Amos, Christopher I.

Abstract Recently, Wilson et al. (doi:10.1038/onc.2013.396) found that EYA4 was frequently inactivated biallelically in sporadic lung cancer, displays tumor suppressor gene-like properties and affects DNA repair, and that 5 of 17 common SNPs in this 0.3Mb region showed nominal association to familial lung cancer (FLC, p<0.05) although these associations are not genome-wide significant after correction for multiple testing.. However, this is an interesting candidate gene for FLC risk because it is located on chromosome 6q in a region where we previously showed evidence of linkage to FLC (PMID: 15272417, 20215501). Here, we sequenced 75 individuals from our 9 most strongly 6q-linked families, using Illumina technology and a custom Agilent kit to capture 37Mb of chromosome 6 from 130Mb to 167Mb. We closely examined a region around EYA4, between 133Mb and 135Mb. This region contains a number of other genes in addition to EYA4, including the Vanin cluster; ribosomal protein S12; the tumor suppressor gene TCF21 and its antisense RNA TARID which directs methylation and activation of TCF21; solute carriers SLC18B1 and SLC2A12 and the serum/glucocorticoid regulated kinase SGK1. To detect sharing of variants among affecteds in each family while allowing for phenocopies, singlepoint affected-only linkage analysis was performed on lung cancer affection status for all sequence variants using the Elston-Stewart algorithm implemented in the R package paramlink assuming penetrance of 0.01, 0.1 and 0.1 for dd/Dd/DD and a disease allele (D) frequency of 0.01, at a recombination fraction (theta) of 0. The highest total LOD score (summed over all 9 families) in the entire 37Mb targeted region was not near EYA4. In only one family was there any variant in EYA4 that appeared on the linked haplotype with close to the highest family-specific LOD score: Family 30 had a LOD of 0.6514 at several EYA4 variants (max LOD across region 0.6519). However, many variants across the region had similar LODs. In the remaining families, all EYA4 variants had LODs much lower than the maximum family-specific LOD score in the region. Thus, EYA4 variants are unlikely to explain our 6q linkage peak in these 6q-linked families. The second highest total LOD score for the entire 37Mb targeted region was found near EYA4 at 133.9Mb (LOD = 3.82), in the middle of the TARID antisense RNA gene. This variant appears to be entirely novel, as it is not present in any of the online variant databases, such as NHLBI's ESP or 1000 Genomes. In two families, the family LOD score at this locus was at or close to the highest in the region: in Family 44 the LOD score was 1.206 (max LOD across entire region 1.207) and in Family 35 the LOD score was 0.3958 (max LOD across region 0.3959). Therefore this variant in the TARID antisense RNA is a candidate in some of our families most strongly linked to chromosome 6q. Citation Format: Joan E. Bailey-Wilson, Claire L. Simpson, Susan M. Pinney, Mariza de Andrade, Colette Gaba, Ping Yang, Ming You, Elena Y. Kupert, Ann G. Schwartz, Diptasri Mandal, Christopher I. Amos, Marshall W. Anderson. Evaluation of EYA4 as a candidate risk locus in familial lung cancer families linked to 6q. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2757. doi:10.1158/1538-7445.AM2015-2757

Abstract To identify genetic variants that contribute to colorectal cancer (CRC) susceptibility, we performed a meta-analysis of two genome-wide association studies in 2,627 cases and 3,797 controls of Japanese ancestry and 1,894 cases and 4,703 controls of African ancestry, followed by a replication of genome-wide statistically significant associations (P < 5E-8) in 16,823 cases and 18,211 controls of European ancestry. This study revealed a new pan-ethnic CRC risk locus at 10q25 (rs12241008, intronic to VTI1A; P=1.5E-9), providing additional insight into the etiology of CRC and highlighting the value of association mapping in diverse populations. Citation Format: Hansong Wang, Terrilea Burnett, Suminori Kono, Christopher Haiman, Motoki Iwasaki, Lynne Wilkens, Lenora Loo, David Van Den Berg, Laurence Kolonel, Brian Henderson, Temitope Keku, Robert Sandler, Lisa Signorello, William Blot, Polly Newcomb, Mala Pande, Christopher Amos, Dee West, Stéphane Bézieau, Sonja Berndt, Brent Zanke, Li Hsu, Noralane Lindor, Robert Haile, John Hopper, Mark Jenkins, Steven Gallinger, Graham Casey, Stephanie Stenzel, Fredrick Schumacher, Ulrike Peters, Stephen Gruber, Shoichiro Tsugane, Dan Stram, Loic Le Marchand. Transethnic genome-wide association study of colorectal cancer identifies a new susceptibility locus in VTI1A. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-282. doi:10.1158/1538-7445.AM2014-LB-282

