Genetic variation in DTNBP1 influences general cognitive ability

Department of Psychiatry Research, The Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Albert Einstein College of Medicine, Glen Oaks, NY 11004, USA.
Human Molecular Genetics (Impact Factor: 6.39). 06/2006; 15(10):1563-8. DOI: 10.1093/hmg/ddi481
Source: PubMed


Human intelligence is a trait that is known to be significantly influenced by genetic factors, and recent linkage data provide
positional evidence to suggest that a region on chromosome 6p, previously associated with schizophrenia, may be linked to
variation in intelligence. The gene for dysbindin-1 (DTNBP1) is located at 6p and has also been implicated in schizophrenia, a neuropsychiatric disorder characterized by cognitive dysfunction.
We report an association between DTNBP1 genotype and general cognitive ability (g) in two independent cohorts, including 213 patients with schizophrenia or schizo-affective disorder and 126 healthy volunteers.
These data suggest that DTNBP1 genetic variation influences human intelligence.


Available from: Raju Kucherlapati
Genetic variation in DTNBP1 influences general
cognitive ability
Katherine E. Burdick
, Todd Lencz
, Birgit Funke
, Christine T. Finn
, Philip R. Szeszko
John M. Kane
, Raju Kucherlapati
and Anil K. Malhotra
Department of Psychiatry Research, The Zuc ker Hillside Hospital , North Shore-Long Island Jewish Health System
Department of Psychiatry, Albert Einstein College of Medicine, Glen Oaks, NY, USA and
Harvard Partners
Center for Genetics and Genomics, Boston, MA, USA
Received November 11, 2005; Revised and Accepted January 8, 2006
Human intelligence is a trait that is known to be significantly influenced by genetic factors, and recent linkage
data provide positional evidence to suggest that a region on chromosome 6p, previously associated with
schizophrenia, may be li nked to variation in intelligence. The gene for dysbindin-1 (DTNBP1) is located at
6p and has also been implicated in schizophrenia, a neuropsychiatric disorder characterized by cogni tive
dysfunction. We r eport an association between DTNBP1 genotype and general cognitive ability (g)intwo
independent cohorts, including 213 patients with schizophrenia or schizo-affective disorder and 126 healthy
volunteers. These data suggest that DTNBP1 genetic variation influences human intelligence.
A robust body of evidence suggests that cognitive abilities,
particularly intelligence, are significantly influenced by
genetic factors (1). The psychometric definition of intelligence
was first described in the early 20th century by Charles
Spearman and measures a ‘general cognitive ability’
(Spearman’s g), which is the product of an unrotated first prin-
cipal component analysis (PCA) score, accounting for 40%
of the variance in performance on diverse cognitive measures
(2). The concept of g is widely accepted as a measure of intel-
ligence (3,4) and is based on the significant covariance, or
phenotypic overlap, of a number of different cognitive pro-
cesses, such as memory, spatial ability and verbal ability (5).
In other words, an individual who performs well on a
measure of spatial ability is also likely to perform well on
a range of other cognitive tasks, with a large proportion of
variation in ability being accounted for by g.
Data from more than 8000 parent offspring pairs, 25 000
sibling pairs, 10 000 twin pairs and adoption studies provide
evidence that genetic factors play a substant ial role in the vari-
ation of g (6), with heritability estimates ranging from 40 to
80%. This suggests that there are genetically influenced mech-
anisms that affect performance across a number of diverse
cognitive measures. That is, a gene that influences working
memory is also very likely to be associated with other cogni-
tive abilities (i.e. processing speed) (79). Given the signifi-
cant overlap of the phenot ypic properties of cognition and
the underlying genetic overlap of independent cognitive abil-
ities, it has been suggested that g, despite its putative pheno-
typic com plexity, can be considered an ideal target for
molecular genetic studies.
