UC San Diego
UC San Diego Previously Published Works
Title
Genome-wide analyses for personality traits identify six genomic loci and show
correlations with psychiatric disorders.
Permalink
https://escholarship.org/uc/item/5td9g058
Journal
Nature genetics, 49(1)
ISSN
1061-4036
Authors
Lo, Min-Tzu
Hinds, David A
Tung, Joyce Y
et al.
Publication Date
2017
DOI
10.1038/ng.3736
Peer reviewed
eScholarship.org Powered by the California Digital Library
University of California
152 VOLUME 49 | NUMBER 1 | JANUARY 2017 Nature GeNetics
Personality is influenced by genetic and environmental factors
1
and associated with mental health. However, the underlying
genetic determinants are largely unknown. We identified six
genetic loci, including five novel loci
2,3
, significantly associated
with personality traits in a meta-analysis of genome-wide
association studies (N = 123,132–260,861). Of these genome-
wide significant loci, extraversion was associated with variants
in WSCD2 and near PCDH15, and neuroticism with variants
on chromosome 8p23.1 and in L3MBTL2. We performed a
principal component analysis to extract major dimensions
underlying genetic variations among five personality traits
and six psychiatric disorders (N = 5,422–18,759). The first
genetic dimension separated personality traits and psychiatric
disorders, except that neuroticism and openness to experience
were clustered with the disorders. High genetic correlations
were found between extraversion and attention-deficit–
hyperactivity disorder (ADHD) and between openness and
schizophrenia and bipolar disorder. The second genetic
dimension was closely aligned with extraversion–introversion
and grouped neuroticism with internalizing psychopathology
(e.g., depression or anxiety).
The five-factor model (FFM) of personality, also known as the ‘Big Five’,
is commonly used to measure individual differences in personality. It
models personality according to five broad domains
4
. Extraversion
(versus introversion) reflects talkativeness, assertiveness and a high
activity level. Neuroticism (versus emotional stability) reflects negative
affect, such as anxiety and depression. Agreeableness (versus antago-
nism) measures cooperativeness and compassion. Conscientiousness
(versus undependability) indicates diligence and self-discipline.
Openness to experience (versus being closed to experience)
captures intellectual curiosity and creativity
4,5
. Personality pheno-
types, measured by various questionnaires, are represented by
continuous quantitative scores for each of the five traits
4
.
A meta-analysis of twin and family studies found that approxi-
mately 40% of the variance in personality could be attributed to genetic
factors
1
. Genome-wide association studies (GWAS) have discovered
several variants associated with FFM traits
6–8
. Neuroticism was reported
to be associated with an intronic variant in MAGI1 (P = 9.26 × 10
−9
,
N = 63,661)
7
, conscientiousness with an intronic variant in KATNAL2
(P = 4.9 × 10
−8
, N = 17,375)
6
, and openness with variants near RASA1
(P = 2.8 × 10
−8
, N = 17,375)
6
and PTPRD (P = 1.67 × 10
−8
, N = 1,089)
8
.
Additionally, recent UK Biobank studies (N = 106,716–170,908)
yielded several SNPs associated with neuroticism
2,3
.
Information collected by the consumer genomics company
23andMe contains well-phenotyped data on personality, as all par-
ticipants were evaluated with the same personality inventory (Online
Methods). Thus, the 23andMe data offer an opportunity to identify
additional genetic variants. We performed a meta-analysis based on
GWAS summary statistics to identify genetic variants associated with
FFM traits. We included participants with European ancestry from
23andMe (N = 59,225) and two samples (GPC-1 and GPC-2) from the
Genetics of Personality Consortium (GPC)
6,7
. GPC-1 (N = 17,375)
6
contains data on agreeableness, conscientiousness and openness,
whereas GPC-2 (N = 63,661)
7
contains information on extraversion
and neuroticism.
Summary statistics of GWAS from 23andMe (Supplementary
Data Sets 1–5) were combined with the two GPC samples separately,
yielding totals of 76,600 and 122,886 subjects for the discovery–stage
1 sample. Eight linkage disequilibrium (LD)-independent SNPs (LD
r
2
< 0.05) exceeded genome-wide significance (P < 5 × 10
−8
) in the
discovery meta-analysis (Table 1 and Fig. 1).
