Supplementary online information (SI) at the website of Molecular Psychiatry
Title: Gene-environment interaction in anorexia nervosa - relevance of non-shared
environment and the serotonin transporter gene
Correspondence: E-mail: andreas.karwautz@meduniwien.ac.at
Online Supplementary contents
Background
Aims and Hypotheses
Material and methods – procedure, patients, measures, statistics, power
Results
Discussion, limitations and strength
Acknowledgements
Additional references
Table legends
Tables
--BACKGROUND
The interaction between genetic and environmental factors are thought to increase the risk
of several psychiatric disorders (1, 2) including major depression (3, 4), posttraumatic stress
disorder (5, 6), suicidality (7), and schizophrenia (8). Thus, although the 5-HTTLPR
polymorphism in the promoter of the serotonin transporter (SLC6A4) alone has a negligible
or weak impact on the risk of developing depression (9), individuals with the short (S) allele
of this polymorphism are at greater risk for depression (3) or anxiety (10) following stressful
life events. The S-allele has also been associated with an increased emotional reactivity to
1
stressors in the amygdala using imaging genetic techniques (11). Several reports (reviewed
by Uher and McGuffin (12), Munafo et al. (13)) have replicated the initial finding of GxE
between the 5-HTTLPR and stressful life events by Caspi et al. (3). Others, however, have
not, even those having sufficient power, as reviewed in Risch et al. (14). Different selection
(Kendler et al. (15)), and also methodological differences may account for inconsistency.
Uher & McGuffin (12), for example, noted that all studies which failed to replicate the
original findings used self-report questionnaire rather than direct interview measures.
Most molecular genetic studies in the field of eating disorders have focussed on the genetics
of the serotonin and dopamine neurotransmitter systems (16-23). Recent meta-analyses of 8
studies including AN-patients and 7 including BN-patients investigating the serotonin
transporter gene (5-HTTLPR) concluded that there was a significant association with the Sallele (OR=1.41, CI: 1.2-1.66, p<0.001) and SS- and SL-genotype (24): OR=1.42, CI: 1.101.83, p=0.007; (25): OR=1.35; CI: 1.07-1.71; p=0.01 with AN, but no association with BN
(26-29).
The Oxford Risk Factor Interview (ORFI) was developed by Fairburn et al. (30) as a
retrospective measure to ascertain putative eating disorder risk factors. The risk factors
differentiating AN from general psychiatric disorders include high parental demands and
critical comments regarding body shape. Non-shared environmental factors are of particular
interest as twin data suggest that they are highly relevant to aetiology (31-33)).
2
AIMS AND HYPOTHESES
The aim of this study was to examine the role of non-shared environmental risk factors (E),
a genetic polymorphism, the 5-HTTLPR (G), and their interactions (GxE) in a sample of
sister-pairs discordant for AN.
A secondary aim was to assess whether there were differences in AN-subtypes (AN-R vs. ANBP) with respect to the G and E variables.
Our hypotheses, developed from the above reviewed evidence and our pilot work (34), were
that:
(1) Patients with AN will have a higher overall risk factor loading (non-shared or individualspecific environment) than their sisters without a history of an eating disorder.
(2) There will be a main effect of the 5-HTTLPR polymorphism on risk for developing AN.
(3) There will be a gene-by-environment interaction between the 5-HTTLPR and specific
environmental factors such as childhood adverse events in AN.
(4) Patients with binge-purging AN will have different loadings of environmental stressors
than strictly defined restricting AN patients.
3
MATERIAL AND METHODS
Procedure
Three university centres contributed to this study in Vienna (N=74 sister-pairs), London
(N=33 sister-pairs), and Barcelona (N=21 sister-pairs). Recruitment of the sib-pairs via
eating disorder clinics, counselling centers, and self-help-groups, approaching a wide variety
of patients within all treatment settings. The inclusion criteria were that one sister had a
current or lifetime history of AN and that her sister had no history of any eating disorder, the
sisters did not differ in age more than 8 years, and that both sisters (and if younger than 18
years also their parents) gave written informed consent. The protocol was approved by all
local Ethics Committees of the participating organisations. All participants were white
European Caucasians. To rule out possible population stratification or cultural effects,
subjects from each center were compared for age, minimum lifetime BMI, genotype, and
environmental factors, which showed no significant differences (data not shown).
