ABSTRACT. We evaluated the influence of gene-gene interactions between VANGL1, FZD3, and FZD6 on the risk of neural tube defects (NTDs) in Han population in the north of China. Two single nucleotide polymorphisms (SNPs) (rs4839469 and rs34059106) within VANGL1, two SNPs (rs2241802 and rs28639533) within FZD3, and three SNPs (rs827528, rs3808553, and rs12549394) within FZD6 were genotyped in 135 NTD patients and 135 controls. The gene-gene 2 R.P. Zhang et al. Genetics and Molecular Research 15 (3): gmr.15039010 interactions between VANGL1, FZD3, and FZD6 were analyzed using multifactor dimensionality reduction (MDR) software. The distribution of genotypes of rs4 839 469 within VANGL1 and rs3 808 553 within FZD6 differed significantly difference between patients and controls (P < 0.05). MDR revealed significance in models with 2 SNPs (rs4839469 and rs3808553) (OR = 3.18, 95%CI = 1.85-5.44; χ 2 = 18.39, P < 0.0001), 3 SNPs (rs4839469, rs2241802, and rs3808553) (OR = 4.17, 95%CI = 2.43-7.14; χ 2 = 28.5, P < 0.0001), and 4 SNPs (rs4839469, rs2241802, rs827528, and rs3808553) (OR = 7.34, 95%CI = 3.98-13.54; χ 2 = 45.3, P < 0.0001). Gene-gene interaction between VANGL1, FZD3, and FZD6 may exist, which may increase the risk of NTDs. This work provides insight into the understanding of the etiology of NTDs.

Background: AKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools. Methods: Extensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases. Results: In this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs—namely, G157R, G159V, G336D, and H265Y—were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer. Conclusions: This study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.