Heritability of borderline personality disorder features is similar across three countries

Psychological Medicine (2008), 38, 1219–1229.f 2007 Cambridge University Press doi:10.1017/S0033291707002024 Printed in the United Kingdom O R I G I N AL A R T IC L E Heritability of borderline personality disorder features is similar across three countries M. A. Distel1*, T. J. Trull2, C. A. Derom3, E. W. Thiery4, M. A. Grimmer5, N. G. Martin5, G. Willemsen1 and D. I. Boomsma1 1 Department of Biological Psychology, VU University, Amsterdam, The Netherlands Department of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, USA 3 Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium 4 Association for Scientific Research in Multiple Births, Gent, Belgium 5 Queensland Institute of Medical Research, Brisbane, Australia 2 Background. Most of our knowledge about borderline personality disorder features has been obtained through the study of clinical samples. Although these studies are important in their own right, they are limited in their ability to address certain important epidemiological and aetiological questions such as the degree to which there is a genetic influence on the manifestation of borderline personality disorder features. Though family history studies of borderline personality disorder indicate genetic influences, there have been very few twin studies and the degree of genetic influence on borderline personality disorder remains unclear. Method. Data were drawn from twin samples from The Netherlands (n=3918), Belgium (n=904) and Australia (n=674). In total, data were available on 5496 twins between the ages of 18 and 86 years from 3644 families who participated in the study by completion of a mailed self-report questionnaire on borderline personality disorder features. Results. In all countries, females scored higher than males and there was a general tendency for younger adults to endorse more borderline personality disorder features than older adults. Model-fitting results showed that additive genetic influences explain 42 % of the variation in borderline personality disorder features in both men and women and that this heritability estimate is similar across The Netherlands, Belgium and Australia. Unique environmental influences explain the remaining 58 % of the variance. Conclusions. Genetic factors play a role in individual differences in borderline personality disorder features in Western society. Received 17 April 2007 ; Revised 21 August 2007 ; Accepted 8 September 2007 ; First published online 8 November 2007 Key words : Borderline personality disorder, genetics, heritability, twin study. Introduction Borderline personality disorder (BPD) is a severe personality disorder whose features include impulsivity, affective instability, relationship problems and identity problems (APA, 2000). BPD is associated with interpersonal and occupational impairment, increased risk for suicide and higher rates of treatment in both medical and psychiatric settings (Skodol et al. 2002). In addition, BPD is frequently co-morbid with Axis I disorders, especially substance use disorders in males, eating disorders in females, anxiety disorders and mood disorders (Zanarini et al. 1998 ; Zimmerman & * Address for correspondence : M. A. Distel, M.Sc., VU University Amsterdam, Department of Biological Psychology, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands. (Email : [email protected]) Mattia, 1999), and this co-morbidity predicts poorer short- and long-term outcome (Skodol et al. 2002). Most of our knowledge about BPD has been obtained through the study of clinical samples. Clinical samples are important for characterizing the syndrome as it typically is presented for treatment, assessing the longitudinal course of the disorder, and evaluating the disorder’s response to forms of treatment. However, clinical samples are limited in their ability to address certain important epidemiological and aetiological questions as they are likely to contain more severe cases and may therefore not be representative of the disorder as it appears in the general population. Also, these clinical cases often exhibit more co-morbidity than cases from the community (Skodol et al. 2002), thereby further clouding the aetiological picture. In addition to clinical studies, it is therefore informative to identify BPD features in the Basic perinatal data. Specifically. to test for quantitative and qualitative sex differences and to determine whether our estimates were consistent across The Netherlands. (2000). At 6 months after the first questionnaire was sent. Belgium Dutch-speaking twins in Belgium were asked to take part in the Dutch health and lifestyle study. Increased rates of BPD have been found in the relatives of individuals with BPD (e. Twins approached by the ATR were . However. However. For this study. of whom 199 (83 %) completed the questionnaire a second time. Belgium and Australia. A. Protocols in all three countries were approved by their respective ethics committees. 1985 . general population to gain a full understanding of the nature of BPD and the developmental pathways leading to BPD. After subtracting the estimated number of incorrect addresses from the number of sent questionnaires. In total. we performed a non-response study by contacting by telephone two subgroups of nonrespondents . respectively .8 % and 42. of whom some individuals had participated before (n=7712) and some had never participated (n=5073). Loranger et al. Stubbe et al. our knowledge of the genetic influence on BPD symptoms and features is rather limited. this study is part of an ongoing study on health and lifestyle in twin families registered with The Netherlands Twin Register (Boomsma et al. 2004). Australia The Netherlands In The Netherlands. 1982 . siblings and parents (one per family).0 % of the two groups. non-respondents who had participated before and non-respondents who had never participated.g.g. 2002b. To extend the work of Torgersen et al. As most targeted Belgian participants had not participated in a study of the EFPTS before.6 %. negative emotionality) is well documented (Nigg & Goldsmith. Young adult twins were contacted by mail and invited to complete a survey which was enclosed with the letter. 