Matsumoto, Martha

Abstract Abstract 709 Background: A recent analysis of merged genome-wide and candidate gene genotypes in VTE cases and controls identified multiple tag SNPs that were strongly associated with VTE. Objective: To identify rare and/or novel functional variants by sequencing the implicated genes. Methods: Cases (n=1488) were Mayo Clinic European-American patients of non-Hispanic ancestry with objectively-diagnosed VTE in the absence of active cancer, venous catheter or antiphospholipid antibodies. Controls (n=1439) were Mayo Clinic outpatients without VTE who were frequency-matched on case age, gender, race, MI/stroke status and state of residence. For this analysis, we selected a subset of these cases and controls for sequencing to take advantage of the joint configuration of two ABO SNPs of primary interest, rs8176719 (ABO exon 6 deletion determining type O blood group) and rs2519093 (ABO intron 1 tag SNP), which were previously shown to be strongly associated with VTE (p=5.7E-12 and p=3.0E-16, respectively). We randomly sampled 82 cases and 14 controls within 3 of the 9 potential allele frequency cells (Figure). The rs8176719 alleles are -−/−- (double deletion is the common allele), –/G, and G/G (the rare allele). The rs2519093 alleles are GG (G is the common allele), AG, and AA (A is the rare allele). For each SNP, the genotypes are represented as 0, 1, or 2 copies of the minor allele. We represented the joint allelic configuration of the two SNPs with the number of copies of the rs8176719 given first as 0/0 (both with 0 copies of the minor allele), 0/1, 0/2 (0 copies of the rs8176719 SNP), 1/0 (1 copy of the rare rs8176719 SNP), 1/1/, and 1/2, and 2/0 (2 copies of the rare allele for the rs8176719 SNP and 0 copies of the rare allele of the rs2519093 SNP), 2/1, and 2/2. From the Figure one observes discrepancies between cases and controls at the 0/0, 1/1 and 2/2 combinations. We randomly sampled from these three combinations, taking one third of the case series. For each SNP, we had 28 cases with 0/0 copies of the rare allele, 27 cases with 1/1 copies of the rare allele; and 27 cases with the combination of 2/2 copies of the rare allele. We compared these 82 cases with 14 controls that do not have any of these combinations. Sixteen genes were selected for deep sequencing, including 5 genes harboring SNPs significantly associated with VTE (F5, SLC19A2, ABO, NME7, ATP1B1), 10 genes with SNPs marginally associated with VTE (C1orf114, KLKB1, SELP, F11, SCUBE1, PRKCB1, CD44, ITPR1, GFRA1, BLZF1), and CYP4V2 which reportedly confounds F11 and KLKB1. Agilent SureSelect probes were designed to capture and enrich the ∼2 Mb genomic regions of these 16 genes. Samples were multiplexed (12-plex) and sequenced using Illumina HiSeq 2000. The sequence reads were aligned to the human genome build 36 using Burrows-Wheeler Aligner, and the single nucleotide variants (SNVs) and small INDELs were called using SNVMix and GATK, respectively. For this analysis, novel ABO SNVs were tested for an association with VTE using age-, sex-adjusted logistic regression and Fisher's Exact Test. Results: 98% of the targeted regions were sequenced with > 20X coverage. On average, ∼2500 SNVs and ∼200 INDELs were detected in each sample. Fifteen novel SNVs in intron 6 and 3' of the ABO gene were associated with VTE (p<E-06) and belonged to 3 distinctive LD blocks; none were in LD with the coding or tag ABO SNPs (rs8176719; rs2519093). SNVs inside the middle LD block at the 3' of ABO are located within an enhancer and promoter histone marked with putative transcription factor binding sites. In addition, strong evidence from both ENCODE and dbEST support the middle LD block as lying within a novel transcript, probably an extension of the 3' of ABO. In addition, we discovered a novel, significant, protective, frame-shifting single base (G) deletion at ABO chr9:135120877. Conclusion: Novel ABO functional variants that are associated with VTE were identified by deep sequencing. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 1242 Background: While bivariate interactions between Factor V Leiden, prothrombin G20201A and hereditary deficiency of antithrombin, protein C and protein S compound VTE risk, whether other gene-gene interactions are associated with VTE is largely unknown. Objective: To test novel gene-gene interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to about 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested all pairwise SNP-SNP interactions using a 2-stage procedure (fast epistasis in the first stage and age, gender, MI/stroke status and state of residence adjusted analysis using logistic regression in the second stage). Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among 2.299×10^12 pairwise interactions tested, 900 million reached a p-value<E-06 and were be tested in the second stage. Of these, 2417, 278 and 22 SNP-SNP interactions reached p-values ≤1E-9, 1E–10, and1E-11 respectively; 121 SNP-SNP interactions reached the Bonferroni statistical significance threshold (≤5.555659E-11). The gene-gene pairwise interactions with p-values≤1E-11 were: (1) chromosome 3 open reading frame 70 (C3orf70) – short-chain dehydrogenase/reductase (SDR family) member 4 (DHRS4), (2) 1-acylglycerol-3-phosphate O-acyltransferase 4 (AGPAT4) - NIMA (never in mitosis gene a)-related kinase 6 (NEK6), and (3) TatD DNase domain containing 2 (TATDN2) – WAS protein family, member 3 (WASF3). No gene function data are available for C3orf70. DHRS4 encodes for a 3-ketosteroid reductase important for active steroid hormone regulation, AGPAT4 is important for signal transduction and lipid biosynthesis, NEK6 encodes for Nek6 which downregulates p53-induced cancer cell senescence, TATDN2 encodes a deoxyribonuclease, WASF3 encodes for a member of the Wiskott-Aldrich syndrome protein family which are key regulators of signal transduction and cytoskeletal reorganization in hematopoietic cells. Conclusion: Pairwise gene-gene interaction analyses suggest potential associations between VTE and novel genes for future testing in replication studies. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

