Phenotypes of Post-COVID syndrome identified by cluster analysis and their association with metabolic markers

Introduction. Post-COVID syndrome (PCS, long COVID, ICD-10 code U09.9) affects approximately 36% of individuals who have had COVID-19 and is characterized by clinical heterogeneity spanning cardiorespiratory, neurocognitive, musculoskeletal, and psychoemotional domains. Cardiovascular manifestations of PCS (myocarditis, arrhythmias, thromboembolic events), and dyslipidaemia may persist for up to three years after acute infection; however, the phenotypic structure of PCS and its association with metabolic risk markers in young patients remain insufficiently studied.

Aim. To identify the main PCS phenotypes in patients aged 18–44 years using symptom-based cluster analysis (k-means) and to assess their association with metabolic markers (lipid profile, systemic inflammation indices, haemostasis parameters).

Materials and methods. A single-centre cross-sectional study (n = 251, aged 18–44 years). Phenotyping was performed by k-means clustering using 9 binary symptom variables. The optimal number of clusters was determined by silhouette coefficient. Assessments included lipid profile, systemic inflammation indices (NLR, PLR, SII), haemostasis markers (D-dimer, fibrinogen), ferritin, and CRP. Statistics: Kruskal–Wallis test, Mann–Whitney test with Bonferroni correction, chi-square test.

Results. Three phenotypes were identified: low-symptom (P1, n = 100; 39.8%), neurocognitive–psychoemotional (P2, n = 83; 33.1%), and multisystem (P3, n = 68; 27.1%). Phenotypes differed significantly in symptom burden (medians 4, 8, and 12 points; H = 160.8; p < 0.001), sex (χ² = 15.9; p = 0.0004), age (H = 18.2; p = 0.0001), and prevalence of overweight (p = 0.003). Ferritin proved to be the only metabolic marker with significant inter-phenotype differences (p = 0.030), with the highest level in P1 (median 64.8 ng/mL), possibly reflecting subclinical inflammatory activation in the presence of minimal symptoms. No significant differences between phenotypes were found for lipid profile (LDL, TC, TG, HDL), systemic inflammation indices (NLR, PLR, SII), or haemostasis markers (fibrinogen, D-dimer) (all p > 0.10). Nevertheless, dyslipidaemia was highly prevalent across the entire PCS cohort: LDL > 3.0 mmol/L in 52.0% and LDL > 2.6 mmol/L in 70.5% of participants.

Conclusion. The multisystem phenotype carries the greatest cumulative cardiovascular burden (oldest age, female predominance, highest prevalence of hypertension history and overweight) and represents a priority group for indepth cardiological follow-up. The high prevalence of dyslipidaemia across all phenotypes supports routine lipid profiling in young PCS patients in primary care.

1. Hou Y., Gu T., Ni Z., Shi X., Ranney M.L., Mukherjee B. Global prevalence of long COVID, its subtypes, and risk factors: an updated systematic review and meta-analysis. Open Forum Infectious Diseases. 2025, vol. 12, no. 9, p. ofaf533. doi: 10.1093/ofid/ofaf533.

2. Moniz M., Ruivinho C., Goes A.R., Soares P., Leite A. Long COVID is not the same for everyone: a hierarchical cluster analysis of long COVID symptoms 9 and 12 months after SARS-CoV-2 test. BMC Infectious Diseases. 2024, vol. 24, no. 1, p. 1001. doi: 10.1186/s12879-024-09896-8.

3. Gentilotti E., Górska A., Tami A. et al.; ORCHESTRA Study Group. Clinical phenotypes and quality of life to define post-COVID-19 syndrome: a cluster analysis of the multinational, prospective ORCHESTRA cohort. EClinicalMedicine. 2023, vol. 62, p. 102107. doi: 10.1016/j.eclinm.2023.102107.

4. Hu M., Song T., Gong Z. et al. Symptom trajectories and clinical subtypes in post-COVID-19 condition: systematic review, meta-analysis, and network analysis. JMIR Public Health Surveillance. 2025, vol. 11, p. e72221. doi: 10.2196/72221.