2006). Vink et al. 4017 (31 %) twins returned the survey.2 %. we sought to assess a large number of community-based adult twins from a wide age range and from multiple countries. One important aetiological issue for which community samples are essential is the degree to which there is a genetic influence on the manifestation of BPD symptoms. For a subsample of the Dutch participants retest data were available. Details on response rates and demographic characteristics of the sample can be found elsewhere (Distel et al. it is unknown to what extent addresses were correct. 2007). Surveys on health and lifestyle were sent to the twin families every 2–3 years. 2004 .7 %. 2005). a population-based register of multiple births in the Belgian province of East Flanders which was started in 1964. neuroticism. (2000) reported on the largest twin study to date (n=221 twin pairs) that examined BPD. Results suggested a genetic liability for BPD of 69 %.0 % and a dizygotic (DZ) concordance rate of 11. and the heritability of traits that are highly associated with BPD (e. suggesting that shared environmental factors influence the variance in BPD. Australian subjects were drawn from the Australian Twin Register (ATR) founded in 1978 (Jardine et al. The pair-wise response rate was 15. The pair-wise response rate of the targeted twins who had and had not participated before was 33. though this heritability estimate must be considered approximate due to the small number of twins. Only two twin studies so far have provided data on BPD diagnoses and features. chorion type and zygosity have been established (Loos et al. Johnson et al. Zanarini et al.6 % and 6.1 % for BPD. of whom 932 (23 %) twins returned the survey. Multiples are ascertained at birth. the estimated ‘true ’ response rates for the two groups were 52. the retest survey was sent to 240 twins. Belgian and Australian twin cohorts. thus a substantial group of targeted participants never received the questionnaire. Method Participants Data were collected as part of an international project on BPD features in Dutch. we initiated a twin study of BPD features in the general population. data from the seventh survey were used which was sent in 2004–2005. A total of 3979 twins were approached. More recently. we were able to provide precise estimates of the genetic influence on BPD features. 1995 . Belgian participants were recruited through the East Flanders Prospective Twin Survey (EFPTS). methodological problems of that study limit any conclusions. Baron et al. 1994). the ascertainment method (sampling those who were treated for mental disorder) and the fact that the zygosity and diagnostic status of co-twins was not hidden from the interviewers. Torgersen et al. 1984). 2006 .1220 M. as well as from a twin group previously recruited by the Queensland Institute of Medical Research (QIMR). In this way. Derom et al.2 % and 13. Addresses proved incorrect in 23. Distel et al. To examine reasons for not participating. respectively. Torgersen (1984) reported a monozygotic (MZ) concordance rate of 0. 1998 . respectively. A total of 12 785 twins from 6764 families were approached. 78 with a structured interview-based assessment of BPD.74. 2005). the zygosity of 3135 same-sex twins was determined either from DNA polymorphism (n=1203) or from self-report answers to survey questions on physical twin resemblance and confusion of the twins by family members and strangers (n=1932). In case of missing or insufficient DNA information. this was renamed Health. as well as on empirical studies of borderline patients. A total of 783 twins were of opposite sex and therefore classified as DZ (see Willemsen et al. identity problems.D. resulting in a total of 699 completed surveys (493 online. 1991).1 years (S. fetal membranes.9. 2006). The English PAI-BOR was translated into Dutch and translated back into English by a native Englishspeaking translator.=3. 1991 . Comparing the resemblance in BPD features within MZ twin pairs with the resemblance in BPD features within DZ twin pairs provides information of how to explain individual differences in BPD features. 1221 Measures Borderline personality features were measured by the Personality Assessment Inventory – Borderline Features scale (PAI-BOR . the majority of the zygosity judgements determined the final outcome. When there were inconsistencies over time or persons reporting. Preliminary studies have supported the reliability and the validity of total PAI-BOR scores in indexing the degree to which borderline personality features are present (Morey. Triplets (n=51). In Belgium. like other siblings (Boomsma et al.=6. range 18–33 years). range 19–86 years). This resulted in a total sample for analysis of 5496 participants from 3644 families. umbilical cord blood groups and placental alkaline phosphatase until 1985. mainly true . 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. twins with unknown zygosity (n=55) or age (n=9) and twins without a valid score on the Personality Assessment Inventory-Borderline Features scale (PAI-BOR) (n=37) were excluded. potential PAI-BOR items were generated to reflect core factors of the construct (affective instability. Targeted participants included Australian twins born between 1972 and 1987 and were invited by mail to participate in the study.3 %) completed the survey. A total of 155 complete ATR twin pairs’ (310 twin individuals) contact details were forwarded to QIMR for approach with details for completing the survey either online or on paper . Morey (1991) also presented data supporting the validity of the four PAI-BOR subscales. 2001). Statistical analysis Twin studies make use of the genetic relatedness of twins and their family members. The PAI-BOR was scored according to Morey’s test manual (Morey. twin zygosity was determined through sequential analysis based on sex. Morey. 1995. The final version of the PAI-BOR consists of 24 items that are rated on a four-point scale (0 to 3 : false . slightly true . Based on a review of the historical conceptualizations of BPD. the zygosity of 674 twins was determined either from self-report answers to standard questions (n=299). Based on the answers to these items from all available surveys. which states that at least 80 % of the items must be answered to calculate a sum score and that missing and ambiguous answers should be substituted by a zero score. The pair-wise response rate was 50.