Genome-wide analyses for personality traits identify
six genomic loci and show correlations with psychiatric
disorders
Min-Tzu Lo
1
, David A Hinds
2
, Joyce Y Tung
2
, Carol Franz
3
, Chun-Chieh Fan
1,4
, Yunpeng Wang
5–7
, Olav B Smeland
6,7
,
Andrew Schork
1,4
, Dominic Holland
5
, Karolina Kauppi
1,8
, Nilotpal Sanyal
1
, Valentina Escott-Price
9
,
Daniel J Smith
10
, Michael O’Donovan
9
, Hreinn Stefansson
11
, Gyda Bjornsdottir
11
, Thorgeir E Thorgeirsson
11
,
Kari Stefansson
11
, Linda K McEvoy
1
, Anders M Dale
1,3,5
, Ole A Andreassen
6,7
& Chi-Hua Chen
1
1
Department of Radiology, University of California, San Diego, La Jolla, California, USA.
2
23andMe, Inc., Mountain View, California, USA.
3
Department of Psychiatry,
University of California, San Diego, La Jolla, California, USA.
4
Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA.
5
Department of Neurosciences, University of California, San Diego, La Jolla, California, USA.
6
NORMENT, KG Jebsen Centre for Psychosis Research, Institute of
Clinical Medicine, University of Oslo, Oslo, Norway.
7
Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
8
Department of Radiation
Sciences, Umea University, Sweden.
9
MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
10
Institute of Health and Wellbeing,
University of Glasgow, Glasgow, UK.
11
deCODE Genetics/Amgen, Reykjavik, Iceland. Correspondence should be addressed to C.-H.C. (chc101@ucsd.edu).
Received 22 July; accepted 2 November; published online 5 December 2016; doi:10.1038/ng.3736
L E T T E R S
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Nature GeNetics VOLUME 49 | NUMBER 1 | JANUARY 2017 153
To evaluate the consistency of association signals between 23andMe
and GPC samples, we conducted genome-wide polygenic analyses
using LD Score regression to examine genetic correlations (r
g
) (ref. 9)
of personality traits between the two samples. The estimated r
g
values were highly significant (r
g
= 0.86–0.96), suggesting that genetic
effects are consistent and replicable between the samples at the poly-
genic level (Supplementary Fig. 1) and that a considerable number of
SNPs below the GWAS significance threshold contain trait-associated
genetic effects.
To assess replicability of the eight significant SNPs identified in
the discovery–stage 1 sample, we obtained their summary statistics
from three independent samples, including an independent 23andMe
replication sample, UK Biobank cohort (neuroticism only) and
an Icelandic sample from deCODE Genetics (Online Methods and
Table 1). In the final combined meta-analysis, six SNPs remained
GWAS significant. The other two fell just below GWAS significance
but had consistent direction of effects in all samples, suggesting that
these may be significant in larger samples. Overall, the directions
of effects were consistent for all eight SNPs between the discovery
and replication tests, except two SNPs in the smaller (N = 7,137)
deCODE sample.
The strongest associations were detected for neuroticism within a
subregion of 8p23.1, which spans ~4 Mb (chr. 8: 8091701–11835712)
with highly correlated SNPs in one LD block (Fig. 2a). The 8p23.1
region comprises genes related to innate immunity and the nervous
system and is considered as a potential hub for cancer and develop-
mental neuropsychiatric disorders
10
. Our conditional analysis indi-
cated the presence of multiple associations (conditional P ~ 10
−7
)
independent of the top SNP within the 8p23.1 locus, but these were
not GWAS significant.
The UK Biobank studies also identified multiple associations
with neuroticism in 8p23.1 (refs. 2,3), which were attributed to an
inversion polymorphism
2
. Our association signals reside in the
same inversion region, with an LD of r
2
= 0.35 (LDlink) between
the lead SNP found here and that found in the UK Biobank study
3
.
Additionally, we identified an intronic variant of MTMR9 within
8p23.1 that was associated with extraversion and inversely associated
with neuroticism (Fig. 2b). Together, these findings provide converg-
ing evidence for the association of 8p23.1 with personality.
For extraversion, we found a significant locus on 12q23.3 within
WSCD2. This locus has been implicated in a GWAS of temperament
in bipolar disorder
11
and in a linkage analysis
12
, suggesting that 12q
harbors important alleles for temperament and personality. Another
SNP significantly associated with extraversion is near PCDH15,
which encodes a member of the cadherin superfamily important for
calcium-dependent cell–cell adhesion.
