Covariation of Trait Anger and Borderline Personality

The Covariation of Trait Anger and Borderline Personality:
A Bivariate Twin-Siblings Study
Marijn A. Distel, Mark Patrick Roeling,
Jorim J. Tielbeek, and De´sie van Toor
VU University Amsterdam, Amsterdam, the Netherlands
Catherine A. Derom
University Hospital Gasthuisberg, Katholieke Universiteit
Leuven, Belgium
Timothy J. Trull
University of Missouri–Columbia
Dorret I. Boomsma
VU University Amsterdam, Amsterdam, the Netherlands
Anger can be defined as an emotion consisting of feelings of variable intensity, from mild irritation
or annoyance to intense fury and rage. Borderline personality disorder (BPD) is characterized by
impulsivity and instability of interpersonal relationships, of self-image, and of negative affects.
Borderline personality and trait anger are often observed together. The present study examined the extent
to which a genetic association explains the covariation between a trait measure of borderline personality
and trait anger. To this end, self-report data of 5,457 twins and 1,487 of their siblings registered with the
Netherlands Twin Register and the East Flanders Prospective Twin Survey were analyzed using genetic
structural equation modeling. A significant phenotypic correlation was observed between the two traits (rP
.52). This correlation was explained by genetic (54%) and by environmental influences (46%). A shared
genetic risk factor is thus one of the explanations for the covariation of borderline personality and trait anger.
Keywords: borderline personality, trait anger, twin study, genetic factors
Anger can be defined as an emotion that consists of feelings of
variable intensity, from mild irritation or annoyance to intense fury
and rage (Spielberger, Jacobs, Russell, & Crane, 1983). It can be
conceptualized as state anger, referring to an episode of anger
occurring at a specified time, or as trait anger, referring to an
aspect of personality (Eckhardt, Norlander, & Deffenbacher,
2004). Feelings of anger may be suppressed or directed inward
(“anger-in”) or expressed outwardly in some form of aggressive
behavior (“anger-out”). Anger has been related to several important constructs in behavioral medicine and psychological research.
For example, high levels of internal expression of anger and trait
anger have been associated with increased blood pressure and
induced hypertension (Markovitz, Matthews, Wing, Kuller, &
Meilahn, 1991; Schneider, Egan, Johnson, Drobny, & Julius,
1986), increased risk for coronary heart diseases (Atchison &
Condon, 1993; Williams et al., 2000; Leon, 1992; Kawachi, Sparrow, Spiro, Vokonas, & Weiss, 1996; Eaker, Sullivan, Kelly–
Hayes, D’Agonstino, & Benjamin, 2004; Chang, Ford, Meoni,
Wang, & Klag, 2002), and mental disorders such as anorexia and
bulimia nervosa (Fassino, Daga, Piero, Leombruni, & Rovera,
2001) bipolar disorder (Posternak & Zimmerman, 2002), and
borderline personality disorder (Morse et al., 2009).
Borderline personality disorder (BPD) is characterized by a
pervasive pattern of instability of interpersonal relationships, of
self-image, and of negative affects, and marked impulsivity that
begins by early adulthood and is present in a variety of contexts
(American Psychiatric Association [APA], 2000). BPD is diagnosed in approximately 1% to 2% of the general population
(Lenzenweger, Lane, Loranger, & Kessler, 2007; Torgersen, Kringlen, & Cramer, 2001) and is associated with a variety of negative
outcomes such as self-harm behavior, suicidal behavior, impaired
occupational and interpersonal functioning, delinquent behavior,
and substance abuse (Skodol et al., 2002). Inappropriate, intense
anger or difficulty controlling anger is the most prevalent BPD
criterion in clinical samples (Zanarini, Frankenburg, Hennen,
Reich, & Silk, 2005), nonclinical samples (Trull, 1995), and in first
degree relatives of BPD patients (Zanarini et al., 2004). Further,
This article was published Online First December 12, 2011.
Marijn A. Distel, Department of Biological Psychology, VU University
Amsterdam, Amsterdam, The Netherlands, and EMGO Institute for
Health and Care Research, VU University Medical Center, Amsterdam, the
Netherlands; Mark Patrick Roeling, Jorim Tielbeek, and De´sie van Toor,
Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands; Catherine A. Derom, Department of Human
Genetics, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Belgium; Timothy J. Trull, Department of Psychological Sciences,
University of Missouri–Columbia, Columbia, Missouri; and Dorret I.
