Exploration of deleterious single nucleotide polymorphisms in late-onset Alzheimer disease susceptibility genes

Non-synonymous single nucleotide polymorphisms (nsSNPs) are considered as biomarkers to disease susceptibility. In the present study, nsSNPs in CLU, PICALM and BIN1 genes were screened for their functional impact on concerned proteins and their plausible role in Alzheimer disease (AD) susceptibility. Initially, SNPs were retrieved from dbSNP database, followed by identification of potentially deleterious nsSNPs and prediction of their effect on proteins by PolyPhen and SIFT. Protein stability and the probability of mutation occurrence were predicted using I-Mutant and PANTHER respectively. SNPs3D and FASTSNP were used for the functional analysis of nsSNPs. The functional impact on the 3D structure of proteins was evaluated by SWISSPDB viewer and NOMAD-Ref server. On analysis, 3 nsSNPs with IDs rs12800974 (T158P) of PICALM and rs11554585 (R397C) and rs11554585 (N106D) of BIN1 were predicted to be functionally significant with higher scores of I-Mutant, SIFT, PolyPhen, PANTHER, FASTSNP and SNPs3D. The mutant models of these nsSNPs also showed very high energies and RMSD values compared to their native structures. Current study proposes that the three nsSNPs identified in this study constitute a unique resource of potential genetic factors for AD susceptibility.     

Screening and structural evaluation of deleterious Non-Synonymous SNPs of ePHA2 gene involved in susceptibility to cataract formation

Age-related cataract is clinically and genetically heterogeneous disorder affecting the ocular lens, and the leading cause of vision loss and blindness worldwide. Here we screened nonsynonymous single nucleotide polymorphisms (nsSNPs) of a novel gene, EPHA2 responsible for age related cataracts. The SNPs were retrieved from dbSNP. Using I-Mutant, protein stability change was calculated. The potentially functional nsSNPs and their effect on protein was predicted by PolyPhen and SIFT respectively. FASTSNP was used for functional analysis and estimation of risk score. The functional impact on the EPHA2 protein was evaluated by using SWISSPDB viewer and NOMAD-Ref server. Our analysis revealed 16 SNPs as nonsynonymous out of which 6 nsSNPs, namely rs11543934, rs2291806, rs1058371, rs1058370, rs79100278 and rs113882203 were found to be least stable by I-Mutant 2.0 with DDG value of > -1.0. nsSNPs, namely rs35903225, rs2291806, rs1058372, rs1058370, rs79100278 and rs113882203 showed a highly deleterious tolerance index score of 0.00 by SIFT server. Four nsSNPs namely rs11543934, rs2291806, rs1058370 and rs113882203 were found to be probably damaging with PSIC score of ≥ 2. 0 by Polyp hen server. Three nsSNPs namely, rs11543934, rs2291806 and rs1058370 were found to be highly polymorphic with a risk score of 3-4 with a possible effect of Non-conservative change and splicing regulation by FASTSNP. The total energy and RMSD value was higher for the mutant-type structure compared to the native type structure. We concluded that the nsSNP namely rs2291806 as the potential functional polymorphic that is likely to have functional impact on the EPHA2 gene.     

Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach

The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies.     

Relation of glutathione S-transferase T1, M1 and P1 genotypes and breast cancer risk

The aim of this study was to investigate associations between genetic variability in specific Glutathione S-transferases (GST) genes (GSTM1, GSTT1 and GSTP1) and susceptibility to breast cancer. Genotypes of blood specimen DNA were determined for 65 women with incident cases of breast cancer and 108 control subjects. Associations between specific genotypes and the development of breast cancer were examined by the use of logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Neither GSTT1 nor GSTM1 homozygous null genotype was associated with a significant increased risk of developing breast cancer. The presence of valine alleles compared to isoleucine alleles in codon 105 in GSTP1 did not increase the risk of breast cancer development. The risk of breast cancer associated with a combined GSTT1 and GSTM1 null genotype was 3.37 (95% CI = 0.76-2.95, p = 0.115). The only significant association between increased risk of breast cancer development and GSTs polymorphisms was found when GSTT1 null, GSTM1 null and the presence of valine in GSTP1 in codon 105 were combined (p < 0.048, OR = 3.75, 95% CI = 1.01-13.90). Our findings suggest that combined genetic variability in members of the GST gene family may be associated with an increased susceptibility to breast cancer.     

