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Retrospective Study
Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Diabetes. Aug 15, 2026; 17(8): 122101
Published online Aug 15, 2026. doi: 10.4239/wjd.122101
Non-antibody biomarkers for differentiating ketosis-onset diabetes: A retrospective study
Si-Qi Pei, Jie-Ling Ren, Li Zhang, Yan-Xia Gao, Xia Yang, Xiang Liu, Su-Ning Li, Ping Liu, Xiao-Yan Xu
Si-Qi Pei, Department of Endocrinology, The First People’s Hospital of Yinchuan, Yinchuan 750000, Ningxia Hui Autonomous Region, China
Jie-Ling Ren, Department of Endocrinology and Rheumatology, 3201 Hospital, General Medical Group, Hanzhong 723000, Shaanxi Province, China
Li Zhang, Yan-Xia Gao, Xia Yang, Xiang Liu, Su-Ning Li, Xiao-Yan Xu, Department of Endocrinology, General Hospital of Ningxia Medical University, Yinchuan 750000, Ningxia Hui Autonomous Region, China
Ping Liu, Department of Endocrinology, Longgang District People’s Hospital of Shenzhen, Shenzhen 518172, Guangdong Province, China
Co-corresponding authors: Ping Liu and Xiao-Yan Xu.
Author contributions: Pei SQ drafted the manuscript; Pei SQ, Ren JL, and Zhang L participated in data collection, analysis, and interpretation; Pei SQ and Liu P contributed to the conception and design of the study; Gao YX, Yang X, Liu X, Li SN, and Xu XY accessed and validated the study data; Liu P and Xu XY contributed equally to this manuscript and are co-corresponding authors. All authors critically revised the manuscript, gave final approval for publication, agreed to be accountable for all aspects of the work and for the decision to submit the manuscript for publication.
AI contribution statement: Portions of this manuscript were edited using AI tools solely for language refinement. The authors carefully reviewed and verified all AI-assisted outputs and take full responsibility for the scientific content of the manuscript. AI tools were not used to generate original research data, conduct independent analyses, interpret results autonomously, or draw scientific conclusions. All scientific reasoning, methodological decisions, data interpretation, and conclusions were developed and validated exclusively by the authors.
Institutional review board statement: The study was approved by the Ethics Committee of General Hospital of Ningxia Medical University (Approval No. KYLL-2025-2436).
Informed consent statement: The informed consent was waived due to its retrospective design.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
Corresponding author: Ping Liu, Professor, Department of Endocrinology, Longgang District People’s Hospital of Shenzhen, No. 53 Aixin Road, Yuyuan Community, Longcheng Subdistrict, Shenzhen 518172, Guangdong Province, China. hanner752003@163.com
Received: April 10, 2026
Revised: May 13, 2026
Accepted: July 3, 2026
Published online: August 15, 2026
Processing time: 117 Days and 20.6 Hours
Abstract
BACKGROUND

Adults presenting with ketosis or diabetic ketoacidosis at diabetes onset pose a diagnostic challenge because ketosis-prone (KP) type 2 diabetes mellitus (T2DM) and latent autoimmune diabetes in adults (LADAs) share overlapping clinical features but require fundamentally different long-term management strategies. In many clinical settings, limited access to islet autoantibody testing further complicates early classification.

AIM

To characterize the clinical, metabolic, and endocrine features of ketosis-onset diabetes in adults and to identify potential non-antibody biomarkers to differentiate LADA from KP-T2DM and distinguish ketosis-onset from nonketotic diabetes.

METHODS

A total of 294 newly diagnosed adult patients were classified into LADA, KP-T2DM, and nonketotic T2DM groups. Clinical and metabolic characteristics were compared. Multivariable logistic regression was performed to identify factors associated with ketosis onset and LADA classification, and receiver operating characteristic analysis was used to evaluate the discriminatory performance of candidate biomarkers.

RESULTS

LADA accounted for 27.3% of ketosis-onset cases. Compared with patients with KP-T2DM, those with LADA exhibited significantly impaired β-cell function and lower insulin resistance. Multivariable analysis identified postprandial C-peptide as the strongest independent discriminator between LADA and KP-T2DM. Receiver operating characteristic analysis demonstrated that 2-hour C-peptide showed good discriminatory performance for differentiating LADA from KP-T2DM (area under the curve = 0.852). Other metabolic parameters, including high-density lipoprotein cholesterol, gamma-glutamyl transferase, alkaline phosphatase, free triiodothyronine, fasting plasma glucose, and homeostasis model assessment of insulin resistance, showed additional but more limited discriminatory value.

CONCLUSION

Among adults presenting with ketosis at diabetes onset, LADA represents a substantial proportion of cases and should be considered in the differential diagnosis. Readily available non-antibody biomarkers, particularly 2-hour postprandial C-peptide, demonstrated promising discriminatory performance for differentiating LADA from KP-T2DM, whereas other metabolic markers provided supplementary information. These findings may support the clinical evaluation of atypical diabetes in settings where autoantibody testing is unavailable; however, independent validation is required before routine clinical application.

Keywords: Ketosis-onset adult diabetes; Latent autoimmune diabetes in adults; Ketosis-prone; Type 2 diabetes mellitus; Non-antibody biomarkers; Retrospective study

Core Tip: More than one-quarter of adults presenting with ketosis at diabetes onset in our cohort were diagnosed with latent autoimmune diabetes in adults, highlighting the importance of considering autoimmune diabetes in this clinical setting. We identified a panel of readily available non-antibody biomarkers, including 2-hour C-peptide, high-density lipoprotein cholesterol, gamma-glutamyl transferase, homeostasis model assessment of insulin resistance, alkaline phosphatase, free triiodothyronine, and fasting plasma glucose, that demonstrated discriminatory value for differentiating latent autoimmune diabetes in adults from ketosis-prone type 2 diabetes mellitus and for distinguishing ketosis-onset from nonketotic diabetes within the study cohort. These findings may provide supportive information for the clinical evaluation of atypical diabetes when islet autoantibody testing is unavailable; however, independent validation is required before routine clinical application.

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