Embracing diversity: a genetic marker dataset with increased marker density facilitates association studies in maize

Assessing causal relationship between non-alcoholic fatty liver disease and risk of atrial fibrillation

1 Background: Currently genome-wide association studies (GWAS) have identified over 100 prostate cancer (PrCa) susceptibility loci, capturing 33% of the PrCa familial relative risk (FRR) in Europeans. To identify further susceptibility variants, we conducted a PrCa GWAS, larger than previous studies, comprising ~49,000 cases and ~29,000 controls among individuals of European and Asian descent using the OncoArray, a platform consisting of a 260K GWAS backbone and 310K custom content selected from previous GWAS and fine-mapping studies of multiple cancers ( http://epi.grants.cancer.gov/oncoarray/ ). Methods: Genotypes from the OncoArray were used to impute genotypes from ~70M variants using the October 2014 release of the 1000 genomes project as a reference, and then combined with several previous PrCa GWAS of European ancestry: UK stage 1 (1,906 cases/1,934 controls) and stage 2 (3,888 cases/3,956 controls); CaPS 1 (498 cases/502 controls) and CaPS 2 (1,483 cases/519 controls); BPC3 (2,137 cases/3,101 controls); NCI PEGASUS (4,622 cases/2,954 controls); and iCOGS (21,209 cases/ 20,440 controls). Risk analyses for overall PrCa risk, aggressive PrCa (several definitions defined by PrCa clinical characteristics), and Gleason score were performed. Logistic and linear regression summary statistics were meta-analysed using an inverse variance fixed effect approach. Results: We identified novel loci significantly associated ( P < 5.0x10-8) with overall PrCa (N = 65). Our novel findings are comprised of several missense variants, including a SNP in the ATM gene - a key member of the DNA repair pathway. When combined multiplicatively, the 65 novel PrCa loci identified here increases the captured heritability of PrCa, explaining 38.5% of the FRR when combining novel and previously identified PrCa loci. Conclusions: In risk stratification, men in the top 1% of the genetic risk score group have a relative risk of 5.6 fold for developing PrCa compared with the median risk group. These results will improve the utility of genetic risk scores for targeted screening and prevention for prostate cancer.

Genome-Wide Association Studies Go Green: Novel and Cost-Effective Opportunities for Identifying Genetic Associations

The contribution of genetics to stroke risk, and whether this differs for different stroke subtypes, remainsuncertain. Genomewide complex trait analysis allows heritability to be assessed from genomewide association study (GWAS) data. Previous candidate gene studies have identified many associations with stoke but whether these are important requires replication in large independent data sets. GWAS data sets provide a powerful resource to perform replication studies. We applied genomewide complex trait analysis to a GWAS data set of 3752 ischemic strokes and 5972 controls and determined heritability for all ischemic stroke and the most common subtypes: large-vessel disease, small-vessel disease, and cardioembolic stroke. By systematic review we identified previous candidate gene and GWAS associations with stroke and previous GWAS associations with related cardiovascular phenotypes (myocardial infarction, atrial fibrillation, and carotid intima-media thickness). Fifty associations were identified. For all ischemic stroke, heritability was 37.9%. Heritability varied markedly by stroke subtype being 40.3% for large-vessel disease and 32.6% for cardioembolic but lower for small-vessel disease (16.1%). No previously reported candidate gene was significant after rigorous correction for multiple testing. In contrast, 3 loci from related cardiovascular GWAS studies were significant: PHACTR1 in large-vessel disease (P=2.63e(-6)), PITX2 in cardioembolic stroke (P=4.78e(-8)), and ZFHX3 in cardioembolic stroke (P=5.50e(-7)). There is substantial heritability for ischemic stroke, but this varies for different stroke subtypes. Previous candidate gene associations contribute little to this heritability, but GWAS studies in related cardiovascular phenotypes are identifying robust associations. The heritability data, and data from GWAS, suggest detecting additional associations will depend on careful stroke subtyping.

