Diabetes & Metabolism Journal

Original Articles

Genetics
Elucidating the Epigenetic Landscape of Type 2 Diabetes Mellitus: A Multi-Omics Analysis Revealing Novel CpG Sites and Their Association with Cardiometabolic Traits: Ren-Hua Chung, Chun-Chao Wang, Djeane Debora Onthoni, Ben-Yang Liao, Tzu-Sheng Hsu, Eden R. Martin, Chao A. Hsiung, Wayne Huey-Herng Sheu, Hung-Yi Chiou; Diabetes Metab J. 2026;50(1):153-164. Published online October 28, 2025; DOI: https://doi.org/10.4093/dmj.2025.0041

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Background
Type 2 diabetes mellitus (T2DM) is a complex, multifactorial disease with a significant global burden. Although genome-wide association studies (GWAS) have identified many T2DM-associated variants, most lie in non-coding regions, making it difficult to interpret their functional roles.
Methods
We aimed to identify genetically regulated Cytosine–phosphate–Guanine (CpG) sites associated with T2DM by conducting a methylome-wide association study (MWAS), followed by Mendelian randomization (MR) and functional validation using human pancreatic cells and mouse models. MWAS was performed using summary statistics from large-scale GWAS and a DNA methylation (DNAm) prediction model to test associations between genetically predicted DNAm and T2DM.
Results
We identified 111 CpG sites significantly associated with T2DM in Europeans, including 8 novel sites near genes not previously linked to T2DM. These findings were replicated in independent datasets. Many CpGs also showed associations with cardiometabolic traits, highlighting shared epigenetic mechanisms. Trans-ethnic MR analysis confirmed consistent effects for six CpGs in East Asians. Functional analysis revealed that several CpGs regulate gene expression in human pancreatic α- and β-cells. Among them, 2´-5´-oligoadenylate synthetase like (OASL) expression, regulated by a significant CpG, was differentially expressed in α-cells of T2DM cases compared to controls. Supporting evidence from mouse models suggests a role for OASL in glucose regulation.
Conclusion
Our study identifies novel genetically regulated CpG sites associated with T2DM risk and highlights OASL as a potential epigenetic regulator of glucose metabolism in α-cells. These findings provide mechanistic insights into the epigenetic architecture of T2DM and suggest potential targets for cross-ethnic biomarker development and therapeutic intervention.

Citations

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Unravelling the molecular mechanisms causal to type 2 diabetes across global populations and disease-relevant tissues
Ozvan Bocher, Ana Luiza Arruda, Satoshi Yoshiji, Chi Zhao, Alicia Huerta-Chagoya, Chen-Yang Su, Xianyong Yin, Davis Cammann, Henry J. Taylor, Jingchun Chen, Ken Suzuki, Ravi Mandla, Ta-Yu Yang, Fumihiko Matsuda, Josep M. Mercader, Jason Flannick, James B.
Nature Metabolism.2026; 8(2): 506. CrossRef
Identification and functional validation of EPS15L1 as a key driver of triple-negative breast cancer
Chun-Chao Wang, Sabareeswaran Krishnan, Yen-Hsun Wang, Kai-Chen Hsu, Tzu-Sheng Hsu, Chung-Hsing Chen, Shang-Hung Chen, Ren-Hua Chung
npj Breast Cancer.2026;[Epub] CrossRef

Complications
The Causal Relationship and Association between Biomarkers, Dietary Intake, and Diabetic Retinopathy: Insights from Mendelian Randomization and Cross-Sectional Study: Xuehao Cui, Dejia Wen, Jishan Xiao, Xiaorong Li; Diabetes Metab J. 2025;49(5):1087-1105. Published online March 31, 2025; DOI: https://doi.org/10.4093/dmj.2024.0731

