Association of NID2 SNPs with Glioma Risk and Prognosis in the Chinese Population.

Glioma is the most common primary intracranial tumor with high mortality and poor prognosis. The purpose of this study was to investigate how single-nucleotide polymorphisms (SNPs) of the NID2 gene affect glioma risk and prognosis. Four candidate SNPs of NID2 in 529 glioma patients and 478 healthy controls were successfully genotyped by Agena MassARRAY mass spectrometer. Logistic regression was utilized to assess the associations between NID2 SNPs and glioma risk under different genetic models. Furthermore, the relationship between risk-related SNPs in NID2 and the prognosis of glioma patients was explored through Kaplan-Meier (KM) survival curve and Cox proportional hazard regression analysis. The results showed that rs11846847 (OR 1.24, p = 0.017) and rs1874569 (OR 1.22, p = 0.026) were significantly associated with an increased risk of glioma, and rs11846847 also had a risk-increasing effect on glioma in participants ≤ 40 years old. The interaction model of rs11846847 and rs1874569 could be more suitable for forecasting glioma risk. We also discovered a significant association between rs1874569 and poor prognosis in glioma patients (HR 1.32, p = 0.039) and especially CC genotype was relevant to shorter overall survival (OS) and progression-free survival (PFS) in patients with high-grade glioma. Additionally, the study demonstrated that gross total resection or chemotherapy improve glioma prognosis in the Chinese Han population. This study is the first to provide evidence for the association of NID2 SNPs with glioma risk and prognosis, suggesting that NID2 variants might be potential factors for glioma.

Very important pharmacogenes polymorphism landscape and potential clinical relevance in the Chinese Mongolian.

PURPOSE: Our study genotyped pharmacogenes in 200 individuals from Inner Mongolia Autonomous Region, China. Aim to find distinct pharmacogenomic variations among the Mongolian population and to investigate the potential clinically operable gene-drug connection and genotype-phenotype correlation of differential variation in the Mongolian population. METHODS: We sampled 61 variations of 28 genes in PharmGKB and genotyped them using Agena MassARRAY Assay. We also obtained the allele frequency and genotype distribution data of 26 populations from the 1000 Genomes Project (1000G), and then conducted comparison and statistical analysis. RESULTS: After Bonferroni correction, there were significant genotype frequency distribution differences between the Mongolian and 26 populations: PTGS2 (rs20417), NAT2 (rs1801280, rs1799929, and rs1208), ALOX5(rs2115819), and CYP2D6 (rs1065852). It was also found that the KHV showed the smallest differences from the Mongolian and the GWD showed the largest differences. Furthermore, the differences in variants might be related to the risk of non-steroidal anti-inflammatory drug use, the slow acetylation phenotype, and other pharmacological effectiveness and toxicity in the Mongolian population. CONCLUSION: Our study demonstrates different pharmacogenomic variants in the Mongolian and fills the gaps in pharmacogenomic information of the Mongolian. Our analysis of VIPs variants in the Mongolian population may contribute to the development of safer treatment regimens and the use of personalized treatment approaches.

Genetic polymorphisms of pharmacogenomic VIP variants in the Lahu population from Yunnan Province.

BACKGROUND: Pharmacogenomics has been widely used to study the very important pharmacogenetic (VIP) variants among populations, but information on pharmacogenomics in the Lahu population is limited. The purpose of this study was to determine the differences in the distribution of VIP variants between the Lahu and the other 26 populations. METHODS: We genotyped 55 VIP variants of 27 genes in the Lahu population from the PharmGKB database. χ2 test was used to compare the genotype and allele frequencies between the Lahu and the other 26 populations from the 1000 Genomes Project. RESULTS: The genotype and allele frequencies of single nucleotide polymorphisms (SNPs) on rs20417 (PTGS2), rs776746 (CYP3A5), rs2115819 (ALOX5), and rs3093105 (CYP4F2) were considerably different in the Lahu population compared with those in the other 26 populations. Besides, based on the PharmGKB database, we identified several VIP variants that may alter the drug metabolism of aspirin (PTGS2), tacrolimus (CYP3A5), montelukast (ALOX5), and vitamin E (CYP4F2). CONCLUSION: The results show that there are significant differences in the genotype frequency distribution between the Lahu and the other 26 populations. Our study supplements the pharmacogenomics information of the Lahu population and provides a theoretical basis for individualized medicine in Lahu.

Effect of PITX2 genetic variants on the susceptibility to stroke in the Chinese Han population.

PURPOSE: Stroke is a multifactorial and complex disease caused by the obstruction or rupture of cerebrovascular. To explore the influence of genetic factors on stroke susceptibility, we investigated the association between four single nucleotide polymorphisms (SNPs) in the paired-like homeodomain transcription factor 2 (PITX2) gene and stroke risk. METHODS: A total of 977 volunteers including 476 stroke patients and 501 control individuals were recruited. The association between PITX2 polymorphisms and stroke risk was evaluated using genetic models and haplotype analyses. The strength of the association between each studied polymorphisms and stroke risk was evaluated by calculating odds ratios (ORs) and 95% confidence intervals (CIs). What's more, multifactor dimensionality reduction (MDR) was used to predict the interaction between SNPs. RESULTS: Our study showed that rs6817105 in PITX2 was related to a significant increase in stroke susceptibility (OR = 1.42, 95% CI = 1.04-1.94, p = 0.028). Stratified analyses based on gender indicated that rs6817105, rs13143308, and rs6843082 polymorphisms were significantly associated with an increased risk of stroke in male (OR = 0.68, 95% CI = 0.47-0.99, p = 0.042; OR = 0.53, 95% CI = 0.30-0.96, p = 0.035; and OR = 0.55, 95% CI = 0.30-0.99, p = 0.047). Besides, SNP rs6817105 was significantly increased the risk of stroke in people at age over 65 years (OR = 1.87, 95% CI =1.12-3.11, p = 0.016). MDR showed that the interaction model of rs6817105 and rs3853445 emerged as the best predictor between the PITX2 gene and stroke susceptibility. CONCLUSIONS: This study indicated that there was a significant association between the PITX2 gene and stroke risk, and provided some data as far as possible to support the prevention of stroke.

Association between the ABCA1 (R219K) polymorphism and lipid profiles: a meta-analysis.

Conflicting evidence was found about the relationship between lipid profiles and R219K polymorphism in adenosine triphosphate-binding cassette exporter A1 (ABCA1) gene. In this study, four meta-analyses were conducted to assess the effect of R219K on lipid levels, including high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol, total cholesterol, and triglycerides (TG). A total of 125 samples of 87 studies (about 60,262 subjects) were included. The effect of each study was expressed using the standard mean difference (SMD) and 95% confidence interval (95% CI) and pooled by meta-analysis in the random-effects model. Subgroup and meta-regression analyses were conducted to explore potential heterogeneity sources. The overall pooled effect showed the following results. (1) The R219K was significantly associated with HDLC level (SMD = - 0.25 mmol/L, 95%CI - 0.32 to - 0.18, z = - 6.96, P < 0.01, recessive genetic model). People with different genotypes had significantly different HDLC levels under the recessive, codominant and dominant genetic models (all Ps < 0.01). (2) A weak and indeterminate relationship between R219K and TG level was observed (SMD = 0.18 mmol/L, 95%CI 0.06-0.30, z = 3.01, P < 0.01, recessive genetic model). These findings suggested that R219K was associated with HDLC and TG levels, which might implicate a promising clinical application for lipid-related disorders, though the influences of race, health status, BMI, and other heterogeneity sources should be considered when interpreting current findings. The protocol was registered at PROSPERO (registration number: CRD42021231178).