Affymetrix Single Nucleotide Polymorphism Arrays Research Articles

Transcriptomic and genomic heterogeneity in blastic plasmacytoid dendritic cell neoplasms: from ontogeny to oncogenesis

Oncogenesis and ontogeny of blastic plasmacytoid dendritic cell neoplasm (BPDCN) remain uncertain, between canonical plasmacytoid dendritic cells (pDCs) and AXL+ SIGLEC6+ DCs (AS-DCs). We compared 12 BPDCN to 164 acute leukemia by Affymetrix HG-U133 Plus 2.0 arrays: BPDCN were closer to B-cell acute lymphoblastic leukemia (ALL), with enrichment in pDC, B-cell signatures, vesicular transport, deubiquitination pathways, and AS-DC signatures, but only in some cases. Importantly, 1 T-cell ALL clustered with BPDCN, with compatible morphology, immunophenotype (cCD3+ sCD3− CD123+ cTCL1+ CD304+), and genetics. Many oncogenetic pathways are deregulated in BPDCN compared with normal pDC, such as cell-cycle kinases, and importantly, the transcription factor SOX4, involved in B ontogeny, pDC ontogeny, and cancer cell invasion. High-throughput sequencing (HaloPlex) showed myeloid mutations (TET2, 62%; ASXL1, 46%; ZRSR2, 31%) associated with lymphoid mutations (IKZF1), whereas single-nucleotide polymorphism (SNP) array (Affymetrix SNP array 6.0) revealed frequent losses (mean: 9 per patient) involving key hematological oncogenes (RB1, IKZF1/2/3, ETV6, NR3C1, CDKN2A/B, TP53) and immune response genes (IFNGR, TGFB, CLEC4C, IFNA cluster). Various markers suggest an AS-DC origin, but not in all patients, and some of these abnormalities are related to the leukemogenesis process, such as the 9p deletion, leading to decreased expression of genes encoding type I interferons. In addition, the AS-DC profile is only found in a subgroup of patients. Overall, the cellular ontogenic origin of BPDCN remains to be characterized, and these results highlight the heterogeneity of BPDCN, with a risk of a diagnostic trap.

Assessment of Height Prediction Model Based on SNPs Loci

To establish a height prediction model of Chinese Han male based on the reported 547 height-associated single nucleotide polymorphisms （SNPs） loci in Europeans, and assess its accuracy for height estimation. The DNA typing was analyzed in 59 Han male samples of Shandong province by Affymetrix SNP Array 6.0 chip and HiSeq 4000 sequencing platform. Prediction model was established using 547 height-associated SNPs loci as predictors and weight allele sums （WAS） as computing method. The accuracy of height prediction model was analysed using receiver operating characteristic （ROC） curve and area under curve （AUC）. There was no height-associated SNPs locus was found by genome-wide association studies. In present study, height prediction model was established by WAS and obtained an AUC of 0.67 （95% CI: 0.53-0.90）. It has reference value for predicting the height of Han male in Shandong province by WAS model based on 547 SNPs loci, while it is still necessary to further promote the accuracy of the prediction model by screening more height-associated SNPs loci with population heterogeneity.

Genome-wide genotype-based risk model for survival in core binding factor acute myeloid leukemia patients.

The present study attempted to build a single nucleotide polymorphism (SNP)-based risk model for predicting overall survival (OS) and event-free survival (EFS) in patients with core binding factor acute myeloid leukemia (CBF-AML). Adopting genome-wide SNP array using Affymetrix SNP array 6.0, we analyzed 868,157 SNPs with respect to OS and EFS in 104 patients with CBF-AML. Significant SNPs were identified from single SNP analysis. The risk model was constructed with incorporation of six SNPs and three clinical factors (age, c-kit exon 17 mutation, and LDH) for OS and six SNPs and three clinical factors (age, WBC, and LDH) for EFS. The model was further defined into low- and high-risk groups based on risk scores. The median age was 39years, and the subgroup of t(8;21) and inv(16) or t(16;16) was assessed in 68 (65.4%) and 36 patients (34.6%). Finally, six SNPs per each OS (rs4353685, rs4908185, rs7709207, rs12034, rs1554844, and rs17241868) and EFS (rs13385610, rs11210617, rs11169282, rs7709207, rs4438401, and rs16894846) were incorporated into the risk model. OS was significantly different in favor of the low risk group (80.4 ± 8.4%) compared to the high-risk group (22.0 ± 7.3% at 3years; p = 8.75 × 10- 13; HR 8.67). For EFS, there was also a significant difference between the low- (75.0 ± 5.8%) versus high-risk group (17.1 ± 6.3% at 3years; p = 5.95 × 10- 13; HR 7.67). A genome-wide SNP-based risk model can stratify CBF-AML patients according to their OS and EFS in 104 patients.

