Specific metabolic and inflammatory profiles of patients with hyperglycemia in bipolar affective disorder, recurrent depression and schizophrenia: results of a transdiagnostic study

Specific metabolic and inflammatory profiles of patients with hyperglycemia in bipolar affective disorder, recurrent depression and schizophrenia: results of a transdiagnostic study

 

Authors

 

A.O. Kibitov

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation; Federal State Budgetary Educational Institution of Higher Education “First Saint Petersburg State Medical University named after academician I.P. Pavlov” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

D.S. Shumskaia

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

D.V. Pinakhina

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

I.S. Chensky

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

M.G. Yanushko

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

M.Yu. Popov

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

T.V. Zhilyaeva

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

G.E. Mazo

Federal State Budgetary Institution “V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology” of the Ministry of Health of the Russian Federation, St. Petersburg, Russian Federation

 

https://doi.org/10.26617/1810-3111-2025-4(129)-43-56

 

Journal: Siberian Herald of Psychiatry and Addiction Psychiatry. 2025; 4 (129):  43-56.

 

Abstract

Background. High comorbidity of mental disorders and metabolic syndrome (MS) is the main reason for the reduction in life expectancy of psychiatric patients. The search for biomarkers of MS risk is relevant, and hyperglycemia (HG) as a component of MS is a key target for a comparative study of patients with different diagnoses. Objective. To assess the association of HG with MS components, hematological indices of inflammation, and clinical characteristics of patients with bipolar disorder (BD), recurrent depressive disorder (RDD), and schizophrenia (SZ) within the framework of a transdiagnostic approach. Materials and Methods. The study included 153 inpatients, including 84 women (54.9%) and 69 men (45.1%), with bipolar disorder (n=50), RDD (n=38), and SZ (n=65). Socio-demographic, anthropometric, clinical and laboratory data were obtained from medical records. Results.The diagnostic groups did not differ in age, gender, frequency of somatic diseases and individual components of metabolic syndrome and their combinations. In the RDD group, there was a statistically significant (p=0.0447) increased absolute number of lymphocytes compared with the SZ group and a statistically significant (p=0.044) higher inflammation coefficient LHR (lymphocyte to HDL ratio) compared with the BD group. Comparison of subgroups identified by the presence or absence of HG within the diagnostic groups of patients revealed two levels of differences. Patients with HG in all groups had: 1) statistically significantly higher insulin levels: BD (p=0.003), SZ (p=0.013), RDD (p=0.048); 2) statistically significant higher levels of glycated hemoglobin: RDD (p=0.001), SZ (p=0.001), BD (p=0.028). Unique profiles of differences were established in patients with HG: 1) BD: statistically significant higher levels of prolactin (p=0.024) and creatinine (p=0.0069), but lower levels of lymphocytes (p=0.028) and C-reactive protein (p=0.036), older age (p=0.035), later onset of the disease (p=0.023) and first visit to the doctor (p=0.039); 2) RDD: statistically significant higher hemoglobin levels (p=0.02), lower T4 levels (p=0.045), as well as higher BMI (p=0.017) and waist circumference (p=0.041); 3) SZ: no other differences were found except for those common to all groups. Conclusion. The study has shown for the first time that hyperglycemia in patients with bipolar disorder, RDD, and SZ is associated with diagnosis-specific metabolic and inflammatory profiles. The findings confirm the complex bidirectional relationship between mental disorders and metabolic disturbances, emphasizing that metabolic dysregulation is not just a comorbid condition, but an integral part of the disease course, which requires close attention from clinicians. Detection of hyperglycemia at the initial consultation is an economically justified and clinically important procedure that allows the psychiatrist to make more informed decisions regarding therapy and metabolic interventions, which improves the quality of life and life expectancy of patients.

 

Keywords: metabolic syndrome, hyperglycemia, schizophrenia, depression, bipolar disorder, transdiagnostic approach.

