extending the phenotype of recurrent rearrangements of 16p11.2:
deletions in mentally retarded patients without autism and in normal
individuals. Eur. J. Med. Genet., 52, 77–87.
108. Mefford, H.C., Cooper, G.M., Zerr, T., Smith, J.D., Baker, C., Shafer, N.,
Thorland, E.C., Skinner, C., Schwartz, C.E., Nickerson, D.A. et al.
(2009) A method for rapid, targeted CNV genotyping identifies rare
variants associated with neurocognitive disease. Genome Res., 19,
109. Ullmann, R., Turner, G., Kirchhoff, M., Chen, W., Tonge, B.,
Rosenberg, C., Field, M., Vianna-Morgante, A.M., Christie, L.,
Krepischi-Santos, A.C. et al. (2007) Array CGH identifies reciprocal
16p13.1 duplications and deletions that predispose to autism and/or
mental retardation. Hum. Mutat., 28, 674–682.
110. Hoogendoorn, M.L., Vorstman, J.A., Jalali, G.R., Selten, J.P., Sinke,
R.J., Emanuel, B.S. and Kahn, R.S. (2008) Prevalence of 22q11.2
deletions in 311 Dutch patients with schizophrenia. Schizophr. Res., 98,
111. Bassett, A.S. and Chow, E.W. (2008) Schizophrenia and 22q11.2
deletion syndrome. Curr. Psychiatry Rep., 10, 148–157.
112. Karayiorgou, M., Morris, M.A., Morrow, B., Shprintzen, R.J., Goldberg,
R., Borrow, J., Gos, A., Nestadt, G., Wolyniec, P.S., Lasseter, V.K. et al.
(1995) Schizophrenia susceptibility associated with interstitial deletions
of chromosome 22q11. Proc. Natl Acad. Sci. USA, 92, 7612–7616.
Human Molecular Genetics, 2009, Vol. 18, No. 23 4661