Number Of Single Nucleotide Polymorphisms Research Articles

Construction of relatedness matrices using genotyping-by-sequencing data.

BackgroundGenotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set.ResultsWe show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2–4 for relatedness between individuals and 5–10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a ‘fin plot’) is given to illustrate this issue and to guide filtering parameters.ConclusionWe provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2252-3) contains supplementary material, which is available to authorized users.

Renin angiotensinogen system gene polymorphisms and essential hypertension among people of West African descent: a systematic review.

This systematic review investigates the high level of hypertension found among urban dwellers in West Africa and in the West African Diaspora in the Americas in relation to variants within the genes encoding the renin angiotensinogen system. For comparison, the results from the Caucasian populations are reviewed as well. Through a PubMed search, 1252 articles were identified and 28 eligible articles assessed in detail of which 13 included a Caucasian population. The results suggest that among the people of West African descent and among the people of Caucasian descent, hypertension is partly related to a number of single nucleotide polymorphisms (SNPs) and haplotypes in the renin gene, the angiotensinogen gene, the angiotensinogen I-converting enzyme gene and the angiotensinogen II type 1 receptor gene. Concordance between these two populations was found for some SNPs. However, for others, it was found that the SNPs associating with hypertension and the disease allele frequencies differed between these populations. Understanding the importance of these variants in a modern life setting may assist our understanding of the increased risk of developing hypertension among West Africans. Because of inconsistency in the results, low statistical power and methodological differences between studies, these results can only be taken as indicative of an association.

Allelic variation on DcAOX1 gene in carrot (Daucus carota L.): An interesting simple sequence repeat in a highly variable intron

The alternative oxidase (AOX) is a key enzyme of the alternative respiration pathway and is involved in plant response to a variety of environmental stresses. The genes encoding for this enzyme are highly polymorphic and thus likely good candidates for molecular marker development to assist plant breeding on stress tolerance. In carrot, DcAOX1 gene has shown to be the most responsive to environmental changes. Therefore, we have studied its allelic variation in different carrot materials, including commercial cultivars, inbred lines, carrot subspecies and carrot crop wild relatives. This work is thus a first step to develop molecular markers based on AOX1 gene. Sequence comparison revealed the existence of high number of single nucleotide polymorphisms (SNPs), as well as several insertion/deletion events (InDels), especially in exon 1 and intron 1. Intron 1 showed to be the most polymorphic region and harbored an insertion event of 400bp, which had highly divergent sequences depending on the carrot genotype. The insertion was located in a region of single tandem repeats (SSR) that was also polymorphic between genotypes. This intronic insertion, together with its associated SSRs, arises as a good source of candidate functional markers (FMs) that, once validated, could greatly contribute to marker assisted selection of new carrot genotypes.

Prediction of the gene expression in normal lung tissue by the gene expression in blood.

BackgroundComparative analysis of gene expression in human tissues is important for understanding the molecular mechanisms underlying tissue-specific control of gene expression. It can also open an avenue for using gene expression in blood (which is the most easily accessible human tissue) to predict gene expression in other (less accessible) tissues, which would facilitate the development of novel gene expression based models for assessing disease risk and progression. Until recently, direct comparative analysis across different tissues was not possible due to the scarcity of paired tissue samples from the same individuals.MethodsIn this study we used paired whole blood/lung gene expression data from the Genotype-Tissue Expression (GTEx) project. We built a generalized linear regression model for each gene using gene expression in lung as the outcome and gene expression in blood, age and gender as predictors.ResultsFor ~18 % of the genes, gene expression in blood was a significant predictor of gene expression in lung. We found that the number of single nucleotide polymorphisms (SNPs) influencing expression of a given gene in either blood or lung, also known as the number of quantitative trait loci (eQTLs), was positively associated with efficacy of blood-based prediction of that gene’s expression in lung. This association was strongest for shared eQTLs: those influencing gene expression in both blood and lung.ConclusionsIn conclusion, for a considerable number of human genes, their expression levels in lung can be predicted using observable gene expression in blood. An abundance of shared eQTLs may explain the strong blood/lung correlations in the gene expression.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-015-0152-7) contains supplementary material, which is available to authorized users.