All six SNPs discovered here reside in loci for which genome-wide
significant associations with other phenotypes have been reported
(US National Human Genome Research Institute GWAS catalog). For
example, we found a variant associated with neuroticism in L3MBTL2,
a gene reported to be associated with schizophrenia
13
. Etiologically,
neuroticism has been associated with schizophrenia risk
14
. Further,
MTMR9, in which we found a variant associated with extraversion,
has been related to response to antipsychotic medications
15
. The SNP
associated with conscientiousness in the discovery sample, though not
significant in the final meta-analysis, was located in a locus linked to
educational attainment
16
, and high conscientiousness was found to
correlate positively with academic performance
17
.
These six SNPs were significantly associated with gene expression,
and all are listed as expression quantitative trait loci (eQTL) for brain
tissues (Supplementary Table 1). We performed a Bayesian test
18
Table 1 LD-independent genetic variants significantly associated with personality traits
Discovery–stage 1 Replication–stage 2
Combined analysis
SNP Chr.
Closest
gene (region)
A1/
A2 Frq.
23andMe
(N = ~59,200)
GPC (N = 17,375 and
63,661)
b
Combined
analysis
23andMe replication
(N = ~39,500)
deCODE
(N = ~7,100)
UK Biobank
(N = 91,370)
β
SE P
β
SE P P N
β
SE P
β
SE P
β
SE P P N R
2
(%)
Conscientiousness
rs3814424 5q LINC00461
a
T/C 0.17 –0.289 0.050 9.75 ×
10
−9
–0.138 0.131 0.294 2.98 ×
10
−8
76,551 –0.051 0.051 0.313 –0.005 0.027 0.855 6.19 ×
10
−7
123,132 0.0202
Extraversion
rs57590327 3p GBE1
(intergenic)
T/G 0.26 0.236 0.054 1.37 ×
10
−5
0.026 0.006 2.03 ×
10
−5
1.61 ×
10
−9
122,886 0.088 0.052 0.091 0.007 0.019 0.713 1.26 ×
10
−9
169,507 0.0217
rs2164273 8p MTMR9
(intron)
G/A 0.39 0.179 0.047 1.14 ×
10
−4
0.024 0.006 4.08 ×
10
−5
1.79 ×
10
−8
122,845 0.093 0.045 0.037 0.021 0.018 0.255 1.61 ×
10
−9
169,466 0.0215
rs6481128 10q PCDH15
(intergenic)
G/A 0.45 0.205 0.046 7.10 ×
10
−6
0.018 0.005 0.0010 4.15 ×
10
−8
122,886 0.154 0.045 5.58 ×
10
−4
–0.011 0.017 0.528 5.44 ×
10
−10
169,507 0.0227
rs1426371 12q WSCD2
(intron)
A/G 0.28 –0.308 0.053 4.65 ×
10
−9
–0.023 0.006 2.56 ×
10
−4
2.09 ×
10
−11
122,886 –0.177 0.051 5.09 ×
10
−4
–0.037 0.021 0.077 9.54 ×
10
−15
169,507 0.0354
rs7498702 16p RBFOX1
(intron)
C/T 0.29 –0.166 0.050 8.94 ×
10
−4
–0.026 0.006 1.17 ×
10
−5
4.73 ×
10
−8
122,886 –0.006 0.048 0.907 –0.005 0.018 0.777 1.89 ×
10
−6
169,507 0.0134
Neuroticism
rs6981523 8p XKR6
(intergenic)
T/C 0.50 0.250 0.042 2.68 ×
10
−9
0.022 0.006 1.01 ×
10
−4
4.25 ×
10
−12
122,867 0.138 0.042 1.05 ×
10
−3
0.032 0.018 0.070 0.098 0.015 1.04 ×
10
−10
3.17 ×
10
−24
260,861 0.0395
rs9611519 22q L3MBTL2
(exon) CHADL
(intron)
T/C 0.31 0.235 0.046 4.05 ×
10
−7
0.020 0.007 0.003 1.87 ×
10
−8
122,867 0.002 0.047 0.966 –0.002 0.023 0.931 0.053
c
0.017
c
0.0015
c
9.16 ×
10
−9
260,861 0.0127
A1, effect allele; A2, noneffect allele; frq., allele frequency of A1;
β
, linear regression association coefficient; SE, standard error; N, sample size.
