Associations of nine insulin resistance-related indices with the incidence and progression of cardiovascular-liver-metabolic multimorbidity: a large prospective cohort study

BACKGROUND: Cardiovascular-liver-metabolic (CLM) diseases are interrelated, yet prior studies have mostly examined single-disease outcomes. We aimed to investigate the associations of insulin resistance (IR)-related indices with the incidence and progression of CLM multimorbidity (CLMM), while secondarily evaluating comparative predictive performance and exploring potential biological domains. METHODS: This prospective study included 371,207 UK Biobank participants from England, Scotland, and Wales who were recruited between 2006 and 2010 and were free of CLM diseases at baseline. CLMM was defined as the coexistence of ≥ 2 CLM conditions. Outcomes were ascertained through linkage to national inpatient hospital records and death registries. Nine IR-related indices were computed, including the triglyceride-glucose (TyG) index and its derivatives (e.g., TyG-WC and TyG-WHtR). Associations with CLMM incidence and progression were assessed using Cox proportional hazards and multistate models. Secondary predictive analyses assessed incremental value and discrimination, and exploratory mediation analyses examined whether inflammatory, hepatic, and renal biomarkers were statistically related to the associations between IR-related indices and CLMM risk. RESULTS: During a median follow-up of 16.4 years, 8651 participants developed CLMM. All nine IR-related indices were positively associated with both CLMM incidence and progression (all P < 0.001), with TyG-WHtR and TyG-WC demonstrating comparatively stronger associations. For incident CLMM, each SD increase in TyG-WHtR and TyG-WC was associated with hazard ratios (HRs) of 2.08 (95% CI 2.04-2.12) and 2.14 (95% CI 2.10-2.19), respectively. In multistate analyses, each SD increase in TyG-WHtR and TyG-WC was associated with 59% (HR 1.59, 95% CI 1.58-1.60) and 62% (HR 1.62, 95% CI 1.61-1.63) higher risks of transitioning from a healthy state to a first CLM disease, 44% (HR 1.44, 95% CI 1.41-1.46) and 44% (HR 1.44, 95% CI 1.41-1.47) higher risks of progressing to CLMM, and 24% (HR 1.24, 95% CI 1.15-1.34) and 22% (HR 1.22, 95% CI 1.13-1.31) higher risks of progression to triple CLM diseases, respectively. Secondary predictive analyses indicated that all indices significantly improved incremental value and discrimination, with TyG-WHtR and TyG-WC exhibiting comparatively better performance (all P < 0.001). Biomarkers reflecting systemic inflammation and liver- and kidney-related function might statistically contribute to the observed associations, although these findings are exploratory and primarily hypothesis-generating. CONCLUSION: Nine IR-related indices were positively associated with the incidence and progression of CLMM, with TyG-WHtR and TyG-WC showing comparatively stronger associations and better predictive performance. These findings support their relevance for comparative CLMM risk assessment, while further validation is warranted. Exploratory biomarker analyses provided hypothesis-generating clues regarding biological domains potentially relevant to the associations.