Abstract 15716: Non-Targeted Metabolomic Profiling Identifies Novel Markers of Insulin Resistance
Background: Targeted metabolomic profiling has identified metabolite classes associated with insulin resistance (IR) and incident metabolic disease, including branched-chain (BCAAs) and aromatic amino acids (AAAs). Emerging non-targeted profiling methods, which facilitate screening of many-fold more metabolites, hold great promise for the identification of additional disease biomarkers and pathways. We developed a non-targeted workflow to determine differentially regulated metabolites in two groups that differed by the homeostatic model assessment of IR (HOMA-IR). Methods: We analyzed fasting plasma from subjects with IR (HOMA-IR ≥ 2.6) (mean age = 67 ± 1.49; BMI = 28 ± 0.63; HOMA-IR = 7.94 ± 1.67) and normal subjects (HOMA-IR ≤ 1.85) (mean age = 68 ± 2.42; BMI = 26 ± 0.86; HOMA-IR = 1.13 ± 0.08), using HILIC chromatography coupled to an Agilent™ 6550 iFunnel Q-TOF mass spectrometer operated in positive ion mode. Batch recursive metabolite feature extraction was performed using MH Profinder software followed by differential metabolite analysis and identification using MPP software. Results: We identified 56 differentially abundant compounds [p < 0.05; unpaired t-test with Benjamini-Hochberg FDR (B-H FDR) correction] in a derivation cohort (n=15 IR; n=15 control) and validated 28 of these compounds in a similarly sized independent cohort (p <0.05, BH-FDR corrected). As expected, we confirmed compounds known to be associated with IR, including the BCAA valine (p=2.9E-3), the AAA tryptophan (p=1.01E-2), and a hexanoylcarnitine (p=4.8E-2). In addition, we made putative identifications of novel compounds that were significantly elevated in IR subjects in both cohorts, including aminooctanoic acid (+41%, p=3.68E-3), methylhistidine (+92%, p=4.78E-3), and methylinosine (+51%, p=3.29E-2). Novel compounds that were significantly decreased in IR subjects included isovalerylglycine (-48%, p=2.03E-2). Conclusions: We have developed a non-targeted metabolite profiling platform and detected novel compounds associated with IR. Future work includes unambiguous identification and quantification of these metabolites using isotope-labeled standards, as well as evaluation of these markers in large, heterogeneous clinical populations.