Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study.

BACKGROUND: This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective. METHODS: Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification. FINDINGS: During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 µg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival. INTERPRETATION: Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110. FUNDING: Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer.

BACKGROUND: We aimed to identify plasma and urinary metabolites related to colorectal cancer (CRC) risk and elucidate their mediator role in the associations between modifiable risk factors and CRC. METHODS: Metabolite quantitative trait loci were derived from two published metabolomics genome-wide association studies (GWASs), and summary-level data were extracted for 651 plasma metabolites and 208 urinary metabolites. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (100,204 cases; 154,587 controls) and the FinnGen cohort (4,957 cases; 304,197 controls). Mendelian randomization (MR) and colocalization analyses were performed to evaluate the causal roles of metabolites in CRC. Druggability evaluation was employed to prioritize potential therapeutic targets. Multivariable MR and mediation estimation were conducted to elucidate the mediating effects of metabolites on the associations between modifiable risk factors and CRC. RESULTS: The study identified 30 plasma metabolites and four urinary metabolites for CRC. Plasma sphingomyelin and urinary lactose, which were positively associated with CRC risk, could be modulated by drug interventions (ie, Olipudase alfa, Tilactase). Thirteen modifiable risk factors were associated with nine metabolites and eight of these modifiable risk factors were associated with CRC risk. These nine metabolites mediated the effect of modifiable risk factors (Actinobacteria, BMI, waist-hip ratio, fasting insulin, smoking initiation) on CRC. CONCLUSION: This study identified key metabolite biomarkers associated with CRC and elucidated their mediator roles in the associations between modifiable risk factors and CRC. These findings provide new insights into the etiology and potential therapeutic targets for CRC and the etiological pathways of modifiable environmental factors with CRC.

Circulating 25-hydroxyvitamin D and survival outcomes of colorectal cancer: evidence from population-based prospective cohorts and Mendelian randomisation.

BACKGROUND: To investigate the association between circulating 25-hydroxyvitamin D (25-OHD) and colorectal cancer (CRC) survival outcomes. METHODS: We conducted analyses among the Study of Colorectal Cancer in Scotland (SOCCS) and the UK Biobank (UKBB). Both cancer-specific survival (CSS) and overall survival (OS) outcomes were examined. The 25-OHD levels were categorised into three groups, and multi-variable Cox-proportional hazard models were applied to estimate hazard ratios (HRs). We performed individual-level Mendelian randomisation (MR) through the generated polygenic risk scores (PRS) of 25-OHD and summary-level MR using the inverse-variance weighted (IVW) method. RESULTS: We observed significantly poorer CSS (HR = 0.65,95%CI = 0.55-0.76,P = 1.03 × 10-7) and OS (HR = 0.66,95%CI = 0.58-0.75,P = 8.15 × 10-11) in patients with the lowest compared to those with the highest 25-OHD after adjusting for covariates. These associations remained across patients with varied tumour sites and stages. However, we found no significant association between 25-OHD PRS and either CSS (HR = 0.98,95%CI = 0.80-1.19,P = 0.83) or OS (HR = 1.07,95%CI = 0.91-1.25,P = 0.42). Furthermore, we found no evidence for causal effects by conducting summary-level MR analysis for either CSS (IVW:HR = 1.04,95%CI = 0.85-1.28,P = 0.70) or OS (IVW:HR = 1.10,95%CI = 0.93-1.31,P = 0.25). CONCLUSION: This study supports the observed association between lower circulating 25-OHD and poorer survival outcomes for CRC patients. Whilst the genotype-specific association between better outcomes and higher 25-OHD is intriguing, we found no support for causality using MR approaches.

Machine learning framework to extract the biomarker potential of plasma IgG N-glycans towards disease risk stratification.