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Background
Diabetic retinopathy (DR) is a major cause of vision loss, linked to hyperglycemia, oxidative stress, and inflammation. Despite advancements in DR treatments, approximately 40% of patients do not respond effectively, underscoring the need for novel, noninvasive biomarkers to predict DR risk and progression. This study investigates causal relationships between specific biomarkers, dietary factors, and DR development using Mendelian randomization (MR) and cross-sectional data.
Methods
We conducted a two-phase analysis combining MR and cross-sectional methods. First, MR analysis examined causal associations between 35 biomarkers, 226 dietary factors, and DR progression using data from the UK Biobank and Genome-Wide Association Study (GWAS) datasets. Second, a cross-sectional study with National Health and Nutrition Examination Survey (NHANES) and a clinical cohort from Tianjin Medical University Eye Hospital validated findings and explored biomarkers’ predictive capabilities through a nomogram-based prediction model.
Results
MR analysis identified eight biomarkers (e.g., glycosylated hemoglobin [HbA1c], high-density lipoprotein cholesterol [HDL-C]) with significant causal links to DR. Inflammatory markers and metabolic factors, such as high glucose and HDL-C levels, were strongly associated with DR risk and progression. Specific dietary factors, like cheese intake, exhibited protective roles, while alcohol intake increased DR risk. Validation within NHANES and Tianjin cohorts supported these causal associations.
Conclusion
This study elucidates causal relationships between biomarkers, dietary habits, and DR progression, emphasizing the potential for personalized dietary interventions to prevent or manage DR. Findings support the use of HDL-C, HbA1c, and dietary factors as biomarkers or therapeutics in DR, though further studies are needed for broader applicability.

Citations

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Exploring potential therapeutic targets for myopia: Causal analysis and biological annotation with gut microbiota
Zixun Wang, Yimeng Sun, Xiaoling Zhang, Luqiang Wang, Desheng Song, Jingtao Yu, Xiaoxue Hu, Weiping Lin, Ruihua Wei
Computational Biology and Chemistry.2026; 120: 108634. CrossRef
Research Status of Diabetic Retinopathy Prediction Models: From Traditional Risk Factors to Artificial Intelligence
银娟李
Journal of Clinical Personalized Medicine.2026; 05(01): 332. CrossRef
Integrative Proteogenomic Analysis Identifies Genetically Supported Plasma Proteins, Metabolites, and Pathways in Glaucoma
Jiajia Yuan, Xuehao Cui, Patrick Yu-Wai-Man, Xuan Xiao
Investigative Ophthalmology & Visual Science.2026; 67(2): 21. CrossRef
Antioxidant vitamin index and risk of age-related macular degeneration: multicenter validation and clinical translation
Xuehao Cui, Jingwen Hui, Zheya Han, Quanhong Han
npj Aging.2026;[Epub] CrossRef
Comprehensive multi-method analysis of blood heavy metals and nutrient intake in myopia and high myopia
Jingwen Hui, Xinyuan Feng, Quanhong Han, Xuehao Cui
Journal of Translational Medicine.2026;[Epub] CrossRef
Exposome-induced dysregulation of glycemic homeostasis: Emerging biomarkers for diabetes risk and progression
Singamoorthy Amalraj, Venkatesan Karthick, Rajkumar Thamarai, Mani Suganya
Environmental Pollution.2026; 397: 128012. CrossRef
Integrated plasma proteomics and metabolomics reveal immunometabolic pathways and predictive signatures for age-related eye diseases
Xuehao Cui, Qiuchen Zhao, Jiajia Yuan, Patrick Yu-Wai-Man
Metabolism.2026; 180: 156624. CrossRef
Association between diabetic retinopathy and suicidal ideation among U.S. adults with diabetes: A cross-sectional NHANES study, 2005–2018
Najuan Huang, Yaru Du, Yan Zheng, Pengfei Wang
Medicine.2026; 105(28): e49694. CrossRef
Associations between dietary nutrient intake and the risk of multiple age-related ocular diseases: evidence from longitudinal analysis
Yuchen Yang, Haidong Zou
The Journal of nutrition, health and aging.2026; 30(9): 100927. CrossRef
Association between weight-adjusted-waist index and retinopathy among American adults: a cross-sectional study and mediation analysis
Junmeng Li, Qianshuo Yin, Jianchen Hao, Ruilin Zhu, Jing Zhang, Yadi Zhang, Xiaopeng Gu, Zihui Wu, Liu Yang
Frontiers in Nutrition.2025;[Epub] CrossRef
Exploring the impact of diet, sleep, and metabolomic pathways on Glaucoma subtypes: insights from Mendelian randomization and cross-sectional analyses
Zhang Shengnan, Wang Tao, Zhang Yanan, Sun Chao
Nutrition & Metabolism.2025;[Epub] CrossRef
Association between endothelial activation and stress index and diabetic retinopathy in patients with diabetic kidney disease: a cross-sectional study based on NHANES database
Jinping Liu, Di’en Yan, Xiaohui Wang, Yinhua Yao, Ling Wang
BMC Endocrine Disorders.2025;[Epub] CrossRef
Hypertriglyceridemic waist phenotype in relation to diabetes mellitus and cardiovascular diseases in the Indonesian and Korean populations: evidence from two national surveys
Fathimah S. Sigit, Sinyoung Cho, Farid Kurniawan, Hye-Ryeong Jeon, Ratu Ayu Dewi Sartika, Dicky L. Tahapary, Hyuktae Kwon
Diabetology & Metabolic Syndrome.2025;[Epub] CrossRef
Non-linear association between Life’s Essential 8 and diabetic retinopathy: mediating role of depression in US adults with diabetes
Long Xie, Yu Qin Peng, Wei Qiang Wei, Xiang Shen
BMC Public Health.2025;[Epub] 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

