Predicting Skeletal Muscle and Whole-Body Insulin Sensitivity Using NMR-Metabolomic Profiling

• Published in: Journal of the Endocrine Society 2020-04, Vol.4 (4), p.bvaa026-bvaa026
• Main Authors: Klén, Riku, Honka, Miikka-Juhani, Hannukainen, Jarna C, Huovinen, Ville, Bucci, Marco, Latva-Rasku, Aino, Venäläinen, Mikko S, Kalliokoski, Kari K, Virtanen, Kirsi A, Lautamäki, Riikka, Iozzo, Patricia, Elo, Laura L, Nuutila, Pirjo
• Format: Article
• Language: English
• Subjects: Amino acids; Clinical; Dextrose; Glucose; Insulin; Insulin resistance; Metabolites; Muscles; Nuclear magnetic resonance spectroscopy; PET imaging; Type 2 diabetes
• ISSN: 2472-1972; 2472-1972
• DOI: 10.1210/jendso/bvaa026

Abstract Purpose Abnormal lipoprotein and amino acid profiles are associated with insulin resistance and may help to identify this condition. The aim of this study was to create models estimating skeletal muscle and whole-body insulin sensitivity using fasting metabolite profiles and common clinical and laboratory measures. Material and Methods The cross-sectional study population included 259 subjects with normal or impaired fasting glucose or type 2 diabetes in whom skeletal muscle and whole-body insulin sensitivity (M-value) were measured during euglycemic hyperinsulinemic clamp. Muscle glucose uptake (GU) was measured directly using [18F]FDG-PET. Serum metabolites were measured using nuclear magnetic resonance (NMR) spectroscopy. We used linear regression to build the models for the muscle GU (Muscle-insulin sensitivity index [ISI]) and M-value (whole-body [WB]-ISI). The models were created and tested using randomly selected training (n = 173) and test groups (n = 86). The models were compared to common fasting indices of insulin sensitivity, homeostatic model assessment—insulin resistance (HOMA-IR) and the revised quantitative insulin sensitivity check index (QUICKI). Results WB-ISI had higher correlation with actual M-value than HOMA-IR or revised QUICKI (ρ = 0.83 vs −0.67 and 0.66; P