CDKN2A-rs10811661 polymorphism, waist-hip ratio, systolic blood pressure, and dyslipidemia are the independent risk factors for prediabetes in a Vietnamese population

Impact of Genetic Risk Score and Dietary Protein Intake on Vitamin D Status in Young Adults from Brazil

Given the relationship between vitamin D deficiency (VDD) and adverse outcomes of metabolic diseases, we investigated the interplay of dietary and genetic components on vitamin D levels and metabolic traits in young adults from Brazil. Genetic analysis, dietary intake, and anthropometric and biochemical measurements were performed in 187 healthy young adults (19−24 years). Genetic risk scores (GRS) from six genetic variants associated with vitamin D (vitamin D-GRS) and 10 genetic variants associated with metabolic disease (metabolic-GRS) were constructed. High vitamin D-GRS showed a significant association with low 25(OH)D concentrations (p = 0.001) and high metabolic-GRS showed a significant association with high fasting insulin concentrations (p = 0.045). A significant interaction was found between vitamin D-GRS and total protein intake (g/day) (adjusted for non-animal protein) on 25(OH)D (pinteraction = 0.006), where individuals consuming a high protein diet (≥73 g/d) and carrying >4 risk alleles for VDD had significantly lower 25(OH)D (p = 0.002) compared to individuals carrying ≤4 risk alleles. Even though our study did not support a link between metabolic-GRS and vitamin D status, our study has demonstrated a novel interaction, where participants with high vitamin D-GRS and consuming ≥73 g of protein/day had significantly lower 25(OH)D levels. Further research is necessary to evaluate the role of animal protein consumption on VDD in Brazilians.

Relationship between PI3K-Akt pathway related gene polymorphisms and symptomatic intracranial atherosclerotic stenosis with hypertension in Chinese Han population

BACKGROUND

PI3K-Akt signaling was proved to be closely related to atherosclerosis, in which hypertension is an important risk factor for atherosclerosis. Studies have shown that genetic susceptibility is vital in the etiology of symptomatic intracranial atherosclerotic stenosis (sICAS), but few candidate genes were identified. This research explores latent connections between single nucleotide polymorphisms (SNPs) of PI3K-Akt related genes and sICAS with hypertension in Han Chinese subjects.

METHODS

Eight genes related to the PI3K-Akt pathway in 400 sICAS patients and 1007 healthy controls of Han nationality were sequenced, and further subgroup analysis based on hypertension was carried out. Chi-squared testing and multiple logistic regression in dominant, recessive, and additive models were used to evaluate the association between SNPs and risk of sICAS with hypertension. When linkage disequilibrium exists in different loci of the same gene, tagSNP represents the SNP in haplotype block.

RESULTS

There were 4 common variants of 1 candidate gene differently distributed between sICAS with or without hypertension. Among these four common variations, INSR rs3745551 was significantly related to the risk of sICAS with hypertension after multiple regression analysis, with the T allele being more prevalent in the sICAS with hypertension.

CONCLUSION

The variant of the INSR rs3745551 loci may be crucial in the pathogenesis of sICAS with hypertension in Chinese Han populations. Furthermore, the C allele at this locus may be a potentially harmful variant in sICAS with hypertension.

Association Between CDKAL1, HHEX, CDKN2A/2B and IGF2BP2 Gene Polymorphisms and Susceptibility to Type 2 Diabetes in Uttarakhand, India

INTRODUCTION

Current study aimed to find the association of genes polymorphism of CDKAL1, HHEX, CDKN2A/2B, and IGF2BP2 with type 2 diabetes (T2DM) in the population of Uttarakhand.

RESEARCH DESIGN AND METHODS

Overall 469 persons comprising 369 recently diagnosed T2DM cases and 100 healthy control were enrolled in the present study. The polymorphisms were analyzed through the PCR-RFLP technique.

RESULTS

For the rs10440833 variant (CDKAL1), CC genotype's frequency was significantly high among T2DM subjects than controls and increase the T2DM risk (OR: 4.46, 95% CI: 2.22-8.99, p <0.0001). The c allele was significantly found to increase the T2DM risk (OR: 2.20, 95% CI: 1.54-3.14, p <0.001). In the rs1111875 variant (HHEX), the difference of genotype frequencies among T2DM cases and control was statistically non-significant (p-0.138). We did not observe significant differences in allelic frequencies among T2DM cases and control (p-0.444). In the case of rs10811661 variant (CDKN2A/2B), frequency of both TC (OR: 3.16, 95% CI: 1.84-5.42, p <0.0001) and TT (OR: 5.84, 95% CI: 1.75-19.45, p -0.004) genotype were significantly higher in T2DM cases in comparison with control and significantly associated with higher T2DM risk. Compared to the C allele, a significant increase in T2DM risk was documented with the T allele (OR: 2.47, 95% CI: 1.55-3.92, p <0.001). For rs4402960 variant (IGF2BP2), TT genotype contributed to increased T2DM risk (OR: 4.25, 95% CI: 2.02-8.93, p -0.0001). T allele's frequency was significantly high in T2DM cases in comparison with healthy control. Except WHR, HDL-C, exercise, household chores, standing work more than 3 hours, and family history, significant differences were found between T2DM cases and healthy individuals in all other parameters.

CONCLUSION

Our study concluded a significant association of CDKAL1, CDKN2A/2B, and IGF2BP2 polymorphism with T2DM in the Uttarakhand population. For HHEX, the genotype and allelic frequencies difference between T2DM cases and control were statistically non-significant. However, a significant association of HHEX gene polymorphism with T2DM was observed only under the dominant model.

Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population

BACKGROUND

Several type 2 diabetes (T2D) susceptibility loci identified via genome-wide association studies were found to be replicated among various populations. However, the influence of these loci on T2D in Thai population is unknown. The aim of this study was to investigate the influence of eight single nucleotide polymorphisms (SNPs) reported in GWA studies on T2D and related quantitative traits in Thai population.

METHODS

Eight SNPs in or near the KCNQ1, CDKN2A/2B, SLC30A8, HHEX, CDKAL1, TCF7L2, MTNR1B, and UBE2E2 genes were genotyped. A case-control association study comprising 500 Thai patients with T2D and 500 ethnically-matched control subjects was conducted. Associations between SNPs and T2D were examined by logistic regression analysis. The impact of these SNPs on quantitative traits was examined by linear regression among case and control subjects.

RESULTS

Five SNPs in KCNQ1 (rs2237892), CDK2A/2B (rs108116610, SLC30A8 (rs13266634), TCF7L2 (rs7903146) and MTNR1B (rs1387153) were found to be marginally associated with risk of developing T2D, with odds ratios ranging from 1.43 to 2.02 (p = 0.047 to 3.0 × 10-4) with adjustments for age, sex, and body mass index. Interestingly, SNP rs13266634 of SLC30A8 gene reached statistical significance after correcting for multiple testing (p = 0.0003) (p < 0.006 after Bonferroni correction). However, no significant association was detected between HHEX (rs1111875), CDKAL1 (rs7756992), or UBE2E2 (rs7612463) and T2D. We also observed association between rs10811661 and both waist circumference and waist-hip ratio (p = 0.007 and p = 0.023, respectively). In addition, rs13266634 in SLC30A8 was associated with glycated hemoglobin (p = 0.018), and rs7903146 in TCF7L2 was associated with high-density lipoprotein cholesterol level (p = 0.023).

CONCLUSION

Of the eight genes included in our analysis, significant association was observed between KCNQ1, CDKN2A/2B, SLC30A8, TCF7L2, and MTNR1B loci and T2D in our Thai study population. Of these, CDKN2A/2B, SLC30A8, and TCF7L2 genes were also significantly associated with anthropometric, glycemic and lipid characteristics. Larger cohort studies and meta-analyses are needed to further confirm the effect of these variants in Thai population.

CDC123/CAMK1D gene rs12779790 polymorphism and rs10811661 polymorphism upstream of the CDKN2A/2B gene in women with gestational diabetes

OBJECTIVE

Gestational diabetes mellitus (GDM) is carbohydrate intolerance occurring in pregnant women. CDC123/CAMK1D and CDKN2A/2B are associated with increased risk of type 2 diabetes and may affect pancreatic beta cell function. The aim of this study was to examine the association between CDKN2A/2B rs10811661 and CDC123/CAMK1D rs12779790 gene polymorphisms and GDM.

STUDY DESIGN

This study included 411 pregnant women. The diagnosis of GDM was based on the International Association of Diabetes and Pregnancy Study Groups criteria. According to the results of their oral glucose tolerance test, the women were divided into two groups: 204 pregnant women with GDM and 207 pregnant women with normal glucose tolerance.

RESULTS

There were no statistically significant differences in the distribution of CDC123/CAMK1D rs12779790 genotypes and alleles between women with GDM and healthy pregnant women. However, there was a statistically significant association between the C allele of CDKN2A/2B rs10811661 polymorphism and reduced risk of GDM (C vs T, OR 0.53, 95% CI 0.36 to 0.79, P=0.0014). In the multivariate logistic regression analysis, older age and higher body mass index before pregnancy were independent significant predictors of a higher risk of GDM, while higher number of C alleles (CDKN2A/2B rs10811661) was a protective factor against GDM.

CONCLUSION

The results of this study suggest an association between CDKN2A/2B gene rs10811661 polymorphism and GDM.

High-Throughput Screening and Prediction Model Building for Novel Hemozoin Inhibitors Using Physicochemical Properties

It is essential to continue the search for novel antimalarial drugs due to the current spread of resistance against artemisinin by Plasmodium falciparum parasites. In this study, we developed in silico models to predict hemozoin inhibitors as a potential first-step screening for novel antimalarials. An in vitro colorimetric high-throughput screening assay of hemozoin formation was used to identify hemozoin inhibitors from 9,600 structurally diverse compounds. The physicochemical properties of positive hits and randomly selected compounds were extracted from the ChemSpider database; they were used for developing prediction models to predict hemozoin inhibitors using two different approaches, i.e., traditional multivariate logistic regression and Bayesian model averaging. Our results showed that a total of 224 positive-hit compounds exhibited the ability to inhibit hemozoin formation, with 50% inhibitory concentrations (IC₅₀s) ranging from 3.1 μM to 199.5 μM. The best model according to traditional multivariate logistic regression included the three variables octanol-water partition coefficient, number of hydrogen bond donors, and number of atoms of hydrogen, while the best model according to Bayesian model averaging included the three variables octanol-water partition coefficient, number of hydrogen bond donors, and index of refraction. Both models had a good discriminatory power, with area under the curve values of 0.736 and 0.781 for the traditional multivariate model and Bayesian model averaging, respectively. In conclusion, the prediction models can be a new, useful, and cost-effective approach for the first screen of hemozoin inhibition-based antimalarial drug discovery.