=11. The Dutch translation of the PAIBOR was reviewed and approved by the test author and publishing company (Psychological Assessment Resources). Zygosity In The Netherlands.Heritability of borderline personality disorder features asked to participate in the Personality Features in Adulthood study . PAI-BOR items tap features of severe personality pathology that are clinically associated with BPD. DNA fingerprinting was used. Lifestyle and Personality study for the QIMR approach. range 18–67 years) and of the Australian twins 23.D.4 years (S. the Dutch adaptation of the PAI-BOR was used. 268 of the 310 twins (86. Demographics The mean age of the Dutch twins was 34. 431 (53. of the Belgian twins 28. indicating high convergent validity.9 years (S. because the twins were of opposite sex (n=91) or from DNA testing (n=284) (see Nyholt. 2001). 206 paper). After that time. zygosity was assigned. Kurtz & Morey (2001) for example showed that PAI-BOR scores correlated 0. In The Netherlands and Belgium. Trull.4 %) completed the survey. Final selection of items was guided by both the conceptual nature of the items as well as the items ’ psychometric properties.6 %. In Australia. When the DZ correlation is more . 2005). 2002a).6. Of the 808 twins approached directly by QIMR. 1988. Additive genetic effects (A) are suggested if the correlation in MZ twins is larger than the correlation in DZ twins. 1991). and the PAI-BOR has been used in a number of studies of non-clinical participants as well (Trull. 1991). negative relationships and selfharm/impulsivity) (Morey.D. MZ twins are genetically identical while DZ twins share on average 50 % of their segregating genes. very true). 1995. C and E (Neale & Cardon. 2006). The same direction of effect was observed in the other two samples. simultaneous genetic analyses of the data from the three countries were carried out. which also include measurement error.3 % in Australia. D and E. the standard deviations and age regression effects in Table 1 were based on the raw. Richmond. suggesting that the Dutch translation of the PAI-BOR is a reliable measure. by subtracting the negative log-likelihood (x2LL) for the more restricted model from the x2LL for the more general model. A. while a BPD diagnosis was suggested for 0. If the x2 test yields a p value higher than 0. Coid et al. Because the data showed a somewhat skewed distribution. Table 1 displays the twin correlations using the transformed data.94 points higher than men. D). The mean borderline scores for males and females (corrected for age). 2003). Results The 6-month test–retest correlation of the Dutch PAI-BOR was 0. Akaike. which implies that the genetic correlation for both DZ same-sex and DZ opposite-sex twins is 0. Finally. We tested for homogeneity of means and variances for MZ twins and DZ twins and for fixed effects of age and sex on BPD features. 1990 . Akaike’s Information Criterion (AIC . Johnson et al. Samuels et al. In each country mean borderline scores did not differ significantly between MZ and DZ twins. 1996 . a total PAI-BOR score of 38 or more indicates the presence of significant BPD features. Differences in BPD feature scores within MZ twin pairs are due to unique environmental influences (E). 1987 . Stone. The first model decomposed the variance of BPD features into A. standard deviations and correlation structure between the three countries. Statistical analyses were performed using structural equation modelling as implemented in the software package Mx (Virginia Commonwealth University. To obtain the estimated proportion of variance explained by A. D and E were modelled in this study. covariances and means were estimated.1222 M. 0. APA. a square root data transformation was performed. The raw data full information maximum likelihood approach in Mx was used to fit different models to the data. This yields a statistic that is distributed as x2 with degrees of freedom (df) equal to the difference in the number of parameters in the two models.0 % in Belgium and 5. the constrained model is deemed not significantly worse than the previous model and is kept as the most parsimonious model to which the next model will be compared. Testing of submodels was done by means of likelihood-ratio tests. there is evidence for non-additive genetic effects (dominance . we tested the significance of A and D separately by constraining these parameters to zero in each country.01. 2000 .84.03 % in The Netherlands. For each country the most parsimonious model was retained for simultaneous analysis of data from the three countries. The age regression coefficients on the . Standard deviations were equal between males and females and DZ and MZ twins. Next. untransformed data. According to Morey.1 % in Belgium and 0. Zygosity groups were separated by sex and both age and sex were included in the means model as a covariate. than half the MZ correlation. and for qualitative sex differences by constraining the DZ same-sex correlation to equal the DZ opposite-sex twin correlations. where women scored on average 1. Results of the tests performed in the saturated models for each country are shown in Table 2. but due to the smaller sample size these effects were not significant. 4. We first fitted a saturated model for each country separately in which variances. The internal consistency of the PAI-BOR items in the Australian sample was 0. Based on the pattern of twin correlations (see Results section).2 % in The Netherlands. Finally we tested for quantitative sex differences by constraining the correlations between men and women within zygosity to be equal. whereas a score of 60 or more indicates a likely Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV BPD diagnosis. we constrained the standardized estimates to be equal across the countries to obtain pooled estimates of the variance components explaining individual differences in BPD features. 