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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.

Sec. General Cardiovascular Medicine

Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1523997

Use of serum long non-coding RNA expression panel as a marker for diabetic retinopathy

Provisionally accepted
Eric Zirui Wang Eric Zirui Wang 1Shali Chen Shali Chen 1Anorin Ali Anorin Ali 1Biao Feng Biao Feng 1Selina Liu Selina Liu 2John Gonder John Gonder 3Tom Sheidow Tom Sheidow 3Phil Hooper Phil Hooper 3Subrata Chakrabarti Subrata Chakrabarti 1,3,4*
  • 1 Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
  • 2 Centre for Diabetes, Endocrinology, and Metabolism, St. Joseph's Hospital, London, Canada
  • 3 Ivey Eye Institute, St. Joseph's Hospital, London, Canada
  • 4 Department of Pathology and Laboratory Medicine, London Health Sciences Centre, London, Canada

The final, formatted version of the article will be published soon.

    Introduction Diabetic retinopathy (DR) is the most common chronic complication of diabetes, the leading cause of vision impairments in working-aged adults, and a significant cause of reduced quality of life for diabetic patients. Diabetic patients are recommended to have regular screening in order to catch DR at an early enough stage for effective management. However, due to a variety of factors, many patients can still fall through the cracks with the current screening methods.Methods Several long non-coding RNAs (lncRNAs), essential regulators of physiological and pathological processes, were previously identified by us as potential markers for DR phenotypes.In this study, we used a significantly larger sample set to validate our panel of lncRNAs. We also explored the possibility of creating a statistical model to detect DR from serum samples using the expression profiles of these lncRNAs.Our regression models, based solely on lncRNA expression data, demonstrated the ability to adequately detect DR and potentially predict it. Models based solely on lncRNA expression performed equally or better compared to models with additional patient information. The models showed promising performance, suggesting that serum lncRNA expression profiles could serve as reliable markers for DR detection.Further longitudinal studies are necessary to validate the model's capability to predict retinopathy in diabetic patients not yet diagnosed with DR. Nevertheless, our findings indicate that this lncRNA panel may offer a viable option for a simple, accessible, and convenient blood-based screening test for DR.

    Keywords: long non-coding RNA, Diabetic Retinopathy, epigenetics, diagnosis, biomarker

    Received: 06 Nov 2024; Accepted: 25 Mar 2025.

    Copyright: © 2025 Wang, Chen, Ali, Feng, Liu, Gonder, Sheidow, Hooper and Chakrabarti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Subrata Chakrabarti, Department of Pathology and Laboratory Medicine, Western University, London, N6A 3K7, Ontario, Canada

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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