Genetic susceptibility to arsenic-induced skin lesions and health effects: a review.

Arsenic toxicity in humans manifests several outcomes in humans, which include arsenic-induced genomic instability, DNA damage, impaired DNA repair, carcinogenesis, dermatological lesions and other health related problems. Of the 137 million individuals affected, nearly 26 million individuals are in the state of West Bengal, India. Studies have identified dermatological lesions like keratosis, basal cell carcinoma, Bowen’s diseases, squamous cell carcinoma, etc., as key indicators of aggressive arsenic toxicity in humans. Although a large number of individuals are exposed to arsenic but only about 15 to 20 % individuals showed arsenic induced skin lesions. This clearly indicates that genetic susceptibility plays an important role in arsenic susceptibility. Analyses of genetic susceptibility have been carried out to study the prevalence of single nucleotide polymorphisms (SNPs) in number of genes as they might be involved arsenic metabolism and detoxification. It has been observed that a number SNPs in these genes were significantly associated with arsenic induced skin lesions and other health effects. In the present review we try to coalesce the different observations and associations of SNPs with arsenic-induced toxicity, with special emphasis on the study population from West Bengal. We have adopted certain candidate gene approaches to evaluate the association of arsenic-induced toxic outcomes like skin lesions, conjunctival irritations, DNA damage, epimutagenesis, cancer, etc. This review shall be helpful in understanding the importance of genetic make-up of an individual towards evaluating the xenotoxic outcomes, like those in case of arsenic exposure.

High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool.

SummaryIn wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheat's secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra‐high‐density Axiom® genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site.

Bayesian pedigree inference with small numbers of single nucleotide polymorphisms via a factor-graph representation

We develop a computational framework for addressing pedigree inference problems using small numbers (80–400) of single nucleotide polymorphisms (SNPs). Our approach relaxes the assumptions, which are commonly made, that sampling is complete with respect to the pedigree and that there is no genotyping error. It relies on representing the inferred pedigree as a factor graph and invoking the Sum-Product algorithm to compute and store quantities that allow the joint probability of the data to be rapidly computed under a large class of rearrangements of the pedigree structure. This allows efficient MCMC sampling over the space of pedigrees, and, hence, Bayesian inference of pedigree structure. In this paper we restrict ourselves to inference of pedigrees without loops using SNPs assumed to be unlinked. We present the methodology in general for multigenerational inference, and we illustrate the method by applying it to the inference of full sibling groups in a large sample (n=1157) of Chinook salmon typed at 95 SNPs. The results show that our method provides a better point estimate and estimate of uncertainty than the currently best-available maximum-likelihood sibling reconstruction method. Extensions of this work to more complex scenarios are briefly discussed.

MicroRNA-derived network analysis of differentially methylated genes in schizophrenia, implicating GABA receptor B1 [GABBR1] and protein kinase B [AKT1