2000 . VA . the better the fit of the model relative to the number of parameters estimated. The lower the AIC value. The sample prevalence of significant borderline features was 2. 1992) but the observed variances and covariances only provide enough information to model either an ACE model or an ADE model. D and E with different parameter estimates for each country.78 and the internal consistencies (Cronbach’s a) of the PAI-BOR items in the Dutch and Belgium samples were both 0. Bernstein et al.87. 2002 . Neale et al. The somewhat higher prevalence in Australia could be due to the younger age range of the Australian sample as the prevalence rates of BPD are known to be highest among young adults (Paris et al. Sex effects on the means were significant in the Dutch sample. The observed variance in BPD features can thus be decomposed in four possible sources of variance . A. We tested for differences in means. D.5. A.7 % in Australia. there is evidence for environmental effects shared by twins from the same family (C) but when the DZ correlation is less than half the MZ correlation. 1987) (x2x2df) was evaluated because it reflects both the goodness of fit and the parsimony of the model. In addition. Distel et al. 43 (0.33) 0. From complete (incomplete) twin pairs Maximum likelihood estimate (95 % CI) All monozygotic twins Maximum likelihood estimate (95 % CI)b All dizygotic twins Maximum likelihood estimate (95 % CI)b 374 (189) 0.43 (0.48) 0. untransformed (transformed)c 8. This indicates that there is no sex difference in the heritability of BPD features and that the same genes influence BPD features in males and females.24 (0.45 (0.12 (x0.36 to 0.86 (1.19 (x0.09) 22.35 to 0.03) x0.32 to 0.23 to 0.10) x0.32) Mean score males.29) 0.19 (0.55) 0.43 (0.40) 142 (74) 0.03 to 0.27 (0.01 (4.56) Australian twins 118 (45) 100 (36) 0.12 (x0. b After constraining these correlations to be equal.41 (1.25 (x0.03 to 0. Table 3 shows the results of the simultaneous modelling of the data from the three countries.07 to 0. Number of participants from complete and incomplete twin pairs in each zygosity group.07) 8.13 (x0. the maximum likelihood estimates of twin correlationsa (95 % CIs) and estimates for mean borderline scores for males and females.28 to 0. From complete (incomplete) twin pairs Maximum likelihood estimate (95 % CI) Monozygotic females n.49 (0.63) Standard deviation.58) 22.07 (x0.32 to 0.12 (x0.21 to 0.48 (0.32 (x0.30 (4.53) 1120 (396) 242 (73) 0.55) 0.Heritability of borderline personality disorder features 1223 Table 1.22 (0.36) 0.48) 0.37 to 0.11 to 0.24) 410 (373) Belgian twins 0. Confidence interval. Mean .02 to 0.52) Mean score females. From complete (incomplete) twin pairs Maximum likelihood estimate (95 % CI) Dizygotic opposite sex n.28 (x0.94 (1.42 (0.31 (x0.05 to 0. means were negative in all samples. the twin correlations for MZ males and MZ females were equal as were the twin correlations for DZ males.11 to 0.01) x0. For all three countries.56) 476 (275) 86 (59) 0.50) 58 (18) 0.45) 0. DZ females and DZ opposite-sex twins.03) Regression of age per year.27) 0.34 to 0. From complete (incomplete) twin pairs Maximum likelihood estimate (95 % CI) Dizygotic males n. untransformed (transformed)c 16.05 to 0.12 to 0. indicating that BPD features decrease with age.05 to 0.98 (4.64) 154 (151) 32 (33) 0.50) 170 (23) 0.46 (0. From complete (incomplete) twin pairs Maximum likelihood estimate (95 % CI) Dizygotic females n.62) 96 (12) 0.04 (3.11 (x0.55) 126 (35) 0. standard deviations and age regression Dutch twins Monozygotic males n. c Estimates are given for the untransformed data and using square root-transformed data.44) 21. untransformed (transformed)c CI. a Correlations were estimated from the square root-transformed data.83) 21.28 to 0. The age effect was significant in The Netherlands and in Belgium but not in Australia.43 (4.16 (x0.07) 9.35) 0. untransformed (transformed)c 17.94 (4.25 to 0. Mean MZ=mean DZ 2.03 x8. 5 1993. 2 4 v. 5 11467.52 5478 5480 5480 5484 76.D.61 x3.05 0.96 Australia 0. DZM=DZF 6. Twin correlations NL=BE=AU Test x2LL df Dx2 Ddf p AIC 1 v. Saturated model-fitting results for borderline personality disorder features in the Dutch.00 0.00). AU. 3 5 v. standard deviation. Distel et al. degrees of freedom . D and E were estimated for the three countries.22 2017.95 2632.3 % of the variance in BPD features in the Dutch sample.98 2642. dizygotic male .84 3. Correlation DZM=DZF=DOS 1 v.95 72. Table 2. monozygotic female .64 0.66 11477.83 x0.14 2008.26 655 656 665 666 667 669 670 2.90 16207. 2 4 v.08 0. DZ.87 Belgium 0. Table 3. S.5 % in the Belgium sample and 33. males=females and S.13 1 9 1 1 2 1 0.29 0.12 x3. 5 2627. 1 and 2.78 11474. 6. monozygotic . Means NL=BE=AU 2. Belgian and Australian twin data Test x2LL df Dx2 Ddf p AIC The Netherlands 0. df.50 6.91 0.00 0. 2 4 v.09 x7.16 0. dizygotic female . 3 6 v.29 2. AIC.23 0. explaining 34. 1 3 v. x2 log-likelihood .78 11476.55 x2LL.17 2007.97 885 886 895 896 897 898 899 5. 5. 0 2 v.D.63 1996.89 0. Akaike’s Information Criterion .71 2645.53 10.81 2018.81 16132. In addition. 0 2 v.37 0.D. 8. Saturated model 1. Correlation MZM=MZF. MZ=DZ 3. DZM=DZF 6. Removing D from the full model did not give a significant worsening of the goodness of fit (p=0.03 0.D. Saturated model 1.03 9. 0 2 v.11 0. Saturated model-fitting results including the data from three countriesa 0. Age effect on mean 5. AIC. MZF. 1 3 v. males=females and S. Mean MZ=mean DZ 2. Correlation DZM=DZF=DOS 1 v.D. 1 3 v.28 42.17 1. BE.98 for females).3.41 x1.53 x7. dizygotic .73 33.93 2645. resulting in model 3 as the best-fitting model.1 % in the Australian sample. Australia . Belgium and Australia and the same was true for DZ twins. NL.49 11519. MZ=DZ 3. Age effect on mean 5. 2 6 v.59 0. dizygotic opposite sex.D.1224 M.29 x2LL.31 2645.99 24.75 11469. 