Diabetes & Metabolism Journal

Corrigendum

Contributions of Hepatic Insulin Resistance and Islet β-Cell Dysfunction to the Blood Glucose Spectrum in Newly Diagnosed Type 2 Diabetes Mellitus: Mengge Yang, Ying Wei, Jia Liu, Ying Wang, Guang Wang; Diabetes Metab J. 2026;50(2):432-433. Published online February 5, 2026; DOI: https://doi.org/10.4093/dmj.2024.0537.c1; Corrects: Diabetes Metab J 2025;49(4):883

1,624 View
55 Download
1 Crossref

PDF PubReader ePub

Citations

Citations to this article as recorded by

Association between ZJU index and glycemic outcomes in individuals with impaired fasting glucose: a retrospective multicenter Chinese cohort study
Wanlan Huang, Duo Yang, Renzhe Lin, Sen Li, Shujun Ye, Zitian Luo, Huankai Zhang, Si Wu, Longsheng Zhang
Frontiers in Endocrinology.2026;[Epub] CrossRef

Original Articles

Complications
Optimizing Early Detection of Diabetic Kidney Disease through Synergistic Biomarkers and Serum Metabolites in Humans: Xianke Zhou, Yuan Gui, Jia-Jun Liu, Shijia Liu, Dongning Liang, Yuanyuan Wang, Henry Wells Shaffer, Samantha Mae Mallari, Cameron Jones, Priya Gupta, Dier Li, Ke Zhang, Ying Yu, Jianling Tao, Yanlin Wang, Silvia Liu, Dong Zhou, Haiyan Fu; Diabetes Metab J. 2026;50(4):752-769. Published online January 29, 2026; DOI: https://doi.org/10.4093/dmj.2025.0193

2,807 View
140 Download
1 Web of Science
1 Crossref

Abstract PDF Supplementary Material PubReader ePub

Background
Diabetic kidney disease (DKD) often progresses to end-stage renal disease more rapidly than nondiabetic kidney disease because of persistent hyperglycemia and early activation of multiple pathogenic pathways. Early detection of DKD is crucial for identifying subtle kidney damage before clinical symptoms appear.
Methods
This study combined human serum proteomics with public single-cell RNA sequencing and spatial transcriptomics data from diabetic kidneys to identify key biomarkers for DKD diagnosis. These biomarkers were validated in multiple organs of db/db mice at early and advanced stages. In a discovery cohort, sera from 173 healthy adults and 444 patients with type 2 diabetes mellitus (T2DM), with or without kidney disease, were analyzed using metabolomics and enzyme-linked immunosorbent assay (ELISA). Multiple machine learning algorithms were developed to integrate synergistic biomarkers and serum metabolites for early DKD detection, with results validated in 435 participants from four independent clinical cohorts.
Results
Metalloproteinase-7 (MMP-7) and tenascin C (TNC) were elevated in human diabetic kidneys at the single-cell and spatial levels. Proteomics indicated upregulation of serum amyloid A1 (SAA1) and TNC in the serum of patients with DKD. In db/db mice, all three biomarkers increased in multiple organs by 18 weeks of age. In sera from patients with DKD, MMP-7 and TNC levels were consistently elevated across cohorts. The new algorithms combining MMP-7, SAA1, and TNC enhanced early-stage DKD detection, with approximately 13% improvements in accuracy when serum metabolites were included to distinguish progression from early to advanced DKD stages.
Conclusion
Integrating synergistic biomarkers with serum metabolomics enhances the early detection of DKD, potentially improving outcomes by slowing disease progression in patients with T2DM.