BackgroundWhile hundreds of genes have been implicated already in the etiology of schizophrenia, the exact cause is not known or the disease is considered multigenic in origin. Recent discoveries of new types of RNAs and the gradual elimination of the “junk DNA” hypothesis refocused the attention on the noncoding part of the human genome. Here we re-analyzed a recent dataset of differentially methylated genes from schizophrenic patients and cross-tabulated them with cis regulatory and repetitive elements and microRNAs known to be involved in schizophrenia.ResultsWe found that the number of schizophrenia-related (SZ) microRNA targets follows a scale-free distribution with several microRNA hubs and that schizophrenia-related microRNAs with shared targets form a small-world network. The top ten microRNAs with the highest number of SZ gene targets regulate approximately 80 % of all microRNA-regulated genes whereas the top two microRNAs regulate 40–52 % of all such genes. We also found that genes that are regulated by the same microRNAs tend to have more protein-protein interactions than randomly selected schizophrenia genes. This highlights the role microRNAs possibly play in coordinating the abundance of interacting proteins, an important function that has not been sufficiently explored before. The analysis revealed that GABBR1 is regulated by both of the top two microRNAs and acts as a hub by interacting with many schizophrenia-related genes and sharing several types of transcription-binding sites with its interactors. We also found that differentially methylated repetitive elements are significantly more methylated in schizophrenia, pointing out their potential role in the disease.ConclusionsWe find that GABBR1 has a central importance in schizophrenia, even if no direct cause and effect have been shown for it for the time. In addition to being a hub in microRNA-derived regulatory pathways and protein-protein interactions, its centrality is also supported by the high number of cis regulatory elements and transcription factor-binding sites that regulate its transcription. These findings are in line with several genome-wide association studies that repeatedly find the major histocompatibility region (where GABBR1 is located) to have the highest number of single nucleotide polymorphisms in schizophrenics. Our model also offers an explanation for the downregulation of protein kinase B, another consistent finding in schizophrenic patients. Our observations support the notion that microRNAs fine-tune the amount of proteins acting in the same biological pathways in schizophrenia, giving further support to the emerging theory of competing endogenous RNAs.Open Peer ReviewThe manuscript was reviewed by Jaap Heringa, Sandor Pongor and Zoltan Gaspari.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-015-0089-y) contains supplementary material, which is available to authorized users.

A transcriptomic analysis of the kidney tissue of tra catfish (Pangasianodon hypophthalmus) reared in saline condition: de novo assembly, annotation, snp discovery

Tra catfish (Pangasianodon hypophthalmus) is a commercially important freshwater fish used in inland aquaculture in the Mekong Delta, Vietnam. The current study using Ion Torrent technology generated EST resources from the kidney for Tra catfish reared at a salinity level of 9 ppt. We obtained 2,623,929 reads after trimming and processing with an average length of 104 bp. De novo assemblies were generated using CLC Genomic Workbench, Trinity and Velvet/Oases with the best overall contig performance resulting from the CLC assembly. De novo assembly using CLC yielded 29,940 contigs, and allowing identification of 5,710 putative genes when comppared with NCBI non-redundant database. A large number of single nucleotide polymorphisms (SNPs) were also detected. The sequence collection generated in our study represents the most comprehensive transcriptomic resource for P. hypophthalmus available to date.

CNV Analysis Associates AKNAD1 with Type-2 Diabetes in Jordan Subpopulations.

Previous studies have identified a number of single nucleotide polymorphisms (SNPs) associated with type-2 diabetes (T2D), but copy number variation (CNV) association has rarely been addressed, especially in populations from Jordan. To investigate CNV associations for T2D in populations in Jordan, we conducted a CNV analysis based on intensity data from genome-wide SNP array, including 34 T2D cases and 110 healthy controls of Chechen ethnicity, as well as 34 T2D cases and 106 healthy controls of Circassian ethnicity. We found a CNV region in protein tyrosine phosphatase receptor type D (PTPRD) with significant association with T2D. PTPRD has been reported to be associated with T2D in genome-wide association studies (GWAS). We additionally identified 16 CNV regions associated with T2D which overlapped with gene exons. Of particular interest, a CNV region in the gene AKNA Domain Containing 1 (AKNAD1) surpassed the experiment-wide significance threshold. Endoplasmic reticulum (ER)-related pathways were significantly enriched among genes which are predicted to be functionally associated with human or mouse homologues of AKNAD1. This is the first CNV analysis of a complex disease in populations of Jordan. We identified and experimentally validated a significant CNVR in gene AKNAD1 associated with T2D.

A Comprehensive Analysis of Influence ERCC Polymorphisms Confer on the Development of Brain Tumors.

