Genome-Wide Association Study Identifies Major Loci for Carcass Weight on BTA14 in Hanwoo (Korean Cattle)

This genome-wide association study (GWAS) was conducted to identify major loci that are significantly associated with carcass weight, and their effects, in order to provide increased understanding of the genetic architecture of carcass weight in Hanwoo. This genome-wide association study identified one major chromosome region ranging from 23 Mb to 25 Mb on chromosome 14 as being associated with carcass weight in Hanwoo. Significant Bonferroni-corrected genome-wide associations (P<1.52×10⁻⁶) were detected for 6 Single Nucleotide Polymorphic (SNP) loci for carcass weight on chromosome 14. The most significant SNP was BTB-01280026 (P = 4.02×10⁻¹¹), located in the 25 Mb region on Bos taurus autosome 14 (BTA14). The other 5 significant SNPs were Hapmap27934-BTC-065223 (P = 4.04×10⁻¹¹) in 25.2 Mb, BTB-01143580 (P = 6.35×10⁻¹¹) in 24.3 Mb, Hapmap30932-BTC-011225 (P = 5.92×10⁻¹⁰) in 24.8 Mb, Hapmap27112-BTC-063342 (P = 5.18×10⁻⁹) in 25.4 Mb, and Hapmap24414-BTC-073009 (P = 7.38×10⁻⁸) in 25.4 Mb, all on BTA 14. One SNP (BTB-01143580; P = 6.35×10⁻¹¹) lies independently from the other 5 SNPs. The 5 SNPs that lie together showed a large Linkage disequilibrium (LD) block (block size of 553 kb) with LD coefficients ranging from 0.53 to 0.89 within the block. The most significant SNPs accounted for 6.73% to 10.55% of additive genetic variance, which is quite a large proportion of the total additive genetic variance. The most significant SNP (BTB-01280026; P = 4.02×10⁻¹¹) had 16.96 kg of allele substitution effect, and the second most significant SNP (Hapmap27934-BTC-065223; P = 4.04×10⁻¹¹) had 18.06 kg of effect on carcass weight, which correspond to 44% and 47%, respectively, of the phenotypic standard deviation for carcass weight in Hanwoo cattle. Our results demonstrated that carcass weight was affected by a major Quantitative Trait Locus (QTL) with a large effect and by many SNPs with small effects that are normally distributed.     

Identification of a Functional Genetic Variant at 16q12.1 for Breast Cancer Risk: Results from the Asia Breast Cancer Consortium

Genetic factors play an important role in the etiology of breast cancer. We carried out a multi-stage genome-wide association (GWA) study in over 28,000 cases and controls recruited from 12 studies conducted in Asian and European American women to identify genetic susceptibility loci for breast cancer. After analyzing 684,457 SNPs in 2,073 cases and 2,084 controls in Chinese women, we evaluated 53 SNPs for fast-track replication in an independent set of 4,425 cases and 1,915 controls of Chinese origin. Four replicated SNPs were further investigated in an independent set of 6,173 cases and 6,340 controls from seven other studies conducted in Asian women. SNP rs4784227 was consistently associated with breast cancer risk across all studies with adjusted odds ratios (95% confidence intervals) of 1.25 (1.20−1.31) per allele (P = 3.2×10⁻²⁵) in the pooled analysis of samples from all Asian samples. This SNP was also associated with breast cancer risk among European Americans (per allele OR  = 1.19, 95% CI  = 1.09−1.31, P = 1.3×10⁻⁴, 2,797 cases and 2,662 controls). SNP rs4784227 is located at 16q12.1, a region identified previously for breast cancer risk among Europeans. The association of this SNP with breast cancer risk remained highly statistically significant in Asians after adjusting for previously-reported SNPs in this region. In vitro experiments using both luciferase reporter and electrophoretic mobility shift assays demonstrated functional significance of this SNP. These results provide strong evidence implicating rs4784227 as a functional causal variant for breast cancer in the locus 16q12.1 and demonstrate the utility of conducting genetic association studies in populations with different genetic architectures.     

