Testing computational prediction of missense mutation phenotypes: Functional characterization of 204 mutations of human cystathionine beta synthase

Predicting the phenotypes of missense mutations uncovered by large‐scale sequencing projects is an important goal in computational biology. High‐confidence predictions can be an aid in focusing experimental and association studies on those mutations most likely to be associated with causative relationships between mutation and disease. As an aid in developing these methods further, we have derived a set of random mutations of the enzymatic domains of human cystathionine beta synthase. This enzyme is a dimeric protein that catalyzes the condensation of serine and homocysteine to produce cystathionine. Yeast missing this enzyme cannot grow on medium lacking a source of cysteine, while transfection of functional human CBS into yeast strains missing endogenous enzyme can successfully complement for the missing gene. We used PCR mutagenesis with error‐prone Taq polymerase to produce 948 colonies and compared cell growth in the presence or absence of a cysteine source as a measure of CBS function. We were able to infer the phenotypes of 204 single‐site mutants, 79 of them deleterious and 125 neutral. This set was used to test the accuracy of six publicly available prediction methods for phenotype prediction of missense mutations: SIFT, PolyPhen, PMut, SNPs3D, PhD‐SNP, and nsSNPAnalyzer. The top methods are PolyPhen, SIFT, and nsSNPAnalyzer, which have similar performance. Using kernel discriminant functions, we found that the difference in position‐specific scoring matrix values is more predictive than the wild‐type PSSM score alone, and that the relative surface area in the biologically relevant complex is more predictive than that of the monomeric proteins. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Characterization of novel and uncharacterized p53 SNPs in the Chinese population--intron 2 SNP co-segregates with the common codon 72 polymorphism

Multiple single nucleotide polymorphisms (SNPs) have been identified in the tumor suppressor gene p53, though the relevance of many of them is unclear. Some of them are also differentially distributed in various ethnic populations, suggesting selective functionality. We have therefore sequenced all exons and flanking regions of p53 from the Singaporean Chinese population and report here the characterization of some novel and uncharacterized SNPs - four in intron 1 (nucleotide positions 8759/10361/10506/11130), three in intron 3 (11968/11969/11974) and two in the 3'UTR (19168/19514). Allelic frequencies were determined for all these and some known SNPs, and were compared in a limited scale to leukemia and lung cancer patient samples. Intron 2 (11827) and 7 (14181/14201) SNPs were found to have a high minor allele frequency of between 26-47%, in contrast to the lower frequencies found in the US population, but similar in trend to the codon 72 polymorphism (SNP12139) that shows a distribution pattern correlative with latitude. Several of the SNPs were linked, such as those in introns 1, 3 and 7. Most interestingly, we noticed the co-segregation of the intron 2 and the codon 72 SNPs, the latter which has been shown to be expressed in an allele-specific manner, suggesting possible regulatory cross-talk. Association analysis indicated that the T/G alleles in both the co-segregating intron 7 SNPs and a 4tagSNP haplotype was strongly associated increased susceptibility to lung cancer in non-smoker females [OR: 1.97 (1.32, 3.394)]. These data together demonstrate high SNP diversity in p53 gene between different populations, highlighting ethnicity-based differences, and their association with cancer risk.     

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.     

SNP mining porcine ESTs with MAVIANT, a novel tool for SNP evaluation and annotation

MOTIVATION: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators. RESULTS: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies. AVAILABILITY: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Genetic association of LOXL1 gene variants and exfoliation glaucoma in a Utah cohort

Exfoliation glaucoma (XFG) is the commonest identifiable cause of secondary open-angle glaucoma worldwide, characterized by the deposition of fibrillar proteins in the anterior segment of the eye. We investigated LOXL1 gene variants previously identified to confer susceptibility to exfoliation glaucoma (XFG) in a Utah Caucasian cohort. After a standard eye examination protocol we genotyped SNPs rs2165241 and rs3825942 in 62 XFG or XFS patients and 170 normal controls. Genotype frequency distribution, odds ratios (ORs), and population attributable risks were calculated for the risk alleles. The SNP rs2165241 was significantly associated with XFG and XFS (p=4.13x10-9 for an additive model, ORhet=4.42 (2.30-8.50), ORhom=34.19 (4.48-261.00); T allele: 83.1% in cases versus 52.4% in controls). Significant association was also found for rs3825942: (p=1.89x10-6). Our findings confirm genetic association of LOXL1 with XFG and XFS and implicate a potential role of cross linking of elastin in the pathogenesis of XFG. This information will potentially guide glaucoma monitoring efforts by targeting individuals whose genetic profiles put them at higher risk for XFG.     