Colorectal cancer (CRC) is the second most common cancer in Hong Kong. While high-penetrance germline mutations account for up to 6% of cases, much of the variation in genetic risk may be attributable to multiple low-penetrance variants. Previous genome wide association studies (GWAS) have identified a number of CRC susceptibility alleles in Caucasian populations. Our GWAS investigated the association between genetic variants with CRC risk in the Han Chinese population in Hong Kong. In Stage I, genomic DNA samples from 455 female Chinese CRC subjects were genotyped using the Illumina 610 Quad SNP chip. Association analysis was performed on 439 cases and 771 general population female controls recruited for a study on bone mineral density. Population stratification was examined through principal components analysis using EIGENSTRAT version 2.0. From the association results, 46 SNPs (Group 1) were selected for follow-up replication (Stage II), together with 10 SNPs (Group 2) from previous GWAS studies. Genomic DNA samples from 3,571 Chinese subjects were genotyped using Sequenom MassARRAY system. Association analysis was performed on 1,505 cases and 1,452 controls. 5 SNPs (rs835378, rs2652007, rs2139273, rs2139273 and rs9286410) exceeded the genome-wide significance level in stage I, although none replicated in Stage 2, suggesting genotyping error. Results from stage II showed that the three most significant SNP were among those selected from the previous studies, yet their significance levels in Stage I were very weak . None of the SNPs selected from Stage I was significant at p<0.01 in Stage 2. Two composite scores of genetic susceptibility, one for each group of SNPs, were calculated in stage II genotype data, as the total number of high-risk alleles (according to the direction of effect in Stage I results or previous GWAS) present in an individual. Both composite scores were significantly associated with CRC risk in Stage 2 (Group 1, p=2.38 x 10-5, beta=0.046, SE=0.012; Group 2 p=1.06 x 10-7, beta=0.10, SE=0.019), suggesting that while we had insufficient power to confirm individual SNPs identified in our GWAS and the previous GWAS, these findings indicate that the SNP sets selected from Stage I results, as well as those selected from previous GWAS, contain SNPs with genuine effects on CRC risk. One SNP, rs10795668 (OR = 0.79 [CI] 95%:0.71 – 0.87 p=3.78 x 10-6), was significantly associated with CRC risk in Stage II after adjustment for multiple testing. Two further SNPs, rs6983267 and rs4939827, also achieved suggestive p-values in Stage II. All these SNPs were selected from previous GWAS in the Caucasian population, demonstrating that shared genetic factors operate for CRC in diverse populations.

Maize (Zea mays ssp. mays) is genetically diverse, yet it is also morphologically distinct from its wild relatives. These two observations are somewhat contradictory: the first observation is consistent with a large historical population size for maize, but the latter observation is consistent with strong, diversity-limiting selection during maize domestication. In this study, we sampled sequence diversity, coupled with simulations of the coalescent process, to study the dynamics of a population bottleneck during the domestication of maize. To do this, we determined the DNA sequence of a 1,400-bp region of the Adh1 locus from 19 individuals representing maize, its presumed progenitor (Z. mays ssp. parviglumis), and a more distant relative (Zea luxurians). The sequence data were used to guide coalescent simulations of population bottlenecks associated with domestication. Our study confirms high genetic diversity in maize-maize contains 75% of the variation found in its progenitor and is more diverse than its wild relative, Z. luxurians-but it also suggests that sequence diversity in maize can be explained by a bottleneck of short duration and very small size. For example, the breadth of genetic diversity in maize is consistent with a founding population of only 20 individuals when the domestication event is 10 generations in length.

Are there any novel genetic markers of susceptibility to polycystic ovary syndrome (PCOS)? We identified a novel susceptibility locus on chromosome 8q24.2 and several moderately associated loci for PCOS in Korean women. PCOS is a highly complex disorder with significant contributions from both genetic and environmental factors. Previous genome-wide association studies (GWAS) in the Han Chinese population identified several risk loci for PCOS. However, GWAS studies on PCOS remain very few. The aim of this study was to identify novel markers of susceptibility to PCOS through GWAS. A two-stage GWAS was conducted. The initial discovery set for GWAS consisted of 976 PCOS cases and 946 controls. The second stage (replication study) included 249 PCOS cases and 778 controls. Patients were diagnosed according to the Rotterdam criteria. Genomic DNAs were genotyped using the HumanOmni1-Quad v1 array. In the replication stage, the 21 most promising signals selected from the discovery stage were tested for their association with PCOS. One novel locus with genome-wide significance and seven moderately associated loci for PCOS were identified. The strongest association was on chromosome 8q24.2 (rs10505648, OR = 0.52, P = 5.46 × 10(-8)), and other association signals were located at 4q35.2, 16p13.3, 4p12, 3q26.33, 9q21.32, 11p13 and 1p22 (P = 5.72 × 10(-6)-6.43 × 10(-5)). The strongest signal was located upstream of KHDRBS3, which is associated with telomerase activity, and could drive PCOS and related phenotypes. The limitation of our study is the modest sample size used in the replication cohort. The limited sample size may contribute to a lack of statistical power to detect an association or show a trend in severity. Our findings provide new insight into the genetics and biological pathways of PCOS and could contribute to the early diagnosis and prevention of metabolic and reproductive morbidities. This work was supported in part by the grant from the Korea Centers for Disease Control and Prevention (2009-E00591-00). The work was also supported by the Ewha Global Top5 Grant 2013 of Ewha Womans University. None of the authors has any conflict of interest to declare.