 

Article (pdf)

 

Contacts

This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Materials  

For citation: Kibitov A.O., Shumskaia D.S., Pinakhina D.V., Chensky I.S., Yanushko M.G., Popov M.Yu., Zhilyaeva T.V., Mazo G.E. Specific metabolic and inflammatory profiles of patients with hyperglycemia in bipolar affective disorder, recurrent depression and schizophrenia: results of a transdiagnostic study. Siberian Herald of Psychiatry and Addiction Psychiatry.2025; 4 (129): 43-56. https://doi.org/10.26617/1810-3111-2025-4(129)-43-56

 

REFERENCES

  1. Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep. 2018 Feb 26;20(2):12. https://doi.org/10.1007/s11906-018-0812-z. PMID: 29480368; PMCID: PMC5866840.
  2. Ventriglio A, Gentile A, Stella E, Bellomo A. Metabolic issues in patients affected by schizophrenia: clinical characteristics and medical management. Front Neurosci. 2015 Sep 3;9:297. https://doi.org/10.3389/fnins.2015.00297. PMID: 26388714; PMCID: PMC4558473.
  3. Newcomer JW. Metabolic syndrome and mental illness. Am J Manag Care. 2007 Nov;13(7 Suppl):S170-7. Erratum in: Am J Manag Care. 2008 Feb;14(2):76. PMID: 18041878.
  4. Manta A, Georganta A, Roumpou A, Zoumpourlis V, Spandidos DA, Rizos E, Peppa M. Metabolic syndrome in patients with schizophrenia: Underlying mechanisms and therapeutic approaches (Review). Mol Med Rep. 2025 May;31(5):114. https://doi.org/10.3892/mmr.2025.13479. Epub 2025 Feb 28. PMID: 40017113; PMCID: PMC11894597.
  5. Osmanova DZ, Freidin MB, Fedorenko OY, Pozhidaev IV, Boiko AS, Vyalova NM, Tiguntsev VV, Kornetova EG, Loonen AJM, Semke AV, Wilffert B, Bokhan NA, Ivanova SA. A pharmacogenetic study of patients with schizophrenia from West Siberia gets insight into dopaminergic mechanisms of antipsychotic-induced hyperprolactinemia. BMC Med Genet. 2019 Apr 9;20(Suppl 1):47. https://doi.org/10.1186/s12881-019-0773-3. PMID: 30967134; PMCID: PMC6454588.
  6. Polcwiartek C, O'Gallagher K, Friedman DJ, Correll CU, Solmi M, Jensen SE, Nielsen RE. Severe mental illness: cardiovascular risk assessment and management. Eur Heart J. 2024 Mar 27;45(12):987-997. https://doi.org/10.1093/eurheartj/ehae054. PMID: 38538149; PMCID: PMC10972692.
  7. Fleischhacker WW, Cetkovich-Bakmas M, De Hert M, Hennekens CH, Lambert M, Leucht S, Maj M, McIntyre RS, Naber D, Newcomer JW, Olfson M, Osby U, Sartorius N, Lieberman JA. Comorbid somatic illnesses in patients with severe mental disorders: clinical, policy, and research challenges. J Clin Psychiatry. 2008 Apr;69(4):514-9. https://doi.org/10.4088/jcp.v69n0401. PMID: 18370570.
  8. Ho CSH, Zhang MWB, Mak A, Ho RCM. Metabolic syndrome in psychiatry: advances in understanding and management. Adv Psychiatr Treat. 2014March; 20(2):101-112. https://doi.org/10.1192/apt.bp.113.011619.
  9. Penninx BWJH, Lange SMM. Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications. Dialogues Clin Neurosci. 2018 Mar;20(1):63-73. https://doi.org/10.31887/DCNS.2018.20.1/bpenninx.PMID: 29946213; PMCID: PMC6016046.
  10. Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, Rosenbaum S, Correll CU. Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: a systematic review and meta-analysis. World Psychiatry. 2015 Oct;14(3):339-47.https://doi.org/10.1002/wps.20252. PMID: 26407790; PMCID: PMC4592657.
  11. Neznanov NG, Rukavishnikov GV, KasyanovED, Philippov DS, Kibitov AO, Mazo GE. Biopsychosocial model in psychiatry as an optimal paradigm for relevant biomedical research. VM Bekhterev Review of Psychiatry and Medical Psychology. 2020;(2):3-15. https://doi.org/10.31363/2313-7053-2020-2-3-15(in Russian).
