Genome-wide association studies have identified several loci associated with an increased risk for cardiovascular disease (CVD) and type 2 diabetes (T2D). Polymorphisms within the KCNQ1 (potassium voltage-gated channel, KQT-like subfamily, member 1) gene are consistently associated with T2D in a number of populations. The current study was undertaken to evaluate the association of 3 polymorphisms of KCNQ1 (rs2237892, rs151290 and rs2237895) with T2D and/or CVD. Patients diagnosed with either T2D (320 patients), CVD (250 patients) or both (60 patients) and 516 healthy controls were genotyped by TaqMan assay run on a real time PCR thermocycler. A statistically significant association was found for SNPs rs151290 (OR = 1.76; 95%CI = 1.02-3.05; p = 0.0435) and rs2237895 (OR = 2.49; 95%CI = 1.72-3.61; p < 0.0001) with CVD. SNP rs151290 (OR = 7.43; 95%CI = 1.00-55.22; p = 0.0499) showed a strong association in patients with both T2D and CVD. None of the SNPs showed any significant association with T2D. Haploview analysis showed that the ACC (rs151290, rs2237892 and rs2237895) haplotype is the most significant risk allele combination for CVD, while CCA is the most significant risk haplotype for co-morbidity with T2D. KCNQ1 polymorphism at SNPs rs151290 and rs2237895 is strongly associated with CVD in this population, but presented no association with T2D.
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http://dx.doi.org/10.1590/1678-4685-GMB-2017-0005 | DOI Listing |
BMC Infect Dis
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Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
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Biol Trace Elem Res
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Department of Nutrition and Metabolism, Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, 100050, China.
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Department of Gastroenterology, Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou Medical Center, Nanjing Medical University, 68 Gehu Middle Road, Wujing District, Changzhou, 213000, Jiangsu, China.
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State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao SAR, China.
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January AI, Menlo Park, CA, USA.
This retrospective cohort study evaluates the impact of an AI-supported continuous glucose monitoring (CGM) mobile app ("January V2") on glycemic control and weight management in 944 users, including healthy individuals and those with prediabetes or type 2 diabetes (T2D). The app, leveraging AI to personalize feedback, tracked users' food intake, activity, and glucose responses over 14 days. Significant improvements in time in range (TIR) were observed, particularly in users with lower baseline TIR.
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