Selection and use of SNP markers for animal identification and paternity analysis in U.S. beef cattle

DNA marker technology represents a promising means for determining the genetic identity and kinship of an animal. Compared with other types of DNA markers, single nucleotide polymorphisms (SNPs) are attractive because they are abundant, genetically stable, and amenable to high-throughput automated analysis. In cattle, the challenge has been to identify a minimal set of SNPs with sufficient power for use in a variety of popular breeds and crossbred populations. This report describes a set of 32 highly informative SNP markers distributed among 18 autosomes and both sex chromosomes. Informativity of these SNPs in U.S. beef cattle populations was estimated from the distribution of allele and genotype frequencies in two panels: one consisting of 96 purebred sires representing 17 popular breeds, and another with 154 purebred American Angus from six herds in four Midwestern states. Based on frequency data from these panels, the estimated probability that two randomly selected, unrelated individuals will possess identical genotypes for all 32 loci was 2.0 × 10⁻¹³ for multi-breed composite populations and 1.9 × 10⁻¹⁰ for purebred Angus populations. The probability that a randomly chosen candidate sire will be excluded from paternity was estimated to be 99.9% and 99.4% for the same respective populations. The DNA immediately surrounding the 32 target SNPs was sequenced in the 96 sires of the multi-breed panel and found to contain an additional 183 polymorphic sites. Knowledge of these additional sites, together with the 32 target SNPs, allows the design of robust, accurate genotype assays on a variety of high-throughput SNP genotyping platforms.     

Application of Gene Network Analysis Techniques Identifies AXIN1/PDIA2 and Endoglin Haplotypes Associated with Bicuspid Aortic Valve

Bicuspid Aortic Valve (BAV) is a highly heritable congenital heart defect. The low frequency of BAV (1% of general population) limits our ability to perform genome-wide association studies. We present the application of four a priori SNP selection techniques, reducing the multiple-testing penalty by restricting analysis to SNPs relevant to BAV in a genome-wide SNP dataset from a cohort of 68 BAV probands and 830 control subjects. Two knowledge-based approaches, CANDID and STRING, were used to systematically identify BAV genes, and their SNPs, from the published literature, microarray expression studies and a genome scan. We additionally tested Functionally Interpolating SNPs (fitSNPs) present on the array; the fourth consisted of SNPs selected by Random Forests, a machine learning approach. These approaches reduced the multiple testing penalty by lowering the fraction of the genome probed to 0.19% of the total, while increasing the likelihood of studying SNPs within relevant BAV genes and pathways. Three loci were identified by CANDID, STRING, and fitSNPS. A haplotype within the AXIN1-PDIA2 locus (p-value of 2.926×10⁻⁰⁶) and a haplotype within the Endoglin gene (p-value of 5.881×10⁻⁰⁴) were found to be strongly associated with BAV. The Random Forests approach identified a SNP on chromosome 3 in association with BAV (p-value 5.061×10⁻⁰⁶). The results presented here support an important role for genetic variants in BAV and provide support for additional studies in well-powered cohorts. Further, these studies demonstrate that leveraging existing expression and genomic data in the context of GWAS studies can identify biologically relevant genes and pathways associated with a congenital heart defect.     

Analytical and statistical consideration on the use of the ISAG-ICAR-SNP bovine panel for parentage control,using the Illumina BeadChip technology: example on the German Holstein population

Background

Parentage control is moving from short tandem repeats- to single nucleotide polymorphism (SNP) systems. For SNP-based parentage control in cattle, the ISAG-ICAR Committee proposes a set of 100/200 SNPs but quality criteria are lacking. Regarding German Holstein-Friesian cattle with only a limited number of evaluated individuals, the exclusion probability is not well-defined. We propose a statistical procedure for excluding single SNPs from parentage control, based on case-by-case evaluation of the GenCall score, to minimize parentage exclusion, based on miscalled genotypes. Exclusion power of the ISAG-ICAR SNPs used for the German Holstein-Friesian population was adjusted based on the results of more than 25 000 individuals.

