UCL Great Ormond Street Institute of Child Health


Great Ormond Street Institute of Child Health


Risk and resilience for eating disorders: a longitudinal study

Supervisors: Dr Nadia Micali, Professor Bianca De Stavola

Eating Disorders (ED) such as anorexia nervosa (AN), bulimia nervosa (BN), and binge-eating disorder (BED) are debilitating and often chronic disorders, with impact on an individuals’ social, physical, and psychological well-being.1,2, ED affect a large proportion of adolescents, between 10-15%; although females are at higher risk of developing AN and BN, males do develop ED, and BED is equally present in males and females.3,4 ED typically peak in onset in adolescence and young adulthood (between ages 15-25), hence occurring at a crucial time of heightened brain, body and social development. There is evidence that ED are increasing in incidence in middle and high-income countries, and that age of onset is decreasing (younger onset) in Europe. ED are one of the leading causes of chronic disability in young women,5 Although effective treatments for ED are available, we still cannot predict who will develop an ED or who will have a good prognosis. Much progress has been made in genomics and neurobiology in the last few years; but this has resulted in few breakthroughs in clinical care for patients with ED. The availability of big data, novel statistical methods to analyse them, are an ideal and timely foundation to improve our understanding of risk and resilience and the way we identify, diagnose, and treat individuals with ED.Although we know that some youth (i.e., high-risk group) will go onto develop ED, little is known about which biological, psychological, and social factors will trigger the onset of illness, This project focuses on susceptibility and resilience to ED across genes, environment, and neurobiology.

This project is an offshoot of a larger programme grant already funded, the programme grant does not fund a PhD student however.

1.  Characterising resilience to ED at a population-level.
2. Identify brain markers of genetic risk for ED.
3. To determine whether the same factors that predict onset of ED behaviours (appearance concerns, dieting), also predict progression from high-risk behaviours into ED.

Aim1: For this objective prospectively collected data from two longitudinal cohorts will be used: ALSPAC (n~8,000), Generation R (n~6,000). Both have investigated children from prior to birth (ALSPAC/Generation R), to late adolescence/adulthood (16yrs for Generation R, 30 yrs for ALSPAC). All cohorts have collected prospective data on variables of interest to this study and data on ED diagnosis on participants (N Micali has led this data collection in ALSPAC and supported it in Generation R). Data analyses will be carried out in steps; data will be analysed separately in each cohort prior to carrying out a meta-regression across all cohorts. All data analyses will take into account biological sex, and stratify by sex if there is evidence of differences.
Aim 2:  data from a sub-sample of Generation R children who received brain MRI scans at 9/11 years of age (n=4,245) and at 13/16 years of age (n~4,000) will be used. All analyses will take into account biological sex, and stratify by sex if there is evidence of differences. Neuroimaging data were collected using 3 Tesla GE 750 Discovery system in a dedicated child friendly scanner room. Each session comprised high-resolution T1-weighted and resting-state functional MRI (rs-fMRI).
Aim 3: will use a combination of six, well-characterised cohorts: IMAGEN: 2k adolescents from across Europe; ESTRA/STRATIFY: Clinical cohort »500 YP (»23 yrs); Eating Disorders Genetic Initiative (EDGI) Clinical cohort 500+ ppts (16+ yrs). A range of modelling approaches such as latent class growth analyses, mixture growth models to define trajectories of high-risk (e.g. those who transition to full-blown EDs) will be used. Risk models will be built as a second step.

1.  Micali N, Ploubidis G, De Stavola B, Simonoff E, Treasure J. Frequency and patterns of eating disorder symptoms in early adolescence. J Adolesc Health. 2014;54(5):574-581.
2.  Micali N, Solmi F, Horton NJ, et al. Adolescent Eating Disorders Predict Psychiatric, High-Risk Behaviors and Weight Outcomes in Young Adulthood. J Am Acad Child Adolesc Psychiatry. 2015;54(8):652-659 e651.
3.  Field AE, Sonneville KR, Micali N, et al. Prospective association of common eating disorders and adverse outcomes. Pediatrics. 2012;130(2):e289-295.
4.  Calzo JP, Horton NJ, Sonneville KR, et al. Male Eating Disorder Symptom Patterns and Health Correlates From 13 to 26 Years of Age. J Am Acad Child Adolesc Psychiatry. 2016;55(8):693-700 e692.
5.  Keshaviah A, Edkins K, Hastings ER, et al. Re-examining premature mortality in anorexia nervosa: a meta-analysis redux. Compr Psychiatry. 2014;55(8):1773-1784.