Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls

Recent evidence suggests that inflammation plays a pivotal role in the development of lung cancer. In this study, we used a two-stage approach to investigate associations between genetic variants in inflammation pathways and lung cancer risk based on genome-wide association study (GWAS) data. A total of 7,650 sequence variants from 720 genes relevant to inflammation pathways were identified using keyword and pathway searches from Gene Cards and Gene Ontology databases. In Stage 1, six GWAS datasets from the International Lung Cancer Consortium were pooled (4,441 cases and 5,094 controls of European ancestry), and a hierarchical modeling (HM) approach was used to incorporate prior information for each of the variants into the analysis. The prior matrix was constructed using (1) role of genes in the inflammation and immune pathways; (2) physical properties of the variants including the location of the variants, their conservation scores and amino acid coding; (3) LD with other functional variants and (4) measures of heterogeneity across the studies. HM affected the priority ranking of variants particularly among those having low prior weights, imprecise estimates and/or heterogeneity across studies. In Stage 2, we used an independent NCI lung cancer GWAS study (5,699 cases and 5,818 controls) for in silico replication. We identified one novel variant at the level corrected for multiple comparisons (rs2741354 in EPHX2 at 8q21.1 with p value = 7.4 × 10^?6), and confirmed the associations between TERT (rs2736100) and the HLA region and lung cancer risk. HM allows for prior knowledge such as from bioinformatic sources to be incorporated into the analysis systematically, and it represents a complementary analytical approach to the conventional GWAS analysis.     

Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility

Previous genome-wide association studies (GWAS) have shown several risk alleles to be associated with breast cancer. However, the variants identified so far contribute to only a small proportion of disease risk. The objective of our GWAS was to identify additional novel breast cancer susceptibility variants and to replicate these findings in an independent cohort. We performed a two-stage association study in a cohort of 3,064 women from Alberta, Canada. In Stage I, we interrogated 906,600 single nucleotide polymorphisms (SNPs) on Affymetrix SNP 6.0 arrays using 348 breast cancer cases and 348 controls. We used single-locus association tests to determine statistical significance for the observed differences in allele frequencies between cases and controls. In Stage II, we attempted to replicate 35 significant markers identified in Stage I in an independent study of 1,153 cases and 1,215 controls. Genotyping of Stage II samples was done using Sequenom Mass-ARRAY iPlex platform. Six loci from four different gene regions (chromosomes 4, 5, 16 and 19) showed statistically significant differences between cases and controls in both Stage I and Stage II testing, and also in joint analysis. The identified variants were from EDNRA, ROPN1L, C16orf61 and ZNF577 gene regions. The presented joint analyses from the two-stage study design were not significant after genome-wide correction. The SNPs identified in this study may serve as potential candidate loci for breast cancer risk in a further replication study in Stage III from Alberta population or independent validation in Caucasian cohorts elsewhere.     

A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium

Genome-wide association studies (GWAS) have been successful in identifying common genetic variation involved in susceptibility to etiologically complex disease. We conducted a GWAS to identify common genetic variation involved in susceptibility to upper aero-digestive tract (UADT) cancers. Genome-wide genotyping was carried out using the Illumina HumanHap300 beadchips in 2,091 UADT cancer cases and 3,513 controls from two large European multi-centre UADT cancer studies, as well as 4,821 generic controls. The 19 top-ranked variants were investigated further in an additional 6,514 UADT cancer cases and 7,892 controls of European descent from an additional 13 UADT cancer studies participating in the INHANCE consortium. Five common variants presented evidence for significant association in the combined analysis (p≤5×10⁻⁷). Two novel variants were identified, a 4q21 variant (rs1494961, p = 1×10⁻⁸) located near DNA repair related genes HEL308 and FAM175A (or Abraxas) and a 12q24 variant (rs4767364, p = 2×10⁻⁸) located in an extended linkage disequilibrium region that contains multiple genes including the aldehyde dehydrogenase 2 (ALDH2) gene. Three remaining variants are located in the ADH gene cluster and were identified previously in a candidate gene study involving some of these samples. The association between these three variants and UADT cancers was independently replicated in 5,092 UADT cancer cases and 6,794 controls non-overlapping samples presented here (rs1573496-ADH7, p = 5×10⁻⁸; rs1229984-ADH1B, p = 7×10⁻⁹; and rs698-ADH1C, p = 0.02). These results implicate two variants at 4q21 and 12q24 and further highlight three ADH variants in UADT cancer susceptibility.     