5. Wang W., Wang C.Y., Wang S.I., Wei J.C.C. Long-term cardiovascular outcomes in COVID-19 survivors among non-vaccinated population: a retrospective cohort study from the TriNetX US collaborative networks. EClinicalMedicine. 2022, vol. 53, p. 101619. doi: 10.1016/j.eclinm.2022.101619.

6. Hilser J.R., Spencer N.J., Afshari K. et al. COVID-19 is a coronary artery disease risk equivalent and exhibits a genetic interaction with ABO blood type. Arterioscler Thromb Vasc Biol. 2024, vol. 44, no. 11, pp. 2321–2333. doi: 10.1161/ATVBAHA.124.321001.

7. Xu E., Xie Y., Al-Aly Z. Risks and burdens of incident dyslipidaemia in long COVID: a cohort study. Lancet Diabetes Endocrinol. 2023, vol. 11, no. 2, pp. 120–128. doi: 10.1016/S2213-8587(22)00355-2.

8. Mohamed F., Engel P., Ntusi N.A.B. et al. Metabolic implications of COVID-19 with a focus on lipid profiles and inflammatory markers. Scientific Reports. 2026, vol. 16, p. 6217. doi: 10.1038/s41598-026-37439-5.

9. Chidambaram V., Kumar A., Sadaf M.I. et al. COVID-19 in the initiation and progression of atherosclerosis: pathophysiology during and beyond the acute phase. JACC Advances. 2024, vol. 3, no. 8, p. 101107. doi: 10.1016/j.jacadv.2024.101107.

10. Tsampasian V., Bäck M., Bernardi M. et al. Cardiovascular disease as part of long COVID: a systematic review. Eur J Prev Cardiol. 2025, vol. 32, no. 6, pp. 485–498. doi: 10.1093/eurjpc/zwae070.

11. Dhariwal R., Thakkar K., Vaghela K., Jain M. Evaluating post-acute COVID-19 sequelae in younger population using symptom burden questionnaire. BMC Public Health. 2025, vol. 25, no. 1, p. 3195. doi: 10.1186/s12889-025-24446-w.

12. Camara B., Buonsenso D. Biomarkers of long COVID in children and young adults: a scoping review. Eur J Pediatr. 2026, vol. 185, no. 3, p. 132. doi: 10.1007/s00431-026-06789-7.

13. Quer G., Arnaout R., Haber M., Arnaout R. A survey on the role of artificial intelligence in managing long COVID. Front Artif Intell. 2024, vol. 6, p. 1292466. doi: 10.3389/frai.2023.1292466.

14. Azhir A., Hügel J., Tian J. et al. Precision phenotyping for curating research cohorts of patients with unexplained post-acute sequelae of COVID-19. Med, 2025, vol. 6, no. 3, p. 100532. doi: 10.1016/j.medj.2024.10.009.

15. Chuchalin A.G., Ametov A.S., Arutyunov G.P. et al. Questionnaire for initial self-assessment in post-covid period: recommendations of multidisciplinary expert board on screening of post-covid syndrome during an expanded medical check-up. Pulmonologiya. 2021, vol. 31, no. 5, pp. 599–612. doi: 10.18093/0869-0189-2021-31-5-599-612. (in Russian).

16. Mrochek A.G. et al. Post-COVID syndrome: clinical manifestations and prevalence in working-age patients of the Republic of Belarus. Cardiology in Belarus. 2022, vol. 14, no. 3, pp. 398–410. (in Russian).

17. Hamming I., Timens W., Bulthuis M.L.C. et al. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus: a first step in understanding SARS pathogenesis. J Pathol. 2004, vol. 203, no. 2, pp. 631–637. doi: 10.1002/path.1570.

18. Varga Z., Flammer A.J., Steiger P. et al. Endothelial cell infection and endotheliitis in COVID-19. The Lancet. 2020, vol. 395, no. 10234, pp. 1417–1418. doi: 10.1016/S0140-6736(20)30937-5.

19. Wallukat G., Hohberger B., Wenzel K. et al. Functional autoantibodies against G-protein coupled receptors in patients with persistent long-COVID-19 symptoms. J Transl Autoimmun. 2021, vol. 4, p. 100100. doi: 10.1016/j.jtauto.2021.100100.