Within DNA repair genes, there lie a number of single nucleotide polymorphisms that may impair protein function and attenuate DNA repair capability, resulting in genomic instability and individual predisposition to malignancies. The purpose of this study was to assess the previously reported inconsistent association of polymorphisms in ERCC1 (rs11615, rs3212986), ERCC2 (rs13181, rs1799793, rs238406), and ERCC5 (rs17655) with the development of brain tumors. In the present work, we carried out a comprehensive meta-analysis of results from all published data (5 data sets for rs11615, 7 for rs3212986, 11 for rs13181, 5 for rs1799793, 3 for rs238406, and 4 for rs17655) to evaluate risk of brain tumors contributed by the polymorphisms being investigated. Either the analytic method described by Mantel and Haenszel or that proposed by DerSimonian and Laird was properly used to summarize the risk estimates (OR and 95% CI). Data analyses were done with Stata version 12.0. Meta-analyses were performed for all polymorphisms, and only rs3212986 in the ERCC1 gene showed a significant association with glioma incidence. In the homozygote comparison, we found 1.26-fold elevated risk of glioma in relation to presence of the AA genotype (OR = 1.26, 95% CI = 1.05-1.52, P OR = 0.013, P heterogeneity = 0.849, I(2) = 0.0%). We also noted that individuals with the rs3212986-AA as compared to those with rs3212986-CC/CA had a 28% higher risk to develop glioma (OR = 1.28, 95% CI = 1.06-1.53, P OR = 0.008, Pheterogeneity = 0.808, I(2) = 0.0%). No major effects were observed for Caucasians or Asians in subgroup analysis by ethnicity. ERCC1 rs3212986 is a common single nucleotide polymorphism and may contribute toward individual susceptibility for glioma. Further research in this filed is required to verify the association obtained based on a relatively small number.

Advances in the Association between Apolipoprotein (a) Gene Polymorphisms and Coronary Heart Disease

Human apolipoprotein (a) (LPA) gene is highly polymorphic, and the polymorphic loci on this gene include the Kringle 4 subtype 2(KIV-2) repeat polymorphism, the pentanucleotide repeat (TTTTA)n polymorphism, and a number of single nucleotide polymorphisms. KIV-2 repeat polymorphism was found to be significantly associated with coronary heart disease(CHD), and the reducing number of KIV-2 repeats is a risk factor for CHD. Both the increase and decrease of the pentanucleotide repeat(TTTTA)n polymorphism repeats are possibly associated with CHD risk. In single nucleotide polymorphisms loci, the rs10455872 and rs3798220 loci were widely reported to be associated with CHD, while other loci were less reported. The association between LPA polymorphisms and CHD may be mediated by either the elevation of plasma LPA level or the change of LPA subtypes. This article reviews the association between the LPA polymorphisms and CHD and the underlying mechanisms.

Abstract 4617: An alternatively spliced isoform of TMEM129 shows association with bladder cancer GWAS marker rs798766

Abstract Genome-wide association studies (GWAS) have identified a number of single nucleotide polymorphisms (SNPs) associated with bladder cancer risk. Here, we explored the bladder cancer GWAS signal SNP rs798766 (C/T), which is located in the intron of TACC3 upstream of FGFR3 at 4p16.3 locus. This region represents a high linkage disequilibrium (LD) block and includes two more genes, TMEM129 and SLBP. Several SNPs in r2 = 1 with rs798766 are located within coding and non-coding regions of these genes; however, the coding SNPs are synonymous. Previously, genetic association of this GWAS marker has been shown by eQTL analysis with FGFR3 and TACC3 mRNA expression in adipose tissue. However, genetic association for all four genes and their several alternatively spliced isoforms remains largely unexplored in primary bladder normal and tumor tissue. We used genotype and RNA-seq data from The Cancer Genome Atlas (TCGA), bladder cancer data set (n = 242). Within the 1000 Kb region surrounding rs798766 we imputed genotypes of 13,529 SNPs in the TCGA data set based on the 1000 Genomes reference panel. Next, we performed eQTL analysis of FGFR3, TACC3, SLBP and TMEM129 both at gene level and at individual isoform level with genotypes of GWAS and several other markers. For validation, we used an independent panel of 42 bladder tumor and 42 adjacent normal tissue samples, using TaqMan expression assays. Expression was analyzed by general linear regression based on an additive genetic model, adjusting for age, sex and race. At the gene level in the TCGA data, we found significant association with TACC3 expression (p = 1.9 × 10−2unadj and p = 3.5 × 10−2 adj). The association was stronger for expression of an alternatively spliced isoform of TMEM129, designated TMEM129β, (p = 4.57×10−4unadj and p = 3.5 × 10−3adj). Computational annotation revealed that SNP rs2236786, r2 = 1 with GWAS marker, is located within a cassette exon that is an intron for isoform TMEM129β. Further analysis revealed that rs2236786 alleles affect a binding motif for alternative splicing factors SF2ASF, hnRNPF and CUG-BP. The functional exploration of this finding is underway. In conclusion, we suggest that the molecular phenotype of the 4p16.3 bladder cancer GWAS signal could be associated with differential expression of more than one gene (FGFR3, TACC3, SLBP and TMEM129) and their alternatively spliced isoforms. We present the first evidence for possible association of alternative splicing of TMEM129 and bladder cancer GWAS signal. Note: This abstract was not presented at the meeting. Citation Format: A. Rouf Banday, Ashley Paquin, Candace Middlebrooks, Eniko Kiss, Ludmila Prokunina-Olsson. An alternatively spliced isoform of TMEM129 shows association with bladder cancer GWAS marker rs798766. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4617. doi:10.1158/1538-7445.AM2015-4617