Tuberculosis infection and lung adenocarcinoma: Mendelian randomization and pathway analysis of genome-wide association study data from never-smoking Asian women

We investigated whether genetic susceptibility to tuberculosis (TB) influences lung adenocarcinoma development among never-smokers using TB genome-wide association study (GWAS) results within the Female Lung Cancer Consortium in Asia. Pathway analysis with the adaptive rank truncated product method was used to assess the association between a TB-related gene-set and lung adenocarcinoma using GWAS data from 5512 lung adenocarcinoma cases and 6277 controls. The gene-set consisted of 31 genes containing known/suggestive associations with genetic variants from previous TB-GWAS. Subsequently, we followed-up with Mendelian Randomization to evaluate the association between TB and lung adenocarcinoma using three genome-wide significant variants from previous TB-GWAS in East Asians. The TB-related gene-set was associated with lung adenocarcinoma (p = 0.016). Additionally, the Mendelian Randomization showed an association between TB and lung adenocarcinoma (OR = 1.31, 95% CI: 1.03, 1.66, p = 0.027). Our findings support TB as a causal risk factor for lung cancer development among never-smoking Asian women.     

Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55×10⁻¹⁵¹). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases.     

Phase I Metabolic Genes and Risk of Lung Cancer: Multiple Polymorphisms and mRNA Expression

Polymorphisms in genes coding for enzymes that activate tobacco lung carcinogens may generate inter-individual differences in lung cancer risk. Previous studies had limited sample sizes, poor exposure characterization, and a few single nucleotide polymorphisms (SNPs) tested in candidate genes. We analyzed 25 SNPs (some previously untested) in 2101 primary lung cancer cases and 2120 population controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) study from six phase I metabolic genes, including cytochrome P450s, microsomal epoxide hydrolase, and myeloperoxidase. We evaluated the main genotype effects and genotype-smoking interactions in lung cancer risk overall and in the major histology subtypes. We tested the combined effect of multiple SNPs on lung cancer risk and on gene expression. Findings were prioritized based on significance thresholds and consistency across different analyses, and accounted for multiple testing and prior knowledge. Two haplotypes in EPHX1 were significantly associated with lung cancer risk in the overall population. In addition, CYP1B1 and CYP2A6 polymorphisms were inversely associated with adenocarcinoma and squamous cell carcinoma risk, respectively. Moreover, the association between CYP1A1 rs2606345 genotype and lung cancer was significantly modified by intensity of cigarette smoking, suggesting an underling dose-response mechanism. Finally, increasing number of variants at CYP1A1/A2 genes revealed significant protection in never smokers and risk in ever smokers. Results were supported by differential gene expression in non-tumor lung tissue samples with down-regulation of CYP1A1 in never smokers and up-regulation in smokers from CYP1A1/A2 SNPs. The significant haplotype associations emphasize that the effect of multiple SNPs may be important despite null single SNP-associations, and warrants consideration in genome-wide association studies (GWAS). Our findings emphasize the necessity of post-GWAS fine mapping and SNP functional assessment to further elucidate cancer risk associations.     

Rare variation at the TNFAIP3 locus and susceptibility to rheumatoid arthritis

Genome-wide association studies (GWAS) conducted using commercial single nucleotide polymorphisms (SNP) arrays have proven to be a powerful tool for the detection of common disease susceptibility variants. However, their utility for the detection of lower frequency variants is yet to be practically investigated. Here we describe the application of a rare variant collapsing method to a large genome-wide SNP dataset, the Wellcome Trust Case Control Consortium rheumatoid arthritis (RA) GWAS. We partitioned the data into gene-centric bins and collapsed genotypes of low frequency variants (defined here as MAF ≤0.05) into a single count coupled with univariate analysis. We then prioritised gene regions for further investigation in an independent cohort of 3,355 cases and 2,427 controls based on rare variant signal p value and prior evidence to support involvement in RA. A total of 14,536 gene bins were investigated in the primary analysis and signals mapping to the TNFAIP3 and chr17q24 loci were selected for further investigation. We detected replicating association to low frequency variants in the TNFAIP3 gene (combined p = 6.6 × 10^?6). Even though rare variants are not well-represented and can be difficult to genotype in GWAS, our study supports the application of low frequency variant collapsing methods to genome-wide SNP datasets as a means of exploiting data that are routinely ignored.     