Effective management of chronic diseases and cancer can greatly benefit from disease-specific biomarkers that enable informative screening and timely diagnosis. IgG N-glycans found in human plasma have the potential to be minimally invasive disease-specific biomarkers for all stages of disease development due to their plasticity in response to various genetic and environmental stimuli. Data analysis and machine learning (ML) approaches can assist in harnessing the potential of IgG glycomics towards biomarker discovery and the development of reliable predictive tools for disease screening. This study proposes an ML-based N-glycomic analysis framework that can be employed to build, optimise, and evaluate multiple ML pipelines to stratify patients based on disease risk in an interpretable manner. To design and test this framework, a published colorectal cancer (CRC) dataset from the Study of Colorectal Cancer in Scotland (SOCCS) cohort (1999-2006) was used. In particular, among the different pipelines tested, an XGBoost-based ML pipeline, which was tuned using multi-objective optimisation, calibrated using an inductive Venn-Abers predictor (IVAP), and evaluated via a nested cross-validation (NCV) scheme, achieved a mean area under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.771 when classifying between age-, and sex-matched healthy controls and CRC patients. This performance suggests the potential of using the relative abundance of IgG N-glycans to define populations at elevated CRC risk who merit investigation or surveillance. Finally, the IgG N-glycans that highly impact CRC classification decisions were identified using a global model-agnostic interpretability technique, namely Accumulated Local Effects (ALE). We envision that open-source computational frameworks, such as the one presented herein, will be useful in supporting the translation of glycan-based biomarkers into clinical applications.

Altered DNA methylation within DNMT3A, AHRR, LTA/TNF loci mediates the effect of smoking on inflammatory bowel disease.

This work aims to investigate how smoking exerts effect on the development of inflammatory bowel disease (IBD). A prospective cohort study and a Mendelian randomization study are first conducted to evaluate the association between smoking behaviors, smoking-related DNA methylation and the risks of Crohn's disease (CD) and ulcerative colitis (UC). We then perform both genome-wide methylation analysis and co-localization analysis to validate the observed associations. Compared to never smoking, current and previous smoking habits are associated with increased CD (P = 7.09 × 10-10) and UC (P < 2 × 10-16) risk, respectively. DNA methylation alteration at cg17742416 [DNMT3A] is linked to both CD (P = 7.30 × 10-8) and UC (P = 1.04 × 10-4) risk, while cg03599224 [LTA/TNF] is associated with CD risk (P = 1.91 × 10-6), and cg14647125 [AHRR] and cg23916896 [AHRR] are linked to UC risk (P = 0.001 and 0.002, respectively). Our study identifies biological mechanisms and pathways involved in the effects of smoking on the pathogenesis of IBD.

Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome.

BACKGROUND: The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC). METHODS: Protein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets. RESULTS: Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC. CONCLUSIONS: This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

Dissecting the pathogenic effects of smoking and its hallmarks in blood DNA methylation on colorectal cancer risk.

BACKGROUND: Tobacco smoking is suggested as a risk factor for colorectal cancer (CRC), but the complex relationship and the potential pathway are not fully understood. METHODS: We performed two-sample Mendelian randomisation (MR) analyses with genetic instruments for smoking behaviours and related DNA methylation in blood and summary-level GWAS data of colorectal cancer to disentangle the relationship. Colocalization analyses and prospective gene-environment interaction analyses were also conducted as replication. RESULTS: Convincing evidence was identified for the pathogenic effect of smoking initiation on CRC risk and suggestive evidence was observed for the protective effect of smoking cessation in the univariable MR analyses. Multivariable MR analysis revealed that these associations were independent of other smoking phenotypes and alcohol drinking. Genetically predicted methylation at CpG site cg17823346 [ZMIZ1] were identified to decrease CRC risk; while genetically predicted methylation at cg02149899 would increase CRC risk. Colocalization and gene-environment interaction analyses added further evidence to the relationship between epigenetic modification at cg17823346 [ZMIZ1] as well as cg02149899 and CRC risk. DISCUSSION: Our study confirms the significant association between tobacco smoking, DNA methylation and CRC risk and yields a novel insight into the pathogenic effect of tobacco smoking on CRC risk.

Development and Validation of Risk Prediction Models for Colorectal Cancer in Patients with Symptoms.