Two recent linkage studies have provided converging pos-
itional evidence implicating a region on chromosome 6p in
general cognitive abilities in both healthy subjects (10) and
patients with schizophrenia (11). Posthuma et al. (10)
recently reported a genome-wide scan identifying two chro-
mosomal regions that demonstrate evidence of linkage for
intelligence. In 634 sibling pairs derived from two unselected
samples (475 sibling pairs from Australian families, 159
sibling pairs from Dutch families), model-free multipoint
linkage analysis revealed strongly suggestive linkage at
6p25.322.3 for full-scale IQ (LOD score 3.20) and for
verbal IQ (LOD score 2.33). This region overlaps with
regions implicated in dyslexia, reading disability (12) and
schizophrenia (13). Hallmayer et al. (11) reported that the
linkage of schizophrenia to this region was specific to a
subset of patients who were characterized by general
cognitive deficit.
# The Author 2006. Published by Oxford University Press. All rights reserved.
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*To whom correspondence should be addressed at: Department of Psychiatry Research, The Zucker Hillside Hospital, North-Shore-Long Island Jewish
Health System, 75-59 263rd Street, Albert Einstein College of Medicine, Glen Oaks, NY 11004, USA. Tel: þ1 7184708167; Fax: þ1 7183431659;
Human Molecular Genetics, 2006, Vol. 15, No. 10 15631568
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The gene for dysbindin-1 (DTNBP1) is located at 6p22.3
and is a strong candidate to explain these linkage results.
Although the specific role of DTNBP1 in the central nervous
system is unknown, dysbindin-1 is expressed widely in the
brain, including regions in the frontal cortex, temporal
cortex, hippocampus, caudate, putamen, nucleus accumbens,
amygdala, thalamus and midbrain (14). Moreover, DTNBP1
is demonstrated to influence risk for schizophrenia, a neuro-
psychiatric disorder characterized by cognitive impai rment
(15). Initial linkage of schizophrenia to this region was
reported by Straub et al. (16), with subsequent demonstration
of significant association of several variants in the gene that
encodes for dysbindin at chromosome 6p22.3 (17). Several
studies in different populations have been reported since and
most have confirmed an association of schizophrenia with
DTNBP1 (18 24).
Recent work by our group (25) supports an association of
DTNBP1 with schizophrenia. In a study comprising 524
patients with schizophrenia or schizo-affective disorder and
573 healthy volunteers, we identified a six-locus haplotype
(CTCTAC) that was significantly over-represented in the
Caucasian patients when compared with Caucasian healthy
volunteers (P ¼ 0.005). The minor alleles of three individual
SNPs [P1578-(rs1018381), P1763-(rs2619522) and P1765-
(rs2619528)] were also significantly over-represented in
patients (25). These studies, as well as reports of reductions
in DTNBP1 gene and protein expression in dorsolateral pre-
frontal cortex and hippocampal formation (26) in patients
with schizophrenia, provide convergent evidence that
DTNBP1 is involved in schizophrenia. However, to date,
there are no data that provide specific information on the
relationship betwee n DTNBP1 genotype and cognition.
Therefore, as linkage and association data suggest that dys-
bindin may influence cognition, we have conducted a study
specifically examining DTNBP1 genotype in a large sample
of subjects who were characterized for their cognitive per-
formance. Subjects included patients with schizophrenia or
schizo-affective disorder and healthy volunteers. We focussed
our analyses on the phenotype of g because of its broader var-
iance in schizophrenia, demonstrated heritability, and the
recent positional evidence of linkage for intelligence to the
chromosomal region containing DTNBP1. We hypothesized
that carriers of the six-locus haplotype that we previously
observed to be associated with increased risk for schizophrenia
(25) would have lower g than subjects without the risk haplo-
type. We focused our primary analyses on this haplotype for
several reasons: (i) This was the haplotype identified in our
Caucasian population to increase risk for schizophrenia. (ii)
This risk haplotype significantly overlaps with risk haplotypes
observed by other groups (17,18,22). (iii) The frequency of the
haplotype in schizophrenia patient s and in healthy volunteers
provided sufficient power to test its relationship to cognition
in our data set.