Do personality traits moderate the manifestation of type 2 diabetes genetic risk?

Objective. To test whether personality traits moderate type 2 diabetes (T2D) genetic risk. Methods. Using a large community-dwelling sample (n=837, Mage=69.59±0.85years, 49% males) we fitted a series of linear regression models predicting glycated haemoglobin (HbA1c) from T2D polygenic risk — aggregation of small individual effects of a large number of single nucleotide polymorphisms (SNPs) — and five personality traits. We tested the main effects of personality traits and their interactions with T2D polygenic risk score, controlling for age and sex. The models in the final set were adjusted for cognitive ability, highest educational qualification, and occupational class. Results. Lower levels of openness were associated with heightened levels of HbA1c (β=−0.014, p=.032). There was a significant interaction between T2D polygenic risk score and agreeableness: lower agreeableness was related to a stronger association between T2D polygenic risk and HbA1c (β=−0.08, p=.021). In the model adjusted for cognitive ability, the main effect of openness was not significant (β=−0.08, p=.057). The interaction between agreeableness and T2D polygenic risk was still present after controlling for cognitive ability and socioeconomic status indicators, and the interaction between conscientiousness and polygenic risk score was also significant: lower conscientiousness was associated with a stronger association between T2D polygenic risk and HbA1c levels (β=0.09, p=.04). Conclusions. Personality may be associated with markers of diabetes, and may moderate the expression of its genetic risk.

Rule-based analysis for detecting epistasis using associative classification mining

The advancements in sequencing high-throughput human genome and computational abilities have tremendously improved the understanding of the genetic architecture behind the complex diseases. The development of high-throughput genotyping and next-generation sequencing technologies enables large-scale data for genetic epidemiological analysis. These advances led to the identification of a number of single nucleotide polymorphisms (SNPs) associated with complex diseases. The interactions between SNPs responsible for disease susceptibility have been increasingly explored in the current literature. These interaction studies are mathematically challenging and computationally complex. These challenges have been addressed by a number of data mining and machine learning approaches. The goal of this research is to implement associative classification and study its effectiveness for detecting the epistasis in balanced and imbalanced datasets. The proposed approach was evaluated for single-locus models to six-locus models using simulated data. The datasets were generated for five different penetrance functions by varying heritability, minor allele frequency and sample size. In total, 57,300 datasets were generated and several experiments conducted to identify the disease causal SNP interactions. The accuracy of classification by the proposed approach was compared with the existing approaches. The experimental results demonstrated significant improvements in accuracy for detecting interactions associated with the phenotype. Further, the approach was successfully applied over sporadic breast cancer data. The results show interaction among six polymorphisms, which included five different estrogen-metabolism genes.