  12. Saccaro LF, Aimo A, Panichella G, Sentissi O. Shared and unique characteristics of metabolic syndrome in psychotic disorders: a review. Front Psychiatry. 2024 Mar 4;15:1343427. https://doi.org/10.3389/fpsyt.2024.1343427. PMID: 38501085; PMCID: PMC10944869.
  13. Ermakov E, Mednova I, Boiko A, Ivanova S. Neuroinflammation in schizophrenia: An overview of evidence and implications for pathophysiology. J Integr Neurosci. 2025 Jul 25;24(7):27636. https://doi.org/10.31083/JIN27636. PMID: 40767005.
  14. Zeng Y, Chourpiliadis C, Hammar N, Seitz C, Valdimarsdóttir UA, Fang F, Song H, Wei D. Inflammatory biomarkers and risk of psychiatric disorders. JAMA Psychiatry. 2024 Nov 1;81(11):1118-1129. https://doi.org/10.1001/jamapsychiatry.2024.2185. PMID: 39167384; PMCID: PMC11339698.
  15. Neznanov NG, Kibitov AO, Rukavishnikov GV, Mazo GE. The prognostic role of depression as a predictor of chronic somatic diseases. Therapeutic Archive. 2018;90(12):122-132.https://doi.org/10.26442/00403660.2018.12.000019(in Russian).
  16. KibitovAO, ShumskayaDS. Modern genome-wide association studies of mental disorders: focus on the mechanisms of inflammation. Siberian Herald of Psychiatry and Addiction Psychiatry. 2024;4(125):56-65.https://doi.org/10.26617/1810-3111-2024-4(125)-56-65 (in Russian).
  17. Herder C, Zhu A, Schmitt A, Spagnuolo MC, Kulzer B, Roden M, Hermanns N, Ehrmann D. Associations between biomarkers of inflammation and depressive symptoms-potential differences between diabetes types and symptom clusters of depression. Transl Psychiatry. 2025 Jan 11;15(1):9. https://doi.org/10.1038/s41398-024-03209-y. PMID: 39799156; PMCID: PMC11724873.
  18. McQuaid RJ. Transdiagnostic biomarker approaches to mental health disorders: Consideration of symptom complexity, comorbidity and context. Brain Behav Immun Health. 2021 Jul 28;16:100303. https://doi.org/10.1016/j.bbih.2021.100303. PMID: 34589795; PMCID: PMC8474161.
  19. Gorbunova AP, Rukavishnikov GV, Kasyanov ED, Mazo GE. The role of hematological coefficients of systemic inflammation in the diagnosis and risk assessment of affective disorders. V.M. Bekhterev Review of Psychiatry and Medical Psychology. 2024;58(1):47-55. https://doi.org/10.31363/2313-7053-2024-794(in Russian).
  20. Pereira AC, Oliveira J, Silva S, Madeira N, Pereira CMF, Cruz MT. Inflammation in bipolar disorder (BD): Identification of new therapeutic targets. Pharmacol Res. 2021 Jan;163:105325. https://doi.org/10.1016/j.phrs.2020.105325. Epub 2020 Dec 2. PMID: 33278569.
  21. Marra A, Bondesan A, Caroli D, Sartorio A. Complete blood count-derived inflammation indexes are useful in predicting metabolic syndrome in children and adolescents with severe obesity. J Clin Med. 2024 Apr 5;13(7):2120. https://doi.org/10.3390/jcm13072120.PMID: 38610885; PMCID: PMC11012534.
  22. Ozomaro U, Wahlestedt C, Nemeroff CB. Personalized medicine in psychiatry: problems and promises. BMC Med. 2013 May 16;11:132. https://doi.org/10.1186/1741-7015-11-132. PMID: 23680237; PMCID: PMC3668172.
  23. The IDF consensus worldwide definition of the metabolic syndrome. Obesity and Metabolism. 2005;2(3):47-49. https://doi.org/10.14341/2071-8713-4854(in Russian).
  24. Bartoli F, Carrà G, Crocamo C, Carretta D, Clerici M. Bipolar disorder, schizophrenia, and metabolic syndrome. Am J Psychiatry. 2013 Aug;170(8):927-8. https://doi.org/10.1176/appi.ajp.2013.13040447.PMID: 23903338.
  25. Mousa FA, A, Dessoki HH, El Kateb SM, Ezzat AA, Soltan MR. Metabolic syndrome in psychiatric patients (comparative study). Egypt J Psychiatr. 2017;38:179-191.
