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Abstract

Aims: Dyslipidemia represents a critical cardiovascular risk factor in type 2 diabetes mellitus (T2DM), yet distinct metabolic phenotypes and their therapeutic implications remain inadequately characterized in Saudi populations. This study aimed to identify dyslipidemia phenotypes, establish therapeutic hierarchies, and examine metabolic determinants in Saudi T2DM patients.

Methods: A cross-sectional study enrolled 406 T2DM patients at Madinah Diabetic Center, Saudi Arabia (August-December 2024). Comprehensive sociodemographic, clinical, lifestyle, and laboratory data were collected. Statistical analyses included cluster analysis for phenotype identification, multivariate linear regression for lipid determinants, and chi-square tests for categorical associations. Ethical approval was obtained from IRB-Madinah (H-03-M-84).

Results: Dyslipidemia prevalence reached 78.4%, with low HDL-C affecting 79.6% and elevated triglycerides in 67.2% of participants. Three distinct phenotypes emerged: severe atherogenic (23.4%), moderate mixed (34.2%), and isolated dyslipidemia (42.4%). Statin therapy demonstrated universal benefit across all lipid parameters (LDL-C: β= –42.3 mg/dL, P < 0.001; triglycerides: β= –28.4 mg/dL, P < 0.001; HDL-C: β= +3.2 mg/dL, P < 0.001). Gender-specific patterns showed males with higher triglycerides (β= +18.6 mg/dL, P = 0.003) and lower HDL-C (β= –6.4 mg/dL, P < 0.001). Notably, glycemic control (HbA1c, P = 0.234), BMI (P = 0.567), and diabetes duration (P = 0.421) showed no significant lipid associations, challenging conventional paradigms.

Conclusion: This study establishes metabolic phenotyping and precision medicine approaches for diabetic dyslipidemia management. The identification of distinct phenotypes, demonstration of statin therapy as universal first-line treatment, recognition of gender-specific metabolic programming, and evidence for glycemic-independent lipid pathophysiology fundamentally reframe dyslipidemia as requiring dedicated therapeutic strategies beyond glucose control. The developed risk stratification framework provides immediate clinical tools for personalized diabetes care.

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