We aimed to develop and validate prediction models incorporating demographics, clinical features, and a weighted genetic risk score (wGRS) for individual prediction of colorectal cancer (CRC) risk in patients with gastroenterological symptoms. Prediction models were developed with internal validation [CRC Cases: n = 1686/Controls: n = 963]. Candidate predictors included age, sex, BMI, wGRS, family history, and symptoms (changes in bowel habits, rectal bleeding, weight loss, anaemia, abdominal pain). The baseline model included all the non-genetic predictors. Models A (baseline model + wGRS) and B (baseline model) were developed based on LASSO regression to select predictors. Models C (baseline model + wGRS) and D (baseline model) were built using all variables. Models' calibration and discrimination were evaluated through the Hosmer-Lemeshow test (calibration curves were plotted) and C-statistics (corrected based on 1000 bootstrapping). The models' prediction performance was: model A (corrected C-statistic = 0.765); model B (corrected C-statistic = 0.753); model C (corrected C-statistic = 0.764); and model D (corrected C-statistic = 0.752). Models A and C, that integrated wGRS with demographic and clinical predictors, had a statistically significant improved prediction performance. Our findings suggest that future application of genetic predictors holds significant promise, which could enhance CRC risk prediction. Therefore, further investigation through model external validation and clinical impact is merited.

Exploring the cross-cancer effect of smoking and its fingerprints in blood DNA methylation on multiple cancers: A Mendelian randomization study.

Aberrant smoking-related DNA methylation has been widely investigated as a carcinogenesis mechanism, but whether the cross-cancer epigenetic pathways exist remains unclear. We conducted two-sample Mendelian randomization (MR) analyses respectively on smoking behaviors (age of smoking initiation, smoking initiation, smoking cessation, and lifetime smoking index [LSI]) and smoking-related DNA methylation to investigate their effect on 15 site-specific cancers, based on a genome-wide association study (GWAS) of 1.2 million European individuals and an epigenome-WAS (EWAS) of 5907 blood samples of Europeans for smoking and 15 GWASs of European ancestry for multiple site-specific cancers. Significantly identified CpG sites were further used for colocalization analysis, and those with cross-cancer effect were validated by overlapping with tissue-specific eQTLs. In the genomic MR, smoking measurements of smoking initiation, smoking cessation and LSI were suggested to be casually associated with risk of seven types of site-specific cancers, among which cancers at lung, cervix and colorectum were provided with strong evidence. In the epigenetic MR, methylation at 75 CpG sites were reported to be significantly associated with increased risks of multiple cancers. Eight out of 75 CpG sites were observed with cross-cancer effect, among which cg06639488 (EFNA1), cg12101586 (CYP1A1) and cg14142171 (HLA-L) were validated by eQTLs at specific cancer sites, and cg07932199 (ATXN2) had strong evidence to be associated with cancers of lung (coefficient, 0.65, 95% confidence interval [CI], 0.31-1.00), colorectum (0.90 [0.61, 1.18]), breast (0.31 [0.20, 0.43]) and endometrium (0.98 [0.68, 1.27]). These findings highlight the potential practices targeting DNA methylation-involved cross-cancer pathways.

Genome-Wide Methylation Profiling in 229 Patients With Crohn's Disease Requiring Intestinal Resection: Epigenetic Analysis of the Trial of Prevention of Post-operative Crohn's Disease (TOPPIC).