Abstract Abstract 2295 Background: While interaction between Factor V Leiden and other VTE risk exposures compound VTE risk, whether other gene-environment interactions are associated with VTE is largely unknown. Objective: To test novel gene-environment interactions for an association with VTE. Methods: Genome-wide scan (Illumina 660Q [557,112 SNPs]) and candidate gene (12,551 SNPs in 764 genes within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways) genotypes from 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status) were merged and imputed to 2.5 million SNPs with MACH using HapMap Phase 2 (60 CEU). We tested pairwise interactions between these SNPS and each of 7 exposures (“stress” [defined as ever hospitalized, ever surgery, ever trauma, ever transfemoral procedure or ever leg paresis], ever surgery, ever neurosurgery, ever orthopedic surgery; and among women, ever pregnant, ≥3 pregnancies and ever oral contraceptives/hormone therapy), adjusted for age, gender, MI/stroke status and state of residence, using logistic regression. Results: The mean ± standard deviation case and control ages were 54.4 ± 16.2 and 55.6 ± 15.8 years, respectively and 51% were female. Among the 7 models, a significant interaction was found between stress and A2BP1 (rs735919, OR=0.2, p=2.8E-07), ever surgery and ABCG8 (rs6709904, OR=0.27, p=2.1E-07), orthopedic surgery and SLC24A3 (rs6081599, OR=0.53, p=2.8E-07), neurosurgery and TBC1D4 (rs17064485, OR=8.5, p=3.5E-07), every pregnant and MICALCL (rs11022321, OR=0.17, p=8.3E-07), >3 pregnancies and KLRB1 (rs2536929, OR=0.31, p=1.1E-07) and ever oral contraceptives/hormone therapy and LINGO2 (rs10969259, OR=2.02, p=4.9E-07). A2BP1 plays a role in RBC shape and size, ABCG8 is associated with severe hypercholesterolemia, SLC24A3 is important for intracellular calcium homeostasis, TBC1D4 participates in cell signaling in CD4+/CD45RO+ memory T-cells, MICALCL is an extracellular signal-regulated kinase 2-binding protein, KLRB1 regulates natural killer cell function, and LINGO2 encodes a leucine-rich repeat signaling protein. Our observed interaction of VTE risk factors with these genes to compound the risk of VTE requires replication in future studies. If confirmed, functional studies will be important to determine the roles of these gene products in the causal pathway to VTE. Conclusion: VTE risk factors and SNPs within several novel genes may interact to compound the risk of VTE. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.

AbstractGenome‐wide association studies (GWAS) are being conducted at an unprecedented rate in population‐based cohorts and have increased our understanding of the pathophysiology of complex disease. Regardless of context, the practical utility of this information will ultimately depend upon the quality of the original data. Quality control (QC) procedures for GWAS are computationally intensive, operationally challenging, and constantly evolving. Here we enumerate some of the challenges in QC of GWAS data and describe the approaches that the electronic MEdical Records and Genomics (eMERGE) network is using for quality assurance in GWAS data, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of GWAS data, including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We propose best practices and discuss areas of ongoing and future research. Curr. Protoc. Hum. Genet. 68:1.19.1‐1.19.18 © 2011 by John Wiley & Sons, Inc.

Abstract Background: Inherited risk of pancreatic cancer has been associated with mutations in several genes, including BRCA2, CDKN2A (p16), PRSS1, and PALB2. We hypothesized that common variants in these genes, single nucleotide polymorphisms (SNP), may also influence risk for pancreatic cancer development. Methods: A clinic-based case-control study in non-Hispanic white persons compared 1,143 patients with pancreatic adenocarcinoma with 1,097 healthy controls. Twenty-eight genes directly and indirectly involved in the Fanconi/BRCA pathway (includes BRCA1, BRCA2, and PALB2) were identified and 248 tag SNPs were selected. In addition, 11 SNPs in CDKN2A, PRSS1, and PRSS2 were selected. Association studies were done at the gene level by principal components analysis, whereas recursive partitioning analysis was used to investigate pathway effects. At the individual SNP level, adjusted additive, dominant, and recessive models were investigated, and gene-environment interactions were also assessed. Results: Gene level analyses showed no significant association of any genes with altered pancreatic cancer risk. Multiple single SNP analyses showed associations, which will require replication. Exploratory pathway analyses by recursive partitioning showed no association between SNPs and risk for pancreatic cancer. Conclusion: In a candidate gene and pathway SNP association study analysis, common variations in the Fanconi/BRCA pathway and other candidate familial pancreatic cancer genes are not associated with risk for pancreatic cancer. Cancer Epidemiol Biomarkers Prev 2009;18(9):2549–52)