Boomsma, Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands, EMGO Institute for Health and Care
Research, and Neuroscience Campus Amsterdam, VU University Medical
Center, Amsterdam, the Netherlands.
The present study was supported by the Borderline Personality Disorder
Research Foundation, Spinozapremie (NWO/SPI 56 – 464-14192), and
Twin-Family Database for behavior genetics and genomics studies (NWO
480 – 04-004). The authors declare no financial or other conflicts of interest.
Correspondence concerning this article should be addressed to Marijn A.
Distel, Department of Biological Psychology, VU University Amsterdam,
Van der Boechorststraat 1, 1081 BT Amsterdam, the Netherlands. E-mail:
[email protected]/[email protected]
Journal of Abnormal Psychology © 2011 American Psychological Association
2012, Vol. 121, No. 2, 458 – 466 0021-843X/11/$12.00 DOI: 10.1037/a0026393
458
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this feature was found to be among the slowest symptoms to remit
in BPD patients across 8- to 10-year follow up (Zanarini et al.,
2007).
Both trait anger and the trait of borderline personality are
heritable. Rebollo and Boomsma (2006) conducted a longitudinal
twin family study into the genetics of trait anger. The genetic
architecture of the trait differed in men and women. In males 23%
of the variance was explained by additive genetic effects and 26%
by dominant genetic effects, leading to a total heritability of 49%.
In women, 34% of the variance was explained by additive genetic
effects and no dominant genetic effects were found. Other studies
only focused indirectly on the heritability of anger or violence, for
example in genetic studies on antisocial personality disorder for
which the heritability was estimated at 38% (Cadoret & Stewart,
1991; Torgersen et al., 2008). Large-scale twin and twin family
studies of BPD and the trait of borderline personality report
heritability estimates around 40% (Distel et al., 2008a; Bornovalova et al., 2009; Kendler et al., 2008; Torgersen et al., 2008;
Distel et al., 2009). The study by Distel et al. (2009), included
twins as well as their parents and nontwin siblings and provided
evidence for the influence of nonadditive genetic effects, while
suggesting no effects of cultural transmission from parents to
offspring.
Some overlap between trait anger and the trait of borderline
personality is expected, considering that one of the nine criteria for
BPD concerns inappropriate expressions of anger and intense,
chronic feeling of anger (APA, 2000). However, most of the BPD
criteria do not directly tap trait anger. On the other hand, there are
many cognitive processes associated with trait anger (Owen, 2011;
Wilkowski & Robinson, 2010) that may at least partially explain
some of the remaining symptoms and features of borderline personality. For example, selective attention and reasoning biases
associated with trait anger may lead individuals to be hypervigilant
to possible threat or aggression and to attribute hostile intentions to
others so as to arouse anger more frequently (Wilkowski & Robinson, 2010). These cognitive processes associated with anger may
lead to rejection sensitivity and to interpersonal conflict and disruption often seen in those with BPD, for example (Romero–
Canyas et al., 2010). Therefore, an examination of the phenotypic
and genotypic association between trait anger and borderline personality can help to index the degree to which the two traits may
share a common underlying cause as well as point to potential
shared mechanisms (e.g., cognitive processes and biases) that may
inform theories of the etiology of BPD.
In the present study, we explored shared genetic risk factors as
a possible explanation for the covariation of borderline personality
and trait anger in the population. Data from twins and their siblings
were available from the Netherlands Twin Register (NTR;
Boomsma et al., 2006) and the East Flanders Prospective Twin
Survey (EFPTS; Derom et al., 2006) to disentangle genetic and
environmental influences on the covariance between borderline
personality and trait anger.
Methods
Participants
The present study is part of an ongoing study on health, lifestyle,
and personality in twins and their family members registered with
the NTR established in 1978 (Boomsma et al., 2006). Every 2
years, surveys on health and lifestyle were sent to the twin families. For the present study, data from the seventh survey were used
which was sent in 2004 –2005. Dutch-speaking twins in Belgium
were also asked to take part in the Dutch health, lifestyle, and
personality study. Belgian participants were recruited through the
EFPTS, a population-based register of multiple births in the Belgian province of East Flanders which was started in 1964 (Derom
et al., 2006). Young adult twins were contacted by mail and invited
to complete a survey which was enclosed with the letter. A
nonresponse study (Distel et al., 2007) showed that for a substantial group of targeted participants the addresses were incorrect.