Sample characteristics by genotype are presented in Table 1.
The haplotype groups did not significantly differ on age, sex
or education level. Patients did not differ by haplotype
group on illness features including age at onset or global
assessment of functioning (GAF).
Analysis of g revealed a significant overall effect of geno-
type, with poorer performance by carriers of the risk haplotype
(mean ¼ 20.40 + 1.0) when compared with non-carriers
(mean ¼ 0.08 + 1.0) (F ¼ 7.03, df ¼ 1, 338, P ¼ 0.008). As
expected, the effect of diagnostic type was significant
(F ¼ 75.91, df ¼ 1, 338, P , 0.001); however, the diagnostic
type by genotype interaction was not significant (F ¼ 0.02,
df ¼ 1, 338, P ¼ 0.88). Nonethele ss, we assessed the effect
of genotype on g in each group independently, with con-
sistent results in each group. Health y volunteers carrying the
risk haplotype (mean ¼ 0.42 + 0.5) performed significantly
worse than non-carriers (mean ¼ 0.79 + 0.66) (F ¼ 4.29,
df ¼ 1, 125, P ¼ 0.040) and schizophrenia patients carrying
the risk haplotype (mean ¼ 20.72 + 1.0) performed signifi-
cantly worse than non-carriers (mean ¼ 20.38 + 0.9)
(F ¼ 4.50, df ¼ 1, 212, P ¼ 0.035) (Fig. 1). An effect size
estimate (partial
) suggests that genotype explains 3%
of the overall variance in g and was slightly larger in
healthy volunteers (3.3%) than in patients with schizophreni a
(2.1%). The absolute magnitude of the effect, however, is
similar in both diagnostic groups (0.37 points in healthy
volunteers and 0.34 points in patients with schizophrenia).
As age and sex are important factors related to cognitive
performance, we ran secondary analyses to control for their
effects and found that when co-varying for age, results
remain significant (P ¼ 0.03) and when entering sex as a
fixed factor, again results remain significant (P ¼ 0.02). In
addition, owing to unequal sample sizes and variances
between carriers and non-carriers, we ran a confirmatory
analysis using a non-parametri c approach, and results were
slightly more significant (MannWhitney U ¼ 5754.0,
P ¼ 0.003).
As we previously identified SNP 1578 to be a tagging SNP
for the risk haplotype, we conducted analyses of this SNP
using genotype and diagnostic type as fixed factors for analy-
sis of g. Results revealed a significant effect of genotype on g
Table 1. Sample characteristics of subjects with and without the DTNBP1 CTCTAC risk haplotype
Sample characteristic Healthy volunteers Schizophrenia patients
Carriers (n ¼ 15) Non-carriers (n ¼ 111) Carriers (n ¼ 39) Non-carriers (n ¼ 174) Statistic (P-value)
Age 54.7 (14.1) 50.7 (16.1) 41.7 (10.5) 37.9 (10.6) 21.17 (0.24)
Sex (% female) 86.7 57.6 41.0 31.6 X
¼ 2.6 (0.11)
Education 15.7 (2.7) 16.1 (2.4) 13.0 (2.2) 12.8 (3.2) 1.16 (0.25)
Age of onset 18.0 (5.4) 18.1 (5.4) 0.13 (0.89)
GAF 38.2 (12.4) 41.1 (16.1) 0.99 (0.32)
1564 Human Molecular Gen etics, 2006, Vol. 15, No. 10
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(F ¼ 5.09, df ¼ 1338, P ¼ 0.03), with carriers of the risk
allele performing significantly worse than non-carriers.
There were no other significant results at any of the other
five SNPs.