Identifying consensus disease pathways in Parkinson's disease using an integrative systems biology approach

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD.     

Association analysis of 9,560 prostate cancer cases from the International Consortium of Prostate Cancer Genetics confirms the role of reported prostate cancer associated SNPs for familial disease

Previous GWAS studies have reported significant associations between various common SNPs and prostate cancer risk using cases unselected for family history. How these variants influence risk in familial prostate cancer is not well studied. Here, we analyzed 25 previously reported SNPs across 14 loci from prior prostate cancer GWAS. The International Consortium for Prostate Cancer Genetics (ICPCG) previously validated some of these using a family-based association method (FBAT). However, this approach suffered reduced power due to the conditional statistics implemented in FBAT. Here, we use a case–control design with an empirical analysis strategy to analyze the ICPCG resource for association between these 25 SNPs and familial prostate cancer risk. Fourteen sites contributed 12,506 samples (9,560 prostate cancer cases, 3,368 with aggressive disease, and 2,946 controls from 2,283 pedigrees). We performed association analysis with Genie software which accounts for relationships. We analyzed all familial prostate cancer cases and the subset of aggressive cases. For the familial prostate cancer phenotype, 20 of the 25 SNPs were at least nominally associated with prostate cancer and 16 remained significant after multiple testing correction (p ≤ 1E ^?3) occurring on chromosomal bands 6q25, 7p15, 8q24, 10q11, 11q13, 17q12, 17q24, and Xp11. For aggressive disease, 16 of the SNPs had at least nominal evidence and 8 were statistically significant including 2p15. The results indicate that the majority of common, low-risk alleles identified in GWAS studies for all prostate cancer also contribute risk for familial prostate cancer, and that some may contribute risk to aggressive disease.     

Pathway-Based Genome-Wide Association Studies for Plasma Triglycerides in Obese Females and Normal-Weight Controls

Pathway-based analysis as an alternative approach can provide complementary information to single-marker genome-wide association studies (GWASs), which always ignore the epistasis and does not have sufficient power to find rare variants. In this study, using genotypes from a genome-wide association study (GWAS), pathway-based association studies were carried out by a modified Gene Set Enrichment Algorithm (GSEA) method (GenGen) for triglyceride in 1028 unrelated European-American extremely obese females (BMI≥35kg/m²) and normal-weight controls (BMI<25kg/m²), and another pathway association analysis (ICSNPathway) was also used to verify the GenGen result in the same data. The GO0009110 pathway (vitamin anabolism) was among the strongest associations with triglyceride (empirical P<0.001); the result remained significant after FDR correction (P = 0.022). MMAB, an obesity-related locus, included in this pathway. The ABCG1 and BCL6 gene was found in several triglyceride-related pathways (empirical P<0.05), which were also replicated by ICSNPathway (empirical P<0.05, FDR<0.05). We also performed single-marked GWAS using PLINK for TG levels (log-transformed). Significant associations were found between ASTN2 gene SNPs and plasma triglyceride levels (rs7035794, P = 2.24×10⁻¹⁰). Our study suggested that vitamin anabolism pathway, BCL6 gene pathways and ASTN2 gene may contribute to the genetic variation of plasma triglyceride concentrations.     

Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

The ability to establish genetic risk models is critical for early identification and optimal treatment of breast cancer. For such a model to gain clinical utility, more variants must be identified beyond those discovered in previous genome-wide association studies (GWAS). This is especially true for women at high risk because of family history, but without BRCA1/2 mutations. This study incorporates three datasets in a GWAS analysis of women with Ashkenazi Jewish (AJ) homogeneous ancestry. Two independent discovery cohorts comprised 239 and 238 AJ women with invasive breast cancer or preinvasive ductal carcinoma in situ and strong family histories of breast cancer, but lacking the three BRCA1/2 founder mutations, along with 294 and 230 AJ controls, respectively. An independent, third cohort of 203 AJ cases with familial breast cancer history and 263 healthy controls of AJ women was used for validation. A total of 19 SNPs were identified as associated with familial breast cancer risk in AJ women. Among these SNPs, 13 were identified from a panel of 109 discovery SNPs, including an FGFR2 haplotype. In addition, six previously identified breast cancer GWAS SNPs were confirmed in this population. Seven of the 19 markers were significant in a multivariate predictive model of familial breast cancer in AJ women, three novel SNPs [rs17663555(5q13.2), rs566164(6q21), and rs11075884(16q22.2)], the FGFR2 haplotype, and three previously published SNPs [rs13387042(2q35), rs2046210(ESR1), and rs3112612(TOX3)], yielding moderate predictive power with an area under the curve (AUC) of the ROC (receiver-operator characteristic curve) of 0.74. Population-specific genetic variants in addition to variants shared with populations of European ancestry may improve breast cancer risk prediction among AJ women from high-risk families without founder BRCA1/2 mutations.     

Genetic Variants at 6p21.1 and 7p15.3 Are Associated with Risk of Multiple Cancers in Han Chinese

Cancer susceptibility loci identified in reported genome-wide association studies (GWAS) are often tumor-specific; however, evidence of pleiotropy of some genes/loci has also been observed and biologically plausible. We hypothesized that there are important regions in the genome harboring genetic variants associated with risk of multiple types of cancer. In the current study, we attempted to map genetic variants that have consistent effects on risk of multiple cancers using our existing genome-wide scan data of lung cancer, noncardia gastric cancer, and esophageal squamous-cell carcinoma with overall 5,368 cases and 4,006 controls (GWAS stage), followed by a further evaluation in additional 9,001 cases with one of these cancer types and 11,436 controls (replication stage). Five variants satisfying the criteria of pleiotropy with p values from 1.10 × 10⁻⁸ to 8.96 × 10⁻⁶ for genome-wide scans of three cancer types were further evaluated in the replication stage. We found consistent associations of rs2494938 at 6p21.1 and rs2285947 at 7p15.3 with these three cancers in both GWAS and replication stages. In combined samples of GWAS and replication stages, the minor alleles of rs2494938 and rs2285947 were significantly associated with an increased risk of the cancers (odds ratio [OR] = 1.15, 95% confidence interval [CI], 1.10–1.19 and OR = 1.17, 95% CI, 1.12–1.21), with the p values being 1.20 × 10⁻¹² and 1.26 × 10⁻¹⁶, respectively, which are at a genome-wide significance level. Our findings highlight the potential importance of variants at 6p21.1 and 7p15.3 in the susceptibility to multiple cancers.     

Insights into Colon Cancer Etiology via a Regularized Approach to Gene Set Analysis of GWAS Data

Genome-wide association studies (GWAS) have successfully identified susceptibility loci from marginal association analysis of SNPs. Valuable insight into genetic variation underlying complex diseases will likely be gained by considering functionally related sets of genes simultaneously. One approach is to further develop gene set enrichment analysis methods, which are initiated in gene expression studies, to account for the distinctive features of GWAS data. These features include the large number of SNPs per gene, the modest and sparse SNP associations, and the additional information provided by linkage disequilibrium (LD) patterns within genes. We propose a “gene set ridge regression in association studies (GRASS)” algorithm. GRASS summarizes the genetic structure for each gene as eigenSNPs and uses a novel form of regularized regression technique, termed group ridge regression, to select representative eigenSNPs for each gene and assess their joint association with disease risk. Compared with existing methods, the proposed algorithm greatly reduces the high dimensionality of GWAS data while still accounting for multiple hits and/or LD in the same gene. We show by simulation that this algorithm performs well in situations in which there are a large number of predictors compared to sample size. We applied the GRASS algorithm to a genome-wide association study of colon cancer and identified nicotinate and nicotinamide metabolism and transforming growth factor beta signaling as the top two significantly enriched pathways. Elucidating the role of variation in these pathways may enhance our understanding of colon cancer etiology.     