Results

Experimental data were derived from routine genomic selection analyses of the German Holstein-Friesian population using the Illumina BovineSNP50 v2 BeadChip (20 000 individuals) or the EuroG10K variant (7000 individuals). Averages and standard deviations of GenCall scores for the 200 SNPs of the ISAG-ICAR recommended panel were calculated and used to calculate the downward Z-value. Based on minor allelic frequencies in the Holstein-Friesian population, one minus exclusion probability was equal to 1.4×10⁻¹⁰ and 7.2×10⁻²⁶, with one and two parents, respectively. Two monomorphic SNPs from the 100-SNP ISAG-ICAR core-panel did not contribute. Simulation of 10 000 parentage control combinations, using the GenCall score data from both BeadChips, showed that with a Z-value greater than 3.66 only about 2.5% parentages were excluded, based on the ISAG-ICAR recommendations (core-panel: ≥ 90 SNPs for one, ≥ 85 SNPs for two parents). When applied to real data from 1750 single parentage assessments, the optimal threshold was determined to be Z = 5.0, with only 34 censored cases and reduction to four (0.2%) doubtful parentages. About 70 parentage exclusions due to weak genotype calls were avoided, whereas true exclusions (n = 34) were unaffected.

Conclusions

Using SNPs for parentage evaluation provides a high exclusion power also for parent identification. SNPs with a low GenCall score show a high tendency towards intra-molecular secondary structures and substantially contribute to false exclusion of parentages. We propose a method that controls this error without excluding too many parent combinations from the evaluation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0085-1) contains supplementary material, which is available to authorized users.     

A Genome-Wide Association Study Uncovers a Genetic Locus Associated with Thoracic-to-Hip Ratio in Koreans

The thoracic-to-hip circumference ratio (THR) is an anthropometric marker recently described as a predictor of type 2 diabetes. In this study, we performed a genome-wide association study (GWAS) followed by confirmatory analyses to identify genetic markers associated with THR. A total of 7,240 Korean subjects (4,988 for the discovery stage and 2,252 for the confirmatory analyses) were recruited for this study, and genome-wide single nucleotide polymorphism (SNP) genotyping of the initial 4,988 individuals was performed using Affymetrix Human SNP array 5.0. Linear regression analysis was then performed to adjust for the effects of age, sex, and current diabetes medication status on the THR of the study subjects. In the initial discovery stage, there was a statistically nominal association between minor alleles of SNP markers on chromosomes 4, 8, 10, and 12, and THR changes (p < 5.0 × 10⁻⁶). The subsequent confirmatory analyses of these markers, however, only detected a significant association between two SNPs in the HECTD4 gene and decreased THRs. Notably, this association was detected in male (rs11066280: p = 1.14 × 10⁻²; rs2074356: p = 1.10 × 10⁻²), but not in female subjects. Meanwhile, the combined results from the two analyses (initial and confirmatory) indicated that minor alleles of these two intronic variants exhibited a significant genome-wide association with decreased THR in the male subjects (n = 3,155; rs11066280: effect size = −0.008624, p = 6.19 × 10⁻⁹; rs2074356: effect size = −0.008762, p = 1.89 × 10⁻⁸). Furthermore, minor alleles of these two SNPs exhibited protective effects on patients’ risks for developing type 2 diabetes. In conclusion, we have identified two genetic variations in HECTD4 that are associated with THR, particularly in men.     

Genome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort Studies: The CHARGE Consortium

Background

Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting.

Methods

We performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10⁻⁶ in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up.

Results

In Stage I 15 loci passed the threshold of 5×10⁻⁶; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10⁻³) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10⁻⁹). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10⁻³).

Conclusions

QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.     

Genetic Analysis Identifies DDR2 as a Novel Gene Affecting Bone Mineral Density and Osteoporotic Fractures in Chinese Population

DDR2 gene, playing an essential role in regulating osteoblast differentiation and chondrocyte maturation, may influence bone mineral density (BMD) and osteoporosis, but the genetic variations actually leading to the association remain to be elucidated. Therefore, the aim of this study was to investigate whether the genetic variants in DDR2 are associated with BMD and fracture risk. This study was performed in three samples from two ethnicities, including 1,300 Chinese Han subjects, 700 Chinese Han subjects (350 with osteoporotic hip fractures and 350 healthy controls) and 2,286 US white subjects. Twenty-eight SNPs in DDR2 were genotyped and tested for associations with hip BMD and fractures. We identified 3 SNPs in DDR2 significantly associated with hip BMD in the Chinese population after multiple testing adjustments, which were rs7521233 (P = 1.06×10⁻⁴, β: −0.018 for allele C), rs7553831 (P = 1.30×10⁻⁴, β: −0.018 for allele T), and rs6697469 (P = 1.59×10⁻³, β: −0.015 for allele C), separately. These three SNPs were in high linkage disequilibrium. Haplotype analyses detected two significantly associated haplotypes, including one haplotype in block 2 (P = 9.54×10⁻⁴, β: −0.016) where these three SNPs located. SNP rs6697469 was also associated with hip fractures (P = 0.043, OR: 1.42) in the Chinese population. The effect on fracture risk was consistent with its association with lower BMD. However, in the white population, we didn’t observe significant associations with hip BMD. eQTL analyses revealed that SNPs associated with BMD also affected DDR2 mRNA expression levels in Chinese. Our findings, together with the prior biological evidence, suggest that DDR2 could be a new candidate for osteoporosis in Chinese population. Our results also reveal an ethnic difference, which highlights the need for further genetic studies in each ethnic group.     