The complementary analysis, although not independent of
the primary analyses, evaluating haplotype frequencies in
the patient sample by comparing ‘cognitive-deficit’ versus
‘cognitively spared’ subgroups revealed that a sign ificantly
greater proportion of the cognitive-deficit patients carrie d the
risk haplotype (n ¼ 17, 28.3%) when compared with the
cognitively spared subgroup of patients (n ¼ 22, 14.4%)
¼ 5.61, df ¼ 1, P ¼ 0.02).
We evaluated the relationship between a DTNBP1 haplotype
(CTCTAC) previously observed by our group to be associated
with schizophrenia (25) and a calculated measure of g (the first
unrotated factor of a PCA with a number of diverse cognitive
measures) in two independent samples including patients with
schizophrenia and healthy volunteers and found that carriers
of the risk haplotype had lower g when compared with non-
carriers in both cohorts. The tagging SNP (SNP 1578) was
also associated with g in both groups, whereas no other indi-
vidual SNP was associated with neurocognition. Furthermore,
when we characterized the patient sample by cognitive-deficit
patients versus cognitively spared patients, we found that the
cognitive-deficit patients were nearly twice as likely to carry
the risk haplotype (27%) than the cognitively spared patients
(15%). These data suggest that DTNBP1 genotype plays a
significant role in the inter-individual variation in g.
These data are convergent with Posthuma et al. (10), who
recently provided evidence for linkage for intelligence to the
chromosomal region containing DTNBP 1 . In addition, our
results are consistent with the recent data of Hallmayer et al.
(11), which suggested that the linkage to schizophrenia in the
region of 6p may be driven by a cognitively impaired subgroup
of patients characterized as such by a latent structure analysis.
Furthermore, our data are consistent with hypothesized relation-
ship between DTNBP1 genotype and cognition, as suggested by
Williams et al. (24), based on an association in their sample
between level of education and a three-locus DTNBP1 haplo-
type. These data suggest that DTNBP1 may impart an increased
risk for schizophrenia through its effects on the specific
symptom domain of impaired cognition. However, the effect
of DTNBP1 on cognition may be only indirectly linked to its
role in susceptibility to schizophrenia, as we observe a similar
effect in healthy volunteers. Our data are also consistent with
a number of recent associations between candidate genes and
cognition in various populations, including catechol-o-methyl
transferase (COMT ) (7,8,27), disrupted in schizophrenia
(DISC1) (2830), succinate-semialdehyde dehydrogenase
(SSADH ) (31), apolipoprotein-E (APOE) (32) and KLOTHO
The mechanism underlying the effect of DTNBP1 genotype
on cognitive performance is curr ently unclear, especially
because it is broadly distributed throughout the central
nervous system , including regions in the frontal cortex, tem-
poral cortex, hippocampus, caudate, putamen, nucleus accum-
bens, amygdala, thalamus and midbrain (14). Dysbindin-1
binds to b-dystrobrevin, a component of the dystrophin glyc o-
protein complex (DPC) in the brain. Although the DPC is
found at postsynaptic sites, several studies demonstrate pre-
synaptic dysbindin expression in cerebellum and hippocampus
(26,34). b-dystrobrevin interacts with proteins (dysbindin and
muted) that are known subunits of biogenesis of lysosome-
related organelles complex-1 (BLOC-1), raising the possibility
that it may be involved in vesicle trafficking in non-muscle
tissue (35). Li et al. (35) suggest that dysbindin may be inde-
pendently part of both BLOC-1 and the DPC complex, with
distinct vesicle trafficking functions for each (35).
