Intriguingly, the differential polygenic signatures were found when deriving subtypes by LCA applied to all endorsed symptoms or by simply coding the direction of change (increase/decrease) in the highly discriminatory(12–16;18) symptoms of appetite and weight. It should be highlighted that while increased appetite/weight almost perfectly predicted LCA-atypical, the decreased appetite/weight→LCA-typical prediction was less accurate, suggesting that other symptoms beyond appetite/weight may be relevant to reliably identify this subtype. This should be carefully evaluated in specifically dedicated diagnostic-accuracy studies. Nevertheless, the possibility of using parsimonious and effective sub-phenotyping strategies may be relevant for large collaborative studies for which symptom-level data necessary to apply more sophisticated data-driven techniques may not be available in all involved cohorts. Moreover, symptom endorsement profiles may be highly variable across cohorts, reflecting differences such as settings (e.g. clinical, population-based), ascertainment (e.g. psychiatric interviews, medical records) or diagnosis timeframe (e.g. lifetime, current). When applying typical/atypical sub-phenotyping strategies an important aspect to consider may be the possible impact of antidepressant medications (AD), some of which may affect weight change and other metabolic disturbances(49). For the current study, previous results