SNPs for Parentage Testing and Traceability in Globally Diverse Breeds of Sheep

DNA-based parentage determination accelerates genetic improvement in sheep by increasing pedigree accuracy. Single nucleotide polymorphism (SNP) markers can be used for determining parentage and to provide unique molecular identifiers for tracing sheep products to their source. However, the utility of a particular “parentage SNP” varies by breed depending on its minor allele frequency (MAF) and its sequence context. Our aims were to identify parentage SNPs with exceptional qualities for use in globally diverse breeds and to develop a subset for use in North American sheep. Starting with genotypes from 2,915 sheep and 74 breed groups provided by the International Sheep Genomics Consortium (ISGC), we analyzed 47,693 autosomal SNPs by multiple criteria and selected 163 with desirable properties for parentage testing. On average, each of the 163 SNPs was highly informative (MAF≥0.3) in 48±5 breed groups. Nearby polymorphisms that could otherwise confound genetic testing were identified by whole genome and Sanger sequencing of 166 sheep from 54 breed groups. A genetic test with 109 of the 163 parentage SNPs was developed for matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry. The scoring rates and accuracies for these 109 SNPs were greater than 99% in a panel of North American sheep. In a blinded set of 96 families (sire, dam, and non-identical twin lambs), each parent of every lamb was identified without using the other parent’s genotype. In 74 ISGC breed groups, the median estimates for probability of a coincidental match between two animals (P_I), and the fraction of potential adults excluded from parentage (P_E) were 1.1×10(−39) and 0.999987, respectively, for the 109 SNPs combined. The availability of a well-characterized set of 163 parentage SNPs facilitates the development of high-throughput genetic technologies for implementing accurate and economical parentage testing and traceability in many of the world’s sheep breeds.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.     

Results of Genome-Wide Analyses on Neurodevelopmental Phenotypes at Four-Year Follow-Up following Cardiac Surgery in Infancy

Background

Adverse neurodevelopmental sequelae are reported among children who undergo early cardiac surgery to repair congenital heart defects (CHD). APOE genotype has previously been determined to contribute to the prediction of these outcomes. Understanding further genetic causes for the development of poor neurobehavioral outcomes should enhance patient risk stratification and improve both prevention and treatment strategies.

Methods

We performed a prospective observational study of children who underwent cardiac surgery before six months of age; this included a neurodevelopmental evaluation between their fourth and fifth birthdays. Attention and behavioral skills were assessed through parental report utilizing the Attention Deficit-Hyperactivity Disorder-IV scale preschool edition (ADHD-IV), and Child Behavior Checklist (CBCL/1.5-5), respectively. Of the seven investigated, three neurodevelopmental phenotypes met genomic quality control criteria. Linear regression was performed to determine the effect of genome-wide genetic variation on these three neurodevelopmental measures in 316 subjects.

Results

This genome-wide association study identified single nucleotide polymorphisms (SNPs) associated with three neurobehavioral phenotypes in the postoperative children ADHD-IV Impulsivity/Hyperactivity, CBCL/1.5-5 PDPs, and CBCL/1.5-5 Total Problems. The most predictive SNPs for each phenotype were: a LGALS8 intronic SNP, rs4659682, associated with ADHD-IV Impulsivity (P = 1.03×10⁻⁶); a PCSK5 intronic SNP, rs2261722, associated with CBCL/1.5-5 PDPs (P = 1.11×10⁻⁶); and an intergenic SNP, rs11617488, 50 kb from FGF9, associated with CBCL/1.5-5 Total Problems (P = 3.47×10⁻⁷). 10 SNPs (3 for ADHD-IV Impulsivity, 5 for CBCL/1.5-5 PDPs, and 2 for CBCL/1.5-5 Total Problems) had p<10⁻⁵.

