Citations

Abstract Abstract 2443 Background: There is strong and consistent evidence that a genetic component contributes to the etiology of chronic lymphocytic leukemia (CLL). A recent genome-wide association (GWA) study of CLL identified genetic variants located on chromosomes 2q13, 2q37.1, 6p25, 11q24, 15q23, and 19q13 that increased the risk of CLL within a European population. We replicated 5 of these 6 loci in an independent sample of CLL cases and controls from the United States. We now investigate whether these loci also influences MBL, a reported precursor condition of CLL. In addition, a follow-up analysis of the initial GWA study identified four more CLL-susceptibility loci on 2q37.3, 8q24.21, 15q21.3, and 16q24.1. Herein, we also evaluate the association of these four loci with risk of CLL. Methods: Peripheral blood samples were obtained from three ongoing studies: the Genetic Epidemiology CLL (GEC) Consortium, the Mayo Clinic non-Hodgkin lymphoma (NHL)/ CLL study, and the Mayo Clinic Biobank. We implemented rigorous genotyping quality-control measures, and successfully genotyped a total of 407 CLL patients, 965 controls, and 60 MBLs from these studies. Within each locus, the previously reported single nucleotide variants (SNPs) or variants in high linkage disequilibrium (LD) with the previously reported SNPs were evaluated with risk of MBL or CLL. Tests for association was done using the Cochran-Armitage trend test, and unconditional logistic regression was used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for CLL or MBL risk Results: In our evaluation of the six initially reported CLL-susceptibility loci (2q13, 2q37.1, 6p25, 11q24, 15q23, and 19q13) with MBL risk, we found three of the six had suggestive associations (p-value < 0.20) with ORs comparable to and in the same direction as those observed from CLL risk. Our strongest finding was with rs13397985 at locus 2q37.1 (OR= 1.56; 95% CI: 1.05, 2.31; p-trend = 0.041), followed by rs17483466 at locus 2q13 (OR= 1.49; 95% CI: 0.99, 2.24; p-trend = 0.074). As expected given our previously reported findings with CLL risk, the association between rs11083846 on chromosome 19q13 and MBL risk was not significant (p-trend = 0.70). Of the four recently reported CLL-susceptibility loci SNPs located on 2q37.3, 8q24.21, 15q21.3, and 16q24.1, we found all to be associated with CLL risk but one. Specifically, the strongest association was seen for locus 8q24.21 (best tagged SNP rs1021955; OR = 1.37; 95% CI: 1.10, 1.70; p-trend = 0.005), followed by locus 16q24.1 (best tagged SNP rs305065; OR= 0.77; 95% CI: 0.61, 0.97; p-trend = 0.024). However, we found no associations for locus 15q21.3 for the previously reported SNP nor for any SNPs in LD with the previously reported SNP. Conclusions: Our MBL results provide additional robust genetic evidence that MBL is a precursor to CLL and that it shares similar underlying genetic predisposition. Also our results confirm three of the four recently reported CLL-susceptibility loci and further support the role of a genetic basis in the etiology of CLL. More research is needed to elucidate the potential manner in which these genetic loci function in CLL or MBL. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results: As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92 % of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions: Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

