Single SNP Analysis Research Articles

Abstract 4628: Analysis of melanoma GWAS data suggests specific risk loci influencing age of onset of melanoma

Abstract Introduction/Purpose: The average age of diagnosis of melanoma is younger than that of other major cancers. In addition, melanoma is the second most common cancer among individuals in their 20s. Analyzing GWAS data by ‘wide-locus region’ (i.e. analyzing multiple nearby single nucleotide polymorphisms (SNPs) together) increases statistical power compared to single-SNP analyses. This approach has uncovered new associations in GWAS data for diseases other than melanoma. By applying wide-locus analysis to GWAS data from melanoma cases, we aimed to discover common genetic risk variants related to age of melanoma onset. Procedures: We re-analyzed data from the 1977 melanoma cases of European ancestry made available by the MD Anderson Cancer Center study (accession: phs000187.v1.p1). Patients were genotyped on the Illumina OMNI1-Quad chip. Biostatistical analysis was performed from a window moving across the whole genome using u-statistics for multivariate, genetically structured wide-locus data to derive genetic risk scores to determine if any gene regions were associated with age of onset in melanoma patients. This statistical approach resulted in a genome-wide significance level of p<10−5.64. Results: Common variants in several genes were associated with melanoma age-of-onset at the level of genome-wide significance. The most significant functional risk loci were located at DLEU1 (p<10−6.75), NRP1 (p<10−6.66), PTPN11P (p<10−6.49) and BAT1/ATP6/NFKBIL (p<10−6.41). Of note, none of these risk loci have been shown to be associated with risk of developing melanoma overall, or longevity in prior GWAS. The NRP1 and PTPN11P genes have been linked to the RAS pathway, an important driver of melanoma pathogenesis. Conclusions: Our analysis revealed novel associations between several common genetic variants and earlier age of melanoma diagnosis. Some of these loci interact with the RAS pathway. Additional studies of common genetic variants and age of cancer diagnosis using this approach may reveal similar findings in other melanoma cohorts and possibly other cancer types. Citation Format: Rachel M. Cymerman, Benedetta Bigio, Martin P. Seybold, David Polsky, Knut M. Wittkowski. Analysis of melanoma GWAS data suggests specific risk loci influencing age of onset of melanoma. [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 4628. doi:10.1158/1538-7445.AM2015-4628

T2D and Depression Risk Gene Proteasome Modulator 9 is Linked to Insomnia.

Insomnia increases type-2 diabetes (T2D) risk. The 12q24 locus is linked to T2D, depression, bipolar disorder and anxiety. At the 12q24 locus, the Proteasome-Modulator 9 (PSMD9) single nucleotide polymorphisms (SNPs) rs74421874 [intervening sequence (IVS) 3+nt460-G>A], rs3825172 (IVS3+nt437-C>T) and rs14259 (E197G-A>G) are linked to: T2D, depression, anxiety, maturity-onset-diabetes-of the young 3/MODY3, obesity, waist circumference, hypertension, hypercholesterolemia, T2D-macrovascular disease, T2D-microvascular disease, T2D-neuropathy, T2D-carpal-tunnel syndrome, T2D-nephropathy, T2D-retinopathy and non-diabetic retinopathy. PSMD9 SNP rs1043307/rs14259 (E197G-A>G) plays a role in anti-depressant therapy response, depression and schizophrenia. We aimed at determining PSMD9 rs74421874/rs3825172/rs14259 SNPs potential linkage to primary insomnia and sleep hours in T2D families. We recruited 200 Italian T2D families phenotyping them for primary insomnia and sleep hours per night. PSMD9-T2D-risk SNPs rs74421874/rs3825172 and rs1043307/rs14259 were tested for linkage with insomnia and sleep hours. Non-parametric-linkage analysis, linkage-disequilibrium-model analysis, single-SNP analysis, cluster-based-parametric analysis, quantitative-trait and variant-component analysis were performed using Merlin software. To validate data, 1000 replicates were executed for the significant non-parametric data. PSMD9 rs74421874 (IVS3+nt460-G>A), rs3825172 (IVS3+nt437-C>T) and rs1043307/rs14259 (E197G-A>G) SNPs are linked to insomnia in our Italian families.

