Susceptibility transcription factors (TF) whose DNA bindings are altered by genetic variants regulating colorectal cancer (CRC) risk genes remain poorly defined. Using generalized linear mixed models, we analyze 218 TF ChIP-Seq datasets alongside GWAS data from 100,204 CRC cases and 154,587 controls of East Asian and European ancestries. We identify 51 TFs and TF-cofactor interactions, including VDR-cofactors, as key regulators of CRC risk. Integrating these TF insights with transcriptome-wide association studies (TWAS), we further evaluate associations between genetically predicted gene expression, alternative splicing, and alternative polyadenylation with CRC risk, using RNA-seq data from 364 Asian-ancestry and 707 European-ancestry individuals. Multi-ancestry TWAS identify 222 risk genes, including 95 novel genes and 48 potentially druggable targets. Single-cell analysis provides additional functional evidence supporting ~45% of these genes, and experimental validation confirms oncogenic roles for RHPN2, IRS2, and TXN. Our findings elucidate key TF-gene regulatory networks and uncover novel CRC risk genes.

AbstractBackground: Red meat and/or processed meat are established colorectal cancer risk factors. Genome-wide association studies (GWAS) have reported more than 200 variants associated with colorectal cancer risk. We used functional annotation data to identify subsets of variants within known pathways to construct pathway-based polygenic risk scores (pPRS) to assess interactions with meat intake. Methods: A pooled sample of 30,812 cases and 40,504 colorectal cancer controls from 27 studies was analyzed. Quantiles for red and processed meat intake were constructed. A total of 204 GWAS variants were annotated to genes with Annotation Query (AnnoQ) and assessed for overrepresentation in PANTHER-reported pathways. pPRSs were constructed from significantly overrepresented pathways. Covariate-adjusted logistic regression models evaluated interactions between pPRS and red or processed meat intake in relation to colorectal cancer risk. Results: A total of 30 variants were overrepresented in four pathways: presenilin/Alzheimer disease, cadherin/WNT signaling, gonadotropin-releasing hormone receptor, and transforming growth factor-β (TGF-β) signaling. We found a significant interaction between TGF-β pPRS and red meat intake [ORint = 0.95; 95% confidence interval (CI) = 0.92–0.98; P = 0.003). When variants in the TGF-β pathway were assessed, we observed significant interactions of red meat with rs2337113 [intron SMAD family member 7 (SMAD7) gene, Chr18] and rs2208603 [intergenic region bone morphogenetic protein 5 (BMP5), Chr6; P = 0.0005 and 0.036, respectively]. There was no evidence of pPRS × red meat interactions for other pathways or with processed meat. Conclusions: This pathway-based interaction analysis revealed a statistically significant interaction between variants in the TGF-β pathway and red meat consumption that influences colorectal cancer risk. Impact: These findings shed light on the possible mechanistic link between red meat consumption and colorectal cancer risk.

BACKGROUND:An increasing body of evidence has linked fructose intake to colorectal cancer (CRC). African-American (AA) adults consume greater quantities of fructose and are more likely to develop right-side colon cancer than European American (EA) adults. OBJECTIVES:We examined the hypothesis that fructose consumption leads to epigenomic and transcriptomic differences associated with CRC tumor biology. METHODS:Deoxyribonucleic acid methylation data from this cross-sectional study was obtained using the Illumina Infinium MethylationEPIC kit (GSE151732). Right and left colon differentially methylated regions (DMRs) were identified using DMRcate through analysis of Food Frequency Questionnaire data on fructose consumption in normal colon biopsies (n = 79) of AA adults undergoing screening colonoscopy. Secondary analysis of CRC tumors was carried out using data derived from The Cancer Genome Atlas Colon Adenocarcinoma, GSE101764, and GSE193535. Right colon organoids derived from AA (n = 5) and EA (n = 5) adults were exposed to 4.4 mM of fructose for 72 h. Differentially expressed genes (DEGs) were identified using DESeq2. RESULTS:We identified 4263 right colon fructose-associated DMRs [false-discovery rates (FDR) < 0.05]. In contrast, only 24 DMRs survived multiple testing corrections (FDR < 0.05) in matched, left colon. Almost 50% of right colon fructose-associated DMRs overlapped regions implicated in CRC in ≥1 of 3 data sets. Highly significant enrichment was also observed between genes corresponding to right colon fructose-associated DMRs and DEGs associated with fructose exposure in right colon organoids of AA individuals (P = 3.28E-30). Overlapping and significant enrichments for fatty acid metabolism, glycolysis, and cell proliferation pathways were also found. Cross-referencing genes within these pathways to DEGs in CRC tumors reveal potential roles for ankyrin repeat domain containing protein 23 and phosphofructokinase, platelet in fructose-mediated CRC risk for AA individuals. CONCLUSIONS:Our data support that dietary fructose exerts a greater CRC risk-related effect in the right than left colon among AA adults, alluding to its potential role in contributing to racial disparities in CRC.

