Genome-wide diet-gene interaction analyses for risk of colorectal cancer

Decoding the genetic and environmental forces in propelling the surge of early-onset colorectal cancer

ABSTRACT

Early-onset colorectal cancer (EOCRC) shows a different epidemiological trend compared to later-onset colorectal cancer, with its incidence rising in most regions and countries worldwide. However, the reasons behind this trend remain unclear. The etiology of EOCRC is complex and could involve both genetic and environmental factors. Apart from Lynch syndrome and Familial Adenomatous Polyposis, sporadic EOCRC exhibits a broad spectrum of pathogenic germline mutations, genetic polymorphisms, methylation changes, and chromosomal instability. Early-life exposures and environmental risk factors, including lifestyle and dietary risk factors, have been found to be associated with EOCRC risk. Meanwhile, specific chronic diseases, such as inflammatory bowel disease, diabetes, and metabolic syndrome, have been associated with EOCRC. Interactions between genetic and environmental risk factors in EOCRC have also been explored. Here we present findings from a narrative review of epidemiological studies on the assessment of early-life exposures, of EOCRC-specific environmental factors, and their interactions with susceptible loci. We also present results from EOCRC-specific genome-wide association studies that could be used to perform Mendelian randomization analyses to ascertain potential causal links between environmental factors and EOCRC.

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

Genome-wide interaction study of dietary intake of fibre, fruits, and vegetables with risk of colorectal cancer

BACKGROUND

Consumption of fibre, fruits and vegetables have been linked with lower colorectal cancer (CRC) risk. A genome-wide gene-environment (G × E) analysis was performed to test whether genetic variants modify these associations.

METHODS

A pooled sample of 45 studies including up to 69,734 participants (cases: 29,896; controls: 39,838) of European ancestry were included. To identify G × E interactions, we used the traditional 1--degree-of-freedom (DF) G × E test and to improve power a 2-step procedure and a 3DF joint test that investigates the association between a genetic variant and dietary exposure, CRC risk and G × E interaction simultaneously.

FINDINGS

The 3-DF joint test revealed two significant loci with p-value <5 × 10-8. Rs4730274 close to the SLC26A3 gene showed an association with fibre (p-value: 2.4 × 10-3) and G × fibre interaction with CRC (OR per quartile of fibre increase = 0.87, 0.80, and 0.75 for CC, TC, and TT genotype, respectively; G × E p-value: 1.8 × 10-7). Rs1620977 in the NEGR1 gene showed an association with fruit intake (p-value: 1.0 × 10-8) and G × fruit interaction with CRC (OR per quartile of fruit increase = 0.75, 0.65, and 0.56 for AA, AG, and GG genotype, respectively; G × E -p-value: 0.029).

INTERPRETATION

We identified 2 loci associated with fibre and fruit intake that also modify the association of these dietary factors with CRC risk. Potential mechanisms include chronic inflammatory intestinal disorders, and gut function. However, further studies are needed for mechanistic validation and replication of findings.

FUNDING

National Institutes of Health, National Cancer Institute. Full funding details for the individual consortia are provided in acknowledgments.

A new test for trait mean and variance detects unreported loci for blood-pressure variation

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci.

Genome-Wide Gene-Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

BACKGROUND

High red meat and/or processed meat consumption are established colorectal cancer risk factors. We conducted a genome-wide gene-environment (GxE) interaction analysis to identify genetic variants that may modify these associations.

METHODS

A pooled sample of 29,842 colorectal cancer cases and 39,635 controls of European ancestry from 27 studies were included. Quantiles for red meat and processed meat intake were constructed from harmonized questionnaire data. Genotyping arrays were imputed to the Haplotype Reference Consortium. Two-step EDGE and joint tests of GxE interaction were utilized in our genome-wide scan.

RESULTS

Meta-analyses confirmed positive associations between increased consumption of red meat and processed meat with colorectal cancer risk [per quartile red meat OR = 1.30; 95% confidence interval (CI) = 1.21-1.41; processed meat OR = 1.40; 95% CI = 1.20-1.63]. Two significant genome-wide GxE interactions for red meat consumption were found. Joint GxE tests revealed the rs4871179 SNP in chromosome 8 (downstream of HAS2); greater than median of consumption ORs = 1.38 (95% CI = 1.29-1.46), 1.20 (95% CI = 1.12-1.27), and 1.07 (95% CI = 0.95-1.19) for CC, CG, and GG, respectively. The two-step EDGE method identified the rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than median of consumption ORs = 1.18 (95% CI = 1.11-1.24), 1.35 (95% CI = 1.26-1.44), and 1.46 (95% CI = 1.26-1.69) for CC, CT, and TT, respectively.

CONCLUSIONS

We propose two novel biomarkers that support the role of meat consumption with an increased risk of colorectal cancer.

IMPACT

The reported GxE interactions may explain the increased risk of colorectal cancer in certain population subgroups.

Genome-Wide Interaction Study of Dietary Intake and Colorectal Cancer Risk in the UK Biobank

Importance

Candidate gene analysis approaches have shown that colorectal cancer (CRC) risk attributable to diet may differ according to genotype. A genome-wide approach further allows for the exploration of underlying pathways for associations between diet and CRC risk across the genome.

Objectives

To identify genetic variants that modify diet-CRC associations and to further explore the underlying pathways in the cause of CRC.

Design, Setting, and Participants

This nested case-control study used data on White British participants from the prospective cohort UK Biobank. Participants were recruited between March 13, 2006, and October 1, 2010, and data were censored June 25, 2021.

Exposures

The average frequency intake of 11 dietary factors in the year preceding baseline was obtained via a touchscreen questionnaire. After quality control for more than 93 million variants of imputed genetic data, 4 122 345 variants remained.

Main Outcomes and Measures

Colorectal cancer cases were identified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Genome-wide interaction analysis was performed to test interactions between dietary factors and variants using a conditional logistic regression model. Summary statistics of interactions at the variant level were used to calculate empirical P values for interactions at gene and gene-set levels in gene-based and gene-set enrichment analyses.

Results

A total of 4686 participants with CRC (mean [SD] age, 60.7 [6.6] years; 2707 men [57.8%]) received a new diagnosis during a median of 12.4 years (IQR, 11.6-13.1 years) of follow-up. Once a case was detected, 3 matched controls were identified, for a total of 14 058 controls (mean [SD] age, 60.4 [6.6] years; 8121 men [57.8%]). A total of 324 variants were identified that interacted with diet consumption at the suggestive threshold (P < 1 × 10-5). In gene-based analysis, aggregation of multiple EPDR1 gene variants was found to interact with fish intake regarding CRC risk. Furthermore, gene-set enrichment analysis found that several sets of protein-coding genes, which were overrepresented with particular functions and pathways, interacted with the consumption of milk (ART), cheese (OR), tea (KRT), and alcohol (PRM and TNP).

