Background: The lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear.
Objective: To identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980).
Methods: Linear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p < 0.001), in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 590).
Results: In GOLDN, 319 lipids were associated with the LPIR score (false discovery rate-adjusted p-values ranging from 4.59 × 10- 161 to 49.50 × 10- 3). Factors 1 (triglycerides and diglycerides/storage lipids) and 3 (mixed lipids) were positively (β = 0.025, p = 4.52 × 10- 71 and β = 0.021, p = 5.84 × 10- 41, respectively) and factor 2 (phospholipids/non-storage lipids) was inversely (β = - 0.013, p = 2.28 × 10- 18) associated with the LPIR score. These findings were replicated for HOMA-IR in the HAPI Heart Study (β = 0.10, p = 1.21 × 10- 02 for storage, β = - 0.13, p = 3.14 × 10- 04 for non-storage, and β = 0.19, p = 8.40 × 10- 07 for mixed lipids).
Conclusions: Non-storage lipidomics species show a significant inverse association with the LPIR metabolic dysfunction score and present a promising focus for future therapeutic and prevention studies.
Keywords: Diglyceride; GOLDN; Insulin resistance; Lipidomics; Lipids; Lipoprotein; Phospholipid; Triglyceride.