Genome-wide association study of high-altitude pulmonary edema in a Han Chinese population.

A two-stage genome-wide association study (GWAS) was performed to identify and analyze genes and single nucleotide polymorphisms (SNPs) associated with high-altitude pulmonary edema (HAPE) in a Han Chinese patient population. In the first stage, DNA samples from 68 patients with recurrent HAPE were scanned using Affymetrix SNP Array 6.0 Chips, and allele frequencies were compared to those of 84 HapMap CHB samples to identify candidate SNPs. In the second stage, the 77 identified candidate SNPs were examined in an independent cohort of samples from 199 HAPE patients and 304 controls. Associations between SNPs and HAPE risk were tested using various genetic models. Of the 77 original SNPs, 7 were found to be associated with HAPE susceptibility in the second stage of the study. GO and pathway enrichment analysis of the 7 SNPs revealed 5 adjacent genes involved in various processes, including regulation of nucleoside diphosphate metabolism, thyroid hormone catabolism, and low-density lipoprotein receptor activity. These results suggest the identified SNPs and genes may contribute to the physiopathology of HAPE.

Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis.

INTRODUCTIONBreast cancer being a multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. However, the task for the identification of these variances is complicated by the interplay between inherited genetic and epigenetic aberrations. Therefore, this study provides an extrapolate outlook to the sinister partnership between DNA methylation and single-nucleotide polymorphisms (SNPs) in relevance to the identification of prognostic markers in breast cancer. The effect of these SNPs on methylation is defined as methylation quantitative trait loci (meQTL).MATERIALS AND METHODSWe developed a novel method to identify prognostic gene signatures for breast cancer by integrating genomic and epigenomic data. This is based on the hypothesis that multiple sources of evidence pointing to the same gene or pathway are likely to lead to reduced false positives. We also apply random resampling to reduce overfitting noise by dividing samples into training and testing data sets. Specifically, the common samples between Illumina 450 DNA methylation, Affymetrix SNP array, and clinical data sets obtained from the Cancer Genome Atlas (TCGA) for breast invasive carcinoma (BRCA) were randomly divided into training and test models. An intensive statistical analysis based on log-rank test and Cox proportional hazard model has established a significant association between differential methylation and the stratification of breast cancer patients into high- and low-risk groups, respectively.RESULTSThe comprehensive assessment based on the conjoint effect of CpG–SNP pair has guided in delaminating the breast cancer patients into the high- and low-risk groups. In particular, the most significant association was found with respect to cg05370838–rs2230576, cg00956490–rs940453, and cg11340537–rs2640785 CpG–SNP pairs. These CpG–SNP pairs were strongly associated with differential expression of ADAM8, CREB5, and EXPH5 genes, respectively. Besides, the exclusive effect of SNPs such as rs10101376, rs140679, and rs1538146 also hold significant prognostic determinant.CONCLUSIONSThus, the analysis based on DNA methylation and SNPs have resulted in the identification of novel susceptible loci that hold prognostic relevance in breast cancer.

