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Type 2 diabetes (T2D) is a disease with a prevalence of 9.4% in Mexicans. Its etiology is complex involving environmental and genetic factors. The aim of this study was to analyse the association between PPARG rs1801282, PPARGC1A rs8192678, VEGFA rs2010963, ADRA2A rs553668, KCNQ1 rs2237892, SIRT1 rs7896005, IGF2BP2 rs4402960, and UCP3 rs3781907 single nucleotide variants (SNVs) with T2D and metabolic traits in a case-control study of a population from Mexico City. A total of 831 blood samples of non-diabetic, with healthy control participants (416) and individuals with T2D (415) were collected over a five-year period. After DNA extraction, genotyping was performed with TaqMan probes using real-time PCR. The genotypes were analysed for association with T2D in linear and logistic regressions adjusting for age, sex, and body mass index using the dominant, recessive, and additive models with a Bonferroni correction for multiple comparisons p < 0.001 and for association with related T2D traits fixed with a p < 2.3 × 10-4. The univariate analysis gives a significant (p < 1 × 10-4) for sex, triglycerides, and HOMA-IR. Significant association with T2D was found for ADRA2A rs553668 under the recessive model (OR = 3.640 and 95% CI of 2.330-5.690 (p < 1 × 10-4); statistical power 0.999) and under the additive model (OR = 1.640 and 95% CI of 1.340-2.000 (p < 1 × 10-4); statistical power 0.997). Variants PPARG rs1801282, PPARGC1A rs8192678, SIRT1 rs7896005, IGF2BP2 rs4402960 and UCP3 rs3781907 were nominally associated (p > 0.001 and <0.050). Results describe association of ADRA2A rs553668 with T2D in a Mexican population. Variants with nominal association with T2D require to be replicated in additional Mexican populations.
Pubmed ID: 29800730
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Software program that computes sample size or power for association studies of genes, environmental factors, gene-environment interaction, or gene-gene interaction. Available study designs for a disease (binary) outcome include the unmatched case-control, matched case-control, case-sibling, case-parent, and case-only designs. Study designs for a quantitative tra it include independent individuals and case parent designs. Quanto is a 32-bit Windows application requiring Windows 95, 98, NT, 2000, ME or XP to run. The graphical user interface allows th e user to easily change the model and view the results without having to edit an input file and rerun the program for every model. The results of a session are stored to a log file. This log can be printed or saved to a file for reviewing at a later date. An option is included to create a text file of the log that can be imported into other documents. (entry from Genetic Analysis Software)
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