Both fatty liver/fibrosis and insulin resistance (IR) contribute to the development of Cardiovascular-Kidney-Metabolic (CKM) syndrome and elevate cardiovascular risk. This study aimed to investigate the joint associations of IR and fatty liver/fibrosis indices with major adverse cardiovascular events (MACE) and mortality in individuals with CKM syndrome stages 0–3. This study enrolled 259,699 and 6808 CKM syndrome stages 0–3 from the UK Biobank (UKB) and the National Health and Nutrition Examination Survey (NHANES). Two IR-related indices (triglyceride-glucose index, TyG; cardiometabolic index, CMI), fatty liver indices (Fatty Liver Index, FLI; Hepatic Steatosis Index, HSI), and liver fibrosis score (LiverRisk score, LRS) were calculated to construct composite indices. Multivariable Cox proportional hazards models, restricted cubic splines, Kaplan–Meier analyses, and time-dependent receiver operating characteristic curves were employed to assess prognostic associations. Mediation modeling and proteomic enrichment analyses provided a robust framework for exploring the potential pathophysiological pathways. In the UKB, elevated levels of the IR-FLI/HSI/LRS indices were significantly associated with increased risks of MACE and mortality, with consistent findings observed for all-cause and CVD mortality in the NHANES. Significant positive nonlinear relationships were established between the CMI-FLI/HSI/LRS indices and the risk of MACE. Furthermore, these composite indices demonstrated superior 10-year predictive performance compared to individual IR-related indices, and the combination of CMI and LRS showed the best performance for predicting cardiovascular mortality in both cohorts, with AUCs of 0.755 in the UKB and 0.847 in the NHANES. Mediation analysis revealed that C-reactive protein, neutrophils, and leukocytes partially mediated these associations (ratio 5.3%–14.8%). Proteomic analyses identified cytokine–cytokine receptor interactions as a primary regulatory hub, while leukocyte migration, chemotaxis, and neutrophil degranulation emerged as potential effector mechanisms implicated in this process. IR–fatty liver/fibrosis indices are significantly associated with MACE and mortality and may serve as promising biomarkers for early screening and targeted intervention in CKM stages 0–3.
Citation: Yanqiu Huang, Wen Gu, Yadan Xu, Minxi Lin, Jun Lu, Chenghao Zhang, Yan Wu, Dengke Wang, Xia Shen, Yang Yang, Hui Wang. Joint association of insulin resistance, fatty liver and fibrosis indices with MACE and mortality in individuals with Cardiovascular-Kidney-Metabolic syndrome stages 0–3[J]. AIMS Public Health, 2026, 13(3): 761-782. doi: 10.3934/publichealth.2026041
Both fatty liver/fibrosis and insulin resistance (IR) contribute to the development of Cardiovascular-Kidney-Metabolic (CKM) syndrome and elevate cardiovascular risk. This study aimed to investigate the joint associations of IR and fatty liver/fibrosis indices with major adverse cardiovascular events (MACE) and mortality in individuals with CKM syndrome stages 0–3. This study enrolled 259,699 and 6808 CKM syndrome stages 0–3 from the UK Biobank (UKB) and the National Health and Nutrition Examination Survey (NHANES). Two IR-related indices (triglyceride-glucose index, TyG; cardiometabolic index, CMI), fatty liver indices (Fatty Liver Index, FLI; Hepatic Steatosis Index, HSI), and liver fibrosis score (LiverRisk score, LRS) were calculated to construct composite indices. Multivariable Cox proportional hazards models, restricted cubic splines, Kaplan–Meier analyses, and time-dependent receiver operating characteristic curves were employed to assess prognostic associations. Mediation modeling and proteomic enrichment analyses provided a robust framework for exploring the potential pathophysiological pathways. In the UKB, elevated levels of the IR-FLI/HSI/LRS indices were significantly associated with increased risks of MACE and mortality, with consistent findings observed for all-cause and CVD mortality in the NHANES. Significant positive nonlinear relationships were established between the CMI-FLI/HSI/LRS indices and the risk of MACE. Furthermore, these composite indices demonstrated superior 10-year predictive performance compared to individual IR-related indices, and the combination of CMI and LRS showed the best performance for predicting cardiovascular mortality in both cohorts, with AUCs of 0.755 in the UKB and 0.847 in the NHANES. Mediation analysis revealed that C-reactive protein, neutrophils, and leukocytes partially mediated these associations (ratio 5.3%–14.8%). Proteomic analyses identified cytokine–cytokine receptor interactions as a primary regulatory hub, while leukocyte migration, chemotaxis, and neutrophil degranulation emerged as potential effector mechanisms implicated in this process. IR–fatty liver/fibrosis indices are significantly associated with MACE and mortality and may serve as promising biomarkers for early screening and targeted intervention in CKM stages 0–3.
