The Correlation between Serum Biomarkers and Electrocardiogram Characteristics, Pulse Wave Velocity, Blood Lipid Levels, and Carotid Atherosclerosis in Patients with Type 2 Diabetes Mellitus
Serum Biomarkers (adiponectin, leptin, sICAM-1, IL-6, FGF-21) , ECG, PWV, and Blood Lipid Levels for Diabetic CAS
Abstract
Background: Patients with type 2 diabetes mellitus (T2DM) often suffer from atherosclerosis, and timely stratification of patient risk is crucial for preventing cardiovascular events.
Objectives: It aimed to explore the correlation between electrocardiogram (ECG) characteristics, pulse wave velocity (PWV), blood lipid levels, and novel serum biomarkers with carotid atherosclerosis (CAS) in T2DM patients, providing a multidimensional assessment basis for early identification of high-risk patients.
Methods: A retrospective study included 201 T2DM patients at Zhongshan Hospital (Xiamen), Fudan University from January 2024 to December 2025. Patients were allocated to control group (AG, 91 cases with normal carotid arteries or only intimal thickening) or observation group (BG, 110 cases with carotid plaques). General data, ECG indicators, vascular function indicators, blood glucose, blood lipid levels, low-sensitivity C-reactive protein (CRP-L), and novel serum biomarkers (adiponectin, leptin, sICAM-1, IL-6, FGF-21) were collected.
Results: The BG had significantly longer P wave duration (PR) and corrected QT (QTc)interval, with higher PWV-Left and PWV-Right; Fasting plasma glucose (FPG), triglycerides (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels were lower, and glycated hemoglobin (HbA1c) and CRP-L were significantly elevated in the BG (P <0.05). Additionally, serum levels of adiponectin were significantly lower, while leptin, sICAM-1, and IL-6 were higher in the BG compared to AG (*P < 0.05). PR, QT, PWV (left/right), FPG, HbA1c, TG, TC, LDL-C, CRP-L, and several serum biomarkers were independent influencing factors for CAS.
Conclusion: In T2DM patients, ECG repolarization abnormalities, increased arterial stiffness, poor long-term glycemic control, chronic low-grade inflammation, and alterations in novel serum biomarkers are closely related to CAS. Comprehensive assessment of ECG, PWV, inflammatory-metabolic markers, and emerging serum biomarkers helps more accurately identify high-risk populations for atherosclerosis.
References
2. Wang M, Yang Q, Li Y, Zhao Y, Zou J, Luan F, et al. Therapeutic potential of traditional Chinese medicine and mechanisms for the treatment of type 2 diabetes mellitus. Chin Med. 2025;20(1):157.
3. Martínez-Hervás S, Real JT, Carmena R, Ascaso JF. Cardiovascular prevention in diabetes mellitus. Is it appropriate to speak of moderate or intermediate risk? Clin e Investig en Arterioscler. 2024;36(2):80-5.
4. Zanfirescu RL, Anghel L, Tudurachi BS, Clement AM, Zăvoi A, Benchea LC, et al. Improved ASCVD screening in diabetes: A focus on scoring models and detection techniques. Rom J Intern Med. 2025;63(2):127-44.
5. Berezin AE. Early predictors of carotid atherosclerosis in patients with type 2 diabetes mellitus. World J Diabetes. 2025;16(10):112631.
6. Gamayani U, Hidayat S, Calista C, Ong PA, Albertus H, Ifayani I, et al. Comparison of carotid intima-media thickness and cognitive function in systemic lupus erythematosus patients versus healthy subjects. Lupus. 2025;34(5):713-20.
7. Bohare SM, Pathania M, Kant R, Puri O, Chaudhari AS, Dhar M. Correlation of carotid intima-media thickness with glycaemic variability in patients with type 2 diabetes mellitus: A cross-sectional study. Ann Neurosci. 2025; Online ahead of print.
8. Mashaba RG, Phoswa W, Maimela E, Mokgalaboni K. Association of carotid intima-media thickness and dyslipidaemia in patients with type 2 diabetes: A protocol for systematic review and meta-analysis. BMJ Open. 2024;14(3):e079209.
9. Soflaei Saffar S, Nazar E, Sahranavard T, Fayedeh F, Moodi Ghalibaf A, Ebrahimi M, et al. Association of T-wave electrocardiogram changes and type 2 diabetes: A cross-sectional sub-analysis of the MASHAD cohort population using the Minnesota coding system. BMC Cardiovasc Disord. 2024;24(1):48.
10. Harms PP, Elders PPJM, Rutters F, Lissenberg-Witte BI, Tan HL, Beulens JWJ, et al. Longitudinal association of electrocardiogram abnormalities with major adverse cardiac events in people with type 2 diabetes: The hoorn diabetes care system cohort. Eur J Prev Cardiol. 2023;30(6):624-33.
11. Isaksen JL, Sivertsen CB, Jensen CZ, Graff C, Linz D, Ellervik C, et al. Electrocardiographic markers in patients with type 2 diabetes and the role of diabetes duration. J Electrocardiol. 2024;84:129-36.
