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No. 3 (2026)

ORIRGINAL RESEARCH

A model for predicting drug-induced body weight gain based on hematological coefficients of inflammation in mentally ill patients

https://doi.org/10.48612/psyph/gm2x-u2k8-2kpu

Published 2026-10-02

  • M.V. Ivanov
    • ,
  • A.A. Moritz
    • ,
  • M.G. Yanushko
    • ,
  • M.V. Shamanina
    • ,
  • D.V. Bobrik
    • ,
  • D.S. Shumskaia
    • ,
  • K.A. Lukmanova
    • ,
  • M.Y. Popov
    • ,
  • N.B. Lutova

M.V. Ivanov
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

A.A. Moritz
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

M.G. Yanushko
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

M.V. Shamanina
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

D.V. Bobrik
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

D.S. Shumskaia
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

K.A. Lukmanova
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

M.Y. Popov
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

N.B. Lutova
V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology

Abstract

Background. Antipsychotic-induced weight gain reduces treatment adherence and elevates metabolic risks, necessitating the search for accessible and reliable
predictors of this condition.

The Aim — to develop a mathematical model for predicting clinically significant weight gain (≥ 3 % from baseline) using hematological indices of systemic inflammation (HISIs).

Materials and Methods. A 4-week prospective study was conducted in 104 patients with mental disorders. NLR, PLR, MLR, and SII were calculated, along with
integrated factors reflecting innate (IFI) and adaptive (AFI) immune responses. Associations between HISIs and weight gain ≥ 3 % were assessed using Firth-corrected
logistic regression adjusted for clinical covariates. A predictive model based on baseline BMI and AFI was developed, and its discriminative performance was evaluated
using ROC analysis.

Results. Weight gain ≥ 3 % was observed in 24.0 % of patients. Patients who gained weight had lower baseline NLR, MLR, SII, and IFI values and higher AFI values.
The most robust associations in adjusted models were found for MLR and AFI. The model including baseline BMI and AFI demonstrated acceptable discriminative
performance (AUC = 0.753), with a sensitivity of 56.0 % and a specificity of 85.9 %.

Conclusion. Baseline HISIs were associated with the risk of early weight gain during antipsychotic treatment. The model based on baseline BMI and AFI demonstrated
acceptable predictive performance; however, these findings require confirmation in independent samples.

Keywords

schizophrenia, antipsychotics, systemic inflammation, metabolic disorders, weight gain, hematological indices of inflammation

PDF (Русский)