Conclusions and Relevance

In this nested case-control study, the risk of CRC associated with fish intake was modified by multiple single-nucleotide polymorphisms of the EPDR1 gene. The findings further suggested possible functions and pathways that might link the consumption of milk, cheese, tea, and alcohol with CRC development.

Nutrition and Microbiome Interactions in Human Cancer

Individual physiologic responses to changes in dietary patterns can vary widely to affect cancer risk, which is driven by multiple host-specific factors (eg, genetics, epigenetics, inflammatory and metabolic states, and the colonizing microbiome). Emerging evidence indicates that diet-induced microbiota alterations are key modulators of several host functions important to tumor etiology, progression, and response to cancer therapy. Thus, diet may potentially be used to target alterations of the microbiota as an effective means to improve outcomes across the cancer continuum (from cancer prevention to tumor development and progression, to effects on treatment and survivorship). This review will focus on recent examples of functional interactions between dietary components (nutrients and non-nutrients) and the gastrointestinal microbiome, which are 2 critical and malleable environmental variables in cancer risk that affect host immune, metabolic, and cell signaling functions and may provide insights for novel cancer therapeutic and preventive strategies.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Diet quality, common genetic polymorphisms, and bladder cancer risk in a New England population-based study

PURPOSE

We examined the interaction between common genetic bladder cancer variants, diet quality, and bladder cancer risk in a population-based case-control study conducted in New England.

METHODS

At the time of enrollment, 806 bladder cancer cases and 974 controls provided a DNA sample and completed a diet history questionnaire. Diet quality was assessed using the 2010 Alternate Healthy Eating Index (AHEI-2010) score. Single nucleotide polymorphisms (SNPs) reported in genome-wide association studies to be associated with bladder cancer risk were combined into a polygenic risk score and also examined individually for interaction with the AHEI-2010. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression.

RESULTS

A 1-standard deviation increase in polygenic risk score was associated with higher bladder cancer risk (OR, 1.34; 95% CI 1.21-1.49). Adherence to the AHEI-2010 was not associated with bladder cancer risk (OR, 0.99; 95% CI 0.98-1.00) and the polygenic risk score did not appear to modify the association between the AHEI-2010 and bladder cancer risk. In single-SNP analyses, rs8102137 (bladder cancer risk allele, C) modified the association between the AHEI-2010 total score and bladder cancer risk, with the strongest evidence for the AHEI-2010 long chain fat guideline (OR for TT, 0.92; 95% CI 0.87-0.98; OR for CT, 1.02; 95% CI 0.96-1.08; OR for CC, 1.03; 95% CI 0.93-1.14; p for interaction, 0.02).

CONCLUSIONS

In conclusion, rs8102137 near the cyclin E1 gene ( CCNE1 ) may be involved in gene-diet interactions for bladder cancer risk.

An Evaluation of Gene-Diet Interaction Statistical Methods and Discovery of rs7175421-Whole Grain Interaction in Lung Cancer

Dietary factors show different effects on genetically diverse populations. Scientific research uses gene-environment interaction models to study the effects of dietary factors on genetically diverse populations for lung cancer risk. However, previous study designs have not investigated the degree of type I error inflation and, in some instances, have not corrected for multiple testing. Using a motivating investigation of diet-gene interaction and lung cancer risk, we propose a training and testing strategy and perform real-world simulations to select the appropriate statistical methods to reduce false-positive discoveries. The simulation results show that the unconstrained maximum likelihood (UML) method controls the type I error better than the constrained maximum likelihood (CML). The empirical Bayesian (EB) method can compete with the UML method in achieving statistical power and controlling type I error. We observed a significant interaction between SNP rs7175421 with dietary whole grain in lung cancer prevention, with an effect size (standard error) of -0.312 (0.112) for EB estimate. SNP rs7175421 may interact with dietary whole grains in modulating lung cancer risk. Evaluating statistical methods for gene-diet interaction analysis can help balance the statistical power and type I error.

Nutrition for precision health: The time is now

Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi-tiered "omics" makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene-diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

Frequency distribution of cytokine and associated transcription factor single nucleotide polymorphisms in Zimbabweans: Impact on schistosome infection and cytokine levels

Cytokines mediate T-helper (TH) responses that are crucial for determining the course of infection and disease. The expression of cytokines is regulated by transcription factors (TFs). Here we present the frequencies of single nucleotide polymorphisms (SNPs) in cytokine and TF genes in a Zimbabwean population, and further relate SNPs to susceptibility to schistosomiasis and cytokine levels. Individuals (N = 850) were genotyped for SNPs across the cytokines IL4, IL10, IL13, IL33, and IFNG, and their TFs STAT4, STAT5A/B, STAT6, GATA3, FOXP3, and TBX21 to determine allele frequencies. Circulatory levels of systemic and parasite-specific IL-4, IL-5, IL-10, IL-13, and IFNγ were quantified via enzyme-linked immunosorbent assay. Schistosoma haematobium infection was determined by enumerating parasite eggs excreted in urine by microscopy. SNP allele frequencies were related to infection status by case-control analysis and logistic regression, and egg burdens and systemic and parasite-specific cytokine levels by analysis of variance and linear regression. Novel findings were i) IL4 rs2070874*T's association with protection from schistosomiasis, as carriage of ≥1 allele gave an odds ratio of infection of 0.597 (95% CIs, 0.421-0.848, p = 0.0021) and IFNG rs2069727*G's association with susceptibility to schistosomiasis as carriage of ≥1 allele gave an odds ratio of infection of 1.692 (1.229-2.33, p = 0.0013). Neither IL4 rs2070874*T nor IFNG rs2069727*G were significantly associated with cytokine levels. This study found TH2-upregulating SNPs were more frequent among the Zimbabwean sample compared to African and European populations, highlighting the value of immunogenetic studies of African populations in the context of infectious diseases and other conditions, including allergic and atopic disease. In addition, the identification of novel infection-associated alleles in both TH1- and TH2-associated genes highlights the role of both in regulating and controlling responses to Schistosoma.