BACKGROUND & AIMS: DNA methylation alterations may provide important insights into gene-environment interaction in cancer, aging, and complex diseases, such as inflammatory bowel disease (IBD). We aim first to determine whether the circulating DNA methylome in patients requiring surgery may predict Crohn's disease (CD) recurrence following intestinal resection; and second to compare the circulating methylome seen in patients with established CD with that we had reported in a series of inception cohorts. METHODS: TOPPIC was a placebo-controlled, randomized controlled trial of 6-mercaptopurine at 29 UK centers in patients with CD undergoing ileocolic resection between 2008 and 2012. Genomic DNA was extracted from whole blood samples from 229 of the 240 patients taken before intestinal surgery and analyzed using 450KHumanMethylation and Infinium Omni Express Exome arrays (Illumina, San Diego, CA). Coprimary objectives were to determine whether methylation alterations may predict clinical disease recurrence; and to assess whether the epigenetic alterations previously reported in newly diagnosed IBD were present in the patients with CD recruited into the TOPPIC study. Differential methylation and variance analysis was performed comparing patients with and without clinical evidence of recurrence. Secondary analyses included investigation of methylation associations with smoking, genotype (MeQTLs), and chronologic age. Validation of our previously published case-control observation of the methylome was performed using historical control data (CD, n = 123; Control, n = 198). RESULTS: CD recurrence in patients following surgery is associated with 5 differentially methylated positions (Holm P < .05), including probes mapping to WHSC1 (P = 4.1 × 10-9, Holm P = .002) and EFNA3 (P = 4.9 × 10-8, Holm P = .02). Five differentially variable positions are demonstrated in the group of patients with evidence of disease recurrence including a probe mapping to MAD1L1 (P = 6.4 × 10-5). DNA methylation clock analyses demonstrated significant age acceleration in CD compared with control subjects (GrimAge + 2 years; 95% confidence interval, 1.2-2.7 years), with some evidence for accelerated aging in patients with CD with disease recurrence following surgery (GrimAge +1.04 years; 95% confidence interval, -0.04 to 2.22). Significant methylation differences between CD cases and control subjects were seen by comparing this cohort in conjunction with previously published control data, including validation of our previously described differentially methylated positions (RPS6KA2 P = 1.2 × 10-19, SBNO2 = 1.2 × 10-11) and regions (TXK [false discovery rate, P = 3.6 × 10-14], WRAP73 [false discovery rate, P = 1.9 × 10-9], VMP1 [false discovery rate, P = 1.7 × 10-7], and ITGB2 [false discovery rate, P = 1.4 × 10-7]). CONCLUSIONS: We demonstrate differential methylation and differentially variable methylation in patients developing clinical recurrence within 3 years of surgery. Moreover, we report replication of the CD-associated methylome, previously characterized only in adult and pediatric inception cohorts, in patients with medically refractory disease needing surgery.

Field Synopsis of Environmental and Genetic Risk Factors of Sporadic Early-Onset Colorectal Cancer and Advanced Adenoma.

BACKGROUND: To systematically appraise and synthesize available epidemiologic evidence on the associations of environmental and genetic factors with the risk of sporadic early-onset colorectal cancer (EOCRC) and early-onset advanced colorectal adenoma (EOCRA). METHODS: Multiple databases were comprehensively searched to identify eligible observational studies. Genotype data from UK Biobank were incorporated to examine their associations with EOCRC in a nested case-control design. Meta-analyses of environmental risk factors were performed, and the strength of evidence was graded based on predefined criteria. Meta-analyses of genetic associations were conducted using the allelic, recessive, and dominant models, respectively. RESULTS: A total of 61 studies were included, reporting 120 environmental factors and 62 genetic variants. We found 12 risk factors (current overweight, overweight in adolescence, high waist circumference, smoking, alcohol, sugary beverages intake, sedentary behavior, red meat intake, family history of colorectal cancer, hypertension, hyperlipidemia, and metabolic syndrome) and three protective factors (vitamin D, folate, and calcium intake) for EOCRC or EOCRA. No significant associations between the examined genetic variants and EOCRC risk were observed. CONCLUSIONS: Recent data indicate that the changing patterns of traditional colorectal cancer risk factors may explain the rising incidence of EOCRC. However, research on novel risk factors for EOCRC is limited; therefore, we cannot rule out the possibility of EOCRC having different risk factors than late-onset colorectal cancer (LOCRC). IMPACT: The potential for the identified risk factors to enhance the identification of at-risk groups for personalized EOCRC screening and prevention and for the prediction of EOCRC risk should be comprehensively addressed by future studies.

Exploring the Complex Relationship between Gut Microbiota and Risk of Colorectal Neoplasia Using Bidirectional Mendelian Randomization Analysis.