Genetic variants within the TNFRSF1B gene and susceptibility to rheumatoid arthritis and response to anti-TNF drugs

Recent research suggests that genetic variants in the tumor necrosis factor receptor 2 (TNFRSF1B) gene may have an impact on susceptibility to rheumatoid arthritis (RA) and drug response. The present population-based case-control study was carried out to evaluate whether 5 tagging single-nucleotide polymorphisms (SNPs) within the TNFRSF1B gene are associated with the risk of RA and response to antitumor necrosis factor (TNF) drugs. The study population included 1412 RA patients and 1225 healthy controls. A subset of 596 anti-TNF-naive RA patients was selected to assess the association of TNFRSF1B SNPs and drug response according to the EULAR response criteria. We found that carriers of the TNFRSF1Brs3397C allele had a significantly increased risk of developing RA (P=0.0006). Importantly, this association remained significant after correction for multiple testing. We also confirmed the lack of association of the TNFRSF1Brs1061622 SNP with the risk of RA in the single-SNP analysis (P=0.89), but also through well-powered meta-analyses (PDOM=0.67 and PREC=0.37, respectively). In addition, our study showed that carriers of the TNFRSF1Brs3397C/C, TNFRSF1Brs1061622G/G, and TNFRSF1Brs1061631A/A genotypes had an increased risk of having a worse response to anti-TNF drugs at the level of P less than 0.05 (P=0.014, 0.0085 and 0.028, respectively). We also observed that, according to a log-additive model, carriers of the TNFRSF1Brs3397C or TNFRSF1Brs1061622G alleles showed an increased risk of having worse response to anti-TNF medications (P=0.018 and 0.0059). However, the association of the TNFRSF1Brs1061622 SNP only reached marginal significance after correction for multiple testing according to a log-additive model (P=0.0059) and it was not confirmed through a meta-analysis (PDOM=0.12). Our results suggest that the TNFRSF1Brs3397 variant may play a role in modulating the risk of RA, but does not provide strong evidence of an impact of TNFRSF1B variants in determining response to anti-TNF drugs.

Longevity GWAS Using the Drosophila Genetic Reference Panel.

We used 197 Drosophila melanogaster Genetic Reference Panel (DGRP) lines to perform a genome-wide association analysis for virgin female lifespan, using ~2M common single nucleotide polymorphisms (SNPs). We found considerable genetic variation in lifespan in the DGRP, with a broad-sense heritability of 0.413. There was little power to detect signals at a genome-wide level in single-SNP and gene-based analyses. Polygenic score analysis revealed that a small proportion of the variation in lifespan (~4.7%) was explicable in terms of additive effects of common SNPs (≥2% minor allele frequency). However, several of the top associated genes are involved in the processes previously shown to impact ageing (eg, carbohydrate-related metabolism, regulation of cell death, proteolysis). Other top-ranked genes are of unknown function and provide promising candidates for experimental examination. Genes in the target of rapamycin pathway (TOR; Chrb, slif, mipp2, dredd, RpS9, dm) contributed to the significant enrichment of this pathway among the top-ranked 100 genes (p = 4.79×10−06). Gene Ontology analysis suggested that genes involved in carbohydrate metabolism are important for lifespan; including the InterPro term DUF227, which has been previously associated with lifespan determination. This analysis suggests that our understanding of the genetic basis of natural variation in lifespan from induced mutations is incomplete.

Linking Genetics of Brain Changes to Alzheimer's Disease: Sparse Whole Genome Association Scan of Regional MRI Volumes in the ADNI and AddNeuroMed Cohorts.

Alzheimer's disease (AD) is a highly heritable disease, but until recently few replicated genetic markers have been identified. Markers identified so far are likely to account for only a tiny fraction of the heritability of AD and many more genetic risk alleles are thought to be undiscovered. Identifying genetic markers for AD using combined analysis of genetics and brain imaging data. Imaging quantitative trait loci (iQTLs) has recently emerged as an interesting research area for linking genetics of brain changes to AD. We consider a genome-wide association scan of 109 brain-wide regional imaging phenotypes to identify genetic susceptibility loci for AD from a combined set of 1,045 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the AddNeuroMed studies. We use one-SNP-at-a-time as well as multi-SNP Hyperlasso based iQTL methods for the analysis. We identified several novel markers associated with AD, namely HOMER2 (rs1256429; intronic, p = 8.7 × 10⁻¹⁰), EOMES (rs2724509; flanking), JAM2 (rs2829841; intronic), and WEE1 (rs10770042; coding). The SNP rs1256429 (HOMER2) was one of the top hits in Hyperlasso as well as in the single-SNP analysis showing an association with the volume of the right thalamus and AD, a brain region reported to be linked with AD in several studies. We believe that the markers identified in this study are novel additions to the existing list of genetic variants associated with AD which can be validated in future replicated studies.