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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; 69(7): 1935. 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
Opportunities and Challenges for Precision Nutrition in Gestational Obesity Management
Emmie Söderström Shields, Nina Kaegi-Braun, Johanna Sandborg, Caroline Lilliecreutz, Marie Löf
Current Obesity Reports.2026;[Epub] CrossRef
Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1 , and CMIP variants
Sarocha Suthon, Wachirawit Angkatavanich, Shukri Husein Mohamud, Saranya Innang, Suavaluk Songlilitchuwong, Nipaporn Teerawattanapong, Tassanee Narkdontri, Dittakarn Boriboonhirunsarn, Watip Tangjittipokin
Annals of Medicine.2026;[Epub] 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

Genetics
Genome-Wide Association Study on Longitudinal Change in Fasting Plasma Glucose in Korean Population: Heejin Jin, Soo Heon Kwak, Ji Won Yoon, Sanghun Lee, Kyong Soo Park, Sungho Won, Nam H. Cho; Diabetes Metab J. 2023;47(2):255-266. Published online January 19, 2023; DOI: https://doi.org/10.4093/dmj.2021.0375

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Background
Genome-wide association studies (GWAS) on type 2 diabetes mellitus (T2DM) have identified more than 400 distinct genetic loci associated with diabetes and nearly 120 loci for fasting plasma glucose (FPG) and fasting insulin level to date. However, genetic risk factors for the longitudinal deterioration of FPG have not been thoroughly evaluated. We aimed to identify genetic variants associated with longitudinal change of FPG over time.
Methods
We used two prospective cohorts in Korean population, which included a total of 10,528 individuals without T2DM. GWAS of repeated measure of FPG using linear mixed model was performed to investigate the interaction of genetic variants and time, and meta-analysis was conducted. Genome-wide complex trait analysis was used for heritability calculation. In addition, expression quantitative trait loci (eQTL) analysis was performed using the Genotype-Tissue Expression project.
Results
A small portion (4%) of the genome-wide single nucleotide polymorphism (SNP) interaction with time explained the total phenotypic variance of longitudinal change in FPG. A total of four known genetic variants of FPG were associated with repeated measure of FPG levels. One SNP (rs11187850) showed a genome-wide significant association for genetic interaction with time. The variant is an eQTL for NOC3 like DNA replication regulator (NOC3L) gene in pancreas and adipose tissue. Furthermore, NOC3L is also differentially expressed in pancreatic β-cells between subjects with or without T2DM. However, this variant was not associated with increased risk of T2DM nor elevated FPG level.
Conclusion
We identified rs11187850, which is an eQTL of NOC3L, to be associated with longitudinal change of FPG in Korean population.

