Lymphoma in Border Collies: Genome-Wide Association and Pedigree Analysis

Background: Prostate cancer (Pca) is the most common cancer among men in the U.S., and African American (AA) men have higher incidence compared to European American men. Environmental and sociocultural factors may play a role for increasing Pca risk among AA men, but the causal relationship of any environmental and social/cultural factors with Pca risk is not well demonstrated. On the other hand, there is strong evidence for genetic factors that explain increased incidence in AAs. Admixture mapping identified loci at 8q24 region showing association between African genetic ancestry and Pca risk, and a genome-wide association study (GWAS) in AAs identified a novel locus at 17q21 associated with Pca. However, replication of variants identified in GWAS among European and Asian populations has been difficult in AAs. Here, we performed population genetics analyses of Pca GWAS identified single nucleotide polymorphisms (SNPs) to evaluate whether these SNPs are informative of genetic ancestry and whether West African genetic Ancestry (WAA) is a Pca risk factor. Samples and Methods: We accessed National Human Genome Research Institute GWAS catalog in December, 2012, and there were 80 SNPs reported in 17 studies. We downloaded genotype data of 76 SNPs in 1000 Genomes (1KG) Project Phase I May 2011 and 62 SNPs in Human Genome Diversity Project (HGDP) from SPSmart. We performed principal component analysis using Golden Helix SVS 7. STRUCTURE was also used to estimate genetic ancestry and examine population clustering patterns. Replication study subjects, 470 AA men from Washington, DC (220 Pca cases and 250 controls) were genotyped as a part of GWAS in AAs with Illumina Infinium 1M. Logistic regression analysis was performed adjusting for age and 5 principal components (PCs). Results: Mean heterozygosity of 76 Pca GWAS SNPs in the 1KG Project dataset was lower in African populations than in European populations, possibly due to ascertainment bias. The majority of Pca GWAS SNPs had FST less than 0.20, but rs9623117 on chromosome 22 was highly differentiated (FST=0.63). In the 1KG Project dataset, PC1 separated African populations from non-African populations, and PC2 reflects variation in non-African populations separating East Asian from European populations. AA (ASW) individuals fell between the African and European clusters. Fewer Pca GWAS SNPs were genotyped in HGDP dataset, but they successfully captured global human genome variation forming African and non-African population clusters. In the STRUCTURE analysis with the 1KG project dataset, K=2 separated African from non-African populations, and K=3 separated European from East Asian populations. WAA estimated using 76 Pca GWAS SNPs was significantly correlated with WAA estimated using ancestry informative markers. Only four Pca GWAS SNPs were replicated and three of them were independently associated (P<0.05) in our replication samples. The number of risk alleles were positively associated with Pca risk (PTREND=0.002), and AAs carrying ≥5 risk alleles had 3.5 times greater odds of Pca (95% C.I.; 1.36-9.17; P=0.009) compared to AAs with ≤ 2 risk alleles. Risk allele frequencies of the three independently associated SNPs were higher in West Africans than in Europeans and was positively correlated with WAA estimates (PANOVA<0.001). Conclusion: Results of our analyses provide evidence suggesting that WAA is a risk factor for Pca. Population genetics analyses show that Pca GWAS SNPs can successfully capture global human genome variation and are informative of genetic ancestry. AAs with high WAA are likely to carry more Pca risk alleles than AAs with low WAA. Citation Format: Ken Batai, Ebony Shah, Rick A. Kittles. Population genetics analysis of prostate cancer GWAS SNPs to evaluate West African genetic ancestry as a risk factor. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B14. doi:10.1158/1538-7755.DISP13-B14