Rural, low-income communities in the U.S. experience a disproportionate burden of cancer, with higher incidence and mortality rates linked to structural and environmental disparities. Advanced glycation end products (AGEs), byproducts of metabolism that accumulate with poor diet and metabolic stress, have emerged as a novel biological link between social disadvantage and cancer risk. Yet, exploration of this biomarker in low-resource communities is challenging. The Partnership to Improve Community Health (PICH) cohort was launched to investigate how diet, neighborhood deprivation, and environmental exposures impact biological aging and gut microbiome changes linked to cancer risk in rural Southern Virginia (VA), a region that is ∼50% African American. This abstract highlight key lessons learned from the community-engaged development of this multi-level cohort. To ensure cultural relevance and feasibility, a Community Cohort Study Advisory Team (CCSAT) was established, with ∼15 representatives from local community organizations, Federally Qualified Health Centers (FQHCs), colleges/technical schools, Community Health Workers (CHWs), and community champions. From October 2024 to May 2025, six structured meetings were held to receive feedback on study elements. The PICH cohort will enroll ∼1,000 adults from rural Southern VA. Participants will complete structured interviews on their lifestyle, medical history, diet (including meat preparation), unmet needs, and stress. Biological specimens (blood, stool, saliva, urine, hair, buccal swabs, toenails), environmental samples, and Area Deprivation Index data will be collected. CCSAT input was integrated throughout the study protocol and implementation plan. CCSAT input has been provided on the study protocol, recruitment materials (e.g., posters, flyers), survey content (e.g., adding a question on military service), biospecimen instructions, study title, and study consent form. They guided recruitment communication strategies and helped develop plain-language explanations for technical content. The CCSAT suggested flexible survey modes (phone/online) to accommodate participants’ preferences and digital literacy. They guided recruitment strategies through CHWs, FQHCs, and community events. Feedback helped tailor, remove, or add study components to improve clarity, cultural fit, and logistical feasibility. For example, one proposed study component—collecting wall scrapings for lead analysis—was removed following strong community objection. Engaging community stakeholders throughout study design helped tailor the PICH cohort to focus on the unique needs of a rural, underserved population. This process strengthened community trust, improved alignment with local infrastructure, and is expected to enhance participant recruitment and retention. The PICH study offers a model for culturally responsive, community-informed research to address cancer risk in underserved rural populations. Findings will inform precision prevention and locally relevant interventions. Hania M. Taha, Kara P. Wiseman, Samyukta Venkatesh, Anasia Harrell, Lindsay Hauser, Wendy Cohn, Matthew Devall, Li Li. Community engagement in designing a lifestyle, environmental, and biological risk factor cohort study for cancer disparities [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr A065.

