Integration of Proteomic and Lipidomic Analysis Reveals Potential Markers of Insulin Resistance in Young Children With Obesity.

Objective: This study aimed to identify novel proteomic and lipidomic biomarkers of insulin resistance (IR) in young children with obesity and to assess the ability of hub lipids and proteins in the diagnosis of IR. Methods: The discovery cohort consisted of 50 prepubertal children, including 30 children with obesity and 20 lean. The validation cohort included 25 children with obesity and IR (obese-IR) and 25 children with obesity without IR (obese-NIR). Fasting plasma was collected from all participants for Olink proteomics and untargeted lipidomics. Pearson correlation analysis was used to identify proteins and lipids associated with IR, and area under the receiver operating characteristic (AUROC) was applied to compare the ability of the identified proteins and lipids with traditional indices in the diagnosis of IR. Results: In the discovery cohort, a total of 15 lipids and 10 proteins had significant correlation with IR. In the validation cohort, protein fatty acid binding protein 4 (FABP4) and gene serpin family E member 1 (PAI) were overexpressed in obese-IR children compared to obese-NIR children, while insulin like growth factor binding protein 1 (IGFBP-1) and paraoxonase 3 (PON3) were lower in the IR group than in the obese-NIR group; five lipids including sphingosine (d16:0), coenzyme (Q8), ceramides phosphate (d42:2), phosphatidylethanolamine (37:2e), and phosphatidylcholine (18:1e_16:0), showed significant (p < 0.05) change in obese-IR children compared to obese-NIR children. In addition, the AUC-ROC was 0.89 for IGFBP-1, 0.81 for PON3, and 0.65 for PAI. The ability of IGFBP-1, PON3, and PAI to diagnose IR was better than that of adiponectin and leptin. The AUROC of phosphatidylcholine (18:1e_16:0) and coenzyme (Q8) were 0.80 and 0.73, respectively, which was significantly higher than the AUROC of triglycerides(TGs), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Conclusion: Proteomic and lipidomic analysis can allow for the identification of potential new candidate biomarkers for IR. The ability of novel biomarkers to diagnose IR was better than traditional indicators. Trial Registration: Chinese Clinical Trial Registry: ChiCTR2300072179.