Dataset Information

Germline genetic contributions to risk for esophageal adenocarcinoma, Barrett's esophagus, and gastroesophageal reflux.

ABSTRACT:

Background

Esophageal adenocarcinoma (EA) is an increasingly common cancer with poor survival. Barrett's esophagus (BE) is the main precursor to EA, and every year 0.12% to 0.5% of BE patients progress to EA. BE typically arises on a background of chronic gastroesophageal reflux (GERD), one of the risk factors for EA.

Methods

We used genome-wide association data to investigate the genetic architecture underlying GERD, BE, and EA. We applied a method to estimate the variance explained (array heritability, h(2)g) and the genetic correlation (rg) between GERD, BE, and EA by considering all single nucleotide polymorphisms (SNPs) simultaneously. We also estimated the polygenic overlap between GERD, BE, and EA using a prediction approach. All tests were two-sided, except in the case of variance-explained estimation where one-sided tests were used.

Results

We estimated a statistically significant genetic variance explained for BE (h(2)g = 35%; standard error [SE] = 6%; one-sided P = 1 × 10(-9)) and for EA (h(2)g = 25 %; SE = 5%; one-sided P = 2 × 10(-7)). The genetic correlation between BE and EA was found to be high (rg = 1.0; SE = 0.37). We also estimated a statistically significant polygenic overlap between BE and EA (one-sided P = 1 × 10(-6)), which suggests, together with the high genetic correlation, that shared genes underlie the development of BE and EA. Conversely, no statistically significant results were obtained for GERD.

Conclusions

We have demonstrated that risk to BE and EA is influenced by many germline genetic variants of small effect and that shared polygenic effects contribute to risk of these two diseases.

SUBMITTER: Ek WE

PROVIDER: S-EPMC3833931 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND & AIMS:Genome-wide association studies (GWAS) have identified more than 20 susceptibility loci for esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). However, variants in these loci account for a small fraction of cases of EA and BE. Genetic factors might interact with environmental factors to affect risk of EA and BE. We aimed to identify single nucleotide polymorphisms (SNPs) that may modify the associations of body mass index (BMI), smoking, and gastroesophageal reflux disease (GERD), with risks of EA and BE. METHODS:We collected data on single BMI measurements, smoking status, and symptoms of GERD from 2284 patients with EA, 3104 patients with BE, and 2182 healthy individuals (controls) participating in the Barrett's and Esophageal Adenocarcinoma Consortium GWAS, the UK Barrett's Esophagus Gene Study, and the UK Stomach and Oesophageal Cancer Study. We analyzed 993,501 SNPs in DNA samples of all study subjects. We used standard case-control logistic regression to test for gene-environment interactions. RESULTS:For EA, rs13429103 at chromosome 2p25.1, near the RNF144A-LOC339788 gene, showed a borderline significant interaction with smoking status (P = 2.18×10-7). Ever smoking was associated with an almost 12-fold increase in risk of EA among individuals with rs13429103-AA genotype (odds ratio=11.82; 95% CI, 4.03-34.67). Three SNPs (rs12465911, rs2341926, rs13396805) at chromosome 2q23.3, near the RND3-RBM43 gene, interacted with GERD symptoms (P = 1.70×10-7, P = 1.83×10-7, and P = 3.58×10-7, respectively) to affect risk of EA. For BE, rs491603 at chromosome 1p34.3, near the EIF2C3 gene, and rs11631094 at chromosome 15q14, at the SLC12A6 gene, interacted with BMI (P = 4.44×10-7) and pack-years of smoking history (P = 2.82×10-7), respectively. CONCLUSION:The associations of BMI, smoking, and GERD symptoms with risks of EA and BE appear to vary with SNPs at chromosomes 1, 2, and 15. Validation of these suggestive interactions is warranted.

Project description:BACKGROUND & AIMS:We developed comprehensive models to determine risk of Barrett's esophagus (BE) or esophageal adenocarcinoma (EAC) based on genetic and non-genetic factors. METHODS:We used pooled data from 3288 patients with BE, 2511 patients with EAC, and 2177 individuals without either (controls) from participants in the international Barrett's and EAC consortium as well as the United Kingdom's BE gene study and stomach and esophageal cancer study. We collected data on 23 genetic variants associated with risk for BE or EAC, and constructed a polygenic risk score (PRS) for cases and controls by summing the risk allele counts for the variants weighted by their natural log-transformed effect estimates (odds ratios) extracted from genome-wide association studies. We also collected data on demographic and lifestyle factors (age, sex, smoking, body mass index, use of nonsteroidal anti-inflammatory drugs) and symptoms of gastroesophageal reflux disease (GERD). Risk models with various combinations of non-genetic factors and the PRS were compared for their accuracy in identifying patients with BE or EAC using the area under the receiver operating characteristic curve (AUC) analysis. RESULTS:Individuals in the highest quartile of risk, based on genetic factors (PRS), had a 2-fold higher risk of BE (odds ratio, 2.22; 95% confidence interval, 1.89-2.60) or EAC (odds ratio, 2.46; 95% confidence interval, 2.07-2.92) than individual in the lowest quartile of risk based on PRS. Risk models developed based on only demographic or lifestyle factors or GERD symptoms identified patients with BE or EAC with AUC values ranging from 0.637 to 0.667. Combining data on demographic or lifestyle factors with data on GERD symptoms identified patients with BE with an AUC of 0.793 and patients with EAC with an AUC of 0.745. Including PRSs with these data only minimally increased the AUC values for BE (to 0.799) and EAC (to 0.754). Including the PRSs in the model developed based on non-genetic factors resulted in a net reclassification improvement for BE of 3.0% and for EAC of 5.6%. CONCLUSIONS:We used data from 3 large databases of patients from studies of BE or EAC to develop a risk prediction model based on genetic, clinical, and demographic/lifestyle factors. We identified a PRS that increases discrimination and net reclassification of individuals with vs without BE and EAC. However, the absolute magnitude of improvement is not sufficient to justify its clinical use.