β
and SE may have varying scales in different cohorts; thus sample-based meta-analyses were used.
a
SNP in non-protein coding region.
b
The sample sizes of GPC1 and GPC2 are 17,375 and 63,661, respectively.
c
Owing to absence of rs9611519 in the UK Biobank data, a proxy SNP (rs2273085, LD r
2
= 0.99) was used.
L E T T E R S
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154 VOLUME 49 | NUMBER 1 | JANUARY 2017 Nature GeNetics
L E T T E R S
to examine whether GWAS signals colocalize with eQTL. COLOC-
estimated posterior probabilities
18
(Online Methods) indicated
that one SNP-associated locus (rs57590327) and its correspond-
ing eQTL (Supplementary Table 1) were probably attributable to a
common causal variant (posterior probability = 0.76). Another SNP
(rs216273) showed evidence of independence with eQTL (posterior
probability = 0.75). For the rest of the SNPs, the posterior probability
ranged between 0 and 0.45, failing to support any of the specified
hypotheses. Our analyses did not show consistent evidence for these
SNPs influencing personality traits through gene expression in the
brain, but cautious interpretation is warranted owing to the small
eQTL sample (N = 134).
Beyond identifying single genetic variants that each account for
very little phenotypic variance, we estimated SNP-based heritability
of the traits. All heritability estimates were significant in the 23andMe
discovery sample, with the largest estimate for extraversion (H
2
= 0.18)
(Supplementary Table 2). These findings extend those from a previ-
ous heritability analysis of FFM traits (N = 5,011), in which SNP-based
heritability estimates were significant for neuroticism and openness
19
.
As expected, SNP-based heritability estimates were lower than those
reported in family studies
1
.
Relationships among personality traits are also of interest. Although
the FFM traits were derived through factor analysis and were thus
orthogonal in the original findings, most studies observe some degree
of phenotypic correlation between traits
19
. Using 23andMe data,
we found that neuroticism was inversely correlated with the other
personality traits, whereas agreeableness, conscientiousness, extra-
version and openness were all positively correlated; all phenotypic
correlations were highly significant except that between openness
and conscientiousness (Supplementary Table 3). Genetic correlation
8
7
6
5
4
3
2
Chromosome
Extraversion
–log
10
(P)
Agreeableness
Conscientiousness
rs3814424
9
8
7
6
5
4
3
2
–log
10
(P)
Neuroticism
rs6981523
rs9611519
12
10
8
6
4
2
rs57590327
rs2164273
rs6481128
rs1426371
rs7498702
12
10
8
6
4
2
8
7
6
5
3
4
2
Openness
–log
10
(P)–log
10
(P)–log
10
(P)
1
2 3 4
5
6 7 8
9 10 11 12
13 211917161514
Chromosome
1 2 3 4 5
6
7 8 9 10 11 12
13
2119
17161514
Chromosome
1
2
3 4 5 6 7 8 9 10 11 12
13
21
1917161514
Chromosome
1
2
3
4
5 6 7 8 9 10 11 12
13
2119
17161514
Chromosome
1 2 3
4
5
6
7 8 9 10 11 12 13 211917161514
Figure 1 Manhattan plots for personality traits in the combined sample
of 23andMe and GPC data (discovery–stage1 sample). Sample sizes
were as follows: agreeableness, N = 76,551; conscientiousness,
N = 76,551; extraversion, N = 122,886; neuroticism, N = 122,867;
openness, N = 76,581. Number of SNPs: agreeableness, N = 2,165,398;
conscientiousness, N = 2,166,809; extraversion, N = 6,343,667;
neuroticism, N = 6,337,541; openness, N = 2,167,320.
