Background: The protein encoded by the selenoprotein S gene is considered to be an anti-inflammatory and antioxidant protein and is involved in a variety of diseases. Therefore, we want to study the distribution characteristics of this gene in Chinese diabetic population.
Methods: A total of 170 patients with DM (including 100 patients with T2DM and 70 patients with diabetic nephropathy [DN]) and 100 healthy controls (HC) were selected from Haikou People's Hospital (China) between January 2017 and July 2017. The polymorphisms of three SEPS1 genes (SNP ID: rs4965814, rs28665122, and rs34713741) were measured by massARRAY method, while the polymorphisms of SEPS1 genes (SNP ID: rs4965373) were detected by Sanger sequencing.
Results: Comparing three groups, the results were the following: (a) There was a significant difference in the genotype and allele distribution of rs34713741 between DN group and HC group and between T2DM group and DN group; For this gene locus, the risk of diabetic nephropathy in healthy individuals with T allele was 0.6 times higher than that in individuals with GG genotype (OR = 0.60, 95% CI: 0.46 ~ 0.77). (b) There was a significant difference in the distribution of rs4975814 genotype between DN group and HC group; for this gene locus, the risk of diabetic nephropathy in healthy individuals with T allele was 2.71 times higher than that in individuals with GG genotype (OR = 2.71, 95% CI: 1.66 ~ 4.45).
Conclusion: We conclude that rs34713741 (GT + TT) may be a protective gene for DN and the rs4975814 (GT + TT) may be a susceptibility gene for DN.
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http://dx.doi.org/10.1002/jcla.22967 | DOI Listing |
Chem Res Toxicol
January 2025
Department of Traditional Chinese Medicine, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, China.
J Diabetes Investig
January 2025
Department of Diabetes, Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan.
Aim: To determine the epidemiological characteristics and risk factors for heart failure (HF) among Japanese patients with type 2 diabetes.
Methods: A retrospective cohort analysis, using J-DREAMS database, was conducted from December 2015 to January 2020 with type 2 diabetes. The primary objectives were to describe patient characteristics stratified by HF history at baseline and new HF events during follow-up.
Mar Drugs
January 2025
Division of Functional Food Research, Korea Food Research Institute, Wanju-gun 55365, Republic of Korea.
(), an edible brown alga, is rich in isophloroglucin A (IPA) phlorotannin compounds and is effective in preventing diseases, including diabetes. We evaluated its anti-glycation ability, intracellular reactive oxygen species scavenging activity, inhibitory effect on the accumulation of intracellular MGO/MGO-derived advanced glycation end products (AGE), and regulation of downstream signaling pathways related to the AGE-receptor for AGEs (RAGE) interaction. IPA (0.
View Article and Find Full Text PDFCurr Issues Mol Biol
December 2024
Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
Diabetic nephropathy (DN) affects about one-third of patients with diabetes and can lead to end-stage renal disease despite numerous trials aimed at improving diabetic management. Non-coding RNAs (ncRNAs) represent a new frontier in DN research, as increasing evidence suggests their involvement in the occurrence and progression of DN. A growing body of evidence suggests that long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) in DN signaling pathways might serve as novel biomarkers or therapeutic targets, although this remains to be fully explored.
View Article and Find Full Text PDFDiscov Med
January 2025
Department of Urology, The Affiliated Hefei Hospital of Anhui Medical University (The Second People's Hospital of Hefei), 230011 Hefei, Anhui, China.
Background: Diabetes mellitus is a common metabolic disorder, and diabetic erectile dysfunction (DMED) is one of its common complications. The differentiation of the types of erectile dysfunction (ED) is fundamental to treatment, yet there is a lack of simple and efficacious tools for this purpose in clinical practice. In this study, we endeavor to predict ED types using commonly available clinical data from diabetic patients, aiming to develop and assess a risk prediction model for organic erectile dysfunction in individuals with type 2 diabetes.
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