Genome-Wide Genotype-Based Risk Model for Survival in Core Binding Factor Acute Myeloid Leukemia Patients

Introduction: The present study attempted to build a single nucleotide polymorphism (SNP)-based risk model for predicting overall survival (OS) and event free survival (EFS) in patients with core binding factor acute myeloid leukemia (CBF-AML).Methods: Adopting genome-wide SNP array using Affymetrix SNP array 6.0, we analyzed 868,157 SNPs with respect to OS and EFS in 104 patients with CBF-AML. Significant SNPs were identified from single SNP analysis. The risk model was constructed with incorporation of six SNPs and three clinical factors (age, c-kit exon 17 mutation, and LDH) for OS, and six SNPs and three clinical factors (age, WBC, and LDH) for EFS. The model was further defined into low and high risk groups based on risk scores.Results: The median age was 39 years, and the subgroup of t(8;21) and inv(16) or t(16;16) was assessed in 68 (65.4%) and 36 patients (34.6%). Finally 6 SNPs per each OS (rs4353685, rs4908185, rs7709207, rs12034, rs1554844, and rs17241868) and EFS (rs13385610, rs11210617, rs11169282, rs7709207, rs4438401 and rs16894846) were incorporated into the risk model. OS was significantly different in favor of the low risk group (80.4%) compared to the high risk group (22.0% at 3 years; p= 8.75 x 10-13; HR 8.67). For EFS, there was also a significant difference between the low (75.0%) versus high risk group (17.1% at 3 years; p=5.95 x 10-13; HR 7.67).Conclusion: A genome-wide SNP based risk model can stratify CBF-AML patients according to their OS and EFS in 104 patients. [Display omitted] [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Multiplicative interaction of functional inflammasome genetic variants in determining the risk of gout

IntroductionThe acute gout flare results from a localised self-limiting innate immune response to monosodium urate (MSU) crystals deposited in joints in hyperuricaemic individuals. Activation of the caspase recruitment domain-containing protein 8 (CARD8) NOD-like receptor pyrin-containing 3 (NLRP3) inflammasome by MSU crystals and production of mature interleukin-1β (IL-1β) is central to acute gouty arthritis. However very little is known about genetic control of the innate immune response involved in acute gouty arthritis. Therefore our aim was to test functional single nucleotide polymorphism (SNP) variants in the toll-like receptor (TLR)-inflammasome-IL-1β axis for association with gout.Methods1,494 gout cases of European and 863 gout cases of New Zealand (NZ) Polynesian (Māori and Pacific Island) ancestry were included. Gout was diagnosed by the 1977 ARA gout classification criteria. There were 1,030 Polynesian controls and 10,942 European controls including from the publicly-available Atherosclerosis Risk in Communities (ARIC) and Framingham Heart (FHS) studies. The ten SNPs were either genotyped by Sequenom MassArray or by Affymetrix SNP array or imputed in the ARIC and FHS datasets. Allelic association was done by logistic regression adjusting by age and sex with European and Polynesian data combined by meta-analysis. Sample sets were pooled for multiplicative interaction analysis, which was also adjusted by sample set.ResultsEleven SNPs were tested in the TLR2, CD14, IL1B, CARD8, NLRP3, MYD88, P2RX7, DAPK1 and TNXIP genes. Nominally significant (P < 0.05) associations with gout were detected at CARD8 rs2043211 (OR = 1.12, P = 0.007), IL1B rs1143623 (OR = 1.10, P = 0.020) and CD14 rs2569190 (OR = 1.08; P = 0.036). There was significant multiplicative interaction between CARD8 and IL1B (P = 0.005), with the IL1B risk genotype amplifying the risk effect of CARD8.ConclusionThere is evidence for association of gout with functional variants in CARD8, IL1B and CD14. The gout-associated allele of IL1B increases expression of IL-1β – the multiplicative interaction with CARD8 would be consistent with a synergy of greater inflammasome activity (resulting from reduced CARD8) combined with higher levels of pre-IL-1β expression leading to increased production of mature IL-1β in gout.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0802-3) contains supplementary material, which is available to authorized users.

TAFFYS: An Integrated Tool for Comprehensive Analysis of Genomic Aberrations in Tumor Samples.