BackgroundFeed intake and growth are economically important traits in swine production. Previous genome wide association studies (GWAS) have utilized average daily gain or daily feed intake to identify regions that impact growth and feed intake across time. The use of longitudinal models in GWAS studies, such as random regression, allows for SNPs having a heterogeneous effect across the trajectory to be characterized. The objective of this study is therefore to conduct a single step GWAS (ssGWAS) on the animal polynomial coefficients for feed intake and growth.ResultsCorrected daily feed intake (DFIAdj) and average daily weight measurements (DBWAvg) on 8981 (n = 525,240 observations) and 5643 (n = 283,607 observations) animals were utilized in a random regression model using Legendre polynomials (order = 2) and a relationship matrix that included genotyped and un-genotyped animals. A ssGWAS was conducted on the animal polynomials coefficients (intercept, linear and quadratic) for animals with genotypes (DFIAdj: n = 855; DBWAvg: n = 590). Regions were characterized based on the variance of 10-SNP sliding windows GEBV (WGEBV). A bootstrap analysis (n =1000) was conducted to declare significance. Heritability estimates for the traits trajectory ranged from 0.34-0.52 to 0.07-0.23 for DBWAvg and DFIAdj, respectively. Genetic correlations across age classes were large and positive for both DBWAvg and DFIAdj, albeit age classes at the beginning had a small to moderate genetic correlation with age classes towards the end of the trajectory for both traits. The WGEBV variance explained by significant regions (P < 0.001) for each polynomial coefficient ranged from 0.2-0.9 to 0.3-1.01 % for DBWAvg and DFIAdj, respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95 % for DBWAvg and DFIAdj. Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior.ConclusionsWe have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBWAvg and DFIAdj. These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0218-8) contains supplementary material, which is available to authorized users.

Systematic review of genome-wide association studies of abdominal aortic aneurysm

The two main hormonal events of a woman's life, menarche and menopause, have a paramount impact on the duration of exposure to estrogen. Reproductive aging phenotypes, including age at menarche (AM) and age at natural menopause (ANM) have been consistently associated with breast cancer risk. Despite an estimated strong genetic component, genome-wide association studies (GWAS) for AM and ANM found that common variants identified to date account for only 7.4% for SNPs related to AM and 2.5-4.1% for ANM. As most previous GWAS on AM and ANM were conducted in women of European ancestry (EA), studies examining genetic components of reproductive aging in African-American (AA) women are needed. We hypothesize that although the index GWAS variants discovered in EA women may differ from those in AA women, rare and low-frequency causal variants may reside in the same genetic regions. A candidate analysis of previously identified GWAS variants and genes in association with AM, ANM was conducted in the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. All SNPs within a 500kb window of previously discovered GWAS SNPs for AM and ANM were extracted from the Illumina Human Exome Beadchip v1.1, leading to 1,505 candidate SNPs from 125 genes for AM and 1,198 candidate SNPs from 35 genes for ANM in a total of 7,886 AA subjects. Single SNP association tests were run in PLINK using linear regressions for the continuous trend test for AM/ANM and logistic regression for the extreme AM phenotype (&amp;lt;11 v. &amp;gt;=≥15 years). The SKAT-O test for the gene-based analyses was performed using the SKAT R package to aggregate variants with an MAF upper bound of 5%. The top variants related to AM were two SNPs, rs314277 (β=0.11, MAF= 0.45, p=6.24E-05) and rs4742314 (β= -0.11, MAF= 0.39, p=6.44E-05), located in LIN28B and KDM4C respectively. rs974828 (RORA, MAF= 0.23, OR=0.71, p=0.0003) and rs314277 (p=0.0007) were found to be the top variants in association with the extreme AM phenotype. For ANM, rs16991615, located in MCM8, was the most significant variant associated with increased ANM ((β=2.06, MAF= 0.01, p=0.0005). rs314277 (LIN28B) has been previously associated with AM, and rs16991615 (MCM8) had also been related to ANM in previous GWAS in EAs. In gene-based analysis for AM, SLC38A3 (p=0.0007) and WDR6 (p= 0.003) were nominally significant; and EPS8L1 (p= 0.005) and RBM6 (p= 0.01) were associated with the AM phenotype. For ANM, RBMS2 (p= 0.006) was nominally significant in gene-based analysis. This is to date the largest study in AA women for reproductive life events to interrogate rare and low-frequency variants, which are beyond the spectrum of common variants in previous GWAS. Although the overall replication success rate is low, our analyses identified several rare and low-frequency variants in regions from previous GWAS. Our data contributed to the literature on genetic variation for reproductive aging in AA women. Citation Format: Marie V. Coignet, Qianqian Zhu, David G. Cox, Kathryn Lunetta, Elisa V. Bandera, Christopher Haiman, Andrew Olshan, Julie Palmer, Christine Ambrosone, Song Yao. Single variant and gene-based replication analysis of reproductive aging in African American women in the AMBER Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 226.