Locally Confined Clonal Complexes of Mycobacterium ulcerans in Two Buruli Ulcer Endemic Regions of Cameroon.

Background Mycobacterium ulcerans is the causative agent of the necrotizing skin disease Buruli ulcer (BU), which has been reported from over 30 countries worldwide. The majority of notified patients come from West African countries, such as Côte d’Ivoire, Ghana, Benin and Cameroon. All clinical isolates of M. ulcerans from these countries are closely related and their genomes differ only in a limited number of single nucleotide polymorphisms (SNPs).Methodology/Principal FindingsWe performed a molecular epidemiological study with clinical isolates from patients from two distinct BU endemic regions of Cameroon, the Nyong and the Mapé river basins. Whole genome sequencing of the M. ulcerans strains from these two BU endemic areas revealed the presence of two phylogenetically distinct clonal complexes. The strains from the Nyong river basin were genetically more diverse and less closely related to the M. ulcerans strain circulating in Ghana and Benin than the strains causing BU in the Mapé river basin.ConclusionsOur comparative genomic analysis revealed that M. ulcerans clones diversify locally by the accumulation of SNPs. Case isolates coming from more recently emerging BU endemic areas, such as the Mapé river basin, may be less diverse than populations from longer standing disease foci, such as the Nyong river basin. Exchange of strains between distinct endemic areas seems to be rare and local clonal complexes can be easily distinguished by whole genome sequencing.

Genetic modifiers of folate, vitamin B-12, and homocysteine status in a cross-sectional study of the Canadian population

Genetic variation can cause variable responses to environmental stimuli. A number of single-nucleotide polymorphisms (SNPs) have been associated with B vitamin status or chronic diseases related to vitamin B-12 and folate metabolism. Our objective was to identify associations between common SNPs in genes related to folate and vitamin B-12 metabolism or associated with B vitamin-related chronic diseases and biomarkers of nutrient status in a population exposed to folic acid fortification. A panel of 116 SNPs was sequenced by using the Sequenom iPLEX Gold platform in a sample of 3114 adults aged 20-79 y from the Canadian Health Measures Survey, cycle 1. Associations between these SNPs and red blood cell (RBC) folate, serum vitamin B-12, and plasma total homocysteine were determined. Twenty-one SNPs and 6 haplotype blocks were associated with RBC folate, serum vitamin B-12, and/or plasma homocysteine concentrations. Vitamin status was associated mainly with SNPs in genes directly involved in vitamin absorption/uptake (CUBN, CD320), transport (TCN1, TCN2), or metabolism (BHMT2, CBS, MTHFR, MUT, SHMT1). Other SNPs included those in the DNMT2, DPEP1, FUT2, NOX4, and PON1 genes. We identified novel associations between SNPs in CD320 and DNMT2, which had been previously associated with neural tube defects, and vitamin B-12 status, as well as between SNPs in SHMT1, which had been previously associated with colorectal cancer and cardiovascular disease risk, and RBC folate status. These novel associations provide a plausible metabolic rationale for the association of these SNPs with B vitamin-related diseases. We also observed a novel association between an SNP in CUBN with RBC folate and confirmed the association of a number of SNPs with B vitamin status in this large cross-sectional study.

Selenium and chronic diseases: a nutritional genomics perspective.

Mechanistic data have revealed a key role for selenium (Se) and selenoproteins in biological pathways known to be altered in multifactorial diseases, such as cellular maintenance, response to oxidative stress and correct protein folding. Although epidemiological studies indicate that low Se intake is linked to increased risk for various chronic diseases, supplementation trials have given confusing outcomes, suggesting that additional genetic factors could affect the relationship between Se and health. Genetic data support this hypothesis, as risk for several chronic diseases, in particular cancer, was linked to a number of single nucleotide polymorphisms (SNP) altering Se metabolism, selenoprotein synthesis or activity. Interactions between SNPs in selenoprotein genes, SNPs in related molecular pathways and biomarkers of Se status were found to further modulate the genetic risk carried by the SNPs. Taken together, nutritional genomics approaches uncovered the potential implication of some selenoproteins as well as the influence of complex interactions between genetic variants and Se status in the aetiology of several chronic diseases. This review discusses the results from these genetic associations in the context of selenoprotein functions and epidemiological investigations and emphasises the need to assess in future studies the combined contribution of Se status, environmental stress, and multiple or individual SNPs to disease risk.