| [1] |
Ndumele CE, Rangaswami J, Chow SL, et al. (2023) Cardiovascular-kidney-metabolic health: a presidential advisory from the American heart association. Circulation 148: 1606-1635. https://doi.org/10.1161/CIR.0000000000001184
|
| [2] |
Ndumele CE, Neeland IJ, Tuttle KR, et al. (2023) A synopsis of the evidence for the science and clinical management of cardiovascular-kidney-metabolic (CKM) syndrome: a scientific statement from the American heart association. Circulation 148: 1636-1664. https://doi.org/10.1161/CIR.0000000000001186
|
| [3] | Zhang M, Qiu Z, Wang Y, et al. (2026) Associations of different definitions of prediabetes and diabetes with all-cause and cause-specific mortality: a nationally representative cohort study. Mil Med Res 13: 100028. https://doi.org/10.1016/j.mmr.2026.100028 |
| [4] |
Max F, Tesař T, Gažová A, et al. (2026) Impact of high doses of vitamin D on specific metabolic parameters in type 2 diabetes patients: a prospective biomedical study. Int J Vitam Nutr Res 96: 46454. https://doi.org/10.31083/IJVNR46454
|
| [5] |
Roth S, M'Pembele R, Matute P, et al. (2024) Cardiovascular-kidney-metabolic syndrome: association with adverse events after major noncardiac surgery. Anesth Analg 139: 679-681. https://doi.org/10.1213/ANE.0000000000006975
|
| [6] | Zhou XD, Chen QF, Fan QY, et al. (2025) Cardiovascular-kidney-metabolic syndrome and the risk of liver fibrosis progression and liver-related events in MASLD. Hepatology . |
| [7] |
Lyu YS, Park M, Kim HK, et al. (2025) Combined impact of prediabetes and fatty liver index on cardiometabolic outcomes and mortality in middle aged adults: a nationwide cohort study. Cardiovasc Diabetol 24: 279. https://doi.org/10.1186/s12933-025-02793-7
|
| [8] |
Luci C, Bourinet M, Leclère PS, et al. (2020) Chronic inflammation in non-alcoholic steatohepatitis: molecular mechanisms and therapeutic strategies. Front Endocrinol 11: 597648. https://doi.org/10.3389/fendo.2020.597648
|
| [9] |
Alfaddagh A, Martin SS, Leucker TM, et al. (2020) Inflammation and cardiovascular disease: From mechanisms to therapeutics. Am J Prev Cardiol 4: 100130. https://doi.org/10.1016/j.ajpc.2020.100130
|
| [10] | Jiang D, Li MM, Li JF, et al. (2026) EGCG accelerates wound healing in diabetic mice by Notch pathway to enhance epidermis formation. Food Med Homol . |
| [11] |
Dong B, Chen Y, Yang X, et al. (2025) Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study. Cardiovasc Diabetol 24: 163. https://doi.org/10.1186/s12933-025-02729-1
|
| [12] |
Lee SH, Park SY, Choi CS (2022) Insulin resistance: from mechanisms to therapeutic strategies. Diabetes Metab J 46: 15-37. https://doi.org/10.4093/dmj.2021.0280
|
| [13] |
Ahmed B, Sultana R, Greene MW (2021) Adipose tissue and insulin resistance in obese. Biomed Pharmacother 137: 111315. https://doi.org/10.1016/j.biopha.2021.111315
|
| [14] |
Yu C, Qiu C, Zhang Q, et al. (2026) Association of atherogenic index of plasma and cardiometabolic index with all-cause mortality and cardiovascular disease in NAFLD patients: NHANES 1999–2018. Cardiovasc Diabetol 25: 74. https://doi.org/10.1186/s12933-025-03043-6
|
| [15] |
Huang Y, Zhou Y, Xu Y, et al. (2025) Inflammatory markers link triglyceride-glucose index and obesity indicators with adverse cardiovascular events in patients with hypertension: insights from three cohorts. Cardiovasc Diabetol 24: 11. https://doi.org/10.1186/s12933-024-02571-x
|
| [16] |
Wu H, Zhou Y, Lai X, et al. (2025) Association between metabolic score for insulin resistance and future stroke risk in patients with cardiovascular-kidney-metabolic syndrome stages 0–3: a longitudinal analysis based on CHARLS. Cardiovasc Diabetol 24: 379. https://doi.org/10.1186/s12933-025-02932-0
|
| [17] |
Tan MY, Zhang YJ, Zhu SX, et al. (2025) The prognostic significance of stress hyperglycemia ratio in evaluating all-cause and cardiovascular mortality risk among individuals across stages 0-3 of cardiovascular-kidney-metabolic syndrome: evidence from two cohort studies. Cardiovasc Diabetol 24: 137. https://doi.org/10.1186/s12933-025-02689-6
|
| [18] |
