A person-centred and data-driven approach to phenotyping anorexia nervosa

Area of Science:

• Psychiatry
• Clinical Psychology
• Medical Research

Background:

• Anorexia nervosa (AN) is a severe psychiatric disorder with high mortality and significant heterogeneity.
• Current diagnostic subtypes have limited predictive value for illness trajectory or treatment response.
• Understanding distinct AN phenotypes is essential for improving treatment outcomes.

Purpose of the Study:

• To identify distinct anorexia nervosa (AN) phenotypes within a treatment-seeking sample.
• To investigate how these identified phenotypes differ in their response to standard treatment.

Main Methods:

• Latent profile analysis was used on anthropometric and clinical variables from the TRIANGLE study (n=382).
• Phenotypic subgroups of adult patients with AN or atypical AN were identified.
• Linear mixed models (n=370) analyzed differences in depression, anxiety, stress, work/social impairment, BMI, and ED psychopathology over 18 months.

Main Results:

• Four distinct AN profiles emerged, varying in illness duration and symptom severity.
• High-severity, shorter-duration profiles showed significant improvements across most variables.
• Higher-severity profiles generally demonstrated greater treatment response magnitude than lower-severity profiles, with some exceptions.

Conclusions:

• Prognosis in AN is influenced by multiple interacting factors, not single indicators.
• Subtyping and treatment planning for AN should incorporate psychological, social, and functional complexity.
• Recognizing distinct AN phenotypes is key for effective, individualized treatment strategies.