Colorectal cancer (CRC) is a major public health concern, with incidence rates increasing over the past decades particularly among younger adults. The identification of novel intervention targets for CRC prevention becomes imperative. In the present study we explored patterns of genes and pathways underlying the observed associations using estimates from genome-wide interaction studies (GWIS) of 15 exposures with established or putative CRC risk. GWIS estimates were derived from a pool of 36 primary studies including up to 38, 578 CRC cases and 49, 658 controls. The 15 risk factors included body mass index (BMI), height, physical activity, smoking, type 2 diabetes, hormone replacement therapy (HRT), and intake of non-steroidal anti-inflammatory drugs (NSAIDs) including aspirin, alcohol, calcium, fiber, folate, fruits, processed meat, red meat, and vegetables. We conducted pathway-environment interaction analysis for CRC risk to identify associated pathways using the adaptive combination of Bayes Factors (ADABF) framework. The pathway findings were further investigated by exploring the relevance of the enriched genes for CRC using publicly available resources [hallmarks of cancer, Open Targets Platform (OTP)]. Using the ADABF, a total of 1, 973 pathways were enriched out of the 2, 950 analyzed for at least one exposure. Additionally, within the enriched pathways, 1, 227 genes showed evidence of interaction with at least one exposure. A high overlap of associated genes was observed between the three exposures with higher number of associated genes: BMI (n=768), followed by smoking (n=223) and NSAIDs (n=173), while for remaining exposures the number of enriched genes ranged from 3 to 27. Data were available for 811/1, 227 genes in the OTP, of which an overall association score >0.05 was found for 241 coding genes. Fifty percent of the genes (617/1, 227) mapped to at least one hallmark of cancer, most of which (388/617) pertained to the Sustaining Proliferative Signaling hallmark. Our findings reflect previously established pathways for CRC risk, such as mitogen-activated protein kinase (MAPK), Notch, PI3K/AKT, transforming growth factor-β (TGF-β), Wnt, and participating genes, for BMI, NSAIDs, and smoking, and highlight the emerging importance of several less studied genes (such as argonaute RISC component, UDP-glucuronosyltransferase, and taste receptor coding genes). Common pathways were found for several combinations of exposures (mostly for BMI, NSAIDs, and smoking), potentially suggesting common underlying mechanisms. The results of the present analysis can be used in future investigations, and, if confirmed, may aid in elucidating the etiological associations and inform personalized CRC prevention strategies. Emmanouil Bouras, Ren Yu, Andre E. Kim, Georgios Markozannes, Neil Murphy, Demetrius Albanes, Laura N. Anderson, Elizabeth L. Barry, Hermann Brenner, Peter T. Campbell, Robert Carreras-Torres, Andrew T. Chan, Jenny Chang-Claude, Iona Cheng, Matthew A. Devall, Niki Dimou, David A. Drew, Stephen B. Gruber, Andrea Gsur, Li Hsu, Jeroen R. Huyghe, Temitope O. Keku, Anshul Kundaje, Loïc Le Marchand, Li Li, Brigid M. Lynch, Victor Moreno, John Morrison, Christina C. Newton, Nikos Papadimitriou, Andrew J. Pellatt, Anita R. Peoples, Paul D. Pharoah, Elizabeth A. Platz, Conghui Qu, Joel Sanchez Mendez, Robert E. Schoen, Mariana C. Stern, Claire E. Thomas, Caroline Y. Um, Pavel Vodicka, Veronika Vymetalkova, Emily White, Alicja Wolk, Anna H. Wu, Marc J. Gunter, W. James Gauderman, Ulrike Peters, Marina Evangelou, Konstantinos K. Tsilidis. Using gene-environment interactions to explore pathways for colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3817.

Quantile-quantile plots of the genome-wide interaction scans for red meat and processed meat.

Gene expression appears altered in apparently normal tissue surrounding tumor tissue. The observed biological alterations in the tumor microenvironment play a crucial role in cancer development and are named the cancer field effect (FE). A robust set of overexpressed FE genes in tissue surrounding colorectal cancer (CRC) tumor were identified in previous studies. Our study aimed to investigate the influence of common medication intake and modifiable risk factors on FE gene expression using a colonic mucosa sample dataset of healthy individuals (BarcUVa-Seq). We applied expression enrichment analysis of the FE genes for each studied medication and factor. Both observational and instrumental (Mendelian randomization) analysis were conducted, and the results were validated using independent datasets. The findings from the observational and instrumental analyses consistently showed that medication intake, especially metformin, considerably downregulated the FE genes. Chemopreventive effects were also noted for antihypertensive drugs targeting the renin-angiotensin system. Conversely, benzodiazepines usage might upregulate FE genes, thus fostering a tumor-promoting microenvironment. In contrast, the findings from the observational and instrumental analyses on modifiable risk factors showed some discrepancies. The instrumental results indicated that obesity and smoking might promote a tumor-favorable microenvironment. These findings offer insights into the biological mechanisms through which risk factors might influence CRC development and highlight the potential chemopreventive roles of metformin and antihypertensive drugs in CRC risk.