A scalable hierarchical lasso for gene-environment interactions

We describe a regularized regression model for the selection of gene-environment (G×E) interactions. The model focuses on a single environmental exposure and induces a main-effect-before-interaction hierarchical structure. We propose an efficient fitting algorithm and screening rules that can discard large numbers of irrelevant predictors with high accuracy. We present simulation results showing that the model outperforms existing joint selection methods for (G×E) interactions in terms of selection performance, scalability and speed, and provide a real data application. Our implementation is available in the gesso R package.

Adaptive capacity to dietary Vitamin B12 levels is maintained by a gene-diet interaction that ensures optimal life span

Diet regulates complex life-history traits such as longevity. For optimal lifespan, organisms employ intricate adaptive mechanisms whose molecular underpinnings are less known. We show that Caenorhabditis elegans FLR-4 kinase prevents lifespan differentials on the bacterial diet having higher Vitamin B12 levels. The flr-4 mutants are more responsive to the higher B12 levels of Escherichia coli HT115 diet, and consequently, have enhanced flux through the one-carbon cycle. Mechanistically, a higher level of B12 transcriptionally downregulates the phosphoethanolamine methyltransferase pmt-2 gene, which modulates phosphatidylcholine (PC) levels. Pmt-2 downregulation activates cytoprotective gene expression through the p38-MAPK pathway, leading to increased lifespan only in the mutant. Evidently, preventing bacterial B12 uptake or inhibiting one-carbon metabolism reverses all the above phenotypes. Conversely, supplementation of B12 to E. coli OP50 or genetically reducing PC levels in the OP50-fed mutant extends lifespan. Together, we reveal how worms maintain adaptive capacity to diets having varying micronutrient content to ensure a normal lifespan.

A Systematic Review and Recommendations Around Frameworks for Evaluating Scientific Validity in Nutritional Genomics

Background: There is a significant lack of consistency used to determine the scientific validity of nutrigenetic research. The aims of this study were to examine existing frameworks used for determining scientific validity in nutrition and/or genetics and to determine which framework would be most appropriate to evaluate scientific validity in nutrigenetics in the future.

Methods: A systematic review (PROSPERO registration: CRD42021261948) was conducted up until July 2021 using Medline, Embase, and Web of Science, with articles screened in duplicate. Gray literature searches were also conducted (June-July 2021), and reference lists of two relevant review articles were screened. Included articles provided the complete methods for a framework that has been used to evaluate scientific validity in nutrition and/or genetics. Articles were excluded if they provided a framework for evaluating health services/systems more broadly. Citing articles of the included articles were then screened in Google Scholar to determine if the framework had been used in nutrition or genetics, or both; frameworks that had not were excluded. Summary tables were piloted in duplicate and revised accordingly prior to synthesizing all included articles. Frameworks were critically appraised for their applicability to nutrigenetic scientific validity assessment using a predetermined categorization matrix, which included key factors deemed important by an expert panel for assessing scientific validity in nutrigenetics.

Results: Upon screening 3,931 articles, a total of 49 articles representing 41 total frameworks, were included in the final analysis (19 used in genetics, 9 used in nutrition, and 13 used in both). Factors deemed important for evaluating nutrigenetic evidence related to study design and quality, generalizability, directness, consistency, precision, confounding, effect size, biological plausibility, publication/funding bias, allele and nutrient dose-response, and summary levels of evidence. Frameworks varied in the components of their scientific validity assessment, with most assessing study quality. Consideration of biological plausibility was more common in frameworks used in genetics. Dose-response effects were rarely considered. Two included frameworks incorporated all but one predetermined key factor important for nutrigenetic scientific validity assessment.

Discussion/Conclusions: A single existing framework was highlighted as optimal for the rigorous evaluation of scientific validity in nutritional genomics, and minor modifications are proposed to strengthen it further.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=261948, PROSPERO [CRD42021261948].

Epidemiology, Molecular Mechanisms, and Clinical Trials: an Update on Research on the Association Between Red Meat Consumption and Colorectal Cancer

PURPOSE OF THE REVIEW

Colorectal cancer is the second most common cause of cancer death in the world. The aim of this review is to provide an update on recent epidemiological studies, the molecular mechanisms involved, and ongoing clinical trials investigating the relationship between red meat consumption and colorectal cancer.

RECENT FINDINGS

Evidence in the literature proposes an association between red meat consumption and development of colorectal cancer, and there is some insight with regard to the mechanisms involved. Twenty studies of the IARC report (1990-2015) showed that red meat is positively associated with colorectal cancer whereas 14 studies either supported no positive association or no statistically significant association between red meat consumption and risk for CRC. More recent epidemiological studies conducted from 2016 and onwards provided further evidence that adherence to diets low in red and/or processed meat reduces the risk of colorectal cancer. Evidence from recent studies supports that quantity, doneness, and preparation of red meat play a role in colorectal carcinogenesis. Red meat's degradation products allow for the creation of a pro-inflammatory colonic microenvironment, and the gut microbiome plays a role in colorectal carcinogenesis. Heme, hydrogen sulfide, lipid peroxidation, nitroso compounds, and the bacterium Fusobacterium Nucleatum (as well as possibly other bacteria such as Akkermansia muciniphila, Eubacterium cylindroides, Eubacterium eligens 1 and 2, and Eubacterium rectale 1 and 2) also partake in the process of colorectal carcinogenesis. Several clinical trials are underway investigating the effects of different diets and red meat substitution products on colorectal cancer incidence as well as the underlying molecular mechanisms involved in the process.

Association of four genetic variants with colorectal cancer in Kazakhstan population

The study was conducted to search for polymorphisms located in the 10th chromosome associated with colorectal adenocarcinoma in representatives of the Kazakhstan population. Study was performed with 282 colorectal cancer (CRC) patients and 159 controls. Genotyping of SNPs was performed by QuantStudio 12K Flex PCR. For four significant SNPs inheritance model analysis was performed. Increasing risk of CRC was noted for rs10795668 in log-additive model (OR = 1.45, 95% CI: 1.05–1.99, p = 0.023); for rs1035209 in log-additive model (OR = 1.79, 95% CI: 1.18–2.72, p = 0.003); for rs11190164 in log-additive model (OR = 1.67, 95% CI: 1.17–2.38, p = 0.004). Decreasing risk of CRC was noted for rs10506868 in log-additive model (OR = 0.56, 95% CI: 0.37–0.85, p = 0.006). We detected SNPs that are associated with CRC risk in the Kazakhstan population.

Guanylyl cyclase 2C (GUCY2C) in gastrointestinal cancers: recent innovations and therapeutic potential

INTRODUCTION

Gastrointestinal (GI) cancers account for the second leading cause of cancer-related deaths in the United States. Guanylyl cyclase C (GUCY2C) is an intestinal signaling system that regulates intestinal fluid and electrolyte secretion as well as intestinal homeostasis. In recent years, it has emerged as a promising target for chemoprevention and therapy for GI malignancies.