BackgroundTumor single nucleotide polymorphism (SNP) array is a common platform for investigating the cancer genomic aberration and the functionally important altered genes. Original SNP array signals are usually corrupted by noise, and need to be de-convoluted into absolute copy number profile by analytical methods. Unfortunately, in contrast with the popularity of tumor Affymetrix SNP array, the methods that are specifically designed for this platform are still limited. The complicated characteristics of noise in signals is one of the difficulties for dissecting tumor Affymetrix SNP array data, as they inevitably blur the distinction between aberrations and create an obstacle for the copy number aberration (CNA) identification.ResultsWe propose a tool named TAFFYS for comprehensive analysis of tumor Affymetrix SNP array data. TAFFYS introduce a wavelet-based de-noising approach and copy number-specific signal variance model for suppressing and modelling the noise in signals. Then a hidden Markov model is employed for copy number inference. Finally, by using the absolute copy number profile, statistical significance of each aberration region is calculated in term of different aberration types, including amplification, deletion and loss of heterozygosity (LOH). The result shows that copy number specific-variance model and wavelet de-noising algorithm fits well with the Affymetrix SNP array signals, leading to more accurate estimation for diluted tumor sample (even with only 30% of cancer cells) than other existed methods. Results of examinations also demonstrate a good compatibility and extensibility for different Affymetrix SNP array platforms. Application on the 35 breast tumor samples shows that TAFFYS can automatically dissect the tumor samples and reveal statistically significant aberration regions where cancer-related genes locate.ConclusionsTAFFYS provide an efficient and convenient tool for identifying the copy number alteration and allelic imbalance and assessing the recurrent aberrations for the tumor Affymetrix SNP array data.

Polymorphisms in PDE4D are Associated with a Risk of COPD in Non-Emphysematous Koreans

Despite extensive effort, only a few chronic obstructive pulmonary disease (COPD)-associated genes have been suggested, indicating that there must be additional risk-associated loci. Here we aimed to identify additional COPD-associated SNPs and to explore the potential relationship between COPD subgroups and the SNPs in the Korean population. We performed a genome-wide association study (GWAS) with 990 Korean individuals; 102 COPD cases and 544 controls for GWAS using Affymetrix SNP array 5.0, and 173 COPD cases and 171 controls for replication. After validating the candidate single nucleotide polymorphisms (SNP), we performed subgroup analysis by disease phenotype. Through GWAS, we identified a novel SNP in the phosphodiesterase-4D (PDE4D) gene [rs16878037 (C>T), p = 1.66 ◊ 10−6] that was significantly associated with COPD. This signal in PDE4D was successfully replicated in the independent set (p = 0.041). When we combined the discovery and replication data, the association signal became more significant (p = 5.69 ◊ 10−7). In the COPD subgroup analysis, the T allele of rs16878037 was significantly more frequent in COPD patients without severe diffusion capacity impairment (mild mixed and obstruction-dominant group) than in patients with severe impairment (severe mixed and emphysema-dominant groups). This result supports that PDE4D polymorphisms might be involved in the susceptibility to COPD especially in non-emphysematous individuals and that they could also affect the responsiveness of the PDE4 inhibitor treatment.

Evaluation of copy number variation detection for a SNP array platform

BackgroundCopy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform.We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the “gold standard”. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the “gold standard”. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package.ResultsSimply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest.ConclusionWe found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling.

Genome-wide association study of high-altitude pulmonary edema in Han Chinese

High-altitude pulmonary edema (HAPE) is a non-cardiogenic pulmonary edema that is always found among unacclimatized persons after rapid ascent to high altitude, and HAPE is caused by the interaction of genetic and environmental factors. To screen and analyze the susceptibility genes and single nucleotide polymorphisms (SNPs) of HAPE in Han Chinese, the DNA samples of 40 patients with HAPE and 33 healthy controls, who performed the reconstruction tasks from the plain region in Yushu area of Qinghai province during May of 2010 to July of 2012, were scanned by Affymetrix SNP Array 6.0 Chips in this study. Genome-wide association study (GWAS, by PLINK software) was used to screen the susceptibility genes and genetic markers, and a total of 57 SNPs were found to be significantly different between case and control groups (adjust P < 0.05). GO and Pathway enrichment analysis of 74 genes around the 57 SNPs indicated that these genes were significantly correlated with prostanoid metabolic process, arachidonic acid metabolism and nitrogen metabolism (adjust P < 0.05), which were involved in the physiopathologic mechanism of HAPE. Our studies suggest that these genetic polymorphisms and genes were associated with HAPE.