Locus Zoom plots for the two polymorphisms reported in the genome-wide gene-interaction main results.

(1) Introduction: The global rise of gastrointestinal diseases, including colorectal cancer and inflammatory bowel diseases, highlights the need to understand their causes. Diet is a common risk factor and a crucial regulator of gene expression, with alterations observed in both conditions. This study aims to elucidate the specific biological mechanisms through which diet influences the risk of bowel diseases. (2) Methods: We analyzed data from 436 participants from the BarcUVa-Seq population-based cross-sectional study utilizing gene expression profiles (RNA-Seq) from frozen colonic mucosal biopsies and dietary information from a semi-quantitative food frequency questionnaire. Dietary variables were evaluated based on two dietary patterns and as individual variables. Differential expression gene (DEG) analysis was performed for each dietary factor using edgeR. Protein–protein interaction (PPI) analysis was conducted with STRINGdb v11 for food groups with more than 10 statistically significant DEGs, followed by Reactome-based enrichment analysis for the resulting networks. (3) Results: Our findings reveal that food intake, specifically the consumption of blue fish, alcohol, and potatoes, significantly influences gene expression in the colon of individuals without tumor pathology, particularly in pathways related to DNA repair, immune system function, and protein glycosylation. (4) Discussion: These results demonstrate how these dietary components may influence human metabolic processes and affect the risk of bowel diseases.

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.

BACKGROUND:Colorectal cancer (CRC) is a common, fatal cancer. Identifying subgroups who may benefit more from intervention is of critical public health importance. Previous studies have assessed multiplicative interaction between genetic risk scores and environmental factors, but few have assessed additive interaction, the relevant public health measure. METHODS:Using resources from CRC consortia, including 45,247 CRC cases and 52,671 controls, we assessed multiplicative and additive interaction (relative excess risk due to interaction, RERI) using logistic regression between 13 harmonized environmental factors and genetic risk score, including 141 variants associated with CRC risk. RESULTS:There was no evidence of multiplicative interaction between environmental factors and genetic risk score. There was additive interaction where, for individuals with high genetic susceptibility, either heavy drinking (RERI = 0.24, 95% confidence interval [CI] = 0.13, 0.36), ever smoking (0.11 [0.05, 0.16]), high body mass index (female 0.09 [0.05, 0.13], male 0.10 [0.05, 0.14]), or high red meat intake (highest versus lowest quartile 0.18 [0.09, 0.27]) was associated with excess CRC risk greater than that for individuals with average genetic susceptibility. Conversely, we estimate those with high genetic susceptibility may benefit more from reducing CRC risk with aspirin/nonsteroidal anti-inflammatory drugs use (-0.16 [-0.20, -0.11]) or higher intake of fruit, fiber, or calcium (highest quartile versus lowest quartile -0.12 [-0.18, -0.050]; -0.16 [-0.23, -0.09]; -0.11 [-0.18, -0.05], respectively) than those with average genetic susceptibility. CONCLUSIONS:Additive interaction is important to assess for identifying subgroups who may benefit from intervention. The subgroups identified in this study may help inform precision CRC prevention.