Conclusions

No SNPs met genome-wide significance for our three neurobehavioral phenotypes; however, 10 SNPs reached a threshold for suggestive significance (p<10⁻⁵). Given the unique nature of this cohort, larger studies and/or replication are not possible. Studies to further investigate the mechanisms through which these newly identified genes may influence neurodevelopment dysfunction are warranted.     

A High Throughput Single Nucleotide Polymorphism Multiplex Assay for Parentage Assignment in New Zealand Sheep

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development- firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 “parentage SNP panel” was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test’s suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.     

Exonic Variants Associated with Development of Aspirin Exacerbated Respiratory Diseases

Aspirin-exacerbated respiratory disease (AERD) is one phenotype of asthma, often occurring in the form of a severe and sudden attack. Due to the time-consuming nature and difficulty of oral aspirin challenge (OAC) for AERD diagnosis, non-invasive biomarkers have been sought. The aim of this study was to identify AERD-associated exonic SNPs and examine the diagnostic potential of a combination of these candidate SNPs to predict AERD. DNA from 165 AERD patients, 397 subjects with aspirin-tolerant asthma (ATA), and 398 normal controls were subjected to an Exome BeadChip assay containing 240K SNPs. 1,023 models (2¹⁰-1) were generated from combinations of the top 10 SNPs, selected by the p-values in association with AERD. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves was calculated for each model. SNP Function Portal and PolyPhen-2 were used to validate the functional significance of candidate SNPs. An exonic SNP, exm537513 in HLA-DPB1, showed the lowest p-value (p = 3.40×10⁻⁸) in its association with AERD risk. From the top 10 SNPs, a combination model of 7 SNPs (exm537513, exm83523, exm1884673, exm538564, exm2264237, exm396794, and exm791954) showed the best AUC of 0.75 (asymptotic p-value of 7.94×10⁻²¹), with 34% sensitivity and 93% specificity to discriminate AERD from ATA. Amino acid changes due to exm83523 in CHIA were predicted to be “probably damaging” to the structure and function of the protein, with a high score of ‘1’. A combination model of seven SNPs may provide a useful, non-invasive genetic marker combination for predicting AERD.     

A Genome-Wide Association Study of Hypertension and Blood Pressure in African Americans

The evidence for the existence of genetic susceptibility variants for the common form of hypertension (“essential hypertension”) remains weak and inconsistent. We sought genetic variants underlying blood pressure (BP) by conducting a genome-wide association study (GWAS) among African Americans, a population group in the United States that is disproportionately affected by hypertension and associated complications, including stroke and kidney diseases. Using a dense panel of over 800,000 SNPs in a discovery sample of 1,017 African Americans from the Washington, D.C., metropolitan region, we identified multiple SNPs reaching genome-wide significance for systolic BP in or near the genes: PMS1, SLC24A4, YWHA7, IPO7, and CACANA1H. Two of these genes, SLC24A4 (a sodium/potassium/calcium exchanger) and CACNA1H (a voltage-dependent calcium channel), are potential candidate genes for BP regulation and the latter is a drug target for a class of calcium channel blockers. No variant reached genome wide significance for association with diastolic BP (top scoring SNP rs1867226, p = 5.8×10⁻⁷) or with hypertension as a binary trait (top scoring SNP rs9791170, p = 5.1×10⁻⁷). We replicated some of the significant SNPs in a sample of West Africans. Pathway analysis revealed that genes harboring top-scoring variants cluster in pathways and networks of biologic relevance to hypertension and BP regulation. This is the first GWAS for hypertension and BP in an African American population. The findings suggests that, in addition to or in lieu of relying solely on replicated variants of moderate-to-large effect reaching genome-wide significance, pathway and network approaches may be useful in identifying and prioritizing candidate genes/loci for further experiments.     