AREAS COVERED

The loss of GUCY2C signaling early in colorectal tumorigenesis suggests it could have a significant impact on tumor initiation. Recent studies highlight the importance of GUCY2C signaling in preventing colorectal tumorigenesis using agents such as linaclotide, plecanatide, and sildenafil. Furthermore, GUCY2C is a novel target for immunotherapy and a diagnostic marker for primary and metastatic diseases.

EXPERT OPINION

There is an unmet need for prevention and therapy in GI cancers. In that context, GUCY2C is a promising target for prevention, although the precise mechanisms by which GUCY2C signaling affects tumorigenesis remain to be defined. Furthermore, clinical trials are exploring its role as an immunotherapeutic target for vaccines to prevent metastatic disease. Indeed, GUCY2C is an emerging target across the disease continuum from chemoprevention, to diagnostic management, through the treatment and prevention of metastatic diseases.

Nongenetic Determinants of Risk for Early-Onset Colorectal Cancer

Background

Incidence of early-onset (younger than 50 years of age) colorectal cancer (CRC) is increasing in many countries. Thus, elucidating the role of traditional CRC risk factors in early-onset CRC is a high priority. We sought to determine whether risk factors associated with late-onset CRC were also linked to early-onset CRC and whether association patterns differed by anatomic subsite.

Methods

Using data pooled from 13 population-based studies, we studied 3767 CRC cases and 4049 controls aged younger than 50 years and 23 437 CRC cases and 35 311 controls aged 50 years and older. Using multivariable and multinomial logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) to assess the association between risk factors and early-onset CRC and by anatomic subsite.

Results

Early-onset CRC was associated with not regularly using nonsteroidal anti-inflammatory drugs (OR = 1.43, 95% CI = 1.21 to 1.68), greater red meat intake (OR = 1.10, 95% CI = 1.04 to 1.16), lower educational attainment (OR = 1.10, 95% CI = 1.04 to 1.16), alcohol abstinence (OR = 1.23, 95% CI = 1.08 to 1.39), and heavier alcohol use (OR = 1.25, 95% CI = 1.04 to 1.50). No factors exhibited a greater excess in early-onset compared with late-onset CRC. Evaluating risks by anatomic subsite, we found that lower total fiber intake was linked more strongly to rectal (OR = 1.30, 95% CI = 1.14 to 1.48) than colon cancer (OR = 1.14, 95% CI = 1.02 to 1.27; P = .04).

Conclusion

In this large study, we identified several nongenetic risk factors associated with early-onset CRC, providing a basis for targeted identification of those most at risk, which is imperative in mitigating the rising burden of this disease.

Identifying Novel Susceptibility Genes for Colorectal Cancer Risk From a Transcriptome-Wide Association Study of 125,478 Subjects

BACKGROUND AND AIMS

Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes.

METHODS

Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted.

RESULTS

We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis.

CONCLUSIONS

Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.

Healthy lifestyles, genetic modifiers, and colorectal cancer risk: a prospective cohort study in the UK Biobank

BACKGROUND

Both genetic and lifestyle factors play an etiologic role in colorectal cancer (CRC).

OBJECTIVES

We evaluated potential gene-environment interactions in CRC risk.

METHODS

We used data from 346,297 participants in the UK Biobank cohort. Healthy lifestyle scores (HLSs) were constructed using 8 lifestyle factors, primarily according to the American Cancer Society guidelines, and were categorized into unhealthy, intermediate, and healthy groups. A polygenic risk score (PRS) was created using 95 genetic risk variants identified by genome-wide association studies of CRC and was categorized by tertile. Cox models were used to estimate the HRs and 95% CIs of CRC risk associated with the HLS and PRS.

RESULTS

During a median follow-up of 5.8 y, 2066 incident cases of CRC were identified. Healthier HLSs were associated with reduced risk of CRC in a dose-response manner. The risk reduction was more apparent among those with high PRS (HRhealthy vs. unhealthy HLS1: 0.58; 95% CI: 0.43, 0.79 for men and 0.71; 0.58, 0.85 for men and women combined) than those with low PRS. Although no multiplicative interactions were identified, the HLS1 and PRS showed a significant additive interaction (P = 0.02 for all participants combined, 0.04 for men). In analyses including all participants, the adjusted CRC cumulative risk from age 40 to 75 y was 6.40% for those with high PRS/unhealthy HLS1, with a relative excess risk due to interaction of 0.58 (95% CI: 0.06, 1.10), compared with 2.09% among those with low PRS/healthy HLS1. This pattern was more apparent among those who reported not having received any bowel screening before baseline.

CONCLUSIONS

Although the observational nature of the study precludes proof of causality, our findings suggest that individuals with a high genetic susceptibility could benefit more substantially than those with a low genetic risk from lifestyle modification in reducing CRC risk.

Modulation of the Canonical Wnt Signaling Pathway by Dietary Polyphenols, an Opportunity for Colorectal Cancer Chemoprevention and Treatment

In the last few decades there has been a rise in the worldwide incidence of colorectal cancer which can be traced back to the influence of well-known modifiable risk factors such as lifestyle, diet and obesity. Conversely, the consumption of fruits, vegetables and fiber decreases the risk of CRC, which is why dietary polyphenols have aroused interest in recent years as potentially anti-carcinogenic compounds. One of the driving forces of colorectal carcinogenesis, in both sporadic and hereditary CRC, is the aberrant activation/regulation of the Wnt/β-catenin pathway. This review discusses reports of modulation of the Wnt/β-Catenin signaling pathway by dietary polyphenols (resveratrol, avenanthramides, epigallocatechinin, curcumin, quercetin, silibinin, genistein and mangiferin) specifically focusing on CRC, and proposes a model as to how this modulation occurs. There is potential for implementing these dietary polyphenols into preventative and therapeutic therapies for CRC as evidenced by some clinical trials that have been carried out with promising results.