This group thus never received the questionnaire. After correcting
for this, the response rate was estimated at 52.2% in the group of
targeted participants who participated before and 13.6% in the
group of targeted participants who were already registered, but
never completed a questionnaire.
For the Dutch sample zygosity was determined either from
DNA typing or from self-report answers to eight survey questions
on physical twin resemblance and confusion of the twins by family
members and strangers. Zygosity agreement reached 97% (Willemsen, Posthuma, & Boomsa, 2005). For the Belgian sample,
twin zygosity was determined through sequential analysis based on
sex, fetal membranes, umbilical cord blood groups, and placental
alkaline phosphatase until 1985. After that time, DNA fingerprinting was used. In case of missing or insufficient DNA information,
the zygosity of the same-sex DZ twins was based on survey items
on physical twin resemblance and confusion of the twins (see
Derom & Derom, 2005).
Data from 7,261 twins and siblings with valid scores on the trait
measures of borderline personality and anger were available. A
total of 928 twins were registered with the EFPTS. Twins with
unknown zygosity (N 94), individuals with an unknown age
(N 148) or sex (N 12) and individuals aged below 18 (N
14) were excluded. A maximum of two brothers and two sisters
were included in the analyses, remaining siblings were excluded
(N 49). This resulted in a total sample of 5,457 twins and 1,487
siblings from 3,946 families. The twin sample consisted of 813
monozygotic males (MZM), 416 dizygotic males (DZM), 2,095
monozygotic females (MZF), 1008 dizygotic females (DZF),
1,125 dizygotic opposite sex (DOS), and 528 brothers and 959
sisters. Table 1 shows the complete family configuration of the
sample. There were 1,866 families in which both members of a
twin pair completed the questionnaire, 1,725 families in which
only one member of the twin pair completed the questionnaire and
355 families in which only nontwin siblings completed the questionnaire. The mean (M) age of the twins was 34.46 years (standard deviation [SD] 10.98, range 18 – 87 years). The mean
age for the siblings was 39.89 years (SD 12.55, range 18 –91
years).
Measures
Trait anger was measured with the Dutch adaptation of the State
Trait Anger Scale (STAS, Spielberger et al., 1983; van der Ploeg,
Defanes, & Spielberger, 1982). The scale is designed to assess the
frequency of which an individual experiences the state anger over
time and in response to a variety of situations. The STASadaptation was scored on a 4-point Likert scale (1– 4; almost never,
TRAIT ANGER AND BORDERLINE PERSONALITY 459
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sometimes, often, almost always) and consists of 10 items concerning for example getting easily annoyed and irritated, being a
hotheaded person, flying off the handle, and having a fiery temper.
Participants were asked to indicate the extent to which an item
occurred in their everyday lives. The items were scored according
to the test manual, which states that at least 80% of the items must
be answered to calculate a sum score and that missing values or
ambiguous answers should be substituted by a score of 2 (sometimes true). Several studies have reported excellent psychometric
qualities, reliability () of 0.86 and good discriminant and convergent validity (Eckhardt et al., 2004). In the present sample, the
internal consistency (Cronbach’s alpha) was 0.85. Borderline personality was measured by the Dutch translation of the Personality
Assessment Inventory – Borderline features scale (PAI-BOR;
Morey, 1991). The PAI-BOR consists of 24 items rated on a
4-point scale (0 –3; false, slightly true, mainly true, very true) that
tap features of severe personality pathology clinically associated
with BPD, such as stability of mood and affects, self-image,
feelings of emptiness, intense and unstable relationships, impulsivity, and self-harm. The items were scored according to Morey’s
test manual, which states that at least 80% of the items must be
answered to calculate a sum score and that missing values or
ambiguous answers should be substituted by a zero score. Several
studies in clinical, as well as nonclinical samples, have supported
the reliability and validity of the PAI-BOR total score in indexing
the degree to which borderline features are present (Distel et al.,
2008b; Trull, 1995; Trull, 2001; Morey, 1991). Bell–Pringle et al.
(1997) and Stein, Pinkster–Aspen, and Hilsenroth (2007), for
example, showed that the PAI-BOR differentiates between patients
diagnosed with BPD and patients without borderline personality
pathology or unscreened controls with 75% to 80% accuracy.