Functional variants regulating LGALS1 (Galectin 1) expression affect human susceptibility to influenza A(H7N9).

The fatality of avian influenza A(H7N9) infection in humans was over 30%. To identify human genetic susceptibility to A(H7N9) infection, we performed a genome-wide association study (GWAS) involving 102 A(H7N9) patients and 106 heavily-exposed healthy poultry workers, a sample size critically restricted by the small number of human A(H7N9) cases. To tackle the stringent significance cutoff of GWAS, we utilized an artificial imputation program SnipSnip to improve the association signals. In single-SNP analysis, one of the top SNPs was rs13057866 of LGALS1. The artificial imputation (AI) identified three non-genotyped causal variants, which can be represented by three anchor/partner SNP pairs rs13057866/rs9622682 (AI P = 1.81 × 10−7), rs4820294/rs2899292 (2.13 × 10−7) and rs62236673/rs2899292 (4.25 × 10−7) respectively. Haplotype analysis of rs4820294 and rs2899292 could simulate the signal of a causal variant. The rs4820294/rs2899292 haplotype GG, in association with protection from A(H7N9) infection (OR = 0.26, P = 5.92 × 10−7) correlated to significantly higher levels of LGALS1 mRNA (P = 0.050) and protein expression (P = 0.025) in lymphoblast cell lines. Additionally, rs4820294 was mapped as an eQTL in human primary monocytes and lung tissues. In conclusion, functional variants of LGALS1 causing the expression variations are contributable to the differential susceptibility to influenza A(H7N9).

Epistatic Analysis of Clarkson Disease

Abstract Genome Wide Association Studies (GWAS) have predominantly focused on the association between single SNPs and disease. It is probable, however, that complex diseases are due to combined effects of multiple genetic variations, as opposed to single variations. Multi-SNP interactions, known as epistatic interactions, can potentially provide information about causes of complex diseases, and build on previous GWAS looking at associations between single SNPs and phenotypes. By applying epistatic analysis methods to GWAS datasets, it is possible to identify significant epistatic interactions, and map SNPs identified to genes allowing the construction of a gene network. A large number of studies have applied graph theory techniques to analyse gene networks from microarray data sets, using graph theory metrics to identify important hub genes in these networks. In this work, we present a graph theory study of SNP and gene interaction networks constructed for a Clarkson disease GWAS, as a result of applying epistatic interaction methods to identify significant epistatic interactions. This study identifies a number of genes and SNPs with potential roles for Clarkson disease that could not be found using traditional single SNP analysis, including a number located on chromosome 5q previously identified as being of interest for capillary malformation.

Genetic Variation in NFATC2 Is Associated with a Higher Risk of Asparaginase Allergy