The 18p11.22 locus is associated with never smoker non-small cell lung cancer susceptibility in Korean populations

The proportion of never smoker non-small cell lung cancer (NSCLC) in Asia is about 30-40%. Despite the striking demographics and high prevalence of never smoker NSCLC, the exact causes still remain undetermined. Although several genome wide association (GWA) studies were conducted to find susceptibility loci for lung cancer in never smokers, no regions were replicated except for 5p15.33, suggesting locus heterogeneity and different environmental toxic effects. To identify genetic loci associated with susceptibility of lung cancer in never smokers, we performed a GWA analysis using the Affymetrix 6.0 SNP array. For discovery GWA set, we recruited 446 never smoking Korean patients with NSCLC and 497 normal subjects. We tested association of SNPs with lung cancer susceptibility using the Cochran-Armitage trend test. For validation, 39 SNPs were selected from the top 50 SNPs and five additional SNPs were selected in the DAB1 gene region which showed significant associations in the GWA analysis. The validation SNPs were genotyped in an independent sample including 434 patients and 1,000 controls. Among the 44 validation SNPs, two SNPs (rs11080466 and rs11663246) near the APCDD1, NAPG and FAM38B genes in the 18p11.22 region were replicated. P value of rs11080466 was 1.08 × 10(-6) in the combined sets (2.68 × 10(-5) in the discovery set and 2.60 × 10(-3) in the validation set) and odds ratio was 0.68 (0.58-0.79). We observed similar association for rs11663246. Our result suggests the 18p11.22 region as a novel lung cancer susceptibility locus in never smokers.     

Evidence of admixture from haplotyping in an epidemiological study of UK Caucasian males: implications for association analyses

OBJECTIVE: Cohort and case-control genetic association studies offer the greatest power to detect small genotypic influences on disease phenotypes, relative to family-based designs. However, genetic subdivisions could confound studies involving unrelated individuals, but the topic has been little investigated. We examined geographical and interallelic association of SNP and microsatellite haplotypes of the Y chromosome, of regions of chromosome 11, and of autosomal SNP genotypes relevant to cardiovascular risk traits in a UK-wide epidemiological survey. RESULTS: We show evidence (p = 0.00001) of the Danelaw history of the UK, marked by a two-fold excess of a Viking Y haplotype in central England. We also found evidence for a (different) single-centre geographical over-representation of one haplotype, both for APOC3-A4-A5 and for IGF2. The basis of this remains obscure but neither reflect genotyping error nor correlate with the phenotypic associations by centre of these markers. A panel of SNPs relevant to cardiovascular risks traits showed neither association with geographical location nor with Y haplotypes. CONCLUSION: Combinations of Y haplotyping, autosomal haplotyping, and genome-wide SNP typing, taken together with phenotypic2 associations, should improve epidemiological recognition and interpretation of possible confounding by genetic subdivision.     

人染色体8p11(CHRNB3-CHRNA6)区域基因多态性与中国汉族人群肺癌易感性的相关性

为探讨人染色体8p11(CHRNB3-CHRNA6)区域基因多态性与中国汉族人群肺癌遗传易感性之间的关系,文章采用病例-对照研究,对784例肺癌患者和782例性别、年龄、籍贯频数与之相匹配的健康对照中该区域6个标签SNP位点进行基因分型,并统计分析其基因型频率分布与肺癌易感性的关系,以及吸烟在其中的影响。结果发现rs16891561位点TT基因型在60岁以上人群(校正OR=0.42,95%CI=0.20-0.88;P=0.022)、女性人群(校正OR=0.34,95%CI=0.13-0.87;P=0.025)、非吸烟人群中(校正OR=0.32,95%CI=0.13-0.79;P=0.013)对肺癌发生具有保护效应;rs4236926位点TT基因型在60岁以上人群(校正OR=0.48,95%CI=0.23-0.99;P=0.048)、非吸烟人群(校正OR=0.32,95%CI=0.13-0.80;P=0.014)中对肺癌发生具有保护效应,这两种保护效应主要是与腺癌相关。对这两个位点进行累积效应分析发现,含有3~4个变异等位基因型的非吸烟者罹患肺癌的风险显著降低(校正OR=0.29,95%CI=0.11-0.71;P=0.007),并且,含有3~4个变异等位基因型的个体累计吸烟量("包-年"平均数=13.2)与其他个体相比显著降低。由此可见人染色体8p11(CHRNB3-CHRNA6)区域基因多态性与中国汉族人群肺癌易感性和吸烟行为相关。     