Chromosome 15q25 (CHRNA3-CHRNA5) variation impacts indirectly on lung cancer risk

Genetic variants at the 15q25 CHRNA5-CHRNA3 locus have been shown to influence lung cancer risk however there is controversy as to whether variants have a direct carcinogenic effect on lung cancer risk or impact indirectly through smoking behavior. We have performed a detailed analysis of the 15q25 risk variants rs12914385 and rs8042374 with smoking behavior and lung cancer risk in 4,343 lung cancer cases and 1,479 controls from the Genetic Lung Cancer Predisposition Study (GELCAPS). A strong association between rs12914385 and rs8042374, and lung cancer risk was shown, odds ratios (OR) were 1.44, (95% confidence interval (CI): 1.29–1.62, P = 3.69×10⁻¹⁰) and 1.35 (95% CI: 1.18–1.55, P = 9.99×10⁻⁶) respectively. Each copy of risk alleles at rs12914385 and rs8042374 was associated with increased cigarette consumption of 1.0 and 0.9 cigarettes per day (CPD) (P = 5.18×10⁻⁵ and P = 5.65×10⁻³). These genetically determined modest differences in smoking behavior can be shown to be sufficient to account for the 15q25 association with lung cancer risk. To further verify the indirect effect of 15q25 on the risk, we restricted our analysis of lung cancer risk to never-smokers and conducted a meta-analysis of previously published studies of lung cancer risk in never-smokers. Never-smoker studies published in English were ascertained from PubMed stipulating - lung cancer, risk, genome-wide association, candidate genes. Our study and five previously published studies provided data on 2,405 never-smoker lung cancer cases and 7,622 controls. In the pooled analysis no association has been found between the 15q25 variation and lung cancer risk (OR = 1.09, 95% CI: 0.94–1.28). This study affirms the 15q25 association with smoking and is consistent with an indirect link between genotype and lung cancer risk.     

Associations between Gene Expression Variations and Ovarian Cancer Risk Alleles Identified from Genome Wide Association Studies

Functional genetic variations play important roles in shaping phenotypic differences among individuals through affecting gene expression, and thus, very likely to influence disease susceptibility, such as cancer susceptibility. One critical question in this era of post-genome wide association studies (GWAS) is how to assess the functional significance of the genetic variations identified from GWAS. In the current study, with lymphoblastoid cell lines (LCLs) from 74 non-related women with familial ovarian cancer and 47 unrelated controls matched on gender and race, we explored the associations between seven ovarian cancer risk variants identified from GWAS (rs3814113 on 9p22.2, rs2072590 on 2q31, rs2665390 on 3q25, rs10088218, rs1516982, rs10098821 on 8q24.21, and rs2363956 on 19p13) and whole genome mRNA expression profiles. We observed 95 significant trans-associations at a permutation level of 0.001. Compared to the other risk variants, rs10088218, rs1516982, and rs10098821 on 8q24.21 had the greatest number of significant associations (25, 16, and 38, respectively). Two possible cis-associations were observed between rs10098821 and c-Myc, and rs2072590 and HS.565379 (Permutated P = 0.0198 and 0.0399, respectively). Pathway enrichment analysis showed that several key biological pathways, such as cell cycle (P = 2.59×10⁻⁰⁶), etc, were significantly overrepresented. Further characterization of significant associations between mRNAs and risk alleles might facilitate understanding the functions of GWAS discovered risk alleles in the genetic etiology of ovarian cancer.     

Pathway Analysis Based on a Genome-Wide Association Study of Polycystic Ovary Syndrome

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age, and it is affected by both environmental and genetic factors. Although the genetic component of PCOS is evident, studies aiming to identify susceptibility genes have shown controversial results. This study conducted a pathway-based analysis using a dataset obtained through a genome-wide association study (GWAS) to elucidate the biological pathways that contribute to PCOS susceptibility and the associated genes.

