Constrained Score Statistics Identify Genetic Variants Interacting with Multiple Risk Factors in Barrett's Esophagus

Likelihood-based inference under nonconvex boundary constraints

Likelihood-based inference under nonconvex constraints on model parameters has become increasingly common in biomedical research. In this paper, we establish large-sample properties of the maximum likelihood estimator when the true parameter value lies at the boundary of a nonconvex parameter space. We further derive the asymptotic distribution of the likelihood ratio test statistic under nonconvex constraints on model parameters. A general Monte Carlo procedure for generating the limiting distribution is provided. The theoretical results are demonstrated by five examples in Anderson's stereotype logistic regression model, genetic association studies, gene-environment interaction tests, cost-constrained linear regression and fairness-constrained linear regression.

eQTL Set-Based Association Analysis Identifies Novel Susceptibility Loci for Barrett Esophagus and Esophageal Adenocarcinoma

BACKGROUND

Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett esophagus (BE), explaining a small portion of heritability.

METHODS

Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene-expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression.

RESULTS

Although the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641, and HSP90AA1).

CONCLUSIONS

This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set-based genetic association approach.

IMPACT

This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set-based genetic association approach as an alternative method for TWAS analysis.

A risk variant for Barrett's esophagus and esophageal adenocarcinoma at chr8p23.1 affects enhancer activity and implicates multiple gene targets

Nineteen genetic susceptibility loci for esophageal adenocarcinoma (EAC) and its precursor Barrett's esophagus (BE) have been identified through genome-wide association studies (GWAS). Clinical translation of such discoveries, however, has been hindered by the slow pace of discovery of functional/causal variants and gene targets at these loci. We previously developed a systematic informatics pipeline to prioritize candidate functional variants using functional potential scores, applied the pipeline to select high-scoring BE/EAC risk loci, and validated a functional variant at chr19p13.11 (rs10423674). Here, we selected two additional prioritized loci for experimental interrogation: chr3p13/rs1522552 and chr8p23.1/rs55896564. Candidate enhancer regions encompassing these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two regions tested exhibited allele-specific enhancer activity - 8p23.1/rs55896564. CRISPR-mediated deletion of the putative enhancer in EAC cell lines correlated with reduced expression of three candidate gene targets: B lymphocyte kinase (BLK), nei like DNA glycosylase 2 (NEIL2), and cathepsin B (CTSB). Expression quantitative trait locus (eQTL) mapping in normal esophagus and stomach revealed strong associations between the BE/EAC risk allele at rs55896564 (G) and lower expression of CTSB, a protease gene implicated in epithelial wound repair. These results further support the utility of functional potential scores for GWAS variant prioritization, and provide the first experimental evidence of a functional variant and risk enhancer at the 8p23.1 GWAS locus. Identification of CTSB, BLK, and NEIL2 as candidate gene targets suggests that altered expression of these genes may underlie the genetic risk association at 8p23.1 with BE/EAC.

Prioritization and functional analysis of GWAS risk loci for Barrett's esophagus and esophageal adenocarcinoma

Genome-wide association studies (GWAS) have identified ~ 20 genetic susceptibility loci for esophageal adenocarcinoma (EAC), and its precursor, Barrett's esophagus (BE). Despite such advances, functional/causal variants and gene targets at these loci remain undefined, hindering clinical translation. A key challenge is that most causal variants map to non-coding regulatory regions such as enhancers, and typically, numerous potential candidate variants at GWAS loci require testing. We developed a systematic informatics pipeline for prioritizing candidate functional variants via integrative functional potential scores consolidated from multi-omics annotations, and used this pipeline to identify two high-scoring variants for experimental interrogation: chr9q22.32/rs11789015 and chr19p13.11/rs10423674. Minimal candidate enhancer regions spanning these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two variants tested (rs10423674) exhibited allele-specific enhancer activity. CRISPR-mediated deletion of the putative enhancer region in EAC cell lines correlated with reduced expression of two genes-CREB-regulated transcription coactivator 1 (CRTC1) and Cartilage oligomeric matrix protein (COMP); expression of five other genes remained unchanged (CRLF1, KLHL26, TMEM59L, UBA52, RFXANK). Expression quantitative trait locus (eQTL) mapping indicated that rs10423674 genotype correlated with CRTC1 and COMP expression in normal esophagus. This study represents the first experimental effort to bridge GWAS associations to biology in BE/EAC, and supports the utility of functional potential scores to guide variant prioritization. Our findings reveal a functional variant and candidate risk enhancer at chr19p13.11, and implicate CRTC1 and COMP as putative gene targets, suggesting that altered expression of these genes may underlie the BE/EAC risk association.