Citations

Citations to this article as recorded by

Recent advances in point-of-care colorimetric biosensors for detecting small molecule metabolites
Zhiqiang Zhu, Zhun Gu, Xinxing Cao, Shanshan Zhang, Shao Su
Chemical Communications.2026; 62(48): 12000. CrossRef

Pharmacotherapy
Novel Insights into the Causal Relationship between Antidiabetic Drugs and Adverse Perinatal Outcomes: A Mendelian Randomization Study: Chang Su, Xueqing He, Xiaona Chang, Juan Tian, Guang Wang, Jia Liu; Diabetes Metab J. 2025;49(6):1242-1251. Published online June 2, 2025; DOI: https://doi.org/10.4093/dmj.2024.0521

4,588 View
189 Download
1 Web of Science
1 Crossref

Abstract PDF Supplementary Material PubReader ePub

Background
Hyperglycemia during pregnancy increases the risk of adverse perinatal outcomes and birth defects. Evidence regarding the long-term safety of antidiabetic drugs during pregnancy is still lacking.
Methods
A two-sample Mendelian randomization (MR) study was performed to assess the causal association between six antidiabetic drug targets (ABCC8, DPP4, INSR, GLP1R, PPARG, and SLC5A2) and seven adverse perinatal outcomes and five congenital malformation outcomes. Inverse variance weighted (IVW) was adopted as the main MR method, and sensitivity analysis using traditional MR methods was performed to evaluate the robustness of the results.
Results
We observed strong evidence that sodium-glucose cotransporter 2 (SGLT2) inhibitors (odds ratio [OR], 0.084; 95% confidence interval [CI], 0.009 to 0.834; P=0.034) reduces the risk of preterm birth; genetic variation in sulfonylurea drug targets (OR, 0.015; 95% CI, 2.50E-04 to 0.919; P=0.045) and genetic variation in thiazolidinedione drug targets (OR, 0.007; 95% CI, 4.16E-04 to 0.121; P=0.001) reduced the risk of eclampsia/preeclampsia; glucagon-like peptide 1 (GLP-1) analogues target (β=–0.549; 95% CI, –0.958 to –0.140; P=0.009) was inversely associated with fetal birth weight; thiazolidinedione target was inversely associated with gestational age (β=–0.952; 95% CI, –1.785 to –0.118; P=0.025); SGLT2 inhibitors reduced the risk of cardiocirculatory malformations (OR, 0.001; 95% CI, 8.75E-06 to 0.126; P=0.005).
Conclusion
Most antidiabetic drugs are safe when used during the perinatal period. Of note, GLP-1 analogues may lead to a risk of low birth weight, while thiazolidinediones may lead to a reduction in fetal gestational age.

Citations

Citations to this article as recorded by

Prenatal chemical exposures and fetal growth: a narrative review of gene-environment interactions (2025)
Sumitaka Kobayashi, Fumihiro Sata, Yasuaki Saijo, Reiko Kishi
Pediatric Research.2026;[Epub] CrossRef

Others
Contributions of Hepatic Insulin Resistance and Islet β-Cell Dysfunction to the Blood Glucose Spectrum in Newly Diagnosed Type 2 Diabetes Mellitus: Mengge Yang, Ying Wei, Jia Liu, Ying Wang, Guang Wang; Diabetes Metab J. 2025;49(4):883-892. Published online February 13, 2025; DOI: https://doi.org/10.4093/dmj.2024.0537; Correction in: Diabetes Metab J 2026;50(2):432

10,006 View
316 Download
13 Web of Science
18 Crossref

Abstract PDF Supplementary Material PubReader ePub

Background
Our previous studies have investigated the role of hepatic insulin resistance (hepatic IR) and islet β-cell function in the pathogenesis of diabetes. This study aimed to explore the contributions of hepatic IR and islet β-cell dysfunction to the blood glucose spectrum in patients with newly diagnosed type 2 diabetes mellitus.
Methods
Hepatic IR was assessed by the hepatic insulin resistance index (HIRI). Islet β-cell function was assessed by insulin secretion- sensitivity index-2 (ISSI2). The associations between blood glucose spectrum and hepatic IR and ISSI2 were analyzed.
Results
A total of 707 patients with new-onset diabetes were included. The fasting blood glucose (FBG) and 30 minutes postload blood glucose elevated with rising HIRI (both P for trend <0.001). The FBG, 30 minutes, 2 hours, and 3 hours post-load blood glucose elevated with decreasing ISSI2 quartiles (all P for trend <0.001). There was a negative correlation between ISSI2 and HIRI after adjusting blood glucose levels (r=–0.199, P<0.001).
Conclusion
Hepatic IR mainly contributed to FBG and early-phase postprandial plasma glucose, whereas β-cell dysfunction contributed to fasting and postprandial plasma glucose at each phase.

