ArticleThe Journal of clinical endocrinology and metabolism2022
Metabolic and Genetic Markers Improve Prediction of Incident Type 2 Diabetes: A Nested Case-Control Study in Chinese.
Article in The Journal of clinical endocrinology and metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Circulating metabolites, genetics and lifestyle factors in relation to future risk of type 2 diabetes.Nature medicine · 2026Article
- Artificial Intelligence in Personalized Medicine for Diabetes Mellitus: A Narrative Review.Cureus · 2025Review
- The Relationship Between Cardiometabolic Index and New-Onset Diabetes in Adults Aged Over 45: A Longitudinal Analysis Based on CHARLS.International journal of endocrinology · 2025Article
- Exploring the Link Between Vitamin B Levels and Metabolic Syndrome Risk: Insights from a Case-Control Study in Kazakhstan.Journal of clinical medicine · 2024Article
- Metabolomic Profiling Reveals That Exercise Lowers Biomarkers of Cardiac Dysfunction in Rats with Type 2 Diabetes.Antioxidants (Basel, Switzerland) · 2024Article
- AI-based diabetes care: risk prediction models and implementation concerns.NPJ digital medicine · 2024Article
- A scoping review of artificial intelligence-based methods for diabetes risk prediction.NPJ digital medicine · 2023Article
- Polygenic Risk Score, Lifestyles, and Type 2 Diabetes Risk: A Prospective Chinese Cohort Study.Nutrients · 2023Article
- Metabolic and Genetic Markers Improve Prediction of Incident Type 2 Diabetes: A Nested Case-Control Study in Chinese.The Journal of clinical endocrinology and metabolism · 2022Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
contextIt is essential to improve the current predictive ability for type 2 diabetes (T2D) risk.
objectiveWe aimed to identify novel metabolic markers for future T2D in Chinese individuals of Han ethnicity and to determine whether the combined effect of metabolic and genetic markers improves the accuracy of prediction models containing clinical factors.
methodsA nested case-control study containing 220 incident T2D patients and 220 age- and sex- matched controls from normoglycemic Chinese individuals of Han ethnicity was conducted within the Wuxi Non-Communicable Disease cohort with a 12-year follow-up. Metabolic profiling detection was performed by high-performance liquid chromatography‒mass spectrometry (HPLC-MS) by an untargeted strategy and 20 single nucleotide polymorphisms (SNPs) associated with T2D were genotyped using the Iplex Sequenom MassARRAY platform. Machine learning methods were used to identify metabolites associated with future T2D risk.
resultsWe found that abnormal levels of 5 metabolites were associated with increased risk of future T2D: riboflavin, cnidioside A, 2-methoxy-5-(1H-1, 2, 4-triazol-5-yl)- 4-(trifluoromethyl) pyridine, 7-methylxanthine, and mestranol. The genetic risk score (GRS) based on 20 SNPs was significantly associated with T2D risk (OR = 1.35; 95% CI, 1.08-1.70 per SD). The area under the receiver operating characteristic curve (AUC) was greater for the model containing metabolites, GRS, and clinical traits than for the model containing clinical traits only (0.960 vs 0.798, P = 7.91 × 10-16).
conclusionIn individuals with normal fasting glucose levels, abnormal levels of 5 metabolites were associated with future T2D. The combination of newly discovered metabolic markers and genetic markers could improve the prediction of incident T2D.
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