The pathogenesis of cardiovascular diseases (CVDs) is intimately linked to cholesterol dysregulation. While high-density lipoprotein cholesterol (HDL-C) is classically considered cardioprotective, contemporary epidemiological evidence reveals a noncausal, often U-shaped, relationship with CVD risk. Static measurements of HDL-C obscure the structural and functional heterogeneity of circulating HDL particles. Under pathological stress, HDL undergoes extensive structural remodeling into dysfunctional HDL, thereby losing its vasculoprotective properties and instead mediating proatherogenic and proinflammatory responses. This review critically evaluates the biogenesis, maturation, and metabolic trajectory of HDL. By integrating recent advancements in proteomics and lipidomics, we map the intricate compositional shifts within HDL subpopulations and clarify the regulatory roles of HDL-associated microRNAs in intercellular communication. We investigate the specific drivers of HDL dysfunction, which is often exacerbated by comorbidities such as diabetes and chronic kidney disease. Furthermore, we outline the methodological transition from automated homogeneous HDL-C quantification to multidimensional profiling. Shifting the clinical focus from HDL quantity to functional quality resolves the HDL-C paradox, helping to drive the development of precision lipidology and targeted therapies to reverse HDL dysfunction in CVDs.

Abdominal aortic aneurysm (AAA) is a progressive and often asymptomatic vascular disease associated with high mortality after rupture, but reliable circulating biomarkers for noninvasive detection remain limited. We aimed to identify and validate plasma protein biomarkers for AAA using an integrated proteomics-based approach. Plasma samples from 22 patients with AAA and 22 healthy controls were analyzed through data-independent acquisition (DIA) mass spectrometry. Differentially expressed proteins were subjected to bioinformatic analyses, including Gene Ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein–protein interaction, and weighted gene coexpression network analyses. Candidate biomarkers were selected on the basis of differential abundance, diagnostic performance, and biological relevance and subsequently validated by enzyme-linked immunosorbent assay in an independent cohort comprising 93 patients with AAA and 83 non-AAA controls. DIA proteomics identified 111 differentially abundant proteins, revealing enrichment of pathways related to mitochondrial respiration, oxidative stress, inflammation, extracellular matrix remodeling, and proteostasis. Among the candidates, plasma CHRDL1 levels were significantly reduced, whereas OGN and CCL18 levels were significantly elevated in patients with AAA; these findings were consistently confirmed in the validation cohort. A combined three-protein model demonstrated strong diagnostic performance, with an area under the receiver operating characteristic curve of 0.890. These findings identify CHRDL1, OGN, and CCL18 as promising plasma biomarkers for AAA detection and further highlight mitochondrial dysfunction, chronic inflammation, ECM remodeling, and dysregulated proteostasis as key molecular features of AAA.