Genetic Modulation of LDL-C and Triglyceride Response to Mediterranean-Style Diet: Whole-Exome Evidence with a Focus on Plasma Lipoprotein Pathways

Background/Objectives: Inter-individual variability in lipid response to dietary modification highlights the need for precision nutrition. Current evidence is fragmented and primarily based on a limited set of historical candidate genes. To address these gaps and facilitate broader discovery, this study investigated whether exome-wide genetic variation is associated with changes in LDL cholesterol (LDL-C) and triglycerides (TAG) following a Mediterranean-style diet. Methods: A longitudinal study was conducted with 51 dyslipidemic patients who underwent a 2–6 month Mediterranean-style dietary intervention. High-depth whole-exome sequencing (mean 112×) was performed, and a two-tier analytical approach was used: an exploratory exome-wide association analysis to identify novel loci, and a targeted gene-level analysis of the 'Plasma Lipoprotein Assembly, Remodeling, and Clearance' pathway to prioritize biologically plausible signals. Results: The intervention resulted in significant reductions in LDL-C (mean -33.4 mg/dL) and TAG (-17.9 mg/dL). genome-wide association study (GWAS) identified top signals in ABCA2 (LDL-C response, p = 2.05 × 10^⁻5) and ABCA7 (TAG response, p = 5.48 × 10^⁻5). Targeted pathway analysis revealed the strongest gene-level associations for LDL-C change in APOC3, APOC2, and adaptor protein complex subunits AP2A1 and AP2A2 (Simes p = 0.007–0.018; false discovery rate (FDR) = 0.21), while APOB (Simes p = 0.010; FDR = 0.46) was the top signal for TAG change. These loci implicate convergent mechanisms involving triglyceride-rich lipoprotein remodeling and clathrin-dependent receptor trafficking. Conclusions: The results suggest that genetic modulation of dietary lipid response involves distributed effects within biologically coherent pathways rather than single high-impact variants. By combining exploratory genome-wide screening with process-focused gene prioritization, this demonstrates a pragmatic framework for identifying functional candidates to inform genetically guided dietary recommendations.