Abstract Introduction Pancreatic cancer is a highly lethal malignancy due to late diagnosis and aggressiveness of the tumor. Characterization of high-risk populations for monitoring, intervention and early detection remains challenging. Obesity and diabetes are potentially modifiable contributors to pancreatic cancer. Genetic factors modifying the risk of obesity- and diabetes-induced pancreatic cancer have previously not been fully investigated at the genome-wide level. Hypothesis There are potential genetic factors modifying the associations between obesity/diabetes and pancreatic cancer. Methods Integrating genotype with risk factor data from a GWAS for the Pancreatic Cancer Case Control Consortium, we performed a genome-wide gene-environment interaction (G x E) scan for 457,688 SNPs in a discovery study of 2,028 cases and 2,109 controls using state-of-the-art methods including case-only (CO), case-control (CC), Empirical Hierarchical Bayes (EHB), Empirical-Bayes test (EB) and three 2-step approaches (DG2, EG2, DGEG2). Results We detected a genome-wide significant (P < 1.09 x 10-7 ) interaction of diabetes with rs13061928 (in CNTN4) in CO (P = 8.8 x 10-8 ), which was independent of diabetes in control group (P = 0.08). The minor allele was in a synergism with diabetes on the cancer risk: diabetics carrying GA/AA genotype had a 3.39-fold (95% CI: 2.47-4.65) increased disease risk compared with non-diabetics carrying GG genotype. Consistently, the SNP-diabetes interaction had a high ranking statistic in EHB (No.1) and high p-value ranks for EG2 and DGEG2 methods (No.1, P= 5.44 x 10-5). Conclusions These observations, once validated/confirmed, may help define at-risk subpopulation and initiate targeted intervention and prevention of pancreatic cancer. Genome-wide G x E analysis requires larger sample size than genetic main effects scan; combining the CO method with alternative methods may be the optimal scheme for genome-wide G x E analysis. Citation Format: Hongwei Tang, Eric J. Duell, Harvey A. Risch Risch, Sara H. Olson, H. Bas Bueno-de-Mesquita, Steven Gallinger, Elizabeth A. Holly, Gloria M. Petersen, Paige M. Bracci, Robert R. McWilliams, Mazda Jenab, Elio Riboli, Anne Tjønneland, Marie Christine Boutron-Ruault, Rudolf Kaaks, Dimitrios Trichopoulos, Salvatore Panico, Malin Sund, Petra H. M Peeters, Kay-Tee Khaw, Christopher I Amos, Donghui Li, Peng Wei. Genome-wide gene-diabetes and gene-obesity interaction scan in the pancreatic cancer case control consortium. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2214. doi:10.1158/1538-7445.AM2014-2214

Abstract In order to select samples that are optimally informative for sequence analysis, studies for the Genetic Epidemiology Consortium, we implemented three strategies for analysis, taking into account the known family histories of lung cancer. Susceptibility for lung cancer arises from a complex interplay between largely unknown genetic factors and smoking behavior. In order to optimize our ability to identify genetic factors for lung cancer we have recruited individuals with extensive family histories of lung cancer and also collected information about their smoking behaviors. For this study, we have modeled family history to identify individuals to select for sequencing using three approaches. First, we used an expert opinion approach in which multiple investigators evaluated pedigree structures with family history to reach a consensus priority in selecting individuals. Second we developed an approximation that assumes a low penetrance among noncarriers and uses known cancer status in first degree relatives. Third, we used the cancer, smoking behaviors and family information along with a likelihood that models penetrance according to genetic susceptibility and an interaction with smoking to estimate the probabilities individuals carry susceptibility factors. In this analysis we compare results among these methods. We evaluate effectiveness of these methods using simulation-based approaches. Citation Format: Christopher Amos, Joan Bailey-Wilson, Susan Pinney, Maria de Andrada, Colette Gaba, Diptasri Mandal, Ming You, Margaret Spitz, Marshall Anderson. Optimal strategies for selecting samples for sequencing families with a common cancer: The Genetic Epidemiology of Lung Cancer Consortium. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr A106.

ObjectiveTo identify new genetic associations with juvenile and adult dermatomyositis (DM).MethodsWe performed a genome‐wide association study (GWAS) of adult and juvenile DM patients of European ancestry (n = 1,178) and controls (n = 4,724). To assess genetic overlap with other autoimmune disorders, we examined whether 141 single‐nucleotide polymorphisms (SNPs) outside the major histocompatibility complex (MHC) locus, and previously associated with autoimmune diseases, predispose to DM.ResultsCompared to controls, patients with DM had a strong signal in the MHC region consisting of GWAS‐level significance (P < 5 × 10–8) at 80 genotyped SNPs. An analysis of 141 non‐MHC SNPs previously associated with autoimmune diseases showed that 3 SNPs linked with 3 genes were associated with DM, with a false discovery rate (FDR) of <0.05. These genes were phospholipase C–like 1 (PLCL1; rs6738825, FDR = 0.00089), B lymphoid tyrosine kinase (BLK; rs2736340, FDR = 0.0031), and chemokine (C‐C motif) ligand 21 (CCL21; rs951005, FDR = 0.0076). None of these genes was previously reported to be associated with DM.ConclusionOur findings confirm the MHC as the major genetic region associated with DM and indicate that DM shares non‐MHC genetic features with other autoimmune diseases, suggesting the presence of additional novel risk loci. This first identification of autoimmune disease genetic predispositions shared with DM may lead to enhanced understanding of pathogenesis and novel diagnostic and therapeutic approaches.