AbstractBackground: 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.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Background Transcriptome-wide association studies have been successful in identifying candidate susceptibility genes for colorectal cancer (CRC). To strengthen susceptibility gene discovery, we conducted a large transcriptome-wide association study and an alternative splicing transcriptome-wide association study in CRC using improved genetic prediction models and performed in-depth functional investigations.Methods We analyzed RNA-sequencing data from normal colon tissues and genotype data from 423 European descendants to build genetic prediction models of gene expression and alternative splicing and evaluated model performance using independent RNA-sequencing data from normal colon tissues of the Genotype-Tissue Expression Project. We applied the verified models to genome-wide association studies (GWAS) summary statistics among 58 131 CRC cases and 67 347 controls of European ancestry to evaluate associations of genetically predicted gene expression and alternative splicing with CRC risk. We performed invitro functional assays for 3 selected genes in multiple CRC cell lines.Results We identified 57 putative CRC susceptibility genes, which included the 48 genes from transcriptome-wide association studies and 15 genes from splicing transcriptome-wide association studies, at a Bonferroni-corrected P value less than .05. Of these, 16genes were not previously implicated in CRC susceptibility, including a gene PDE7B (6q23.3) at locus previously not reported by CRC GWAS. Gene knockdown experiments confirmed the oncogenic roles for 2 unreported genes, TRPS1 and METRNL, and a recently reported gene, C14orf166.Conclusion This study discovered new putative susceptibility genes of CRC and provided novel insights into the biological mechanisms underlying CRC development.

Abstract Epigenetic age (EA) may serve as a risk stratification biomarker for early-onset colorectal cancer (EOCRC, <50 years old), which has been rising substantially in recent decades. We utilized publicly available data in a descriptive analysis to compare epigenetic clocks in colorectal tissue and to investigate differences between chronological age (CA) and biological age, as measured by EA, in relation to demographic and clinical features. We analyzed DNA methylation (DNAm) array data on 144 participants (96 CRC cases, 48 healthy controls) from the Colonomics Study (CLX; Barcelona, Spain) and 331 CRC cases (51 EOCRC, 316 average-onset (≥50) colorectal cancer (AOCRC)) from The Cancer Genome Atlas (TCGA) as well as corresponding demographic and clinical variables. Among CLX participants, the 96 CRC cases provided colon tumor and paired normal mucosa samples, while the 48 controls provided healthy colon mucosa samples. TCGA included primary tumor samples from 331 cases with colon or rectal adenocarcinoma (TCGA-COADREAD). The 2013 Horvath clock estimated EA based on CA, while epiTOC, estimated the relative stem cell division rate from tissue biospecimens. We examined the correlations between CA and EA stratified by case/control status, sample type, sex, and age of onset (TCGA only). Tissue from CLX controls demonstrated a strong, positive correlation (r>0.9) between CA and EA for both the 2013 Horvath and epiTOC clocks. Using the Horvath clock, CA and EA correlations in normal mucosa and tumor tissue samples from CLX varied, with r = 0.74 and r = 0.41, respectively, and were weaker using the epiTOC clock, with r = 0.26 (normal) and r = 0.10 (tumor). When CLX cases were stratified by sex, the CA and EA (Horvath) correlations among female cases were r = 0.80 (normal) and r = -0.12 (tumor), while the correlations for males were stronger at r = 0.58 (normal) and r = 0.31 (tumor). This is in comparison to the epiTOC clock with females showing correlations of r = -0.02 (normal) and r = 0.41 (tumor), while males had r = 0.06 (normal) and r = 0.11 (tumor). In TCGA, correlations for EOCRC were r = -0.20 (Horvath) and r = -0.08 (epiTOC) and for AOCRC were r = 0.29 and 0.20, respectively. By sex, correlations for females with EOCRC for Horvath and epiTOC were r = -0.09 and r = -0.07, respectively, while correlations for males with EOCRC were r = -0.02 and r = -0.08, respectively. For TCGA cases with AOCRC, the correlations between CA and EA were r = 0.35 and r = 0.22 for females, and r = 0.26 and r = 0.20 for males, respectively for Horvath and epiTOC. This study revealed substantial variability in the ability of existing epigenetic clocks to accurately predict chronological age, with tissue type and sex strongly influencing the resulting correlations. Our findings highlight the importance of considering these factors when choosing an epigenetic clock. Citation Format: Christopher L. Benson, Ferran Moratalla-Navarro, Anna Diez-Villanueva, Matthew A. Devall, Victor Moreno, Stephanie L. Schmit, Fredrick R. Schumacher. Factors affecting the performance of existing epigenetic clocks to predict chronological age in colorectal tumor and normal tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3439.

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Summary of G × BMI analyses using 1DF, two-step, and 3DF analyses.