Metabolic pathways in sporadic colorectal carcinogenesis: A new proposal

Given the reports made about geographical differences in Colorectal Cancer (CRC) occurrence, suggesting a link between dietary habits, genes and cancer risk, we hypothesise that there are four fundamental metabolic pathways involved in diet-genes interactions, directly implicated in colorectal carcinogenesis: folate metabolism; lipid metabolism; oxidative stress response; and inflammatory response. Supporting this hypothesis are the evidence given by the significant associations between several diet-genes polymorphisms and CRC, namely: MTHFR, MTR, MTRR and TS (involved in folate metabolism); NPY, APOA1, APOB, APOC3, APOE, CETP, LPL and PON1 (involved in lipid metabolism); MNSOD, SOD3, CAT, GSTP1, GSTT1 and GSTM1 (involved in oxidative stress response); and IL-1, IL-6, TNF-α, and TGF-β (involved in inflammatory response). We also highlight the association between some foods/nutrients/nutraceuticals that are important in CRC prevention or treatment and the four metabolic pathways proposed, and the recent results of genome-wide association studies, both assisting our hypothesis. Finally, we propose a new line of investigation with larger studies, using accurate dietary biomarkers and investigating the four metabolic pathways genes simultaneously. This line of investigation will be essential to understand the full complexity of the association between nature and nurture in CRC and perhaps in other types of cancers. Only with this in-depth knowledge will it be possible to make personalised nutrition recommendations for disease prevention and management.

Multi-omics analysis to identify susceptibility genes for colorectal cancer

Most genetic variants for colorectal cancer (CRC) identified in genome-wide association studies (GWAS) are located in intergenic regions, implying pathogenic dysregulations of gene expression. However, comprehensive assessments of target genes in CRC remain to be explored. We conducted a multi-omics analysis using transcriptome and/or DNA methylation data from the Genotype-Tissue Expression, The Cancer Genome Atlas and the Colonomics projects. We identified 116 putative target genes for 45 GWAS-identified variants. Using summary-data-based Mendelian randomization approach (SMR), we demonstrated that the CRC susceptibility for 29 out of the 45 CRC variants may be mediated by cis-effects on gene regulation. At a cutoff of the Bonferroni-corrected PSMR < 0.05, we determined 66 putative susceptibility genes, including 39 genes that have not been previously reported. We further performed in vitro assays for two selected genes, DIP2B and SFMBT1, and provide functional evidence that they play a vital role in colorectal carcinogenesis via disrupting cell behavior, including migration, invasion and epithelial-mesenchymal transition. Our study reveals a large number of putative novel susceptibility genes and provides additional insight into the underlying mechanisms for CRC genetic risk loci.

Association of Body Mass Index With Colorectal Cancer Risk by Genome-Wide Variants

BACKGROUND

Body mass index (BMI) is a complex phenotype that may interact with genetic variants to influence colorectal cancer risk.

METHODS

We tested multiplicative statistical interactions between BMI (per 5 kg/m2) and approximately 2.7 million single nucleotide polymorphisms with colorectal cancer risk among 14 059 colorectal cancer case (53.2% women) and 14 416 control (53.8% women) participants. All analyses were stratified by sex a priori. Statistical methods included 2-step (ie, Cocktail method) and single-step (ie, case-control logistic regression and a joint 2-degree of freedom test) procedures. All statistical tests were two-sided.

RESULTS

Each 5 kg/m2 increase in BMI was associated with higher risks of colorectal cancer, less so for women (odds ratio [OR] = 1.14, 95% confidence intervals [CI] = 1.11 to 1.18; P = 9.75 × 10-17) than for men (OR = 1.26, 95% CI = 1.20 to 1.32; P = 2.13 × 10-24). The 2-step Cocktail method identified an interaction for women, but not men, between BMI and a SMAD7 intronic variant at 18q21.1 (rs4939827; Pobserved = .0009; Pthreshold = .005). A joint 2-degree of freedom test was consistent with this finding for women (joint P = 2.43 × 10-10). Each 5 kg/m2 increase in BMI was more strongly associated with colorectal cancer risk for women with the rs4939827-CC genotype (OR = 1.24, 95% CI = 1.16 to 1.32; P = 2.60 × 10-10) than for women with the CT (OR = 1.14, 95% CI = 1.09 to 1.19; P = 1.04 × 10-8) or TT (OR = 1.07, 95% CI = 1.01 to 1.14; P = .02) genotypes.

CONCLUSION

These results provide novel insights on a potential mechanism through which a SMAD7 variant, previously identified as a susceptibility locus for colorectal cancer, and BMI may influence colorectal cancer risk for women.

Deriving stratified effects from joint models investigating gene-environment interactions

Background

Models including an interaction term and performing a joint test of SNP and/or interaction effect are often used to discover Gene-Environment (GxE) interactions. When the environmental exposure is a binary variable, analyses from exposure-stratified models which consist of estimating genetic effect in unexposed and exposed individuals separately can be of interest. In large-scale consortia focusing on GxE interactions in which only the joint test has been performed, it may be challenging to get summary statistics from both exposure-stratified and marginal (i.e not accounting for interaction) models.

Results

In this work, we developed a simple framework to estimate summary statistics in each stratum of a binary exposure and in the marginal model using summary statistics from the “joint” model. We performed simulation studies to assess our estimators’ accuracy and examined potential sources of bias, such as correlation between genotype and exposure and differing phenotypic variances within exposure strata. Results from these simulations highlight the high theoretical accuracy of our estimators and yield insights into the impact of potential sources of bias. We then applied our methods to real data and demonstrate our estimators’ retained accuracy after filtering SNPs by sample size to mitigate potential bias.

Conclusions

These analyses demonstrated the accuracy of our method in estimating both stratified and marginal summary statistics from a joint model of gene-environment interaction. In addition to facilitating the interpretation of GxE screenings, this work could be used to guide further functional analyses. We provide a user-friendly Python script to apply this strategy to real datasets. The Python script and documentation are available at https://gitlab.pasteur.fr/statistical-genetics/j2s.

A Systematic Analysis of Interactions between Environmental Risk Factors and Genetic Variation in Susceptibility to Colorectal Cancer

BACKGROUND

The underlying etiology of colorectal cancer includes both genetic variation and environmental exposures. The main aim of this study was to search for interaction effects between well-established environmental risk factors and published common genetic variants exerting main effects on colorectal cancer risk.

METHODS

We used a two-phase approach: (i) discovery phase (2,652 incident colorectal cancer cases and 10,608 controls from UK Biobank) and (ii) validation phase (1,656 cases and 2,497 controls from the Study of Colorectal Cancer in Scotland). Interactions with nominal P < 0.05 in phase I were taken forward for validation in phase II. Furthermore, we constructed a weighted genetic risk score (GRS) of colorectal cancer risk for each individual and studied interactions between the GRS and the environmental risk factors.