A bioinformatics strategy for detecting the complexity of Chronic Obstructive Pulmonary Disease in Northern Chinese Han Population

Chronic Obstructive Pulmonary Disease (COPD) is a complex human disease which is driven not only by genetic factors, but also by various environmental variables, such as gender, age and smoking. Therefore, there is a demand for investigating the complexity among various risk factors involved in COPD. In this study, 44 tagging SNPs from EPHX1, GSTP1, SERPINE2 and TGFB1 were selected and genotyped in 310 COPD cases and 203 controls, all of which belong to the Han from North China. We integrated functional prediction algorithms of nonsynonymous SNPs (nsSNPs) into Bayesian network to explore the complex regulatory relationships among disease traits and various risk factors. The results showed that three basic variables (age, sex and smoking) were risk factors of COPD-related trait and phenotype. Besides these environmental risk factors, deleterious nsSNPs were found to perform better than those of significant synonymous SNPs when used as variables to make risk prediction of disease outcome. This study provides further evidences for detecting the complexity of COPD in Northern Chinese Han Population.     

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3'' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.     

Glutathione S-transferase M1, T1, and P1 genotypes and breast cancer risk: a study in a Portuguese population

Glutathione S-transferases are a superfamily of multifunctional enzymes that play a key role in Phase II metabolism, detoxifying therapeutic drugs, and various carcinogens by conjugation with glutathione. We undertook a case-control study in Central-Eastern Portuguese population to evaluate the association of null genotype in GSTM1 and GSTT1 along with the polymorphism in GSTP1 (A/G) and susceptibility to breast cancer. The population sample consisted of 85 patients with histological diagnosis of breast cancer and 102 healthy women. Genomic DNA was extracted from blood samples, and genotyping analyses were performed by PCR-based methods. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by unconditional logistic regression. We found a increased breast cancer risk associated with GSTM1 null genotype (OR = 3.597; 95% CI = 1.849-6.999; P = 0.0001) and GSTT1 (OR = 2.592; 95% CI = 1.432-4.690; P = 0.002), but the presence of valine alleles compared to isoleucine alleles in codon 105 in GSTP1 did not increase the risk of breast cancer development. The two-way combination of GSTM1 and GTTT1 null genotypes resulted in 8-fold increase for breast cancer risk (OR = 8.287; 95% CI = 3.124-21.980; P = 0.0001) and the three-way combination of GSTP1 105AA/AG and null genotypes for both GSTM1 and GSTT1 resulted in 5-fold increase for breast cancer risk (OR = 5.040; 95% CI = 1.392-18.248; P = 0.016). Our results suggest that GSTM1 and GSTT1 null genotype alone, both combined or combined with GSTP1 valine alleles, are associated with higher susceptibility to breast cancer development.     

In silico analysis of structural and functional consequences in p16INK4A by deleterious nsSNPs associated CDKN2A gene in malignant melanoma

In this study, we identified the most deleterious nsSNP in CDKN2A gene through structural and functional properties of its protein (p16INK4A) and investigated its binding affinity with cdk6. Out of 118 SNPs, 14 are nsSNPs in the coding region and 17 SNPs were found in the untranslated region (UTR). FastSNP suggested that 7 SNPs in the 5' UTR might change the protein expression levels. Sixty-four percent of nsSNPs are found to be damaged in PolyPhen server among the 14 nsSNPs investigated. With this effort, we modeled the mutant p16INK4A proteins based on these deleterious nsSNPs, out of which three nsSNPs associated p16INK4A had RMSD values of greater than 3.00 A with native protein. From a comparison of total energy of these three mutant proteins, we identified that the major mutation is from Aspartic acid to Tyrosine at the residue position of 84 of p16INK4A. Further, we compared the binding efficiency of both native and mutant p16INK4A with cdk6. We found that mutant p16INK4A has less binding affinity with cdk6 compared to native type. This is due to ten hydrogen bonds and eight salt bridges which exist between the native type and cdk6, whereas the mutant type makes only nine hydrogen bonds and five salt bridges with cdk6. Based on our investigation, we propose that the SNP with the ID rs11552822 could be the most deleterious nsSNP in CDKN2A gene, causing malignant melanoma, as it was well correlated with experimental studies carried out elsewhere.     