0 3 v. but standard deviations could be equated. df.86 0.70 2672.34 0.71 2 2 4 0.22 0.02 4. Belgium .7.02 x13. S. 3 5 v.26 0. The lowest mean score (corrected for age) was found in The Netherlands (16. scores differed between the three countries. Mean MZ=mean DZ 2.8 and 55.00 0. Correlation MZM=MZF. DZF. DZM=DZF 6.77 x1. Akaike’s Information Criterion .72 44. In the full genetic model without sex differences the variance components A. Sex effect on mean 4. respectively. NL=BE=AU 3. MZ. Saturated model 1.D..97 1.22 11509.58 x1. MZM. DOS.6. The Netherlands . MZ=DZ 3.D. degrees of freedom . indicating that model 3 was the most parsimonious model.71) of the model but removing A did (p=0. monozygotic male . Sex effect on mean 4. S.04 for males and 17. males=females and S.D. S.50 4. A. S.61 0. x2 log-likelihood . Sex effect on mean 4.3 and 58.74 2. Model-fitting results are shown in Table 4. 0 2 v.28 0. .99 26. the AIC of model 3 was lower than the AIC of models 0. Saturated model 1.58 2.79 3899 3900 3909 3910 3910 3911 3912 2.00 0.64 2015.45 1 9 1 1 2 1 0. 2 16130.73 35.12 0. Age effect on mean 5. 4 6 v.03 16131.04 1 9 1 1 2 1 0.. S.27 0. Correlation DZM=DZF=DOS 1 v. DZM. 37. standard deviation .4 and 57. The correlations for MZ twins were equal for The Netherlands. 2 5 v. Correlation MZM=MZF. a Effects of sex and age are modelled for each country separately.29 x1.03 x0.01 0. Although BPD is more often diagnosed in women than in men (Gunderson & Zanarini. (2000) reported a higher heritability estimate (69 %). 1 3 v. df. Widiger & Weissman.87 0. 2001) did not find sex differences. APA. Akaike’s Information Criterion . Grilo et al. 2002 . x2 log-likelihood . probably due to the narrow age range in the Australian sample (18 to 33 years) and the smaller sample size. a Effects of sex and age are modelled for each country separately. unique environmental factors . AIC. 2006). APA. mean scores on the PAI-BOR did not significantly differ between men and women in Belgium and Australia while in The Netherlands women scored higher than men. 2002 . AU. In our study. Environmental factors unique to an individual accounted for the remaining 58 % of the variance in BPD features.00 1 x4.5 41. Table 5. does not differ between men and women and acts in an additive manner. Results from non-clinical studies are also inconsistent . Coid et al.3 42.97 points (on a scale ranging from 0 to 72). similar across the three countries. additive genetic factors . Discussion The present study is a large-scale multinational twin study specifically focusing on BPD symptoms and features in community samples. 2000 . 1991 . Carter et al. Belgium . The aim of this study was to examine the genetic liability to BPD features in a large sample drawn from general populations. NL. Golomb et al.16 16132. 2000 . 2002) but only one (Carter et al.6 42. to test quantitative and qualitative sex differences. Several clinical studies have tested for sex differences in DSM personality disorders (Jackson et al. and the disorder occurs less frequently with increasing age (Paris et al. 1999 . Samuels et al. Grilo. Standardized estimates A and E equal. 1996 . Recently. However. Generally BPD symptoms appear by early adulthood.38 223. Table 5 shows the estimates of the proportion of variance explained by A and E for each country and the three countries pooled. all age regression coefficients on the mean borderline features score were negative. 2006). AE for each country 2. In the present study. research findings about the sex difference in the prevalence of BPD are inconclusive. Johnson et al. NL=BE=AUb Test x2LL df Dx2 Ddf p AIC 1 v. 1999) found a sex difference. Torgersen et al. Maximum likelihood estimates of proportions of variance explained by additive genetic and unique environmental effects The Netherlands ( %) Belgium ( %) Australia ( %) Estimates constrained to be equal ( %) A E 42. Coid et al. 1991 . this sex difference was relatively small with a mean difference of 1. others in men (Samuels et al. non-additive genetic factors (dominance) . while the only large representative populationbased study (Torgersen et al. Additive genetic effects .7 57.71 0. 1990 . 1995 . indicating that BPD features decrease with increasing age.29 16356.01 3 3 4 0. We found that BPD features are genetically influenced (42 %) and that this genetic influence. unique environmental effects. Bernstein et al. Stone. E for each country 3. 2007). The Netherlands . b Best-fitting model. E.4 57.90 16132. ADE 1.5 58. degrees of freedom .87 x7. BE.30 5478 5481 5484 5485 1. 0 2 v. 1996 . Genetic model-fitting results including the data from three countriesa 0. though this estimate is probably too high due to methodological limitations.8 A.2 57.62 217. D. The young age of the Australian cohort may also explain why the number of subjects scoring >60 is higher in the Australian sample than in the Dutch and Belgian sample. 1989).99 x2LL. the prevalence being unexpectedly higher in men. A. Australia. Belgium and Australia. 1987 . The DSMIV-R defines personality disorders within a categorical system. In the Australian cohort this age effect was not significant. but the inclusion of a dimensional model of . and for differences between The Netherlands. some reported higher prevalence rates in women (Zimmerman & Coryell. 2000). the nature of personality disorders and its relationship to normal personality has received extensive attention (Widiger & Trull. E.Heritability of borderline personality disorder features 1225 Table 4. 1 16130. 1987 . although the effects were small. 47 in clinical (Pukrop et al. 2004). for example. 2005). and for Cloninger’s novelty-seeking scale (Keller et al. and the Five Factor Model (FFM) of personality (Costa & McCrae. 1991). Jang et al. cooperativeness and selftranscendence). which distinguishes four higher-order factors (emotional dysregulation. Zimmerman & Mattia. 2000 . the diagnostic construct of BPD. Trull. at least in the Dutch sample. but are broader than. suggesting non-response will be higher among subjects with more BPD features. According to Livesley. many of invited family members participate) with data provided by the participating members of less cooperative families (i. 1998 . Jacobo et al. Widiger & Trull. c). when nonresponse influences the data collected in survey research. 1998). In addition. (2007). However. 2003) samples. this may seriously limit the validity of the findings. Three proposed dimensional models of personality are Livesley’s 18-factor model of personality pathology (Livesley. the PAI-BOR questionnaire was used to measure BPD features. The co-morbidity between BPD and other personality disorders as well as Axis I disorders is also well documented by studies using clinical samples (Zanarini et al. Johnson et al. 1995). This suggests that although there is a difference. 