Genome‐wide genotype‐based risk model for survival in acute myeloid leukaemia patients with normal karyotype

Single nucleotide polymorphisms (SNP) are inter-individual genetic variations that could explain inter-individual differences of response/survival to chemotherapy. The present study was performed to build up a risk model for survival in 247 patients with acute myeloid leukaemia (AML) with normal karyotype (AML-NK). Genome-wide Affymetrix SNP array 6.0 was used for genotyping in discovery set (n = 118). After identifying significant SNPs for overall survival (OS) in single SNP analysis, a risk model was constructed. Out of 632 957 autosomal SNPs analysed, finally four SNPs (rs2826063, rs12791420, rs11623492 and rs2575369) were introduced into the risk model. The model could stratify the patients according to their OS in discovery set (P = 1·053656 × 10−4). Replication was performed using Sequenom platform for genotyping in the validation cohort (n = 129). The model incorporated with clinical and four SNP risk score was successfully replicated in a validation set (P = 5·38206 × 10−3). The integration of four SNPs and clinical factors into the risk model showed higher area under the curve (AUC) reults than in the model incorporating only clinical or only four SNPs, suggesting improved prognostic stratification power by combination of four SNPs and clinical factors. In conclusion, a genome-wide SNP-based risk model in 247 patients with AML-NK can identify a group of high risk patients with poor survival.

Genome-wide association study of serum albumin:globulin ratio in Korean populations

Low albumin:globulin (A/G) ratios are associated with vascular adverse events, nephrotic syndrome and autoimmune disease. Genome-wide association studies (GWASs) have been identifying genetic variants associated with total serum protein, serum albumin and globulins, but A/G ratio has never been considered the target phenotype. To identify the genetic basis of the A/G ratio, we performed a GWAS on A/G ratio in 4205 individuals from the Ansan cohort and confirmed the results in 4637 subjects from the Ansung cohort. The single-nucleotide polymorphism (SNP) genotypes of Affymetrix SNP array 5.0 were obtained from the Korean Association Resource Consortium, and we selected 290 659 common SNPs with a minor allele frequency >0.05. Genetic factors for A/G ratio were analyzed by linear regression analysis, controlling for age, sex, body mass index, smoking status and alcohol drinking status as covariates. From the GWAS of the Ansan cohort, we identified two significant genome-wide signals (P-values<5 × 10(-8)) and 36 moderate signals (P-value<1.0 × 10(-4)). These 38 signals were tested in the Ansung population. Eleven SNPs from six loci (GALNT2, IRF4, HLA-DBP1, SLC31A1, FADS1 and TNFRSF13B) were replicated, with P-values<0.05. The most compelling association was observed in the TNFRSF13B locus on chromosome 17p11.2 (SNP: rs4561508), with an overall combined P-value=7.80 × 10(-24). The other significant signal was observed on chromosome 11q12.2-the FADS1 locus (SNP: rs174548)-with an overall combined P-value=3.54 × 10(-8).

Preterm Birth Genome Project (PGP) – validation of resources for preterm birth genome-wide studies

We determined a series of quality control (QC) analyses to assess the usability of DNA collected and processed from different countries utilizing different DNA extraction techniques prior to genome-wide association studies (GWAS). The quality of DNA collected utilizing four different DNA extraction techniques and the impact of shipping DNA at different temperatures on array performance were evaluated. Fifteen maternal-fetal pairs were used from four countries. DNA was extracted using four approaches: whole blood, blood spots with whole genome amplification (WGA), saliva and buccal swab. Samples were sent to a genotyping facility, either on dry ice or at room temperature and genotyped using Affymetrix SNP array 6.0. QC measured included extraction techniques, effect of shipping temperatures, accuracy and Mendelian concordance. Significantly fewer (50 % ) single nucleotide polymorphisms (SNPs) passed QC metrics for buccal swab DNA (P < 0.0001) due to missing genotype data (P < 0.0001). Whole blood or saliva DNA had the highest call rates (99.2 0.4 % and 99.3 0.2 % , respectively) and Mendelian concordance. Shipment temperature had no effect. DNA from blood or saliva had the highest call rate accuracy, and buccal swabs had the lowest. DNA extracted from blood, saliva and blood spots were found suitable for GWAS in our study.