Asparaginase is an important drug for the treatment of acute lymphoblastic leukemia (ALL); however, hypersensitivity reactions to asparaginase can lead to suboptimal asparaginase exposure and to a higher risk of disease recurrence. Factors influencing the frequency of asparaginase hypersensitivity include asparaginase formulation, the schedule of asparaginase administration, and concurrent chemotherapy. In addition, using a candidate gene approach, our group previously identified a genetic association between HLA-DRB1*07:01 and asparaginase hypersensitivity in patients of European ancestry.[PMID 24970932] The objective of our current study was to use a genome-wide approach to identify additional genetic loci associated with hypersensitivity and to assess the relative importance of HLA-DRB1 as a genetic risk factor.Asparaginase hypersensitivity was assessed in children with ALL enrolled on SJCRH protocols Total XIIIA (n = 154), Total XV (n = 498) and Total XVI (n = 271) or Children’s Oncology Group (COG) protocols POG 9906 (n = 222) and AALL0232 (n = 2,163). Patients enrolled on protocols Total XIIIA, Total XV and POG 9906 received native E. coli asparaginase during treatment, whereas patients on Total XVI and AALL0232 received PEGylated E. coli asparaginase. Hypersensitivities were graded according to the NCI common toxicity criteria, and reactions of grade 2 and above were considered cases. Germline DNA was genotyped using the Affymetrix 500K, Affymetrix 6.0, or the Illumina Exome Beadchip array. Univariate analysis of risk factors associated with asparaginase hypersensitivity using the combined cohort of patients (n = 3,308) identified a significant positive association with treatment arm (P < 2.2x10-16; highest risk in patients enrolled on Total XV), native E coli asparaginase formulation (P < 2.2x10-16), age < 10 years (P = 3.3x10-4), male gender (P = 0.06), and racial ancestry (P = 2.1x10-4; highest risk among African ancestry). In multivariate analysis, treatment arm (P < 2.2x10-16), gender (P = 0.04), racial ancestry (P = 0.07), and ALL lineage (P = 0.003) remained significant risk factors.A multivariate logistic regression model adjusted for treatment arm, racial ancestry, gender, age, and ALL lineage was used to identify genomic variants associated with asparaginase hypersensitivity in the combined patient cohort. The minor allele of an intronic polymorphism in NFATC2 (rs6021191) was associated with hypersensitivity at the genome-wide significance threshold (P = 2.6x10-8, OR = 3.17). The minor allele frequency (MAF) for the NFATC2 high-risk variant was highest in non-European ancestries (MAFEuropean = 0.001, MAFAfrican = 0.142, MAFHispanic = 0.043, MAFAsian = 0.151, MAFOther = 0.034). Using RNA-seq data available from the ALL tumor samples of 65 SJCRH patients, we found that patients carrying the variant had higher expression of NFATC2 compared to non-carriers (P = 1.0x10-3). NFATC2 is known to play a critical role in inducing T-cell gene transcription during immune responses.The strongest association detected using SNPs from the Illumina Exome array was found in HLA-DRB1 (rs17885382, P = 4.0x10-6, OR = 1.65), and the SNP is in near complete linkage disequilibrium with the HLA-DRB1*07:01 allele, which we previously found associated with asparaginase hypersensitivity. A gene-level analysis was performed using SNP-set Kernel Association Test (SKAT), and the gene with the strongest association with hypersensitivity was PPT2, located in the HLA class III region on chromosome 6 (P = 3.70x10-6). To determine potential biological pathways differentially represented by the genes identified by our analysis, we used Ingenuity Pathway Analysis on the top 1% of genes associated with hypersensitivity as identified by our single SNP (68 genes) and gene level analysis (18 genes). We found an enrichment of genes (8 out of 21 genes, P = 2.6x10-5) within the top network involved in humoral immunity, suggesting that other genes regulating immune responses may also contribute to the risk of developing asparaginase hypersensitivity.In conclusion, the top inherited genetic loci (NFATC2, HLA-DRB1*0701, PPT2) associated with asparaginase hypersensitivity are directly involved in human immune response, and pathway analysis suggests that inherited variations in other genes involved in humoral immunity likely play a role in the development of asparaginase hypersensitivity. DisclosuresEvans:St. Jude: In accordance with institutional policy (St. Jude), I and/or my spouse have in the past received a portion of the income St. Jude receives from licensing patent rights related to TPMT polymorphisms as clinical diagnostics. Patents & Royalties. Relling:St. Jude: In accordance with institutional policy (St. Jude), I and/or my spouse have in the past received a portion of the income St. Jude receives from licensing patent rights related to TPMT polymorphisms as clinical diagnostics. Patents & Royalties.

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants.