RESULTS

Seventy of the 1,500 tested interactions were nominally significant in phase I. After testing these 70 interactions in phase II, an interaction between rs11903757 (2q32.3) and body mass index (BMI) was nominally significant (P = 0.02) with the same direction of effect. The rs11903757*BMI interaction was also significant (ratio of ORs = 1.26; 95% confidence interval, 1.10-1.44; P interaction = 6.03 × 10-4; P heterogeneity = 0.63) in a meta-analysis combining results from both phases. No interactions were significant in phase II after accounting for multiple testing. No interactions involving the GRS were found with statistical significance.

CONCLUSIONS

Limited evidence of gene-environment interactions in colorectal cancer risk was observed. There are potential modifications of the rs11903757 effect by BMI on colorectal cancer risk.

IMPACT

Our findings might contribute to identifying subpopulations with different susceptibility to the effect of BMI on colorectal cancer risk.

A gene-diet interaction-based score predicts response to dietary fat in the Women's Health Initiative

BACKGROUND

Although diet response prediction for cardiometabolic risk factors (CRFs) has been demonstrated using single genetic variants and main-effect genetic risk scores, little investigation has gone into the development of genome-wide diet response scores.

OBJECTIVE

We sought to leverage the multistudy setup of the Women's Health Initiative cohort to generate and test genetic scores for the response of 6 CRFs (BMI, systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and fasting glucose) to dietary fat.

METHODS

A genome-wide interaction study was undertaken for each CRF in women (n ∼ 9000) not participating in the dietary modification (DM) trial, which focused on the reduction of dietary fat. Genetic scores based on these analyses were developed using a pruning-and-thresholding approach and tested for the prediction of 1-y CRF changes as well as long-term chronic disease development in DM trial participants (n ∼ 5000).

RESULTS

Only 1 of these genetic scores, for LDL cholesterol, predicted changes in the associated CRF. This 1760-variant score explained 3.7% (95% CI: 0.09, 11.9) of the variance in 1-y LDL cholesterol changes in the intervention arm but was unassociated with changes in the control arm. In contrast, a main-effect genetic risk score for LDL cholesterol was not useful for predicting dietary fat response. Further investigation of this score with respect to downstream disease outcomes revealed suggestive differential associations across DM trial arms, especially with respect to coronary heart disease and stroke subtypes.

CONCLUSIONS

These results lay the foundation for the combination of many genome-wide gene-diet interactions for diet response prediction while highlighting the need for further research and larger samples in order to achieve robust biomarkers for use in personalized nutrition.

Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations

Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations.

Our f3 and f4 statistics–based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.

Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta-analyses of observational studies that investigated gene-environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta-analyses of candidate gene- or single-nucleotide polymorphism-based studies on 521 G×E interactions, and 8 articles reporting 33 genome-wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

Intake of Processed Meat and Association with Sociodemographic and Lifestyle Factors in a Representative Sample of the Swiss Population

Processed meat (PM) intake is associated with health risks, but data are lacking in Switzerland. Using national representative data from a recent menuCH Survey, we first aimed to quantify intake of PM and its subtypes, and second to investigate associations with sociodemographic and lifestyle factors by multivariable regression analysis. PM was consumed by 72% of the population, and mean daily intake was 42.7 g/day (standard error of the mean (SEM) 1.2 g/day), ranging considerably across PM subtypes: highest intake of sausages 18.1 g/day (SEM 0.7 g/day) and lowest of bacon 2.0 g/day (SEM 0.2 g/day). PM intake by women was 4.7 g/1000 kcal lower than men (95% confidence interval (CI): -6.7; -2.7) and 2.9 g/1000 kcal lower in the French- language region compared with the German region (95% CI: 2.4; 8.7). Among sociodemographic and lifestyle factors examined, BMI (obese vs. normal: 5.5 g/1000 kcal, 95% CI: 2.4; 8.7) and current smoking (vs. never smoked: 3.1 g/kcal, 95% CI: 0.6; 5.6) were independently associated with PM intake. The results are a first description of PM intake, separate from other meat types, and which identified associations with two unhealthy lifestyle factors in Switzerland. Such data will contribute to better nutritional recommendations and guidance for public health interventions.

Lifestyle and dietary environmental factors in colorectal cancer susceptibility

Colorectal cancer (CRC) incidence changes with time and by variations in diet and lifestyle, as evidenced historically by migrant studies and recently by extensive epidemiologic evidence. The worldwide heterogeneity in CRC incidence is strongly suggestive of etiological involvement of environmental exposures, particularly lifestyle and diet. It is established that physical inactivity, obesity and some dietary factors (red/processed meats, alcohol) are positively associated with CRC, while healthy lifestyle habits show inverse associations. Mechanistic evidence shows that lifestyle and dietary components that contribute to energy excess are linked with increased CRC via metabolic dysfunction, inflammation, oxidative stress, bacterial dysbiosis and breakdown of gut barrier integrity while the reverse is apparent for components associated with decreased risk. This chapter will review the available evidence on lifestyle and dietary factors in CRC etiology and their underlying mechanisms in CRC development. This short review will also touch upon available information on potential gene-environment interactions, molecular sub-types of CRC and anatomical sub-sites within the colorectum.

Gene-environment interaction and Mendelian randomisation

Genetic factors only account for up to a third of the cases of Parkinson's disease (PD), while the remaining cases are of unknown aetiology. Environmental exposures (such as pesticides or heavy metals) and the interaction with genetic susceptibility factors (summarized in the concept of impaired xenobiotic metabolism) are believed to play a major role in the mechanisms of neurodegeneration. Beside of the classical association studies (e.g. genome-wide association studies), a novel approach to investigate environmental risk factors are Mendelian randomisation studies. This review explores the gene-environment interaction and the gain of Mendelian randomisation studies in assessing causalities of modifiable risk factors for PD.

Meeting report from the joint IARC-NCI international cancer seminar series: a focus on colorectal cancer

Despite significant progress in our understanding of the etiology, biology and genetics of colorectal cancer, as well as important clinical advances, it remains the third most frequently diagnosed cancer worldwide and is the second leading cause of cancer death. Based on demographic projections, the global burden of colorectal cancer would be expected to rise by 72% from 1.8 million new cases in 2018 to over 3 million in 2040 with substantial increases anticipated in low- and middle-income countries. In this meeting report, we summarize the content of a joint workshop led by the National Cancer Institute and the International Agency for Research on Cancer, which was held to summarize the important achievements that have been made in our understanding of colorectal cancer etiology, genetics, early detection and treatment and to identify key research questions that remain to be addressed.