Effect of Genetic Variants in Two Chemokine Decoy Receptor Genes,DARC and CCBP2, on Metastatic Potential of Breast Cancer

The inhibitory effect of two chemokine decoy receptors (CDRs), DARC and D6, on breast cancer metastasis is mainly due to their ability to sequester pro-malignant chemokines. We hypothesized that genetic variants in the DARC and CCBP2 (encoding D6) genes may be associated with breast cancer progression. In the present study, we evaluated the genetic contributions of DARC and CCBP2 to metastatic potential, indicated by lymph node metastasis (LNM). Ten single-nucleotide polymorphisms (SNPs) (potentially functional SNPs and block-based tagging SNPs) in DARC and CCBP2 were genotyped in 785 breast cancer patients who had negative lymph nodes and 678 patients with positive lymph nodes. Two non-synonymous SNPs, rs12075 (G42D) in DARC and rs2228468 (S373Y) in CCBP2, were observed to be associated with LNM in univariate analysis and remained significant after adjustment for conventional clinical risk factors, with odds ratios (ORs) of 0.54 (95% confidence interval [CI], 0.37 to 0.79) and 0.78 (95% CI, 0.62 to 0.98), respectively. Additional functional experiments revealed that both of these significant SNPs could affect metastasis of breast cancer in xenograft models by differentially altering the chemokine sequestration ability of their corresponding proteins. Furthermore, heterozygous GD genotype of G42D on human erythrocytes had a significantly stronger chemokine sequestration ability than homozygous GG of G42D ex vivo. Our data suggest that the genetic variants in the CDR genes are probably associated with the varied metastatic potential of breast cancer. The underlying mechanism, though it needs to be further investigated, may be that CDR variants could affect the chemokine sequestration ability of CDR proteins.     

Computational and Structural Investigation of Deleterious Functional SNPs in Breast Cancer BRCA2 Gene

In this work, we have analyzed the genetic variation that can alter the expression and the function in BRCA2 gene using computational methods. Out of the total 534 SNPs, 101 were found to be non synonymous (nsSNPs). Among the 7 SNPs in the untranslated region, 3 SNPs were found in 5′ and 4 SNPs were found in 3′ un-translated regions (UTR). Of the nsSNPs 20.7% were found to be damaging by both SIFT and PolyPhen server among the 101 nsSNPs investigated. UTR resource tool suggested that 2 SNPs in the 5′ UTR region and 4 SNPs in the 3′ UTR regions might change the protein expression levels. The mutation from asparagine to isoleucine at the position 3124 of the native protein of BRCA2 gene was most deleterious by both SIFT and PolyPhen servers. A structural analysis of this mutated protein and the native protein was made which had an RMSD value of 0.301 nm. Based on this work, we proposed that this most deleterious nsSNP with an SNPid rs28897759 is an important candidate for the cause of breast cancer by BRCA2 gene.     

Computational refinement of functional single nucleotide polymorphisms associated with ATM gene

Background

Understanding and predicting molecular basis of disease is one of the major challenges in modern biology and medicine. SNPs associated with complex disorders can create, destroy, or modify protein coding sites. Single amino acid substitutions in the ATM gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown.

Principal findings

We analyzed the deleterious nsSNPs associated with ATM gene based on different computational methods. An integrative scoring system and sequence conservation of amino acid residues was adapted for a priori nsSNP analysis of variants associated with cancer. We further extended our approach on SNPs that could potentially influence protein Post Translational Modifications in ATM gene.

Significance

In the lack of adequate prior reports on the possible deleterious effects of nsSNPs, we have systematically analyzed and characterized the functional variants in both coding and non coding region that can alter the expression and function of ATM gene. In silico characterization of nsSNPs affecting ATM gene function can aid in better understanding of genetic differences in disease susceptibility.     

Polymorphisms of glutathione S-transferases M1, T1, P1 and A1 genes in the Tunisian population: an intra and interethnic comparative approach