20. Vaduganathan M., Vardeny O., Michel T. et al. Renin–angiotensin–aldosterone system inhibitors in patients with Covid-19. New Engl J Med. 2020, vol. 382, pp. 1653–1659. doi: 10.1056/NEJMsr2005760.

21. Teixeira R.B., Maurício A.F., Pereira A.H.M. et al. Oxidative stress-induced endothelial dysfunction and decreased vascular nitric oxide in COVID-19 patients. EBioMedicine. 2022, vol. 77, p. 103893. doi: 10.1016/j.ebiom.2022.103893.

22. Muhamad S.A., Ugusman A., Kumar J. et al. SARS-CoV-2 induced HDL dysfunction may affect the host’s immune response and worsen COVID-19 outcome. Immun Inflamm Dis. 2023, vol. 11, no. 5, p. e861. doi: 10.1002/iid3.861.

23. Katsoularis I., Fonseca-Rodríguez O., Farrington P. et al. Risks of deep vein thrombosis, pulmonary embolism, and bleeding after covid-19: nationwide self-controlled case series and matched cohort study. BMJ. 2022, vol. 377, p. e069590. doi: 10.1136/bmj-2021-069590.

24. Blitshteyn S., Whitelaw S. Postural orthostatic tachycardia syndrome (POTS) and other autonomic disorders after COVID-19 infection: a case series of 20 patients. Immunol Res. 2021, vol. 69, no. 2, pp. 205–211. doi: 10.1007/s12026-021-09185-5.

25. Mancini I., Bottaro E., Porretti M. et al. The long-term residual effects of COVID-associated coagulopathy. Thromb Res. 2023, vol. 226, pp. 100–108. doi: 10.1016/j.thromres.2023.02.009.

26. PHOSP-COVID Collaborative Group. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study. Lancet Respir Med. 2022, vol. 10, no. 8, pp. 761–775. doi: 10.1016/S2213-2600(22)00127-8.

27. Thaweethai T., Jolley S.E., Karlson E.W. et al. Development of a definition of postacute sequelae of SARS-CoV-2 infection. JAMA, 2023, vol. 329, no. 22, pp. 1934–1946. doi: 10.1001/jama.2023.8823.

28. Altmann D.M., Whettlock E.M., Liu S. et al. The immunology of long COVID. Nat Rev Immunol. 2023, vol. 23, no. 10, pp. 618–634. doi: 10.1038/s41577-023-00904-7.

29. Klein J., Wood J., Jaycox J.R. et al. Distinguishing features of long COVID identified through immune profiling. Nature, 2023, vol. 623, no. 7985, pp. 139–148. doi: 10.1038/s41586-023-06651-y.

30. Fois A.G., Paliogiannis P., Scano V. et al. The systemic inflammation index on admission predicts in-hospital mortality in COVID-19 patients. Molecules. 2020, vol. 25, no. 23, p. 5725. doi: 10.3390/molecules25235725.

31. Pochinka I.G., Davydova N.V., Markova Ye.A. et al. Systemic inflammatory index and neutrophil-to-lymphocyte ratio in risk stratification of post-COVID cardiovascular complications. Russian Journal of Cardiology. 2023, vol. 28, no. 7, p. 5356. doi: 10.15829/1560-4071-2023-5356. (in Russian).

32. Luk’yanov M.M., Boytsov S.A., Yakushin S.S. et al. Characteristics of the course and outcomes of COVID-19 in patients with cardiovascular diseases according to the COVID-19 registry. Cardiovascular Therapy and Prevention. 2021, vol. 20, no. 2, p. 2727. doi: 10.15829/1728-8800-2021-2727. (in Russian).

33. Drapkina O.M., Markelova Ye.I., Shestakova M.V. et al. Post-COVID syndrome in the Russian population: data from the COVID-19 registry of the National Medical Research Center for Therapy and Preventive Medicine. Cardiovascular Therapy and Prevention. 2022, vol. 21, no. 6, p. 3307. doi: 10.15829/1728-8800-2022-3307. (in Russian).

34. Zabozlaev F.G., Krupnov N.M., Gallyamova A.R. et al. Neutrophil-to-leukocyte ratio as a predictor of post-COVID syndrome severity. Therapeutic Archive. 2023, vol. 95, no. 1, pp. 28–34. doi: 10.26442/00403660.2023.01.202064. (in Russian).