This study examined the relative heritability of specific AN symptoms in a large population-based twin sample using an item-factor approach. The overall heritability of AN was moderate, and lower than that obtained in both the only previous study to examine the full AN diagnosis (Bulik et al., 2006
), as well as that found in studies using broader definitions of AN (e.g., Klump et al., 2001
; Kortegaard et al., 2001
; Wade et al., 2000
). However, the current estimate is within the (albeit wide) CI obtained in the Bulik et al. study. The use of sum scores in previous studies (e.g., Bulik et al., 2006
), which assessed contributions to the variance of AN at a diagnostic level, may also account for differing results. Heterogeneity of items assessing a given trait, which is not accounted for in models using sum scores, can bias parameter estimates (Neale et al., 2005
Thus, of particular interest in this study were the symptom-level analyses using the MML method. Items assessing weight loss and weight itself were moderately heritable. Heritability estimates for items assessing weight concern at low weight were somewhat lower, clustering around .25. The amenorrhea item was most strongly influenced by unshared environment. This result further supports the argument that amenorrhea is not a promising endophenotype or liability index for AN, and may be of limited value to the overall diagnosis if we are seeking more biologically valid diagnostic criteria (Bulik et al., 2007
; Pinheiro et al., 2007
Results regarding the influence of weight on self-evaluation differ from those of Reichborn-Kjennerud et al. (2004)
, who found greater support for the influence of shared and unique environmental factors on this construct. However, current results are more consistent with those of Wade and Bulik (2007)
, who found small to moderate heritability estimates for the undue influence of weight and shape concern on self-evaluation. Perhaps some of these differences among studies are related to the varying items used to assess this construct. For example, Reichborn-Kjennerud et al. used a single item, self-report question to assess undue influence, whereas Wade and Bulik used EDE items. In the current study, participants were asked, using a single question, how they felt about themselves when their weight was at its lowest.
Further, we only assessed a specific subgroup of the sample, most notably, those with a low enough BMI to be considered for the AN diagnosis. Specifically, participants had to endorse the gateway items to even be asked about self-evaluation. This is a common problem in large scale epidemiological studies, in which participant burden and fatigue must be considered. In Wade and Bulik’s (2007)
study, all participants completed the EDE. In theirs as well as Reichborn-Kjennerud et al.’s (2004)
investigations, participants did not need a history of low weight to respond to these items assessing undue influence/weight concern. These contrasting results across studies suggest that perhaps genetic and environmental factors operate differently within individuals who are already at a low BMI, compared to the general population. Moreover, it seems important to examine heritability within specific subgroups of interest, as it is possible that heritability estimates obtained at a population level differ from estimates obtained from specific subsets of individuals. Future research should address this possibility.
Current findings also highlight the importance of unshared or unique environmental factors, which contributed significantly to all AN symptoms. These results are similar to of Wade and colleagues (Wade, Bergin, Martin, Gillespie, & Fairburn, 2006
) who found that unshared environmental factors contributed significantly to the number of lifetime eating disordered behaviors. This influence of the unshared environment may reflect individual experiences twins had outside of their family environment that affected their weight-related behaviors, such as comments made by peers, coaches, or other influential people. Future research should examine the interaction of these unique environmental experiences with underlying genetic vulnerabilities. This line of work may help to identify triggering experiences among the subset of the population particularly vulnerable to AN.
Further, it should be noted that, in addition to measuring unshared environmental experiences, the E component of the ACE model captures variance attributable to measurement error. Thus, the relatively higher influence of E found in the current study, compared to others which have evaluated AN at the diagnostic level (e.g., Bulik et al., 2006
; Klump et al., 2001
; Kortegaard et al., 2001
; Wade et al., 2000
) could reflect both measurement error and nonshared environmental experiences. It is not possible to determine exactly what proportion of variance accounted for by E in this study is due to either true unshared experiences or to measurement error. Consequently, it is important for future studies to replicate the current methodology, particularly given that estimates of heritability are sample dependent. For example, previous studies have identified significant developmental differences in the influence of genetic and environmental factors on eating disorder symptoms (e.g., Klump, Burt, McGue, & Iacono, 2007
; Klump et al., 2000
; Silberg & Bulik, 2005
). In addition, studies in other areas (e.g., smoking) have found that birth cohort influences estimates of A, C, and E parameters (e.g., Kendler, Thornton, & Pedersen, 2000
). In sum, no single study can provide a definitive value regarding the heritability of AN that would be applicable to all. Rather, multiple studies such as this one, which examine genetic and environmental influences on specific AN symptoms, can lead to an accumulation of evidence which will facilitate identification of particularly promising targets for intervention and prevention efforts.
Several limitations of this study should be noted. First, the sample included exclusively Norwegian female twins. Thus, it is unclear whether these results are applicable to men, nontwins, or other cultural groups. Further, measurement issues should be considered, particularly the issue of the gateway items. Use of gateway items is helpful in reducing participant burden and response biases due to fatigue; however, because these items, by definition, screen out the majority of the sample, heritability estimates derived from studies using gateway items assess this component of variance among those individuals who have met the screening criteria. These individuals are likely to differ from those in the total population. In addition, the use of gateway items may have led to an underestimate of the number of women affected by AN, because, as Wade (2007)
has noted, AN symptoms are ego-syntonic, and, thus, are likely under-reported by affected individuals. Consequently, our results may not represent the full range of individuals with AN, but may include individuals with more chronic or severe cases. A final measurement limitation is that participants were classified as low weight if their BMI value was <18.5. BMI age and gender-specific percentiles are considered more accurate for individuals under the age of 18 (Cole, Flegal, Nicholls, & Jackson, 2007
); consequently, the current study may have incorrectly classified some individual as underweight whose weight was truly in the low-normal range. However, these same individuals would have had to have met all other AN criteria to be diagnosed with the disorder. Thus, it is unlikely that this decision regarding BMI cutoffs significantly influenced the overall results.
Further, substantial attrition was observed in this sample from the original birth registry through three waves of contact. Detailed analyses of the predictors of non-response across waves will be presented elsewhere (Harris et al, unpublished observations), and suggest that cooperation was predicted by female sex, monozygosity, older age, and higher educational status. Few of the mental or physical health measures showed significant effects. Analyses did not show evidence of changes in the genetic and environmental covariance structure due to recruitment bias for a broad range of mental health indicators. While we cannot be certain that our sample was representative with respect to AN psychopathology, these findings suggest that significant bias is unlikely. Finally, in order to increase statistical power, the measure used in the current study assessed lifetime history of AN. Thus, results may have been influenced by recall bias.
Despite these limitations, this study has several strengths, including the use of a large, population-based sample. Further, use of symptom level modeling provides much richer data that can prove informative to the development of endophenotypes or liability indices (Bulik et al., 2007