Jacobo, Blais, Baity, and Harley (2007) administered the PAIBOR to patients diagnosed with BPD and found a significant
correlation of .58 between the total number of BPD SCID-II
criteria and the PAI-BOR scale. Finally, the 6-month test–retest
correlation of the Dutch version of the PAI-BOR assessed on 200
unrelated individuals was 0.78 (Distel et al., 2008a) and multigroup confirmatory factor analysis showed that the PAI-BOR is
measurement invariant across sex and age (De Moor, Distel, Trull,
& Boomsa, 2009).
The PAI-BOR does include two items that directly assess anger,
one asking whether the respondent has control over his or her
anger, and the other asking whether the respondent gets so mad,
s/he has trouble controlling feelings of anger. Therefore, as detailed below, we repeated all phenotypic and genotypic analyses
after deleting these two PAI-BOR items from the total PAI-BOR
score. In the present sample, the internal consistency (Cronbach’s
alpha) was 0.83 for the full PAI-BOR scale and 0.82 for the
22-item scale.
Twin Studies
In twin-family studies, the different degree of genetic relatedness of monozygotic (MZ) and dizygotic (DZ) twins and sibling
pairs is used to identify the relative contribution of genes and
environment to the phenotypic variation in a trait, or to the covariation between traits. MZ twins are (almost) genetically identical
and DZ twin and sibling pairs share on average half of their
segregating genes (Boomsma, Busjahn, & Peltonen, 2002). The
total phenotypic variance is decomposed into a part due to the
additive effects of alleles at all genomic loci (A), the nonadditive
genetic effects of alleles (D; dominance), the effects of the environment that is shared by individuals growing up in the same
family (C), and the effects of nonshared environment (which also
includes measurement error, E). The expectation for the phenotypic variance may be written as: V(P) V(A) V(D) V(C)
V(E). Broad-sense heritability (h2
) is the proportion of phenotypic
variance that is attributable to genotypic variance, h2 [V(A)
V(D)]/V(P); narrow-sense heritability is the proportion of variation
explained by additive genetic factors, hn
2 V(A)/V(P). Based on
Table 1
Family Configuration in the Sample According to Zygosity, Cohort, and Number of Additional Nontwin Siblings
Families yielding
No siblings 1 sibling 2 siblings 3 siblings 4 siblings Total
MZM
Families yielding a twin pair 202 64 12 6 1 285
Families yielding a single twin 207 27 9 0 0 243
DZM
Families yielding a twin pair 67 35 3 3 1 109
Families yielding a single twin 157 35 6 0 0 198
MZF
Families yielding a twin pair 613 164 39 9 2 827
Families yielding a single twin 373 56 12 0 0 441
DZF
Families yielding a twin pair 233 70 24 2 0 329
Families yielding a single twin 290 42 14 4 0 350
DOS
Families yielding a twin pair 223 79 11 2 1 316
Families yielding a single twin 404 67 17 4 1 493
Families yielding no twins — 282 62 10 1 355
Total 2769 921 209 40 7 3,946
Note. MZM monozygotic males; DZM dizygotic males; MZF monozygotic females; DZF dizygotic females; DOS dizygotic opposite sex.
460 DISTEL ET AL.
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data from only MZ and DZ twins and siblings this full model (i.e.,
ACDE) is not identified, and either an ADE or an ACE model can
be fitted to the data. The choice between these latter two models
may be based on prior knowledge or on the pattern of correlations
in MZ and DZ twins. When the DZ correlation is more than half
the MZ correlation, there is evidence for environmental effects
shared by twins from the same family (C) and when the DZ
correlation is less than half the MZ correlation, there is evidence
for nonadditive genetic effects (D). In the present study an ADE
model was fitted to the data. The ADE model is identified because
of the difference in correlations among the latent factors influencing the phenotype in MZ and DZ twin pairs. For MZ twin pairs
correlations between the A and the D factor score in twin 1 and
twin 2 are both one. For DZ and sibling pairs, these correlations are
0.5 and 0.25, respectively. Correlations between unique environmental factor scores in twin 1 and twin 2 are zero in MZ and DZ pairs
(e.g., Falconer & Mackay, 1996; Boomsma & Molenaar, 1986).
Bivariate genetic analyses can be applied to determine to what
extent the covariation between two traits can be explained by
genetic and environmental factors. The comparison of MZ and DZ
cross-twin cross-trait correlations provides a first indication about
the shared etiology between traits. If a significant cross-twin
cross-trait correlation is present it suggests that there is a familial
influence on the etiology of the correlation between the two traits.