1990. but these are unlikely to be large. For example. These findings support the present finding of moderate genetic effects on the manifestation of traits related to BPD features. reward dependence and persistence) and three dimensions of character (self-directedness. The heritability estimate of 42 % may include some non-additive effects. openness to experience. which distinguishes five personality traits (neuroticism. we did not find evidence for non-additive genetic effects though the twin correlations suggested a contribution of non-additive genetic influence. a high score on the PAI-BOR is associated with higher prevalence rates for several Axis I disorders (Trull. Distel et al. Livesley’s trait model of personality pathology is operationalized through a self-report questionnaire. Several prior studies have shown the PAI-BOR to be a reliable and valid measure of BPD features. 1986. Second. In the future we will collect and include data of siblings and parents of twins in the model to increase statistical power. 2001) and 0. provided support for the heritability of most of the 18 lower-order DAPPBQ traits and of all of the four higher-order factors. both higher-order personality traits believed to be associated with BPD (Morey. 2007 . First. 1996b. 1993). Because BPD has a familial component. The heritability for emotional dysregulation has been reported at 53 % and for the primary traits making up emotional dysregulation at 44 % to 53 % (Jang et al. Livesley. the difference between participants from less cooperative and highly cooperative families was relatively small. Concerning traits from the FFM and Cloninger’s psychobiological model. which constituted the largest sample in the present study. Livesley et al. BellPringle et al. 1991 .1226 M. A. and support the usefulness of the PAI-BOR in assessing BPD features in the general population as well as BPD in the clinical setting (Kurtz et al. While clinical studies tend to sample the most severe cases. 2007). In the present study. 2002). 2007). 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. Korner et al. 1996 a . McGlashan et al. . Several issues should be kept in mind when interpreting the results of this study.58 between the total number of BPD SCID-II criteria and the PAI-BOR scale. the correlation between DAPP-BQ emotional dysregulation scores and the number of BPD symptoms has been estimated to be 0. the emotional dysregulation factor and its first-order traits resemble. 2000 . inhibitedness. Becker et al. 1995). 1996c . 1992). dissocial behaviour. harm avoidance. In addition.62 in non-clinical (Bagge & Trull. agreeableness and conscientiousness). 2007 . Distel et al. (1997) and Stein et al. 2006). (2007) administered the PAI-BOR to patients diagnosed with BPD and found a significant correlation of 0. 1998 . As expected. with a mean difference of less than 1 point on a scale ranging from 0 to 72. 1987).e. Grilo et al. heritability estimates between 41 % and 55 % have been reported for the big five factor neuroticism (Jang et al.e. extraversion. questionnaire data on BPD features are relatively unbiased. compulsivity). the Dimensional Assessment of Personality Pathology – Basic Questionnaire (DAPP-BQ . The PAI-BOR does not diagnose BPD per se. needed to address this issue more thoroughly. which distinguishes four dimensions of temperament (novelty seeking. non-response bias might cause affected individuals to be under-represented in population studies. personality is increasingly recommended (Trull et al. twin-family studies can study this possible nonresponse bias by using data from respondents as a proxy for the data of their non-responding family members. A series of small-sample twin studies (Livesley et al. few invited family members participate). 1993. Saulsman & Page. the participating members of less cooperative families showed somewhat higher scores on the PAI-BOR scale. 2004 . (2007) compared borderline personality scores from highly cooperative families (i. 1999 . Livesley. but assesses features related to the BPD syndrome which are also common to other personality disorders (Morey. 1993 . Cloninger’s psychobiological model (Cloninger et al. Zanarini MC (1987). Mulder RT. Asnis L. Distel MA. Tyrer P. Psychological Assessment Resources : Odessa. Grilo CM. Trull TJ (2003). American Journal of Psychiatry 153. 19–32. American Journal of Psychiatry 152. Abraham M. Leroy FOG. Hottenga JJ. Genome-wide analyses of European twin and population cohorts to identify genes predisposing to common diseases (EU/QLRT2001-01254). Journal of Personality Disorders 13. In Multiple Pregnancy : Epidemiology. Gunderson JG. BellPringle VJ. Pate JL. 401–406. Bagge CL. 733–738. Grilo CM. McGlashan TH (2000). de Geus EJC. Edell WS. Brown RC (1997). Are there gender differences in DSM-IV personality disorders? Comprehensive Psychiatry 43. pp. Netherlands Twin Register : a focus on longitudinal research. Twin Research and Human Genetics 10. Knol LI. VA. Walker ML. Assessment of borderline personality disorder using the MMPI-2 and the personality assessment inventory. K. Anez LM. American Journal of Psychiatry 142. Netherlands Twin Register : from twins to twin families. neuroimaging findings and psychophysiological indicators. Grilo CM (2002). it will be important to try to replicate these findings in other samples and with other measures of BPD. Cloninger CR. Ullrich S (2006). Journal of Nervous and Mental Disease 184. 