Genetic polymorphisms in glutathione S-transferases (GSTs) genes might influence the detoxification activities of the enzymes predisposing individuals to cancer risk. Owing to the presence of these genetic variants, inter-individual and ethnic differences in GSTs detoxification capacity have been observed in various populations. Therefore, the present study was performed to determine the prevalence GSTM1 0/0, GSTT1 0/0, GSTP1 Ile(105)Val, and GSTA1 A/B polymorphisms in 154 healthy individuals from South Tunisia, and to compare them with those observed in North and Centre Tunisian populations and other ethnic groups. GSTM1 and GSTT1 polymorphisms were analyzed by a Multiplex-PCR approach, whereas GSTP1 and GSTA1 polymorphisms were examined by PCR-RFLP. The frequencies of GSTM10/0 and GSTT1 0/0 genotypes were 53.9% and 27.9%, respectively. The genotype distribution of GSTP1 was 47.4% (Ile/Ile), 40.9% (Ile/Val), and 11.7% (Val/Val). For GSTA1, the genotype distribution was 24.7% (A/A), 53.9% (A/B), and 21.4% (B/B). The combined genotypes distribution of GSTM1, GSTT1, GSTP1 and GSTA1 polymorphisms showed that thirty one of the 36 possible genotypes were present in our population; eight of them have a frequency greater than 5%. To the best of our knowledge, this is the first report of GSTs polymorphisms in South Tunisian population. Our findings demonstrate the impact of ethnicity and reveal a characteristic pattern for Tunisian population. The molecular studies in these enzymes provide basis for further epidemiological investigations in the population where these functional polymorphisms alter therapeutic response and act as susceptibility markers for various clinical conditions.     

Next generation sequencing exome data analysis aids in the discovery of SNP and INDEL patterns in Parkinson's disease

Whole exome sequencing is an adept method to reveal novel and disease-related SNPs and INDELs as it screen the actionable areas of the genome. We evaluated the exome sequenced datasets of patients with Parkinson's disease (PD) in South African ethnic origin. The primary focus of this study was to discover the SNPs and INDELs patterns responsible for PD. The variant discovery was performed with genome analysis tool kit best practices variant detection pipelines. The SNPs were linked to the genes and categorized based on the filter-based annotation from ANNOVAR. We identified a total of 7955 SNPs and 9952 INDELs in all seven datasets together. A total of 130 missense nsSNPs were prioritized based on its damaging effect predicted from SIFT and Polyphen2 annotation. We noticed a novel nsSNP rs111655870 in gene LRRK2 that shows the mutation of a Leucine to Phenylalanine at position 208 which can alter the protein function. The study also filtered seven nsSNPs in genes NAGA, SULT4A1, MYH8, FLNA, TPM3, ATP13A1, CLN8 that have potentially deleterious effects predicted by various computational tools. This analysis suggested that the above filtered nsSNPs and INDELs have a functional impact and provide the footing for genetic studies related to PD. Further screening of these variations provides deeper insight for molecular mechanism of disease progression.     

PicSNP: a browsable catalog of nonsynonymous single nucleotide polymorphisms in the human genome

Recent progress in identification and mapping of single nucleotide polymorphisms (SNPs) in the human genome generates an unprecedented opportunity to explore cause-effect relationships between genetic variations and susceptibility to common diseases. For this purpose, one promising strategy would be to select a set of SNPs that potentially alter the function of proteins involved in the pathogenesis of the diseases and compare their frequencies in the affected individuals and the healthy population. In this respect, SNPs that change amino acid sequences (nonsynonymous SNPs; nsSNPs) are of particular interest, since they are more likely to affect protein functions. In this study, we have constructed a catalog of nsSNPs (PicSNP), whose unique features are (i) nsSNPs are classified according to the functions of the affected genes and are searchable under the guidance of hierarchical lists of protein functions and (ii) nsSNPs that lead to amino acid changes in the known functional sites and domains of proteins are highlighted. Out of 1,190,295 SNPs extracted from public database, we identified 3793 nsSNPs and classified them in 1247 categories of protein functions. 495 sites and domains annotated in the Swiss-Prot database were found to include nsSNPs, including 2 nsSNPs in disulfide-binding sites and 38 nsSNPs in transmembrane regions. PicSNP is available via the World Wide Web (http://picsnp.org) and would support research questing for SNPs involved in common diseases.     

Exploring the structural and functional effect of pRB by significant nsSNP in the coding region of RB1 gene causing retinoblastoma

In this study,we identified the most deleterious nsSNP in RB1 gene through structural and functional properties of its protein (pRB) and investigated its binding affinity with E2F-2.Out of 956 SNPs,we investigated 12 nsSNPs in coding region in which three of them (SNPids rs3092895,rs3092903 and rs3092905) are commonly found to be damaged by I-Mutant 2.0,SIFT and PolyPhen programs.With this effort,we modeled the mutant pRB proteins based on these deleterious nsSNPs.From a comparison of total energy,stabilizing residues and RMSD of these three mutant proteins with native pRB protein,we identified that the major mutation is from Glutamic acid to Glycine at the residue position of 746 of pRB.Further,we compared the binding efficiency of both native and mutant pRB (E746G) with E2F-2.We found that mutant pRB has less binding affinity with E2F-2 as compared to native type.This is due to sixteen hydrogen bonding and two salt bridges that exist between native type and E2F-2,whereas mutant type makes only thirteen hydrogen bonds and one salt bridge with E2F-2.Based on our investigation,we propose that the SNP with an id rs3092905 could be the most deleterious nsSNP in RB1 gene causing retinoblastoma.     

