Interaction between alcohol consumption and methylenetetrahydrofolate reductase polymorphisms in thyroid cancer risk: National Cancer Center cohort in Korea

Associations of MTHFR gene polymorphism with lipid metabolism and risk of cerebral infarction in the Northwest Han Chinese population

Objective

Genetic variation in the methylenetetrahydrofolate reductase (MTHFR) gene may contribute to the development of cerebral infarction (CI); however, results have been inconsistent across studies with different populations, including studies of the Chinese population. The aim of this study was to analyze the effect of MTHFR gene polymorphism on serum lipid and homocysteine levels among patients with CI in the Northwest Chinese Han population.

Patients and methods

A total of 521 CI patients and 524 non-CI controls were enrolled in the study. Polymerase chain reaction and hybridization were utilized to identify MTHFR gene polymorphisms. Multivariate logistic regression analysis was used to assess the associations of MTHFR gene polymorphism with risk of CI.

Results

Frequencies of the TT genotype and the T allele were markedly higher among CI patients than among controls. After stratifying our data by sex and age, we determined that these differences in frequency of the TT genotype and the T allele were statistically significant among participants of two different age brackets and among men, but not among women (i.e., there were no statistically significant differences between female patients and female controls). CI patients and control participants with the CT or TT genotype had significantly higher homocysteine (Hcy) levels than those with the CC genotype. Among CI patients, CT/TT carriers showed significantly lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-I (ApoA-I) levels as compared with CC carriers, but there was no significant difference for control participants. Multivariable logistic regression analysis showed that drinking; smoking; diabetes mellitus; levels of Hcy, direct bilirubin (DB), indirect bilirubin (IB), ApoA-I, and total protein (TP); and TT genotype were significant independent risk factors for CI.

Conclusions

The results suggested that the TT genotype of the MTHFR C677T gene polymorphism, which is associated with hyperhomocysteinemia (HHcy), might be of great clinical significance in the identification of new biomarkers for CI and in the development of individualized preventive and therapeutic strategies.

Computational Prediction of Probable Single Nucleotide Polymorphism-Cancer Relationships

Genetic variations such as single nucleotide polymorphisms (SNPs) can cause susceptibility to cancer. Although thousands of genetic variants have been identified to be associated with different cancers, the molecular mechanisms of cancer remain unknown. There is not a particular dataset of relationships between cancer and SNPs, as a bipartite network, for computational analysis and prediction. Link prediction as a computational graph analysis method can help us to gain new insight into the network. In this article, after creating a network between cancer and SNPs using SNPedia and Cancer Research UK databases, we evaluated the computational link prediction methods to foresee new SNP-Cancer relationships. Results show that among the popular scoring methods based on network topology, for relation prediction, the preferential attachment (PA) algorithm is the most robust method according to computational and experimental evidence, and some of its computational predictions are corroborated in recent publications. According to the PA predictions, rs1801394-Non-small cell lung cancer, rs4880-Non-small cell lung cancer, and rs1805794-Colorectal cancer are some of the best probable SNP-Cancer associations that have not yet been mentioned in any published article, and they are the most probable candidates for additional laboratory and validation studies. Also, it is feasible to improve the predicting algorithms to produce new predictions in the future.