If the MZ cross-twin cross-trait correlation exceeds the DZ crosstwin cross-trait correlation it suggests that the familial influence on
the correlation is at least partly genetic in origin. A graphical
representation of the bivariate genetic model is shown in Figure 1.
Statistical Analyses
We first fitted a saturated model in which variances, covariances
(among family members and among traits) and means were estimated. Mean borderline personality and trait anger scores were
estimated separately for twins and siblings. An effect of sex (coded
as 0 for males and 1 for females) and age (in years) were included
as fixed effects (regression coefficients) on each trait.
We tested for the significance of differences in mean scores of
twins and siblings and for the effect of sex and age on borderline
personality and trait anger scores. Significant effects of sex and
age were retained in subsequent genetic analyses. All correlations
between MZ and DZ twin and sibling pairs within and between
traits were estimated as a function of zygosity and sex. By constraining within-trait and cross-trait correlations to be equal for DZ
twins and nontwin siblings and between men and women within
the zygosity groups we tested for a specific twin environment and
for qualitative and quantitative sex differences. Qualitative sex
differences (i.e., different genes influence the trait in males and
females) are suggested if correlations in DZ twins of opposite sex
(DOS) cannot be predicted based on the pattern of correlations in
same-sex twin pairs. Quantitative sex differences (differences in
the magnitude of A, D, and E between males and females) are
suggested when the correlations in male–male and female–female
pairs within zygosity cannot be constrained to be equal without a
significant deterioration in the fit of the model.
To assess to what extent borderline personality and trait
anger share genetic liability, a bivariate genetic model was
fitted to the data in which the variance in borderline personality
and trait anger and the covariance between them was decomposed into sources of A, D, and E. In this model the first
variable loads only on the first factor and the second variable
loads on the first two factors. Constraining the contributions of the
latent factors of A or D at zero provides a test of whether these factors
significantly contribute to the total variance in the traits. The significance of the genetic and environmental covariance structure was
tested by constraining subsequent pathways (a21, d21, and e21 in
Figure 1) in the model at zero.
Figure 1. Bivariate genetic model; A1 and A2 additive genetic factors; D1 and D2 dominant genetic
factors; E1 and E2 unique environmental factors; a factor loading of A; d factor loading of D; e factor
loading of E. All latent A, D, and E factors have unit variance. For clarity reasons the nontwin sibling is not
drawn.
TRAIT ANGER AND BORDERLINE PERSONALITY 461
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All analyses were conducted using structural equation modeling
in MX (Neale, Boker, Xie, & Maes, 2006). Testing of submodels
was done by means of likelihood ratio tests, by subtracting the
negative log-likelihood (-2LL) for the more general model from
the 2LL of the more restricted model. This gives a 2 test with
the degrees of freedom (df) equal to the difference in the number
of estimated parameters in the two models. A significant 2
(p
.05) indicates that the constrained model is significantly worse
than the previous model and is therefore rejected. As a result, the
previous model is kept as the most parsimonious model, to which
a new model can be compared. In line with previous publication
based on these data, a square root data transformation was performed for the borderline personality data but not for the trait
anger data. To make sure this approach did not influence our
results we reran all analyses with transformations for both measures but this did not change the results.
Results
Tests of Fixed Effects on the Means and Variances
The borderline personality and the trait anger scores were not
significantly different for twins and siblings, (1)
2 0.008, p
.929 for borderline and (1)
2 0.053, p .818 for anger, and were
dependent on age (all p .01). Both age regression coefficients
were negative indicating that the borderline and anger scores
decrease with age. A sex effect was only significant for borderline
personality trait, (1)
2 6.349, p .012. Women had significantly
higher borderline personality scores than men. In subsequent analyses the significant effects of sex and age were retained in the
means model. Standard deviations were equal in males and females for both measures, (1)
2 0.072, p .788 for borderline
personality and (1)
2 2.092, p .148 for trait anger.
Correlation Structure
Table 2 shows the twin and sibling correlations from the saturated model (upper part) and the correlations from the most constrained model (lower part). Table 3 gives the results of the tests
performed on the correlation structure. The phenotypic correlation
between borderline personality and trait anger scores did not differ
for men and women and was estimated at .52 (Model 1). Correlations were similar for DZ twins and siblings for males and
females for both variables (Model 2). For both variables, the
correlations were equal for DZ males and females and same sex
siblings and for MZ males and females suggesting that the heritability is the same for men and women (Model 3). Additionally,
the DZ and sibling same sex correlations were equal to the DZ and
sibling opposite sex correlations indicating that the same genes
influence the borderline personality and trait anger in men and
women (Model 4).