Abstract Introduction: Several B-cell malignancies, including chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), are known to have a familial component to disease risk. Although several common inherited genetic variants have been found to be associated with risk of these malignancies, a large proportion of the heritability remains unexplained. Here we set out to identify rare high-penetrance susceptibility variants for CLL and MM using the established Mayo Clinic family study of B-cell malignancies. Methods: We performed exome sequencing on germ line DNA of 106 families with either two or more members with CLL (n=93 families) or two or more members with MM or monoclonal gammopathy of undetermined significance (MGUS) (n=13 families) using Aglient capture kits. All samples were sequenced on an Illumina HiSeq2000. Bioinformatics analyses leveraged the following software packages: Novoalign, Picard, The Genome Analysis Toolkit (GATK), and the Biological Reference Repository (bioR). Quality control filters were implemented; subjects with mis-specified relationships were removed as were variants with <95% call rate or <20x coverage, and those variants identified as sequencing artifacts. To identify potentially functional single nucleotide variants, the following was required a) uncommon in public databases, b) cosegregating variants in multiple families, c) variants to be highly conserved and in coding regions, and d) functional prediction status of deleterious (SIFT score), damaging (PolyPhen score), and a moderate, or high variant impact (SNPEffect). The association of these variants with risk was then evaluated in large samples of cases and controls in genome-wide association studies (GWAS). Results: In the CLL familial cohort, there were 443 individuals (160 with CLL, 73 with monoclonal B cell lymphocytosis (MBL), and 210 relatives without CLL or MBL) sequenced; and in the MM cohort, there were 39 individuals (13 with MM, 13 with MGUS and 13 without MM or MGUS) sequenced. A total of 61,992 single nucleotide variants passed quality control filters in the CLL cohort and 39,456 single nucleotide variants in the MM cohort. From these, we identified 32 variants in the CLL cohort and 39 variants in the MM cohort that were cosegregating in multiple CLL or MM families, respectively, and were predicted to affect protein structure or function. Of these, one CLL variant was within 1 Mb of a known GWAS-discovered locus. Moreover, there were seven CLL and four MM variants that were within 1 Mb of single nucleotide polymorphisms (SNPs) that had statistical significance between p<10-4 and p<10-6 in GWAS. Finally, there were 3 variants found to be common between CLL and MM families (see Table). Conclusions: Through whole exome sequencing, we identified a number of rare, highly penetrant predisposition variants for CLL and MM. Several of these variants were common to both B-cell malignancies providing evidence of shared genetic components; one variant may be a functional driver of the GWAS-discovered loci. These identified variants provide a list for future validation studies. Table: Exome variants common in both Chronic Lymphocytic Leukemia and Multiple Myeloma SNP ID rs41314099 rs61754114 rs143025033 Chromosome 17 6 7 Gene WSCD1 BACH2 TNS3 Penetrance (CLL) 0.70 0.75 0.80 Penetrance (MM) 1.00 0.80 0.75 Allele Frequency (CLL) 0.015 0.025 0.017 Allele Frequency (MM) 0.077 0.077 0.058 1000 Genome Frequency (European) 0.010 0.020 0.010 SIFT Term Deleterious Deleterious Deleterious PolyPhen Term Probably Damaging Probably Damaging Probably Damaging SNP: Single Nucleotide Polymorphism; CLL: Chronic Lymphocytic Leukemia; MM: Multiple Myeloma; Penetrance is defined as proportion of individuals carrying the alternate allele that are also affected; SIFT: Sorting Intolerant From Tolerant, predicts whether an amino acid substitution affects protein function; PolyPhen: Polymorphism Phenotyping, predicts possible impact of an amino acid substitution on the structure of a human protein Disclosures No relevant conflicts of interest to declare.