Genome-Wide Association Study (GWAS) on Bilirubin Concentrations in Subjects with Metabolic Syndrome: Sex-Specific GWAS Analysis and Gene-Diet Interactions in a Mediterranean Population

Although, for decades, increased serum bilirubin concentrations were considered a threatening sign of underlying liver disease and had been associated with neonatal jaundice, data from recent years show that bilirubin is a powerful antioxidant and suggest that slightly increased serum bilirubin concentrations are protective against oxidative stress-related diseases, such as cardiovascular diseases. Therefore, a better understanding of the gene-diet interactions in determining serum bilirubin concentrations is needed. None of the previous genome-wide association studies (GWAS) on bilirubin concentrations has been stratified by sex. Therefore, considering the increasing interest in incorporating the gender perspective into nutritional genomics, our main aim was to carry out a GWAS on total serum bilirubin concentrations in a Mediterranean population with metabolic syndrome, stratified by sex. Our secondary aim was to explore, as a pilot study, the presence of gene-diet interactions at the GWAS level. We included 430 participants (188 men and 242 women, aged 55–75 years, and with metabolic syndrome) in the PREDIMED Plus-Valencia study. Global and sex-specific GWAS were undertaken to analyze associations and gene-diet interaction on total serum bilirubin. Adherence (low and high) to the Mediterranean diet (MedDiet) was analyzed as the dietary modulator. In the GWAS, we detected more than 55 SNPs associated with serum bilirubin at p < 5 × 10⁻⁸ (GWAS level). The top-ranked were four SNPs (rs4148325 (p = 9.25 × 10⁻²⁴), rs4148324 (p = 9.48 × 10⁻²⁴), rs6742078 (p = 1.29 × 10⁻²³), rs887829 (p = 1.39 × 10⁻²³), and the rs4148324 (p = 9.48 × 10⁻²⁴)) in the UGT1A1 (UDP glucuronosyltransferase family 1 member A1) gene, which replicated previous findings revealing the UGT1A1 as the major locus. In the sex-specific GWAS, the top-ranked SNPs at the GWAS level were similar in men and women (the lead SNP was the rs4148324-UGT1A1 in both men (p = 4.77 × 10⁻¹¹) and women (p = 2.15 × 10⁻¹⁴), which shows homogeneous genetic results for the major locus. There was more sex-specific heterogeneity for other minor genes associated at the suggestive level of GWAS significance (p < 1 × 10⁻⁵). We did not detect any gene-MedDiet interaction at p < 1 × 10⁻⁵ for the major genetic locus, but we detected some gene-MedDiet interactions with other genes at p < 1 × 10⁻⁵, and even at the GWAS level for the IL17B gene (p = 3.14 × 10⁻⁸). These interaction results, however, should be interpreted with caution due to our small sample size. In conclusion, our study provides new data, with a gender perspective, on genes associated with total serum bilirubin concentrations in men and women, and suggests possible additional modulations by adherence to MedDiet.

Colorectal carcinogenesis: an archetype of gut microbiota-host interaction

Sporadic colorectal cancer (CRC) remains a major cause of worldwide mortality. Epidemiological evidence of markedly increased risk in populations that migrate to Western countries, or adopt their lifestyle, suggests that CRC is a disease whose aetiology is defined primarily by interactions between the host and his environment. The gut microbiome sits directly at this interface and is now increasingly recognised as a modulator of colorectal carcinogenesis. Bacteria such as Fusobacterium nucleatum and Escherichia coli (E. Coli) are found in abundance in patients with CRC and have been shown in experimental studies to promote neoplasia. A whole armamentarium of bacteria-derived oncogenic mechanisms has been defined, including the subversion of apoptosis and the production of genotoxins and pro-inflammatory factors. But the microbiota may also be protective: for example, they are implicated in the metabolism of dietary fibre to produce butyrate, a short chain fatty acid, which is anti-inflammatory and anti-carcinogenic. Indeed, although our understanding of this immensely complex, highly individualised and multi-faceted relationship is expanding rapidly, many questions remain: Can we define friends and foes, and drivers and passengers? What are the critical functions of the microbiota in the context of colorectal neoplasia?

Replicability and Prediction: Lessons and Challenges from GWAS

Since the publication of the Wellcome Trust Case Control Consortium (WTCCC) landmark study a decade ago, genome-wide association studies (GWAS) have led to the discovery of thousands of risk variants involved in disease etiology. This success story has two angles that are often overlooked. First, GWAS findings are highly replicable. This is an unprecedented phenomenon in complex trait genetics, and indeed in many areas of science, which in past decades have been plagued by false positives. At a time of increasing concerns about the lack of reproducibility, we examine the biological and methodological reasons that account for the replicability of GWAS and identify the challenges ahead. In contrast to the exemplary success of disease gene discovery, at present GWAS findings are not useful for predicting phenotypes. We close with an overview of the prospects for individualized prediction of disease risk and its foreseeable impact in clinical practice.

Dietary Inflammatory Index and Site-Specific Cancer Risk: A Systematic Review and Dose-Response Meta-Analysis

Existing evidence suggests a link between the inflammatory potential of diet and risk of cancer. This study aimed to test the linear and potential nonlinear dose-response associations of the Dietary Inflammatory Index (DII), as being representative of inflammatory features of the diet, and site-specific cancer risk. A systematic search was conducted with the use of PubMed and Scopus from 2014 to November 2017. Prospective cohort or case-control studies reporting the risk estimates of any cancer type for ≥3 categories of the DII were selected. Studies that reported the association between continuous DII score and cancer risk were also included. Pooled RRs were calculated by using a random-effects model. Eleven prospective cohort studies (total n = 1,187,474) with 28,614 incident cases and 29 case-control studies with 19,718 cases and 33,229 controls were identified. The pooled RRs for a 1-unit increment in the DII were as follows: colorectal cancer, 1.06 (95% CI: 1.04, 1.08; I2 = 72.5%; n = 9); breast cancer, 1.03 (95% CI: 1.00, 1.07; I2 = 84.0%; n = 7); prostate cancer, 1.06 (95% CI: 0.97, 1.15; I2 = 56.2%; n = 6); pancreatic cancer, 1.16 (95% CI: 1.05, 1.28; I2 = 61.6%; n = 2); ovarian cancer, 1.08 (95% CI: 1.03, 1.13; I2 = 0%; n = 2); esophageal squamous cell carcinoma, 1.24 (95% CI: 1.10, 1.38; I2 = 64.3%; n = 2); renal cell carcinoma, 1.08 (95% CI: 1.02, 1.13; I2 = 0%; n = 2); and esophageal adenocarcinoma, 1.26 (95% CI: 1.13, 1.39; I2 = 0%; n = 2). A nonlinear dose-response meta-analysis showed that, after a somewhat unchanged risk within initial scores of the DII, the risk of colorectal cancer increased linearly with increasing DII score. In the analyses of breast and prostate cancers, the risk increased with a very slight trend with increasing DII score. In conclusion, the results showed that dietary habits with high inflammatory features might increase the risk of site-specific cancers.