Computational detection of deleterious SNPs and their effect on sequence and structural level of the <Emphasis Type="Italic">VHL</Emphasis> gene

In this work we have analyzed the genetic variation that can alter the expression and the function of the VHL gene using computational methods. Of 110 single nucleotide polymorphisms (SNPs), 33 were found to be nonsynonymous (nsSNPs) and 23 SNPs were found in untranslated regions. Of the 33 nsSNPs investigated, 36.3% were found to be deleterious by both SIFT and PolyPhen servers. An untranslated region (UTR) resource tool suggested that two SNPs in the 5' UTR region and six SNPs in the 3' UTR region might change the protein expression levels. It was found by both SIFT and PolyPhen servers that a mutation from histidine to arginine at position 115 of the native protein of the VHL gene was most deleterious. A structural analysis of this mutated protein and the native protein was performed and had a root mean square deviation (RMSD) of 2.78 A. Based on this work, we propose that the nsSNP with a SNPid of rs5030812 is an important candidate for the cause of von Hippel-Lindau syndrome via the VHL gene.     

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.     

Strong signature of natural selection within an FHIT intron implicated in prostate cancer risk

Previously, a candidate gene linkage approach on brother pairs affected with prostate cancer identified a locus of prostate cancer susceptibility at D3S1234 within the fragile histidine triad gene (FHIT), a tumor suppressor that induces apoptosis. Subsequent association tests on 16 SNPs spanning approximately 381 kb surrounding D3S1234 in Americans of European descent revealed significant evidence of association for a single SNP within intron 5 of FHIT. In the current study, re-sequencing and genotyping within a 28.5 kb region surrounding this SNP further delineated the association with prostate cancer risk to a 15 kb region. Multiple SNPs in sequences under evolutionary constraint within intron 5 of FHIT defined several related haplotypes with an increased risk of prostate cancer in European-Americans. Strong associations were detected for a risk haplotype defined by SNPs 138543, 142413, and 152494 in all cases (Pearson's chi(2) = 12.34, df 1, P = 0.00045) and for the homozygous risk haplotype defined by SNPs 144716, 142413, and 148444 in cases that shared 2 alleles identical by descent with their affected brothers (Pearson's chi(2) = 11.50, df 1, P = 0.00070). In addition to highly conserved sequences encompassing SNPs 148444 and 152413, population studies revealed strong signatures of natural selection for a 1 kb window covering the SNP 144716 in two human populations, the European American (pi = 0.0072, Tajima's D = 3.31, 14 SNPs) and the Japanese (pi = 0.0049, Fay & Wu's H = 8.05, 14 SNPs), as well as in chimpanzees (Fay & Wu's H = 8.62, 12 SNPs). These results strongly support the involvement of the FHIT intronic region in an increased risk of prostate cancer.     

Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome

Significant interest has emerged in mapping genetic susceptibility for complex traits through whole-genome association studies. These studies rely on the extent of association, i.e., linkage disequilibrium (LD), between single nucleotide polymorphisms (SNPs) across the human genome. LD describes the nonrandom association between SNP pairs and can be used as a metric when designing maximally informative panels of SNPs for association studies in human populations. Using data from the 1.58 million SNPs genotyped by Perlegen, we explored the allele frequency dependence of the LD statistic r(2) both empirically and theoretically. We show that average r(2) values between SNPs unmatched for allele frequency are always limited to much less than 1 (theoretical approximately 0.46 to 0.57 for this dataset). Frequency matching of SNP pairs provides a more sensitive measure for assessing the average decay of LD and generates average r(2) values across nearly the entire informative range (from 0 to 0.89 through 0.95). Additionally, we analyzed the extent of perfect LD (r(2) = 1.0) using frequency-matched SNPs and found significant differences in the extent of LD in genic regions versus intergenic regions. The SNP pairs exhibiting perfect LD showed a significant bias for derived, nonancestral alleles, providing evidence for positive natural selection in the human genome.     