A quantitative trait locus on Bos taurus autosome 17 explains a large proportion of the genetic variation in de novo synthesized milk fatty acids

A genomic region associated with milk fatty acid (FA) composition has been detected on Bos taurus autosome (BTA)17 based on 50,000 (50K) single nucleotide polymorphism (SNP) genotypes. The aim of our study was to fine-map BTA17 with imputed 777,000 (777K) SNP genotypes to identify candidate genes associated with milk FA composition. Phenotypes consisted of gas chromatography measurements of 14 FA based on winter and summer milk samples. Phenotypes and genotypes were available on 1,640 animals in winter milk, and on 1,581 animals in summer milk samples. Single-SNP analyses showed that several SNP in a region located between 29.0 and 34.0Mbp were in strong association with C6:0, C8:0, and C10:0. This region was further characterized based on haplotypes. In summer milk samples, for example, these haplotypes explained almost 10% of the genetic variance in C6:0, 9% in C8:0, 3.5% in C10:0, 1.8% in C12:0, and 0.9% in C14:0. Two groups of haplotypes with distinct predicted effects could be defined, suggesting the presence of one causal variant. Predicted haplotype effects tended to increase from C6:0 to C14:0; however, the proportion of genetic variance explained by the haplotypes tended to decrease from C6:0 to C14:0. This is an indication that the quantitative trait locus (QTL) region is involved either in the elongation process or in early termination of de novo synthesized FA. Although many genes are present in this QTL region, most of these genes on BTA17 have not been characterized yet. The strongest association was found close to the progesterone receptor membrane component 2 (PGRMC2) gene, which has not yet been associated with milk FA composition. Therefore, no clear candidate gene associated with milk FA composition could be identified for this QTL.

Synergistic association of PI4KA and GRM3 genetic polymorphisms with poor antipsychotic response in south Indian schizophrenia patients with low severity of illness.

Literature indicates key role of glutamatergic pathway genes in antipsychotic response among schizophrenia patients. However, molecular basis of their underlying role in antipsychotic response remained unexplained. Thus, to unravel their molecular underpinnings, we sought to investigate interactions amongst GRM3, SLC1A1, SLC1A2, SLC1A3, SLC1A4 gene polymorphisms with drug response in south Indian schizophrenia patients. We genotyped 48 SNPs from these genes in 423 schizophrenia patients stratified into low and high severity of illness groups. The SNPs and haplotypic combinations of associated SNPs were examined for their association with antipsychotic response. Multifactor-dimensionality-reduction was further used to explore gene-gene interaction among these SNPs and 53 SNPs from previously studied genes (BDNF, RGS4, SLC6A3, PI4KA, and PIP4K2A). Single SNP and haplotype analyses revealed no significant association with drug response irrespective of severity of illness. Gene-gene interaction analyses yielded promising leads, including an observed synergistic effect between PI4KA_rs165854 and GRM3_rs1468412 polymorphisms and incomplete antipsychotic response in schizophrenia patients with low severity of illness (OR = 12.4; 95%CI = 3.69-41.69). Further, this interaction was also observed in atypical monotherapy (n = 355) and risperidone (n = 260) treatment subgroups (OR = 11.21; 95%CI = 3.30-38.12 and OR = 13.5; 95%CI = 3.03-121.61 respectively). PI4KA is known to be involved in the biosynthesis of phosphatidylinositol-4, 5-bisphosphate which regulates exocytotic fusion of synaptic vesicles (glutamate, dopamine) with the plasma membrane and regulates duration of signal transduction of GPCRs. Whereas GRM3 regulates glutamate and dopamine transmission. Present findings indicate that PI4KA and GRM3 polymorphisms have potential to jointly modulate antipsychotic response. These results warrant additional replication studies to shed further light on these interactions.

Detecting local haplotype sharing and haplotype association.

A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.

Polymorphisms in inflammatory genes are associated with term small for gestational age and preeclampsia.

Inflammatory biomarkers are associated with preeclampsia (PE) and poor fetal growth; however, genetic epidemiologic studies have been limited by reduced gene coverage and the exclusion of African American mothers. Cases and controls (N=1646) from a pregnancy cohort were genotyped for 503 tagSNPs in 40 genes related to inflammation. Gene-set analyses were stratified by race and were followed by a single SNP analysis within significant gene sets. Gene-level associations were found for IL6 and KLRD1 for term small for gestational age (SGA) among African Americans. LTA/TNF and TBX21 were associated with PE among European Americans. The strongest association was for PE among European Americans for an upstream regulator of TNF with RR=1.8 (95% CI 1.1-2.7). Although previous studies have suggested null associations, increased tagging and stratification by genetic ancestry suggests important associations between IL6 and term SGA for African Americans, and a TNF regulator and PE among European Americans (N=149).