CN04-02: Interrogating the heritable genome to achieve the goal of personalized cancer therapeutics.

Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.

Background: Genetic predisposition to docetaxel (Doc) toxicity contributes to unacceptable toxicity and reduced dose intensity, and may influence disease outcomes. We previously reported variants associated with Doc toxicity in candidate gene single nucleotide polymorphism (SNP) associations in a breast cancer treatment setting (Damaraju et al. Eur J Cancer (suppl); Vol 8 (7), page 175, 2010) and the identified variants were confirmed in an independent validation study (Damaraju et al, J Clin Oncol Vol 33, Issue 15 suppl, 2015: 540). Others have reported candidate SNP (Breast Cancer Res Treat, 2011 SWOG 0221 study) and GWAS (Clin Cancer Res 2012 CALGB 40101 study) identified variants associated with paclitaxel mediated peripheral neuropathy. However, the overlap on the variants identified thus far between Doc and paclitaxel are limited, prompting a genome wide search to find variants contributing to Doc specific toxicity. Methods: TRIO-012 is a double blinded, multinational trial that randomized 1,144 patients with advanced breast cancer to receive first-line Doc in combination with ramucirumab (RAM) or placebo (Mackey et al. J Clin Oncol Jan 10, 2015:141-148). Study subjects (n=719) in the Doc+RAM or Doc+placebo arm with available germline DNA are being genotyped; all subjects provided ethics-committee approved prospective consent for this genetic study. Genotyping are being performed with Affymetrix SNP 6.0 arrays. Genotype data will be filtered for deviations from Hardy Weinberg Equilibrium and minor allele frequency of &amp;gt;0.05. Doc-induced adverse events (AEs) are based on CTCAE (Common Terminology Criteria for Adverse Events v4.1) toxicity grades. Toxicities &amp;gt;2 scored for fatigue (n=96), myalgia (n=22), peripheral neuropathy (n=17) will be analysed as individual phenotypes in comparison with the no toxicity group (toxicity grades 0-1) and in a combined analysis of all Doc induced toxicities (0-1, n=599 vs. &amp;gt;2, n=120). Dominant genotypic model is assumed; Chi-square test, FDR and/or 10000 permutations were employed using SVS v8.3 and p&amp;lt;0.05 considered statistically significant. We will identify population stratification using EIGENSTRAT method and will correct the association statistics using the Eigenvectors along with age and BMI as covariates. Fine mapping of the identified loci will be attempted using imputation tools. We will interrogate the data for cumulative dose to toxicity and correlate SNPs identified with survival outcomes. Results and conclusions: We expect to reconfirm the associations of loci reported in candidate SNP and previous GWAS studies; XKR4 (rs4737264) for peripheral neuropathy, CYP3A5*3 (rs776746) with fatigue, and FACND2 (rs7637888) with myalgia in addition to the potential novel variants distinct from paclitaxel AE GWAS studies. Fine mapping around these loci may help identify potential causal variants. Both candidate SNP and GWAS identified variants may aid in developing risk stratification models. The GWAS identified loci and the flanking genes will be interrogated using the ingenuity pathway analysis for insights in to the biological roles in the drug metabolism. We expect to complete the analysis by mid-November 2015. Citation Format: Damaraju S, Gorbunova V, Gelmon K, García-Saenz J, Morales-Murillo S, AbiGerges D, Canon J-L, Kiselev I, Cohen GL, Jerusalem G, Thireau F, Fresco R, Houé V, Press MF, Kumaran M, Mackey JR. Genome wide association study (GWAS) of genetic variants associated with docetaxel toxicity in the ROSE/TRIO-012 trial. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-13-03.