Patients
The mean age when the first persistent eating disorder symptoms occurred (index age (IA),
defined according to Fairburn et al. (30)) was 16.5 (SD=4.2) in the patients. Healthy sisters
were 17.3 years (SD=5.9) at that time point. Patients and controls differed significantly on
current BMI (mean=18.4 [SD=2.3] vs. 22.6 [SD=7.9]), lowest ever BMI (mean=14.4
[SD=2.0] vs. 22.4 [SD=4.6]), and highest ever BMI (mean=21.2 [SD=2.8] vs. 24.8
[SD=1.0] kg/m2). AN-patients and healthy sisters did not differ in employment and
educational level: 50% were employed, 45% were students, and 6% were on health or
social benefit.
Measures
Non-shared environment
4
According to Turkheimer and Waldron (35), non-shared experiences occur as objective and
effective environment. Differential treatment by parents, disruptive events, specific peergroup experiences, and disparate school experiences are “objective non-shared
environmental factors”. Following this classification method, we had 21 variables as
“objective non-shared environmental factors” (see supplemental table 1).
Diagnostic procedure
A European adaptation of the LIFE (Longitudinal Interval Follow-up Evaluation), the EATAETI was used to measure lifetime eating disorder history (36-37). This involved constructing
anchor points and time lines for the development of eating disorder symptoms. The method
is described in detail in Anderluh et al. (37).
The patients fulfilled the criteria for AN according to DSM-IV (38). Their sisters did not fulfil
criteria for any eating disorder at any point in their lifetime. AN-R was strictly defined using a
three year criterion of presence of restricting behaviour and absence of purging or bingeing
behaviour during this period (according to the Price foundation studies, e.g., (39)).
The Oxford Risk Factor Interview for Eating Disorders (ORFI) is a semi-structured
investigator-based interview designed to examine the specific risk factors associated with an
eating disorder (30). The areas (40-42) covered by the ORFI and their combination within 4
domains can be found in the supplemementary Table 1.
The interview starts with establishing a time-line with index age as the end point for the
proband and sister, to ensure that the (risk-) variable of interest preceded the outcome (4142). Inter-rater reliability is good (kappa=0.66, SD=0.17) (30). The environmental variables
(N=21) were then combined a priori into 4 domains of environment called parenting style
(E1; N=6), disruptive events (E2; N=3), interpersonal problems (E3; N=6), and dieting
5
environment (E4; N=6). In order to be comparable with other studies (30, 34, 42), we used
all the environmental variables reported in these studies. We did not include in this analysis
all personality-related variables from the ORFI as they are not measuring environments. In
Table 1, the distribution of risk factors in the patients and the sister without an eating
disorder history is shown.
Genetics
Blood samples or cheek cell swabs were collected from both sisters and their parents to
prepare genomic DNA by established procedures (for whole blood, Nucleon BACC3 [GE
Healthcare Life Sciences, UK] or for cheek swabs as described by Freeman et al. (43)). The
polymorphism in the promoter region of the SERT (5-HTTLPR) was genotyped by standard
methods as previously described (44).
Statistical Analyses
Diagnostic variables, age, BMI and genotype distribution were compared across sib-pairs
using paired t-tests and Pearson 2-tests. Individual environmental risk variables were
compared using McNemar-tests for paired samples (two-tailed). Clinical variables, genotype
frequencies, and frequencies of environmental factors in the three recruiting centers were
compared using ANOVAs and Pearson 2-tests. Differences of environmental and clinical
factors between the subtypes of AN were calculated using U-tests and t-tests.
