Long non-coding RNAs (lncRNAs) play important roles in the maintenance of metabolic homeostasis. Recently, many studies have suggested that lncRNAs, such as Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) and Imprinted Maternally Expressed Transcript (H19), might participate in the pathogenesis of metabolic disorders such as obesity. We conducted a case-control study with 150 Russian children and adolescents aged between 5 and 17 years old in order to assess the statistical association between the single nucleotide polymorphisms (SNPs) rs3200401 in and rs217727 in , and the risk of developing obesity in this population. We further explored the possible association of rs3200401 and rs217727 with BMI Z-score and insulin resistance. The rs3200401 and rs217727 SNPs were genotyped using Taqman SNP genotyping assay. The rs3200401 SNP was identified as a risk factor for childhood obesity ( 0.05) under the dominant and allelic models, and the CT heterozygous genotype was associated with the risk of increased BMI and with insulin resistance. The rs217727 SNP had no significant association with obesity risk (all 0.05). Our findings thus suggest that SNP rs3200401 is a potential indicator of obesity susceptibility and pathogenesis in children and adolescents.
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http://dx.doi.org/10.3390/ncrna9020022 | DOI Listing |
Noncoding RNA
March 2023
College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates.
Long non-coding RNAs (lncRNAs) play important roles in the maintenance of metabolic homeostasis. Recently, many studies have suggested that lncRNAs, such as Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) and Imprinted Maternally Expressed Transcript (H19), might participate in the pathogenesis of metabolic disorders such as obesity. We conducted a case-control study with 150 Russian children and adolescents aged between 5 and 17 years old in order to assess the statistical association between the single nucleotide polymorphisms (SNPs) rs3200401 in and rs217727 in , and the risk of developing obesity in this population.
View Article and Find Full Text PDFJ Mol Neurosci
July 2020
Student of Dentistry, Dental School, Shahid Beheshti University of Medical Science, Tehran, Iran.
The artificial neural network (ANN) is a sort of machine learning method which has been used in determination of risk of human disorders. In the current investigation, we have created an ANN and trained it based on the genetic data of 401 multiple sclerosis (MS) patients and 390 healthy subjects. Single nucleotide polymorphisms (SNPs) within ANRIL (rs1333045, rs1333048, rs4977574 and rs10757278), EVI5 (rs6680578, rs10735781 and rs11810217), ACE (rs4359 and rs1799752), MALAT1 (rs619586 and rs3200401), GAS5 (rs2067079 and rs6790), H19 (rs2839698 and rs217727), NINJ2 (rs11833579 and rs3809263), GRM7 (rs6782011 and rs779867), VLA4 (rs1143676), CBLB (rs12487066) and VEGFA (rs3025039 and rs2071559) had been genotyped in all individuals.
View Article and Find Full Text PDFMol Brain
October 2018
Department of Neurology, The First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China.
Objectives Long non-coding RNAs (lncRNAs) have been identified as key regulators in the development of atherosclerosis, which is a major cause of ischemic stroke. However, to date, there are no reports on the association between lncRNA gene variation and the risk of ischemic stroke. Therefore, we assessed the association between H19 and MALAT1 gene polymorphisms and susceptibility to ischemic stroke in a northern Chinese Han population.
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