Individual and combined effects of MDM2 SNP309 and TP53 Arg72Pro on breast cancer risk: an updated meta-analysis

The tumor suppressor gene TP53 and its negative regulator murine double minute 2 are involved in multiple cellular pathways. Two potentially functional single nucleotide polymorphisms (SNPs) MDM2 SNP309 and TP53 R72P have been extensively investigated to be associated with breast cancer risk. However, the original studies as well as the subsequent meta-analysis, have yielded contradictory results for the individual effect of the two SNPs on breast cancer risk, plus that conflicting results also existed for the combined effects of MDM2 SNP309 and TP53 R72P on breast cancer risk. This meta-analysis aimed to clarify the individual and combined effects of these two genes on breast cancer risk. We performed a meta-analysis of publications with a total 9,563 cases and 9,468 controls concerning MDM2 SNP309 polymorphism and 19,748 cases and 19,962 controls concerning TP53 R72P. Odds ratios (ORs) with 95 % confidence intervals (CIs) were used to assess the strength of the association. In overall meta-analysis, individuals with the MDM2 SNP309TG genotype were associated with a borderline higher breast cancer risk than those with TT genotype (OR = 1.11, 95 % CI: 1.00-1.24, P (heterogeneity) = 0.007), whereas the TP53 R72P CC or GC genotype had no effects on breast cancer risk. In the stratified analyses, a significant association between MDM2 SNP309 and breast cancer risk were observed in Asian, but null significant association between TP53 R72P and breast cancer risk were found even in various subgroups. Moreover, no significant combined effects of MDM2 SNP309 and TP53 R72P were observed on breast cancer risk. The borderline association between MDM2 SNP309 and breast cancer risk in overall analysis should be treated with caution, and no significant combined effects for the two SNPs on breast cancer risk suggested functional investigations warranted to explore the molecular mechanism of the TP53-MDM2 circuit genes.     

Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers

Germline mutations in BRCA1 and BRCA2 confer high risks of breast cancer. However, evidence suggests that these risks are modified by other genetic or environmental factors that cluster in families. A recent genome-wide association study has shown that common alleles at single nucleotide polymorphisms (SNPs) in FGFR2 (rs2981582), TNRC9 (rs3803662), and MAP3K1 (rs889312) are associated with increased breast cancer risks in the general population. To investigate whether these loci are also associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers, we genotyped these SNPs in a sample of 10,358 mutation carriers from 23 studies. The minor alleles of SNP rs2981582 and rs889312 were each associated with increased breast cancer risk in BRCA2 mutation carriers (per-allele hazard ratio [HR] = 1.32, 95% CI: 1.20-1.45, p(trend) = 1.7 x 10(-8) and HR = 1.12, 95% CI: 1.02-1.24, p(trend) = 0.02) but not in BRCA1 carriers. rs3803662 was associated with increased breast cancer risk in both BRCA1 and BRCA2 mutation carriers (per-allele HR = 1.13, 95% CI: 1.06-1.20, p(trend) = 5 x 10(-5) in BRCA1 and BRCA2 combined). These loci appear to interact multiplicatively on breast cancer risk in BRCA2 mutation carriers. The differences in the effects of the FGFR2 and MAP3K1 SNPs between BRCA1 and BRCA2 carriers point to differences in the biology of BRCA1 and BRCA2 breast cancer tumors and confirm the distinct nature of breast cancer in BRCA1 mutation carriers.     

Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia

Many common diseases are accompanied by disturbances in biochemical traits. Identifying the genetic determinants could provide novel insights into disease mechanisms and reveal avenues for developing new therapies. Here, we report a genome-wide association analysis for commonly measured serum and urine biochemical traits. As part of the WTCCC, 500,000 SNPs genome wide were genotyped in 1955 hypertensive individuals characterized for 25 serum and urine biochemical traits. For each trait, we assessed association with individual SNPs, adjusting for age, sex, and BMI. Lipid measurements were further examined in a meta-analysis of genome-wide data from a type 2 diabetes scan. The most promising associations were examined in two epidemiological cohorts. We discovered association between serum urate and SLC2A9, a glucose transporter (p = 2 x 10(-15)) and confirmed this in two independent cohorts, GRAPHIC study (p = 9 x 10(-15)) and TwinsUK (p = 8 x 10(-19)). The odds ratio for hyperuricaemia (defined as urate >0.4 mMol/l) is 1.89 (95% CI = 1.36-2.61) per copy of common allele. We also replicated many genes previously associated with serum lipids and found previously recognized association between LDL levels and SNPs close to genes encoding PSRC1 and CELSR2 (p = 1 x 10(-7)). The common allele was associated with a 6% increase in nonfasting serum LDL. This region showed increased association in the meta-analysis (p = 4 x 10(-14)). This finding provides a potential biological mechanism for the recent association of this same allele of the same SNP with increased risk of coronary disease.     