Methods

We used GWAS data on 636,797 autosomal single nucleotide polymorphisms (SNPs) from 1,221 individuals (432 PCOS patients and 789 controls) for analysis. A pathway analysis was conducted using meta-analysis gene-set enrichment of variant associations (MAGENTA). Top-ranking pathways or gene sets associated with PCOS were identified, and significant genes within the pathways were analyzed.

Results

The pathway analysis of the GWAS dataset identified significant pathways related to oocyte meiosis and the regulation of insulin secretion by acetylcholine and free fatty acids (all nominal gene-set enrichment analysis (GSEA) P-values < 0.05). In addition, INS, GNAQ, STXBP1, PLCB3, PLCB2, SMC3 and PLCZ1 were significant genes observed within the biological pathways (all gene P-values < 0.05).

Conclusions

By applying MAGENTA pathway analysis to PCOS GWAS data, we identified significant pathways and candidate genes involved in PCOS. Our findings may provide new leads for understanding the mechanisms underlying the development of PCOS.     

Whole-Genome Sequencing of Individuals from a Founder Population Identifies Candidate Genes for Asthma

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.     

Genetic Variants on Chromosome 1p13.3 Are Associated with Non-ST Elevation Myocardial Infarction and the Expression of DRAM2 in the Finnish Population

Myocardial infarction (MI) is divided into either ST elevation MI (STEMI) or non-ST elevation MI (NSTEMI), differing in a number of clinical characteristics. We sought to identify genetic variants conferring risk to NSTEMI or STEMI by conducting a genome-wide association study (GWAS) of MI stratified into NSTEMI and STEMI in a consecutive sample of 1,579 acute MI cases with 1,576 controls. Subsequently, we followed the results in an independent population-based sample of 562 cases and 566 controls, a partially independent prospective cohort (N = 16,627 with 163 incident NSTEMI cases), and examined the effect of disease-associated variants on gene expression in 513 healthy participants. Genetic variants on chromosome 1p13.3 near the damage-regulated autophagy modulator 2 gene DRAM2 associated with NSTEMI (rs656843; odds ratio 1.57, P = 3.11 × 10⁻¹⁰) in the case-control analysis with a consistent but not statistically significant effect in the prospective cohort (rs656843; hazard ratio 1.13, P = 0.43). These variants were not associated with STEMI (rs656843; odds ratio, 1.11, P = 0.20; hazard ratio 0.97, P = 0.87), appearing to have a pronounced effect on NSTEMI risk. A majority of the variants at 1p13.3 associated with NSTEMI were also associated with the expression level of DRAM2 in blood leukocytes of healthy controls (top-ranked variant rs325927, P = 1.50 × 10⁻¹²). The results suggest that genetic factors may in part influence whether coronary artery disease results in NSTEMI rather than STEMI.     

Transcriptome Profiling of Human Ulcerative Colitis Mucosa Reveals Altered Expression of Pathways Enriched in Genetic Susceptibility Loci

Human colonic mucosa altered by inflammation due to ulcerative colitis (UC) displays a drastically altered pattern of gene expression compared with healthy tissue. We aimed to understand the underlying molecular pathways influencing these differences by analyzing three publically-available, independently-generated microarray datasets of gene expression from endoscopic biopsies of the colon. Gene set enrichment analysis (GSEA) revealed that all three datasets share 87 gene sets upregulated in UC lesions and 8 gene sets downregulated (false discovery rate <0.05). The upregulated pathways were dominated by gene sets involved in immune function and signaling, as well as the control of mitosis. We applied pathway analysis to genotype data derived from genome-wide association studies (GWAS) of UC, consisting of 5,584 cases and 11,587 controls assembled from eight European-ancestry cohorts. The upregulated pathways derived from the gene expression data showed a highly significant overlap with pathways derived from the genotype data (33 of 56 gene sets, hypergeometric P = 1.49×10^–19). This study supports the hypothesis that heritable variation in gene expression as measured by GWAS signals can influence key pathways in the development of disease, and that comparison of genetic susceptibility loci with gene expression signatures can differentiate key drivers of inflammation from secondary effects on gene expression of the inflammatory process.