Association between GSK3β gene and increased impulsivity in bipolar disorder

Bipolar patients present increased levels of impulsivity even during remission periods. It is known that this dimensional trait negatively impacts on the course of illness and worsens their prognosis and outcome. Evidence from both basic and clinical researches supports that Lithium (Li) may decrease impulsivity. Owing to the fact that Li inhibits both glycogen synthetase kinase-3 (GSK3) isoenzimes, our aim was to analyze the potential impact of genetic variants located at the GSK3 α and β genes on impulsivity levels in a bipolar sample. Our sample consisted of 199 unrelated Caucasian bipolar outpatients who were recruited from the Bipolar Disorder Unit of the Hospital Clinic of Barcelona and from primary care settings from Oviedo. Four polymorphisms at the GSK3 α and β genes were genotyped in order to analyze the impact of genetic variability on impulsivity as measured by the BIS-11 scale. Single SNP analysis showed that patients carrying T and G alleles at the rs1732170-GSK3β and the rs334558-GSK3β, respectively, presented increased levels of attentional impulsivity compared to non-carriers. These results were also confirmed by haplotype analysis. Our results suggest that genetic variability at GSK3β gene is associated to increased impulsivity in bipolar patients.

Association study between BDNF gene variants and Mexican patients with obsessive–compulsive disorder

Obsessive–compulsive disorder (OCD) is a psychiatric disorder whose etiology is not yet known. We investigate the role of three variants of the BDNF gene (rs6265, rs1519480 and rs7124442) by single SNP and haplotype analysis in OCD Mexican patients using a case–control and family-based association design. BDNF gene variants were genotyped in 283 control subjects, 232 OCD patients and first degree relatives of 111 OCD subjects. Single SNP analysis in case–control study showed an association between rs6265 and OCD with a high frequency of Val/Val genotype and Val allele (p=0.0001 and p=0.0001, respectively). Also, genotype and allele analysis of rs1519480 showed significant differences (p=0.0001, p=0.0001; respectively) between OCD and control groups. Haplotype analysis showed a high frequency of A–T (rs6265–rs1519480) in OCD patients compared with the control group (OR=2.06 [1.18–3.59], p=0.0093) and a low frequency of haplotype A–C in the OCD patients (OR=0.04 [0.01–0.16], p=0.000002). The family-based association study showed no significant differences in the transmission of any variant. Our study replicated the association between BDNF Val66Met gene polymorphism and OCD. Also, we found a significant association of rs1519480 in OCD patients compared with a control group, region that has never been analyzed in OCD. In conclusion, our findings suggest that BDNF gene could be related to the development of OCD.

Whole Genome Association Studies of Residual Feed Intake and Related Traits in the Pig

BackgroundResidual feed intake (RFI), a measure of feed efficiency, is the difference between observed feed intake and the expected feed requirement predicted from growth and maintenance. Pigs with low RFI have reduced feed costs without compromising their growth. Identification of genes or genetic markers associated with RFI will be useful for marker-assisted selection at an early age of animals with improved feed efficiency.Methodology/Principal findingsWhole genome association studies (WGAS) for RFI, average daily feed intake (ADFI), average daily gain (ADG), back fat (BF) and loin muscle area (LMA) were performed on 1,400 pigs from the divergently selected ISU-RFI lines, using the Illumina PorcineSNP60 BeadChip. Various statistical methods were applied to find SNPs and genomic regions associated with the traits, including a Bayesian approach using GenSel software, and frequentist approaches such as allele frequency differences between lines, single SNP and haplotype analyses using PLINK software. Single SNP and haplotype analyses showed no significant associations (except for LMA) after genomic control and FDR. Bayesian analyses found at least 2 associations for each trait at a false positive probability of 0.5. At generation 8, the RFI selection lines mainly differed in allele frequencies for SNPs near (<0.05 Mb) genes that regulate insulin release and leptin functions. The Bayesian approach identified associations of genomic regions containing insulin release genes (e.g., GLP1R, CDKAL, SGMS1) with RFI and ADFI, of regions with energy homeostasis (e.g., MC4R, PGM1, GPR81) and muscle growth related genes (e.g., TGFB1) with ADG, and of fat metabolism genes (e.g., ACOXL, AEBP1) with BF. Specifically, a very highly significantly associated QTL for LMA on SSC7 with skeletal myogenesis genes (e.g., KLHL31) was identified for subsequent fine mapping.Conclusions/significanceImportant genomic regions associated with RFI related traits were identified for future validation studies prior to their incorporation in marker-assisted selection programs.

