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- Li, Ning, et al.
(författare)
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Associations of genetically determined lipid traits and lipid-modifying agents with the risk of diabetic retinopathy : A Mendelian randomization study
- 2023
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Ingår i: Atherosclerosis. - : Elsevier BV. - 1879-1484 .- 0021-9150. ; 369, s. 9-16
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND AIMS: The evidence that dyslipidemia is associated with hyperglycemia calls for an investigation of whether dyslipidemia, as well as lipid-modifying agents, could affect the subsequent development of diabetic retinopathy (DR). Therefore, we aimed to address these unanswered questions by utilizing Mendelian randomization (MR) analysis.METHODS: Genetic variants were selected from the UK Biobank as instruments to serve as proxies for lipid traits [high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), apolipoprotein A-I (APOA-I) and apolipoprotein B (APOB)]. Univariable and multivariable MR analyses were performed to examine the associations of these lipid traits with DR and different levels of severity of DR. Based on the evidence for the effects of lipids on outcomes, we estimated the causal relevance of cholesteryl ester transfer protein (CETP) inhibitors in severe nonproliferative and proliferative DR using protein quantitative trait loci (pQTLs) and expression quantitative trait loci (eQTLs) as instruments.RESULTS: Genetically determined HDL-C levels were inversely associated with the risk of severe nonproliferative DR (OR = 0.70, 95% CI = 0.52-0.94) and proliferative DR (OR = 0.90, 95% CI = 0.83-0.97) in the main analyses utilizing the inverse variance-weighted (IVW) MR method and a couple of sensitivity analyses. No association was noted between genetically proxied CETP inhibitors and DR.CONCLUSIONS: This MR study suggests the casual protective roles of HDL-C in severe nonproliferative DR and proliferative DR, which calls for further studies to confirm these findings. Current lipid-modifying agents acting on HDL-C may not reduce the risk of DR and new treatments are required in the future.
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| 2. |
- Zheng, Manqi, et al.
(författare)
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Development and validation of risk prediction models for new-onset type 2 diabetes in adults with impaired fasting glucose
- 2023
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Ingår i: Diabetes Research and Clinical Practice. - : Elsevier BV. - 0168-8227. ; 197
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Tidskriftsartikel (refereegranskat)abstract
- Aims: To develop and validate sex-specific risk prediction models based on easily obtainable clinical data for predicting 5-year risk of type 2 diabetes (T2D) among individuals with impaired fasting glucose (IFG), and generate practical tools for public use. Methods: The data used for model training and internal validation came from a large prospective cohort (N = 18,384). Two independent cohorts were used for external validation. A two-step approach was applied to screen variables. Coefficient-based models were constructed by multivariate Cox regression analyses, and score-based models were subsequently generated. The predictive power was evaluated by the area under the curve (AUC). Results: During a median follow-up of 7.55 years, 5697 new-onset T2D cases were identified. Predictor variables included age, body mass index, waist circumference, diastolic blood pressure, triglycerides, fasting plasma glucose, and fatty liver. The proposed models outperformed five existing models. In internal validation, the AUCs of the coefficient-based models were 0.741 (95% CI 0.723–0.760) for men and 0.762 (95% CI 0.720–0.802) for women. External validation yielded comparable prediction performance. We finally constructed a risk scoring system and a web calculator. Conclusions: The risk prediction models and derived tools had well-validated performance to predict the 5-year risk of T2D in IFG adults.
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