579–582. Twin Research and Human Genetics 9. Classical twin studies and beyond. Distel MA. Posthuma D. 67–74. Brook JS (1996). Willemsen G (2006). although our findings were consistent across three samples. Factor analysis and AIC. Twinfamily database for behavior genetics and genomics studies (NWO 480-04-004) . Spinozapremie (NWO/SPI 56-464-14192) . Becker DF. 39–47. A psychobiological model of temperament and character. Acknowledgements The present study was supported by : Borderline Personality Disorder Research Foundation . DSM-IV axis II comorbidity with borderline personality disorder in monolingual Hispanic psychiatric outpatients. Yang M. Derom R (2005). McGlashan TH (1996). Professional Manual : Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI). Jackson HJ. genetically influenced. Costa PT. de Geus EJC. Nyholt DR. Boomsma DI. Boomsma DI. Childhood antecedents of adolescent personality disorders. Derom CA. Baron M. 348–353. Diagnostic and Statistical Manual of Mental Disorders. McGlashan TH (2002). Lord S (1985). Polderman TJ. American Psychiatric Press : Arlington. Gender differences in personality disorders in psychiatrically hospitalized young adults. several other lines of future research on BPD are suggested. Luty SE (1999). Carter JD. 927–934. Stroet T. Mulder EJ. Current overview of the borderline diagnosis. Vink JM. Trull TJ. 324–330. Derom C. 975–990. Ligthart L. Willemsen G. 907–913. Bates GW. Golomb M. Kupper NH. G. Diagnosing personality disorders in . factors that could be used in future aetiological studies. Sullivan PF. Peltonen L (2002a). 317–332. 5–11. Whiteside HL. Rosenbaum JF (1995). 427–430. References Akaike H (1987). Psychometrika 52. Taylor and Francis : Oxford. van Beijsterveldt TC. British Journal of Psychiatry 188. van Beijsterveld CEM.Heritability of borderline personality disorder features In addition. 2011–2016. Cohen P. Personality. Center for Neurogenomics and Cognitive Research . our results and future studies using the PAI-BOR may aid in the evaluation of endophenotypes that have been proposed for this disorder. 2nd edn (ed. Finally. Bernstein DP. Stubbe JH. 4th edn. Vlietinck RF. Prevalence and correlates of personality disorder in Great Britain. Coid J. Derom RM (2006). revised. Blickstein). 754–757. Rudd RP. Edell WS. Thiery EW. Becker DF. I. Journal of Nervous and Mental Disease 190. Boomsma DI (2007). Gruen R. Journal of Clinical Psychiatry 48. 131–139. FL. Journal of Personality Disorders 17. McCrae RR (1992). Joyce PR. Gender differences in personality disorders. including laboratory tasks. Bezirganian S. First. Gestation and Perinatal Outcome. Roberts A. Riese H. further phenotypic and genetic analyses of PAI-BOR items may be informative as these analyses may point to cohesive. APA (2000). Grilo CM. Hudziak JJ. Gender differences in the frequency of personality disorders in depressed outpatients. Bell R. Center for Medical Systems Biology (NWO Genomics) . Twin Research and Human Genetics 9. Vink JM. Assessment 4. suggesting no significant cultural role in BPD features. Derks EM. Rietveld MJ. 423–431. Bartels M. L. Declaration of Interest None. Nature Reviews Genetics 3. Skodol A. The East Flanders prospective twin survey. The East Flanders Prospective Twin Survey (EFPTS). 849–857. 872–882. Willemsen GA. Second. Bartels M. Stubbe JH. Familial transmission of schizotypal and borderline personality disorders. Beem AL. Fava M. Przybeck TR (1993). Archives of General Psychiatry 50. Twin Research 5. Comorbidity of borderline personality disorder with other personality disorders in hospitalized adolescents and adults. 1227 Boomsma DI. DAPP-BQ : factor structure and relations to personality disorder symptoms in a non-clinical sample. Busjahn A. Posthuma D. health and lifestyle in a questionnaire family study : a comparison between highly cooperative and less cooperative families. van den Berg M. van Baal GC (2002b). Fryns JP. Svrakic DM. American Journal of Psychiatry 157. Edwards J (1991). Genetics of personality disorders : perspectives from personality and psychopathology research. 27–32. Twin Research and Human Genetics 9. Distel et al. Johnson JG. Vernon PA. A framework for integrating dimensional and categorical classifications of personality disorder. Kluwer Academic Publishers : Dordrecht. Heritability of personality disorder traits : a twin study. Genetic covariation between neuroticism and the symptoms of anxiety and depression. Morey LC (1991). 194–197. Springer Publishing Company : New York. 936–950. 265–275. Journal of Abnormal Psychology 97. S. Stout RL (2000). 450–456. Jang KL. 577–591. Vernon PA (1993). Heritability of the big five personality dimensions and their facets : a twin study. 314–321. Biological Psychiatry 51. Vlietinck R. pp. Borderline pathology and the personality assessment . Journal of Personality 64. 199–224. A. Genetic and environmental contributions to dimensions of personality disorder. Brook JS (2000). Derom C. Gunderson JG. Jang KL. Keller MC. Livesley WJ. Brown R. Clinical Psychology Review 23. The categorical representation of personality disorder : a cluster analysis of DSM-III-R personality features. Constantine D. Jang KL. Nestadt G (2002). Meares R (2007). Gerull F. Livesley WJ. 1055–1085. Paris J. The genetic basis of personality at different ages : a cross-sectional twin study. 401–425. Gunderson JG. Factorial structure of the German version of the dimensional assessment of personality pathology – basic questionnaire in clinical and nonclinical samples. The five-factor model and personality disorder empirical literature : a meta-analytic review. Brown CH. Harley R (2007). Livesley WJ (1987). Harris JA. 291–300. Loos R. psychic pain. The concurrent validity of three self-report measures of borderline personality. 167–175. Steinmeyer E (2001). Rather C. Journal of Psychopathology and Behavioral Assessment 15. Livesley WJ. Jacobo MC. Cohen P. Oldham JM. 728–732. Henderson AS (1984). Journal of Personality Disorders 15. 772–777. Zanarini MC. Morey LC. Archives of General Psychiatry 55. Jang KL. Strack). In Differentiating Normal and Abnormal Personality. Twin Research 1. Baity MR. Prevalence and correlates of personality disorders in a community sample. Cardon L (1992). Skodol AE. Saulsman LM. Xie G. self-harm. Heath AC. Familial aggregation of adolescent personality disorders. On the probability of dizygotic twins being concordant for two alleles at multiple polymorphic loci. 2nd edn (ed. Kasen S. VA. Nigg JT. Acta Psychiatrica Scandinavica 102. Stevenson J. Costa PT. Phenotypic and genetic structure of traits delineating personality disorder. Jardine R. Tulis EH (1982). 1826–1831. Vernon PA. Morey LC. Journal of Personality Disorders 21. Tomarken AJ (1993). Loranger AW. Virginia Commonwealth University : Richmond. psychiatric inpatients. Jang KL (2004). 