Maintaining genetic diversity in dog breeds is an important consideration for the management of inherited diseases. We evaluated genetic diversity in Border Collies using molecular and genealogical methods, and examined changes to genetic diversity when carriers for Trapped Neutrophil Syndrome (TNS) and Neuronal Ceroid Lipofuscinosis (NCL) are removed from the genotyped population. Genotype data for 255 Border Collies and a pedigree database of 83,996 Border Collies were used for analysis. Molecular estimates revealed a mean multi-locus heterozygosity (MLH) of 0.311 (SD 0.027), 20.79% of the genome consisted of runs of homozygosity (ROH ) > 1 Mb, effective population size (Ne) was 84.7, and mean inbreeding (F) was 0.052 (SD 0.083). For 227 genotyped Border Collies that had available pedigree information (GenoPed), molecular and pedigree estimates of diversity were compared. A reference population (dogs born between 2005 and 2015, inclusive; N = 13,523; RefPop) and their ancestors (N = 12,478) were used to evaluate the diversity of the population that are contributing to the current generation. The reference population had a Ne of 123.5, a mean F of 0.095 (SD 0.082), 2276 founders (f), 205.5 effective founders (fe), 28 effective ancestors (fa) and 10.65 (SD 2.82) founder genomes (Ng). Removing TNS and NCL carriers from the genotyped population had a small impact on diversity measures (ROH > 1 Mb, MLH, heterozygosity), however, there was a loss of > 10% minor allele frequency for 89 SNPs around the TNS mutation (maximum loss of 12.7%), and a loss of > 5% for 5 SNPs around the NCL mutation (maximum 5.18%). A common ancestor was identified for 38 TNS-affected dogs and 64 TNS carriers, and a different common ancestor was identified for 33 NCL-affected dogs and 28 carriers, with some overlap of prominent individuals between both pedigrees. Overall, Border Collies have a high level of genetic diversity compared to other breeds.

The quest for genes associated with different phenotypes and diseases is a central theme of research in human genetics. Several human phenotypes/diseases including height, myopia, diabetes, and others show complex pattern of inheritance where many genes together with environmental factors influence the intensity of a phenotype or disease. The genome-wide association study (GWAS) has been successful in mapping loci associated to variety of human traits and diseases. GWAS test for association of single nucleotide polymorphism (SNP) markers with a phenotype of interest at the genome-wide scale, this hence requires a severe multiple testing correction for statistical significance (p-value < 5 × 10-8). A single marker association approach has limited power in finding disease susceptibility genes especially in situations where the risk architecture of a gene is defined by many SNPs rather than one or two. This issue can be addressed through gene-based association approaches where the combined (or mean) statistics of a number of markers in a gene is tested for association with the trait of interest. Gene-based association approaches are established as a complementary approach to GWAS. It is well established that genes work in concert as molecular networks and cellular pathways to perform biological processes. Individual tests for association of a gene (or a SNP in a gene) with phenotype may have limited power in identifying interacting genes with small effects. SNP or gene-based tests are limited in how much they can reveal of the biological mechanism behind phenotypic variation. Pathway-based association approaches, where gene-based tests statistics are combined into gene sets and tested for association, have been developed to overcome these limitations. Each gene set represents a biological pathway or a process, based on prior biological knowledge. Various techniques have been proposed to perform pathway-based association tests on GWAS data, including ALIGATOR, MAGENTA, and INRICH. These packages show several limitations, which can be addressed by the development of a new pathway-based association approach. The aim of this thesis is to demonstrate the analytical approaches (GWAS and post-GWAS) to identify genes and pathways associated with complex ophthalmology traits and report methods for gene- and pathways-based analysis of GWAS summary data. Chapter 1 introduces the basic principles and strategies involved in GWAS analysis. Further, it extensively reviews the popular methods available for gene-based and pathway-based association tests. Chapter 2 describes an initial GWAS on corneal curvature, a phenotype of interest to diseases such as myopia and keratoconus, in Australians and further meta-analysis of two cohorts comprising of 1788 Australian twins and their families and 1013 individuals from a birth cohort from Western Australia. It also reports on replication in Australians of Northern European ancestry of the previously reported association of SNPs in PDGFRA and FRAP1 genes with corneal curvature in an Asian population. Chapter 3 is a demonstration of GWAS and pathway-based analysis. It reports the first GWAS and meta-analysis for corneal astigmatism in two Australian cohort studies, total sample size ~2,700. This chapter describes the application of Pathway-VEGAS, an extension of the gene-based analysis tool Versatile Gene-based Association Study (VEGAS) program for pathway-based analysis. Chapter 4 reports the successful application of VEGAS and Pathway-VEGAS to GWAS meta-analysis data. As part of the international glaucoma genetics consortium (IGGC), I participated in genetic analysis of the vertical cup disc ratio (VCDR) phenotype. This manuscript describes the meta-analysis of GWAS on a discovery sample of 21,094 individuals from ten cohorts of northern European ancestry and a replication sample of 6,784 individuals from four Asian cohorts. Gene-based and pathway-based tests were performed using the VEGAS and Pathway-VEGAS programs separately for northern European ancestry samples and Asian ancestry samples, and respective results were meta-analysed. This chapter demonstrates the advantages of using different approaches such as single marker GWAS, gene-based association approach and pathway based association approach. Chapter 5 presents the VEGAS2 software. VEGAS is one of the most popular gene-based association software. VEGAS however has some limitations such as the inability to perform a gene-based tests on the X chromosome, dependence on HapMap2 data to model the correlation between SNPs and inflexibility in the selection of gene boundary. The VEGAS2 software is an extension of VEGAS, redeveloped and upgraded to overcome these limitations. Chapter 6 presents the VEGAS2Pathway approach for pathway analysis of GWAS summary data. This chapter describes the shortcomings of many popular pathway-based association approaches, and how VEGAS2-Pathway overcomes these limitations. Further it demonstrates the application of VEGAS2Pathway on the endometriosis GWAS summary data. The last chapter provides the contributions this thesis makes to the literature and discusses its implications, limitations and future directions. In conclusion, my thesis provides the methodological and analytical approaches to further our knowledge in human genetics.