Visceral Obesity, Metabolic Syndrome, and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) represents an exemplar of obesity-associated carcinogenesis, with a progressive increase in EAC risk with increased body mass index. In this context, there is increased focus on visceral adipose tissue and associated metabolic dysfunction, including hypertension, diabetes mellitus and hyperlipidemia, or combinations of these in the metabolic syndrome. Visceral obesity (VO) may promote EAC via both directly impacting on gastro-esophageal reflux disease and Barrett's esophagus, as well as via reflux-independent effects, involving adipokines, growth factors, insulin resistance, and the microbiome. In this review these pathways are explored, including the impact of VO on the tumor microenvironment, and on cancer outcomes. The current evidence-based literature regarding the role of dietary, lifestyle, pharmacologic and surgical interventions to modulate the risk of EAC is explored.

Gene-Environment Interactions and the Risk of Barrett's Esophagus in Three US Cohorts

OBJECTIVES

Several single-nucleotide polymorphisms (SNPs) have been associated with Barrett's esophagus (BE) risk. In addition, environmental factors including smoking, alcohol consumption, and heartburn increase BE risk. However, data on potential interactions between these genetic and environmental factors on BE risk are scant. Understanding how genes and environmental risk factors interact may provide key insight into the pathophysiology of BE, and potentially identify opportunities for targeted prevention and treatment. The objectives of this study were to examine the main effects and the potential effect modification between known genetic loci (SNPs) and established environmental risk factors for BE.

METHODS

We performed a nested case-control study using data on 401 incident BE cases and 436 age-matched controls from the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study cohorts, who gave blood and completed biennial questionnaires. Overall, we genotyped 46 SNPs identified in previous BE genome-wide association studies as well as SNPs in candidate genes related to BE susceptibility (i.e., related to excess body fat, fat distribution, factors associated with insulin resistance, and inflammatory mediators). A genetic risk score (GRS) was constructed to evaluate the combined effect of the selected SNPs on BE risk. Interactions between SNPs and BE risk factors were also assessed.

RESULTS

We observed a suggestive, but not statistically significant, association between our GRS and BE risk: a one-allele increase in the unweighted GRS increased the risk of BE by a factor of 1.20 (95% confidence interval = 1.00-1.44; P = 0.057). We did not observe any meaningful multiplicative interactions between smoking, alcohol consumption, or heartburn duration and BE genotypes. When we assessed the joint effect of weighted GRS and BE risk factors, we did not observe any significant interaction with alcohol and heartburn duration, whereas smoking showed a significant multiplicative interaction (P = 0.016).

CONCLUSIONS

Our results suggest that SNPs associated with BE at genome-wide significant levels can be combined into a GRS with a potential positive association with BE risk.

The Evolving Genomic Landscape of Barrett's Esophagus and Esophageal Adenocarcinoma

We have recently gained unprecedented insight into genetic factors that determine risk for Barrett's esophagus (BE) and progression to esophageal adenocarcinoma (EA). Next-generation sequencing technologies have allowed us to identify somatic mutations that initiate BE and track genetic changes during development of tumors and invasive cancer. These technologies led to identification of mechanisms of tumorigenesis that challenge the current multistep model of progression to EA. Newer, cost-effective technologies create opportunities to rapidly translate the analysis of DNA into tools that can identify patients with BE at high risk for cancer, detect dysplastic lesions more reliably, and uncover mechanisms of carcinogenesis.