The shared allelic architecture of adiponectin levels and coronary artery disease

ObjectiveA large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. MethodsUsing 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). ResultsIn single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10−4). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10−7). ConclusionThese findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

Abstract 2571: Genetic variations in telomere maintenance pathway genes are associated with risk of esophageal cancer.

Abstract Many studies have shown the association of telomere dysfunction with aging and cancer development. We hypothesize that genetic variations in telomere maintenance genes may modulate esophageal cancer risk. To test this hypothesis, we comprehensively assessed the association of 616 SNPs in 45 telomere maintenance pathway genes in 602 esophageal adenocarcinoma cases and 1,512 healthy controls. Unconditional multivariate logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (CI) while adjusting for age, gender, and smoking status. In single SNP analysis, a total of 77 SNPs had P value &amp;lt; 0.05. 5 SNPs remained significant after adjusting for multiple comparisons at FDR &amp;lt; 0.10 including 3 SNPs in PINX1 gene and 2 SNPs in TPP1 gene. The most significant association was observed for rs9657541 in PINX1 gene that exhibited a significantly reduced risk of esophageal cancer in dominant model (OR = 0.62, 95% CI = 0.50-0.77, P = 1.54×10−5, FDR = 0.020). Cumulative effects of SNPs were assessed by the number of unfavorable genotypes. Each subject was classified into low (zero unfavorable genotype), medium (one to three unfavorable genotypes), and high-risk groups (more than three unfavorable genotypes). Compared with the low-risk group, the OR was 1.58 (95% CI = 1.20-2.09) for the median-risk group and 2.57 (95% CI = 1.87-3.54) for the high-risk group. Classification and regression tree (CART) analysis was performed to identify genetic profiles that can classify individuals into differential risk of esophageal cancer. CART analysis identified 3 terminal nodes. Compared to terminal node 1, individuals in terminal nodes 2 and 3 had significantly increased risks of esophageal cancer with ORs of 1.43 (95% CI = 1.13-1.80) and 2.46 (95% CI = 1.81-3.34), respectively. We also performed gene-based analysis to determine the combined effect of SNPs within a gene region and identified four genes (TPP1, PINX1, TNKS, TERF1) significantly associated with the risk of esophageal cancer. In conclusion, our results suggest that genetic variants in telomere maintenance pathway genes may contribute to the altered risk of esophageal cancer, both individually and jointly. Citation Format: Yuanqing Ye, Jaffer Ajani, Xifeng Wu. Genetic variations in telomere maintenance pathway genes are associated with risk of esophageal cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2571. doi:10.1158/1538-7445.AM2013-2571

Abstract 1336: A population-based study of Transforming Growth Factor-Beta1 (TGFB1) polymorphisms and risk of breast cancer.