Domestic dogs can suffer from hearing losses that can have profound impacts on working ability and quality of life. We have identified a type of adult-onset hearing loss in Border Collies that appears to have a genetic cause, with an earlier age of onset (3–5 years) than typically expected for aging dogs (8–10 years). Studying this complex trait within pure breeds of dog may greatly increase our ability to identify genomic regions associated with risk of hearing impairment in dogs and in humans. We performed a genome-wide association study (GWAS) to detect loci underlying adult-onset deafness in a sample of 20 affected and 28 control Border Collies. We identified a region on canine chromosome 6 that demonstrates extended support for association surrounding SNP Chr6.25819273 (p-value = 1.09×10−13). To further localize disease-associated variants, targeted next-generation sequencing (NGS) of one affected and two unaffected dogs was performed. Through additional validation based on targeted genotyping of additional cases (n = 23 total) and controls (n = 101 total) and an independent replication cohort of 16 cases and 265 controls, we identified variants in USP31 that were strongly associated with adult-onset deafness in Border Collies, suggesting the involvement of the NF-κB pathway. We found additional support for involvement of RBBP6, which is critical for cochlear development. These findings highlight the utility of GWAS–guided fine-mapping of genetic loci using targeted NGS to study hereditary disorders of the domestic dog that may be analogous to human disorders.

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case-control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST ) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2Mb) to highly significant regions identified by GWAS and FST analyses. Moreover, one candidate marker identified by GWAS and FST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome-wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome-wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.

Endocrine therapy, with SERMs and AIs, is the most important treatment modality for the 70% of patients with ER+ early breast cancer. Clinically, there is marked variability between patients in response to treatment and adverse events (AEs) such as musculoskeletal (MS) AEs with AIs. In 649 women with early-stage breast cancer we identified large inter-individual variations in pretreatment and on-anastrozole (A) plasma estrogens as well as plasma A concentrations, suggesting that the approved A dose of 1 mg per day may not be optimal for all patients. We performed a series of genome-wide association studies (GWAS) and identified a genome-wide significant variant SNP associated with concentrations of E2 that created an estrogen response element (ERE), and a significant SNP associated with E1-conjugates, providing potential insights into the variability. Pharmacogenomics (PGx) is the study of the role of germline and somatic genetic variation in individual variability in drug response phenotypes, i.e., disease response and AEs. The scientific goal is to understand mechanisms for the phenotype and the clinical goal is the determination of the right drug at the right dose for the right patient. The Mayo PGx Research Network Center and Breast SPORE and the RIKEN Center for Integrative Medical Science have worked collaboratively with cooperative groups to perform GWAS in women treated with both SERMs and AIs. The PGx paradigm consists of the GWAS as the initial step in a process that goes beyond the identification of associations to study the relationship of the single nucleotide polymorphisms (SNPs) to genes and the relationships of these SNPs and genes to the drug effect and the phenotype under study. Using the phenotype of AI-related MS-AEs, the major reason women stop therapy, a case-control GWAS was performed with patients from MA.27. The GWAS identified a SNP on chromosome (Chr) 14 that was associated with MS-AEs, near a gene (TCL1A), and created an ERE. Importantly, TCL1A expression was related to expression of multiple cytokine receptors, NFκB, and chemokines (related to rheumatoid arthritis) in an E2- and SNP-dependent fashion. These results provide a pharmacogenomic basis for MS-AEs with AIs. Using the phenotype of development of breast cancer in high-risk women receiving SERMs, a case-control GWAS was performed with patients entered on the NSABP P-1 and P-2 trials. The GWAS revealed variant SNPs on Chr 4 near CTSO (deleterious) and Chr 16 in ZNF423 (protective). The OR for differences in risk of breast cancer for participant homozygous for both protective or both deleterious alleles was 5.71. Both CTSO and ZNF423 were shown to participate in E2-dependent induction of BRCA1 expression in a SNP-dependent fashion. Most remarkable was that the presence of a SERM reversed the E2-inducible expression of ZNF423 and BRCA1 in a SNP-dependent fashion. In addition, ZNF423 was shown to be an E2-inducible BRCA1 transcription factor. The deleterious variant SNP near CTSO was found to disrupt an ERE. The GWAS described led to functional genomic studies that produced new knowledge relating to endocrine biology that provide a focus for further research to move towards precision endocrine therapy for women with breast cancer. Citation Format: James N. Ingle. Pharmacogenomics in the Quest for Precision Endocrine Therapy of Breast Cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr ML-1.