Preliminary data suggest that DTNBP1 genotype may
impact upon the GABAergic and glutamatergic systems
through reduced DTNBP1 expression (36 38). For example,
Numakawa et al. (37) presented a dysbindin knockdown
model resulting in reduced glutamate release, thought to be
caused by suppression of presynaptic proteins involved in
intracellular vesicle trafficking. Interestingl y, Bray et al. (36)
demonstrated that the A allele of rs1047631, a SNP related
to the schizophrenia risk haplotype in the Cardiff sample
(24), was linked to reduced cortical expression of DTNBP1
mRNA (36) . Further, the T allele of the tagging SNP P1578,
which was associated with lower g in the present study, is in
complete linkage disequilibrium (D
¼ 1) with the A allel e
of rs1047631 in both the postmor tem samples of Bray et al.
and the CEPH (Utah residents with ancestry from Northern
and Western Europe) samples of the HapMap Project (39).
Thus, it is possible to speculate that the risk haplotype
described in this report is associated with reduced dysbindin
expression, resulting in decreased levels of glutamate release
(24). It is important to emphasize, however, that no variant
within DTNBP1 has, as yet, provided direct evidence of func-
tional effects; therefore, additional efforts will be needed to
identify the putative functional locus.
Figure 1. DTNBP1 risk haplotype and general cognitive ability (g) in subjects
with and without the DTNBP1 CTCTAC risk haplotype. The X-axis represents
subject type. The Y-axis represents the first factor from the PCA calculated for
g. Z-scores are calculated using the standardized mean ¼ 0 and SD ¼ 1 from
the healthy volunteer sample, such that lower values reflect worse perform-
ance. Error bars represent 95% confidence interval. The overall effect of geno-
type is significant at P ¼ 0.008, and the subject type by genotype interaction is
not significant.
Human Molecular Genetics, 2006, Vol. 15, No. 10 1565
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In summary, we report an association between DTNBP1 and
g in two independent cohorts including patients with schizo-
phrenia and healthy volunteers, suggesting that DTNBP1 gen-
otype influences variation in human cognitive ability and
intelligence. Although these data suggest that DTNBP1 may
be a candidate gene for intelligence, DTNBP1 genotype
explained only a small proportion (3%) of the variance on
this measure, supporting a model involving multiple genetic
and environmental influences.
The study group included 213 unrelated Caucasian patients
with schizophrenia or schizo-affective disorder and 126
unrelated Caucasian healthy volunteers. All subjects provided
written informed consent to an Institutional Review Board of
the North Shore-Long Island Jewish Health System
(NSLIJHS)-approved protocol. Patients were recruited from
the inpatient units of the Zucker Hillside Hospital (ZHH), a
division of the NSLIJHS, in Glen Oaks, New York. Diagnosis
was established through structured interv iew (structured
clinical interview-DSM-IV; SCID-IV) (40) and confirmed by
diagnostic consensus conference.
Healthy volunteers for the project were recruited from the
general population. Advertisement was made by word of
mouth, newspaper and internet advertisements and posted
flyers. Prospective participants were administered the SCID-
IV, non-patient edition (SCID-NP) specifica lly designed to
assess healthy subjects.
In addition to the structured diagnostic interview, all poten-
tial subjects were screened to rule out any history of CNS
trauma, neurological disorder or learning disability. A urine
toxicology screen was also performed, and in the case of posi-
tive results, the subject was excluded. Healthy volunteers who
identified a first-degree relative with an Axis I disorder were
also excluded.
Cognitive measures
All subjects were administered a battery of standardized cog-
nitive measures comprising the Wide Range Achievement
Test-Third Edition-Reading Subtest (WRAT-3), Wechsler
Adult Intelligence Test-Revised (WAIS-R)-Digit Span, Con-
tinuous Performance Test-Identical Pairs Version (CPT-I/P),
California Verbal Learning Test (CVLT)-Abridged, Con-
trolled Oral Word Association Test (COWAT) and Trail
Making Te sts A&B (41). Our primary-dependent measure
was g, the first factor score derived from an unrotated principal
components analysis, as previously described (2). Data
reduction was achieved through factor analysis using principal
components as the extracti on method. All cognitive variable
data were transformed to standardized Z-scores, using the
healthy volunteers as the normative sample. Z-scores for all
variables were entered, and a total of 14 missing valu es in
the patient sample were replaced by the mean of the patient
group. There were no missing values in the healthy sample.