Citations

Citations to this article as recorded by

Interaction between insulin resistance and depression in predicting cardiovascular risk: Evidence from a longitudinal study
Siyu Chen, Lijing Yang, Yu Zhou, Hao Yu
Diabetes & Vascular Disease Research.2026;[Epub] CrossRef
Engineering the pancreatic niche: Mechanobiological insights into stem cell-derived β-cell therapy for diabetes mellitus
Swaminadhan Dandapani, Yongsung Hwang
Mechanobiology.2026;[Epub] CrossRef
Associations of adipose tissue insulin resistance with fasting blood glucose and HbA1c in adults without diabetes
Ying Wei, Yong Tian, Ruixiang Cui, Ying Wang, Jia Liu, Guang Wang
Diabetes, Obesity and Metabolism.2026; 28(4): 3209. CrossRef
Advancing in vitro vascular wall modelling using digital light processing to study hyperglycemia-driven cell changes
Ianina Pokholenko, Marguerite Meeremans, Sandra Van Vlierberghe, Nele Pien, Catharina De Schauwer
Frontiers in Bioengineering and Biotechnology.2026;[Epub] CrossRef
Redefining β-Cell Function in Type 2 Diabetes Mellitus: From Comprehensive Assessment to Precision Medicine
YongKyung Kim, Joon Ha, Jun Sung Moon
Diabetes & Metabolism Journal.2026; 50(2): 235. CrossRef
Molecular epidemiology of the MTHFR C677T polymorphism and its association with type 2 diabetes mellitus at the University of Gondar Comprehensive Specialized Hospital
Genetu Kassahun Berie, Mequanente Dagnaw, Meera Indracanti, Muluken Dejen, Nega Berhane
Annals of Human Biology.2026;[Epub] CrossRef
Lipoprotein(a) concentration, kringle IV-2 repeat copy number, and myocardial infarction risk in Chinese populations: insights from the INTERHEART China study
Jinsong Jiang, Xiaonan Ma, Ying Wei, Binong Su, Xin Liu, Yanyan Xiao, Yan Gu, Ziyu Wang, Dong Luo, Huafang Gao, Xingyu Wang, Aihua Hu
Lipids in Health and Disease.2026;[Epub] CrossRef
Not loss of stability but steady-state shift: A systems biology explanation for elevated fasting blood glucose in type 2 diabetes
Guanyu Wang
Advances in Differential Equations and Control Processes.2026;[Epub] CrossRef
Digital health technologies for diabetes-centered five-condition co-management in China: Theoretical foundations, practical experience, and technical challenges
Jia-Li Xu, Cheng Luo, Cheng-Zheng Duan, Shi-Yu Xu, Zhi-Qiang Wu, Li-Ya Ye, Zhi-Peng Li, Mao-Sen Wang, Xian-Mei Yu, Dong-Juan He
World Journal of Diabetes.2026;[Epub] CrossRef
GLDC attenuates liver ischemia-reperfusion injury by inhibiting macrophage recruitment and activation via PTBP1/P2RY6
Zhitao Li, Li Jin, Yuan Fang, Siming Qu, Bo Yuan, Kai Gan, Hanfei Huang
Cellular Signalling.2025; 135: 111976. CrossRef
The Physiological and Pathological Mechanisms of LIN2, LIN7, LIN10 and Their Tripartite Complex
Yangyang Shang, Xinyi Gan, Yue Dang, Jie Liu, Peijun Liu
Journal of Cellular and Molecular Medicine.2025;[Epub] CrossRef
Cinnamic Acid: A Shield Against High-Fat-Diet-Induced Liver Injury—Exploring Nrf2’s Protective Mechanisms
Asmahan Taher Alahdal, Laila Naif Al-Harbi, Ghedeir M. Alshammari, Ali Saleh, Mohammed Abdo Yahya
International Journal of Molecular Sciences.2025; 26(16): 7940. CrossRef
Sodium Butyrate Ameliorated Bile Acid Metabolism in Diabetes Mellitus by PI3K/AKT Signaling Pathway via the Gut–Liver Axis
Tingting Zhao, Xi Zhang, Qian Xiang, Yadi Liu, Xuling Li, Junling Gu, Wenqian Zhang, Zhe Wang, Yiran Li, Xiaoshan Lai, Yonghua Zhao, Youhua Xu
Current Issues in Molecular Biology.2025; 47(9): 732. CrossRef
Chronic Intermittent Low-Pressure Hypoxia Suppresses Inflammation and Regulates Glycolipids by Modulating Mitochondrial Respiration in db/db Mice
Xin Jiang, Keqing Yuan, Xiaofeng Ge, Lili Yu, Yufei Cui, Lianhai Jin, Ying Chang
Metabolites.2025; 15(11): 707. CrossRef
Expanding horizons: the role of robotic surgery in modern transplantation practices
Arya Afrooghe, Pedram Pirmoradian, Moein Ghasemi, Benyamin Mohammadi, Mahya Soleymani Mehranjani, Elham Ahmadi, Seyed Amir Miratashi Yazdi
Journal of Robotic Surgery.2025;[Epub] CrossRef
Elevated PEDF promotes the occurrence of diabetes mellitus via suppressing GSIS by downregulating the SNARE complex
Zhen Zhao, Yandan Tan, Jie Fang, Gan Xia, Junchen Li, Qilong Tang, Wanting Xie, Tianxiao Gao, Zhenzhen Fang, Ti Zhou, Xia Yang, Guoquan Gao, Weiwei Qi
Communications Biology.2025;[Epub] CrossRef
Distinct Circulating Biomarker Profiles Associated with Type 2 Diabetes in a Regional Cohort—A Cross-Sectional Study
Abdullah Alsrhani, Muhammad Atif, Aisha Farhana
Metabolites.2025; 15(12): 776. CrossRef
Application and Predictive Potential of Novel Insulin Resistance Assessment Indices in Metabolic Diseases
莹莹郑
Advances in Clinical Medicine.2025; 15(12): 2174. CrossRef