BRCA1 基因启动子区SNPs 与散发性乳腺癌易感性的相关研究

目的:探讨BRCA1基因启动子区rs11655505、rs73625095位点单核苷酸多态性与散发性乳腺癌易感性的关系。方法:采用ASA-PCR方法对200例乳腺癌患者(均经病理确诊)及200例正常女性BRCA1基因启动子区rs11655505(A/G)、rs73625095(A/G)位点单核苷酸多态性(SNP)进行分析,并将其PCR产物进行测序。结果:乳腺癌患者BRCA1基因启动子区rs11655505位点的A/G基因型频率为75%,显著高于正常人的40%;A/A基因型频率为7%,G/G基因型频率为18%,分别低于正常人的30%、30%。此位点的A或G等位基因在乳腺癌病例组及对照组中均无差别(x2=2.427,P=0.119);rs73625095位点的A/G基因型频率为68%,显著高于正常人的15%;G/G基因型频率为32%,低于正常人的84%;乳腺癌病例组中BRCA1基因启动子区rs11655505、rs73625095位点的A/G基因型与淋巴结转移与否相比,差别均有统计学意义(x2=7.321,P=0.026、x2=4.782,P=0.029)。结论:BRCA1基因rs11655505位点、rs736...     

Exploring the structural and functional effect of pRB by significant nsSNP in the coding region of <Emphasis Type="Italic">RB1</Emphasis> gene causing retinoblastoma

In this study, we identified the most deleterious nsSNP in RB1 gene through structural and functional properties of its protein (pRB) and investigated its binding affinity with E2F-2. Out of 956 SNPs, we investigated 12 nsSNPs in coding region in which three of them (SNPids rs3092895, rs3092903 and rs3092905) are commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen programs. With this effort, we modeled the mutant pRB proteins based on these deleterious nsSNPs. From a comparison of total energy, stabilizing residues and RMSD of these three mutant proteins with native pRB protein, we identified that the major mutation is from Glutamic acid to Glycine at the residue position of 746 of pRB. Further, we compared the binding efficiency of both native and mutant pRB (E746G) with E2F-2. We found that mutant pRB has less binding affinity with E2F-2 as compared to native type. This is due to sixteen hydrogen bonding and two salt bridges that exist between native type and E2F-2, whereas mutant type makes only thirteen hydrogen bonds and one salt bridge with E2F-2. Based on our investigation, we propose that the SNP with an id rs3092905 could be the most deleterious nsSNP in RB1 gene causing retinoblastoma.     

Glutathione S-transferase M1, T1 and P1 genetic polymorphisms, cigarette smoking and gastric cancer risk

Glutathione S-transferases (GSTs) belong to a superfamily of detoxification enzymes that provide critical defences against a large variety of chemical carcinogens and environmental toxicants. GSTs are present in most epithelial tissues of the human gastrointestinal tract. We investigated associations between genetic variability in specific GST genes (GSTM1, GSTT1 and GSTP1), the interaction with cigarette smoking and susceptibility to gastric cancer. The GSTM1, GSTT1 and GSTP1 polymorphisms were determined using real-time polymerase chain reaction (PCR) and fluorescence resonance energy transfer with Light Cycler Instrument. The study included 70 patients with gastric cancer and 204 controls. Associations between specific genotypes and the development of gastric cancer were examined by use of logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI). The GSTM1 homozygous null genotype was associated with an increased risk of developing gastric cancer (OR = 1.73; 95% CI = 1.10-3.04). GSTT1 homozygous null genotype and GSTP1 genotypes were not associated with the risk of gastric cancer. Also there was no difference between cases and controls in the frequency of val-105 and ile-105 alleles (p = 0.07). After grouping according to smoking status, GSTM1 null genotype was associated with an increased gastric cancer risk for smokers (OR = 2.15; 95% CI, 1.02-4.52). There were no significant differences in the distributions of any of the other GST gene combinations. Our findings suggest that the GSTM1 null genotype may be associated with an increased susceptibility to gastric cancer.