Abstract Abstract 150 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 gene-gene interactions for an association with VTE. Methods: Cases (n=1004) 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=1066) were Mayo Clinic outpatients without VTE who were frequency-matched on case age, gender, race, MI/stroke status and state of residence. We selected candidate genes relevant to the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways, focusing on platelet, monocyte, neutrophil and endothelial cell agonists, receptors, ligands, signal transduction and adhesion molecules, granule contents and effectors; plasma proteases and inhibitors; matrix metalloproteases; inflammatory cytokines and receptors; estrogen, progesterone and androgen receptors; co-regulators and enzymes related to estrogen metabolism; important enzymes for catechol, homocysteine, thromboxane A2 and prostacyclin biosynthesis and metabolism; and HMG CoA reductase. For these genes (n=780), we selected all non-synonymous coding single nucleotide polymorphisms (SNPs) with minor allele frequency ≥0.5%; the remaining SNPs were selected using an LD tagging algorithm (Carlson et al. AJHG 2004); 558 ancestry-informative markers were also included (total n=13,237 SNPs). Leukocyte genomic DNA was genotyped using a custom Illumina Infinium iSelect chemistry and platform, including appropriate controls. For these analyses, all pairwise SNP-SNP interactions for 12,313 SNPs were tested using logistic regression. In addition, we tested all Factor V Leiden -, prothrombin G20210A - and ABO non-O blood group - SNP interactions. Results: The mean ± SD case and control ages were 55.3 ± 16.4 and 56.5 ± 15.9 years, respectively, and 51% were female. Analysis of ancestry-informative markers gave no evidence of population stratification. Among almost 76 million pairwise interactions tested, 504, 44 and 8 SNP-SNP interactions reached p-values ≤ 1E-5, 1E-6, and 1E-7 respectively; none reached the Bonferroni statistical significance threshold (≤ 6.6E-10). The gene-gene pairwise interactions with p-values ≤ 1E-7 included: Leptin receptor - Estrogen receptor 1, α1 Antichymotrypsin - β2 glycoprotein 1, CRADD(caspace) - B1 Bradykinin receptor, ILF10 - Prolactin receptor and GFRA2(TGFβ neurotrophic factor receptor) - Bactericidal permeability-increasing protein. Gene-gene pairwise interactions with the lowest p-value for Factor V Leiden -, prothrombin G20210A - and ABO non-group O - were Protein kinase C beta (2.1E-5), von Willebrand Factor (7.6E-4) and Phospholipase C gamma-2 (6.7E-4), respectively. Conclusion: Pairwise gene-gene interaction analyses suggest potential associations between VTE and novel genes and gene pathways. These potential associations require confirmation in future replication studies. Disclosures: No relevant conflicts of interest to declare.

Abstract Background Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different library preparations. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting fromcytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

Abstract Background Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different library preparations. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting fromcytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

The catechol-O-methyltransferase Val158Met polymorphism has been associated with alterations in pain perception, but the influence of the polymorphism on pain perception in patients with chronic pain receiving daily opioid therapy has not been previously reported. The primary aim of this study was to investigate the effects of the catechol-O-methyltransferase Val158Met polymorphism on heat pain perception in a cohort of adults receiving daily opioid therapy for chronic pain. Adults with chronic pain consecutively admitted to an outpatient pain rehabilitation program who met inclusion criteria and were receiving daily opioid therapy were recruited for study participation (N = 142). Individuals were genotyped for catechol-O-methyltransferase Val158Met (rs4680), and the polymorphism was analyzed using an additive and codominant genotype models. The distribution of the Val158Met genotypes was 25% for Val/Val, 41% for Val/Met and 34% for Met/Met (Hardy–Weinberg, P > 0.05). A main effect of genotype was observed for heat pain perception ( P = 0.028). Under the codominant model of allele effects, exploratory post hoc pairwise comparisons adjusted for morphine equivalent dose and pain catastrophizing demonstrated that individuals with the Val/Met genotype were hyperalgesic compared to individuals with the Val/Val ( P = 0.039) and Met/Met ( P = 0.023) genotypes. No significant association was observed between heat pain perception and genotype under the additive model of allele effects. Among patients with chronic pain who were receiving daily opioids, the Val/Met genotype was associated with hyperalgesia using a measure of heat pain perception that has been previously indicative of opioid-induced hyperalgesia in other heterogeneous samples of adults with chronic pain. This study contributes to the emerging understanding of how catechol-O-methyltransferase activity affects pain perception in the context of daily opioid use, and these findings may be useful in the design of future trials aimed at investigating the potential efficacy of ß-2 adrenergic receptor antagonism for opioid-induced hyperalgesia.

AbstractBackground:Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.Methods:CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (&gt;1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.Results:Three CNVRs were associated (P &lt; 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (&lt;5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10−5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10−47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10−2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10−5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10−7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10−5).Conclusions:Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.Impact:Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.