941–948. 438–444. Genetic Epidemiology 1. Harm avoidance. Assessment 8. Vernon PA (1996a). Acta Psychiatrica Scandinavica 94. Stein MB. Martin NG (2005). Shea MT. Comprehensive Psychiatry 28. Derom R (1998). Psychological Bulletin 115. Neale MC. 256–264. Trait and behavioral prototypes of personality disorder. Hilsenroth MJ (2007). Livesley WJ (2007). Concurrent validity of personality assessment inventory scales in patients seeking dialectical behaviour therapy. 74–80. Brent DA. Nowlis D (1987). Goldsmith HH (1994). Widespread evidence for non-additive genetic variation in Cloninger’s and Eysenck’s personality dimensions using a twin plus sibling design. Twin Research 7. Eaton WW. Age-related change in personality disorder trait levels between early adolescence and adulthood : a community-based longitudinal investigation. Coventry WL. 206–213. American Journal of Psychiatry 150. Jackson DN (1996c). Boker SM. Grilo CM. Vernon PA (1996b). American Journal of Psychiatry 143. Acta Psychiatrica Scandinavica 83. White T (1995). Blais MA. Mx : Statistical Modeling. Livesley WJ. and personality structure. Livesley WJ. A systematic approach to the delineation of personality disorders. American Journal of Psychiatry 144. Jang KL. Samuels J. Siever LJ (2002). Personality and Individual Differences 21. Archives of General Psychiatry 39. Page AC (2004). Pfohl B. comorbidity. Johnson BA. Widiger TA. Acta Psychiatrica Scandinavica 102. 346–380. Pukrop R. Steinbring I. Korner A. The Personality Assessment Inventory : Professional Manual. British Journal of Psychiatry 180. Bridge J. Vernon PA (1998). 89–107. Journal of the American Academy of Child and Adolescent Psychiatry 34. Neale MC. Hamagami F. 6th edn. Psychological Assessment Resources : Odessa. Behavior Genetics 35. Comprehensive Psychiatry 48. 303–308. Livesley WJ (2006). Kurtz JE. Matta J. Bienvenu OJ. Connolly J. Gentil I. 530–535. Methodology for Genetic Studies of Twins and Families. The borderline diagnosis I : Psychopathology. The East Flanders prospective twin survey (Belgium) : a populationbased register. Johnson AM. FL. Journal of Personality Assessment 88. Long-term follow-up of borderline patients in a general hospital. Skodol AE. 255–266. The dimensional assessment of personality pathology (DAPP) approach to personality disorder. 536–542. Jackson DN. 299–301. Maes HH (2003). 798–804. McGlashan TH. Pinkster-Aspen JH. 707–721. Use of structured self-report assessment to diagnose borderline personality disorder during major depressive episodes. The collaborative longitudinal personality disorders study : baseline axis I/II and II/II diagnostic co-occurrence. Livesley WJ (1986). Martin NG.1228 M. and the borderline personality : life in a ‘ haunted house’. Skodol AE. Livesley WJ. Kurtz JE. Nyholt DR (2006). Morey LC (1988). A behavior genetic investigation of the relationship between leadership and personality. 795–799. Familial transmission of DSM-III borderline personality disorder. Morey LC (2001). Mattia JI (1999). Trull TJ. Demographic correlates and comorbidity. Willemsen G. Ligthart RS. Boomsma DI (2004). Tragesser SL. Lygren S. Structural relations between borderline personality disorder features and putative etiological correlates. Psychological Medicine 35. Dimensional models of personality disorder : Diagnostic and Statistical Manual of Mental Disorders Fifth Edition and beyond. Torgersen S. Comprehensive Psychiatry 41. Stubbe JH. Archives of General Psychiatry 58. DSM-III personality disorder diagnoses in a nonpatient sample. Kringlen E. European Journal of Epidemiology 19. 52–56. Reynolds V (1998). Oien PA. Archives of General Psychiatry 46. Sickel AE. Journal of Personality Assessment 88. 1015–1021. Zimmerman M. Levin A. Twin Research and Human Genetics 8. A twin study of personality disorders. 416–425. Borderline psychopathology in the first-degree relatives of borderline and axis II comparison probands. Heritability of life satisfaction in adults : a twin-family study. Zanarini MC. Posthuma D. Gunderson JG (2004). Trull TJ (2007). Edvardsen J. Boomsma DI. Guthrie P (1990). 682–689. Genetic and nosological aspects of schizotypal and borderline personality disorders. Epidemiology of borderline personality disorder. Dirkzwager HJ. Trull TJ (1995). Archives of General Psychiatry 41. Zanarini MC. Plate tectonics in the classification of personality disorder : shifting to a dimensional model. Torgersen S (1984). Journal of Personality Disorders 18. The Fate of Borderline Patients : Successful Outcome and Psychiatric Practice. Boomsma DI (2005). Weissman MM (1991). Coryell W (1989). 71–83. Yong L. 1581–1588. Journal of Abnormal Psychology 99. American Psychologist 62. Guilford Press : New York. Middeldorp CM. Stone MH (1990). Stubbe JH. Widiger TA. Hennen J. Zimmerman M. American Journal of Psychiatry 155. 1229 Vink JM. Onstad S. Borderline personality disorder features in nonclinical young adults : 1. de Geus EJ. Skre I. Widiger TA. Posthuma D. Dubo ED. Torgersen S. 40–48. NY. 81–89. . Axis I comorbidity of borderline personality disorder. Hudson JI. Kringlen E (2000). 1733–1739. Willemsen G. 623–630. de Geus EJC (2005). Reich DB. 312–317. Categorical versus dimensional status of borderline personality disorder. Schwartz-Mette R (2007). Baas KD. Raviola G. Current Opinion in Psychiatry 20. Widiger TA. Axis I diagnostic comorbidity and borderline personality disorder. Solhan M. 471–481. Trikha A. Estimating non-response bias in family studies : application to mental health and lifestyle. Identification and validation. 546–554. 439–447. DC) 42. 33–41. 590–596. Frankenburg FR. 245–252. Trull TJ. Journal of Abnormal Psychology 110.Heritability of borderline personality disorder features inventory (PAI) : an evaluation of criterion and concurrent validity. The prevalence of personality disorders in a community sample. Psychological Assessment 7. A twin study. Comprehensive Psychiatry 40. Hospital and Community Psychiatry (Washington. Environmental factors determine where the Dutch live : results from the Netherlands Twin Register. Trull TJ (2001). Frankenburg FR. Cramer V (2001). Tambs K.