Genetic Model
Based on the correlation structure, which does not provide
evidence for the influence of C, and the results from prior studies
(Distel et al., 2009; Torgersen et al., 2008; Kendler et al., 2008),
we fitted an ADE model to the data. Genetic model-fitting results
are summarized in Table 4. Removal of the dominant genetic
effects (Model 1) resulted in a significant worsening of the goodness of fit (p .027). Dropping path d21 from the model did not
result in a significant deterioration in model fit (Model 2; p
.237), but dropping the path a21 (Model 3; p .001) and the path
e21 (Model 4; p .001) did result in a significant decrease in
model fit. This means that there are additive genetic and unique
environmental factors that contribute to the covariance between
the traits. Table 5 shows the estimates A, D, and E on variance in
borderline personality and trait anger, the additive genetic and
environmental correlations and the percentage of the phenotypic
correlation explained by A and E. Figure 1 is a graphical representation of the bivariate model and gives the path coefficients
from the best fitting model in the right part of the graph. The total
variance in borderline personality can be written as (a11
2 ) (d11
2 )
(e11
2 ). The broad-sense heritability of borderline personality [calculated as (a11
2 ) (d11
2 )/(a11
2 ) (d11
2 ) (e11
2 )] was estimated at
46%. The influence of E on individual differences in borderline
personality [calculated as (e11
2 )/(a11
2 ) (d11
2 ) (e11
2 )] was estimated at 54%. Total variance in trait anger can be written as
(a21
2 ) (a22
2 ) (d21
2 ) (d22
2 ) (e21
2 ) (e22
2 ). The broad-sense
heritability of trait anger [calculated as (a21
2 ) (a22
2 ) (d21
2 )
(d22
2 )/(a21
2 ) (a22
2 ) (d21
2 ) (d22
2 ) (e21
2 ) (e22
2 )] was estimated
at 40%. The influence of E on trait anger [calculated as (e21
2 )
(e22
2 )/(a21
2 ) (a22
2 ) (d21
2 ) (d22
2 ) (e21
2 ) (e22
2 )] was estimated
at 60%. The additive genetic and environmental covariance may be
written as (a11 a21) and (e11 e21), respectively. The dominant
genetic covariance did not significantly explain covariance beTable 2
Twin and Sibling Correlations for Trait Anger and Borderline Personality
Twin correlation
trait anger
Twin correlation
borderline personality
Cross-twin cross-trait
correlation
Monozygotic males twin pairs .31 .46 .27
Dizygotic male twin pairs .14 .23 .11
Monozygotic female twin pairs .44 .46 .29
Dizygotic female twin pairs .12 .15 .09
Dizygotic opposite sex twin pairs .14 .20 .12
Brothers .15 .14 .10
Sisters .17 .24 .15
Brother–sister pairs .11 .13 .08
All monozygotic twins .41 .47 .29
All dizygotic twins/siblings .14 .18 .12
462 DISTEL ET AL.
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tween the traits. The additive genetic correlation (rGa) [calculated
as a11 a21/((a11
2 ) (a21
2 a22
2 ))] was estimated at .93 and
the environmental correlation [calculated as e11 e21/((e11
2 )
(e21
2 e22
2 ))] at .42. The percentage of the phenotypic correlation explained by A may be calculated as (hbpd
2 ) rG
(hanger
2 ) divided by the phenotypic correlation. Likewise, the
percentage of the phenotypic correlation explained by E may be
calculated as (ebpd
2 ) rE (eanger
2 ) divided by the phenotypic
correlation. Based on these calculations the phenotypic correlation
can be explained for 54% by A and 46% by E.
Replication Using the 22-Item PAI-BOR Scale
We repeated all analyses after deleting the two PAI-BOR items
that directly tapped anger from the total PAI-BOR score for each
participant. The same pattern of results was obtained. Specifically,
the phenotypic correlation was estimated at 0.50 as compared with
.52 in the original analyses. The correlation pattern was similar to
the original analyses. The MZ twin correlations and DZ twin/sib
correlations were estimated at 0.41 and 0.14 for trait anger, and at
0.46 and 0.18 for borderline personality, respectively. The cross
correlation was estimated at 0.28 for MZ twins and at 0.11 for DZ
twins and siblings. The heritability estimated found in the genetic
analyses were equal to those found in the original analyses. Only
the genetic correlation decreased from 0.93 to .89 and the unique
environmental decreased from 0.42 to 0.40.
