TCERG1L hypermethylation is a risk factor of diabetic retinopathy in Chinese children with type 1 diabetes.

AIM: To identify the differential methylation sites (DMS) and their according genes associated with diabetic retinopathy (DR) development in type 1 diabetes (T1DM) children. METHODS: This study consists of two surveys. A total of 40 T1DM children was included in the first survey. Because no participant has DR, retina thinning was used as a surrogate indicator for DR. The lowest 25% participants with the thinnest macular retinal thickness were included into the case group, and the others were controls. The DNA methylation status was assessed by the Illumina methylation 850K array BeadChip assay, and compared between the case and control groups. Four DMS with a potential role in diabetes were identified. The second survey included 27 T1DM children, among which four had DR. The methylation patterns of the four DMS identified by 850K were compared between participants with and without DR by pyrosequencing. RESULTS: In the first survey, the 850K array revealed 751 sites significantly and differentially methylated in the case group comparing with the controls (|Δß|>0.1 and Adj.P<0.05), and 328 of these were identified with a significance of Adj.P<0.01. Among these, 319 CpG sites were hypermethylated and 432 were hypomethylated in the case group relative to the controls. Pyrosequencing revealed that the transcription elongation regulator 1 like (TCERG1L, cg07684215) gene was hypermethylated in the four T1DM children with DR (P=0.018), which was consistent with the result from the first survey. The methylation status of the other three DMS (cg26389052, cg25192647, and cg05413694) showed no difference (all P>0.05) between participants with and without DR. CONCLUSION: The hypermethylation of the TCERG1L gene is a risk factor for DR development in Chinese children with T1DM.

Changes and related factors of blood CCN1 levels in diabetic patients.

Objective: To study the differences in blood cellular communication network factor 1 (CCN1) levels between patients with diabetes mellitus (DM) and healthy individuals and to explore the relationship between CCN1 and diabetic retinopathy (DR). Methods: Plasma CCN1 levels were detected using ELISA in 50 healthy controls, 74 patients with diabetes without diabetic retinopathy (DM group), and 69 patients with diabetic retinopathy (DR group). Correlations between CCN1 levels and age, body mass index, mean arterial pressure, hemoglobin A1c, and other factors were analyzed. The relationship between CCN1 expression and DR was explored using logistic regression after adjusting for confounding factors. Blood mRNA sequencing analysis was performed for all subjects, and the molecular changes that may be related to CCN1 were explored. The retinal vasculature of streptozotocin-induced diabetic rats was examined using fundus fluorescein angiography; in addition, retinal protein expression was examined using western blotting. Results: Plasma CCN1 levels in patients with DR were significantly higher than in the control and DM groups; however, no significant differences were observed between healthy controls and patients with DM. CCN1 levels negatively correlated with body mass index and positively correlated with the duration of diabetes and urea levels. It was observed that high (OR 4.72, 95% CI: 1.10-20.25) and very high (OR 8.54, 95% CI: 2.00-36.51) levels of CCN1 were risk factors for DR. Blood mRNA sequencing analysis revealed that CCN1-related pathways were significantly altered in the DR group. The expression of hypoxia-, oxidative stress-, and dephosphorylation-related proteins were elevated, while that of tight junction proteins were reduced in the retinas of diabetic rats. Conclusion: Blood CCN1 levels are significantly elevated in patients with DR. High and very high levels of plasma CCN1 are risk factors for DR. Blood CCN1 level may be a potential biomarker for diagnosis of DR. The effects of CCN1 on DR may be related to hypoxia, oxidative stress, and dephosphorylation.

Recent Epidemiology Study Data of Myopia.

Myopia, a pandemic refractive error, is affecting more and more people. The progression of myopia could cause numerously serious complications, even leading to blindness. This review summarizes the epidemiological studies on myopia after 2018 and analyzes the risk factors associated with myopia. The prevalence of myopia varies in different regions, age, and observation time. East Asia has been gripped by an unprecedented rise in myopia, and other parts of the world have also seen an increase. The prevalence of myopia in children continues to rise and aggravates with age. The prevalence of high myopia has also increased along with myopia. Racial dependence and family aggregation can be seen frequently in myopia patients. Increased outdoor activities are proven to be protective factors for myopia, as near-distance work and higher education levels affect in the opposite. The impact of gender or urbanization on myopia is controversial. The relationship between nutrition, digital screens, Kawasaki disease, pregnant women smoking during pregnancy, and myopia is still not clear for lack of sufficient evidence. Understanding the various factors that affect myopia helps to clarify the mechanism of myopia formation and also to formulate reasonable prevention and control measures of myopia to protect people's health, especially for adolescents.