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

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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

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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

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Diabetes & Vascular Disease Research.2026;[Epub] CrossRef
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Mechanobiology.2026;[Epub] CrossRef
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Ying Wei, Yong Tian, Ruixiang Cui, Ying Wang, Jia Liu, Guang Wang
Diabetes, Obesity and Metabolism.2026;[Epub] 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
GLDC attenuates liver ischemia-reperfusion injury by inhibiting macrophage recruitment and activation via PTBP1/P2RY6
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International Journal of Molecular Sciences.2025; 26(16): 7940. CrossRef
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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
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Xin Jiang, Keqing Yuan, Xiaofeng Ge, Lili Yu, Yufei Cui, Lianhai Jin, Ying Chang
Metabolites.2025; 15(11): 707. CrossRef
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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
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莹莹郑
Advances in Clinical Medicine.2025; 15(12): 2174. CrossRef

Genetics
Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women: Claudia Ha-ting Tam, Ying Wang, Chi Chiu Wang, Lai Yuk Yuen, Cadmon King-poo Lim, Junhong Leng, Ling Wu, Alex Chi-wai Ng, Yong Hou, Kit Ying Tsoi, Hui Wang, Risa Ozaki, Albert Martin Li, Qingqing Wang, Juliana Chung-ngor Chan, Yan Chou Ye, Wing Hung Tam, Xilin Yang, Ronald Ching-wan Ma; Diabetes Metab J. 2025;49(1):128-143. Published online September 20, 2024; DOI: https://doi.org/10.4093/dmj.2024.0139

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Background
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI], 1.38 to 1.96), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; P_meta=7.6×10^-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; P_meta=3.1×10^-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Citations

Citations to this article as recorded by

Maternal and fetal genetic predispositions to insulin deficiency and resistance affect fetal growth through distinct pathways
Gechang Yu, Claudia H. T. Tam, Mai Shi, Alice E. Hughes, Chuiguo Huang, Yuzhi Deng, Michael N. Weedon, Cadmon K. P. Lim, Chi Chiu Wang, Juliana C. N. Chan, Wing Hung Tam, William Lowe, Rachel M. Freathy, Richard A. Oram, Ronald C. W. Ma
Diabetologia.2026;[Epub] CrossRef
Gestational Diabetes and Genetics: MTNR1B, CDKAL1, and IRS1 as Critical Players
Guluzar Arzu Turan, Nehir Aran, Bulent Tolga Delibasi
Genes.2026; 17(3): 287. CrossRef
GWAS in Gestational Diabetes Mellitus: Research Advances
Dikun Zhou, Z. Shi, A.H. Hashash, Z.H. Khan
BIO Web of Conferences.2025; 174: 01018. CrossRef
Advancing Early Prediction of Gestational Diabetes Mellitus with Circular RNA Biomarkers
Joon Ho Moon, Sung Hee Choi
Diabetes & Metabolism Journal.2025; 49(3): 403. CrossRef
Association between maternal glucose levels in pregnancy and offspring’s metabolism and adiposity: an 18-year birth cohort study
Yuzhi Deng, Hanbin Wu, Noel Y. H. Ng, Claudia H. T. Tam, Atta Y. T. Tsang, Michael H. M. Chan, Kenneth Ka Hei Lo, Chi Chiu Wang, Wing Hung Tam, Ronald C. W. Ma
Diabetologia.2025; 68(10): 2205. CrossRef
DNA Methylation Biomarkers Predict Offspring Metabolic Risk From Mothers With Hyperglycemia in Pregnancy
Johnny Assaf, Ishant Khurana, Ram Abou Zaki, Claudia H.T. Tam, Ilana Correa, Scott Maxwell, Julie Kinnberg, Malou Christiansen, Caroline Frørup, Heung Man Lee, Harikrishnan Kaipananickal, Jun Okabe, Safiya Naina Marikar, Kwun Kiu Wong, Cadmon K.P. Lim, La
Diabetes.2025; 74(9): 1695. CrossRef
Polygenic Risk Score Associated with Gestational Diabetes Mellitus in an AmericanIndian Population
Karrah Peterson, Camille E. Powe, Quan Sun, Crystal Azure, Tia Azure, Hailey Davis, Kennedy Gourneau, Shyanna LaRocque, Craig Poitra, Sabra Poitra, Shayden Standish, Tyler J. Parisien, Kelsey J. Morin, Lyle G. Best
Journal of Personalized Medicine.2025; 15(9): 395. CrossRef
Apolipoprotein C1 -317H1/H2 and the rs4420638 genetic variations and risk of gestational diabetes mellitus in Chinese women: a case-control study
Wandi Ma, Linbo Guan, Xinghui Liu, Yujie Wu, Zhengting Zhu, Yuwen Guo, Ping Fan, Huai Bai
Frontiers in Endocrinology.2025;[Epub] CrossRef
Hexokinase Domain Containing 1 (HKDC1) Gene Variants and Their Association With Gestational Diabetes Mellitus: A Mini-Review
Sekar Kanthimathi, Polina Popova, Viswanathan Mohan, Wesley Hannah, Ranjit Mohan Anjana, Venkatesan Radha
Journal of Diabetology.2024; 15(4): 354. CrossRef

Metabolic Risk/Epidemiology
A Vegetable Dietary Pattern Is Associated with Lowered Risk of Gestational Diabetes Mellitus in Chinese Women: Qiong Chen, Weiwei Wu, Hailan Yang, Ping Zhang, Yongliang Feng, Keke Wang, Ying Wang, Suping Wang, Yawei Zhang; Diabetes Metab J. 2020;44(6):887-896. Published online September 11, 2020; DOI: https://doi.org/10.4093/dmj.2019.0138

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Background
Identification of modifiable dietary factors, which are involved in the development of gestational diabetes mellitus (GDM), could inform strategies to prevent GDM.
Methods
We examined the dietary patterns in a Chinese population and evaluated their relationship with GDM risk using a case-control study including 1,464 cases and 8,092 control subjects. Propensity score matching was used to reduce the imbalance of covariates between cases and controls. Dietary patterns were identified using factor analysis while their associations with GDM risk were evaluated using logistic regression models.
Results
A “vegetable” dietary pattern was characterized as the consumption of green leafy vegetables (Chinese little greens and bean seedling), other vegetables (cabbages, carrots, tomatoes, eggplants, potatoes, mushrooms, peppers, bamboo shoots, agarics, and garlic), and bean products (soybean milk, tofu, kidney beans, and cowpea). For every quartile increase in the vegetables factor score during 1 year prior to conception, the first trimester, and the second trimester of pregnancy, the GDM risk lowered by 6% (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.89 to 0.99), 7% (OR, 0.94; 95% CI, 0.88 to 0.99), and 9% (OR, 0.91; 95% CI, 0.86 to 0.96).
Conclusion
In conclusion, our study suggests that the vegetable dietary pattern is associated with lower GDM risk; however, the interpretation of the result should with caution due to the limitations in our study, and additional studies are necessary to explore the underlying mechanism of this relationship.

Citations

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Wenzheng Guan, Tian Zhou, Jiao Jiao, Liwen Xiao, Zhen Wang, Siyuan Liu, Fujie Yan, Fangqing Zhao, Xiuxia Wang
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Moderate Chili Consumption During Pregnancy Is Associated with a Low Risk of Gestational Diabetes (GDM)
Xiaozhong Wen, Fatima Makama, Ryan Buzby, Jeremy Nguyen, Rose Durnell, Iyobosa Ekhator, Daren Chan, Todd C. Rideout
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