No case with more than one missing value was retained in
the sample. PCA was conducted in each group separately.
The factor structure was nearly identical in our healthy volun-
teers and patients with schizophrenia, with no factor loading
difference greater than 0.15; therefore, the data were
merged. The first unrotated factor explained 50% of the var-
iance and represented our general cognitive ability factor.
Each of the individual measures loaded onto the first factor
with covariance of .0.55. Factor scores representing g are
standardized using a Z-score scale with a mean of 0 and
standard deviation of 1.
DNA procedures
Genomic DNA was extracted from venous blood samples using
a standard protocol. Seven single nucleotide polymorphisms
[P1583-(rs909706), P1578-(rs1018381), P1763-(rs2619522),
P1320-(rs760761), P1765-(rs2619528), P1635-(rs3213207) and
P1325-(rs1011313)] were genotyped using the MALDI-TOF
mass spectrometry by the Sequenom system. However, only six
of the markers met the criteria for HardyWeinberg equilibrium;
hence, the seventh marker (P1635) was excluded from further
We utilized the SNPHAP program (David Clayton, Univer-
sity of Cambridge, UK) for estimating the haplotype frequen-
cies, which uses an expectation-maximization algorithm to
calculate maximum likelihood estimates of haplotype frequen-
cies, given genotype measurements which do not specify
phase. Any individual whose haplotypes could not be assigned
with a confidence of 95% or greater were excluded from the
final sample.
Statistical analyses
General cognitive ability (g) of subjects with at least one copy
of the risk haplotype (CTCTAC) identified by Funke et al.
(25) was compared with g of subj ects having no copies of
the haplotype, with independent univariate analysis of var-
iance (ANOVA). Owing to the low frequency of homozygote
risk haplotype carriers (n ¼ 7), these subjects were grouped
with heterozygote carriers for all analyses. Genotype and diag-
nostic type (patient versus healthy volunteer) were entered as
fixed factors and alpha level was set at 0.05. Follow-up testing
was conducted to assess the effect of genotype on g in each
subject group independently.
In a complementary analysis of the patient sample, we
assessed risk haplotype frequencies in a subgroup of patients
defined as ‘cognitive-deficit’ (whose performance fell at
least 1 SD below the mean g)(n ¼ 60) and compared them
with risk haplotype frequencies of a ‘cognitively spared’
subgroup of patients (n ¼ 153) using
The authors acknowledge Pamela DeRosse for her contri-
bution to subject diagnosis and database management and
Kate Nassauer, Gail Reiter, Adriana Franco, Erica Greenberg
and Denise Coscia for their role in the collection of the neuro-
cognitive data. In addition, we acknowledge Jenny M. Ekholm
for her cont ribution to the haplotype estimation for this study.
This work was supported by grants K23MH001760 to A.K.M.,
1566 Human Molecular Gen etics, 2006, Vol. 15, No. 10
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Page 4
K01MH65580-03 to T.L., P30MH60575-05 to J.M.K.,
HD034980-09 to R.K., NARSAD and the Stanley Medical
Research Institute (03-RC-001).
Conflict of Interest statement. None declared.