  26. Launders N, Dotsikas K, Marston L, Price G, Osborn DPJ, Hayes JF. The impact of comorbid severe mental illness and common chronic physical health conditions on hospitalisation: A systematic review and meta-analysis. PLoS One. 2022 Aug 18;17(8):e0272498. https://doi.org/10.1371/journal.pone.0272498. PMID: 35980891; PMCID: PMC9387848.
  27. Fountoulakis KN, Karakatsoulis GN, Abraham S et al. Somatic multicomorbidity and disability in patients with psychiatric disorders in comparison to the general population: a quasi-epidemiological investigation in 54,826 subjects from 40 countries (COMET-G study). CNS Spectr. 2024 Apr;29(2):126-149. https://doi.org/10.1017/S1092852924000026. Epub 2024 Jan 25. PMID: 38269574.
  28. Makeenko VE, Shumskaia DS, Kibitov AO. The problem of assessing the extent of somatic comorbidity in patients with major depressive disorder and bipolar disorder: metabolic syndrome, cardiovascular diseases, and type II diabetes mellitus. VM Bekhterev Review of Psychiatry and Medical Psychology. 2024;58(4-2):29-38. https://doi.org/10.31363/2313-7053-2024-1035(in Russian).
  29. Canli D. Evaluation of systemic immune inflammation index and neutrophil-to-lymphocyte ratio in schizophrenia, bipolar disorder and depression. Bratisl Lek Listy. 2024;125(8):472-476.https://doi.org/10.4149/BLL_2024_73. PMID: 38989747.
  30. Chen J, Huang Y, Li X. The association between lymphocyte to high-density lipoprotein ratio and depression: Data from NHANES 2015-2018. Brain Behav. 2024 Mar;14(3):e3467. https://doi.org/10.1002/brb3.3467. PMID: 38468463; PMCID: PMC10928332.
  31. Mazo GE, Neznanov NG, Kibitov AO, Rukavishnikov GV. Do antidepressants modify the risk of developing chronic somatic diseases? Depression and the risk of developing somatic diseases: Handbook for physicians. Moscow: Special Publishing House of Medical Books, 2018:195-204(in Russian).
  32. Kornetova EG, Galkin SA, Kornetov AN, Schastniy ED, Petkun DA, Mednova IA, Bokhan NA. Comparative study of metabolic disorders in inpatients with schizophrenia and affective disorders. Social and Clinical Psychiatry. 2024;34(2):5-12 (in Russian).
  33. Laaboub N, Ranjbar S, Crettol S, Ansermot N, Vandenberghe F, Grandjean C, Piras M, Elowe J, Preisig M, Gunten AV, Conus P, Eap CB. Metabolic syndrome and its components are associated with lengths of stay in a psychiatric hospital: Results from a Swiss psychiatric cohort and first-episode psychosis patients. Eur Psychiatry. 2025 May 26;68(1):e65. https://doi.org/10.1192/j.eurpsy.2025.10036. PMID: 40415581; PMCID: PMC12303775.
  34. Mazereel V, Detraux J, Vancampfort D, van Winkel R, De Hert M. Impact of psychotropic medication effects on obesity and the metabolic syndrome in people with serious mental illness. Front Endocrinol (Lausanne). 2020 Oct 9;11:573479. https://doi.org/10.3389/fendo.2020.573479. PMID: 33162935; PMCID: PMC7581736.
  35. Jarari AM, Peela JR, Zakoko A, Hawda S, Abd El Rasoul H, Peela AST, Addagarla S, Madompoyil B. The role of antipsychotic medications on metabolic and hematological parameters. Cureus. 2025 Apr 15;17(4):e82293. https://doi.org/10.7759/cureus.82293.PMID: 40376339; PMCID: PMC12081135.
  36. Rukavishnikov GV, Kasyanov ED, Pinakhina DV, Kibitov AO, Neznanov NG, Mazo GE. The concept of multimorbidity as an integrative method for studying the mechanisms of formation of mental and somatic diseases. VMBekhterev Review of Psychiatry and Medical Psychology. 2023;57(4):8-19. https://doi.org/10.31363/2313-7053-2023-854(in Russian).
  37. KibitovAO, MazoGE. Metabolic side effects of atypical antipsychotics: interindividual variability and genetic risk. Social and Clinical Psychiatry. 2018;28(1):90-100 (in Russian).