Abstract P6-09-05: Value of adding single-nucleotide polymorphism panel markers to phenotypic algorithms of breast cancer risk

Abstract Currently, breast cancer risk prediction algorithms incorporate phenotypic risk factors, including age, family history, reproductive history and benign breast disease. Since 2007, genome-wide association studies have identified a growing number of single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. While no single SNP is very informative on its own, a polygenic approach to genetic screening could improve estimates of individual risk, creating the possibility of screening strategies individually tailored to each woman. We studied cases and controls recruited to the Australian Breast Cancer Family Registry, to investigate whether a SNP risk score derived from a panel of 77 SNPs can improve risk estimates obtained from the commonly used breast cancer risk prediction models (BCRAT, IBIS, BRCAPRO and BOADICEA). SNP risk scores were calculated using previously published Odds Ratios (ORs) and risk-allele frequencies based on the assumption of independence of additive risks on the log OR scale. SNP risk scores were calculated by multiplying adjusted risk scores for each of the SNPs. Combined risk scores were calculated by multiplying the SNP risk score and the algorithm derived risk scores, under the assumption of independence. Overall, the inclusion of data on 77 SNPs improved the area under the receiver operating characteristic curve (AUC) for all of the breast cancer risk prediction models: Preliminary data analysis provided AUC values as follows: BCRAT+SNP = 0.656, IBIS+SNP= 0.628, BRCAPRO+SNP= 0.689, BOADICEA+SNP= 0.698. The breast cancer risk prediction models examined place different weighting on the phenotypic components. For example, the IBIS model is weighted towards uncommon high-risk phenotypes, while the BCRAT is weighted towards lower risks in the general population. A combination of the 77 SNP score and the most appropriate model might substantially improve the ability to identify high-risk women in different screening populations. Citation Format: Gillian Dite, Richard Allman, John L Hopper. Value of adding single-nucleotide polymorphism panel markers to phenotypic algorithms of breast cancer risk [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-09-05.

Obstructive sleep apnea syndrome susceptible genes in the Chinese population: a meta-analysis of 21 case-control studies.

Numbers of single nucleotide polymorphisms (SNPs) were identified as risk factors for obstructive sleep apnea syndrome (OSAS) in the Chinese population; however, published articles drew incompatible or even contradictory results. The aim of this study was to investigate the susceptible SNPs and risk of OSAS in the Chinese population. We conducted a meta-analysis of seven polymorphisms and risk of OSAS based on 21 case-control studies. The results of our study showed that tumor necrosis factor-α (TNF-α) -308 G/A (OR = 3.70, 95% CI = 1.39-9.83), gene-linked polymorphic region (LPR) (OR = 0.57, 95% CI = 0.41-0.79), and variable number tandem repeat (VNTR) of the 5-hydroxytryptamine transporter gene (5-HTT) (OR = 3.44, 95% CI = 1.49-7.95) polymorphisms were associated with OSAS risk in the Chinese population, while there was no significant association between 5-hydroxytryptamine 2A receptor (5-HTR2A) 102C/T, 5-HTR2A A1438G, angiotensin-converting enzyme (ACE) insertion (I)/deletion (D), or leptin receptor (LEPR)-Gln 223Arg polymorphism and risk of OSAS in the Chinese population. Our study demonstrated that TNF-α 308 G/A, 5-HTT LPR, and 5-HTT-VNTR polymorphisms were associated with OSAS risk, whereas little association was observed between 5-HTR2A 102C/T, 5-HTR2A A1438G, ACE I/D, or LEPR-Gln 223Arg polymorphism and risk of OSAS in the Chinese population.