ObjectiveTo identify genetic determinants of granulomatosis with polyangiitis (Wegener's) (GPA).MethodsWe carried out a genome‐wide association study (GWAS) of 492 GPA cases and 1,506 healthy controls (white subjects of European descent), followed by replication analysis of the most strongly associated signals in an independent cohort of 528 GPA cases and 1,228 controls.ResultsGenome‐wide significant associations were identified in 32 single‐nucleotide polymorphic (SNP) markers across the HLA region, the majority of which were located in the HLA–DPB1 and HLA–DPA1 genes encoding the class II major histocompatibility complex (MHC) DPβ chain 1 and DPα chain 1 proteins, respectively. Peak association signals in these 2 genes, emanating from SNPs rs9277554 (for DPβ chain 1) and rs9277341 (DPα chain 1) were strongly replicated in an independent cohort (in the combined analysis of the initial cohort and the replication cohort, P = 1.92 × 10−50 and 2.18 × 10−39, respectively). Imputation of classic HLA alleles and conditional analyses revealed that the SNP association signal was fully accounted for by the classic HLA–DPB1*04 allele. An independent single SNP, rs26595, near SEMA6A (the gene for semaphorin 6A) on chromosome 5, was also associated with GPA, reaching genome‐wide significance in a combined analysis of the GWAS and replication cohorts (P = 2.09 × 10−8).ConclusionWe identified the SEMA6A and HLA–DP loci as significant contributors to risk for GPA, with the HLA–DPB1*04 allele almost completely accounting for the MHC association. These two associations confirm the critical role of immunogenetic factors in the development of GPA.

Background —The renin-angiotensin system regulates blood pressure through its effects on vascular tone, renal hemodynamics, and renal sodium and fluid balance. Methods and Results —Using data from a large population-based sample of 1488 siblings having a mean age of 14.8 years and belonging to the youngest generation of 583 randomly ascertained three-generation pedigrees from Rochester, Minn, we carried out variance components–based linkage analyses to evaluate the contribution of variation in four renin-angiotensin system gene regions (angiotensinogen, renin, angiotensin I–converting enzyme, and angiotensin II receptor type 1) to interindividual variation in systolic, diastolic, and mean arterial pressure. We rejected the null hypothesis that allelic variation in the region of the angiotensin-converting enzyme ( ACE ) gene does not contribute to interindividual blood pressure variability. After conditioning on measured covariates, variation in this region accounted for 0%, 13% ( P =0.04), and 16% ( P =0.04) of the interindividual variance in systolic, diastolic, and mean arterial pressures, respectively. These estimates were even greater in a subset of subjects with a positive family history of hypertension (0%, 29% [ P =0.005], and 32% [ P <0.005], respectively). In sex-specific analyses, genetic variation in the region of the ACE gene significantly influenced interindividual blood pressure variation in males (37% for SBP [ P =0.03], 38% for DBP [ P =0.04], and 53% for MAP [ P <0.005]) but not in females. Conclusions —Although it is possible that variation in a gene near the ACE gene may explain the observed results, knowledge about the physiological involvement of ACE in blood pressure regulation supports the proposition that the ACE gene itself influences blood pressure variability in a sex-specific manner.

AbstractOver the past several years, genome‐wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large‐Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large‐scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene‐gene and gene‐environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.Genet. Epidemiol. 36 : 22–35, 2012. © 2011 Wiley Periodicals, Inc.

AbstractLung cancer in lifetime never smokers is distinct from that in smokers, but the role of separate or overlapping carcinogenic pathways has not been explored. We therefore evaluated a comprehensive panel of 11,737 single-nucleotide polymorphisms (SNP) in inflammatory-pathway genes in a discovery phase (451 lung cancer cases, 508 controls from Texas). SNPs that were significant were evaluated in a second external population (303 cases, 311 controls from the Mayo Clinic). An intronic SNP in the ACVR1B gene, rs12809597, was replicated with significance and restricted to those reporting adult exposure to environmental tobacco smoke. Another promising candidate was an SNP in NR4A1, although the replication OR did not achieve statistical significance. ACVR1B belongs to the TGFR-β superfamily, contributing to resolution of inflammation and initiation of airway remodeling. An inflammatory microenvironment (second-hand smoking, asthma, or hay fever) is necessary for risk from these gene variants to be expressed. These findings require further replication, followed by targeted resequencing, and functional validation.Significance: Beyond passive smoking and family history of lung cancer, little is known about the etiology of lung cancer in lifetime never smokers that accounts for about 15% of all lung cancers in the United States. Our two-stage candidate pathway approach examined a targeted panel of inflammation genes and has identified novel structural variants that appear to contribute to risk in patients who report prior exposure to sidestream smoking. Cancer Discovery; 1(5): 420–9. ©2011 AACR.This article is highlighted in the In This Issue feature, p. 367

Abstract Background: Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity. Methods: We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage. Results: A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23–25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31–q33, 14q11, and 16q24. Conclusions: Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers. Impact: OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci. Cancer Epidemiol Biomarkers Prev; 19(12); 3157–66. ©2010 AACR.