References

  1. Биологические методы терапии психических расстройств. Доказательная медицина – клинической практике / под ред. С.Н. Мосолова. – М.: Социально-политическая мысль, 2012. – 1073 с.
  2. Федеральное руководство по использованию лекарственных средств (формулярная система) / под ред. А.Г. Чучалина. – Вып. XII. – М.: Человек и лекарство, 2011. – 956 с.
  3. Незнанов Н.Г., Мосолов С.Н., Иванов М.В. Психофармакотерапия // Психиатрия: национальное руководство / под ред. Н.Г. Незнанова, Ю.А. Александровского. – М.: ГЭОТАР-Медиа, 2018. – С. 820–893.
  4. Корнетова Е.Г., Галкин С.А., Меднова В.А. и др. Метаболические последствия антипсихотической терапии: мнение психиатров // Современная терапия психических расстройств. – 2025. – № 3. – С. 23–28. – https://doi.org/10.48612/psyph/6rr5-31p2-nbp2
  5. Мосолов С.Н., Рывкин П.В., Сердитов О.В. и др. Метаболические побочные эффекты современной антипсихотической фармакотерапии // Социальная и клиническая психиатрия. – 2008. – № 18 (3). – С. 75–90.
  6. Huhn M., Nikolakopoulou A., Schneider-Thoma J. et al. Comparative efficacy and tolerability of 32 oral antipsychotics for the acute treatment of adults with multi-episode schizophrenia: A systematic review and network meta-analysis // The Lancet. – 2019. – Vol. 394 (10202). – Pp. 939–951. – https://doi.org/10.1016/S0140-6736(19)31135-3
  7. Pillinger T., McCutcheon R.A., Vano L. et al. Comparative effects of 18 antipsychotics on metabolic function in patients with schizophrenia, predictors of metabolic dysregulation, and association with psychopathology: A systematic review and network meta-analysis // The Lancet Psychiatry. – 2020. – Vol. 7 (1). – Pp. 64–77. – https://doi.org/10.1016/S2215-0366(19)30416-X
  8. De R., Smith E.C.C., Navagnanavel J. et al. The impact of weight gain on antipsychotic nonadherence or discontinuation: A systematic review and meta-analysis // Acta Psychiatrica Scandinavica. – 2025. – Vol. 151 (2). – Pp. 109–126. – https://doi.org/10.1111/acps.13758
  9. Semahegn A., Torpey K., Manu A. et al. Psychotropic medication non-adherence and its associated factors among patients with major psychiatric disorders: a systematic review and meta-analysis // Systematic Reviews. – 2020. – Vol. 9 (1). – Art. 17. – https://doi.org/10.1186/s13643-020-1274-3
  10. Сосин Д.Н., Хасанова А.К., Мощевитин С.Ю., Мосолов С.Н. Фармакогенетические предикторы метаболических нарушений при применении клозапина // Современная терапия психических расстройств. – 2024. – № 4. – С. 30–40. – https://doi.org/10.21265/PSYPH.2024.88.88.004
  11. Моритц А.А., Рерих Д.С., Иванов М.В. Перспективы применения биоимпедансометрии в мониторинге метаболических нарушений у больных шизофренией // Современная терапия психических расстройств. – 2025. – № 3. – С. 44–52. – https://doi.org/10.48612/psyph/787x-859p-1v7v
  12. Segarceanu L.M., Zanfir A.G., Minca D.G., Trifu S. Evaluation of inflammatory markers in perception disorders in major psychiatric pathology // International Journal of Molecular Sciences. – 2025. – Vol. 26 (19). – Art. 9299. – https://doi.org/10.3390/ijms26199299
  13. Lee S.Y., Chen S.L., Chang Y.H. et al. Inflammation’s association with metabolic profiles before and after a twelve-week clinical trial in drug-naïve patients with bipolar II disorder // PLoS One. – 2013. – Vol. 8 (6). – Art. e66847. – https://doi.org/10.1371/journal.pone.0066847
  14. Герасимчук Е.С., Моритц А.А., Иванов М.В., Сорокин М.Ю., Лутова Н.Б. Разработка взвешенных факторов системного воспаления на основе гематологических коэффициентов у пациентов с психическими расстройствами // Сибирский вестник психиатрии и наркологии. – 2025. – № 4 (129). – С. 13–22. – https://doi.org/10.26617/1810-3111-2025-4(129)-13-22
  15. Моритц А.А., Иванов М.В. Роль гематологических индексов воспаления в оценке эффективности и безопасности антипсихотической терапии при шизофрении // Социальная и клиническая психиатрия. – 2025. – Т. 35 (4). – С. 15–22.
  16. Sapienza J., Agostoni G., Repaci F. et al. Metabolic syndrome and schizophrenia: adding a piece to the interplay between the kynurenine pathway and inflammation // Metabolites. – 2025. – Vol. 15 (3). – Art. 176. – https://doi.org/10.3390/metabo15030176
  17. Prestwood T.R., Asgariroozbehani R., Wu S. et al. Roles of inflammation in intrinsic pathophysiology and antipsychotic drug-induced metabolic disturbances of schizophrenia // Behavioural Brain Research. – 2021. – Vol. 402. – Art. 113101. – https://doi.org/10.1016/j.bbr.2020.113101
  18. Maravi P. et al. Relationship of PLR, NLR and LMR with metabolic syndrome in schizophrenia // Journal of Clinical and Diagnostic Research. – 2023. – Vol. 17 (2). – Pp. VC06–VC11. – https://doi.org/10.7860/JCDR/2023/58357.17551
  19. Özdin S., Böke Ö. Neutrophil/lymphocyte, platelet/lymphocyte and monocyte/lymphocyte ratios in different stages of schizophrenia // Psychiatry Research. – 2019. – Vol. 271. – Pp. 131–135. – https://doi.org/10.1016/j.psychres.2018.11.043
  20. Šagud M., Madžarac Z., Nediс Erjavec G. et al. The associations of neutrophil-lymphocyte, platelet–lymphocyte, monocyte–lymphocyte ratios and immune-inflammation index with negative symptoms in patients with schizophrenia // Biomolecules. – 2023. – Vol. 13 (2). – Art. 297. – https://doi.org/10.3390/biom13020297
  21. Wang Q., Wang Y., Xu D. The roles of T cells in obese adipose tissue inflammation // Adipocyte. – 2021. – Vol. 10 (1). – Pp. 435–445. – https://doi.org/10.1080/21623945.2021.1965314
  22. Fitzgerald I., Sahm L.J., Byrne A. et al. Predicting antipsychotic-induced weight gain in first episode psychosis - a field-wide systematic review and meta-analysis of non-genetic prognostic factors // European Psychiatry. – 2023. – Vol. 66 (1). – Art. e42. – https://doi.org/10.1192/j.eurpsy.2023.2417
  23. Горбунова А.П., Рукавишников Г.В., Касьянов Е.Д., Мазо Г.Э. Роль гематологических коэффициентов системного воспаления в диагностике и оценке риска аффективных расстройств // Обозрение психиатрии и медицинской психологии имени В.М. Бехтерева. – 2024. – Т. 58 (1). – С. 47–55. – https://doi.org/10.31363/2313-7053-2024-794

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