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Abstract
Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body mass index, we calculated associations between parameters of whole-body positron emission tomography (PET)/magnetic resonance imaging (MRI) during hyperinsulinemic euglycemic clamp and non-targeted metabolomics profiling for subcutaneous adipose tissue (SAT) and plasma. Plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Visceral adipose tissue (VAT) and SAT insulin sensitivity (Ki), were positively associated with several lysophospholipids, while the opposite applied to branched-chain amino acids. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. Bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Furthermore, we detected several metabolites that were significantly higher in T2D than normal/prediabetes. In this study we present novel associations between several metabolites from SAT and plasma with the fat fraction, volume and insulin sensitivity of various tissues throughout the body, demonstrating the benefit of an integrative multi-omics approach.
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1 Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
2 Department of Surgical Sciences, section of Radiology, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
3 Department of Medical Sciences, Clinical Diabetes and Metabolism, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
4 Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
5 Translational Science & Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden (GRID:grid.418151.8) (ISNI:0000 0001 1519 6403); Karolinska Institute/AstraZeneca Integrated CardioMetabolic Centre (KI/AZ ICMC), Department of Medicine, Novum, Sweden (GRID:grid.418151.8)
6 Pharmaceutical Technology & Development, AstraZeneca AB, Gothenburg, Sweden (GRID:grid.418151.8); Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X)
7 Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457)
8 Department of Surgical Sciences, section of Radiology, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457); Antaros Medical AB, Mölndal, Sweden (GRID:grid.8993.b)
9 Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (GRID:grid.8993.b) (ISNI:0000 0004 1936 9457); Institute of Computer Science, PAN, Warsaw, Poland (GRID:grid.425308.8) (ISNI:0000 0001 2158 4832)