HDL-related biomarkers after acute ischemic stroke: HDL particle remodeling, HDL-C–based immune–lipid ratios, and clinical interpretation

Abstract Acute ischemic stroke (AIS) induces neurovascular injury and systemic inflammatory and metabolic responses that alter high-density lipoprotein (HDL) particles. HDL-cholesterol (HDL-C) measures cholesterol mass in HDL particles but does not report particle composition or biological function. Ratios using HDL-C as the denominator have emerged as candidate biomarkers, but their biological specificity and clinical meaning remain uncertain. This critical narrative review evaluates three evidence domains: directly measured HDL particle remodeling and function after AIS; HDL-C-based immune–lipid ratios, including monocyte/HDL-C, neutrophil/HDL-C, high-sensitivity C-reactive protein/HDL-C and white blood cell/HDL-C; and thromboinflammatory mechanisms relevant to their interpretation. Human AIS studies report altered cholesterol efflux, paraoxonase-1 activity, HDL particle cargo and antioxidant capacity, but cohorts and assays remain limited. Routine ratios show observational associations with outcomes, yet are epidemiological composites, not functional assays or proof of immune–lipid interaction, and ratio-specific genetic architecture or causality has not been established. Here, serial immune–lipid profiling means repeated, prespecified measurement of leukocyte counts, high-sensitivity C-reactive protein, HDL-C and ratios, whereas direct HDL functional assays constitute a separate research tier and are not validated for routine care. Post-stroke immune–HDL mismatch remains a provisional framework requiring immune activation and directly measured HDL functional impairment. Current clinical and imaging predictors remain indispensable but incompletely capture evolving systemic inflammation and metabolism. HDL-related biomarkers should not replace them; validation requires standardized sampling, external cohorts and reproducible incremental prognostic or decision value beyond established predictors.