Polyclonal human antibodies against glycans bearing red meat-derived non-human sialic acid N-glycolylneuraminic acid are stable, reproducible, complex and vary between individuals: Total antibody levels are associated with colorectal cancer risk

BACKGROUND

N-glycolylneuraminic acid (Neu5Gc) is a non-human red-meat-derived sialic acid immunogenic to humans. Neu5Gc can be metabolically incorporated into glycan chains on human endothelial and epithelial surfaces. This represents the first example of a "xeno-autoantigen", against which circulating human "xeno-autoantibodies" can react. The resulting inflammation ("xenosialitis") has been demonstrated in human-like Neu5Gc-deficient mice and contributed to carcinoma progression via antibody-mediated inflammation. Anti-Neu5Gc antibodies have potential as biomarkers for diseases associated with red meat consumption such as carcinomas, atherosclerosis, and type 2 diabetes.

METHODS

ELISA assays measured antibodies against Neu5Gc or Neu5Gc-glycans in plasma or serum samples from the Nurses' Health Studies, the Health Professionals Follow-up Study, and the European Prospective Investigation into Cancer and Nutrition, including inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over 1-3 years in archived samples. We also assessed associations between antibody levels and coronary artery disease risk (CAD) or red meat intake. A glycan microarray was used to detected antibodies against multiple Neu5Gc-glycan epitopes. A nested case-control study design assessed the association between total anti-Neu5Gc antibodies detected in the glycan array assay and the risk of colorectal cancer (CRC).

RESULTS

ELISA assays showed a wide range of anti-Neu5Gc responses and good inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over time, but these antibody levels did not correlate with CAD risk or red meat intake. Antibodies against Neu5Gc alone or against individual Neu5Gc-bearing epitopes were also not associated with colorectal cancer (CRC) risk. However, a sialoglycan microarray study demonstrated positive association with CRC risk when the total antibody responses against all Neu5Gc-glycans were combined. Individuals in the top quartile of total anti-Neu5Gc IgG antibody concentrations had nearly three times the risk compared to those in the bottom quartile (Multivariate Odds Ratio comparing top to bottom quartile: 2.98, 95% CI: 0.80, 11.1; P for trend = 0.02).

CONCLUSIONS

Further work harnessing the utility of these anti-Neu5Gc antibodies as biomarkers in red meat-associated diseases must consider diversity in individual antibody profiles against different Neu5Gc-bearing glycans. Traditional ELISA assays for antibodies directed against Neu5Gc alone, or against specific Neu5Gc-glycans may not be adequate to define risk associations. Our finding of a positive association of total anti-Neu5Gc antibodies with CRC risk also warrants confirmation in larger prospective studies.

Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors

BACKGROUND & AIMS

Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.

METHODS

We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.

RESULTS

In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62-0.64) for men and 0.62 (95% confidence interval, 0.61-0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk.

CONCLUSIONS

We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

Critical research gaps and recommendations to inform research prioritisation for more effective prevention and improved outcomes in colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) leads to significant morbidity/mortality worldwide. Defining critical research gaps (RG), their prioritisation and resolution, could improve patient outcomes.

DESIGN

RG analysis was conducted by a multidisciplinary panel of patients, clinicians and researchers (n=71). Eight working groups (WG) were constituted: discovery science; risk; prevention; early diagnosis and screening; pathology; curative treatment; stage IV disease; and living with and beyond CRC. A series of discussions led to development of draft papers by each WG, which were evaluated by a 20-strong patient panel. A final list of RGs and research recommendations (RR) was endorsed by all participants.

RESULTS

Fifteen critical RGs are summarised below: RG1: Lack of realistic models that recapitulate tumour/tumour micro/macroenvironment; RG2: Insufficient evidence on precise contributions of genetic/environmental/lifestyle factors to CRC risk; RG3: Pressing need for prevention trials; RG4: Lack of integration of different prevention approaches; RG5: Lack of optimal strategies for CRC screening; RG6: Lack of effective triage systems for invasive investigations; RG7: Imprecise pathological assessment of CRC; RG8: Lack of qualified personnel in genomics, data sciences and digital pathology; RG9: Inadequate assessment/communication of risk, benefit and uncertainty of treatment choices; RG10: Need for novel technologies/interventions to improve curative outcomes; RG11: Lack of approaches that recognise molecular interplay between metastasising tumours and their microenvironment; RG12: Lack of reliable biomarkers to guide stage IV treatment; RG13: Need to increase understanding of health related quality of life (HRQOL) and promote residual symptom resolution; RG14: Lack of coordination of CRC research/funding; RG15: Lack of effective communication between relevant stakeholders.

CONCLUSION

Prioritising research activity and funding could have a significant impact on reducing CRC disease burden over the next 5 years.

Dietary components that counteract the increased risk of colorectal cancer related to red meat consumption

Western-style diets are associated with an increased risk of colorectal cancer (CRC). In particular, a strong correlation has been documented between CRC and the consumption of large amounts of red meat, especially processed red meat. Compared with white meat, red meat contains high levels of haem iron, a molecule that can exert a variety of genotoxic and other adverse effects on the colonic epithelium. According to current international guidelines, the reduction of red meat intake combined with the consumption of food containing antioxidant and chemoprotective substances may significantly reduce the risk of developing CRC. The dietary strategies that can help to contrast the harmful effects of haem iron are reported and discussed in this review.

Nature, Nurture, and Cancer Risks: Genetic and Nutritional Contributions to Cancer

It is speculated that genetic variants are associated with differential responses to nutrients (known as gene-diet interactions) and that these variations may be linked to different cancer risks. In this review, we critically evaluate the evidence across 314 meta-analyses of observational studies and randomized controlled trials of dietary risk factors and the five most common cancers (breast, lung, prostate, colorectal, and stomach). We also critically evaluate the evidence across 13 meta-analyses of observational studies of gene-diet interactions for the same cancers. Convincing evidence for association was found only for the intake of alcohol and whole grains in relation to colorectal cancer risk. Three nutrient associations had highly suggestive evidence and another 15 associations had suggestive evidence. Among the examined gene-diet interactions, only one had moderately strong evidence.