12
10
8
6
4
2
0
–log
10
(P)
10
8
6
4
2
0
–log
10
(P)
rs6981523
rs2164273
MSRA
PRSS55
SOX7
PINX1
LINCR-0001
RP1L1
C8orf74
XKR6
MIR598
MTMR9
BLK
SLC35G5
LINC00208
GATA4
DEFB136
DEFB130
DEFB135
DEFB134
FDFT1
C80rf49
NEIL2
CTSB
FAM66D
TDH
C8orf12
FAM167A
MIR1322
10 10.5 11 11.5 12
Position on chromosome 8 (Mb)
0.8
0.6
0.4
0.2
r
2
a
b
Figure 2 Regional association plot. (a,b) Distribution of −log
10
(P) of SNPs
on chr. 8p of the significant SNPs for neuroticism (a) and extraversion
(b, top) in the combined discovery analysis. The most significant SNPs
(rs6981523 and rs2164273) are shown in purple; otherwise, the colors
of the circles denote their correlations (LD r
2
) with the top SNP. These
SNPs (LD r
2
= 0.5 in LDlink) have opposite β signs in GWAS results for
neuroticism and extraversion. The opposite signals might be attributable
to negative phenotypic association between neuroticism and extraversion.
Gene symbols and locations within the region derived from UCSC Genome
Browser human hg19 assembly are shown (b, bottom). Regional plots
with detailed annotation information for significant SNPs are also
shown in Supplementary Figure 4.
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Nature GeNetics VOLUME 49 | NUMBER 1 | JANUARY 2017 155
L E T T E R S
patterns were congruent with phenotypic correlations, but the associa-
tions were more apparent in genetic structure, which reflected shared
genetic factors contributing to the correlations (Fig. 3a).
A notable feature of personality is its link with a wide range
of social, mental and physical health outcomes
5
. High levels of
neuroticism, extraversion and openness have been associated with
bipolar disorder
20
, and high neuroticism has been associated with
major depression and anxiety
21
. Low agreeableness has been asso-
ciated with narcissism, Machiavellianism and psychopathy
22
. In
addition to phenotypic relationships, twin and GWAS studies have
demonstrated genetic correlations between personality traits and
psychiatric disorders
3,21,23
, though most focus on neuroticism
(Supplementary Note).
We thus sought to quantify the genetic correlations between the five
personality traits and six psychiatric disorders from the Psychiatric
Genomics Consortium (PGC): schizophrenia (N = 17,115), bipolar
disorder (N = 16,731), major depressive disorder (N = 18,759), ADHD
(N = 5,422) and autism spectrum disorder (N = 10,263), and from
the Genetic Consortium for Anorexia Nervosa (N = 17,767) (Online
Methods and Supplementary Table 2). A pairwise genetic correlation
matrix (11 × 11) revealed several significant correlations (Fig. 3a and
Supplementary Table 4). For example, neuroticism was highly corre-
lated with depression, and extraversion with ADHD. To complement
genetic correlation estimation via LD Score regression
9
, we compared
the pattern of GWAS results by assessing whether signs of genetic
effects were concordant between the top associations among these
traits and disorders. The results of the sign tests of directional effects
closely matched the genetic correlations (Supplementary Fig. 2).
Given the moderate and high genetic correlations, we subsequently
conducted a principal component analysis (PCA) to extract principal
components of genetic variation (Fig. 3b). We projected all pheno-
types onto a two-dimensional space spanned by the top two principal
components (PC1 and PC2) of genetic variation to summarize the
genetic relationships between personality traits and psychiatric disor-
ders. The analysis integrates genomic information with traditionally
defined phenotypes to better understand basic dimensions of the full
range of human behavior, from typical to pathological, in line with the
research strategy of the Research Domain Criteria (RDoC)
24
.
Our results indicated that openness, bipolar disorder and schizo-
phrenia cluster in the first quadrant (Fig. 3b). Notably, all three share
phenotypic commonality in that they have been linked to height-
ened creativity and dopamine activity
25,26
. Most personality traits
(conscientiousness, agreeableness and extraversion) clustered in the
second quadrant. Neuroticism and depression were in the fourth
quadrant. Autism and anorexia nervosa were captured by factors in
higher dimensions and have relatively low loadings on the first two
components (as indicated by short arrows on these two dimensions
in Fig. 3b). Notably, ADHD showed a high genetic correlation with
extraversion and low correlations with other psychiatric disorders
(except bipolar disorder), as also shown in hierarchical clustering
analysis, in which ADHD clustered with personality traits rather than
psychiatric disorders (Supplementary Fig. 3). This may indicate that
ADHD, or some ADHD subtypes, represent a variant of extraversion.