BACKGROUND: Human gut microbiome has complex relationships with the host, contributing to metabolism, immunity, and carcinogenesis. METHODS: Summary-level data for gut microbiota and metabolites were obtained from MiBioGen, FINRISK and human metabolome consortia. Summary-level data for colorectal cancer were derived from a genome-wide association study meta-analysis. In forward Mendelian randomization (MR), we employed genetic instrumental variables (IV) for 24 gut microbiota taxa and six bacterial metabolites to examine their causal relationship with colorectal cancer. We also used a lenient threshold for nine apriori gut microbiota taxa as secondary analyses. In reverse MR, we explored association between genetic liability to colorectal neoplasia and abundance of microbiota studied above using 95, 19, and 7 IVs for colorectal cancer, adenoma, and polyps, respectively. RESULTS: Forward MR did not find evidence indicating causal relationship between any of the gut microbiota taxa or six bacterial metabolites tested and colorectal cancer risk. However, reverse MR supported genetic liability to colorectal adenomas was causally related with increased abundance of two taxa: Gammaproteobacteria (ß = 0.027, which represents a 0.027 increase in log-transformed relative abundance values of Gammaproteobacteria for per one-unit increase in log OR of adenoma risk; P = 7.06×10-8), Enterobacteriaceae (ß = 0.023, P = 1.29×10-5). CONCLUSIONS: We find genetic liability to colorectal neoplasia may be associated with abundance of certain microbiota taxa. It is more likely that subset of colorectal cancer genetic liability variants changes gut biology by influencing both gut microbiota and colorectal cancer risk. IMPACT: This study highlights the need of future complementary studies to explore causal mechanisms linking both host genetic variation with gut microbiome and colorectal cancer susceptibility.

Cross-cancer pleiotropic analysis identifies three novel genetic risk loci for colorectal cancer.

BACKGROUND: To understand the shared genetic basis between colorectal cancer (CRC) and other cancers and identify potential pleiotropic loci for compensating the missing genetic heritability of CRC. METHODS: We conducted a systematic genome-wide pleiotropy scan to appraise associations between cancer-related genetic variants and CRC risk among European populations. Single nucleotide polymorphism (SNP)-set analysis was performed using data from the UK Biobank and the Study of Colorectal Cancer in Scotland (10 039 CRC cases and 30 277 controls) to evaluate the overlapped genetic regions for susceptibility of CRC and other cancers. The variant-level pleiotropic associations between CRC and other cancers were examined by CRC genome-wide association study meta-analysis and the pleiotropic analysis under composite null hypothesis (PLACO) pleiotropy test. Gene-based, co-expression and pathway enrichment analyses were performed to explore potential shared biological pathways. The interaction between novel genetic variants and common environmental factors was further examined for their effects on CRC. RESULTS: Genome-wide pleiotropic analysis identified three novel SNPs (rs2230469, rs9277378 and rs143190905) and three mapped genes (PIP4K2A, HLA-DPB1 and RTEL1) to be associated with CRC. These genetic variants were significant expressions quantitative trait loci in colon tissue, influencing the expression of their mapped genes. Significant interactions of PIP4K2A and HLA-DPB1 with environmental factors, including smoking and alcohol drinking, were observed. All mapped genes and their co-expressed genes were significantly enriched in pathways involved in carcinogenesis. CONCLUSION: Our findings provide an important insight into the shared genetic basis between CRC and other cancers. We revealed several novel CRC susceptibility loci to help understand the genetic architecture of CRC.

N6-methyladenosine related gene expression signatures for predicting the overall survival and immune responses of patients with colorectal cancer.

N6-methyladenosine (m6A) modification has been demonstrated to exhibit a crucial prognostic effect on colorectal cancer (CRC). Nonetheless, potential mechanism of m6A in survival rate and immunotherapeutic response remains unknown. Here we investigated the genes associated with m6A regulators and developed a risk score for predicting the overall survival (OS) of CRC patients. RNA-seq transcriptomic profiling data of COAD/READ samples were obtained from The Cancer Genome Atlas (TCGA) database. Absolute Shrinkage and Selection Operator (LASSO)- Cox regression analysis was conducted to identify the m6A-related gene expression signatures and the selected genes were inputted into stepwise regression to develop a prognostic risk score in TCGA, and its predictive performance of CRC survival was further validated in Gene Expression Omnibus (GEO) datasets. According to our results, the risk score comprising 18 m6A-related mRNAs was significantly associated with CRC survival in both TCGA and GEO datasets. And the stratified analysis also confirmed that high-risk score acted as a poor factor in different age, sex, T stage, and tumour, node, metastasis (TNM) stages. The m6A-related prognostic score in combination with clinical characteristics yielded time-dependent area under the receiver operating characteristic curve (AUCs) of 0.85 (95%CI: 0.79-0.91), 0.84 (95%CI: 0.79-0.90) and 0.80 (95%CI: 0.71-0.88) for the prediction of the 1-, 3-, 5-year OS of CRC in TCGA cohort. Furthermore, mutation of oncogenes occurred more frequently in the high-risk group and the composition of immune cells in tumour microenvironment (TME) was significantly distinct between the low- and high-risk groups. The low-risk group had a lower microsatellite instability (MSI) score, T-cell exclusion score and dysfunction score, implying that low-risk patients may have a better immunotherapy response than high-risk patients. In summary, a prognostic risk score derived from m6A-related gene expression signatures could serve as a potential prognostic predictor for CRC survival and indicator for predicting immunotherapy response in CRC patients.