Genotype Imputation for African Americans Using Data From HapMap Phase II Versus 1000 Genomes Projects

Genotype imputation provides imputation of untyped single nucleotide polymorphisms (SNPs) that are present on a reference panel such as those from the HapMap Project. It is popular for increasing statistical power and comparing results across studies using different platforms. Imputation for African American populations is challenging because their linkage disequilibrium blocks are shorter and also because no ideal reference panel is available due to admixture. In this paper, we evaluated three imputation strategies for African Americans. The intersection strategy used a combined panel consisting of SNPs polymorphic in both CEU and YRI. The union strategy used a panel consisting of SNPs polymorphic in either CEU or YRI. The merge strategy merged results from two separate imputations, one using CEU and the other using YRI. Because recent investigators are increasingly using the data from the 1000 Genomes (1KG) Project for genotype imputation, we evaluated both 1KG-based imputations and HapMap-based imputations. We used 23,707 SNPs from chromosomes 21 and 22 on Affymetrix SNP Array 6.0 genotyped for 1,075 HyperGEN African Americans. We found that 1KG-based imputations provided a substantially larger number of variants than HapMap-based imputations, about three times as many common variants and eight times as many rare and low-frequency variants. This higher yield is expected because the 1KG panel includes more SNPs. Accuracy rates using 1KG data were slightly lower than those using HapMap data before filtering, but slightly higher after filtering. The union strategy provided the highest imputation yield with next highest accuracy. The intersection strategy provided the lowest imputation yield but the highest accuracy. The merge strategy provided the lowest imputation accuracy. We observed that SNPs polymorphic only in CEU had much lower accuracy, reducing the accuracy of the union strategy. Our findings suggest that 1KG-based imputations can facilitate discovery of significant associations for SNPs across the whole MAF spectrum. Because the 1KG Project is still under way, we expect that later versions will provide better imputation performance.

Abstract 178: RCBTB1 Genotypes Modulate Smoking Effect on Carotid Intima-Media Thickness: A Finding from a Genome-Wide Interaction Analysis

Objective: Smoking is an established risk factor for atherosclerotic disease. However, the degree of the cigarette smoking-induced damage varies from individual to individual, partly due to the between-individual difference in genetic makeup. The aim of this study was to identify genetic loci influencing the effect of cigarette smoking on carotid intima-media thickness (IMT) by performing a genome-wide association smoking-by-SNP interaction analysis. Methods and results: Genome-wide genotyping was performed using the Affymetrix SNP array 6.0 among 1,010 individuals who underwent B-mode ultrasound examination of carotid IMT from the population-based Northern Manhattan Study. Cigarette pack-years was calculated as number of years smoked multiplied by number of cigarettes smoked per day, then divided by 20. After quality control, a total of 722,379 single nucleotide polymorphisms (SNPs) were included in the final analysis. Generalized linear modeling was conducted to look for smoking-by-SNP interaction on carotid IMT while controlling for age, sex, hypertension, diabetes, dyslipidemia, body mass index, waist-to-hip ratio, and the top 3 principal components estimated to capture ancestry by EIGENSTRAT. Ten SNPs near or within 5 genes showed an interactive effect with cigarette smoking on IMT with a p value &lt;1.0E-5. Among them, 3 SNPs (including 1 exonic splice enhancer SNP rs3751283, P=8.3E-7) are near or within regulator of chromosome condensation and BTB domain containing protein 1 (RCBTB1) gene on 13q14. Specifically, for SNP rs3751283, the mean IMT was substantially increased among CC-carriers (0.70 mm, 0.76 mm, 0.81 mm for 0, &lt;20, and ≥20 cigarette pack-years, respectively, P=2.6E-6), slightly increased with smoking pack-years among TC-carriers (0.72 mm, 0.74 mm, 0.75 mm for 0, &lt;20, and ≥20 cigarette pack-years, respectively, P=0.03), but very similar (0.73 mm) among TT-carriers for the three smoking groups (P=0.84). Conclusion: Our genome-wide interaction analysis reveals multiple genes, especially RCBTB1, that may modify the effect of smoking on carotid IMT. These genes will be further evaluated in our full dataset with additional genotyping. Also, larger independent studies are needed to validate these findings.