Because of the case-sibling design, conditional logistic regression was used to assess the
association between AN, genotype, and environmental factors (operationalized in the
statistical software package R (45) by means of a Cox proportional hazards regression
model). The dependent variable was lifetime diagnosis of AN (AN-R or AN-BP). 5-HTTLPR
and non-shared environmental risk factors were used as predictor variables. The 5-HTTLPR
genotype (LL, LS, or SS) was coded 0 for LL, 1 for LS and 2 for SS. Environmental
6
subdomains were coded dependent on the maximum possible number of risk factors (Table
1) and the observed frequencies as: 0, 1, 2 risk factor present (subdomain E2), and 0, 1,
2, 3, or ≥4 risk factors present (subdomains E1, E3, E4). Environmental risk factors were
treated as continuous variables, assuming a constant linear increase of risk with increasing
number of risk factors, using robust coefficient-variance estimates. The correlations of
genetic and environmental factors between siblings were taken into account by stratifying on
family (i.e., modelling correlation between sisters by means of a fixed effect of family
assuming homogeneity among the sisters except for the included non-shared environmental
and genetic factors).
Model selection began with the full model (all main and GxE-interaction effects), and nonsignificant interactions were removed stepwise. Model fit was tested using Likelihood Ratio
tests (LR-tests), Wald tests, variance explained, and the Akaike Information Criterion (AIC)
(46). The most parsimonious model, i.e., the model that best explains the data with a
minimum of free parameters and, therefore, is the preferred model, has the lowest AIC
value. Schoenfeld residuals were examined to assess overall fit of the final model.
To test the assumption of linear increase of risk, the resulting model was fitted to the data
treating environmental risk factors as categorical variables using dummy coding. Results
were very similar for both methods, suggesting that the assumption of a linear increase is a
good approximation; due to the great number of model parameters for the categorical case,
results of the continuous variant will be presented to increase readability.
Furthermore, an additional random effect for family was considered (extending the model by
an additional random effects term = frailty-model (47)). The overall α was set to 0.05,
resulting in a significance level of α=0.0071 for the individual tests. All necessary information
was available from 108 sister-pairs.
7
Power analysis
Power analysis was conducted a priori using the program Quanto accounting for correlation
of genes in siblings (http://hydra.usc.edu/gxe/) with the following assumptions: (i) a logadditive inheritance model and a population frequency of the risk allele s = 0.45 resulting
under Hardy-Weinberg equilibrium in genotype frequencies LL=0.3025, LS=0.495,
and SS=0.2025; (ii) a population prevalence for AN of 0.7%; (iii) a relative risk for genotype
LS of 1.5 and of 2.25 for SS carriers, (iv) a continuous environmental factor with standard
deviation=0.7 and a patient-sibling correlation of r=0.6 assuming that the disease odds ratio
increases by a factor of 1.1 per unit, and α=0.05. For the given sample size of N=108 sisterpairs, odds-ratios of 2.0 for exposed LS-genotypes and of 3.65 for exposed SS-genotypes
(GxE) respectively, were necessary to reach a power of 0.83.
8
RESULTS
Comparison of sister groups regarding environmental risk factors
--Table 1 about here
--The AN-patients differed significantly in their experiences during development from their
sisters without an eating disorder history in 5 out of 21 variables (Table 1). They
experienced more parental control (E1: parenting style), more significant life events (E2:
disruptive events), more often had no male friends (E3: interpersonal problems), and were
subject to higher levels of critical comments regarding shape, weight, and appearance by
family or peers (E4: dieting environment).
Genotype frequencies (Table 2)
-Table 2 about here
--The distributions of genotypes did not differ between the ill and the healthy sisters
(2=0.239, df=2, p=0.887). The genotype distribution was in Hardy-Weinberg-Equilibrium
(2=1.15; expected vs. observed number of LL homozygotes: 42.24 vs. 45; heterozygotes
(LS): 55.52 vs. 50; SS homozygotes: 18.24 vs. 21). The genotype distribution in our patients
and controls was similar to that reported in the group of Caucasian samples in a recent
meta-analysis (e.g., LL: 32%, LS: 49%, SS: 19% (48)). As expected, there was a significant
association between the genotypes of the two sisters within each sib-pair (2=23.87, df=4,
p<0.001).