12. Shi L, Li NJ. Comprehensive analysis of risk factors associated with carotid plaque in patients with type 2 diabetes mellitus. World J Diabetes. 2025;16(8):104180.
13. Beros AL, Sluyter JD, Scragg RKR. Evidence of a bi-directional relationship between arterial stiffness and diabetes: A systematic review and meta-analysis of cohort studies. Curr Diabetes Rev. 2025;21(1):11-9.
14. Cheong SS, Samah N, Che Roos NA, Ugusman A, Mohamad MSF, Beh BC, et al. Prognostic value of pulse wave velocity for cardiovascular disease risk stratification in diabetic patients: A systematic review and meta-analysis. J Diabetes Complications. 2024;38(2):108894.
15. Han Y, Ren L, Fei X, Wang J, Chen T, Guo J, et al. Effect of moderate-intensity statin on carotid intraplaque neovascularization of coronary artery disease: A retrospective cohort study. Quant Imaging Med Surg. 2024;14(2):1660-72.
16. Cordoba-Melo BD, Arango-Ibanez JP, Posso-Marín S, Ruiz ÁJ, Molina DI, Gomez-Mesa JE. LDL-C achievement in patients with coronary artery disease: A study protocol for the EDHIPO-MARCA retrospective registry. BMJ Open. 2025;15(1):e100569.
17. Ou L, Liu HR, Shi XY, Peng C, Zou YJ, Jia JW, et al. Terminalia chebula Retz. aqueous extract inhibits the Helicobacter pylori-induced inflammatory response by regulating the inflammasome signaling and ER-stress pathway. J Ethnopharmacol. 2024;320:117428.
18. Liu H, Tang T. MAPK signaling pathway-based glioma subtypes, machine-learning risk model, and key hub proteins identification. Sci Rep. 2023;13(1):19055.
19. Liao H, Ma Q, Chen L, Guo W, Feng K, Bao Y, et al. Machine learning analysis of CD4+ T cell gene expression in diverse diseases: Insights from cancer, metabolic, respiratory, and digestive disorders. Cancer Genet. 2025;290-291:56-60.
20. Welten SJGC, van der Heijden AA, Remmelzwaal S, Blom MT, Nijpels G, Rutters F, et al. Prolongation of the QTc interval is associated with an increased risk of cardiovascular diseases: The Hoorn study. J Electrocardiol. 2023;80:133-8.
21. Sawarthia S, Patel R, Patil PP. A cross-sectional study to determine the association of corrected QT interval with microalbuminuria in type 2 diabetes mellitus. Cureus. 2023;15(4):e38967.
22. Marchand M, Erickson AC, Gillman L, Haywood R, Morrison J, Jaworsky D, et al. The impact of chronic disease on the corrected QT (QTc) value in women in a british columbia first nations population. Can J Cardiol. 2024;40(1):89-97.
23. Wang L, Shi Y, Zhang Z, Xiang F, Fang Y, Ding X, et al. Association between estimated pulse wave velocity and carotid plaques in non-dialysis CKD stages 3-5: A cross-sectional study. J Clin Hypertens. 2025;27(1):e70103.
24. Liu B, Gao L, Zheng B, Yang Y, Jia J, Sun P, et al. Comparison of carotid-femoral and brachial-ankle pulse wave velocity in association with carotid plaque in a Chinese community-based population. J Clin Hypertens. 2022;24(12):1568-76.
25. Vogiatzi G, Lazaros G, Oikonomou E, Kostakis M, Kypritidou Z, Christoforatou E, et al. Impact of drinking water hardness on carotid atherosclerosis and arterial stiffness: Insights from the "Corinthia" study. Hellenic J Cardiol. 2023;74:32-8.
26. Apte M, Zambre S, Pisar P, Roy B, Tupe R. Decoding the role of aldosterone in glycation-induced diabetic complications. Biochem Biophys Res Commun. 2024;721:150107.
27. Liu J, Pan S, Wang X, Liu Z, Zhang Y. Role of advanced glycation end products in diabetic vascular injury: molecular mechanisms and therapeutic perspectives. Eur J Med Res. 2023;28(1):553.
28. Xie F, Liu B, Qiao W, He JZ, Cheng J, Wang ZY, et al. Smooth muscle NF90 deficiency ameliorates diabetic atherosclerotic calcification in male mice via FBXW7-AGER1-AGEs axis. Nat Commun. 2024;15(1):4985.
29. Zhang Q, Wu C, Liu Y, Tan X, Li C, Li L, et al. Chronic inflammation plays a role of a bridge between cardiovascular disease and hyperglycemia. Metab Syndr Relat Disord. 2023;21(9):468-74.
30. Bains M, Aloona S, Singh G, Bains R. A comparative study on levels of hs-CRP and lipid profile in prediabetic and normal population. J Pharm Bioallied Sci. 2024;16(Suppl 2):S2188-90.
31. Reddy KSS, Varadaraj P, Nallusamy G, SenthilNathan S. Correlation between hemoglobin a1c (HbA1c) and high-sensitivity C-reactive protein (hs-CRP) in myocardial infarction patients and their six-month mortality follow-up. Cureus. 2024;16(4):e67070.
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