Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study.
G, C., Y, L., D, W., P, L., H, Z., Y, W., Y, C., & Z, C. (2026). Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study.. Frontiers in endocrinology. https://doi.org/10.3389/fendo.2026.1901020
G C, Y L, D W, P L, H Z, Y W, et al. Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study.. Frontiers in endocrinology. 2026; doi: 10.3389/fendo.2026.1901020
G C, Y L, D W, et al. Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study.[J]. Frontiers in endocrinology. 2026. DOI: 10.3389/fendo.2026.1901020.
@article{g2026,
author = {Chen G and Lan Y and Wu D and Liu P and Zheng H and Wang Y and Chen Y and Chen Z},
title = {Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study.},
journal = {Frontiers in endocrinology},
year = {2026},
doi = {10.3389/fendo.2026.1901020},
note = {PMID: 42666193},
}
TY - JOUR AU - Chen G AU - Lan Y AU - Wu D AU - Liu P AU - Zheng H AU - Wang Y AU - Chen Y AU - Chen Z TI - Metabolic, inflammatory, and lipoprotein(a)-related risk profiling for incident ASCVD: a multi-biomarker study. T2 - Frontiers in endocrinology PY - 2026 DO - 10.3389/fendo.2026.1901020 AN - PMID:42666193 ER -
AIMS: Metabolic dysfunction, inflammation, and lipoprotein(a) [Lp(a)] reflect different biomarker domains associated with atherosclerotic cardiovascular disease (ASCVD) risk. We examined the individual and joint associations of the triglyceride-glucose (TyG) index, high-sensitivity C-reactive protein (hs-CRP), and Lp(a) with incident ASCVD. Coronary heart disease (CHD) and stroke were analyzed as exploratory subtype outcomes of ASCVD. METHODS: We included 320,506 UK Biobank participants free of ASCVD at baseline. TyG, hs-CRP, and Lp(a) were analyzed in quintiles, and elevated biomarkers were defined as values in the fifth quintile. Incident outcomes were assessed using multivariable-adjusted weighted Cox models. RESULTS: Over a median follow-up of 13.88 years, 32,743 ASCVD events occurred. Compared with the lowest quintile, the highest quintile of TyG, hs-CRP, and Lp(a) was associated with higher ASCVD risk, with hazard ratios (HRs) of 1.32 (95% CI 1.27-1.38), 1.36 (1.30-1.43), and 1.23 (1.19-1.27), respectively. In exploratory analyses of ASCVD subtypes, the associations appeared generally more pronounced for CHD than for stroke. ASCVD risk increased progressively with the number of elevated biomarkers: HRs were 1.18 (1.15-1.21), 1.48 (1.42-1.53), and 1.85 (1.68-2.03) for one, two, and three elevated biomarkers, respectively. When the eight possible biomarker combinations were examined separately, concurrent elevation of TyG, hs-CRP, and Lp(a) identified the highest-risk profile for ASCVD (HR 1.90, 95% CI 1.71-2.11). CONCLUSIONS: TyG, hs-CRP, and Lp(a) provide complementary information for ASCVD risk stratification. Multi-biomarker profiling may help identify individuals with higher cardiometabolic risk than single-biomarker assessment alone.