Comparing the three genotype groups regarding total number of environmental
risk factors (Table 3)
9
--Table 3 about here
--No significant differences for the three genotype groups were found for total number of risk
factors in the healthy sisters (F[2,105]=0.46, p=0.63) and in the patients (F[2,110]=0.49,
p=0.62). Further, in patients no significant differences were found regarding diagnosis
(F[1,110]=0.94, p=0.34) and genotype x diagnosis interaction (F[2,110]=0.87, p=0.42). In
addition, number of risk factors in all subdomains did not significantly differ in the sisters
with AN regarding to genotypes (Kruskal-Wallis tests; all p-values >0.23).
Modelling the risk for AN (figure 1, Table 4)
The best-fit conditional logistic regression model (robust model) included significant main
effects for disruptive events (p=0.015), interpersonal problems (p=0.019) and dieting
environment (p<0.0001). Higher levels in these variables independently of the genotype
increased the risk for AN. The risk for a female with one disruptive event to be the AN-sister
was 1.68 fold compared with the risk of a female with no disruptive event. With regards to
exposure to interpersonal problems or to dieting environment, each additional event
increased the risk 1.49 and 1.59 fold, respectively.
We found significant main effects of SS- and SL-genotype compared with the LL-genotype
reducing the risk for AN (Table 4). Significant interactions were found for genotype x
parenting style. With increasing number of harmful parenting style factors, the risk to be in
the AN-group was more than 2-fold for the SS- than for the LL-genotype (p=0.0041).
This model explained 11.9 % of the variance (maximum possible=48 %), which depends on
the likelihood of the null model and the sample size (Wald test=33.1, df=8, p<0.001; LRtest=24.8, df=8, p=0.0017; AIC=133.2).
10
Considering an additional random effect returned a non significant parameter (2=0.02,
df=0.14, p=0.64).
Assuming a lifetime prevalence for AN of 0.7%, an S-allele frequency of 0.45, using a logadditive model of inheritance, and a continuous environmental variable with SD=1.36
(estimated from the healthy sisters), and a patient-sister correlation of r=0.37 (estimated
from our data), using the resulting coefficients from the robust model, we reached a power
of 0.71 for the LSxE1 interaction and a power of 0.98 for the SSxE1 interaction.
Comparisons between AN-R and AN-BP subtypes
Clinical features and genotype
The subgroups of AN (AN-R: N=58, AN-BP: N=70) did not differ in age at onset of illness
(mean=16.47 years [SD=4.2] vs. 16.54 [SD=4.2]; Mann-Whitney U-Test, z=-0.32,
p=0.748). The duration of illness, however, was significantly longer for the AN-BP group
(mean=4.44 years [SD=5.0] vs. 7.43 [SD=7.5]; z=-3.147, p=0.002). Age of onset and
duration of illness were not significantly different between the three genotypes.
Comparison of AN subtypes regarding environmental risk factors (Table 1)
There were no differences in the total number of experienced environmental factors between
AN-R and AN-BP group (Mann-Whitney-U-Test, p=0.714).
However, the odds ratio of “physical abuse and repeated severe physical abuse” was higher
in the AN-BP group compared with the AN-R group (AN-R: 5 [8.6%] vs. AN-BP: 17 [24.3%];
2=5.47, p=0.019; OR=3.4 [CI: 1.2-9.9]). One variable showed a trend towards a higher
odds for AN-BP: “parental over-involvement” (AN-R: 6 [13.8%] vs. 16 [22.9%]; 2=3.49;
p=0.062; OR=2.6 [CI: 0.9-7.1]).
