Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Endocrinol.

Sec. Obesity

This article is part of the Research TopicComparative Perspectives and Translational Models in Eating Behavior: Insights from Animal Models and Human StudiesView all articles

PLASMA OXYTOCIN AND LEPTIN IN RELATION TO DISORDERED EATING: EVIDENCE FROM NON-LINEAR MODELING ACROSS METABOLIC OBESITY PHENOTYPES

Provisionally accepted
Sevara  AnvarovaSevara Anvarova1*Gulchekhra  NarimovaGulchekhra Narimova1Anna  AliyevaAnna Aliyeva1Zamira  KhalimovaZamira Khalimova1Khurshida  NasirovaKhurshida Nasirova2
  • 1Republican specialized scientific practical medical center of Endocrinology named after Turakulov, Tashkent, Uzbekistan
  • 2Tashkent state medical university, Tashkent, Uzbekistan

The final, formatted version of the article will be published soon.

Background Obesity is heterogeneous across metabolic and behavioral dimensions. Oxytocin, a hypothalamic neuropeptide, and leptin, an adiposity signal, have been implicated in appetite and reward, yet their relationships with disordered eating across metabolic obesity phenotypes remain unclear. We examined these associations and evaluated the predictive value of oxytocin alone versus multivariable models. Methods In a cross-sectional cohort of 99 adults, we assessed anthropometry, biochemistry, oxytocin and leptin, and three validated questionnaires (EDE-Q, DEBQ, EBA-O). Participants were classified into four metabolic obesity phenotypes. Group differences used Kruskal–Wallis with Dunn's correction; associations used Spearman correlation and OLS with HC3 robust SEs. Predictive modeling used logistic regression with restricted cubic splines for oxytocin and an elastic-net multivariable model (oxytocin spline + leptin, BMI, waist circumference, HSI, VAI, and a PCA-derived EDE-Q component). Performance was estimated via leakage-free nested cross-validation (outer 5-fold, inner 5-fold) using out-of-fold (OOF) ROC AUC, Brier score, bootstrap CIs, calibration, and decision-curve analysis. Results Oxytocin was lower and leptin higher in metabolically unhealthy obesity (both p<0.01). Oxytocin correlated inversely with disordered-eating severity, while leptin correlated positively. The oxytocin-only spline model achieved OOF AUC 0.87 (95% CI 0.76–0.95; Brier 0.10). The combined elastic-net model achieved OOF AUC 0.97 (95% CI 0.90–1.00; Brier This is a provisional file, not the final typeset article 0.05) and provided significantly better discrimination than oxytocin alone (ΔAUC 0.11, 95% CI 0.01–0.22; p=0.02). Using Youden's index on OOF predictions, the oxytocin-only model's optimal operating probability (0.69) mapped to ~90.5 pg/mL (95% CI 74.8–103.3), yielding sensitivity of 0.94 (0.87–0.99) and specificity of 0.83 (0.70–0.95). Decision-curve analysis showed higher net benefit for multivariable models across clinically relevant thresholds. Conclusion Lower oxytocin is associated with greater disordered-eating severity, but oxytocin is most informative when integrated with metabolic and behavioral markers. A multivariable model substantially improved discrimination and net benefit over oxytocin alone. The ~90.5 pg/mL value is an exploratory operating point rather than a clinical cutoff; external validation and prospective evaluation are needed before translation to practice.

Keywords: oxytocin1, leptin2, disordered eating3, metabolic obesity phenotypes4, splinemodeling5, restricted cubic splines6, roc curve analysis7

Received: 27 Aug 2025; Accepted: 29 Oct 2025.

Copyright: © 2025 Anvarova, Narimova, Aliyeva, Khalimova and Nasirova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Sevara Anvarova, sevaraanvarova243@gmail.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.