Jiang H, Henley D, Jiang FX. Potentially novel surrogate biomarker for diagnosing insulin resistance in type 2 diabetes. World J Diabetes 2025; 16(11): 113457 [DOI: 10.4239/wjd.v16.i11.113457]
Corresponding Author of This Article
Fang-Xu Jiang, PhD, Adjunct Associate Professor, School of Biomedical Sciences, The University of Western Australia, 35 Stirling Hwy, Crawley, Perth 6009, Australia. fang-xu.jiang@perkins.uwa.edu.au
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Letter to the Editor
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Diabetes. Nov 15, 2025; 16(11): 113457 Published online Nov 15, 2025. doi: 10.4239/wjd.v16.i11.113457
Potentially novel surrogate biomarker for diagnosing insulin resistance in type 2 diabetes
Helen Jiang, David Henley, Fang-Xu Jiang
Helen Jiang, Department of Medicine, Northern Health, Melbourne 3076, Victoria, Australia
David Henley, Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Perth 6009, Australia
David Henley, Medical School, The University of Western Australia, Perth 6009, Australia
Fang-Xu Jiang, School of Biomedical Sciences, The University of Western Australia, Perth 6009, Australia
Author contributions: Jiang H, Henley D and Jiang FX reviewed and edited this manuscript; Jiang H wrote the original draft; Jiang FX created the original figure; and all authors have read and approved the final manuscript.
Conflict-of-interest statement: All authors declare no relevant conflict-of-interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fang-Xu Jiang, PhD, Adjunct Associate Professor, School of Biomedical Sciences, The University of Western Australia, 35 Stirling Hwy, Crawley, Perth 6009, Australia. fang-xu.jiang@perkins.uwa.edu.au
Received: August 26, 2025 Revised: September 16, 2025 Accepted: October 23, 2025 Published online: November 15, 2025 Processing time: 80 Days and 12.3 Hours
Abstract
Type 2 diabetes mellitus (T2DM) and obesity are growing global pandemics that shares the common characteristic of insulin resistance (IR). IR leads to progressive β-cell failure, worsening T2DM and its cardiovascular complications. Thus, early diagnosis of IR is important to prevent and reverse β-cell dedifferentiation. However, there is a lack of accessible, non-invasive and affordable tools to early diagnose and stratify IR. The gold standard method used in the research setting is the hyperinsulinemic-euglycemic clamp, however it is invasive, laborious, expensive and difficult to apply at a large scale. Hou et al presents a potential novel surrogate biomarker for diagnosing IR in T2DM. Magnetic resonance imaging derived biomarkers can potentially become the accessible and non-invasive alternative to the hyperinsulinemic-euglycemic clamp, enabling the timely diagnosis of IR with potential clinical applications in T2DM treatments and preventative care.
Core Tip: Hou et al presents a potential novel surrogate biomarker for diagnosing insulin resistance (IR) in type 2 diabetes mellitus. Their study demonstrates magnetic resonance imaging-derived multiparametric biomarkers for IR at the L4-L5 paravertebral muscles. If validated, this represents an accessible and non-invasive tool for early diagnosis of IR with potential clinical diagnostic applications.
