4.7 Article

Assessing the heritability of anorexia nervosa symptoms using a marginal maximal likelihood approach

期刊

PSYCHOLOGICAL MEDICINE
卷 39, 期 3, 页码 463-473

出版社

CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0033291708003310

关键词

Anorexia nervosa; genetic; item-factor model

资金

  1. National Institutes of Health Grants [MH-068520, MH-20030, MH66117-05, MH-65322, MH-068643]
  2. Norwegian Research Council, the Norwegian Foundation for Health and Rehabilitation
  3. European Commission [QLG2-CT-2002-01254]

向作者/读者索取更多资源

Background. Assessment of eating disorders at the symptom level can facilitate the refinement of phenotypes. We examined genetic and environmental contributions to liability to anorexia nervosa (AN) symptoms in a population-based twin sample using a genetic common pathway model. Method. Participants were from the Norwegian Institute of Public Health Twin Panel (NIPHTP) and included all female monozygotic (MZ; 448 complete pairs and four singletons) and dizygotic (DZ; 263 complete pairs and four singletons) twins who completed the Composite International Diagnostic Interview (CIDI) assessing DSM-IV Axis I and ICD-10 criteria. Responses to items assessing AN symptoms were included in a model fitted using the marginal maximum likelihood (MML) approach. Results. Heritability of the overall AN diagnosis was moderate [a(2)=0.22, 95%, confidence interval (CI) 0.0-0.50] whereas heritabilities of the specific items varied. Heritability estimates for weight loss items were moderate (a(2) =0.31-0.34) and items assessing weight concern when at a low weight were smaller (0.18-0.29). Additive genetic factors contributed little to the variance of amenorrhea, which was most strongly influenced by unshared environment (a(2)=0.16, e(2)=0.71). Conclusions. AN symptoms are differentially heritable. Specific criteria such as those related to body weight and weight loss history represent more biologically driven potential endophenotypes or liability indices. The results regarding weight concern differ somewhat from those of previous studies, highlighting the importance of assessing genetic and environmental influences on variance of traits within specific subgroups of interest.

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