Gene-Environment Interaction in Anorexia Nervosa: a Study Including Non-Shared Environment

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 geneCorrespondence: E-mail: [email protected]Online Supplementary contentsBackgroundAims and HypothesesMaterial and methods – procedure, patients, measures, statistics, powerResultsDiscussion, limitations and strengthAcknowledgementsAdditional referencesTable legendsTables---BACKGROUNDThe 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 S- allele (OR=1.41, CI: 1.2-1.66, p<0.001) and SS- and SL-genotype (24): OR=1.42, CI: 1.10-1.83, 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. AN-BP) 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 individual- specific 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 ProcedureThree 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. MeasuresNon-shared environment4 According to Turkheimer and Waldron (35), non-shared experiences occur as objective and effective environment. Differential treatment by parents, disruptive events, specific peer- group 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 procedureA European adaptation of the LIFE (Longitudinal Interval Follow-up Evaluation), the EATAET-I 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 (41-42). 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. GeneticsBlood samples or cheek cell swabs were collected from both sisters and their parents to pre- pare genomic DNA by established procedures (for whole blood, Nucleon BACC3 [GE Health- care 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 AnalysesDiagnostic 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 non- significant 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 analysisPower 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 log- additive 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 sister- pairs, 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 RESULTSComparison 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; LR- test=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 log- additive 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 genotypeThe 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 betweenAN-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 5-HTTLPR 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 SL- genotypes 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, SS- and 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 S- carriers 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.LimitationsAlthough 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.StrengthsThe 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. ACKNOWLEDGEMENTSThe 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.ADDITIONAL REFERENCES1 Wermter AK, Laucht M, Schimmelmann BG, Banaschweski T, Sonuga-Barke EJ, Rietschel M, et al. 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Association of trait-defined, eating-disorder sub-phenotypes with (biallelic and triallelic) 5-HTTLPR variations. J Psychiatr Res 2009; 43: 1086-109419 TABLE LEGENDSTable 1: Environmental risk factors - comparison between AN-patients and their sisters without an eating problem for each subtypeTable 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 r  s SE(ln(OR))] with SE(ln(OR)) = , * 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-controlsTable 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 subtypeTable 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 variables20 TABLESSeparate file with 4 tables – supplementaltables.doc21

Gene-Environment Interaction in Anorexia Nervosa: a Study Including Non-Shared Environment

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