11
DISCUSSION
The primary aim of this study was to assess non-shared environmental risk factors, the 5HTTLPR polymorphism and putative GxE interactions as risk factors for the development of
AN. Firstly, we found that patients with AN had a higher loading on non-shared risk factors in
particular disruptive events (E2), interpersonal problems (E3), and dieting environmental
factors (E4). Secondly, we found a small significant main effect of the 5-HTTLPR on risk of
AN with SL and SS reducing the risk. Thirdly, we found a significant interaction between the
5-HTTLPR and parenting style (E1), with risk higher for individuals with the SS- and the SLgenotypes compared with those with the LL genotype, as the number of problems with
parenting style increased. In the absence of parenting style environmental risk factors, SSand SL-genotypes were associated with a lower risk for AN.
The secondary aim was to examine whether the environmental risk factors for the two AN
subtypes differed. Patients with binge-purging AN had higher (and different) loadings of
environmental stressors than restricting AN patients. Patients with AN-BP experienced more
“physical abuse” and a trend to higher “parental over-involvement”.
Our results on environmental risk using the Oxford Risk Factor Interview is in accordance
with previous findings using this instrument in AN populations and extends these three
studies by reporting data on both subtypes of AN, showing that these have distinct patterns
of risk (30, 34, 42). Disruptive life events, (e.g., distress by the death of a loved one) in the
year before onset of AN (42), having no male friends, and dieting environment such as
repeated critical comments and teasing about shape, weight, eating and appearance (30,
42) were vulnerability factors for AN.
12
Although we did not find that parenting style had a main effect as had been reported in
some studies (e.g., parental control (42) and distress by parental arguments (30, 42)), we
did find an interaction effect between this risk factor and 5HTTLPR genotype. The finding of
a significant interaction of the 5-HTTLPR polymorphism with parenting style is not totally
consistent with what was found in bulimic disorders, where adverse parenting with insecure
attachment was a risk factor in patients with the relevant genotype (27). Further studies
using similar methodologies with BN samples are needed. An interaction of the dopamine
transporter gene with maternal negative parenting has recently been found (49). This
marker would be of further interest.
We found a significant association between SS- and SL-genotypes and lower risk for AN in
the absence of environmental parenting style stressors. This is of specific interest as recent
meta-analyses (24, 25) showed a low (OR=1.35; CI 1.1-1.71) but significant risk for Scarriers to develop AN. However, none of the genetic studies included in the meta-analyses
investigated environmental factors. Our data, therefore, suggest that those individuals who
carry the S-allele and experience more than 2 environmental stressors are at highest risk,
whereas those who carry the S-allele and experience no environmental stressors are at
lowest risk. In the absence of environmental stressors, this may be detectable as a weak
association since the majority of the population will experience environmental stressors and
mask any protective effect in their absence. This would explain the inconsistencies in the
literature and strongly suggest to include environmental factors of interest in further genetic
studies.
Limitations
Although power calculation indicated good power of the present study, it is well-known that
the power for detecting GxE interactions is limited (50), especially in small samples.
Therefore, a cautious interpretation and replication of our results in an independent sample
13
will be needed. The study design is retrospective, rather than prospective (40, 41). Recall of
developmental events may be inaccurate because, in some cases, extensive time had
elapsed. Environments may be coloured by a search for meaning and the measurement of
the environments was not validated by external perceptions. However, the ORFI interview
probed for the context and behaviourally defined variables in an attempt to minimize these
possible biases. Not all of the sisters will have passed the age of risk of developing an eating
disorder and this would reduce the sensitivity of the study to detect differences. GxE
analyses in the AN-subtypes was not possible due to reasons of power. We used the bi-allelic
genotype of the 5-HTTLPR polymorphism (not the tri-allelic genotype including a functional
single nucleotide polymorphism within the repeats). The lower activity ‘LG’-allele has been
recently described and is an uncommon variant in normal populations (5-8%) and in eating
disorders (about 8%) (51). It is unlikely that our results would differ significantly with the
use of the tri-allelic genotype. Other genetic markers should be included in further studies,
such as coding for serotonin and dopamine related traits. Also a further study including
personality traits as moderators of risk, body weight, and comorbidities also in a sample of
anorexia nervosa patients would be a great next step.