Genome-Wide Search for Gene-Gene Interactions in Colorectal Cancer

Genome-wide association studies (GWAS) have successfully identified a number of single-nucleotide polymorphisms (SNPs) associated with colorectal cancer (CRC) risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG) is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI). With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10⁻⁴). For the known locus rs10795668 (10p14), we found an interacting SNP rs367615 (5q21) with replication p = 0.01 and combined p = 4.19×10⁻⁸. Among the top marginal SNPs after LD pruning (n = 163), we identified an interaction between rs1571218 (20p12.3) and rs10879357 (12q21.1) (nominal combined p = 2.51×10⁻⁶; Bonferroni adjusted p = 0.03). Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.     

Susceptibility Loci Associated with Specific and Shared Subtypes of Lymphoid Malignancies

The genetics of lymphoma susceptibility reflect the marked heterogeneity of diseases that comprise this broad phenotype. However, multiple subtypes of lymphoma are observed in some families, suggesting shared pathways of genetic predisposition to these pathologically distinct entities. Using a two-stage GWAS, we tested 530,583 SNPs in 944 cases of lymphoma, including 282 familial cases, and 4,044 public shared controls, followed by genotyping of 50 SNPs in 1,245 cases and 2,596 controls. A novel region on 11q12.1 showed association with combined lymphoma (LYM) subtypes. SNPs in this region included rs12289961 near LPXN, (P_LYM = 3.89×10⁻⁸, OR = 1.29) and rs948562 (P_LYM = 5.85×10⁻⁷, OR = 1.29). A SNP in a novel non-HLA region on 6p23 (rs707824, P_NHL = 5.72×10⁻⁷) was suggestive of an association conferring susceptibility to lymphoma. Four SNPs, all in a previously reported HLA region, 6p21.32, showed genome-wide significant associations with follicular lymphoma. The most significant association with follicular lymphoma was for rs4530903 (P_FL = 2.69×10⁻¹², OR = 1.93). Three novel SNPs near the HLA locus, rs9268853, rs2647046, and rs2621416, demonstrated additional variation contributing toward genetic susceptibility to FL associated with this region. Genes implicated by GWAS were also found to be cis-eQTLs in lymphoblastoid cell lines; candidate genes in these regions have been implicated in hematopoiesis and immune function. These results, showing novel susceptibility regions and allelic heterogeneity, point to the existence of pathways of susceptibility to both shared as well as specific subtypes of lymphoid malignancy.     

A Genome-Wide Association Study Confirms VKORC1, CYP2C9, and CYP4F2 as Principal Genetic Determinants of Warfarin Dose

We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5×10⁻⁷) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that ~30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another ~12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10⁻⁷⁸) at SNPs clustering near VKORC1 and the second lowest p-values (p<10⁻³¹) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p=8.3×10⁻¹⁰) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.     

A Genome Wide Association Study of Mathematical Ability Reveals an Association at Chromosome 3q29, a Locus Associated with Autism and Learning Difficulties: A Preliminary Study

Mathematical ability is heritable, but few studies have directly investigated its molecular genetic basis. Here we aimed to identify specific genetic contributions to variation in mathematical ability. We carried out a genome wide association scan using pooled DNA in two groups of U.K. samples, based on end of secondary/high school national academic exam achievement: high (n = 419) versus low (n = 183) mathematical ability while controlling for their verbal ability. Significant differences in allele frequencies between these groups were searched for in 906,600 SNPs using the Affymetrix GeneChip Human Mapping version 6.0 array. After meeting a threshold of p<1.5×10⁻⁵, 12 SNPs from the pooled association analysis were individually genotyped in 542 of the participants and analyzed to validate the initial associations (lowest p-value 1.14 ×10⁻⁶). In this analysis, one of the SNPs (rs789859) showed significant association after Bonferroni correction, and four (rs10873824, rs4144887, rs12130910 rs2809115) were nominally significant (lowest p-value 3.278 × 10⁻⁴). Three of the SNPs of interest are located within, or near to, known genes (FAM43A, SFT2D1, C14orf64). The SNP that showed the strongest association, rs789859, is located in a region on chromosome 3q29 that has been previously linked to learning difficulties and autism. rs789859 lies 1.3 kbp downstream of LSG1, and 700 bp upstream of FAM43A, mapping within the potential promoter/regulatory region of the latter. To our knowledge, this is only the second study to investigate the association of genetic variants with mathematical ability, and it highlights a number of interesting markers for future study.