Cardiovascular Risk/Epidemiology
Normalized Creatinine-to-Cystatin C Ratio and Risk of Cardiometabolic Multimorbidity in Middle-Aged and Older Adults: Insights from the China Health and Retirement Longitudinal Study: Honglin Sun, Zhenyu Wu, Guang Wang, Jia Liu; Diabetes Metab J. 2025;49(3):448-461. Published online January 20, 2025; DOI: https://doi.org/10.4093/dmj.2024.0100

12,800 View
483 Download
13 Web of Science
13 Crossref

Abstract PDF Supplementary Material PubReader ePub

Background
Normalized creatinine-to-cystatin C ratio (NCCR) was reported to approximate relative skeletal muscle mass and diabetes risk. However, the association between NCCR and cardiometabolic multimorbidity (CMM) remains elusive. This study aimed to explore their relationship in a large-scale prospective cohort.
Methods
This study included 5,849 middle-age and older participants from the China Health and Retirement Longitudinal Study (CHARLS) enrolled between 2011 and 2012. The baseline NCCR was determined as creatinine (mg/dL)/cystatin C (mg/L)×10/body mass (kg). CMM was defined as the simultaneous occurrence of two or more of the following conditions: heart disease, stroke, and type 2 diabetes mellitus. Logistic regression analysis and Cox regression analysis were employed to estimate the relationship between NCCR and CMM. The joint effect of body mass index and NCCR on the risk of CMM were further analyzed.
Results
During a median 4-year follow-up, 227 (3.9%) participants developed CMM. The risk of CMM was significantly decreased with per standard deviation increase of NCCR (odds ratio, 0.72; 95% confidence interval, 0.62 to 0.85) after adjustment for confounders (P<0.001). Further sex-specific analysis found significant negative associations between NCCR and CMM in female either without or with one CMM component at baseline, which was attenuated in males but remained statistically significant among those with one basal CMM component. Notably, non-obese individuals with high NCCR levels had the lowest CMM risk compared to obese counterparts with low NCCR levels in both genders.
Conclusion
High NCCR was independently associated with reduced risk of CMM in middle-aged and older adults in China, particularly females.