Imerslund-Gräsbeck syndrome (IGS) or selective cobalamin malabsorption has been described in humans and dogs. IGS occurs in Border Collies and is inherited as a monogenic autosomal recessive trait in this breed. Using 7 IGS cases and 7 non-affected controls we mapped the causative mutation by genome-wide association and homozygosity mapping to a 3.53 Mb interval on chromosome 2. We re-sequenced the genome of one affected dog at ∼10× coverage and detected 17 non-synonymous variants in the critical interval. Two of these non-synonymous variants were in the cubilin gene (CUBN), which is known to play an essential role in cobalamin uptake from the ileum. We tested these two CUBN variants for association with IGS in larger cohorts of dogs and found that only one of them was perfectly associated with the phenotype. This variant, a single base pair deletion (c.8392delC), is predicted to cause a frameshift and premature stop codon in the CUBN gene. The resulting mutant open reading frame is 821 codons shorter than the wildtype open reading frame (p.Q2798Rfs*3). Interestingly, we observed an additional nonsense mutation in the MRC1 gene encoding the mannose receptor, C type 1, which was in perfect linkage disequilibrium with the CUBN frameshift mutation. Based on our genetic data and the known role of CUBN for cobalamin uptake we conclude that the identified CUBN frameshift mutation is most likely causative for IGS in Border Collies.

There is a lack of data on idiopathic epilepsy (IE) in Border Collies (BCs) in the veterinary literature. Genetic epilepsy occurs in BCs and is frequently characterized by a severe clinical course and poor response to medical treatment. Forty-nine BCs diagnosed with IE. Medical records, seizure data, treatment data, and pedigree information of affected dogs were collected. Cases were classified phenotypically as affected or not affected; mild, moderate, or severe clinical course; active epilepsy (AE) or remission; and drug resistant or not drug resistant. Clinical manifestations were classified as having a moderate (33%) or severe clinical course (49%), characterized by a high prevalence of cluster seizures and status epilepticus. Survival time was significantly decreased in dogs < 2 years of age at seizure onset, and in dogs with a severe clinical course. Drug resistance was apparent in 71% of 24 dogs treated with > 2 antiepileptic drugs. The epilepsy remission rate was 18%. Median age at onset was significantly higher and initial seizure frequency was significantly lower in dogs with remission compared with dogs with AE. Pedigree analyses indicated a strong genetic founder effect in the appearance of epilepsy, resembling autosomal recessive inheritance. The present study confirms the occurrence of genetically mediated epilepsy with a frequent severe clinical course and drug resistance in BCs. The results provide information about the long-term prognosis of IE in BCs for veterinarians and concerned owners, and may benefit breeders as well.