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    • "Dystrobrevin-binding protein 1 (DTNBP1), a gene encoding dysbindin-1, has been identified as a susceptibility gene for schizophrenia. Genetic variation in DTNBP1 affects cognitive function in patients with schizophrenia [1, 2], and in the healthy population [2]. In schizophrenia patients, dysbindin-1 expression is reduced in the dorsolateral prefrontal cortex and during hippocampal formation [3, 4]. "
    [Show abstract] [Hide abstract] ABSTRACT: Dystrobrevin-binding protein 1 (DTNBP1), a gene encoding dysbindin-1, has been identified as a susceptibility gene for schizophrenia. Functioning with partners in synapses or the cytoplasm, this gene regulates neurite outgrowth and neurotransmitter release. Loss of dysbindin-1 affects schizophrenia pathology. Dysbindin-1 is also found in the nucleus, however, the characteristics of dysbindin in the nucleus are not fully understood. Here, we found that dysbindin-1A is degraded in the nucleus via the ubiquitin-proteasome system and that amino acids 2-41 at the N-terminus are required for this process. By interacting with p65, dysbindin-1A promotes the transcriptional activity of NF-kappa B in the nucleus and positively regulates MMP-9 expression. Taken together, the data obtained in this study demonstrate that dysbindin-1A protein levels are highly regulated in the nucleus and that dysbindin-1A regulates transcription factor NF-kappa B activity to promote the expression of MMP-9 and TNF-α.
    Full-text · Article · Jul 2015 · PLoS ONE
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    • "Dysbindin has been implicated in cognitive performance in healthy (Luciano et al., 2009) and schizophrenia cases (Burdick et al., 2006; Fallgatter et al., 2006). Genetic variants of DTNBP1 have been associated with working memory (Donohoe et al., 2007), IQ (Zinkstok et al., 2007; Fatjovilas et al., 2011) and execution function (Luciano et al., 2009; Fatjovilas et al., 2011). "
    [Show abstract] [Hide abstract] ABSTRACT: Dystrobrevin binding protein 1 (DTNBP1) gene is pivotal in regulating the glutamatergic system. Genetic variants of the DTNBP1 affect cognition and thus may be particularly relevant to schizophrenia. We therefore evaluated the association of six single nucleotide polymorphisms (SNPs) with schizophrenia in a Malaysian population (171 cases; 171 controls). Associations between these six SNPs and schizophrenia were tested in two stages. Association signals with p < 0.05 and minor allele frequency > 0.05 in stage 1 were followed by genotyping the SNPs in a replication phase (stage 2). Genotyping was performed with sequenced specific primer (PCR-SSP) and restriction fragment length polymorphism (PCR-RFLP). In our sample, we found significant associations between rs2619522 (allele p = 0.002, OR = 1.902, 95%CI = 1.266 - 2.859; genotype p = 0.002) and rs2619528 (allele p = 0.008, OR = 1.606, 95%CI = 1.130 - 2.281; genotype p = 6.18 × 10−5) and schizophrenia. Given that these two SNPs may be associated with the pathophysiology of schizophrenia, further studies on the other DTNBP1 variants are warranted.
    Full-text · Article · May 2015 · Genetics and Molecular Biology
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    • "Recent studies have made significant progress in identifying genes correlated with greater intelligence. (see, e.g., [41–44]) Based on such findings parents may, in the near future, be able to use genetic manipulation to improve people’s cognitive capacities—which, given the above arguments, would lead to enhancement of autonomy. Of course, genetic manipulation is not the only way to enhance autonomy; other biomedical interventions such as pharmaceuticals, or more traditional means such as education, could have the effect. "
    [Show abstract] [Hide abstract] ABSTRACT: Some have objected to human enhancement on the grounds that it violates the autonomy of the enhanced. These objections, however, overlook the interesting possibility that autonomy itself could be enhanced. How, exactly, to enhance autonomy is a difficult problem due to the numerous and diverse accounts of autonomy in the literature. Existing accounts of autonomy enhancement rely on narrow and controversial conceptions of autonomy. However, we identify one feature of autonomy common to many mainstream accounts: reasoning ability. Autonomy can then be enhanced by improving people’s reasoning ability, in particular through cognitive enhancement; given how valuable autonomy is usually taken to be, this gives us extra reason to pursue such cognitive enhancements. Moreover, autonomy-based objections will be especially weak against such enhancements. As we will argue, those who are worried that enhancements will inhibit people’s autonomy should actually embrace those enhancements that will improve autonomy.
    Full-text · Article · Aug 2014 · Neuroethics
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