# Illuminating Glucose: How to Unveil Organ‐Specific Insulin Resistance and Guide Metabolic Strategies in Diabetes

**Authors:** Shawn Gugliandolo, Cassandra Morciano, Lucia Leccisotti, Umberto Capece, Gianfranco Di Giuseppe, Teresa Mezza, Gea Ciccarelli, Laura Soldovieri, Michela Brunetti, Adriana Avolio, Amelia Splendore, Alfredo Pontecorvi, Andrea Giaccari, Francesca Cinti

PMC · DOI: 10.1002/dmrr.70162 · 2026-03-25

## TL;DR

This paper reviews how imaging techniques can reveal organ-specific insulin resistance, offering new ways to personalize diabetes treatment.

## Contribution

The paper introduces the use of PET imaging with [18F]FDG to map organ-specific glucose metabolism in diabetes.

## Key findings

- PET imaging with [18F]FDG reveals organ-specific glucose uptake in metabolic conditions like T2D.
- Insulin resistance varies across organs such as muscle, liver, and adipose tissue.
- Dynamic imaging can guide personalized metabolic strategies for diabetes management.

## Abstract

Recent evidence has shown that muscle insulin resistance is not the only factor contributing to type 2 diabetes (T2D). Organ‐specific insulin resistance is increasingly recognised as a significant contributor to the metabolic changes that lead to hyperglycemia, although the precise extent of its impact remains unclear. The qualitative and quantitative aspects of regional insulin‐resistance in determining whole body insulin resistance and glucose uptake can be explored through positron emission tomography (PET) combined with computerised tomography images, using specific radio tracers like 2‐deoxy‐2‐[18F]fluoro‐D‐glucose ([18F]FDG). This approach provides new insight into organ‐specific glucose uptake allowing the visualisation of glucose metabolism. This review article seeks to highlight key findings from dynamic imaging, in terms of glucose uptake, focussing on the specific compartments (muscle, liver, adipose organ, heart, kidney and brain) in different metabolic conditions, such as insulin resistance and T2D, and during metabolic treatment. In essence, mapping these distinct organ contributions in the orchestra of glucose metabolism is forging a new frontier in personalised diabetes management, allowing for treatments uniquely tailored to individual metabolic needs.

## Linked entities

- **Chemicals:** [18F]FDG (PubChem CID 68614), 2-deoxy-2-[18F]fluoro-D-glucose (PubChem CID 68614)
- **Diseases:** type 2 diabetes (MONDO:0005148)

## Full-text entities

- **Genes:** SLC5A2 (solute carrier family 5 member 2) [NCBI Gene 6524] {aka SGLT2}, IARS1 (isoleucyl-tRNA synthetase 1) [NCBI Gene 3376] {aka GRIDHH, IARS, ILERS, ILRS, IRS, PRO0785}, APOE (apolipoprotein E) [NCBI Gene 348] {aka AD2, APO-E, ApoE4, LDLCQ5, LPG}, MTOR (mechanistic target of rapamycin kinase) [NCBI Gene 2475] {aka FRAP, FRAP1, FRAP2, RAFT1, RAPT1, SKS}, G6PC1 (glucose-6-phosphatase catalytic subunit 1) [NCBI Gene 2538] {aka G6PC, G6PT, G6Pase, GSD1, GSD1a}, SLC2A4 (solute carrier family 2 member 4) [NCBI Gene 6517] {aka GLUT4}, SLC2A3 (solute carrier family 2 member 3) [NCBI Gene 6515] {aka GLUT3}, INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, GLP1R (glucagon like peptide 1 receptor) [NCBI Gene 2740] {aka GLP-1, GLP-1-R, GLP-1R}, IGKV4-1 (immunoglobulin kappa variable 4-1) [NCBI Gene 28908] {aka B3, IGKV41}, SLC2A2 (solute carrier family 2 member 2) [NCBI Gene 6514] {aka GLUT2}, SLC2A1 (solute carrier family 2 member 1) [NCBI Gene 6513] {aka CSE, DYT17, DYT18, DYT9, EIG12, GLUT}, HK1 (hexokinase 1) [NCBI Gene 3098] {aka CNSHA5, HK, HK1-ta, HK1-tb, HK1-tc, HKD}, GPR83 (G protein-coupled receptor 83) [NCBI Gene 10888] {aka GIR, GPR72}
- **Diseases:** fibrosis (MESH:D005355), cancer (MESH:D009369), adiposity (MESH:D018205), IFG (MESH:D007003), inflammation (MESH:D007249), MASLD (MESH:D005234), visceral adiposity (MESH:D007418), HEC (MESH:D044903), liver failure (MESH:D017093), metabolic syndrome (MESH:D024821), hypoxic (MESH:D002534), hyperglycemia (MESH:D006943), amyloid (MESH:C000718787), T2D (MESH:D003924), obese (MESH:D009765), MBF (MESH:D054318), Hyperinsulinemia (MESH:D006946), hepatic insulin resistance (MESH:D007333), neurofibrillary (MESH:D055956), beta cell dysfunction (MESH:D007340), neurodegeneration (MESH:D019636), coronary artery disease (MESH:D003324), impaired glucose uptake (MESH:C536778), Diabetes (MESH:D003920), ischaemia (MESH:D007511), cognitive decline (MESH:D003072), adipose organ (MESH:D000092124), HGP (MESH:D018149), cardiovascular diseases (MESH:D002318), muscle (MESH:D019042), type 1 diabetes (MESH:D003922)
- **Chemicals:** glycogen (MESH:D006003), blood glucose (MESH:D001786), rosiglitazone (MESH:D000077154), Glucose (MESH:D005947), 18F (MESH:C000615276), FFA (MESH:D005230), thiazolidinedione (MESH:C089946), ATP (MESH:D000255), Metformin (MESH:D008687), carbohydrate (MESH:D002241), glucose-6-phosphate (MESH:D019298), lactate (MESH:D019344), fatty acid (MESH:D005227), 2-deoxy-2-[18F]fluoro-D-glucose (MESH:D019788), oxygen (MESH:D010100), 18F]FDG (-), beta-hydroxy-butyrate (MESH:D020155), nitric oxide (MESH:D009569), dapagliflozin (MESH:C529054), ketone (MESH:D007659), mirabegron (MESH:C520025), RA (MESH:D011883)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC13018302/full.md

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Source: https://tomesphere.com/paper/PMC13018302