Discussion
Both trait anger and borderline personality are influenced by
additive genetic, dominant genetic, and unique environmental factors. These findings are in line with previous studies reporting
heritability estimates for BPD, borderline personality scores, and
trait anger scores. Previous research showed that there is a moderate to high phenotypic correlation between trait anger and BPD
(Dolan, Anderson, & Deakin, 2001; Morse et al., 2009; Newhill,
Eack, & Mulvey, 2009). The basis of the overlap however remained unclear in these previous studies. In the present study,
structural equation modeling was applied to disentangle the relative influence of the genes and the environment on the covariance
between the trait of borderline personality and trait anger. Significant correlations between the latent additive genetic and unique
environmental factors that influence the two traits were found.
Results showed that the phenotypic association (r .52) could be
explained by additive genetic factors that are shared between the
traits (54%) and by shared unique environmental influences
(which also includes some measurement error; 46%). A similar
level of correlation (r .50) was found even after the two
PAI-BOR items that directly indexed anger were deleted from the
total PAI-BOR score. This result suggests that the moderate correlation between anger and borderline personality is not solely due
to shared item content.
Shared genetic risk is thus one of the possible explanations for
the association between trait anger and borderline personality. As
mentioned earlier, one possible shared set of mechanisms that
appear to characterize both those high in trait anger and those with
significant borderline personality features is a cognitive style that
includes selective attention to hostile social cues, a tendency to
interpret the actions of others as potentially hostile or aggressive,
and a propensity to ruminate over past transgressions by others or
anger-provoking experiences in general (Owen, 2011). Attentional
biases observed in BPD may help explain the tendency for those
with this disorder to experience chronic negative affect that is
interrupted only by intense episodes of fear, anxiety, or hostility
(Carpenter, Bagby–Stone, & Trull, 2011). Whether the intense
Table 3
Model Fit Results for the Saturated Bivariate Model
Model Test Versus 2LL df 2 df p
0 Full model — 56053.875 13855
1 Phenotypic correlation males Phenotypic
correlation females
0 56053.885 13856 .01 1 .920
2 Twin correlations sibling correlations 1 56059.194 13865 5.309 9 .807
3 Male correlations female correlations 2 56068.141 13871 8.947 6 .177
4 Same sex DZ/sibling correlations opposite
sex DZ/sibling correlations
3 56069.810 13874 1.669 3 .644
Note. 2LL 2 log likelihood; df degrees of freedom; p p-value; DZ dizygotic. The best fitting model is printed in bold.
Table 4
Genetic Model Fitting Results for Borderline Personality and Trait Anger
Model Test 2LL df 2 df p
0. ADE model — 52603.736 12994 — — —
1. AE model 1 vs. 0 52612.911 12997 9.175 3 .027
2. Drop path d21 2 vs. 0 52605.132 12995 1.396 1 .237
3. Drop path a21 3 vs. 2 52813.758 12996 208.626 1 .001
4. Drop path e21 4 vs. 2 52915.985 12996 310.853 1 .001
Note. v versus; 2LL 2 log likelihood; df degrees of freedom; p p-value; A additive genetic factors; D nonadditive genetic factors
(dominance); E unique environmental factors. The best fitting model is printed in bold.
TRAIT ANGER AND BORDERLINE PERSONALITY 463
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negative affect is experienced and expressed as anger or as fear, for
example, may depend on nature of the situation that arouses the
negative affect; anger is more likely to be aroused if approach
tendencies (goals) are blocked whereas fear or anxiety arise from
avoidance motivation (i.e., experience of threat; Carver &
Harmon–Jones, 2009). It is also worth noting that deficits in the
recruitment of effortful control resources (e.g., Rothbart, 1989) in
hostility-related contexts may play a role in the frequency, duration, and intensity of anger expression (Wilkowski & Robinson,
2010; Wilkowski & Robinson, 2010). Such a cognitive set characterized by these attentional biases, biased appraisals, ruminative
tendencies, and deficits in effortful control may contribute to BPD
features such as conflicted interpersonal relationships, impulsive
behavior, paranoid ideation, and even self-harm behaviors, in
addition to intense negative affects.