Citations

Citations to this article as recorded by

Normalized creatinine-to-cystatin C ratio and cardiovascular disease risk in populations with cardiovascular–kidney–metabolic syndrome stages 0–3: findings from a national and prospective cohort study
Defei Chen, Yuhui Li, Tailin Ran, Fu Song, Zheng Yang, Weilin Tan, Qiuyi Lu, Lanxin Tang, Lining Yang, Dingqun Bai
European Journal of Medical Research.2026;[Epub] CrossRef
Association between the sarcopenia index and osteoarthritis: a cross-sectional and longitudinal study
Xin Cai, Tianzuo Lan, Zong Jiang, Fang Tang, Haixia Fan
European Journal of Medical Research.2026;[Epub] CrossRef
Association of the triglyceride glucose-Chinese visceral adiposity index with incident cardiometabolic multimorbidity in middle-aged and older adults: a nationwide prospective cohort study
Wenling Zheng, Ziyue Man, Yanping Ren, Yu Li, Xiaohong Zhu, Lan Wang, Xi Zhang, Guilin Hu, Yu Cao
Cardiovascular Diabetology.2026;[Epub] CrossRef
Normalized creatinine-to-cystatin C ratio and atherosclerotic cardiovascular disease risk in the UK Biobank
Xiaoyan Liu, Huizhi Zhan, Yi Ou, Yuwen Shangguan, Jingbo Zhang
European Journal of Preventive Cardiology.2026;[Epub] CrossRef
Normalized creatinine-to-cystatin C ratio and risk of hypertension in middle-aged and older adults: findings from the China Health and Retirement Longitudinal Study
Ke Si, Cunwei Sun, Chuanqin Shi, Yajing Huang, Jingwei Chi, Lili Xu, Yangang Wang
Nutrition, Metabolism and Cardiovascular Diseases.2026; 36(8): 104705. CrossRef
Predicting cardiometabolic multimorbidity in Chinese older adults via machine learning
Zhitong Li, Angxian Lü, Wenxia Ren, Wenjing Wang, Boya An, Xiaoying Fan, Yuanyuan Yan, Yajing Bai, Anqi Zhao, Ruixue Duan, Shiwei Liu
Metabolism and Target Organ Damage.2026;[Epub] CrossRef
Associations of cumulative exposure and dynamic trajectories of the triglyceride–total cholesterol–body weight index with new-onset cardiometabolic multimorbidity in middle-aged and older Chinese adults: evidence from a nationwide prospective cohort study
Xiao Chen, Chaochao Wang, Qi Huang, Yuan Luo, Zhe Wu, Jing Chen, Haibo Gong
Cardiovascular Diabetology.2026;[Epub] CrossRef
Mendelian Randomization to Examine the Causal Effects of Cystatin on Ovarian Lesions
Tianqing Yan, Lin Guo, Renquan Lu
International Journal of Women's Health.2026; Volume 18: 1. CrossRef
Monitoring Sarcopenia With Incretin Receptor Activator Treatment
Zachary T. Bloomgarden
Journal of Diabetes.2025;[Epub] CrossRef
Correlation Between Serum Creatinine-to-Cystatin C Ratio and Prognosis of Patients with Hip Fracture
Wenbin Lu, Miaomiao Rao, Fan Jia, Wubin Chen, Bin Li, Jinjun Bian, Jiafeng Wang
International Journal of General Medicine.2025; Volume 18: 4147. CrossRef
Association between creatinine to cystatin C ratio and the incidence of depressive symptoms among middle-aged and older adults: insight from the CHARLS study
Xiaohui Li, Guirong Song, Jiaqi Ding, Dongmei Hu, Ying Zhang, Guorong Li, Xiao Tang
BMC Psychology.2025;[Epub] CrossRef
Cardiometabolic multimorbidity in relation to the metabolic score for insulin resistance and creatinine-to-cystatin C ratio in a middle-aged and aged population
Roushan Zhang, Jian Ma, Li Wang
Frontiers in Endocrinology.2025;[Epub] CrossRef
Elevated Serum Triglycerides Independently Predict Incident Falls in Middle‐Aged and Older Adults
Kai Deng
Geriatrics & Gerontology International.2025; 25(12): 1868. CrossRef

First
Prev
Page of 1
Next
Last

Search