Abstract Transforming growth factor-beta1 (TGFB1) is a multifunctional cytokine that may play an important role in the development and progression of cancer. The results of a number of association studies of TGFB1 polymorphisms and breast cancer risk are inconclusive. This study examined 4 single nucleotide polymorphisms (SNPs) in TGFB1 and risk of breast cancer using data previously collected from a population based case-control study (n=307 cases and 664 controls) of Caucasian women conducted in Northeastern Ontario, Canada. The SNPs (rs8179181, rs8110090, rs1800470 (L10P), rs1800469 (-509C/T)) were selected as either tag SNPs or had been identified as potentially functional in other studies, and were analysed using Taqman genotyping assays. Two of the SNPs were at the 5’ end (rs1800469 (-509C/T), rs1800470) and were in high LD (D’ 0.98); the remaining SNPs (rs8179181, rs8110090) were at the 3’ end and were also in high LD (D’ 0.99). In single-SNP analyses, the variant homozygous genotypes in rs1800470 (CC) and rs8179181 (AA) were significantly protective in the codominant model with Odds Ratios (OR) and 95% Confidence Intervals (95% CIs) of 0.63 (0.40-0.99) and 0.45 (0.21-0.96), while the AG genotype of rs8110090 was significantly associated with increased breast cancer risk with an OR of 1.78 (95% CI 1.14-2.77). Of the seven estimated haplotypes, 3 were significantly protective for breast cancer; when compared to the referent haplotype (see Table). In conclusion, our results suggest that SNPs at both the 3’ and 5’ end of TGFB1 may be associated with risk of breast cancer, and future studies examining additional polymorphisms in these regions would be valuable. Haplotype association with breast cancer risk (n = 969; Global Haplotype Association p-value 0.0021)rs8179181rs8110090rs1800470rs1800469FrequencyOR (95% CI)P-value1GATC0.40281.002GACT0.23870.73 (0.55–0.97)0.033AATC0.17280.67 (0.48–0.93)0.0174GACC0.06710.49 (0.30–0.81)0.00545AACT0.0560.55 (0.30–1.00)0.0526GGTC0.02981.00 (0.48–2.09)0.997GGCT0.02271.82 (0.82–4.06)0.14 Citation Format: Mary A. Bewick, Michael SC Conlon. A population-based study of Transforming Growth Factor-Beta1 (TGFB1) polymorphisms and risk of breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1336. doi:10.1158/1538-7445.AM2013-1336

Abstract 4840: TGFBR1 and TP53 SNPs interactions associated with colorectal cancer risk: Analysis of metabolic pathways using a Random Forest approach.

Abstract Background: We recently found the association of african ancestry with colorrectal cancer risk in Colombian population. Currently due to sample size limitations we can not perform further analysis (ej.GWAS) to explore this finding. Pathway analysis has been proposed as a complementary approach to single SNP analyses in GWAS, specially in hypothesis driven analysis. AIM: To evaluate the association of SNP included in the SNP500 cancer with colorectal cancer risk in colombian population. Methods: We recruited 264 controls and 203 colorectal cancer cases from 5 Colombian cities.Participants gave written informed consent, donated blood samples and answered guided-questionnaires. SNP analysis was done using and high reliable comertial plataform the Illumina Cancer Panel This panel includes 1492 SNP related to different cancer metabolic pathways and were drawn from the SNP500 cancer database. After QC procedures we grouped these SNP according to the pathway maps reported in the KEGG database. Using a Random Forest Analysis we evaluate the discriminative capacity between cancer case and control of each SNP in each pathway separately. Age sex and african ancestry where considered covariates for this analysis. Those SNPs showing a better o similar performance to african ancestry were further analyzed in a conditional logistic regression model, where all known risk factors for colorectal cancer were included. Results: 1192 SNPs and 418 individuals pass through the QC protocol. SNP were grouped in 16 different pathways. Random Forest analysis showed that only 1 pathway, the hsa05210 (i.e colorrectal cancer) contained 2 SNPs, rs868 and rs2909430, that outperformed the discriminatory capacity of african ancestry between cases and controls. Conditional logistic regression analysis showed an interaction between both polymorphisms (p&amp;lt;0.001). Compared against carriers of the mayor alleles of these two SNPs, we found a protective effect against colorectal cancer risk among carriers of only one of the variants (OR 0.04 CI95% 0.01-0.25 and OR 0.26 CI95% 0.12-.053 for rs868 and rs2909430 respectively). In contrast we found a positive association with cancer risk among carriers of both variants (OR 12.5 CI95% 3.15-49-98). African ancestry possitive association remained significant in the multiple regression analysis (p&amp;lt;0.01). Rs868 and rs2909430 are located in TP53 and TGFBR1 genes. Other Polymorphisms in this genes has shown conflicting results in previous analysis on colorectal cancer risk. Conclusion: We report for the first time an epistatic effect between two polymorphism located in genes involved in the colorectal cancer metabolic pathway in an admixed population after controlling for population structure and known risk factors. These results may help to explain the diverging results observed in studies of the association of these genes with colorectal cancer risk Citation Format: Gustavo Hernandez-Suarez, MariaCarolina Sanabria, Martha Serrano, Jovanny Zabaleta, Albert Tenesa. TGFBR1 and TP53 SNPs interactions associated with colorectal cancer risk: Analysis of metabolic pathways using a Random Forest approach. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4840. doi:10.1158/1538-7445.AM2013-4840 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.