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Investigation of the degree of family history of diabetes in different clusters of newly diagnosed type 2 diabetes in Thailand
Watip Tangjittipokin, Tassanee Narkdontri, Nipaporn Teerawattanapong, Sarocha Suthon, Vorthunju Nakhonsri, Rujipat Wasitthankasem, Nirinya Sudtachat, Lukana Preechasuk, Varisara Lapinee, Nuntakorn Thongtang, Sissades Tongsima, Nattachet Plengvidhya
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Review

Islet Studies and Transplantation
Regulation of Pancreatic β-Cell Mass by Gene-Environment Interaction: Shun-ichiro Asahara, Hiroyuki Inoue, Yoshiaki Kido; Diabetes Metab J. 2022;46(1):38-48. Published online January 27, 2022; DOI: https://doi.org/10.4093/dmj.2021.0045

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Graphical Abstract Abstract PDF PubReader ePub

The main pathogenic mechanism of diabetes consists of an increase in insulin resistance and a decrease in insulin secretion from pancreatic β-cells. The number of diabetic patients has been increasing dramatically worldwide, especially in Asian people whose capacity for insulin secretion is inherently lower than that of other ethnic populations. Causally, changes of environmental factors in addition to intrinsic genetic factors have been considered to have an influence on the increased prevalence of diabetes. Particular focus has been placed on “gene-environment interactions” in the development of a reduced pancreatic β-cell mass, as well as type 1 and type 2 diabetes mellitus. Changes in the intrauterine environment, such as intrauterine growth restriction, contribute to alterations of gene expression in pancreatic β-cells, ultimately resulting in the development of pancreatic β-cell failure and diabetes. As a molecular mechanism underlying the effect of the intrauterine environment, epigenetic modifications have been widely investigated. The association of diabetes susceptibility genes or dietary habits with gene-environment interactions has been reported. In this review, we provide an overview of the role of gene-environment interactions in pancreatic β-cell failure as revealed by previous reports and data from experiments.

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High-Fat Diet-Fed Kcnq1 Mutant Mice Have Reduced Pancreatic β-Cell Mass via Gene-Environment Interaction
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Original Article

Genome-Wide Association Study Identifies Two Novel Loci with Sex-Specific Effects for Type 2 Diabetes Mellitus and Glycemic Traits in a Korean Population: Min Jin Go, Joo-Yeon Hwang, Tae-Joon Park, Young Jin Kim, Ji Hee Oh, Yeon-Jung Kim, Bok-Ghee Han, Bong-Jo Kim; Diabetes Metab J. 2014;38(5):375-387. Published online October 17, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.5.375

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Background

Until recently, genome-wide association study (GWAS)-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM) or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population.

Methods

We performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842). The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500). A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively.

Results

A combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356) loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study.

Conclusion

Our study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

Citations

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Impaired fasting glucose and development of chronic kidney disease in non-diabetic population: a Mendelian randomization study
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Opposite Genetic Effects of CMIP Polymorphisms on the Risk of Type 2 Diabetes and Obesity: A Family-Based Study in China
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International Journal of Molecular Sciences.2018; 19(4): 1011. CrossRef
Type 2 Diabetes Genetic Variants and Risk of Diabetic Retinopathy
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10-year trajectory of β-cell function and insulin sensitivity in the development of type 2 diabetes: a community-based prospective cohort study
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The Lancet Diabetes & Endocrinology.2016; 4(1): 27. CrossRef
Sex and Gender Differences in Risk, Pathophysiology and Complications of Type 2 Diabetes Mellitus
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No Interaction with Alcohol Consumption, but Independent Effect of C12orf51 (HECTD4) on Type 2 Diabetes Mellitus in Korean Adults Aged 40-69 Years: The KoGES_Ansan and Ansung Study
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Statistical power considerations in genotype-based recall randomized controlled trials
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Response: Genome-Wide Association Study Identifies Two Novel Loci with Sex-Specific Effects for Type 2 Diabetes Mellitus and Glycemic Traits in a Korean Population (Diabetes Metab J2014;38:375-87)
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