Abstract 1656: Genome wide identification of susceptibility loci in breast cancer survival

Abstract Background: Recently, many studies have been conducted to identify the susceptibility loci related with breast cancer risk, but few studies have examined the genetic variations for survival. Objectives &amp; Methods: To identify the susceptibility loci for breast cancer recurrence or all-cause of death, genome wide survival analysis were performed with 2,171 histologically confirmed incident breast cancer cases. For a genetic association study, DNA was genotyped using Affymetrix SNP Array 6.0 including about 0.9 million single nucleotide polymorphisms (SNPs). We examined the association between genetic variance and disease-free survival (DFS) and overall survival (OS) using Cox proportional hazard regression model adjusting for known prognostic factors. Results: During a median of 5.8 years of follow-up, 297 women recurred and 152 women died. Three SNPs in 2 genes (ARHGAP28 and LGI4) and four intergenic SNPs were identified for DFS (Padjusted &amp;lt;10−6) and five SNPs in 4 genes (CADPS, KCNH7, LGI4, and TGFBRAP1) and one intergenic SNP were associated with OS (Padjusted &amp;lt;10−6). Most significant associated SNP with DFS was located in ARHGAP28 (Padjusted =7.40 X 10−7) and this showed decreased risk of recurrence (aHR=0.6, 95% CI=0.50-0.74). SNP of CADPS was most significantly associated with OS (Padjusted = 9.04 X 10−7), and showed increased risk of all-cause of death (aHR=2.1, 95% CI=1.56-2.83). Conclusions: Our results suggest that the promising SNPs might associate with the breast cancer recurrence and survival in Korean women. We will confirm these findings in the replication stages further. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1656. doi:1538-7445.AM2012-1656

Common variants in RYR1 are associated with left ventricular hypertrophy assessed by electrocardiogram

To identify the genetic risk factors that influence the development of electrocardiographic (ECG) left ventricular hypertrophy (LVH), a major risk factor for cardiovascular (CV) morbidity and mortality. We performed a genomewide association study (GWAS) of ECG-LVH, in which the community-based Korea Association REsource (KARE) study (8432 controls and 398 cases) was analysed by Affymetrix SNP array 5.0. The GWAS results were validated in hospital-based samples (597 controls and 207 cases). Fourteen single-nucleotide polymorphisms (SNPs) in eight genetic loci (5q35.1, 6p22.3-22.1, 8q24.2, 11p15, 11q21-22.1, 14q12, 17q11.2, and 19q13.1) were associated with ECG-LVH in the original GWAS study (P < 1 × 10(-5)). Of these SNPs, 12 were genotyped in the hospital sample. There was consistent association with the 19q13.1 region which contains RYR1 gene. The most significant SNP in the region was rs10500279, which had genomewide significance in the combined GWAS/replication sample [odds ratio = 1.58 (confidence interval: 1.35-1.85), P = 1.0 × 10(-8)]. Mutations in RYR1, which encodes a major Ca(2+) channel in the skeletal muscle, have been reported to correlate with CV diseases. We performed the first GWAS for ECG-LVH, implicating the skeletal muscle Ca(2+) channel protein RYR1 as a genetic risk factor. These results might increase our understanding of the development of ECG-LVH.