THU0002 Fine mapping and expression studies of the 12Q13-14 locus associated with rheumatoid arthritis

The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that applying individual association tests can be problematic because these tests may suffer from power loss in detecting significant associations between diseases and single-nucleotide polymorphism or copy number variant. We propose here a two-stage procedure wherein we first apply an overall chi-square test for multiple diseases with SCs; if the overall test is rejected, then individual tests using the chi-square partition method will be applied to each disease against SCs. A real GWAS data set with SCs and a Monte Carlo simulation study are used to demonstrate that the proposed method is more effective and preferable than other existing methods for analyzing data from GWASs with multiple diseases and SCs.

Characterizing Canine Lymphoma As a Potential Large Animal Model of Human Diffuse Large B-Cell Lymphoma

Common rust is one of the major foliar diseases in maize, leading to significant grain yield losses and poor grain quality. To dissect the genetic architecture of common rust resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid (DH) population, DH1, were used to perform GWAS and linkage mapping analyses. The GWAS results revealed six single-nucleotide polymorphisms (SNPs) significantly associated with quantitative resistance of common rust at a very stringent threshold of P-value 3.70 × 10–6 at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04. Linkage mapping identified five quantitative trait loci (QTL) at bins 1.03, 2.06, 4.08, 7.03, and 9.00. The phenotypic variation explained (PVE) value of each QTL ranged from 5.40 to 12.45%, accounting for the total PVE value of 40.67%. Joint GWAS and linkage mapping analyses identified a stable genomic region located at bin 4.08. Five significant SNPs were only identified by GWAS, and four QTL were only detected by linkage mapping. The significantly associated SNP of S10_95231291 detected in the GWAS analysis was first reported. The linkage mapping analysis detected two new QTL on chromosomes 7 and 10. The major QTL on chromosome 7 in the region between 144,567,253 and 149,717,562 bp had the largest PVE value of 12.45%. Four candidate genes of GRMZM2G328500, GRMZM2G162250, GRMZM2G114893, and GRMZM2G138949 were identified, which played important roles in the response of stress resilience and the regulation of plant growth and development. Genomic prediction (GP) accuracies observed in the GWAS panel and DH1 population were 0.61 and 0.51, respectively. This study provided new insight into the genetic architecture of quantitative resistance of common rust. In tropical maize, common rust could be improved by pyramiding the new sources of quantitative resistance through marker-assisted selection (MAS) or genomic selection (GS), rather than the implementation of MAS for the single dominant race-specific resistance gene.

BackgroundPart of the missing heritability in Genome Wide Association Studies (GWAS) is expected to be explained by interactions between genetic variants, also called epistasis. Various statistical methods have been developed to detect epistasis in case-control GWAS. These methods face major statistical challenges due to the number of tests required, the complexity of the Linkage Disequilibrium (LD) structure, and the lack of consensus regarding the definition of epistasis. Their limited impact in terms of uncovering new biological knowledge might be explained in part by the limited amount of experimental data available to validate their statistical performances in a realistic GWAS context. In this paper, we introduce a simulation pipeline for generating real scale GWAS data, including epistasis and realistic LD structure. We evaluate five exhaustive bivariate interaction methods, fastepi, GBOOST, SHEsisEpi, DSS, and IndOR. Two hundred thirty four different disease scenarios are considered in extensive simulations. We report the performances of each method in terms of false positive rate control, power, area under the ROC curve (AUC), and computation time using a GPU. Finally we compare the result of each methods on a real GWAS of type 2 diabetes from the Welcome Trust Case Control Consortium.ResultsGBOOST, SHEsisEpi and DSS allow a satisfactory control of the false positive rate. fastepi and IndOR present an increase in false positive rate in presence of LD between causal SNPs, with our definition of epistasis. DSS performs best in terms of power and AUC in most scenarios with no or weak LD between causal SNPs. All methods can exhaustively analyze a GWAS with 6.105 SNPs and 15,000 samples in a couple of hours using a GPU.ConclusionThis study confirms that computation time is no longer a limiting factor for performing an exhaustive search of epistasis in large GWAS. For this task, using DSS on SNP pairs with limited LD seems to be a good strategy to achieve the best statistical performance. A combination approach using both DSS and GBOOST is supported by the simulation results and the analysis of the WTCCC dataset demonstrated that this approach can detect distinct genes in epistasis. Finally, weak epistasis between common variants will be detectable with existing methods when GWAS of a few tens of thousands cases and controls are available.

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

Common genetic variation and risk of gallbladder cancer in India: a case-control genome-wide association study