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Cureus · 2025

Unraveling the Association Between Novel Lipid Biomarkers and Metabolic Syndrome: A Cross-Sectional Study.

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Chatterjee Bijoya, Mahant Hardik N, Chatterjee Biswas Prasanta, Nagda Jay, Modi Nikunj

Аннотация

Background Metabolic syndrome (MetS) is a major public-health concern that substantially increases the risk of cardiovascular disease and type 2 diabetes. Traditional lipid profiles may not fully capture the atherogenic burden in MetS, prompting investigation of novel lipid biomarkers, such as lipoprotein(a) (Lp(a)), apolipoproteins, and the Comprehensive Lipid Tetrad Index (CLTI). This study evaluated the association of these biomarkers with MetS in an Indian outpatient population. Methods In a cross-sectional study of 707 adults aged 25-75 years at a tertiary care hospital in Jamnagar, Gujarat, MetS was diagnosed using NCEP-ATP III criteria. Serum Lp(a), apolipoprotein A-I (Apo A-I), apolipoprotein B (Apo B), and CLTI were measured using standard methods. Associations were tested using Chi-square analyses and logistic regression, and diagnostic performance was assessed by receiver operating characteristic (ROC) curve analysis. Results MetS was present in 397/707 (56.15%) participants, occurring in 197/332 (59.34%) of females and 200/375 (53.33%) of males. Elevated Lp(a), elevated Apo B, elevated CLTI, and reduced Apo A-I were all significantly associated with MetS (p < 0.001 for each). ROC analysis demonstrated the highest diagnostic accuracy for CLTI (area under the curve, or AUC = 0.835, 95% CI 0.806-0.862), followed by Lp(a) (AUC = 0.760, 95% CI 0.730-0.794), Apo B (AUC = 0.700, 95% CI 0.665-0.734), and Apo A-I (AUC = 0.620, 95% CI 0.584-0.657). Multivariable logistic regression identified elevated blood pressure, low high-density lipoprotein cholesterol, and elevated triglycerides as significant predictors of abnormal biomarker levels. Conclusion In this Indian outpatient cohort, CLTI and Lp(a) showed strong predictive value for MetS, and outperformed Apo A-I and Apo B when used alone. Incorporating CLTI and Lp(a) into clinical assessment may improve early detection and risk stratification in individuals at risk of MetS.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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