Abdominal aortic aneurysm (AAA) is hallmarked by irreversible dilation of the infrarenal aorta. Lipid deposition in the aortic wall and the potential importance of a lipid disorder in AAA etiology highlight the need to explore lipid variation during AAA development. This study aimed to systematically characterize the lipidomics associated with AAA size and progression. Plasma lipids from 106 subjects (36 non-AAA controls and 70 AAA patients) were comprehensively analyzed using untargeted lipidomics. An AAA animal model was established by embedding angiotensin-II pump in ApoE^-/- mice for four weeks and blood was collected at 0, 2 and 4 weeks for lipidomic analysis. Using a false-discovery rate (FDR) < 0.05, a group of lysophosphatidylcholines (lysoPCs) were specifically decreased in AAA patients and mice. LysoPCs were principally lower in the AAA patients with larger diameter (diameter > 50 mm) than those with a smaller size (30 mm < diameter < 50 mm), and levels of lysoPCs were also found to be decreased with modelling time and aneurysm formation in AAA mice. Correlation matrices between lipids and clinical characteristics identified that the positive correlation between lysoPCs and HDL-c was reduced and negative correlations between lysoPCs and CAD rate, lysoPCs and hsCRP were converted to positive correlations in AAA compared to control. Weakened positive correlations between plasma lysoPCs and circulating HDL-c in AAA suggested that HDL-lysoPCs may elicit instinctive physiological effects in AAA. This study provides evidence that reduced lysoPCs essentially underlie the pathogenesis of AAA and that lysoPCs are promising biomarkers for AAA development.

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.

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.