The Contribution of Genetic Risk and Lifestyle Factors in the Development of Adult-Onset Inflammatory Bowel Disease: A Prospective Cohort Study.

INTRODUCTION: The joint associations across genetic risk, modifiable lifestyle factors, and inflammatory bowel disease (IBD) remains unclear. METHODS: Genetic susceptibility to Crohn's disease (CD) and ulcerative colitis (UC) was estimated by polygenic risk scores and further categorized into high, intermediate, and low genetic risk categories. Weighted healthy lifestyle scores were constructed based on 5 common lifestyle factors and categorized into favorable (4 or 5 healthy lifestyle factors), intermediate (3 healthy lifestyle factors), and unfavorable (0-2 healthy lifestyle factors) groups. Cox proportional hazards regression model was used to estimate the hazard ratios (HR) and 95% confidence interval (CI) for their associations. RESULTS: During the 12-year follow-up, 707 cases with CD and 1576 cases with UC were diagnosed in the UK Biobank cohort. Genetic risk and unhealthy lifestyle categories were monotonically associated with CD and UC risk with no multiplicative interaction between them. The HR of CD and UC were 2.24 (95% CI 1.75-2.86) and 2.15 (95% CI 1.82-2.53) for those with a high genetic risk, respectively. The HR of CD and UC for individuals with an unfavorable lifestyle were 1.94 (95% CI 1.61-2.33) and 1.98 (95% CI 1.73-2.27), respectively. The HR of individuals with a high genetic risk but a favorable lifestyle (2.33, 95% CI 1.58-3.44 for CD, and 2.05, 95% CI 1.58-2.66 for UC) were reduced nearly by half, compared with those with a high genetic risk but an unfavorable lifestyle (4.40, 95% CI 2.91-6.66 for CD and 4.44, 95% CI 3.34-5.91 for UC). DISCUSSION: Genetic and lifestyle factors were independently associated with susceptibility to incident CD and UC. Adherence to a favorable lifestyle was associated with a nearly 50% lower risk of CD and UC among participants at a high genetic risk.

Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data: population based cohort study.

OBJECTIVE: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. DESIGN: Population based cohort study. SETTING: Data from the UK Biobank study, collected between March 2006 and July 2010. PARTICIPANTS: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. MAIN OUTCOME MEASURES: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. RESULTS: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. CONCLUSIONS: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population.

Transcriptional dynamics of colorectal cancer risk associated variation at 11q23.1 correlate with tuft cell abundance and marker expression in silico.

Colorectal cancer (CRC) is characterised by heritable risk that is not well understood. Heritable, genetic variation at 11q23.1 is associated with increased colorectal cancer (CRC) risk, demonstrating eQTL effects on 3 cis- and 23 trans-eQTL targets. We sought to determine the relationship between 11q23.1 cis- and trans-eQTL target expression and test for potential cell-specificity. scRNAseq from 32,361 healthy colonic epithelial cells was aggregated and subject to weighted gene co-expression network analysis (WGCNA). One module (blue) included 19 trans-eQTL targets and was correlated with POU2AF2 expression only. Following unsupervised clustering of single cells, the expression of 19 trans-eQTL targets was greatest and most variable in cluster number 11, which transcriptionally resembled tuft cells. 14 trans-eQTL targets were found to demarcate this cluster, 11 of which were corroborated in a second dataset. Intra-cluster WGCNA and module preservation analysis then identified twelve 11q23.1 trans-eQTL targets to comprise a network that was specific to cluster 11. Finally, linear modelling and differential abundance testing showed 11q23.1 trans-eQTL target expression was predictive of cluster 11 abundance. Our findings suggest 11q23.1 trans-eQTL targets comprise a POU2AF2-related network that is likely tuft cell-specific and reduced expression of these genes correlates with reduced tuft cell abundance in silico.