Background: There have been large Genome Wide Association Studies (GWAS) on breast cancer in most developed countries showing low to modest associations between common polymorphisms and breast cancer risk. In India, however, there have been no GWAS studies and few properly designed retrospective studies with smaller sample size on genetic susceptibility to study this risk. Methodology: DNA was extracted from buffy coat samples in 1204 cases and 1212 control. A customized panel of 384 SNPs was designed using a mixture of 3 strategies such as SNPs selected from GWAS, SNPs selected from Candidate Studies and SNPs selected using Bioinformatics tool. Genotyping was performed on the Illumina Hi-Scan using GoldenGate Genotyping (GGGT) Custom SNP Panel assay on all DNA samples extracted. The reproducibility rate of all the replicate samples (n = 160) for all the assays was 99% and above. Unconditional logistic regression (additive model) was used to estimate OR and corresponding 95% CI between genotypes and case status. This abstract focuses on replicating SNPs in Indian population which have shown to be associated in already conducted GWAS mostly in developed nations. Results: Seven SNPs were replicated from previous studies on BC GWAS. Prevalence of certain SNPs in the present study varied with that observed in GWAS. Out of 40 SNPs which did not show an association with BC, 15 SNPs had a MAF below 20% and 25 SNPs had prevalence of 20% and above. The risk of SNPs which were significantly identified in BC GWAS and in present study were also studied in BCs stratified on hormone receptor status. The SNP rs2046210 in ESR1 showed an increased risk for BCs which were ER-/PR- and triple negative but not ER+/PR+. The SNPs rs10411161 in Zinc Finger Protein 577 (ZNF577) gene showed significant protection in the development of only ER+/PR+ BCs whereas SNPs in FGFR2 (rs2981575, rs2981582), Mitogen-Activated Kinase Kinase Kinase 1 (MAP3K1) (rs889312) and 9q31.2 (rs865686) increased the risk of hormone receptor positive BC. Discussion: SNPs selected from FGFR2 gene were positively associated with BC. 25 SNPs which were identified as a risk factor for BC in the GWAS conducted in other populations did not replicate in the Indian population, even though their prevalence was high (≥ 20%) indicating that they may not be a risk factor in Indian population. The 3 SNPs which were highly prevalent in GWAS population could not be replicated even if they were associated the attributable risk of the SNPs remains low due to their low prevalence in the present study population. The SNPs associated with ER+/PR+ and ER-/PR- BCs were observed to be different suggesting that the cancer stratified on hormone receptor status may differ due to different biological pathways. Citation Format: Rajini T. Nagrani, Sharayu Sitaram Mhatre, Rajendra Badwe, Rajesh Dikshit. Replicating GWAS SNPs for breast cancer in Indian population. [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 2795. doi:10.1158/1538-7445.AM2015-2795

Background Gliomas, the most common malignant primary brain tumors in adults, typically have a poor prognosis irrespective of medical care. Previous large genome-wide association studies (GWAS) have identified 27 single-nucleotide variants (SNVs) that are significantly associated with glioma. However, most of the GWAS are conducted by case-control study designs, it is therefore prone to bias when rapidly lethal cases don’t have chance to be included in the study. This study aims to replicate the previous GWAS findings using prospective study design. Material and Methods We conducted a nested case-control study within the European Prospective Investigation into Cancer (EPIC) cohort from 7 European countries. GSA-MD Infinium global screening array was used for genotyping. Some subjects were genotyped by other platforms previously. In total, 468 glioma patients and 481 controls were included. The genotypes of 27 SNVs were extracted and for ungenotyped SNVs, datasets were imputed using SHAPEIT v4.1.3 and IMPUTE5 v1.1.5 based on the Haplotype Reference Consortium (Release 1.1) reference panel. Conditional logistic regression model was used to investigate the additive effect of SNVs on the risk of glioma. Results 21 SNVs showed a consistent direction of effect with previous studies, whereas 6 SNVs did not (ORs between 0.72-0.99 and not significant). After adjusting for multiple testing, two SNVs, rs10069690 (TERT), and rs75061358 (near EGFR) were significantly associated with glioma risk. We observed that prominent OR (2.23, 95%CI=1.49-3.33) of rs75061358 in our study compared to the result from previous GWAS, which implied rs75061358 might be not only a risk factor but also affect survival. Different risk direction was observed for rs77633900 in ETFA gene (OR=0.72, 95%CI=0.51-1.01). Conclusion Our findings further confirmed the genetic role on the etiology of glioma in the European population. The potential biases from the previous GWAS are required to be elucidated.