Targher G, Byrne CD, Tilg H (2020) NAFLD and increased risk of cardiovascular disease: clinical associations, pathophysiological mechanisms and pharmacological implications. Gut 69: 1691-1705. https://doi.org/10.1136/gutjnl-2020-320622
|
| [19] |
Mantovani A, Csermely A, Petracca G, et al. (2021) Non-alcoholic fatty liver disease and risk of fatal and non-fatal cardiovascular events: an updated systematic review and meta-analysis. Lancet Gastroenterol Hepatol 6: 903-913. https://doi.org/10.1016/S2468-1253(21)00308-3
|
| [20] |
Huang Y, Wan T, Hong Y, et al. (2025) Impact of NAFLD and fibrosis on adverse cardiovascular events in patients with hypertension. Hypertension 82: 1012-1023. https://doi.org/10.1161/HYPERTENSIONAHA.124.24252
|
| [21] |
Liu S, Chen X, Jiang X, et al. (2024) LiverRisk score: An accurate, cost-effective tool to predict fibrosis, liver-related, and diabetes-related mortality in the general population. Med 5: 570-582.e574. https://doi.org/10.1016/j.medj.2024.03.003
|
| [22] |
Huang Y, Xu J, Yang Y, et al. (2024) Association between lifestyle modification and all-cause, cardiovascular, and premature mortality in individuals with non-alcoholic fatty liver disease. Nutrients 16: 2063. https://doi.org/10.3390/nu16132063
|
| [23] |
Serra-Burriel M, Juanola A, Serra-Burriel F, et al. (2023) Development, validation, and prognostic evaluation of a risk score for long-term liver-related outcomes in the general population: a multicohort study. Lancet 402: 988-996. https://doi.org/10.1016/S0140-6736(23)01174-1
|
| [24] |
Hu Y, Li W, Nie J, et al. (2025) Association between the atherogenic index of plasma and major adverse cardiovascular events in individuals with metabolic syndrome: findings from the UK biobank. Cardiovasc Diabetol 24: 444. https://doi.org/10.1186/s12933-025-03010-1
|
| [25] |
Song Z, Miao X, Liu S, et al. (2025) Associations between cardiometabolic indices and the onset of metabolic dysfunction-associated steatotic liver disease as well as its progression to liver fibrosis: a cohort study. Cardiovasc Diabetol 24: 154. https://doi.org/10.1186/s12933-025-02716-6
|
| [26] |
Tutunchi H, Naeini F, Mobasseri M, et al. (2021) Triglyceride glucose (TyG) index and the progression of liver fibrosis: A cross-sectional study. Clin Nutr ESPEN 44: 483-487. https://doi.org/10.1016/j.clnesp.2021.04.025
|
| [27] |
Yan L, Hu X, Wu S, et al. (2024) Association between the cardiometabolic index and NAFLD and fibrosis. Sci Rep 14: 13194. https://doi.org/10.1038/s41598-024-64034-3
|
| [28] |
Zhou XD, Zheng MH (2025) Cardiovascular–kidney–metabolic syndrome and MASLD: integrating medical perspectives. Nat Rev Cardiol 22: 843-843. https://doi.org/10.1038/s41569-025-01199-y
|
| [29] |
Theodorakis N, Nikolaou M (2025) From cardiovascular-kidney-metabolic syndrome to cardiovascular-renal-hepatic-metabolic syndrome: proposing an expanded framework. Biomolecules 15: 213. https://doi.org/10.3390/biom15020213
|
| [30] |
Tilg H, Adolph TE, Dudek M, et al. (2021) Non-alcoholic fatty liver disease: the interplay between metabolism, microbes and immunity. Nat Metab 3: 1596-1607. https://doi.org/10.1038/s42255-021-00501-9
|
| [31] |
Saltiel AR, Olefsky JM (2017) Inflammatory mechanisms linking obesity and metabolic disease. J Clin Invest 127: 1-4. https://doi.org/10.1172/JCI92035
|
| [32] |
Miller DM, McCauley KF, Dunham-Snary KJ (2025) Metabolic dysfunction-associated steatotic liver disease (MASLD): Mechanisms, clinical implications and therapeutic advances. Endocrinol Diabetes Metab 8: e70132. https://doi.org/10.1002/edm2.70132
|
| [33] |
Galicia-Garcia U, Benito-Vicente A, Jebari S, et al. (2020) Pathophysiology of type 2 diabetes mellitus. Int J Mol Sci 21: 6275. https://doi.org/10.3390/ijms21176275
|
| [34] |
Zhang Y, Zheng Y, Fu Y, et al. (2019) Identification of biomarkers, pathways and potential therapeutic agents for white adipocyte insulin resistance using bioinformatics analysis. Adipocyte 8: 318-329. https://doi.org/10.1080/21623945.2019.1649578
|
| [35] |
Yu S, Jiang X, Peng L, et al. (2025) Integrated bioinformatics decoding of the MASLD ceRNA network reveals novel therapeutic targets. Clin Exp Med 25: 354. https://doi.org/10.1007/s10238-025-01890-x
|
publichealth-13-03-041-s001.pdf |
![]() |