These cognitive processes described above, are activated by
environmental circumstances that are likely unique to the individual (i.e., nonshared environmental influence [e.g., rejection]). This
is in line with the moderate degree of correlation between unique
environmental influences on trait anger and on borderline personality found in this study. As there are no known specific environmental events that are unique to the development of BPD or trait
anger, another possibility to consider is the concept of an “invalidating environment,” which is a major component of Linehan’s
biopsychosocial model of BPD (Linehan, 1993). Briefly, Linehan’s model highlights the transactional process between emotional hypersensitivity and the experience of an invalidating environment, a process starting in childhood, which in turn leads to
major features of BPD. In her theory, an invalidating environment
is one that communicates to the individual that her or his emotional/internal experience or behavior is inappropriate or wrong.
Thus, it is not a specific environmental event per se, but rather an
encounter with others in the person’s unique environment context
that contributes to the “invalidating” experience. Therefore, invalidation may take the form of abuse, neglect, or excessive criticism
for example. Further, it is important to note that not all (e.g.,
siblings) are equally vulnerable to invalidation. Based on the
standard quantitative genetic model (Falconer & Mackay, 1996)
we know that siblings within the same family have correlated, but
different genotypes. Linehan proposes that those who are temperamentally emotionally sensitive are most vulnerable to the effects
of invalidation. It is important Linehan (1993) notes that the
consequences of invalidation include increased emotional arousal,
and negative affects such as anger. Therefore, we speculate that
this experience of an invalidating environment may be at least
partially responsible for the finding of a correlation between environmental influences on trait anger and on borderline personality
scores. More research will be necessary to directly test this proposal.
When interpreting the outcomes of this study, some limitations
should be kept in mind. First, as we noted above, the PAI-BOR
questionnaire includes two items (items 10 and 18) that explicitly
deal with anger. Although trait anger and anger as part of BPD are
two related but different concepts, this might have influenced the
results. Therefore, we reran the analyses excluding the two anger
related items from the PAI-BOR. The genetic architecture however
did not change, nor did the general pattern of results. Second,
nonresponse may limit the validity of questionnaire studies when
nonresponse is associated with the traits under study. Distel et al.
(2007) suggest that nonresponse may be higher among subjects
with more BPD features because the participating members of less
cooperative families showed somewhat higher scores on the PAIBOR scale compared to member of highly cooperative families.
However, the difference in borderline personality scores between
less and highly cooperative families was quite small so the practical importance of this difference should not be overestimated. For
trait anger, no significant association with nonresponse was found
(Distel et al., 2007). Third, self-report questionnaires were used to
assess borderline personality and trait anger. Although interview
data and questionnaire data for BPD are highly correlated (Kurtz &
Morey, 2001), results should be generalized to clinical populations
and to a BPD diagnosis specifically with caution. Finally, the
present study did not take possible gene– environment (GE) correlation or interaction into account (Livesley, 2008). If GE interaction plays an important role, its effects would be included in the
“E” component of the model, and thus the role of genetics might
be larger than indicated by the current results. If GE correlation
(the nonrandom distribution of genotypes across environments) is
present, part of the genetic influences derive from the effect of GE
correlation (Rutter, 2007). GE correlation was suggested for borderline personality and certain life events (Distel et al., 2011).
Future studies focusing on identifying the genes and the environmental factors that influence both trait anger and borderline personality will help us better understand the covariance of these
traits.
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Received February 15, 2011
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Accepted October 4, 2011
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You determine when you get the paper by setting the deadline when placing the order. All papers are delivered within the deadline. We are well aware that we operate in a time-sensitive industry. As such, we have laid out strategies to ensure that the client receives the paper on time and they never miss the deadline. We understand that papers that are submitted late have some points deducted. We do not want you to miss any points due to late submission. We work on beating deadlines by huge margins in order to ensure that you have ample time to review the paper before you submit it.

Will anyone find out that I used your services?

We have a privacy and confidentiality policy that guides our work. We NEVER share any customer information with third parties. Noone will ever know that you used our assignment help services. It’s only between you and us. We are bound by our policies to protect the customer’s identity and information. All your information, such as your names, phone number, email, order information, and so on, are protected. We have robust security systems that ensure that your data is protected. Hacking our systems is close to impossible, and it has never happened.

How our Assignment  Help Service Works

1.      Place an order

You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.

2.      Pay for the order

Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.

3.      Track the progress

You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.

4.      Download the paper

The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.

PLACE THIS ORDER OR A SIMILAR ORDER WITH US TODAY AND GET A PERFECT SCORE!!!