Of note, our ADHD data were from individuals ranging in age from 5
to 19 years old. Phenotypically, positive emotionality has been linked
with a subgroup of children with ADHD
27
. Future genetic studies con-
sidering ADHD heterogeneity (e.g., subtypes and differences between
child and adult forms) may help characterize its diverse etiologies and
relationships with personality traits.
Overall, we observed a systematic pattern, with all psychiatric
disorders showing positive loadings on PC1, and agreeableness and
conscientiousness with negative loadings. A combination of low agree-
ableness and low conscientiousness is thought to reflect Eysenck’s
psychoticism trait
4
. PC2 was closely aligned with the extraversion–
introversion axis. Extraversion has been associated with externalizing
traits and behavioral activation, and introversion, with internalizing
traits and behavioral inhibition
28,29
. Internalizing traits (e.g., neuroti-
cism, depression, anxiety and withdrawal)
21
have negative loadings
on PC2. Externalizing traits are predicted by high extraversion, low
agreeableness and low conscientiousness
29
.
These findings provide additional support for shared genetic influ-
ences between personality traits and psychiatric disorders
3,21,23
and
for the idea that personality traits and psychiatric disorders exist on
a continuum in phenotypic and genomic space
5,11
. Maladaptive or
extreme variants of personality may contribute to the persistence of,
or vulnerability to, psychiatric disorders and comorbidity
5,11,21,23
.
Further genomic research in which categorical disease entities are
viewed as variants of quantitative dimensions in a polygenic frame-
work may help elucidate this issue
30
.
Agreeableness
Conscientiousness
Extraversion
Neuroticism
Openness to experience
Schizophrenia
Bipolar disorder
Major depression
ADHD
Autism spectrum disorder
Anorexia nervosa
Genetic
correlation
1.0
0.5
0
–0.5
–1.0
1.00
0.23**
0.23** 0.22** –0.40** 0.11 –0.03 0.07 –0.29* 0.08 –0.24* –0.03
1.00 0.15* –0.18* –0.19* –0.13* –0.18* –0.28* –0.10 –0.21* 0.01
–0.05–0.040.30*0.020.18*–0.010.34**–0.35**1.000.15*0.22**
–0.40** –0.18* –0.35** 1.00 –0.15* 0.14 –0.01 0.56** 0.06 0.10 0.15**
0.090.12
0.11 0.21**
0.19
–0.03
0.28*
0.47**
0.52**
1.00
–0.12
0.12
0.15 0.07 0.16*
0.170.12–0.12
1.00
–0.10
–0.10 –0.06
0.061.00
0.06 1.00
10 11
0.34**0.36**1.00–0.15*0.34**–0.19*0.11
–0.03 –0.13* –0.01 0.14 0.36** 1.00 0.65**
0.07 –0.18* 0.18* –0.01 0.34** 0.65** 1.00
0.52**0.47**0.28*0.56**0.02–0.28*–0.29*
0.08 –0.10 0.30* 0.06 0.19 –0.03 0.15
–0.24* –0.21* –0.04 0.10 0.12 0.11 0.07
–0.060.170.16*
0.21**
0.090.15**–0.050.01–0.03
987654321
0.8
0.6
0.4
0.2
0
–0.2
–0.4
–0.6
–0.8
Principal component 2 (19% of total genetic variance)
–0.9
–0.7
–0.5
–0.3 –0.1 0.1
0.3 0.5 0.7
0.9
Principal component 1 (25% of total genetic variance)
ADHD
Bipolar disorder
Schizophrenia
Anorexia nervosa
Autism
Major
depression
Extraversion
Agreeableness
Openness
Conscientiousness
Neuroticism
II I
III
IV
a
b
Figure 3 Genetic correlations between personality traits (23andMe sample)
and psychiatric disorders. (a) Heat map illustrating genetic correlations
between phenotypes. The values in the color squares correspond to genetic
correlations. Asterisks denote genetic correlations significantly different
from 0: *P < 0.05; **P < 0.00091 (Bonferroni correction threshold).
(b) Loading plot of personality traits and psychiatric disorders on the first
two principal components derived from the genetic correlation matrix
in a. A small angle between arrows indicates a high correlation between
variables, and arrows pointing in opposite directions indicate a negative
correlation in the space of the two principal components.
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