Strengths
The diagnosis of AN was made by rigorous methods, sub-typing was based on a lifetime
approach to symptoms and diagnoses. A validated interview-based instrument was used to
measure a large number of (proximal and distal, acute and also chronically distressing)
environmental risk factors proven to be relevant for the development of mental illness such
as AN. A genetically sensitive discordant sister-pair design was used whereby many shared
genetic and environmental factors were controlled for leaving the focus on non-shared risk
factors. Assessments of environmental issues were blind to genotype.
In conclusion, our study suggests that disruptive events, interpersonal problems, and dieting
environments are non-shared environmental risk factors which act independently of the
14
genotype as measured in this study, whereas parental style increases the risk only in the
63% of the population carrying an S-allele. This has implications for prevention programmes.
Primary prevention could be targeted on features within the domains of disruptive events,
interpersonal problems, and dieting environments which are modifiable, whereas parenting
styles may be of more relevance in secondary prevention or clinical practice.
ACKNOWLEDGEMENTS
The study was supported by the European Commission, Framework 5 research program,
Integrated Project QLK1-CT-1999-00916 “Factors in Healthy Eating” given to the consortium
lead by Prof. J. Treasure and Prof. D. Collier, London.
We are grateful to all sufferers and their sisters volunteering for this study and to Professors
C. Fairburn, B. Davies and H. Doll, Oxford, UK for training in the use of the Oxford Risk
Factor Interview for Eating Disorders. We thank M. de Zwaan for giving us access to a large
database of patients eligible for inclusion, Drs. M. Haidvogl, S. Cejka, and G. Nobis for
interviewing and data entry. We thank P. McCallum for correcting the English text. Prof.
Avshalom Caspi, Duke University, US, and IOP London, UK and R. Uher, PhD, London, UK
have contributed invaluable comments on an earlier draft of the manuscript and gave
detailed methodological advise. CIBEROBN and CIBERESP are both initiatives of ISCIII. AFK
had full access to all of the data in the study and takes responsibility for the integrity of the
data and the accuracy of the data analysis.
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TABLE LEGENDS
Table 1: Environmental risk factors - comparison between AN-patients and their sisters
without an eating problem for each subtype
Table 1: Note:
Distribution of environmental risk factors divided a priori into 4 sub-domains of risk (E1-E4);
comparison between AN-patients and their sisters without an eating problem for each
subtype of AN separately and for the whole group of 128 sib-pairs. Comparison by
McNemar’s tests and regression analyses. Odds Ratio (OR) = r/s; r = number Pat., and s =
number healthy sisters; 95% CI: exp[ln(OR) – 1.96 SE(ln(OR))]; exp[ln(OR) + 1.96
SE(ln(OR))] with SE(ln(OR)) =
rs
, * n.e. : not eligable. Mc Nemar’s tests eliminate
rs
pairs for analyses if both members have a risk factor either present or absent. This does not
allow regression analyses in one variable. IA = index age.
Table 2: Genotype frequencies in both AN subtypes (AN-R, AN-BP), the total AN group and
the healthy sister-controls
Table 2: Note:
For comparison of genotypes and GxE analyses only 108 sister-pairs contributed with
full data sets. HCo = healthy control sisters.
Table 3: Environmental domains: Number of risk factors present (mean (SD))
according to genotype and diagnostic AN subtype
Table 4: Exponential function of the Regression Coefficients (exp(Coeff)), Standard Error
(SE), and 95% Confidence Intervals (CI) for exp(Coeff) for the best-fit model treating
environmental risk factors as continuous variables
20
TABLES
Separate file with 4 tables – supplementaltables.doc
21