ADIPOQ gene polymorphisms and cancer risk: A meta-analysis

The results of studies investigating the association between ADIPOQ gene polymorphisms and risk of cancer have been inconsistent and often contradictory. The present meta-analysis was conducted in order to overcome the limitations of any individual study and to provide a more precise overall effect estimate. Relevant studies were identified by searching PubMed and Embase for articles published through May 2012. The strength of the relationship between the ADIPOQ gene and risk of cancer was assessed using odds ratios (ORs). Either a fixed-effects or a random-effects model was used to calculate the overall risk estimates. Fifteen studies were included and five SNPs were considered. A significant association was found between SNP rs2241766 and risk of cancer in the recessive genetic model (OR: 0.768, 95% CI: [0.626, 0.942], P = 0.011); a significant relationship was also found between SNP rs1501299 and risk of cancer in both an allele contrast (OR: 0.141, 95%CI: [0.113, 0.176], P < 0.001) and the dominant genetic model (OR: 0.904, 95%CI: [0.830, 0.985], P = 0.021); no association was found with the rs266729, rs822395, or rs822396 SNPs. Adjusted ORs were also considered, but no statistically significant association was found in homozygote contrasts for any of the five SNPs after adjustment. Our results suggest that two polymorphisms, SNP rs2241766 and SNP rs1501299, of the ADIPOQ gene may be associated with reduced risk of cancer. However, the overall strength of association is mild to moderate, and additional well-designed studies are needed to confirm the present conclusion.     

An analysis of single nucleotide polymorphisms of 125 DNA repair genes in the Texas genome-wide association study of lung cancer with a replication for the XRCC4 SNPs

DNA repair genes are important for maintaining genomic stability and limiting carcinogenesis. We analyzed all single nucleotide polymorphisms (SNPs) of 125 DNA repair genes covered by the Illumina HumanHap300 (v1.1) BeadChips in a previously conducted genome-wide association study (GWAS) of 1154 lung cancer cases and 1137 controls and replicated the top-hits of XRCC4 SNPs in an independent set of 597 cases and 611 controls in Texas populations. We found that six of 20 XRCC4 SNPs were associated with a decreased risk of lung cancer with a P-value of 0.01 or lower in the discovery dataset, of which the most significant SNP was rs10040363 (P for allelic test=4.89 x 10??). Moreover, the data in this region allowed us to impute a potentially functional SNP rs2075685 (imputed P for allelic test=1.3 x 10?3). A luciferase reporter assay demonstrated that the rs2075685G>T change in the XRCC4 promoter increased expression of the gene. In the replication study of rs10040363, rs1478486, rs9293329, and rs2075685, however, only rs10040363 achieved a borderline association with a decreased risk of lung cancer in a dominant model (adjusted OR=0.80, 95% CI=0.62-1.03 and P=0.079). In the final combined analysis of both the Texas GWAS discovery and replication datasets, the strength of the association was increased for rs10040363 (adjusted OR=0.77, 95% CI=0.66-0.89, P(dominant)=5 x 10?? and P for trend=5 x 10??) and rs1478486 (adjusted OR=0.82, 95% CI=0.71-0.94, P(dominant)=6 x 10?3 and P for trend=3.5 x 10?3). Finally, we conducted a meta-analysis of these XRCC4 SNPs with available data from published GWA studies of lung cancer with a total of 12,312 cases and 47,921 controls, in which none of these XRCC4 SNPs was associated with lung cancer risk. It appeared that rs2075685, although associated with increased expression of a reporter gene and lung cancer risk in the Texas populations, did not have an effect on lung cancer risk in other populations. This study underscores the importance of replication using published data in larger populations.     

Applications of computational algorithm tools to identify functional SNPs in cytokine genes

Understanding the functions of single nucleotide polymorphisms (SNPs) can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. However, how to identify functional SNPs from a pool containing both functional and neutral SNPs is challenging. In this study, we analyzed the genetic variations that can alter the expression and function of a group of cytokine proteins using computational tools. As a result, we extracted 4552 SNPs from 45 cytokine proteins from SNPper database. Of particular interest, 828 SNPs were in the 5'UTR region, 961 SNPs were in the 3' UTR region, and 85 SNPs were non-synonymous SNPs (nsSNPs), which cause amino acid change. Evolutionary conservation analysis using the SIFT tool suggested that 8 nsSNPs may disrupt the protein function. Protein structure analysis using the PolyPhen tool suggested that 5 nsSNPs might alter protein structure. Binding motif analysis using the UTResource tool suggested that 27 SNPs in 5' or 3'UTR might change protein expression levels. Our study demonstrates the presence of naturally occurring genetic variations in the cytokine proteins that may affect their expressions and functions with possible roles in complex human disease, such as immune diseases.