Circulating immune biomarkers were associated with carotid ultrasound parameters, modestly increasing adjusted R² values compared to clinical covariates alone (e.g., cIMT, 0.109 vs 0.072).
Cohort (n=1,134)
Are circulating immune biomarkers associated with carotid ultrasound parameters in a stroke-free, multi-ethnic cohort?
Machine-learning analyses identified distinct candidate immune biomarker profiles associated with subclinical carotid disease phenotypes, supporting a role for immunometabolic pathways in vascular aging.
Inflammation contributes to atherosclerosis and vascular remodeling, but the immune pathways associated with distinct carotid ultrasound phenotypes, including carotid intima-media thickness (cIMT), maximal plaque thickness (MPT), and arterial stiffness remain incompletely characterized. We investigated associations between circulating immune biomarkers and carotid ultrasound measures in a stroke-free, multi-ethnic cohort. We analyzed data from 1,134 stroke-free participants (mean age 70 ± 9 years, 59% women, 66% Hispanic) in the Northern Manhattan Study (NOMAS) who underwent high-resolution B-mode carotid ultrasound. cIMT and MPT were measured using automated edge-detection software, while arterial stiffness was assessed via systolic and diastolic diameter measurements, strain, and β-stiffness. Plasma levels of 60 immune biomarkers were quantified using a multiplex immunoassay. Biomarker selection was performed using LASSO, Random Forest, and XGBoost; markers selected by ≥ 2 methods were prioritized. Associations were tested using multivariable linear regression adjusted for age, sex, race/ethnicity, and cardiovascular risk factors (hypertension, hyperlipidemia, diabetes, and smoking). Machine-learning analyses identified partially distinct candidate biomarker profiles for cIMT, MPT, and arterial stiffness. In fully adjusted regression models, greater cIMT was associated with higher IL-4 and leptin levels and lower IL-10, VCAM-1, and SerpinE1 levels. None of the machine-learning-selected biomarkers was independently associated with MPT at the conventional p < 0.05 threshold. Greater arterial stiffness was associated with higher SCF levels, while CXCL10 demonstrated a nonsignificant inverse trend. Models incorporating the selected biomarkers had modestly higher adjusted R² values than models containing clinical covariates alone (cIMT, 0.072 versus 0.109; MPT, 0.134 versus 0.147; arterial stiffness, 0.063 versus 0.075). In a stroke-free, multiethnic cohort, machine-learning analyses identified distinct and overlapping candidate immune biomarker profiles across cIMT, plaque thickness, and arterial stiffness. However, only a subset of selected biomarkers demonstrated independent associations in fully adjusted regression models. These findings support a hypothesis-generating role for inflammatory and immunometabolic pathways in subclinical carotid disease and vascular aging and require validation in longitudinal studies.
Khasiyev et al. (Mon,) conducted a cohort in Subclinical carotid disease (n=1,134). Circulating immune biomarkers vs. Clinical covariates alone was evaluated on Carotid intima-media thickness (cIMT), maximal plaque thickness (MPT), and arterial stiffness. Circulating immune biomarkers were associated with carotid ultrasound parameters, modestly increasing adjusted R² values compared to clinical covariates alone (e.g., cIMT, 0.109 vs 0.072).