Elston, Robert C.

AbstractBackgroundFamilial aggregation and segregation analysis studies have provided evidence of a genetic basis for esophageal adenocarcinoma (EAC) and its premalignant precursor, Barrett's esophagus (BE). We aim to demonstrate the utility of linkage analysis to identify the genomic regions that might contain the genetic variants that predispose individuals to this complex trait (BE and EAC).MethodsWe genotyped 144 individuals in 42 multiplex pedigrees chosen from 1000 singly ascertained BE/EAC pedigrees, and performed both model‐based and model‐free linkage analyses, using S.A.G.E. and other software. Segregation models were fitted, from the data on both the 42 pedigrees and the 1000 pedigrees, to determine parameters for performing model‐based linkage analysis. Model‐based and model‐free linkage analyses were conducted in two sets of pedigrees: the 42 pedigrees and a subset of 18 pedigrees with female affected members that are expected to be more genetically homogeneous. Genome‐wide associations were also tested in these families.ResultsLinkage analyses on the 42 pedigrees identified several regions consistently suggestive of linkage by different linkage analysis methods on chromosomes 2q31, 12q23, and 4p14. A linkage on 15q26 is the only consistent linkage region identified in the 18 female‐affected pedigrees, in which the linkage signal is higher than in the 42 pedigrees. Other tentative linkage signals are also reported.ConclusionOur linkage study of BE/EAC pedigrees identified linkage regions on chromosomes 2, 4, 12, and 15, with some reported associations located within our linkage peaks. Our linkage results can help prioritize association tests to delineate the genetic determinants underlying susceptibility to BE and EAC.

Abstract Background: Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. Methods: We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Results: Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Conclusions: Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Impact: Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727–35. ©2016 AACR.

Current genome‐wide association studies still heavily rely on a single‐marker strategy, in which each single nucleotide polymorphism (SNP) is tested individually for association with a phenotype. Although methods and software packages that consider multimarker models have become available, they have been slow to become widely adopted and their efficacy in real data analysis is often questioned. Based on conducting extensive simulations, here we endeavor to provide more insights into the performance of simple multimarker association tests as compared to single‐marker tests. The results reveal the power advantage as well as disadvantage of the two‐ vs. the single‐marker test. Power differentials depend on the correlation structure among tag SNPs, as well as that between tag SNPs and causal variants. A two‐marker test has relatively better performance than single‐marker tests when the correlation of the two adjacent markers is high. However, using HapMap data, two‐marker tests tended to have a greater chance of being less powerful than single‐marker tests, due to constraints on the number of actual possible haplotypes in the HapMap data. Yet, the average power difference was small whenever the one‐marker test is more powerful, while there were many situations where the two‐marker test can be much more powerful. These findings can be useful to guide analyses of future studies. Genet. Epidemiol. 36:480‐487, 2012. © 2012 Wiley Periodicals, Inc.

Abstract Background: Genetic influences may be discerned in families that have multiple affected members and may manifest as an earlier age of cancer diagnosis. In this study, we determine whether cancers develop at an earlier age in multiplex Familial Barrett's Esophagus (FBE) kindreds, defined by 3 or more members affected by Barrett's esophagus (BE) or esophageal adenocarcinoma (EAC). Methods: Information on BE/EAC risk factors and family history was collected from probands at eight tertiary care academic hospitals. Age of cancer diagnosis and other risk factors were compared between nonfamilial (no affected relatives), duplex (two affected relatives), and multiplex (three or more affected relatives) FBE kindreds. Results: The study included 830 nonfamilial, 274 duplex, and 41 multiplex FBE kindreds with 274, 133, and 43 EAC and 566, 288, and 103 BE cases, respectively. Multivariable mixed models adjusting for familial correlations showed that multiplex kindreds were associated with a younger age of cancer diagnosis (P = 0.0186). Median age of cancer diagnosis was significantly younger in multiplex compared with duplex and nonfamilial kindreds (57 vs. 62 vs. 63 years, respectively, P = 0.0448). Mean body mass index was significantly lower in multiplex kindreds (P = 0.0033), as was smoking (P < 0.0001), and reported regurgitation (P = 0.0014). Conclusions: Members of multiplex FBE kindreds develop EAC at an earlier age compared with nonfamilial EAC cases. Multiplex kindreds do not have a higher proportion of common risk factors for EAC, suggesting that this aggregation might be related to a genetic factor. Impact: These findings indicate that efforts to identify susceptibility genes for BE and EAC will need to focus on multiplex kindreds. Cancer Epidemiol Biomarkers Prev; 21(2); 376–83. ©2011 AACR.

Abstract Genetic risk factors are important contributors to the development of colorectal cancer. Following the definition of a linkage signal at 9q22-31, we fine mapped this region in an independent collection of colon cancer families. We used a custom array of single-nucleotide polymorphisms (SNP) densely spaced across the candidate region, performing both single-SNP and moving-window association analyses to identify a colon neoplasia risk haplotype. Through this approach, we isolated the association effect to a five-SNP haplotype centered at 98.15 Mb on chromosome 9q. This haplotype is in strong linkage disequilibrium with the haplotype block containing HABP4 and may be a surrogate for the effect of this CD30 Ki-1 antigen. It is also in close proximity to GALNT12, also recently shown to be altered in colon tumors. We used a predictive modeling algorithm to show the contribution of this risk haplotype and surrounding candidate genes in distinguishing between colon cancer cases and healthy controls. The ability to replicate this finding, the strength of the haplotype association (odds ratio, 3.68), and the accuracy of our prediction model (∼60%) all strongly support the presence of a locus for familial colon cancer on chromosome 9q. Cancer Res; 70(13); 5409–18. ©2010 AACR.