Genome-wide molecular characterization of central nervous system primitive neuroectodermal tumor and pineoblastoma

Central nervous system primitive neuroectodermal tumor (CNS PNET) and pineoblastoma are highly malignant embryonal brain tumors with poor prognoses. Current therapies are based on the treatment of pediatric medulloblastoma, even though these tumors are distinct at both the anatomical and molecular level. CNS PNET and pineoblastoma have a worse clinical outcome than medulloblastoma; thus, improved therapies based on an understanding of the underlying biology of CNS PNET and pineoblastoma are needed. To this end, we characterized the genomic alterations of 36 pediatric CNS PNETs and 8 pineoblastomas using Affymetrix single nucleotide polymorphism arrays. Overall, the majority of CNS PNETs contained a greater degree of genomic imbalance than pineoblastomas, with gain of 19p (8 [27.6%] of 29), 2p (7 [24.1%] of 29), and 1q (6[20.7%] of 29) common events in primary CNS PNETs. Novel gene copy number alterations were identified and corroborated by Genomic Identification of Significant Targets In Cancer (GISTIC) analysis: gain of PCDHGA3, 5q31.3 in 62.1% of primary CNS PNETs and all primary pineoblastomas and FAM129A, 1q25 in 55.2% of primary CNS PNETs and 50% of primary pineoblastomas. Comparison of our GISTIC data with publically available data for medulloblastoma confirmed these CNS PNET-specific copy number alterations. With use of the collection of 5 primary and recurrent CNS PNET pairs, we found that gain of 2p21 was maintained at relapse in 80% of cases. Novel gene copy number losses included OR4C12, 11p11.12 in 48.2% of primary CNS PNETs and 50% of primary pineoblastomas. Loss of CDKN2A/B (9p21.3) was identified in 14% of primary CNS PNETs and was significantly associated with older age among children (P = .05). CADPS, 3p14.2 was lost in 27.6% of primary CNS PNETs and was associated with poor prognosis (P = .043). This genome-wide analysis revealed the marked molecular heterogeneity of CNS PNETs and enabled the identification of novel genes and clinical associations potentially involved in the pathogenesis of these tumors.

Differential Effects of MYH9 and APOL1 Risk Variants on FRMD3 Association with Diabetic ESRD in African Americans

Single nucleotide polymorphisms (SNPs) in MYH9 and APOL1 on chromosome 22 (c22) are powerfully associated with non-diabetic end-stage renal disease (ESRD) in African Americans (AAs). Many AAs diagnosed with type 2 diabetic nephropathy (T2DN) have non-diabetic kidney disease, potentially masking detection of DN genes. Therefore, genome-wide association analyses were performed using the Affymetrix SNP Array 6.0 in 966 AA with T2DN and 1,032 non-diabetic, non-nephropathy (NDNN) controls, with and without adjustment for c22 nephropathy risk variants. No associations were seen between FRMD3 SNPs and T2DN before adjusting for c22 variants. However, logistic regression analysis revealed seven FRMD3 SNPs significantly interacting with MYH9—a finding replicated in 640 additional AA T2DN cases and 683 NDNN controls. Contrasting all 1,592 T2DN cases with all 1,671 NDNN controls, FRMD3 SNPs appeared to interact with the MYH9 E1 haplotype (e.g., rs942280 interaction p-value = 9.3E−7 additive; odds ratio [OR] 0.67). FRMD3 alleles were associated with increased risk of T2DN only in subjects lacking two MYH9 E1 risk haplotypes (rs942280 OR = 1.28), not in MYH9 E1 risk allele homozygotes (rs942280 OR = 0.80; homogeneity p-value = 4.3E−4). Effects were weaker stratifying on APOL1. FRMD3 SNPS were associated with T2DN, not type 2 diabetes per se, comparing AAs with T2DN to those with diabetes lacking nephropathy. T2DN-associated FRMD3 SNPs were detectable in AAs only after accounting for MYH9, with differential effects for APOL1. These analyses reveal a role for FRMD3 in AA T2DN susceptibility and accounting for c22 nephropathy risk variants can assist in detecting DN susceptibility genes.